URBAN DYNAMICS AND VULNERABILITY TO DISASTERS IN 
LAGOS STATE, NIGERIA (1982 – 2012) 
 
By 
 
 
OLUWASINAAYOMI FAITH KASIM 
 
 
 
B.Sc (Hons), Geography (Ibadan); M.U.R.P,  
Urban and Regional Planning (Ibadan) 
 
 
 
A Thesis in the Department of Urban and Regional Planning  
Submitted to the Faculty of the Social Sciences,  
in Partial Fulfillment of the Requirements for the Degree of 
 
 
DOCTOR OF PHILOSOPHY 
 
 
of the 
 
 
UNIVERSITY OF IBADAN 
 
 
 
 
   
December, 2014 
 
 
 
 
 
 
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CERTIFICATION 
 
I certify that this work was carried out by Mr. KASIM, O. F. in the Department of Urban and 
Regional Planning, University of Ibadan. 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
……………………………………………………….. 
Supervisor 
Prof. C. O. Olatubara,  
Ph.D. (Ife), 
Professor, Department of Urban and Regional Planning, 
University of Ibadan, Nigeria 
  
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DEDICATION 
 
This thesis is dedicated to my Late Grand Mother Chief Sarah Adesoro for her care, 
mentoring, motivating and super motherly roles in my life and to the Almighty God, the giver 
of wisdom, knowledge and understanding.  
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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ACKNOWLEDGEMENT 
I wish to use this medium to unalloyedly express my profound gratitude to my supervisor, 
friend, financier and tutor, Professor Charles Olufisayo Olatubara who gave all the necessary 
support and soft-landing towards the completion of the thesis. My unreserved 
acknowledgement goes to Professor Samuel Babatunde Agbola, my mentor on and off the 
academic landscape. Sir, the three secrets to success given to me, albeit unmerited but 
invaluable, are still being kept in my cache and acting as my vision and mission statements.  
I wish to acknowledge the effort of Professor Layi Egunjobi and the immediate past Head of 
Department, Dr. Lekan Sanni for their forthrightness but laced with encouragement towards 
the accomplishment of this thesis. I also wish to express my sincere gratitude to Dr Bolanle 
Wahab, Dr Godwin Ode Ikwuyatum and Dr Olutoyin Fashae for reading the post-field work 
and providing necessary suggestions. To Dr. Dickson Ajayi, thank you for the helping hands 
in scaling the hurdles of abstract. My special thanks also go to Dr Olusuyi Ipingbemi, Dr 
Moruf Alabi, Dr Joe Omirin Dr Adams Ajigbogun-Jimoh (Moye) and Dr David Olakunde 
who assisted and encouraged me in various ways during the writing of this thesis. I cannot 
forget Late Monday Shari, Saeed Ojolowo, Segun Morolari, Segun Falola and Abiodun Audu 
for their immeasurable assistance in the final production of this thesis. The administrative 
staffs of the Department are also appreciated. To all my classmates at the Master and 
Doctoral levels especially Tunde Kolade, Ayotunde Olagbemi, Dr Tayo Odunola, Toybat, Dr 
Ifesanya, Sade Odekunle, David Taiwo, Michael Adetunjiand host of others, thank you for 
your support and encouragement.   
My laboratory, the National Emergency Management Agency (NEMA), manned by giants 
which include but not limited to: Muhammad Sani Sidi (DG), Charles Agbo (Ph.D), Aliyu 
Sambo, Kayode Fagbemi, Ben Oghenah, James Akujobi, Fatima Kasim, Adamu Usur, Skari 
Demas, Justin Uwazuruonye, Yinka Afolabi (Oxfam), Tunde Ajiboye, Victor Nwaubani, 
Tony Ephraim, Abdulrazak Musa, Babuba Sunday, Thickman Tanimu, Garki Imam, Fred 
Anusim, Hayatu Abdulkadri, Hajia Hauwa Sabir, Funmi Oyinsan, Joke Raji, Julius Dave, 
Funmi Obolo, Bunmi Akanbi (Moye), Igozi Iyase, Godwin, Williams Uzowulu, Sunday 
Amama, Jumoke Ogungbe, Ogunbambi Kemi (Auntie), Nabila Ibrahim, Isabella Ekpo and 
Bulus Wando (the General). Others who had contributed significantly to the completion of 
this thesis are: Alhassan Nuhu, Akande Iyiola, Pero Oladeinde, Tunde Olowookere, Dapo 
Akingbade, Michael Adeyanju, Saheed Akiode, Kadiri Sakiru, Tope Ajayi, Kazeem 
Olarenwaju, Anjolaoluwa Oguntokun, Alhassan Alhassan, Nkoyo Eyo, Nkiru Nwokeabia and 
Oluchi Gregory. You guys are the bomb. 
To my family: Mama and Baba, Nike, Sola, Sunday, Kemi, Ayo, Taiwo, Kehinde, Idowu and 
everybody on the home fronts especially Michael Adegoke Bakare I am grateful. Tunde 
Babalola, Hassan Adetunji, Ope Olowoniyi, Kayode Alhassan, Taiwo Olurin and other 
friends thank you.  
Finally, my overarching gratitude goes to my divine, better-half, help meet and wife Dr. 
(Mrs) Rita Oyin Kasim and my son, Oluwanife Gomez and daughter, Oluwatomife Elluz, 
thank you for your love, care, provisions and understanding. You are deeply appreciated. 
Stay blessed and be totally transforme 
 
 
Kasim, Oluwasinaayomi Faith 
 
 
 
 
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ABSTRACT 
The terrain, morphology, socio-economic characteristics coupled with lateral urban growth 
and increasing population concentration expose Lagos state to different types of disaster. 
Studies on disasters in Lagos have focused on the types and their impact to the neglect of 
vulnerability factors and disaster patterns. This study, therefore, investigated the relationship 
between urban dynamics (change in population, morphology and urban spatial expansion) 
and vulnerability to disasters in Lagos state (1982-2012) where flooding and building 
collapse are common occurrences.  
   
Forrester‟s urban dynamics theory provided the analytical framework. Cross-sectional survey 
design was adopted. A multi-stage sampling technique was used to select 1576 Heads of 
Household (HH) in direct proportion to existing housing stock in five Mainland Local 
Government Areas (LGAs) [Lagos Mainland –LM (67), Mushin (153), Oshodi-Isolo (197), 
Shomolu (214) and Surulere (106] and four Lagos Suburb (LS) LGAs [Alimosho (290), 
Ajeromi-Ifelodun (232), Ikorodu (234) and Kosofe (83]. A structured questionnaire was used 
to collect data from HH.  Observation checklist containing vulnerability indices and satellite 
imagery were used to document existing infrastructural facilities and residential 
neighbourhood densities, adherence to urban and regional planning regulation and standards 
in addition to recorded data on building collapse in Lagos state. The National Population 
Commission‟s trend of population growth in LM and LS and Land Use/Land-cover Change 
(LULC) imageries obtained from Global Land Cover Facility were used as urban dynamics 
indices. Geographic Information System was used to analyse LULC (Landsat imageries 1984 
and 2010) and to simulate flood-risk scenarios. Data were analysed using descriptive 
statistics, logistic regression and ANOVA at p≤0.05.  
 
Eighty-eight per cent of the buildings were built of sandcrete blocks (91.4% in LS and 83.9% 
in LM); 84.2% (LS) and 38.3% (LM) were not linked to pipe-borne water, while, 72.3 % 
(LS) and 43.1% (LM) did not have storm water drainage. About 74.0% (LS); 37.2% (LM) 
did not adhere to planning setback and maximum building-plot ratio. Also, 68.0% (LS) and 
27.3% (LM) had encroached into natural flood plains. One hundred and thirty-eight buildings 
collapsed in the study area with 81.9% occurring in LM. Population of LM increased by 
32.3% while that of LS increased by 87.4%. Vegetation cover reduced from 46.5% to 26.6% 
in LS and from 32.7% to 22.3% in LM while urban land use increased from 17.3% to 51.3% 
in LS and from 28.8% to 31.5% in LM. Buildings became vulnerable as flood-risk increased 
by one metre Above Sea Level (ASL) (8.3% in LM; 17.6% in LS). At two metres ASL, 
(19.1% LM; 31.5% LS) buildings were vulnerable to flood. The effects of urban dynamics on 
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vulnerability to flood (R =0.473) and building collapse (R =0.524) were significant. 
Vulnerability to disaster varied by housing density across residential neighbourhoods for 
building collapse (F(2,86)=17.88).   
 
Increasing population growth, flood-plains encroachment and non-adherence to planning 
regulation are factors influenced vulnerability to disaster in Lagos state. Adherence to land 
use planning regulation and flood-plain buy-back were recommended as vulnerability 
reduction strategies. 
 
Keywords:  Forester‟s urban dynamics theory, Vulnerability to disasters, Flood-risk   
 simulation, land use planning 
Word count: 481 
 
 
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TABLE OF CONTENTS 
Title page          i 
Certification           ii 
Dedication          iii 
Acknowledgement         iv 
Abstract          v 
Table of contents         vi 
List of tables          xi 
List of figures          xiii 
List of plates          xiv 
 
 
CHAPTER ONE           
1.0 Introduction         1 
1.1 Background to the study       1 
1.2 Statement of problem        5 
1.3 Research questions        8 
1.4 Aim and objectives        9 
1.5 Hypothesis         9 
1.6 The study area settings        9 
 
CHAPTER TWO 
2.0  Theoretical and conceptual issues in vulnerability analysis and 
  literature review        15 
2.1 Post-modern urbanisation concept      15 
2.1.1 Exposure factor        16 
2.1.2 Susceptibility factor        17 
2.1.3 Environmental factor        19 
2.2 Urban dynamics theory       22 
2.3 Urban governance concept        24 
2.4 Vulnerability concept        28 
2.5 Traditional - expanded disaster management cycle concept   30 
2.6       Literature review        33 
2.6.1 Nature, type and characteristics of disasters     33 
2.6.2 Urban dynamics and vulnerability to disasters     36 
2.6.3 Causes and effects of disasters      37 
2.6.4 Remedial measures to mitigate disasters.     47  
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2.6.5 Developmental attributes of disaster      53 
2.6.6 Methodological issues in disaster management    55 
2.6.7 Application of urban dynamic model to city management.    57 
2.6.8 Flood risk assessment and mapping      59 
 
CHAPTER THREE  
3.0  Research methodology       61 
3.1 Research design        61 
3.2  Primary sources of data       61 
3.3  Secondary sources of data       63 
3.4  Sample frame, size and sampling procedure     64 
3.5  GIS: flood risk assessment procedures      72 
3.6 Method of data analysis       74 
3.7 Conclusion          77 
 
CHAPTER FOUR 
4.0 The process and contributing factor to urban dynamics   78 
4.1 Introduction to urban dynamics      78 
4.2 Activators of the process of urban dynamics     79 
4.3 Urban dynamics and vulnerability to disaster: the nexus   87 
4.4 Conclusion         95 
 
CHAPTER FIVE 
5.0  Land use land cover change and flood risk assessment: scenario  
 simulation for  vulnerability analysis      96 
5.1 Introduction         96 
5.2 Land use land cover change       97 
5.3 Simulations         106 
5.4 Conclusion         112 
 
CHAPTER SIX 
6.0 Socio-economic status of respondents and vulnerability to disaster  113 
6.1 Socio-economic indices of the respondents     113 
6.2 Housing and household characteristics     121 
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6.3 Housing infrastructural facilities and services    127 
6.3.1 Water, Sanitation and Hygiene (WASH)      127 
6.3.2 Waste generation and management      131 
6.4 Conclusion         144  
 
CHAPTER SEVEN 
7.0 Prevailing hazards and vulnerability to disaster     145 
7.1 Introduction         145 
7.2 Perception of vulnerability to disaster     146 
7.3 Flood hazard             149 
7.4 Fire hazard           156 
7.5    Building collapse        167 
7.6 Biophysical hazards: disease epidemics     179 
7.7      Hazards prevention and mitigation approaches    185 
7.8 Conclusion         189 
 
CHAPTER EIGHT 
8.0 Disaster management institutions in Lagos State     190 
8.1 Introduction          190 
8.2 Institutional framework        191 
8.3 The agencies and disaster management     194 
8.4 Direct distribution of relief materials      203 
8.5 Identified capacity and gaps at national and state level   208 
8.6 The Lagos State Fire Services       212 
8.7 Disaster management stakeholders in Lagos State    214 
8.8 Challenges to disaster management      214 
8.9 Conclusion         215 
 
CHAPTER NINE 
9.0 Summary of findings, recommendations and conclusion   216 
9.1 Introduction          216 
9.2 Summary of findings        216 
9.3 Theoretical and practical implications of the study    220 
9.4 Disaster management strategies and facilitators    224 
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9.5 Future research area        229 
9.6 Conclusion         230 
9.7 Contributions to knowledge       231 
9.8 REFERENCE         232 
  
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APPENDICES 
APPENDIX I:  Household questionnaire     248 
APPENDIX II: Building collapse and suspected causes of collapse in  
   Lagos State 1978-2012     258 
APPENDIX III: NEMA summary of relief material intervention to State  
   affected by disasters 2010-2012    263 
 
 
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LIST OF TABLES 
Table 2.1: Top 10 countries by persons affected by disasters in 2006  41 
Table 2.2:  Top 10 countries affected by natural disasters and number of  
  deaths in  2012        42 
Table 2.3: Top 10 countries affected by natural disasters and impacts on  
  persons in 2012       43 
Table 2.4: Top 10 countries affected natural disasters and economic  
  damages in 2012       46 
Table 2.5: Assignment of disaster related responsibilities   51 
Table 3.1: 2010 population projections for Lagos State LGAs   65 
Table 3.2: LGAs of interest in Lagos mainland and Lagos suburb  66 
Table 3.3: Lagos mainland LGAs, wards and neighbourhood 
   Classifications       68 
Table 3.4: Lagos suburb LGAs, wards and neighbourhood  
  classifications        69 
Table 3.5: Number of wards and sample size adopted for the study.  71 
Table 4.1: Housing unit produced by FHA in FESTAC Town 1974 –  
  1989         80 
Table 4.2: Housing unit produced by FHA in Ipaja New Town 1982 –  
  1990         81 
Table 4.3: Locations and number of units built in Jakande estates in the  
  1980s          83 
Table 4.4: Perception of urban dynamics as a product of low income  
  housing        91 
Table 4.5: Test of association between urban dynamics and low income  
  housing        93 
Table 5.1: Statistics of land use land cover of the study area in 1984 –  
  2010         104 
Table 6.1: Questionnaire distribution, respondents density and  
  residency Status       115  
Table 6.2: Socio-economic in indices: age, gender and marital  
  status of respondents       117 
Table 6.3: Socio-economic in indices: education, occupation and 
   income        120 
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Table 6.4: Household characteristics      123 
Table 6.5: Number of person per room and housing conditions   126 
Table 6.6: Water supply, sanitation and hygiene     130 
Table 6.7: Waste generation and management     133 
Table 6.8: Logistic regression diagnotic tests for socio-economic indices, 
   Housing characteristics, infrastructural facilities and services    137  
Table 6.9: Logistic regression results predicting disasters on socio- 
  economic indices          138 
Table 6.10: Logistic regression results predicting disasters on household  
  and housing characteristics      141 
Table 6.11: Logistic regression results predicting disasters on housing facilities  
  and services        143 
Table 7.1: Perception of respondents on vulnerability to disaster  148 
Table 7.2: Perception of respondents on flood hazard    150 
Table 7.3: Perception of respondents on causes of flood   152 
Table 7.4: Respondents‟ reason for residing in flood prone area and  
  mitigation strategies       154  
Table 7.5: Perception of respondents on fire hazard    157 
Table 7.6: Respondents‟ response to fire outbreak    160 
Table 7.7: Recorded fire outbreaks and number of deaths and properties  
  affected in Lagos State (2008 – June 2012)    163 
Table 7.8: Perception of respondents on building collapse   170 
Table 7.9: Analysis of recorded building collapses in Lagos State by  
  residential neighbourhoods      172 
Table 7.10: Fire outbreak and building collapse descriptive      175 
Table 7.11: Fire outbreak and building collapse ANOVA    176 
Table 7.12: Least significant difference (multiple comparisons) for building   
  collapse and fire outbreak      178 
Table 7.13: Perception of respondents on disease epidemics   182 
Table 7.14: Causes and measure to curb diseases outbreak   184 
Table 7.15: Institutionalization of disaster management    188 
Table 8.1: Established clusters and designated lead agencies/organization for 
   NCP         197 
Table 8.2: Nigerian Army Disaster Reaction Units areas of responsibility 201 
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Table 8.3: Nigerian Navy and Air Force Reaction Units areas of  
  responsibility        202 
 
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LIST OF FIGURES 
Figure 1.1: Lagos State in Nigeria context     11 
Figure 1.2: Political structure of Lagos State including the study area  12 
Figure 2.1: Post-Modern urbanisation poverty and vulnerability to disaster  
  schema        21 
Figure 3.1: Elevation of the study area      73 
Figure 4.1: Population trend in Lagos State 1911 - 2010    86 
Figure 4.2: Process of urban dynamics and vulnerability to disaster  88 
Figure 5.1:  Land use and land cover as at 1984     99 
Figure 5.2:  Land use and land cover as at 2010     100 
Figure 5.3: Loss of vegetation to urban land (1984 -2010)   101 
Figure 5.4:  Reclamation of wet land (1984 -2010)    102 
Figure 5.5:  Contributors to net change in urban  land use    105 
Figure 5.6:  One metre sea rise flood risk 1984     107 
Figure 5.7: One metre sea rise flood risk 2010     108 
Figure 5.8:  Two metres sea rise flood risk map of 1984    109 
Figure 5.9:   Two metres sea rise flood risk map of 2010      110 
Figure 5.10:  Present flood risk zones      111 
Figure 7.1: Analysis of the recorded fire outbreaks in terms of neighbourhood 
   Classification in Lagos State 2008 – June 2012   165 
Figure 7.2: Analysis of fire outbreaks and impact in Lagos State  166 
Figure 8.1: Disaster management systems in Nigeria    193 
Figure 8.2: Distributions of building materials as relief intervention to states  
  2012         204 
Figure 8.3: Distributions of raw food as relief intervention to states 2012 205 
Figure 8.4: Distributions of household materials as relief intervention to states  
  2012         206 
Figure 9.1: Integrated urban management to strategy to reduce vulnerability 221 
Figure 9.2: Disaster management for safer community strategy    227 
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LIST OF PLATES 
Plate 7.1: Flood inundated Apapa – Oshodi express way   155 
Plate 7.2: Fire disaster at Euroasia Plaza, 10/12 Breadfruit Street, Lagos 161 
Plate 7.3: Newly procured fire tender vehicles and equipment by Lagos State  
  Government        162 
Plate 7.4: Collapsed residential building at Jakande estate, Oke Afa Oshodi- 
  Isolo, LGA        173  
            
 
 
 
 
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CHAPTER ONE 
INTRODUCTION 
1.1 Background to the study 
The world has been experiencing dramatic environmental and socio-economic changes 
in recent decades. Phenomenon like the changing urban dynamics in the developing 
countries is associated with economic development, population growth, rapid 
urbanisation, unprecedented land use and land cover change, environmental 
degradation, climate change, and increase in disaster incidences have affected the 
social and economic development in this region and other parts of the world. The 
consequence of these changes is that many people have become more vulnerable to the 
negative effects of different hazards. Hazard in this context means: a property or 
situation that under particular circumstances could lead to harm. More specific, a 
hazard is a potentially damaging physical event, phenomenon or human activity which 
may cause loss of life or injury, property damage, social, cultural, political and 
economic disruption or environmental degradation. Hazards can be single, sequential 
or combined in their origin and effects. Each hazard is characterised by its location, 
intensity and probability (International Strategy for Disaster Reduction, 2004; Makoka 
and Kaplan, 2005) 
The number of reported major catastrophes and their impact on social and economic 
development has been increasing worldwide. With the growing of an increasingly 
urbanised world population, the potential for human-induced and natural disaster is 
growing daily. According to Munich Reinsurance (2004), over the last decade, around 
7,000 natural disasters including earthquakes, volcanic eruptions, tropical cyclones, 
floods and droughts have occurred, killing more than 300,000 people and causing over 
US$ 800 billion in economic losses. As a result of global climate change and climate 
variability, the frequency and intensity of climate-related events are likely to increase. 
While all countries may be confronted with natural hazards, as noted by Herrmann et 
al (2004), the poorer developing countries, in particular, are disproportionately 
vulnerable to those hazards turning into disasters.  
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Globally, the worsening plight of the millions of people living in appalling shelter 
conditions has been recognized as one of the major problems facing humankind. This 
problem is further compounded by accelerating poverty, while high rate of population 
growth and burgeoning urbanisation continue to adversely affect the quality of the 
existing infrastructural facilities and services in the developing world. The last few 
decades have brought enormous changes to the world‟s population and human 
settlement and these have caused increased flurry of activities and concern amongst 
city analysts, urban managers and policy makers in terms of vulnerability to and or 
occurrence of disaster (UN-Habitat, 2002a).Vulnerability to disaster usually refers to 
the ability of an individual or a group to prepare, respond, cope and recover from a 
disaster (Robertson, 1992 and Blaikie et al, 1994). 
The world‟s population in 1995, according to UN-Habitat (1996), United Nations 
Organisation [UNO] (1996) and International Human Dimensions Programme on 
Global Environmental Change [IHDP] (2005) was estimated at 5.7 billion and it 
continues to grow by 83 million people per year. There has been more growth in 
population in the last fifty years than the previous 2 million years that humans have 
existed. Currently, the rate of population increase is 1.2 % per year, which means the 
global human population is on a trajectory to double again in 58 years. Presently, the 
world population has reached the 7 billion milestone while the global rural-urban 
balance of populations has tipped irreversibly in favour of cities. Tokyo emerges as the 
world‟s largest urban area under this definition, with 36.7 million people, which is 
more than a quarter of the national population. Tokyo is followed by Delhi, with 22 
million; São Paulo, 20 million; Mumbai, 20 million; Mexico City, 19.5 million; New 
York-Newark, 19.4 million; Shanghai, 16.6 million; Kolkata (Calcutta), 15.5 million, 
Dhaka, 14.7 million, Karachi, 13 million and Lagos, 9 million. Each of these cities 
reflects a different pattern or path of planning and governance and a different 
composition of affluence and poverty (United Nations Population Division, 2003; 
Population Media Centre, 2009; United Nations Population Fund, 2011). 
The rate of urbanisation and its attendant socio-economic and spatial consequences 
have been of tremendous concern, especially to all professionals in human settlements 
and to policy makers and analysts. It is pertinent to note that the problem of 
urbanisation in the developing countries is not necessarily that of the level but that of 
the rate. For instance, while the level of urbanisation in Nigeria is 36 %, that of South 
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Korea, Mexico and Colombia is 79, 74, and 71 % respectively (Federal Government of 
Nigeria [FGN] 1997; Population Reference Bureau 2001; Olatubara 2002). However, 
the rate of urbanisation in Seoul is 7.8 %, Mexico City 5.5 % and Bogotá 5.4 % while 
that of Lagos is 15 % per annum. This rapidity in the rate of urban expansion is so 
overwhelming that it generally far exceeds the speed with which urban managers in 
Nigeria are able to respond to the dynamics of urbanisation, occasioned by skewed 
economic growth, population increase and lateral expansion, due to inadequate 
facilities, resources and capabilities at their disposal (Olatubara, 2002 and 2007). 
Thus, the rapid rate of urban agglomeration has been faced with colossal urban 
environmental challenges such as the growth of urban slums and informal settlements 
characterised by substandard housing; inadequate or absence of basic infrastructural 
facilities and services; poor environmental sanitation; air, water and noise pollution; 
urban sprawl and squalor (Agbola, 2005a). Other observable indices of declining urban 
quality include unemployment or underemployment; overcrowding; incessant civil 
unrest; infectious diseases; prostitution, sexually transmitted infections (STI), crime 
and municipal budget crisis. The result is that all the cities and urban agglomerations 
have paradoxically become centre of excellence in urban squalor and aggravated 
poverty, exhibiting human misery, training grounds for various types of gangsterism, 
diverse category of civil and violent crimes and perhaps more despairingly, an 
apparent absence of credible, futuristic and sustainable urban management system 
which could evolve alternative future for the contemporary urban systems (Agbola, 
2005a). The combination of all these environmental challenges create instance recipe 
for human-induced and nature induced disasters (Smith, 2005). 
Twigg (1998) contended that there are no such things as natural disasters, but there are 
natural hazards. A disaster is the result of a hazard‟s impact on the society. Hence, the 
effects of a disaster are determined by the extent of a community‟s vulnerability to the 
hazard or, conversely, its ability or capacity to cope with it. Thus, vulnerability is not 
natural but the result of an entire range of constantly changing physical, social, 
economic, cultural, political and even psychological factors, especially in urban 
settings, that shape people‟s lives and create the environments in which they live. For 
that reason, natural disasters could be seen as nature‟s judgement on what humans 
have wrought. 
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Nigeria is bedevilled with natural and human induced disaster such as, flood, drought, 
famine, disease, fire, land degradation, ocean surge, erosion, landslide, windstorm, 
vehicle and aviation crash, boat mishap, oil spillage, and terrorism (Ojo, 2013; Wahab, 
2013). However, the natural hazards the country faces, from time to time, are ones that 
are aggravated by human activities and are almost always preventable. For example, 
desertification and or desert encroachment in the sahel and sudan savannah of the 
extreme north western and north eastern parts of the country can be stemmed by 
embarking on purposeful and functional enlightenment campaigns to prevent 
communities within these regions from felling trees indiscriminately for fuel wood. In 
addition, flood disasters can be controlled in most of the urban centres if people adhere 
to the minimum space standard between drain and building and by not building 
structures within and or along the natural flood plain of urban rivers. As opined by 
Nigerian Environmental Study/Action Team [NEST] (1991), the increasing frequency 
and severity of floods in urban centres in Nigeria do not stem from increased rainfall. 
On the contrary, rainfall amounts have, overall, been on the decrease, but the increased 
floods are in response to an increasing rate of urbanisation in the absence of well-
articulated and comprehensive physical planning and development control in the cities.  
Urban areas are not, by nature, more vulnerable to disasters. Instead, it is the structural 
and dynamic processes occurring in an urban area which accelerate urbanization and 
concentrate population in places within the city that increase vulnerability. 
Consequently, vulnerability needs to be examined in relationship to changes in socio-
spatial patterns that occur in urban systems (Makoka and Kaplan 2005). However, in 
Lagos State today, the urban dynamic processes triggered by the provision of low 
income housing from early 1970s to early 1980s, increase the probability that a 
dangerous event (natural or technological) could be disastrous or resulted into a 
disaster. Among those factors and processes are the size of the city, the characteristics 
of its settlements, the cultural and economic capacities of its inhabitants, the socio-
economic gaps between the different social groups, demographic and physical factors 
and the nature of urban planning and development control  (Olorunfemi 2009). Lagos 
state is exposed to natural hazards of hydro-meteorological origin (which can cause 
flooding, land subsidence and diseases epidemic). Added to these natural hazards are 
dangers derived from human activities, which also facilitates technological accidents. 
 
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1.2 Statement of problem 
Disaster has never been a new phenomenon in the life of humanity; it dates back to the 
biblical days of Noah, when he was told to build an ark in order to save humanity from 
the impending flood disaster (Holy Bible [Genesis, Chapters 6 and 7], 2010). With an 
increasingly urbanised population, especially in the developing countries, the 
potentials for human-induced and natural disasters are growing daily. According to 
McCall (1992), the concept of natural disaster is an ambiguous one, for many 
catastrophic events within the human environment are human-induced or at least made 
worse by humans‟ activities.  
Ojo (2001), noted that the impact of natural and human-induced disasters on people 
and human settlements in Nigeria, most especially Lagos State, are becoming greater. 
This development is frequently caused by vulnerabilities created by human actions 
such as uncontrolled or inadequately planned human settlements, lack of basic 
infrastructure and the occupation of disaster-prone areas. Poverty and ignorance are 
also identified to be contributing to some of these problems. Therefore, the induced 
disasters exerted heavy toll on humans in terms of loss of lives, destruction of socio-
economic infrastructure and the negative impact on already fragile ecosystems is 
equally colossal (Olorunfemi, 2009). Thus, in many parts of the city, natural and 
human-induced disasters will continue to occur. However, human actions will either 
increase or reduce the vulnerability of societies to disasters depending on the kind of 
practices they engaged in. For example, it has been documented in most of the 
Nigerian‟s cities that, changing demographic and economic patterns resulting from 
rural-urban, inter- and intra-urban migration would lead to uncontrolled urbanisation 
and widespread poverty which would, invariably, push large number of people to live 
in disaster-prone areas. Similarly, there is a considerable possibility for the reduction 
of risks through the application of disaster abatement and mitigation efforts based on 
modern forecasting technology as well as improved human settlement plans and 
building practices.  
Natural and human-induced disasters come in many forms and it is when nature comes 
into conflict with humans that catastrophe results. For a hazard to be called a public 
disaster, according to Blong (1992), human life, property, and social infrastructure had 
to be lost to the event and socio-cultural attributes of people in such environment 
affected. In this regard, if windstorm causes havoc to thatch and mud structures in a 
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remote hamlet, for example, the event may be dramatic but it is seldom a disaster. A 
disaster occurs when wind storm strikes a large city, fire outbreak in densely and 
congested market or residential area, bomb explodes in a densely populated settlement 
or a high-rise building collapses within a city‟s Central Business District (CBD) 
causing multiple collapse of structures within its vicinity. Thus, one cannot talk about 
disaster and vulnerability without considering where people have chosen to live and 
how densely they have spatially occupied the existing space (Zebrowski, 1997). For 
example, Lagos State is likened to densely populated cities such as Mumbai, Dhaka, 
Rio de Janeiro and Hong Kong and if the present population growth rate, the major 
factor deduced to be driving urban dynamics process in Lagos State, is not checked, by 
the year 2025, Lagos will be the most densely populated city in the world (Population 
Reference Bureau, 2005). According to Lagos State Bureau of Statistic (2005) and 
Buffett Centre (2010), the rate of population growth in Lagos State is about 600,000 
per annum with a population density of about 4,193 persons per square kilometre. 
However, in the built-up areas of metropolitan Lagos, the average density is over 
20,000 persons per square kilometre. 
At the city scale, the process of urban dynamics can be understood in three main 
phases: available land in a city that produces a subset of areas to be occupied by 
different land use; changing land use pattern and local level interactions that combine 
to create the distribution of new built-up areas and the effects of the interactions on 
future land use coupled with the interconnectivity between the demographic, social, 
economic and political characteristics of the city. From a practical point of view, 
White, et al (1999), noted that the process of urban dynamics can be defined as an 
iterative probabilistic system in which the probability of a place in a city to be 
occupied by a land use in a time is a function of the concerned factors measured for 
that land use: suitability, accessibility, land use zoning status, socio-economic and 
population characteristics and stochastic perturbation. 
The dynamics of urban process in Lagos, and in other developing countries‟ cities, is 
usually a complex phenomenon measured in terms of highly accelerated demographic 
growth; irregular (in)formal settlements; stress on marginal land by poor intra urban 
and rural migrants, inefficient and oversaturated transport and roadway systems that 
could barely support the massive daily commute of the city‟s inhabitants, irregularities 
in the enforcement of developmental and physical planning norms, construction of 
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structures and indiscriminate dumping of solid waste that impede natural drainage 
patterns and water flow. Additionally, the lateral burgeoning of Lagos to its flood 
plains and marginal land further predisposed the city to natural hazards. The possibility 
of a technological disaster is also emerging due to the concentration of intense 
industrial and other economic activities. This situation increases the vulnerability to 
disasters of not only the city‟s inhabitants but also the systems on which they depend, 
such as water, electrical supply, housing, transportation networks and access to health 
care. 
According to Blaikie, et al (1994) and Martínez-Viveros and López-Caloca (2010), the 
impact of disasters must be interpreted as a consequence of different structural 
situations that expose people and systems to danger. The authors believe that natural 
events, as determining factors of disaster, play a secondary role when compared to the 
socio-economic, political and physical environment. Consequently, vulnerability 
becomes the “active agent” in a disaster, not the natural phenomenon, which only 
serves to ignite preexisting, critical situations. Increased vulnerability increases the 
probability of disaster for the unit under analysis (people, places, social groups, 
systems). In order words, physical, political, socio-economic and demographic 
dynamics within the city‟s sphere, if not holistically managed, combine in a process 
that increases vulnerability and leaves people, individually or in groups, exposed to 
danger as they live or work in precarious areas, construct insecure buildings and 
infrastructure, or utilize unsound transport system. Vulnerability is acutely connected 
to people‟s ways of life, as individuals or in groups, and is related to their assets, 
access to resources (productive, natural, managerial, organizational) and their capacity 
to prevent, face, organise and adapt to disastrous events.  
Once it is accepted that vulnerability is a social process, not a matter of fate, it 
becomes possible to generate capacities to diminish it and better anticipate, not only 
the likely occurrence, but the potential impact of disasters (Ojo, 2013). Planning is a 
purposeful process that links knowledge to action in order to induce changes geared 
toward desired future outcomes (Martinez-Viveros and Lopez-Caloca, 2010). 
However, the spatial changes evident in Lagos have not been the product of planning. 
Rather, intra-city and rural-urban migration and the quest for employment 
opportunities and other attraction parameters brought about chaotic growth and the 
generation of urban sprawl that encroaches on marginal land, leading to adverse land 
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use and land cover change.  Therefore, should the natural and human interaction 
interrupt the drainage network, detonate bomb, shake buildings to the ground, start a 
civil strike (communal clash, crisis, conflict and social disorder) or ignite a few fire, 
the impact on many dwellers will be catastrophic bearing in mind the increasing rate of 
urbanisation and density of development in the absence of well-articulated 
comprehensive physical planning and development control within the cities. The 
association between urban dynamics and vulnerability in Lagos State is succinctly 
captured by the incessant building collapse, fire and disease outbreak, increasing 
perennial flood that singularly and collectively exposed people, property and 
infrastructure to disasters. 
Diverse studies have been carried out in Nigeria on disasters: its types, severity, 
frequency causal factors, and vulnerability patterns. However, there is a paucity of 
investigations on the possible associations between urban dynamics and vulnerability 
to disasters in Nigerian cities. This is a major research gap this study intends to fill 
focusing on Lagos, the most dynamic, the most densely populated and the most 
vulnerable to disaster State in Nigeria. 
1.3  Research questions 
In analysing the nexus between urban dynamics and vulnerability to disasters, the 
under-listed research questions were posed: 
i. What triggers the urban dynamics process in Lagos State?; 
ii. Is there any relationship between urban dynamics and vulnerability to disaster?; 
iii. What are the impacts of disasters in the residential neighbourhoods?; 
iv. What is the importance of Geographic Information System (GIS) in disaster 
management? 
v. Is there any variation in the occurrence of disaster across residential 
neighbourhoods in Lagos State?; 
vi. How does socio-economic indices, household characteristics and housing 
facilities and services affect urban dynamics, vulnerability and trend of 
occurrence of disaster?; 
vii. In what ways do the government institutions respond to disasters?; and 
viii. What are the legislative and institutional policies and programmes developed to 
manage disaster and how effective are these policies? 
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1.4 Aim and objectives 
The aim of this research is to examine the nature of urban dynamics process and 
associated vulnerability to disasters in Lagos State. In order to achieve this aim, the 
specific objectives are to: 
i. Identify the nature and contributing factors to urban dynamics and vulnerability 
to  disasters; 
ii. Determine the land use and land cover change from 1984 – 2010 and simulate 
flood risk using Geographic Information System (GIS);  
iii. Examine the relationship between urban dynamics, socio-economic indices and 
vulnerability to disasters;  
iv. Discuss the legislative and institutional policies enacted and programmes 
implemented to abate disasters by stakeholders in disaster management; and 
v. Provide recommendations with facilitators that will drive the processes of its 
implementations 
1.5 Hypothesis 
The hypotheses to be tested for this study are stated as follows: 
i. Urban dynamics is influenced by the availability of low income housing 
ii. Vulnerability to disasters is a function of socio-economic indices, housing 
characteristics and provision of infrastructural facilities and services 
iii. Occurrence of disasters differs significantly between residential 
neighbourhoods;  
1.6 The study area settings 
Lagos state is located in the South Western part of Nigeria, on the narrow plain of the 
Bight of Benin. It is bounded to the North and East by Ogun state, by the Bight of 
Benin to the South, and by the Republic of Benin to the West. It extends 
approximately from latitude 6°2' N to 6°4'N, and from longitude 2°45'E to 4°20'E. 
Lagos state represents 0.4 % of Nigeria‟s territorial landmass with total land area of 
3,577 square kilometers. Lagos State was created on May 27th, 1967 by virtue of the 
States (Creation and Transitional Provisions) Decree No. 14 of 1967 which 
restructured Nigeria into a Federation of twelve states. However, Lagos as a trading 
port has a recorded history dating back to the Portuguese explorers of the 16th century. 
The State is composed of the old Federal Territory of Lagos which remains the 
financial hub and was the Federal Capital of Nigeria (up to December 12, 1991), and 
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the old Colony Province of the defunct Western Region of Nigeria comprising 
Badagry, Ikeja, Ikorodu and Epe Divisions. The state has not been affected by 
subsequent state creation exercises and, today, it is one of the 36 states making up the 
Federal Republic of Nigeria as shown in Figure 1.1. Figure 1.2 depicts the study area 
in Lagos state context. 
Lagos State is the smallest state (in land area) in Nigeria, yet it has the highest 
population. According to the 1991 national census, Lagos State had a population of 
5,725,116 out of a national total of 88,992,220 (National Population Commission 
2006). However, the results of the 2006 census show that Lagos State and the study 
area have 9,013,534 and 5,641,717 inhabitants respectively out of a national total of 
140,003,542. This is less than what was anticipated. However, based on UN-Habitat 
and International Development Agencies‟ estimate, Lagos is said to have about 18.5 
million inhabitants in 2008. However, within the official population structure of Lagos 
State, the study area accounts for over 60 % of the population on an area that is less 
than 25 % of the land area of Lagos. 
  
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Figure 1.1 Lagos state in Nigeria context  
Source: Dada, et al (2010) 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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Figure 1.2 Political structure of Lagos state including the study area 
Source: Dada, et al (2010) 
 
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Geographically, Lagos state is a wetland dominated by swamp forest consisting of the 
fresh water and mangrove swamp forests. The temperature of the state is high all year 
round and has two climatic seasons: wet (April – October) and dry (November – 
March). During the rainy season, the mean annual and monthly rainfall as well as the 
number of rainy days is high due mainly to the effect of south westerly monsoon wind. 
The high rainfall, especially at the peak of rainy season, coupled with poor waste 
disposal system and inadequate drainage network, results into perennial flooding. The 
drainage network within the state is characterised by maze of lagoons and waterways. 
The major water bodies are the Lagos and Lekki Lagoons, Ogun, Oshun, Yewa and 
Kweme Rivers. Others are Kuramo waters, Badagry, Five Cowries and Omu creeks. 
The network of creeks and lagoons covers about 800 square kilometers, which is about 
22% of Lagos landmass. Though water bodies reduce land availability, however, 
housing construction has increased due to land reclamation. For instance the proposed 
Eko Atlantic City will be built on 10, 000, 000 square meters of reclaimed land from 
the Atlantic Ocean (Eko Atlantic Project 2010). 
Lagos is the commercial and industrial hub of Nigeria with a GNP that triples any 
other West African cities. The economy of the state consists of commercial, industrial, 
financial services undertaking by formal and informal sectors. Energy, water access, 
sewerage, transportation, solid wastes disposal and housing have all been adversely 
affected by haphazard development. 90 % of the population of the state has access to 
electricity but availability is another different ball game. Water supply to Lagos State 
is inadequate with the low income residential neighbourhoods having the least 
provision. Water shortage is rife in Lagos state despite the State‟s natural endowment 
with water bodies. The public sector has almost completely withdrawn from household 
waste collection and disposal. In terms of waste management, about 66 percent of the 
solid wastes in the State are disposed either by government or through private and 
community efforts. The remaining percentage is left at various illegal dump sites. The 
waste generated in Lagos State, especially within the high density neighbourhoods, is 
hardly disposed scientifically; household garbage is dumped in nearly all the vacant 
plots while untreated industrial waste is channeled into public drains or surface water 
bodies. However, with the increasing level of public-private-participation (PPP) and 
the contemporary stand of government towards improved sanitation, there is a ray of 
hope that waste management will improve significantly in the years ahead. 
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Traffic congestion is a daily challenge in Lagos metropolis as a result of high 
passenger trips per daily transport demand. With the introduction of integrated and 
intermodal transportation system coupled with mass transit Bus Rapid Transit Scheme 
(BRT) the transport situation is improving gradually. The disasters that the State is 
most vulnerable to are: road crash, building collapse, fire incidence, communal 
clashes, land subsidence and general environmental degradation and pollution 
aggravating climate change induced disaster like: ocean surge, coastal erosion, flood 
and disease outbreak 
One of the greatest challenges facing Lagos State is the provision of housing. There is 
considerable gap between supply and demand. Overcrowding, slums and substandard 
housing manifested in the landscape of Lagos State. Despite the efforts of the various 
housing authorities, over 90 percent of the housing in metropolitan Lagos is still 
provided by the private sector and individual effort. Residential districts range from 
low-density areas that have been able to retain their characteristics, through medium-
density districts to substandard high density settlements that lack basic amenities. 
Some of the high to medium density neighbourhoods located along the major 
highways in the State have been gentrified to accommodate the evolving commercial 
activities in the State. 
 
  
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CHAPTER TWO 
THEORETICAL AND CONCEPTUAL ISSUES IN VULNERABILITY 
ANALYSIS AND LITERATURE REVIEW 
2.0  Introduction 
In contemporary times, increasing attention is being paid to the evolvement, 
modification and application of theories and concepts in most of the learned 
disciplines, especially in social and environmental sciences. The reason for this 
phenomenon as noted by Agbola and Kasim (2007) is not unconnected with the ever-
increasing urge to either invalidate an existing theory or test its responsiveness, degree 
of fairness or effectiveness. There is plethora of theories and concepts used in 
vulnerability analysis and disaster management; however, the following were adopted 
for this study: Post-Modern Urbanisation Concept; Urban Dynamics Theory; Urban 
Governance Concept; The Vulnerability Concept; and Traditional - Expanded Disaster 
Management Cycle Concept. 
2.1 Post-modern urbanisation concept 
The decade of the 1980s has seen the extensive presentation of a fashionable theory to 
the effect that people today are living in a knowledge-based post-industrial world with 
a postmodern culture. With globalization, industrial restructuring, and new 
breakthroughs in information and communication technologies, post-modern 
urbanization has entered a new phase. New patterns of urbanization are emerging both 
in the industrialized countries and the developing world, increasingly characterized by 
metropolitan regions. 
The new urban model which bridges the distinction between the rural and the urban is 
particularly important for the developing world, where the growth of cities has been 
the greatest. Casting a relief of sharply increasing inequality, post-modern cities bring 
about exclusiveness, social fragmentation and spatial segregation of the rich and the 
poor in terms of vulnerability to disasters. Vulnerability is determined by a variety of 
social, economic, cultural and political factors, which define individual‟s or group‟s 
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status, position and power in society. It also has a distinct spatial dimension, as people 
with similar characteristics tend to settle in the same or similar areas (Wisner, 2003).  
In order to systematize the review of the effects of urbanization on disaster and to 
show that post-modern urbanisation magnified vulnerability, Charveriat (2001) and 
Pantelic, et al (2005), adopted the following concepts as the main factors that 
characterize vulnerability to hazards: Exposure of people and assets to hazards; 
susceptibility of people and assets to disasters; and environmental degradation of 
hazard-prone areas.  
2.1.1 Exposure factor 
Throughout history, one of the functions of cities was to provide safety and protection 
to its inhabitants from disasters, onslaught of invaders or pest and pestilence. The 
concentration of wealth, knowledge and power in great cities made it also possible for 
the construction of some of the greatest projects to protect people and property from 
the vagaries of nature. Drainage and irrigation were the first mitigation projects 
designed to serve and protect ancient civilizations. To this day, cities have continued to 
employ their vast resources and greatest technological advances to protect themselves 
from biological, hydrological, meteorological and geological hazards (Mitchell, 1999).  
Post-modern urbanization has not only exacerbated many of the traditional urban 
development processes that contribute to vulnerability (such as the spread of slums and 
the decay of old or undesirable neighbourhoods) but it has also changed the way urban 
space is developed and managed, creating, thereby, new agents of vulnerability. The 
reality of new economic imperatives has forced city authorities to reconsider their 
priorities. Prudence and safety concerns have become casualties of the cost-conscious 
development strategies. Even in highly industrialized nations like Japan, the high cost 
of urban land in Tokyo encourages overcrowding, restricts open space and pushes new 
developments onto hazardous coastal areas in the paths of cyclones and tsunamis 
(Hoyois, et al 2007). While all social strata may equally be exposed to the risks of 
some hazards, in most cases, this exposure is determined by locations, which people 
choose or in which they are obliged to live (Velasquez, et al 1999). 
In most urban centres, the competition for land is fierce socially and economically. 
Therefore, poverty has made people to squat in the deadly shadows of refineries, 
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chemical factories, toxic dumps, burrow pits, abandoned quarries or in the margins of 
railroads and highways. This development, has „constructed‟ an urban disaster problem 
of unprecedented frequency and scope. Referring to the group of the least developed 
countries, Davis (2004) notes that 78 % of the urban population lives in slums and in 
some countries reaches well over 90 %. In Mozambique, a country that has reached an 
enviable annual economic growth rate of 9 %, almost 80 % of its residents live on less 
than $2 a day and have a life expectancy of 41 years. This scenario is not very far from 
what is happening in most of the Nigerian cities. 
In addition, more than 50 % of Mumbai‟s 16 million residents live in slums, and about 
100,000 actually live on the streets or drainage canals built to take out excess water 
during monsoon months (World Bank, 2005). Also, some of the entrepreneurial street 
residents rent out their makeshift shelters to other homeless people as sleeping quarters 
during a part of a 24-hour period. Recent migrant to urban centres in Cairo and Phnom 
Penh squat or rent space on rooftops, thereby, creating slum cities in the air (Davis 
2004).  
Focusing closer on the situation in individual cities in Nigeria, for example, in Lagos, 
using the basic Millennium Development Goals [MDGs] indicators such as: access to 
improved water; access to improved sanitation facilities; secure tenure; structural 
durability/quality of dwelling unit; and sufficient living area, not overcrowded inherent 
in Millennium Development Goal 7 Target 11, about 60 % of the inhabitants reside in 
slum households that has positive correlation with exposure to hazard and vulnerability 
to disaster (Tibaijuka 2002; UN-Habitat 2003a; 2003b; Agbola 2005b; International 
Strategy for Disaster Reduction [ISDR]. 2006). 
2.1.2 Susceptibility factor 
The rapid urbanisation in the developing countries has engendered one of the greatest 
socio-economic changes ever witnessed in the last five decades leading to the 
burgeoning of new kinds of slum. For instance, after the day‟s work, whether informal 
or formal, all humans must retire to their houses, however defined and wherever 
located. Since urbanisation is increasing at a rate greater than the capacity and 
capability of urban planners and managers, city dwellers, especially migrants, retire to 
what the city planners called slum but which the resident called home. Thus, as 
countries urbanised, the number of people living in slums increase (Agbola 2005a).  
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The susceptibility of people and assets to hazards measures the degree of their 
preparedness and adaptability to known risks. The concept of susceptibility includes 
the quality of construction of assets, the awareness of the residents to risks posed by 
known hazards, the presence or absence of emergency and preparedness plans and 
facilities, and the ability of the population to prepare and withstand the impact of a 
disaster. This is where social and economic status and political clout of the population 
play an important part, since it has been shown a number of times that the poor are 
disproportionately susceptible to the effects of natural hazards (UN-Habitat and 
Department for International Development [DFID]. 2002). The World Disaster Report 
stated that 97 per cent of all disaster-related deaths in 2001 occurred in the developing 
countries (International Federation of Red Crescent Red Cross Societies [IFRCRCS], 
2001). Moreover, as a percentage of GNP, disaster losses are an estimated 20 per cent 
higher in developing than in developed countries (Anderson, 2000). Only 2 per cent of 
all the people affected by disasters every year live in highly developed countries. In 
contrast, about 90 per cent reside in the low- and middle- income countries (IFRCRCS, 
2001).  
Pantoja (2002) observes that the poor are more risk averse in economic terms because 
they lack savings or assets, but are more “risk taking” in spatial terms. The situation in 
the central city slums of Santo Domingo, illustrates the point: The risk of flooding 
during rains varies from 6 to 45 per cent, respectively, for houses located near the river 
and those built on higher, consolidated ground. The quality of housing construction 
reflects the local perception of risk of floods and the residents‟ willingness to spend 
money on shelter. Wooden shacks are thus common in the areas near the river, where 
they are prone to flooding and the investment is likely to be lost, but houses of durable 
material, sometimes several stories high, are built on a higher ground. Rents also 
reflect the safety of location: those on the higher ground pay almost twice the amount 
paid by those near the river and the canals (UN-Habitat 2003a). 
The extent of disaster preparedness of a community speaks not only of their knowledge 
and awareness of risks, but also of their adaptability to change, and enormous public 
investments in social and essential infrastructural facilities and services. In most 
developing countries such investments have been minimized, if they ever existed, 
under the pressure of fiscal retrenchment that characterised the theme of the new 
profit-driven and commercialised urbanization. Interestingly, as noted by International 
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Strategy for Disaster Reduction [ISDR] (2002), the value of such public investments is 
demonstrated by the example of Cuba, one of the rare countries that still practices 
command economy, where natural land use planning and management are integrated 
into risk reduction considerations. In Nigeria, a lot still has to be done to adequately 
integrate disaster risk reduction into the country‟s developmental agenda. 
2.1.3 Environmental factor 
Environmental problems manifest in various forms and dimensions.  The effects 
associated with these problems are felt locally, nationally, continentally and globally.  
For example, in Nigeria, as noted by Adetunji (2006), every state of the federation 
across the various ecological zones suffers from one form of environmental ill or the 
other.  The north „blows‟ away through wind erosion aggravated by deforestation, 
drought, over-grazing and desert encroachment.  The coastal south „washes‟ away into 
the ocean.  Gully erosion opens the middle belt and most southern states especially in 
the south east.  In addition to these, there are other environmental problems such as 
flood, building collapse, bush burning, oil spillage, gas flaring, pollution, municipal 
waste disposal and above all the general urban infrastructural decay. Like the 
kindergarten rhyme that teaches us of little drops of water forming the mighty ocean, 
scientific and empirical evidences have shown that local environmental problems have 
regional and indeed global consequences as manifest in ozone layer depletion, global 
warming and climate change and climate variability challenges. 
Environmental degradation and global environmental change, particularly climate 
change, pose an exceptionally complex challenge to humanity by affecting 
vulnerability and hazard patterns (Strange, 2006 and The Punch Newspaper, 2007).  
Thus, environmental degradation and global environmental change increase the 
intensity of hazards and they are often the factors that transform the hazard into a 
disaster.  For instance, floods are aggravated or even caused by deforestation, which in 
turn causes erosion and silt-up river channels.  Poverty and vulnerability are linked to 
this situation (Martine and Guzman 1999 and Pantelic et al, 2005).   
The poor are compelled to exploit environmental resources for survival, therefore, 
amplifying both susceptibility and exposure to disasters, in particular those triggered 
by floods, drought and landslide. The degradation of the urban environment is, 
therefore, the result of not only uncontrolled urbanization that swallows open spaces 
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and agricultural land, interrupts natural drainage, patterns or denudes hillsides in 
pursuit of new urban land, but also of the breakdown in the ability of local populations 
and their governments to manage urban growth. This breakdown is the inevitable 
consequence of fiscal retrenchment and the restructuring of the public sector that, in 
most cases, leaves the poor sections of the city to fend for themselves as manifested in 
the study area. 
The outcome of the relationship postmodern urbanisation and its explanatory indices 
of exposure, susceptibility and environmental factors is highlighted in Figure 2.1. The 
Figure illustrates that the postmodern urban development especially in the developing 
countries of the world is characterised by social inequality, exclusion, unemployment, 
increasing urban poverty and inability of urban managers to provide the most basic of 
basic infrastructures such as water, electricity and roads. When disaster occurs in this 
kind of situation, the urban poor are further thrown into deprivation.  
  
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Figure 2.1 Post-modern urbanisation, poverty and vulnerability to disaster 
schema 
Source: Derived as a summary of post-modern urbanisation discussions (2013) 
 
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2.2 Urban dynamics theory 
Urban dynamics was developed as a tool for urban policy analysis. Forrester (1969), 
made a unique contribution to the analysis of social systems by introducing computer 
simulation modeling to the study of urban interaction. Urban Dynamics refuted the 
conventional wisdom that urban problems are caused by such factors as rural-urban 
migration, dwindling fiscal resources, and sub urbanization, which are beyond the 
control of central cities. Using a computer simulation model, the analysis showed that 
most urban problems arise, instead, from the interaction of processes that occur within 
the cities. It also identified policies that enable cities to exercise some control over 
their own futures.  
Urban dynamics theory postulates three primary forces that underlie urban growth and 
decline guided by perceptions of relative attractiveness. These are: aging of housing 
and business structures, and the feedback connections among population, housing and 
jobs. As noted by Forrester (1971), often policies that have been adopted for correcting 
a difficulty are actually intensifying it rather than producing a solution. In order words, 
actions believed to alleviate the difficulties of a city can actually make matters worse. 
For example, as noted by Moody (1970), urban dynamics theory explained four 
common programmes aimed at improving the depressed nature of central cities. First 
programme was jobs creation. Second was a skill training programme to increase skills 
of the lowest-income group. Third was financial aid to depressed cities. Fourth was 
low-cost housing construction for low income earners. The four programmes range 
from ineffective to harmful judged either by their effect on the economic health of a 
city or by their long-range effect on the low income population. The results both 
confirm and explain much of what has been happening over the last several decades in 
cities (proliferation of informal settlements, environmental degradation and 
vulnerability to disasters). 
Forrester (1969) observed that naturally, obvious solutions to social problems are apt 
to fall into one of several traps set by the character of complex systems. In other words 
an attempt to relieve one set of symptoms may only create a new mode of system 
behavior that also has unpleasant consequences. Also, attempt to produce short-term 
improvement often sets the stage for a long-term degradation. The local goals of a part 
of a system often conflict with the objectives of the larger system. People are often, 
intuitively, intervene at points in a system where little leverage exists and where effort 
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and money have but slight effect. The question to ask, according to Forrester (1969) 
and Alfeld (1995), is why do the best of intentions for improving a city lead, instead, 
to greater social pressures, more commuting delays, increased drug addiction, higher 
crime rates, greater welfare loads and vulnerability to disasters in most cities? 
In most cities, administrative authority is distributed vertically according to specialized 
tasks and responsibilities. In several respects, urban dynamics has shown that vertical 
forms of municipal government may be relatively ineffective because urban functions 
administered by separate agencies are in fact highly interconnected. As noted by 
Kadanoff (1971), the attractiveness principle in urban dynamics implies that all cities 
tend toward attractiveness equilibrium with their external environments. Because 
people migrate to areas that they perceive as being relatively attractive, efforts by local 
government to improve a single component of urban attractiveness (such as housing 
availability) always lead to rising urban population and the degradation of other 
components of attractiveness (such as job availability).  
The quality of urban life in most cities around the world has not improved since the 
1960s. By any objective measure, the individual problem-solving approach seems to 
have failed. Reports and statistics on urban crime, pollution, slums, traffic, welfare and 
vulnerability to disaster attest to this fact. Most observes (Sanderson, 2000; Aguirre, 
2002; UN-Habitat and Department for International Development (DFID) 2002; UN-
Habitat, 2010) of the urban scene would agree that, relative to our expectations, cities 
are getting worse, not better. Therefore, urban dynamics theory views city as a 
complex social and economic system formed by the interactions of individual efforts to 
achieve personal goals. Unfortunately, in modern life, such a system does not operate 
to further individual goals – or even, in some cases, human goals generally. Many 
individuals can take actions that appear to satisfy their own objectives; the aggregation 
of these efforts constitutes a complex social system. The characteristics of that system 
may cause it to behave in some very different ways from the expectations and the 
desires of its creators (Forrester, 1975).  
Urban dynamics provides a theory that embraces a conceptual understanding of the 
city as a whole. It facilitates the analysis of city‟s various activities as interrelated 
functions. Only when city operates within such a conceptual framework can it be 
certain that new urban programmes will actually solve urban problems. Without 
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embracing the postulation of urban dynamics, the solution to urban problems will be 
elusive and vague. Therefore, cities, especially in the developing countries, should 
begin to exhibit the courage to plan in terms of a maximum population, a maximum 
number of housing units, a maximum permissible building density, and a maximum 
number of jobs (Alfeld and Graham 1976). A city must also choose the type of city it 
wants to be. To become and remain a city that is all things to all people, as epitomized 
by Nigerian cities, is virtually impossible. There can be many uniquely different kinds 
of cities, each with its special mix of advantages and disadvantages. However, the 
policies that create one type of city may destroy another type. A choice of city type 
must be made, and corresponding policies must be chosen to create the combination of 
advantages and disadvantages that are characteristic of that type. There are severe 
limits on how many types of cities that can be created simultaneously in one place. 
When the choices have been made, and when effort is no longer dissipated in growth, 
there will be an opportunity to come to grips with social and economic decay. 
Urban dynamics is a theory of the forces that shape human settlements which, in turn, 
shape human history. The theory is rich with subtle nuances which deserve a vigorous 
reinterpretation, a reinterpretation suited for no less a purpose than the political 
management of the people and resources of every nation on Earth. Urban dynamics 
shows the folly of traditional thinking, both for cities and for the world. Human 
systems, from all indications are too complicated for intuitive solutions. Traditional 
solutions to urban problems hardly work. Feedback, nonlinearities and hidden delays 
defeat most conventional policies (Alfeld, 1995). Eventually, urban managers and 
analysts must shift the paradigm away from traditional analytical methods to the urban 
dynamics viewpoint-conserve the existing development by reinforcing the preferred 
counterbalances. It is the mentality of the great cities of Europe and it is the mentality 
of the well-preserved American suburb. It works there and it can work worldwide 
especially in the developing countries. The major force that could drive the preferred 
urban dynamics in the developing countries is hinged on the inclusive city as 
postulated by the UN-Habitat‟s urban governance concept  
2.3 Urban governance concept 
In recent times, vulnerability to disaster has generated a lot of debates, thus many 
management techniques have evolved through various discussions on vulnerability 
pattern. All the management techniques developed are understood and confined to the 
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intellectual community and hence lack mass participation. Awareness of disaster and 
grass-root inclusion is the only effectual way in which one can bring about mass 
participation in disaster management (Quarantelli, 2005). Also, disaster management is 
successful only when the general public has some awareness about the causes and 
effect of the disaster. Therefore, the importance of the concept of participatory disaster 
management is more fully appreciated if one considers recent developments in 
conceptual debates about achieving integrated and sustainable development, 
particularly in this milieu of global disaster risk reduction campaign (Partnership in 
Environmental Management for the Seas of East Asia (PEMSEA) 2003).  
However, today there is growing convergence of ideas that one should not think about 
social problem in oppositional or one-dimensional ways. Consequently, a fundamental 
prerequisite for effective engagement with new and old intractable development 
challenges is indeed a strong and determined integration involving the local, state, an 
autonomous and democratic civil society and a robust private sector committed to 
sustainable and equitable growth (Simone, 2002). The failure of state-only and market-
only approaches to urban management (disaster inclusive) acts as catalyst to ganger 
paradigm shift towards participatory management that will create ownership over 
decision-making and daily management practices. Participation is necessary to seek 
multiple perspectives of the various stakeholders, encourage involvement and action 
and resolve conflicts for the common and future good. Consequently, change cannot be 
effected without the full involvement of all stakeholders and adequate representation of 
their views and perspectives (Mulwanda, 1992; UN-Habitat 2002a). 
It is from this viewpoint that the global campaign on urban governance was launched 
in 1999 by UN-Habitat to support the implementation of the Agenda of sustainable 
human settlement development in an urbanizing world. As noted by UN-Habitat 
(2001a and 2002b), the campaign comprises the mechanism, processes, and 
institutions (whether formal or informal) through which citizens and groups articulate 
their interests, exercise their rights, meet their obligations, and mediate their 
differences. In operational terms, the campaign is a capacity building programme in 
self-governance. Thus the campaign envisions the inclusive city as a place where 
everyone, including the urban poor, and among them, women, can contribute 
productively, enjoy the benefits of urban life (UN-Habitat, 2002b) and cohabit in a 
harmonious manner. According to Tibaijuka (2006), the campaign on good urban 
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governance is that inclusiveness is not only socially just, but is good for growth and 
central to sustainable development. 
The Global Campaign signals a new and strategic approach for achieving the goals of 
the Istanbul Declaration and the Habitat agenda. Thus, the campaign is designed to 
promote accountability and transparent urban governance, which responds to and 
benefits all sectors of society, particularly the urban minority and strives to eradicate 
all form of exclusion. Its goal is to improve the quality of life in cities, especially for 
the marginalized, through improved local governance. The strategy for achieving this 
is to advocate the norms of good urban governance and promote inclusive decision-
making process especially in disaster situations (Taylor, 2000; Davis, 2004). 
In view of this, Habitat understanding of good governance is based on operational 
experience and the Habitat Agenda. The operational experience, therefore, suggests the 
emergence of a new approach to urban governance based on the shift from direct 
provision of goods and services by government to an enabling approach. Habitat II 
embraces this approach as the best available strategy for achieving sustainable human 
settlements through the efficient management of disasters. It is characterized by three 
strategies, namely, decentralizing responsibilities and resources to local authorities; 
encouraging the participation of civil society; and using partnership to achieve 
common objectives (Taylor, 2000). 
Bad governance could be seen as an additional burden borne by the minority in the 
society. Increasingly, therefore, the impact of governance is acknowledge as critical 
for unleashing national energies to reduce vulnerability to disaster. Therefore, unlike 
bad governance, good urban governance is expected to emphasize government 
involvement in disaster management, thus transparency, accountability, full 
participation and proactive responsiveness in vulnerability analysis are given laudable 
attention. The central argument is that unbridled competitions for power, and the 
failure of government to deliver democratic dividends, have resulted in compounding 
the vulnerability profile of the urban centres in Nigeria. Good governance, especially 
accountability, transparency and equity, would restore governmental legitimacy, 
harmony and promote national development (Kistner, 2007). 
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The concept of governance is complex and controversial, thus, different people and 
organizations define “good governance” according to their experience and interests. 
The theme of the Campaign for Good Urban Governance is the “inclusive city” since 
inclusive decision-making is at the heart of good urban governance. Exclusion as a 
result of physical, social or economic conditions, or because some individuals are not 
politically recognised or due to break-down of trust in government and politics 
prevents certain groups of people from participating in city life and activities. The 
failure of cities to integrate excluded groups into their decision-making process is, 
most often than not, a function of inertia, and bureaucratic and unresponsive forms of 
government (Nwaka 2005; Pieterse 2000).  
Based on major international legal instruments, on commitments made by 
Governments at major United Nations conferences, and on Habitat‟s and its partner‟s 
experience in urban development work, a set of norms of good urban governance has 
been proposed by the campaign. The normative goals according to Rakodi (1999), 
Pieterse (2000) and UN-Habitat (2002b), include the followings: sustainability in all 
dimensions of urban development; subsidiarity of authority and resources at the lowest 
appropriate level; equity of access to decision-making processes and the basic 
necessities of urban life; efficiency in the delivery of public services and in promoting 
local economic development; transparency and accountability of decision-makers and 
all stakeholders; civic engagement and citizenship to promote active contribution of 
urban citizens to the common goods; and security of individuals and their living 
environment. The campaign encourages central and local governments to strive for 
policy and institutional change to support inclusive sustainable development. 
According to Pieterse (2000) and UN-Habitat (2002), the underpinning strength of 
good urban governance is about promoting innovation in urban management to ensure 
that appropriate and sustainable policy options are developed collectively by local 
actors. In particular, it promotes the role of municipal governments in finding solutions 
to the ever-growing problems that converge in the third world cities as the world 
gradually and predominantly becomes urban. Therefore, urban governance to address 
disaster vulnerability should be hinged on integrated development approach that brings 
together sustainability, equitable economic development, responsiveness transparency, 
political voice, social justice and cultural freedom (Pieterse, 2000). However, lack of 
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guarantee for the stated indices predisposed the urban centres to increasing risk and 
vulnerability to disaster.  
2.4 Vulnerability concept 
To individuals committed to environmental issues, the evolving evidence of 
environmental degradation is real. Environment and development are two inseparable 
features of any country.  They both interact and are intertwined. Unfortunately, the fast 
development and progress that accompanied the industrial/technical evolution of the 
modern era have changed all these (Ayoade, 1997; Osuntokun, 1997; Awake, 2005; 
Adetunji, 2006; Ceylan et al, 2007; The Punch Newspaper, 2007). The changes were 
further compounded by the human vulnerability and exposure to disasters. 
Vulnerability is the degree to which a system or unit is likely to experience harm due 
to exposure to hazard or stress (Pelling, 2003 and Wisner 2001a). The concept of 
vulnerability originated in research communities to examine risks and hazards, climate 
impacts and resilience. The concept emerged from the recognition by research 
communities that focus on hazard alone (environmental, socio-economic, 
technological) was insufficient for understanding the responses of, and impacts on, 
systems (social groups, ecosystems, places) exposed to such hazard (Mitchell, 1999 
and Pine 2003).With vulnerability concept, it became clear that the ability of a system 
to attenuate stress or cope with the consequences through various strategies or 
mechanisms constituted a key determinant of system response and, ultimately, of 
system impact. A clearer understanding of coping strategies or mechanisms can, thus, 
throw light on who and what are at risk from what, and how specific stresses and 
perturbations evolve into risks and impacts (Turner, et al 2003; Wisner 2001b; Pine 
2003).   
Also, since the 1970s, but with increasing emphasis in the 1980s and 1990s, 
researchers from the social sciences and humanities have argued that the impact of a 
natural hazard depends not only on the physical resistance of a structure, but on the 
capacity of people to absorb the impact and recover from loss or damage. The focus of 
attention moved to social and economic vulnerability, with mounting evidence that 
natural hazards had widely varying impacts on different social groups and on different 
countries. The causal factors of disaster thus shifted from the natural event towards 
developmental processes that generate different levels of vulnerability (Ojo, 2013). 
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Vulnerability reduction began to be advanced as a key strategy for reducing disaster 
impact in the 1990s. Though this proved elusive to implement, however, by the end of 
the 1990s, it was clear that development processes were not only generating different 
patterns of vulnerability, but were also altering and magnifying patterns of hazard - an 
argument that has gained increasing currency as evidence mounts coupled with the 
impact of global climate change. Vulnerability assessment through risk management 
and reduction has been advanced as an integral disaster management paradigm that 
builds on and incorporates all the previous strategies from the perspective that all 
development activities have the potential to increase or reduce risks (UNDP, 2004). 
There are a number of factors that contribute to the configuration of vulnerability in 
cities. First, is history; where cities have been founded in or expanded into hazardous 
locations. Second, the urbanisation process and weak urban planning and development 
control framework that lead to the concentration of populations in hazard-prone cities, 
and hazard-prone locations within cities. For instance, when populations expand faster 
than the capacity of urban authorities or the private sector to supply basic 
infrastructure, vulnerability in informal settlements can accumulate quickly. Third, in 
cities with transient or migrant populations, social and economic networks tend to be 
loose. Many people, especially minority or groups of low social status, can become 
socially excluded and politically marginalised, leading to lack of access to resources 
and increased vulnerability. The urban poor are often forced to make difficult decisions 
about risk. Hence, living in hazardous locations is sometimes desirable, provided it 
offers access to work in the city centre (UNDP, 2004). Urbanisation as noted by 
UNDP (2004) can also modify hazard patterns. Through process of urban expansion, 
cities transform their surrounding environment and generate new hazards. The 
urbanisation of watersheds can modify hydraulic regimes leading to increasing flood 
and biophysical hazards. 
As noted by Zebrowski (1997), one object does not influence a second unless the 
second also influences the first. Disasters occur when societies or communities are 
exposed to potentially hazardous events, such as extremes of rainfall (rainfall too much 
or too little), temperature or wind speed or tectonic movements, and when people are 
unable to absorb the impact or recover from the hazardous impact. While it is 
commonplace to talk about natural disasters, both vulnerability and hazard are 
conditioned by human activities (Twigg, 1998). In relating the analogy above to this 
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research work, it can be seen, for example, in a swollen and over-stressed urban river 
that floods and devastates a growing city within its channels: humans will perceive the 
flood as the cause of the devastation. People are not inclined to question whether the 
presence of the devastated city may have influenced the river to overflow its bank 
through local deforestation, silting-up of the river channel by refuse and other 
materials or the building of structures on the flood plain of the river preventing it from 
dispersing into a natural flood plain (Ojo, 2001). 
Socially significant disasters do not put a major break on development. Rather, as 
noted by Lavell (1999), they are the logical response to underdevelopment. 
Underdevelopment, environmental unsustainability, and poverty are the major 
contributing factors to disasters vulnerability. Disasters do not in general throw the 
poor into a state of underdevelopment. They are already there prior to the disaster. Due 
to inherent vulnerability, disaster can project the poor from a state of poverty into a 
state of absolute destitution. This is not a problem of the disaster as such; it is a 
problem of where they were prior to the disaster. For instance, when a community is 
on the edge, at the limit, with water nearly inundating it, then any perturbing agent will 
throw the community over and submerge it.  
2.5 Traditional – expanded disaster management concept 
The period 1990 -1999, which the UN general Assembly declared as the International 
Decade for Natural Disaster Reduction (IDNDR), led to a greater awareness of the 
social and economic consequences of natural disasters. Since the world conference in 
Yokohama in May 1994, there has been a conscious paradigm shift towards 
preparedness rather than focusing only on rescue and relief (International Strategy for 
Disaster Reduction (ISDR), 2002).  
Disaster Management today has assumed more holistic dimensions. ISDR uses the 
following formula to determine the impact of disaster: risk is given as the product of 
hazards and the vulnerability of the community over the capacity of the community to 
cope with the disaster (Risk (R) equals to Hazard (H) multiply by Vulnerability (V) 
divided by Capacity (C) (R = H   V   C). In simple terms, this means that the risk of 
a disaster happening depends on: what the hazard is; how vulnerable the community is; 
and how well the community can limit the damage by being prepared and forewarned. 
The risk of a disaster occurring is based on physical, economic and environmental 
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factors which need to be monitored and evaluated continuously. Hence, disaster risk 
reduction involves four phases of activities, these are: Risk Assessment and Analysis; 
developing an Awareness of risk; Developing Early Warning Systems; and Disaster 
Management (ISDR, 2004) 
Thus, issues related to disasters should be properly ingrained into development and 
planning process as sustainable and long-term strategy. The disaster management cycle 
concept aims to reduce, or avoid the potential losses from hazards, assure prompt and 
appropriate assistance to victims of disaster, and achieve rapid and effective recovery. 
The cycle illustrates the on-going process by which governments, businesses, and civil 
society plan for and reduce the impact of disasters, react during and immediately 
following a disaster, and take steps to recover after a disaster has occurred. Appropriate 
actions at all points in the cycle lead to prevention of disasters, reduced vulnerability, 
better warnings and greater preparedness. The complete disaster management cycle 
includes the shaping of public policies and plans that either modify the causes of 
disasters or mitigate their effects on people, property, and infrastructure (Warfield, 
2005).  
The Disaster Management Cycle (DMC) highlights the range of initiatives which 
normally occur before disaster and during both the Emergency Response and Recovery 
Stages of a disaster. Some of the procedure of DMC cut across stages (such things as 
Coordination, Collaboration and the Provision of Ongoing Assistance), whilst other 
activities are unique to each stage, for example, Evacuation during Emergency 
Response; Reconstruction and Economic and Social Recovery as part of Recovery. The 
DMC also highlights the role of the media, and there should be a strong relationship 
between DMC and funding opportunities. Not unnaturally, the relationship between 
media and funding opportunities is highest during Emergency Response Stage, and 
tends to tail off during the later Recovery period. The challenge for all stakeholders 
today is how media and, to a larger extent, funding opportunities can take a greater 
interest in the earlier Disaster Risk Reduction Stage (Piper, 2006). 
The disaster management cycle is in phases, thus, the prevention, mitigation and 
preparedness phases occur as disaster management improvements are made in 
anticipation of a disaster event. Developmental considerations play a key role in 
contributing to prevention, mitigation and preparedness of a community to effectively 
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confront a disaster. As disaster occurs, disaster management actors, in particular 
humanitarian organisations become involved in the immediate response and by 
extension long-term recovery phases. The disaster management cycle is conventionally 
written as: Prevention > Mitigation > Preparedness > Response > Recovery > 
Prevention (abbreviated PMPRR), and ideally it is cumulative.  That is, each phase 
teaches lessons, reveals weaknesses, and provides an opportunity for improving and 
strengthening the DMC (Twigg, 1998; Wisner, 2001b). 
Some practitioners, over time developed the expanded version of DMC. To this school 
of thought, disaster management should be seen as ongoing process where phases in 
the cycle should be done simultaneously. In other words, one phase of the cycle does 
not necessarily have to be completed in order for the next to take place. Often several 
phases are taking place concurrently. Timely decision making during each phase 
results in greater preparedness, better warnings, reduced vulnerability and/or the 
prevention of future disasters. This model is not static and activation of a phase should 
not be dependent on disaster occurrence. The school posited that when disaster occurs 
what is expected from a DMC is an expansion and concentration of activities within 
the relevant phase to adequate manages the disaster.  The expansion model has moved 
away from using a diagrammatic representation of the Disaster Management Cycle 
(DMC), and particularly the earlier model which was more of a circle.  
Over time, most countries‟ economies show steady improvements, as measured, for 
example, by the Human Development Index (HDI), such countries are said to be in a 
disaster free state. During this period, ideally, a range of risk reduction mainstreaming 
initiatives should be introduced, which, when combined with other key mainstreaming 
parameters, particularly community participation, poverty reduction, good governance, 
and environmental sustainability, will result in safer communities. However, 
occasional severe hazards may still affect communities, which can turn into potential 
disasters when they overwhelm the resources of the affected population. In this period, 
a so called disaster may occur, which will normally trigger a range of emergency 
response initiatives. With time, the community will begin to recover, and move from 
an emergency response stage to that of Recovery (Australian Development Gateway, 
2007). 
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2.6     Literature review 
Various studies have been undertaken on human vulnerability to natural and man-
induced disasters, ranging from the study on a specific type of disaster to vulnerability 
study of a given region. However, this study focuses on the nexus between urban 
dynamics and vulnerability to disaster. In this regards the following components of 
vulnerability to disaster and urban interactions were reviewed: nature, type and 
characteristics of disaster; urban dynamics and vulnerability to disasters; causes and 
effects of disasters; remedial measure to manage disasters; development attributes of 
disasters; methodological issues in disaster management; application of urban 
dynamics model to urban management and flood risk assessment and mapping 
2.6.1 Nature, type and characteristics of disasters  
Our psychological profiles as human draw us to disaster; some as volunteers, relief 
workers, others as public servants or engineers whose vision is to prevent future 
catastrophes, and many as intellectually curious onlookers. Millions of people watch 
news telecasts of the latest natural and man-induced disaster with an uneasy 
combination of awe and the personal sense of relief that they are not being counted 
among the affected persons. Disasters can be categorized into natural and man-induced 
or technological disaster. The natural disasters include floods, hurricanes, tornadoes, 
winter storms, landslides, earthquakes/tremors, volcanic eruptions, drought, 
desertification, wind and thunder storms, among others, while man-induced or 
technological disasters include plane crash, train wreck, road accident, ship mishap, 
fire and disease outbreaks, building collapse, industrial accident, hazardous material 
spills, land subsidence, civil disturbance which may include terrorism, riot, shooting, 
bombing and war (Kasim, 2004; National Emergency Management Agency 2011a). 
According to Twigg (2001), there is no natural disaster, but there are natural hazards, 
such as earthquakes and cyclones. The difference between a hazard and a disaster is an 
important one. A disaster takes place when a community is affected by a hazard that is 
usually defined as an event that overwhelms a community‟s capacity to cope without 
calling for external help. Thus, the impact of disaster is determined by the extent of a 
community‟s vulnerability to the hazard (McEntire, 2005). Therefore, a disaster is 
more or less rapid, often unexpected destructive event that occurs in a particular 
natural and human context and in a definable territory causing death and injuries as 
well as extensive damage to property and distracting the social structures of the 
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affected persons. Consequently, the upheavals in the life of the masses is so great that 
the social structure loses its functioning capacity and there is urgent need for special 
organization and mobilization of the social services as manifested in the World Trade 
Centre (WTC) terrorist attack of September 11, 2001, Ikeja (Lagos) Cantonment bomb 
explosion of January 27, 2002, India Ocean Tsunamis in 2004, hurricane Katrina in 
2005, earthquake in Haiti in 2010 and 2011 Tsunami in Japan (New York State Office 
of Mental Health, 2001; Agekameh, 2002; Dolfman, et al 2007; Oxfam International 
2010; Nanto, et al 2011) 
Between 1971 and 1995, disasters caused each year, on average, more than 128,000 
deaths and affected the lives of 136 million people (Canadian Red Cross, 2006). Every 
country is affected by natural hazards to some extent. However, most disasters occur in 
the poorer countries of the Third World: some 97 % of deaths and 99 % of people 
affected between 1971 and 1995 were in developing countries. The economic 
consequences of disasters in developing countries can be massive. From 1995 to 2004, 
5,989 reported disasters killed 901,177 people and affected over 2.5 billion people, 
causing at least US$ 738 billion in estimated damage. This compares to 643,418 
reported killed and 1.74 billion reported affected by disasters from 1985 to 1994. In 
December 2004, 250,000 were reported killed by disasters – mostly from the Indian 
Ocean Tsunami. Disasters affected 146 million people (mainly due to floods in 
Bangladesh, Malaysia, Indonesia, India and China) and inflicted estimated damage of 
US$ 100-145 billion (Twigg, 1998; Canadian Red Cross, 2006). 
Year 2006 was observed by Hoyois et al (2007), to be a return to a kind of „normality‟ 
after the major events of the last few years. Even though the disasters in 2006 have not 
captured as much attention as those of the recent past, it is important to remember that 
they have had devastating impacts. In 2006, there were 427 reported natural disasters 
that killed more than 23,000 people, affected almost 143 million others, and cost up to 
S $ 34.5 billion in economic damages. The 2006 data shows that Asia remains the 
continent most hit by disasters with over 44 % of all reported disasters occurring in the 
region. In addition, the 2006 numbers was an indication that it is not only developing 
countries that are severely affected by disasters. Four European countries - France, the 
Netherlands, Belgium and the Ukraine - rank among the top 10 countries affected by 
deadly disasters (Hoyois et al 2007; Ojo 2013). 
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Prior to the 1970‟s, Hewitt (1983) noted that disasters were viewed purely as natural 
phenomenon. A departure from this postulation came to light in the late 1970‟s. The 
new postulation was an attempt to take the notion of naturalness out of natural disaster. 
As opined by McCall (1992), the line between natural and man-induced disaster is 
finely drawn and may be blurred. Therefore, disaster cannot be explained only in terms 
of its naturalness; some other variables like human interaction with their physical 
environment are also important. The contemporary assumed paradigm shift from the 
notion of disaster naturalness to comprehensive outlook of the relationship between 
natural and man-induced disaster has not fully taken its root. 
A disaster is a natural or man-induced / technological event of severity and magnitude 
that normally results in death, injury and property damage that cannot be managed 
through the routine procedures and resources of individual, community and Local 
Government. It requires immediate coordinated and effective response by multiple 
governments and private sector organisations to meet the medical, logistical and 
emotional needs and to speed recovery of the affected population. As noted by the 
New York State Office of Mental Health (2001), disasters differ from routine 
emergencies and cause unique problem for private-public organisation as well as the 
Local, State and Federal Government affected. Routine emergencies and critical 
incidents are events to which response demands can be met with local resources. 
Disasters, compared to routine emergencies and critical incidents, possess unique 
characteristics. The followings are characteristics of disaster as developed by the 
United States of America‟s Federal Emergency Management Agency (FEMA). 
i. Create demands that exceed the normal capacities of any one organisation 
and/or government. 
ii. Cross jurisdictional boundaries 
iii. Change the number and structures of responding organisation, which may 
result in the creation of new organisations. 
iv. Create new tasks and engage participants who are not ordinarily disaster 
responders. 
v. Disable the routine equipment and facilities needed for emergency response. 
vi. Compound the difficulty of understanding who does what in disaster response 
due to the complexity of government. 
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vii. Impacted by lack of standardisation in disaster planning and response and 
complicated coordination. 
The emerging characteristics of disasters indicate that there is ample justification for 
the promotion of interventions that involve the participation of the general populace in 
the difficult task of determining causes of disasters and in solving the various problems 
posed by its occurrence (Thompson, 1995). The relationship between human actions, 
environmental stewardship, climate change and disaster risks are becoming ever more 
crucial. Disasters not only affect the poor and characteristically more vulnerable 
countries but also countries thought to be well protected. In recent years, Canada, 
Czech Republic, France, Japan, Poland, Germany, United Kingdom, United States of 
America Australia and New Zealand experienced record-setting floods of such 
magnitude that previous accepted procedure for protection and the utility of structural 
barriers have had to be re-evaluated (ISDR, 2002; Awake, 2005; 2007; Chanson, 
2011). 
2.6.2 Urban dynamics and vulnerability to disasters 
Vulnerability is a multi-dimensional concept that comprises physical, social, 
economic, environmental, political, cultural and institutional factors. The perception of 
hazards, disaster, urbanisation and vulnerability is increasing both in the developing 
and developed countries of the world. However, as noted by Olatubara (2007), the 
challenge of urbanisation is more of its rate than the level in the developing countries. 
Thus, rapid rate of urbanisation, particularly the growth of large cities, and the 
problems of unemployment, poverty, inadequate health care facilities, poor sanitation 
and water provision, burgeoning slum and squalor and environmental degradation pose 
formidable challenge and render the living environment precarious and vulnerable to 
disasters in many developing countries.  
The additional billion people added to world population in every 12 to 13 years are 
mortally taxing the earth and its resources. Each individual person has a unique impact 
on the planet‟s environment and no living individual is without an ecological footprint 
(Population Media Centre 2009). Available statistics show that more than half of the 
world‟s 7 billion people live in urban area, crowded into 3 % of the earth‟s land area. 
The proportion of the world‟s population living in urban areas which was less than 5 % 
in 1800 increased to 47 % in 2000 and it is expected to reach 65 % in 2030 (United 
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Nations, 1990; Population Reference Bureau, 2005; UNFPA 2011). From this global 
view, however, more than 90 % of the future population growth will be concentrated in 
developing countries‟ cities and a large percentage of this population will be poor 
living in marginal land vulnerable to disasters (Drakakis-Smith, 2000; UN-Habitat 
2007). 
As a result of unprecedented word population growth, the earth is attempting to impose 
its own natural checks on human population. These checks are witnessed in the form of 
widespread disasters and the emergence of new disease strains, food and water 
shortages, poor harvests, , violent and destructive weather caused by climate change 
and climate variability (Population Media Centre, 2009).   Urban growth does not 
explain human vulnerability to disasters per se rather it is particular processes and 
factors of urban change that characterise rapidly urbanising countries that increase 
human vulnerability to disasters. These processes and factors will vary considerably 
from context to context (Quarantelli, 2005). 
For instance, as noted by Ravallion (2001), the rapid growth of urban areas in the 
developing world in the next few decades poses a huge challenge to the fight against 
poverty. The problem of cities are of staggering proportions a significant increase in 
urban poverty, disproportionately affecting women and children, ethnic and racial 
conflicts, crime, homelessness and environment degradation with far-reaching political 
as well as socio-economic implications (Makoka and Kaplan, 2005). To achieve 
successful sustainable development, urban poor must be the business of everyone. 
Cities with growing economic have the possibility, as least, of improving the condition 
of poor inhabitants. However, among the world‟s megacities with the highest rates of 
population growth are precariously poor cities with sluggish economies, such as Cairo, 
Calcutta, Dhaka, Kinshasa, Kano, Ibadan and Lagos. For these cities the risk of further 
deterioration is obvious and continuous (Sharma et al, 2000).    
2.6.3 Causes and effects of disasters  
Globally, disasters are two-edged. On one edge is the natural and man-induced mishap 
or the trigger mechanism which could be flooding, erosion, earthquake, tremor, 
thunder/windstorm, landslide, land subsidence, technological disasters, among others 
while on the other edge, the receiving end, are the damages done to the built 
environment, the injuries and losses of human life and property. It is apt to note that in 
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most disaster vulnerable environments; most victims are the destitute segment of the 
population. They tend to live in disaster prone areas, which are the least expensive, and 
thus the only residential sites affordable to them. Therefore, vulnerability strongly 
correlates with the extent of a society‟s development. In extreme cases, this correlation 
proves one of the vicious circle of perpetual under-development that renders a society 
more vulnerable to hazards and once hit by a disaster; the society suffers severe 
setbacks to degenerate further into under-development, (Norimichi et al, 1991; Hanley, 
2006) 
Although all countries may be confronted with anthropogenic and natural hazards, the 
poorer developing countries, in particular, are disproportionately vulnerable to those 
hazards turning into disasters (Herrmann et al, 2004). In a nutshell, as noted by 
Martine and Guzman (1999), poverty is a central component of vulnerability. For 
instance, the relation between socio-economic conditions and the impact of 
anthropogenic and natural disasters can be expressed using economic constraints. In 
other words, the poor are forced to live in precarious homes; made of flimsy, non-
durable materials and on the least-valued plots of land. Shacks are built on steep 
hillsides, on floodplains in fragile ecosystems and watersheds, on contaminated land, 
right of ways, squat on the deadly shadows of refineries, chemical factories toxic 
dumps and other inappropriate areas (Davis, 2004). The inappropriateness of these 
locations, evidently, invites serious social and environmental problems while, 
deforestation, as well as inadequate management of rainwater and waste, coupled with 
climate change further aggravate the conditions (van Western and Hosfstee, 2000; 
Agbola, 2011).  
Disasters seek out the poor and ensure they stay poor (Cherpitel, 2002). They are often 
the most exposed to disasters and with the lowest capacity to cope. Inversely, where 
the rich may be exposed to disaster through locational choices: flood plains, hill tops, 
ocean fronts; they have adequate capacity to cope with associated disaster impacts 
(International Federation of Red Cross and Red Crescent Societies [IFRCRCS], 2002). 
In general, the drama of disaster and the urgent international activity to provide 
emergency relief commands the attention of the international media for only a few 
days (NEMA, 2012a). However, the consequences of disasters last much longer and 
are more poignantly measured in isolation. These losses impede human development 
and often erode previously hard-won individual and national accomplishment. Disaster 
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also compromise current and future resources upon which societies and future 
generations depend (Jabeen et al, 2011). 
Disasters continue to target the world‟s poorest and least developed; of those killed in 
2002; just 6 % lived in countries of High Human Development (HHD) while countries 
of Low Human Development (LHD) reported the fewest disasters, and their death toll 
is by far the highest (Centre for Research on the Epidemiology of Disaster [CRED], 
2003). When related to the numbers of reported disasters, an average of 555 people 
died per disaster in LHD nations compared to 133 in countries of Medium Human 
Development (MHD) and 18 people in HHD nations (CRED, 2003). While deaths 
remain low from disaster in highly developed countries; financial costs are very high. 
Among the globally reported disaster damage in 2001, (27 billion dollar) more than 
two thirds occurred in HHD countries and LHD countries reported just 0.15 % of total 
damages. Over the course of the decade, the average costs of damage from each 
natural disaster were 477, 149 and 61 million dollar in HHD, MHD and LHD 
respectively. The high financial value attached to infrastructure in developed countries 
(HHD) is the main reason for these differences. The enormous financial losses related 
to infrastructure in developing countries (LHD) will be better revealed by a 
comparison based on losses to gross domestic product (GDP) rather than losses 
expressed in dollar (CRED, 2003). 
The Munich Reinsurance Company, as quoted by IFRCRCS (2002), gave the top three 
casualty disasters since 1970 to 2000 as follows:1970: Storm and floods in 
Bangladesh: 300,000 victims; 1976: Earthquake in China: 250,000 victims; 1991: 
Tropical cyclone in Bangladesh:138,000 victims. While the three most costly disasters 
in terms of insured losses since 1970 to 2000 were: 1992: Hurricane Andres in the 
USA: 20 billion dollar; 1994: Northridge earthquake in the USA: 17 billion dollar; 
1991: Typhoon Mireille in Japan: 7.5 billion dollar.A cursory look at Table 2.1 shows 
that in 2006, Asia remains the most affected region with China having more than 8.8 
million reported victims, the Philippines had 8.6 million victims and India accounted 
for 7.3 million. However, in terms of the proportion of the total population, the most 
affected continent was Africa. The most affected country was the Malawi with 38.8 % 
of the total population affected mainly with drought followed by Djibouti, 30.8 % and 
Burundi with 26.8 % (Hoyois et al, 2007).   
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Table 2.1 Top 10 countries by persons affected by disaster in 2006 
Countries  No of victims Countries % of the total 
population  
China P. Republic 8,873,953 Malawi 38.8 
Philippines 8,615,801 Djibouti 30.8 
India 7,385,999 Burundi 26.8 
Malawi 5,160,508 Niger 24.3 
Kenya 4,283,526 Kenya 11.9 
Indonesia 3,952,616 Philippines 9.6 
Viet Nam 3,349,989 Mali 8.8 
Thailand 3,257,588 Afghanistan 7.2 
Niger 3,046,476 Mozambique 7.0 
Afghanistan 2,234,292 China P. Republic 6.8 
Source: Hoyois et al, (2007) p 34  
  
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Table 2.2 Top 10 countries affected by natural disasters and number of deaths in 
2012 
Events  Country  Number of death 
Tropical Cyclone (Bopha) December  Philippines  1901 
Flood, August – October Pakistan 480 
Flood, July – October Nigeria  363 
Earthquake, August Iran Islam Republic 306 
Cold Wave, June Peru  252 
Cold Wave, December India  249 
Flood, July Russia  172 
Cold Wave, December Russia  170 
Flood, July China  151 
Avalanche, April Pakistan  135 
Total     4179 
Source: Guha-Sapir et al, (2013). 
  
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Table 2.3 Top 10 countries affected by natural disasters and impacts on persons 
in 2012 
Events  Country  Persons affected (million) 
Flood, June China  17.4 
Flood, April China  13.1 
Flood, July – October Nigeria  7.0 
Tropical Cyclone (Bopha) December  Philippines  6.2 
Tropical Cyclone (Haikui) August  China  6.0 
Flood, June Bangladesh 5.1 
Flood, August – October Pakistan  5.0 
Flood, August Philippines  4.5 
Tropical Cyclone (Damrey) August China 3.8 
Drought  Kenya  3.8 
Total  72.000 
Source: Guha-Sapir et al (2013). 
 
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According to Guha-Sapir et al (2013), the Americas suffered the most damages in 
2012 (65.7% of worldwide natural disaster damages), followed by Asia (17.8%) and 
Europe (15.4%). A share of 0.6% of global disaster damages was reported for Africa 
and of 0.5% for Oceania. This distribution of disaster damages between continents is 
different from the one observed over the last decade, where Asia had the most 
damages, followed by the Americas and Europe. Damages in the Americas increased 
from an annual average of US$ 56.5 billion from 2002-2011 to US$ 103.4 billion in 
2012, mostly due to two disasters which occurred in the U.S.A: hurricane Sandy and 
the drought in the South-Western and Mid-West regions. However, damages in Europe 
also increased from an annual average of US$ 13.5 billion during 2002-2011 to US$ 
24.2 billion in 2011. On the other side, in 2012 compared to the annual average for 
2002-2011, damages decreased by 83% in Oceania, by 58% in Asia and by 21% in 
Africa.   
The distribution of disaster frequency in Africa in 2012 presented a similar profile to 
the one seen over the last decade. Hydrological disasters represented 52.6% of 
occurrence, followed by climatological (28.1%) and meteorological disasters (19.3%). 
No geophysical disasters were recorded in 2012.  However, the number of victims 
increased in 2012 by 43.4% compared to the annual average number of disaster 
victims in Africa during 2002-2011, due to the impact of climatological and 
hydrological disasters. The number of reported climatological disaster victims in 2012 
(28 million) surpassed their 2002-2011 annual average (23.9 million) and the number 
of reported hydrological disaster victims (9.3 million) was far above their 2002-
2011annual average (2.1million). Droughts and food crises made one million victims 
or more in Angola, Burkina Faso, Chad, Ethiopia, Kenya, Malawi, Mali, Niger, Sudan, 
Tanzania and Zimbabwe caused 25.3 million victims, with one flood in Nigeria 
causing 7 million alone. These twelve disasters represent 85% of the total of victims in 
Africa in 2012 (Guha-Sapir et al, 2013). 
The estimation of natural disaster damages in Africa remains extremely challenging as 
data are often poorly reported or lacking altogether. In 2012, like in previous years, no 
damages for climatological disasters in Africa were reported. Reported damages from 
hydrological disasters (US$ 0.83 billion) increased in 2012compared to their annual 
average reported damages during2002to 2011(US$ 0.3 billion) and reported damages 
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from meteorological disasters (US$ 0.1 billion) surpassed also their 2002-2012 
average (0.07 billion) (Guha-Sapir et al, 2013). 
  
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Table 2.4 Top 10 countries affected by natural disasters and economic damages in 
2012 
Events  Country  Damages (US$ bn.) 
Tropical Cyclone (Sandy), October United States 50.0 
Drought, June United States 20.0 
Earthquakes, May Italy  15.8 
Flood, July China 8.0 
Tornado, March United States 5.0 
Severe Storm, April United States 4.5 
Severe Storm, June United States 4.0 
Thunderstorm, May United States 3.4 
Flood, April China  2.5 
Flood, August Pakistan  2.5 
Total    115.7 
Source: Guha-Sapir et al (2013), 
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In August 2005, hurricane Katrina hit New Orleans, the hurricane destroyed lives and 
floodwalls in the river area, causing 80 % of the predominantly black community to be 
flooded (Dyson, 2006). Some parts were more than six metres under water. More than 
80 % of the residents were evacuated, and housed in Louisiana super dome. The 
official death toll was set on 1577 while economic and political damage lasted well 
into 2006 (Enzlar, 2006; Hoyois et al, 2007). Therefore, potentially negative 
consequences for social development do not stop with direct impact. In the aftermath 
of a disaster or during the escalation of a slow-onset disaster such as drought, flood or 
complex political emergency, aid budgets can be skewed towards the recovery of one 
group or sector as opposed to another.  The result is a reduction in social equality. 
Consequently, studies have shown that lower income people are more vulnerable to 
disaster threats than those with greater economic resources. Thus, effects of disasters 
are non-random because vulnerability of harm and damage is patterned by inequality.   
2.6.4 Remedial measures to mitigate disasters. 
Disaster Management is the coordination and integration of all activities necessary to 
build, sustain and improve the capability to prepare for, protect against, respond to and 
recover from threatening or actual natural or human-induced disasters. It is a multi-
jurisdictional, multi-sectoral, multi-disciplinary and multi-resource initiative. Disaster 
management is also the coordination and integration of all activities necessary to build, 
sustain and improve the capability for disaster prevention, mitigation, preparedness, 
response and recovery. (National Emergency Management Agency [NEMA], 2012b). 
More effective prevention strategies would save not only tens of billions of dollars, but 
save tens of thousands of lives. Funds currently spent on intervention and relief could 
be devoted to enhancing equitable and sustainable development instead, which would 
further reduce the risk for war and disaster. Building a culture of prevention is not 
easy. While the costs of prevention have to be paid in the present, its benefits lie in a 
distant future. Moreover, the benefits are not tangible; they are the disasters that did 
not happen (Annan, 1999). 
A major goal of emergency management is to minimize the adverse impact of a 
disaster on a business, community or large geographic area.  The efforts of many 
organizations to build a more sustainable community, business or country are 
consistent with emergency management goals of hazard mitigation (McGuire, 2000). 
In 1987, the United Nations World Commission on Environment and Development 
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coined the term sustainable development. It defined sustainable development as 
“meeting the needs of the present generation without compromising the ability of 
future generations to meet their own needs”. This means that harvesting natural 
resources and developing land, must be done in a manner that will allow other 
generations to have at least the same opportunities that currently exist (Aguirre, 2002; 
Pine, 2003). 
The significance of institutional framework in projecting into the future in disaster 
abatement is crucial. The Federal Government of Nigeria has established several 
ministries, agencies and parastatals for this purpose in addition to the existing disaster 
networks like non-governmental organisations, private concern and international 
bodies. In recent times, Nigeria, especially Lagos State, has been exposed to a wide 
range of human and natural hazard induced disasters. Some of these disasters include 
ethno-religious crisis, political turmoil and electoral violence, floods and drought, 
population movements (Internally Displaced Persons - IDPs - and refugees) and others 
(Ojo, 2013). In addition, some parts of the country face food insecurity and 
malnutrition while health epidemics such as Polio, Meningitis, Cholera and Lassa 
fever, are recurrent diseases that continue to affect the lives and livelihood of the 
populace. The multiple humanitarian challenges posed by these disasters could have 
far reaching impact on the entire country (NEMA, 2012a).  
Over the years, response to disaster in Lagos State and by extension, Nigeria has been 
unanticipated, unplanned and often poorly coordinated so much so that response could 
be as bad as the disaster and often compound the impact of disaster on persons affected 
(Ojo, 2013). Also, those impacted and affected by disaster are often treated as object of 
charity rather than subject and claimants of rights to whom it is accountable. They are 
treated as people who have committed crimes and who deserve to be punished and not 
assisted. Consequently and in order for the country to operate in an organized manner 
by coordinating the activities of all these networks for effective disaster management, 
there is an overarching need to have centralized disaster management agencies at the 
national and regional scales (NEMA, 2003) 
Disaster management being a multi-jurisdictional, multi-stake holding, multi-
disciplinary, multi-sectoral, multi- resource endeavour, requires elaborate policy, 
procedures, systems and guidelines to ensure seamless coordination and collaboration. 
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Disaster management is an enormous task. A disaster is not confined to any particular 
location; neither do they disappear as quickly as they appear (Annan, 1999). Therefore, 
it is imperative that there is proper management to optimize efficiency of planning and 
response. Due to limited resources, collaborative efforts at the governmental, private 
and community levels are necessary (ISDR, 2004)). This level of collaboration 
requires a coordinated and organized effort to prevent, mitigate, prepare for, respond 
to, and recover from emergencies and their effects in the shortest possible time (Kasim, 
2004; Warfield, 2005).  
NEMA, by its mandate, is to coordinate and integrate the activities and efforts of 
disaster management stakeholders and structures, and to complement their resources to 
avoid haphazardness, duplication and waste. In performing the mandate, NEMA is 
faced with several constraints by taking on the responsibilities of other first responder 
agencies who fail to lead in some critical disaster situations for lack of capacity to do 
so. Lessons learnt have highlighted the limited human and material resources available 
for disaster response among responder agencies and stakeholders. Consequently, the 
bulk of the tasks still fall back upon NEMA (NEMA, 2012a; b). However, in the 
process of doing this, as noted by Wahab (2013) and Abin and Wahab (2013), NEMA 
comes in conflict with SEMAs, due largely to turf protection, as highlighted in the 
frequent friction between NEMA and Lagos State Emergency Management Agency 
(LASEMA).  
For effective coordination of the activities of all agencies associated with disaster 
management in Nigeria, according to the National Emergency Management Agency 
(2003), the National Disaster Response Plan (NDRP) assigns a number of primary and 
secondary responsibilities to networks involve in disaster management as shown in 
Table 2.5. From the Table, in accordance with the provision of the Agency‟s 
establishment Act No. 12, 1999, the National Disaster Response Plan [NDRP] provides 
a focus for inter-agency and inter-governmental emergency preparedness, planning, 
training, exercising, coordination and information exchange by organizing the forms of 
federal response assistance that a community is most likely to require under the 13 
Support Service Areas [SSAs] (NEMA, 2003).  
The 13 Support Service Areas (SSAs) are as follows: 1 Transportation; 2 
Communication; 3 Public Works and Engineering; 4 Fire Fighting; 5 Information and 
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Planning; 6 Mass care; 7 Resource Support; 8 Health and Medical Services; 9 Search 
and Rescue; 10 Hazardous materials; 11 Food and water; 12 Energy; and 13 Military 
support. For effective implementation, every agency and organisation relevant to 
emergency management has been systematically divided to fit into a SSA where their 
expertise would be maximally utilized to allow for coordination, efficiency and speed. 
Due to inherent shortcomings of the NDRP document, NEMA in 2012 launched the 
National Emergency Management Framework to incorporate the critical stakeholders 
such as Town Planning Authority, the Community Development Organisation and the 
Private Sector left out in the NDRP 13 Support Service Areas.  
  
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Table 2.5 Assignment of disaster related responsibilities in Nigeria 
Organisation Primary Secondary 
responsibilities responsibilities 
NEMA 6,7.8.11 9,10 
Ministry of Transport 1 4,5,7,10,13 
Nigerian Immigration Service  1,13 
Nigerian Army 1,9,13 2,3,4,6,7,8,11 
Nigerian Air Force 1,9,13 2,3,4,7,8 
Nigerian Navy 1,9,13 2,3,4,7,8 
Nigeria Police 1,9,13 3,4,6,7,8 
Nigerian Ports Authority  1 
NSCDC (Civil Defense)  5,6,7,9,13 
Nigerian Maritime Authority 1  
Federal Road Safety Corps 9 1,4,8,13 
Nigerian Railway Corporation 10 1 
Ministry of Works and Housing 3 1,4,6 
Ministry of Health 6,8,11 1,3,4,5,9,10,13 
Federal Ministry of Environment 10 1,3,5,8 
Ministry of Agriculture 11 1,3,5,6,7,8,10 
Ministry of Communication 2  
Federal Radio Corporation of Nigeria  2 
Nigerian Telecommunications (NITEL)  2,3 
Nigerian Television Authority (NTA)  2 
Ministry of Aviation  2 
Federal Fire Service 4,9 3 
Nigerian Red Cross Society 6 3,4,5,8,10,11,13 
NEPA 12 3 
NAMA 4 9 
Ministry of Water Resources 11 3,4,6,10,11,12 
Ministry of Information 5  
Ministry of Education  5 
Ministry of Labour and Productivity  7 
NAFDAC  8,11 
FAAN  9 
NNPC, Oil Companies 10,12 1,4,8,9,12 
DPR 10  
Ministry of Power and Steel 12  
Construction Companies  1,3,4,9 
NGOs  8,11 
Nigeria Customs Service  13 
Source: NEMA (2003), National Disaster Response Plan  
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For any management method to be successful, it requires mass participation, which not 
only gives strength but also legitimacy and ownership to the project. Thus, when 
awareness and education about disasters are provided to people, disaster management 
becomes a simpler task. One of the causal factors of vulnerability of a population is 
lack of awareness and education about disasters. It is also the only factor, which can be 
tackled very easily and immediately. For example, according to Wisner (2001b), while 
poverty cannot be eliminated in a developing country like India, ungoverned 
population growth has been controlled to some extent through public education and 
awareness. Rapid urbanization and migration cannot be stopped at present which 
would take long years; transition in the cultural practices cannot be stopped that easily, 
which again is a slow process and to a greater extent depends on the people‟s mind-set. 
However, vulnerability to disaster can be addressed through functional public 
awareness and education. 
In view of the above, Thompson (1995), opined that in a given country, what is 
important in the efforts to reduce disaster is to prescribe an appropriate feasible 
package of measures that are not limited to conventional counter-disaster activities. 
Such a package, for instance, most likely includes a rural and urban development 
programme, with particular emphasis on watershed rehabilitation and literacy 
campaign measures not regarded usually as counter-disaster measure. There is, 
however, no universally applicable package of right action. Most often, the structure of 
disaster vulnerability is unique to each country and such a comprehensive package 
cannot be prescribed without thoroughly scrutinizing how and why the country in 
question is vulnerable. For example, following the extensive flooding that covered 
almost three-quarters of Bangladesh in 1987, the Bangladeshi officials launched a 
three year Flood Action Plan to study more than 25 different dimensions of flood 
prevention (World Bank, 2005). The resulting recommendation overwhelmingly 
suggested the need for much greater investment in “flood-proofing” the society by 
learning to live with the inevitable floods in a way that would minimize harm and loss, 
rather than trying to prevent the powerful forces of nature. Findings were ultimately 
guided by the fact that almost the entire country of Bangladesh is a highly fertile flood 
plain. It would neither exist, nor be as productive as it is without the annual floods 
continually renewing and extending its landscape (ISDR, 2002). 
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Preparedness and response to disaster as opined by Ijewere (2003), are not solely the 
work of expert and emergency responders from government disaster organisations. 
Local volunteers, citizens, organisations and businesses have an active and important 
role to play before, during and after major emergencies and disasters. Therefore, 
Community Based Disaster Preparedness (CBDP) that seeks to develop and implement 
a locally owned strategy for disaster risk reduction and preparedness is of paramount 
importance. The local population in disaster stricken areas is the first to respond to a 
disaster in terms of search and rescue as well as providing emergency treatment and 
relief for families, friends and neighbours (Wisner, 2001c). The management of 
disaster is primarily the prerogative and duty of governments. However, a multi-
sectoral and multi-disciplinary cooperation between government agencies, community 
based organisations, corporate bodies, non-governmental organisations and other 
networks in disaster abatement and management is a critical one (Wisner, 2001c; 
Frances and Hanlon, 2001).  
2.6.5 Developmental attributes of disaster 
Disasters constitute a development issue because they can make development risky and 
unsustainable while development processes can cause or reduce disaster risks. Losses 
from disasters negate some development gains and exacerbate poverty, partly because 
natural hazard vulnerability causes, exacerbates or is linked with other vulnerabilities 
and risks. Due to the inter-relationships between disaster risk and developmental 
attributes, effective disaster risk reduction strategies most strive to mainstream and 
ensure sustainable development (ISDR, 2006). 
It is noted by UNDP (2004), that development patterns that do not balance wealth 
creation, equity or environmental soundness are unsustainable and cause disaster risks, 
mainly through worsening underlying factors of vulnerability to hazards or 
contributing to conditions that cause or exacerbate environmental degradation. In 
contrast, sustainable development strengthens the security of populations, hence, 
disaster reduction interventions can effectively help to alleviate or avoid disaster risks 
to the community‟s livelihoods, the supporting physical, economic and social base. 
This mutually beneficial relationship between reducing disaster risks and ensuring 
sustainable development occurs when disaster losses are addressed in a development 
context and development processes and patterns adequately address threats from 
disasters and other livelihood risks (ISDR, 2006). 
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Although a number of studies had been published previously on the theme of disasters 
and social change but the first systematized and comprehensive series of ideas on the 
ways disasters may interrupt development processes, whilst, at the same time, offering 
opportunities for future development was developed by Fred Cuny in 1983. As noted 
in the work, the recovery process could serve as opportunity to build disaster risk 
reduction mechanisms into post-disaster development planning. Disaster-development 
relationships should be reconsidered as development priorities are thought through. 
Importantly, it is not just local actors, but national and international actors who should 
be involved in these reflections. Disruptions caused by disasters create avenue to open 
up political space for alternative forms of social networking that enhance egalitarian 
forms of organization to develop. Support for such organisations could be a way in 
which new development priorities are carried forward beyond the immediate response 
and recovery periods (Cuny, 1983). 
Integrating the results of society‟s responses and reconstruction activities into post 
disaster interventions clearly indicate that disasters are problems for development. 
However the results of numerous studies carried out in regions affected by disaster 
show that in many cases there are marked development gains in the medium and long 
terms (Smith, 2004). This should not be surprising taking into account the argument 
that disasters can be opportunities for development. New investment, improved quality 
of housing, infrastructure and production, and overall gains in risk reduction can be 
expected to occur where the reconstruction process is adequately conceived. Moreover, 
it has also been documented in various areas affected by disaster that new investment 
has greatly exceeded calculated disaster losses and reconstruction needs as stipulated 
in post disaster assessments (Lavell, 1999).  
Disasters are popular events and responses may be driven by social, economic, 
political or ethical reasons. The response could lead to significant positive changes in 
the local or regional economy and society. In an unintentionally cynical way of 
looking at the disaster – development spectrum is that disasters could be seen as abrupt 
writings off of redundant, depreciated capital. However, the argument that disasters 
may lead to greater development, at least in the affected regions, is not an argument for 
letting them happen. It is just a statement on the nature of the process. Crisis provides 
opportunity. Disasters reveal distinct aspects of underdevelopment, expressed through 
the presence of vulnerability. Given this it is not surprising that what happens after 
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disaster may, many times, be better than what existed before. The contradiction is, of 
course, that many regions and population groups have to await a disaster in order to 
have any opportunity to gain a minimal access to development resources (Lavell, 
1999). 
2.6.6 Methodological issues in disaster management 
The purpose of research is to discover, amend or change laws and theories. Research is 
used to define a cause-effect relationship between independent and dependent 
variables. Until recently, reports of disaster responses have been primarily anecdotal 
and descriptive with little or no structure (Wisner et al, 2003). Experimental studies are 
either impossible to conduct in a setting of disaster or are considered unethical (ISDR, 
2002; Quarantelli, 2005). However, during the last two decades, methodologies used in 
the social studies have contributed greatly to the understanding of disaster and the 
effects of specific interventions on the affected populations or populations at risk from 
an event. By seeking to understand and to anticipate future hazards by studying the 
past and monitoring the present situations, a community or public authority can 
minimise the risk of a disaster (ISDR, 2002) 
Researchers in contemporary disaster management have been using quasi-experimental 
survey design. These approaches such as before – and – after studies (longitudinal) 
studies have some application in the study of disaster. Before – and – after studies 
form the bases for assessing the damage caused by an event because assessment of 
disaster is not possible without the knowledge of the pre-event status of the affected 
community (Stephenson, 1994). Australian Development Gateway used this method to 
determine the trends and features associated with each phase of Disaster Risk 
Management Cycle (DRMC). The longitudinal survey is done, most often than not, in 
expectation of a disaster that is about to happen. This is so because the goal of disaster 
preparedness and response is to return the affected society to its pre-event status 
(Australian Development Gateway, 2007). 
Disaster risk is part of everyday life. Awareness of risk is a necessary condition to 
engage in disaster risk reduction. In determining this, Vulnerability and Capacity 
Analysis (VCA) is an indispensable profiling method with specific focus on the 
relationship between hazard and recipient subject. Different approaches to conducting 
VCA have been used in various countries. Methods adopted may be described either as 
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„top-down‟ or „bottom up‟, using quantitative, qualitative or a combination in a 
triangulated methodology. For example, in Palestine, the Palestine Red Crescent 
Society (2000), adopted a participatory approach to disaster management which was 
predominantly qualitative in nature. In Nigeria, the pilot programmes conducted by the 
National Emergency Management Agency (NEMA) for VCA in Kaduna, Benue, 
Adamawa, Akwa Ibom, Imo, Lagos States and Abuja were done using quantitative and 
qualitative approaches to determine how these States could limit the damage 
occasioned by disaster through their inherent capacity and vulnerability components 
(NEMA, 2011). 
Vulnerability is not a simple or readily measured parameter but it is, rather, a 
combination of various measures related to the socio-economic, political, physical, 
cultural and environmental situation of a specific location. Thus, VCA identifies the 
strength and weakness of the recipient community in relation to the identified hazard, 
based on readily available information. As noted by Turner et al (2003), different 
levels of decision-making require assessment of vulnerability at different geographic 
scale on which the VCA is based. Hence, the aim of VCA is to provide decision-
makers with information as to where and when interventions should be made and in 
what form. Vulnerability can be assessed using VCA at various levels such as 
individual, household, village, ecosystem, regional and national. For different levels 
different sets of information will be required. It is recommended by UN-Habitat 
(2001a), that the following procedures should be taken into consideration at any level 
of assessment: 
i. Decision on a target geographical area or assessment unit, taking into 
consideration scale effects; 
ii. Scope study to establish for whom the assessment results can be used and for 
what decision; 
iii. Preparation of a causal schematic illustration; and 
iv. Preparation of profile (assessment statement) for the: 
a. Activity sectors for development (the population); 
b. Environmental setting (mediating factors); and 
c. Hazard. 
Disaster can be studied through spatial planning and Geographical Information System 
(GIS) using hazard mapping procedures. Several initiatives on hazard mapping were 
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developed during the 1990s as part of the International Decade for Natural Disaster 
Reduction strategy. However, as noted by ISDR (2002), hazard mapping is challenged 
by several constraining factors. Among the most challenging are: inadequate 
technological infrastructure, training for human resources and insufficient 
communication and collaboration among relevant bodies adversely affect hazard 
mapping process.  
In recent time, as noted by Eslinger (2001), methodologies which include ground 
surveys, remote sensing and GIS mapping have been employed in hazard mapping. An 
integrated hazard assessment methodology that used a GIS-driven constraint analysis 
to evaluate multiple hazards had been used in sustainable development planning for 
eight Puerto Rico municipalities. The method employs a vulnerability index that 
relates the intensity of past damages to the reoccurrence interval for each hazard, and 
then compares different hazards to create a composite hazard map. 
While hazard mapping has been improved by the wider use of GIS technique, the 
inclusion of socio-economic and environmental variables into GIS models remains a 
major methodological challenge. In other words, the need to assign quantifiable values 
to the variables analysed in the spatial models used by GIS is not always possible for 
social and economic dimensions of vulnerability. Also, the diverse scales at which 
different dimensions of socio-economic vulnerability operate make the spatial 
representation through these techniques very difficult. In addition, the quality and 
detail of the data required by GIS analysis is in many cases non-existent, especially in 
the developing countries (de Jong, 2002). 
2.6.7 Application of urban dynamic model to city management.  
This study of urban dynamics was undertaken principally because of discoveries made 
in modeling the growth process of corporations. It has become clear that complex 
systems are counterintuitive. The ideal city would be one with readily available 
housing at low cost, a surplus of jobs at high wages, excellent schools, no smoke or 
pollution, housing located near one's place of work, no crime, beautiful parks, cultural 
opportunities, and list continues. Suppose such a city existed. What would happen? It 
would be perceived as the ideal place to live. People from everywhere would move 
into the ideal city until the advantages had been so swamped by rising population that 
the city would offer no net attractiveness compared with other locations (Alfeld, 1995). 
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There are many components of urban attractiveness, and if one of these is decreased, 
others can be improved. One cannot create the ideal city. But one can create certain 
ideal features if one is willing to compensate for them by intentionally allowing other 
features to worsen.  
The publication of Urban Dynamics in 1969 generated intense controversy. To help 
assess the model‟s value, the then-new United States Department of Housing and 
Urban Development (HUD) provided a 210,000 dollars research grant to support a 
two-year effort to validate the model. An advisory committee of urban experts drawn 
from academia and city government was to provide guidance and judge the results of 
the research. The principle of urban dynamics was adopted in managing the growth of 
5 United States of America cities namely: Lowell 1971, Boston 1974, Concord 1975 
and Marlborough 1976, all in Massachusetts. The Atlantic beach of Palm Coast, 
Florida was the fifth city where the theory was implemented in 1980 (Alfeld, 1995). 
All five applications differed from one another. In the first city, Lowell, the 
intervention demonstrated the importance of a limited land resource in shaping urban 
policy. Boston, underscored how urban aging widens the gap between the city‟s high-
priced job base and its low-priced housing stock. Work in Concord employed simple 
models to capture the powerful feedback forces that drive migration and growth. 
Marlborough bypassed formal modelling, using the underlying theory to shape a verbal 
logic that supported political actions aimed at preserving the older inner 
neighbourhoods in a dynamic equilibrium. Finally, a substantially revised model was 
constructed to guide the projected 80-year growth of Palm Coast, from a tiny 
community of 3000 to a new town of 224,000 (Alfeld, 1995). 
To encourage that urban renewal according to Kadanoff (1971), two central rules 
ought to guide any future application of urban dynamics: emphasize answers, not 
models, and emphasize interface, not data. The first rule cautions model-builders to 
present their work in terms of answers that urban decision-makers need rather than 
models of urban problems. These answers must be responsive in three areas of 
decision support: how to maximize the leverage of existing programs by highlighting 
some aspects while downplaying others; how to quantify the trade-offs among 
competing programmes in terms of budget, performance and time; and how to use the 
model logic to create a consensus to support needed change. In addition to this, any 
future urban dynamics work must help urban decision-makers grasp four 
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interconnected principles that control urban behaviour: resource constraints; urban 
aging; relative attractiveness and equilibrium growth. These four principles are still the 
fundamental forces driving city evolution today and an understanding of how they 
combine to determine the impact of urban programmes is essential to effective 
decision-making.  
2.6.8 Flood risk assessment and mapping 
Flooding is the most common of all environmental hazards and it regularly claims over 
20,000 lives per year and adversely affects around 75 million people world-wide 
(Smith, 1996). The reason lies in the widespread geographical distribution of river 
floodplains and low-lying coasts, together with their long standing attractions for 
human settlement. Death and destruction due to flooding continue to be all too 
common phenomena throughout the world today, affecting millions of people 
annually. 
Mitigation of flood disaster can be successful only when detailed knowledge is 
obtained about the expected frequency, character, and magnitude of hazardous events 
in an area as well as the vulnerability of the people, buildings, infrastructures and 
economic activities in a potential dangerous area (Van Western and Hosfstee, 2000). 
Unfortunately, as noted by Ifatimehin et al, (2009), this detailed knowledge is always 
lacking in most urban centres of the developing world especially Nigeria. However, 
one of the functional strategies to mitigate the effects of flooding is to ensure that areas 
vulnerable are identified and precautionary measures are taken to ensure adequate 
prevention, mitigation, preparedness, effective response and quick recovery (UN-
Habitat, 2001b). Before these could be done, information is required on important 
indices of flood risk identification which are elevation, slope orientation, proximity of 
built-up areas to drainages, network of drains, presence of buffers, extent of 
inundation, cultural practices as well as attitudes and perceptions (Ishaya et al, 2009). 
Flood risk assessment according to Kates and Kasperson (1983), comprises three 
distinct steps: identification of hazards likely to result in disasters, for example, what 
hazards events may recur?; an estimation of the risks of such event - what is the 
possibility of such event?; and an evaluation of the social consequences of the derived 
risk - what is the loss created by each event? Also, as opined by Ologunorisa and 
Abawua (2005), flood risk assessment comprises all the steps outlined above in 
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addition to the identification of high risk areas with the use of meteorological 
parameters, combination of hydro-meteorological and socio-economic factors, 
hydrological parameters and Geographical Information System (GIS).  
Ologunorisa (2004), undertook an assessment of flood risk in the Niger Delta, Nigeria 
using a combination of hydrological techniques based on some measurable physical 
characteristics of flooding, and social-economic techniques based on vulnerability 
factors. Also, the Nigerian Institute for Oceanography and Marine Research, Lagos 
State Ministry of Environment and Physical Planning (Department of Drainage), the 
United Nations Educational, Scientific and Cultural Organization (UNESCO), and the 
Coastal Regions and Small Islands (CSI) conducted flood risk assessment for Lagos 
State in 2000. Some of the physical characteristics of flooding selected include depth 
of flooding (metres), duration of flood (hours/weeks), perceived frequency of flood 
occurrence, and relief or elevation (m) while the vulnerability factors selected include 
proximity to hazard source, land use or dominant economic activity and adequacy of 
flood alleviation schemes and perceived extent of flood damage. He derived rating 
scale for the nine parameters selected, and 18 settlements randomly selected across the 
three ecological zones in the region were rated on the basis of the parameters. Three 
flood risk zones emerged from the analysis. These are the severe flood risk zones, 
moderate flood risk zones and low flood risk zones. Some strategies for mitigating the 
hazard of flooding in the region were also identified. 
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CHAPTER THREE 
RESEARCH METHODOLOGY 
3.0 Introduction 
This chapter describes the research methodology and the procedures adopted in data 
collection, analysis and interpretation in order to realize the objectives of the study. In 
view of this, the chapter discusses: research design, sources of data, population of the 
study, sampling technique, instrument and method of data collection, Geographic 
Information Systems (GIS) analysis and data analysis. Methodology is paramount to 
and is seen as the hallmark of researches, thus, findings of research depend on the 
methodology adopted. This study drew its data from primary and secondary sources of 
data collection.  
3.1 Research design 
There are two types of research design: cross-sectional survey and longitudinal survey. 
This study adopted the cross-sectional survey research design for the household 
questionnaire distribution and longitudinal survey for the Geographic Information 
System (GIS) Analysis. Cross-sectional research is a research method often used in 
social science and education. It is described as snapshots of the population about which 
it gathers data. Thus, the cross-sectional surveys asked a group of respondents a set of 
questions at one point in time. This type of study utilises different groups of people 
who differ in the variable of interests but share other characteristics such as 
socioeconomic status, educational background, occupation, household and housing 
characteristics. 
3.2 Primary sources of data  
This source of data adopted the following methods: Direct Observation, Interview 
Guide, Administration of Questionnaires, Google Earth and GIS Mapping. The direct 
observation method was used to investigate the environmental and vulnerability 
conditions inherent in the study area. The interview guide focused on disaster 
management agencies and organizations in Nigeria such as the National Emergency 
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Management Agency (NEMA), the Lagos State Emergency Management Agency 
(LASEMA), Nigerian Red Cross Society, Fire Service, the Nigerian Security and Civil 
Defense Corps (NSCDC), Federal and State Ministries, Construction Companies to 
elicit relevant information on various aspects of their operation with regard to disaster 
management. To elicit the needed information, Semi-Structured Interviews through 
face-to-face interviews with the Federal and State Government actors, Local 
Government Authorities, Nigerian Red Cross Society, Community-Based 
Organizations (CBOs) and other partners working on disaster reduction and recovery 
were conducted.  
In addition to these, On-Site Field Visits for capacity assessments were carried out. In 
conducting the exercise, particular attention was given to issues related to capacities 
for preventing and mitigating natural disaster risks in Nigeria at the national, state, and 
local government levels. During the field visits, sector-wide consultations and 
interviews on a wide variety of stakeholders‟ activities from different sectors and 
organizations were examined. 
The interview guide for NEMA and SEMA was structured into five sections as 
follows: general and statutory obligations of the agencies, disaster management and 
mitigation procedure, relationship between the agencies, other disaster networks and 
communities, vulnerability study analysis, and the challenges of the agencies. The 
interview guide for the other disaster networks was sectionalized into four: general 
information, disaster management and mitigation, relationship between the network 
and the disaster management agencies and communities and their knowledge on 
environment and disaster related policies and programmes. 
The household questionnaire was tailored towards the inhabitants (household heads) of 
the study area and has eight sections. These sections include: general information, 
socio-economic information, environmental conditions, types and nature of disasters, 
disaster management knowledge and approach, vulnerability information, policies and 
disaster management agencies, urbanization trend and its impact on the environment. 
For verification and authentication of data, Google Earth was used to count the number 
of buildings within each unit of study. 
 
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3.3 Secondary sources of data 
To buttress and complement data that were collected from the study area, existing data 
were sourced from the Lagos State Ministries of Physical Planning and Urban 
Development, Housing, Environment, Health, NEMA Headquarters Abuja and the 
Lagos Zonal Office, LASEMA and the Lagos State Public Works Corporation in 
determining the Federal and State involvement in disaster management. The Disaster 
Risk Reduction Capacity Assessment (DRR/CA) methodology which is based on a 
review of primary data and relevant documentation related to disaster and 
environmental management in Lagos was employed to review the data sourced from 
secondary sources. The evaluation was based on a methodology developed by the 
UNDP Capacity Development Group (CDG) and adapted for the Disaster Risk 
Reduction in Nigeria in 2013. This methodology outlines the capacity assessment 
questions and these include data collection methodologies, data sources, and key 
respondents. The data collected were primarily qualitative, consisting of background 
documentation, document review and analysis, reports and assessments.  
Other secondary sources of information include population census document that 
shows urban dynamics process over time and also delineates and classifies the selected 
Local Government Areas (LGAs) according to localities. These were obtained from 
the National Population Commission (NPC) and the Independent National Electoral 
Commission (INEC). The documents were used to classify localities into the wards of 
interest. In addition to this, previous environmental and disaster related policies and 
laws of the Federal and State Governments were reviewed. These include: the 1946 
Planning Ordinance, 1992 Urban and Regional Planning Law, NEMA and LASEMA 
Acts, the National Urban Development Policy, among other Acts. 
The map of Lagos State in the context of Nigeria and the maps of LGAs in Lagos state 
were used to describe the study area and in analyzing the spatial dimension of 
vulnerability to disasters from data obtained from the field. Finally, the works, 
researches and studies done in the area of urbanization, population growth and 
vulnerability to disasters contained in journals, books, proceedings of conferences, 
workshops and internet materials especially from websites like www.unisdr.org, 
www.proVenture.comwww.cred.bc, www.redcross.org, www.globalissue.org and 
other website related to disaster management and urbanization were used to anchor the 
theories, concepts and literature review sections. 
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3.4 Sample frame, size and sampling procedure 
Lagos state, at present, has 20 LGAs listed in the Constitution of Federal republic of 
Nigeria. However, for the purpose of this research, the study area was disaggregated 
into Lagos Mainland (LM) and Lagos Suburb (LS) as contained in Table 3.1. A total 
of nine LGAs:  five from LM and four from LS LGAs, accounted for about 25% of 
land cover in Lagos State, were chosen based on current population figures and 
contagiousness of location. In Lagos State, increasing population places undue 
pressure on existing infrastructural facilities and services and invariably led to 
population expansion to marginal land and the burgeoning of informal settlements 
associated with sub-standard buildings, encroachment on natural flood plains and acute 
disregard to planning ordinance and regulation. Thus, the LGAs with the highest 
population figures and most vulnerable to disasters in the regional classification were 
selected for the study as shown in Table 3.2. A multi-stage sampling strategy was 
adopted for households‟ questionnaire administration. According to the NPC, in 1991 
and 2006, the populations of Lagos State were given as 5,725,116 and 9,013,534 
respectively. The United Nations (1996), posited that Lagos is likely to become the 
third largest city in the world after Tokyo and Mumbai (formerly Bombay) by 2015. 
Consequently, the UN-Habitat (2005), has estimated the population of Lagos to be 
16.8 million in 2005. 
  
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Table 3.1 2010 population projections for Lagos state LGAs    
Regional LGAs Number of 2006 Projected 2010 
Classification wards population population 
Lagos Mainland Lagos Mainland 11 317,720 355,243 
Surulere 12 503,975 563,494 
Lagos Island 19 209,437 234,172 
Eti Osa 10 287,785 321,772 
Shomolu 12 402,673 450,229 
Apapa 10 217,362 243,032 
Ikeja 10 313,196 350,184 
Mushin  14 633,009 707,767 
Ojo 11 598,071 668,703 
Oshodi/ Isolo 11 621,509 694,909 
Lagos Suburb Ajeromi-Ifelodun 11 684,105 764,898 
Kosofe 10 665,393 743,976 
Ifako/Ijaiye 11 427,878 478,410 
Agege 11 459,939 514,258 
Ibeju-Lekki 11 117,481 131,356 
Badagry 11 241093 269566 
Alimosho 11 1,277,714 1,428,612 
Amuwo/Odofin 10 318,166 355,741 
 Epe 11 181409 202,833 
Ikorodu 11 535619 598,876 
Total   228 9,013,534 10,078,031 
Source: Federal Republic of Nigeria Official Gazette (2007). 
 
  
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Table 3.2 LGAs of interest in Lagos Mainland and Suburb 
 Regional LGAs 2006 population 2010 projected 
Classification population 
Lagos Mainland Mushin 633,009 707,767 
Oshodi-Isolo 621,509 694,909 
Surulere 503,975 563,494 
 Lagos Mainland 317,720 355,243 
Shomolu 402,673 450,229 
Lagos Suburb Kosofe 665,393 743,976 
Ikorodu 535,619 598,876 
Alimosho 1,277,714 1,428,612 
 Ajeromi-Ifelodun 684,105 764,898 
Total 9 5,641,717 6,308,004 
Source: Federal Republic of Nigeria Official Gazette (2007) 
 
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Lagos manifests the characteristics of high proportion of slum settlements, lack of 
basic infrastructure and amenities, urban decay and obvious cyclical poverty – the 
defining features of the developing nations‟ urban settlement – that further aggravates 
vulnerability to disasters. Given the history of population censuses in Nigeria, 
including the 2006 census figures of 9,013,534 million for Lagos, the UN-Habitat‟s 
and the United Nations‟ projected figures are probably closer to reality than the NPC 
figures. 
The research structured the study area into income classifications as follows: Low 
Income/High Density (LI/HD), Medium Income/ Medium Density (MI/MD) and High 
Income/Low Density (HI/LD). A number of studies (Centre for Democracy and 
Governance, 2000; Smith, 2008) have shown and concluded that the classification of 
LGAs into income groups will not be effective at the LGAs level because LGAs in 
Lagos state are large, heterogeneous and have mixed income groups neighbourhoods. 
To minimize the effects of this evident challenge, the classification was done using the 
Lagos State Independent National Electoral Commission (LSINEC) wards 
classification for the 9 LGAs. 
A ward is a smaller administrative and or political unit which has homogeneous 
characteristics germane to the study. The challenge encountered by using the ward as 
the unit of study was that the available NPC population figures were not classified 
according to ward but the classification was done based on LGAs and their localities. 
However, the population figure for each ward was obtained by identifying the 
localities and classifying them according to their corresponding wards. Therefore, the 
population figure for localities within each ward was summed up to obtain the 
population for the ward. A total number of 54 wards, 6 from each LGA, were selected 
for the study. To determine the wards of interest, 6 wards with the highest population 
figures from each LGA were selected after the population figures for the wards in the 
LGA had been arranged in decreasing order, where possible, along density/income 
classifications as shown in Tables 3.3 and 3.4.   
 
  
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Table 3.3 Lagos mainland LGAs, Wards and neighbourhood classifications 
LGAs Name of ward Neighbourhood 
classifications 
Lagos Mainland Otto/Iddo High Density 
 Makoko/EbuteMetta High Density 
 Olaleye Village High Density 
 Oyediran Estate/Abule-Oja Medium Density 
 Yaba/Iponri/Sabe Medium Density 
 Iwaya Medium Density 
Mushin Mushin/Atewolara High Density 
 Ilasamaja High Density 
 Itire High Density 
 Idi-Oro/Odi-Olowo High Density 
 Ilupeju Low Density 
 Kayode/Fadeyi Medium Density 
Oshodi/Isolo Orile-Oshodi High Density 
 Mafoluku High Density 
 Oke-Afa/Ejigbo High Density 
 Ajao Estate Low Density 
 Isolo Medium Density 
 Sogunle Medium Density 
Surulere Orile High Density 
 Ijesha-Tedo High Density 
 Itire High Density 
 Ikate High Density 
 Adeniran Ogunsanya Low Density 
 Aguda Low Density 
Shomolu Bajulaiye High Density 
 Bariga High Density 
 Abule Okuta/Ilaje/Bariga High Density 
 Palmgrove Low Density 
 Ilaje/Akoka Medium Density 
 Gbagada Phase I/Obanikoro Medium Density 
Source: Lagos State Independent National Electoral Commission (LSINEC), 
2005. 
 
 
  
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Table 3.4 Lagos suburb LGAs, wards and neighbourhood classifications 
LGAs Name of ward Neighbourhood 
classifications 
Ajeromi-Ifelodun Tolu High Density 
 Alaba-Oro High Density 
 Olodi High Density 
 Ojo Road High Density 
 Awodi-Ora High Density 
 Temidire High Density 
Kosofe Ketu/Ikosi High Density 
 Ajegunle High Density 
 Anthony/Mende Low Density 
 Isheri/Olowora Low Density 
 Ojota/Ogudu Medium Density 
 Oworonsoki Medium Density 
Alimosho Abule-Egba/Alagbado High Density 
 Egbe/Agodo High Density 
 Shasha/Akowonjo High Density 
 Egbeda/Alimosho High Density 
 Ipaja North Medium Density 
 Oke-Odo/Pleasure Medium Density 
Ikorodu Ipakodo  High Density 
 Imota  High Density 
 Baiyeku/Ireta  High Density 
 Odogunyan  High Density 
 Igbogbo  Medium Density 
 Ijede Medium Density 
Source: Lagos State Independent National Electoral Commission (LSINEC), 
2005. 
 
 
 
 
 
 
 
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The next stage in the sampling procedure was the identification of houses to be 
sampled. To identify the sampled houses in each ward, data on the number of building 
in Lagos State, disaggregated according to streets, roads and LGAs, was collected from 
the Lagos State Bureau of Statistics. All the streets in the study area were delineated 
according to wards with the aid of Google Map, Google Earth Imagery and Lagos 
State Street Map. To determine the sample size to be adopted for the study, 0.5 % of 
the 315,305 selected houses in the LGAs was taken as the sampling ratio. Thus, the 
sample size arrived at was 1576. The break-up of the respondents for the LGAs is 
contained in Table 3.5 
The houses within the wards of interest were listed and numbered with the aid of 
Google Earth while physical counting and numbering was done to authenticate the 
Google Earth results. The listing and numbering are important because one cannot 
develop an efficient sampling procedure without taking them into consideration. For 
example, if there are 80 houses in a given ward, the houses were numbered 1 – 80 and 
table of random numbers was used to select houses from which to elicit information 
using the households‟ questionnaire. 
After determining the houses in which questionnaires would be administered, all the 
households in the selected building were listed and samples were randomly selected 
using random number. 
  
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Table 3.5 Number of wards and sample size adopted for the study. 
Regional LGA Number of Sample size No. of sampled 
Classification buildings (0.5%) wards in LGAs 
Lagos Mainland Lagos Mainland 13321 67 6 
Mushin 30676 153 6 
Oshodi-Isolo 39359 197 6 
 Shomolu 42876 214 6 
Surulere 21171 106 6 
Lagos Suburb Kosofe 16655 83 6 
Ikorodu 46732 234 6 
Ajeromi-Ifelodun 46443 232 6 
 Alimosho 58072 290 6 
Total  315305 1576 54 
Source: Lagos State Bureau of Statistic 2010 
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3.5 GIS: flood risk assessment procedure 
The systematic study of global urban expansion requires good data which, until 
recently, have not been available. At the minimum, it requires high quality, 
internationally comparable data of the urban land cover in a global sample of cities for 
two time periods. As a result of the absence of comparative data, important debates on 
urban policies continue to take place with little or no data to support one position or 
another. Introducing the debate on the merits of compact city policies for developing 
countries, for example, Burgess (2000), acknowledges that lack of empirical data on 
existing urban expansion, density and trends and a lack of clarity on what are the most 
appropriate indicators to measure them, pose a problem for the assessment of urban 
expansion policies for cities in developing countries.  
Computer-assisted processing of satellite remote sensing data was judged as the most 
cost-effective means to extract this information and the Landsat Thematic Mapper 
(TM) and Enhanced Thematic Mapper+ (ETM) were deemed the optimal sensors for 
this purpose. The data available for this study encompassed: Topographic map; 1984 
and 2010 Landsat ETM+ images; and Elevation Map. Lagos State topographic map 
from Global Land Cover Facility (2011) was scanned and imported into ArcGIS. This 
was digitized and used to define the boundary of urban expansion overtime. The 
elevation map of the study area obtained from Global Land Cover Facility (2011) was 
also imported into ArcGIS (Figure 3.1).  
  
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Figure 3.1 Elevation of the study area 
Source: Global Land Cover Facility 2011 
 
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Elevation is highest in the north eastern and north western parts of the study area but 
very low at the southern part. The Landsat images and elevation map were clipped 
with the digitized image of the topographic map. “False” composite images from 
spectral bands 3 (Red), 4 (near-infrared) and 5 (mid-infrared) of Landsat ETM+ 
images of the study area in 1984 and 2010 were classified to extract the different land 
uses of the study area using CLUSTER unsupervised classification algorithm provided 
by IDRISI Taiga. The Landsat data were orthographically corrected to remove 
geometric distortions and displacements. Each scene was geo-referenced to the 
Universal Transverse Mercator (UTM) projection, while the image pixels were re-
sampled to 28.5 metres. 
3.6 Method of data analysis 
For the purpose of this research, the data collected were analysed using the Statistical 
Packages for Social Sciences (SPSS) and ArcView for Geographic Information 
Systems (GIS) Analysis. Descriptive and inferential statistics were used in analyzing 
the data obtained. A selection of descriptive statistical methods and diagrams were 
used in the initial display of data. These include: frequencies and percentages.  
The first hypothesis states that urban dynamics is influenced by availability of low 
income/high density housing in the study area was tested using two-sample chi square 
 2( ) method. The chi square test aided the study to determine if there is a difference 
between low income housing and urban dynamics. The test is based on a comparison 
of the observed values with the expected if the two distributions are independent. 
2
Thus, (  ) tests if data in the table differ significantly from the expected when the two 
variables were independent of each other. In other to test the hypothesis, primary data 
2
elicited to influence urban dynamics were analysed using (  ) test. The observed 
frequencies from the responses from the 9 LGAs of interest constituted the data that 
were analysed. 
The second hypothesis which states that vulnerability to disasters is a function of 
socio-economic indices, housing characteristics and provision of infrastructural 
facilities and services was analysed using multiple regression model involving dummy 
variables or logistic model. This model is appropriate because the dependent variable 
is dichotomous (binary) as respondents had either experienced disasters or not. The 
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model is probabilistic and also allows for the prediction of likelihood (odd ratio).The 
regression model analysed is stated as follows: 
Y = a + b1X1 + b2X2 + b3X3 + b4X4 + b5X5 + b6X6 + b7X7 + b8X8 + b9X9 + 
b10X10……………… + e  
Where:  
Y is vulnerability to disaster index (flooding, fire outbreak, building collapse and 
disease outbreak) 
a is the intercept 
b is the slope 
e is the stochastic disturbance or error term 
Predictive factors for socio-economic indices are: 
X1 Age: this is constructed as non-discrete variable 
X2 Gender: since there are two groups, the female group is used as the base and 
dummy is  constructed for male. 
X3 Marital Status: this variable has four categories and the married category is 
used as the  based category while dummy is constructed for other categories. 
X4 Employment: this variable has six categories and the business man category is 
used as the based category while dummy is constructed for other categories. 
X5 Household Size: this is constructed as non-discrete variable 
X6 Level of Education: this variable has four categories and the tertiary education 
category is used as the based category while dummy is constructed for other 
categories. 
X7 Income:  this is constructed as non-discrete variable  
Predictive factors for household and housing characteristics are: 
X8 Age of Building: this is constructed as non-discrete variable  
X9 Types Dwelling Unit: this variable has four categories and the rooming 
apartment category is used as the based category while dummy is constructed 
for other categories. 
X10 Number of Rooms in Building: this is constructed as non-discrete variable 
X11 Number of Persons per Room: this is constructed as non-discrete variable 
X12 Distance to Structures to the Right, Left, Rear and Front: all are constructed as 
  non-discrete variable  
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X13 Material Used in Construction: Unit: this variable has two categories and 
sandcrete block category is used as the based category while dummy is 
constructed for other categories. 
X14 Drainage Conditions: this variable has three categories and semi blocked 
drainage category is used as the based category while dummy is constructed for 
other categories. 
X15 Building Setback to Drainage and Water Bodies: this is constructed as non-
  discrete variable  
Predictive factors for housing infrastructural facilities and services include: 
X16 Sources of Domestic Water: this variable has four categories and well/borehole 
category is used as the based category while dummy is constructed for other 
categories. 
X17 Toilet Facility: this variable has four categories and using water closet ensuite 
as the based category dummy is constructed for other categories.  
X18 Number of Persons per Toilet Facility: this is constructed as non-discrete    
  variable  
X19 Waste management: this variable has three categories and government 
collection is used as the based category while dummy is constructed for other 
categories. 
X20 Frequency of Collection: this variable has four categories and weekly 
collection is used as the based category while dummy is constructed for other 
categories  
 
There are certain rules for creating dummy variables. A variable with two categories 
are usually described as dichotomous. The requirement that if K categories exist, by 
default, there must be K – 1 dummy variable is valid when an intercept (a) is included 
in the logistic regression equation. This is because inclusion of all K categories would 
render the normal equations unsolvable. Therefore, it is important in regression 
analysis involving an intercept to exclude one of the dummies from the equation. The 
exclusion does not result in loss of information; however, the excluded category 
becomes a reference point on which the actions of other dummies are predicted and 
interpreted. The excluded category in the literature is referred to as the base category 
(Gujarati 2009). This rule was taken into consideration in the regression analysis. 
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The third hypothesis which states that occurrence of disasters differs significantly 
between residential neighbourhoods (low, medium and high densities) was tested using 
the Analysis of Variance (ANOVA) technique. In most planning situations, the interest 
of intervention is focused on whether the observed differences between more than two 
means are attributable to chance or they are indications of actual differences among 
means of the parent population from where the samples were drawn. The most 
appropriate statistical methodology employed in analysing this is ANOVA. The 
available secondary data on fire outbreak and building collapse satisfied the 
assumptions of ANOVA which include the followings: 
i. Each data is independent and does not relate to any of the other values. One way 
ANOVA should not be used when data values are related. For instance, ANOVA 
should not be performed when the same variable is tested repeatedly 
ii. The population from which the samples are drawn can be approximated closely 
with normal distribution. 
iii. The data for each group have that same variance (standard deviation squared).  
The study ensured that the ANOVA assumptions were satisfied before subjecting data 
on fire outbreak and building collapse to the analysis. 
3.7  Conclusion 
This chapter highlighted the sources of data on which the relationship between urban 
dynamics and vulnerability to disaster could be examined. The cross sectional research 
design was adopted for the study and data were collected from households, National 
Emergency Management Agency, Lagos State National Emergency Management 
Agency, Lagos State Ministries of Physical Planning and Urban Development, 
Environment, Housing, Health and other critical stakeholders in disaster management. 
The GIS was also used to explore the extent of land use and land cover change. The 
next chapter will provide an insight into the process and trigger mechanism of urban 
dynamics and the nexus with vulnerability to disaster. 
 
  
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CHAPTER FOUR 
THE PROCESS AND CONTRIBUTING FACTOR TO URBAN DYNAMICS 
4.1 Introduction 
Urban dynamics looks at land use change, economic development and population 
growth in urban environment over time in order to provide a historical perspective of 
land use change and an assessment of the spatial patterns, rates, correlation, trends, and 
impacts of that change. Organically, cities grow without defined form and 
morphology, spread over every available empty space and overrun the ability of public 
services, where they exist, to meet demands or cope with the growth. Property 
developers, corporations, migrant workers, government bureaucracies, and public 
institutions play important role in the growth and reshaping of cities to curtail and give 
systemic order to this organic growth.  
Universal argument for urban dynamics is hinged on population growth, economic 
development, urban expansion and socio-economic implications on land use, land 
market, land use regulations and public policies on infrastructural facilities and 
housing (Forrester, 1969). Population forecast for Nigerian urban centres projected a 
stable population growth in the near future. However, the expectations of a more 
sustainable development have not been fulfilled. While some parts of Lagos State are 
losing significant population, the share of population in other area is growing very fast. 
In view of this development, this section, among other things, explains why intra-
urban dynamics is taking place by comparing spatial patterns of population growth, 
previous housing development strategies and the effects on the living environment in 
Lagos State.  
 
 
4.2 Activators of the process of urban dynamics 
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The spatial pattern of population growth and the burgeoning urban expansion in Lagos 
State is skewed towards the urban fringe. This phenomenon is producing an important 
land use pattern that is manifesting in the destruction of natural environment and in the 
habitation of areas vulnerable to disasters as shown in subsequent section on flood risk 
assessment. Urban development associated with lateral expansion in Lagos State and 
by extension Nigeria, is connected to deforestation and occupation of environmentally 
protected areas, especially the water-shed. In terms of population growth, the 
demography of the study area has been very unevenly distributed in the past few 
decades. This uneven distribution and the present urban dynamics (process) is 
traceable to the hosting of the Festival of Arts and Culture (FESTAC) in 1977 by 
Nigeria which made available 11,422 and 3,044 housing units in Festival Town and 
Ipaja Town respectively as contained in Tables 4.1 and 4.2 (Federal Housing 
Authority, 2010). The provision of the FESTAC houses is a major contributory factor 
to urban dynamic. This increased the housing capacity to accommodate about 101,262 
persons officially thereby adding impetus to already growing population of Lagos.  
Gleaning from Tables 4.1 and 4.2, the FHA produced 14,466 housing units for 
different categories of income groups. Within this number, 64.8 % of housing units 
produced in the two estates were meant for low income earners, 35 % for medium 
income group and the remaining 0.2 percent were occupied by the high income 
earners. 
  
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Table 4.1 Housing unit produced by FHA in FESTAC Town, 1974 - 1989 
S/N Types of residential development Unit Beneficiary 
produced 
1 T1 (1 Bedroom in a Block of 3 Flat) 1,698 Low Income 
2 T2 (2 Bedroom in a Block of 12 Flat) 4,164 Low income 
3 T3 (2 Bedroom Bungalow Without Garage) 72 Low Income 
4 T4 (2 Bedroom Bungalow Garage) 340 Medium Income 
5 T5 (3 Bedroom in a Block of Flat) 1388 Medium Income 
6 T6 (3 Bedroom in a Block of 8 Flat) 472 Medium Income 
7 T7 (3 Bedroom Terrace House Storey 355 Medium Income 
Building) 
8 T8 (3 Bedroom Semi Detached Storey 1840 High Income 
Building) 
9 T9 (3 Bedroom Detached Storey Building 373 High Income 
with Garage and Boy‟s Quarters) 
10 T10 (5 Bedroom Detached Storey Building 71 High Income 
with Garage and Boy‟s Quarters) 
11 Other (Not Specified) 487 Medium/High 
 Total 11,422  
Source: Adapted from Alabi, 2011 
 
  
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Table 4.2 Housing unit produced by FHA in Ipaja New Town, 1982 - 1990 
S/N Types of residential development Unit Beneficiary 
produced 
1 T2 (2 Bedroom in a Block of 12 Flat) 1512 Low Income 
2 T3 (2 Bedroom Bungalow Without Garage) 72 Low Income 
3 T4 (2 Bedroom Bungalow Garage) 387 Medium 
Income 
4 T5 (3 Bedroom in a Block of 16 Flat) 504 Medium 
Income 
5 T6 (3 Bedroom in a Block of 8 Flat) 224 Medium 
Income 
6 T7 (3 Bedroom Terrace House Storey 335 Medium 
Building) Income 
7 T9 (3 Bedroom Detached Storey Building 2 High Income 
with Garage and Boy‟s Quarters) 
8 T10 (5 Bedroom Detached Storey Building 4 High Income 
with Garage and Boy‟s Quarters) 
 Total 3,040  
Source: Adapted from Alabi, 2011 
 
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Also, the housing policy of the 1979 – 1983 civilian administration activated massive 
intra-urban and rural-urban migration to Lagos Mainland and its hinterland. The main 
focus of the Second Republic Civilian Administration of the 1979 – 1983 in the State 
was to provide at least 20,000 units of affordable low cost housing in 12 locations 
across the State for low income earners especially the Civil Servants, through the 
Lagos State Development and Property Corporation (LSDPC). The period also 
heralded Lagos State into the city of millions in terms of population. The locations and 
number of housing blocks built are shown in Table 4.3. 
 
  
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Table 4.3 Locations and number of units built in Jakande estates in the 1980s 
S/N Name of estate LGAs Unit produced Beneficiary 
1 Abesan-Ipaja Alimosho 4272 Low Income 
2 Amuwo Odofin  Amuwo-Odofin 2068 Low Income 
3 Dairy Farm, Agege Agege 708 Low Income 
4 Ojokoro  Agege 534 Low Income 
5 Oke Afa Isolo  Oshodi-Isolo 1410 Low Income 
6 Badagry Badagry 1122 Low Income 
7 Lekki  Lekki 1506 Low Income 
8 Epe  Epe 2068 Low Income 
9 Iba  Ajeromi-Ifelodun 1560 Low Income 
Sub Total  15248  
10 Ketu Alapere  Kosofe 1140 Medium Income 
11 Ogba Ikeja 936 Medium Income 
12 Omole  Ikeja 100 Medium Income 
13 Ijaiye  Ifako-Ijaiye 796 Medium Income 
14 Adeniji Adele Lagos Island 1206 Medium Income 
Sub Total  4178  
15 Amuwo-Odufin Phase I Amuwo-Odofin 304 High Income 
and II 
16 Ogudu I and II Kosofe 126 High Income 
Sub Total  430  
Sub Total  19856  
Sources: Adapted from Alabi, 2011 and Lagos State Development and Property 
Corporation (LSDPC), 2012 
 
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The development of the housing estates across the study area, at that time, was aimed 
at decreasing and improving population concentration from the congested Lagos 
Island; improving the squalor and poverty many people lived in; and to provide 
comfortable houses for people within the low-income bracket. From Table 4.3 out of 
the 19856 housing units provided in the Jakande Estates across the State, 76.8 % were 
built for low income households, 21.0 % for medium income households while 2.2 % 
were built for high income households. Consequently, while the central business 
district such as Ikoyi, Victoria Island and Lagos Island have lost population in absolute 
terms, some areas where the low cost housing estates are located (Alimosho, Kosofe, 
Ijeromi-Ifelodun, Amuwo-Odofin, Oshodi-Isolo and Ikorodu LGAs) have expanded 
significantly in terms of population and spatial expansion since the 1980s. Currently, 
Alimosho LGA has the highest population figure (1,277,714) in Lagos State. The 
population figure for Alimosho LGA is close to the total population of Lagos State 
before the development of housing estate in the LGA in the 1970s. 
Also, embargo on employment into the State Civil Service during the period under 
review, led to gross inadequacy in the enforcement of development control edicts. 
Inferring from the interview conducted with the officers of the Lagos State Urban and 
Regional Planning Board, the whole of Lagos State had less than 30 Town Planners to 
oversee physical planning and urban development from early 1980s till late 1990s. 
These situations were further compounded in the 1980s and 1990s by the downward 
spiral of the Nigeria‟s economy. Accordingly, accompanying the physical expansion of 
all the listed housing estate locations characterized by significant population growth 
are haphazard development, urban decay, inadequate infrastructural facilities and 
services. However, it could be argued that with the coming of democratic governance 
in 1999, there has been significant residential real estate investment in the study area. 
In addition to this, with the advent of the new housing policy in 2002, the private 
sector has embarked on residential housing projects in Lagos State to meet the ever-
increasing housing needs of the residents.  
Most of the housing units built by private companies, due to the economic 
consideration and the urge for short term recoupment of investment and speedy 
replication of housing stock have been offered almost exclusively to the medium and 
high income families. Thus, as noted by Alabi (2011), the spatial distribution of 
organized private sector housing estates indicated that significant number of the estates 
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is located along Lagos-Epe Express Way. Accordingly, the private sector housing 
support is in the areas far removed from the deprived or informal neighbourhoods. 
Surprisingly, the bulk of such investment took place in areas that lost a significant 
share of their population judging from the 1991 and 2006 census figures. From this 
development, there seems to be a disconnection between housing production by private 
companies and the strong dynamics of population growth in the study area‟s informal 
settlement locations (Torres, et al 2007; Alabi, 2011).  
Therefore, contrary to the benefits expected from the housing-for-all policy of the 
second republic administration, the demographic growth associated with the provision 
of affordable housing resulted in the expansion of existing poor and informal housing 
in most parts of Lagos State. Additionally, the benefits accruing from the economic 
expansion of the second republic era to drive developmental agenda were truncated by 
the oil glut of early 1980s and further sapped by the Structural Adjustment Programme 
(SAP) of late 1980s. The oil glut and the Structural Adjustment Programme activated 
the delay effect in infrastructural provision and economic development (most of the 
industrial estates buildings in 1980s are presently being used as warehouses) to meet 
the needs of the expanding city. Consequently, as the city population and physical 
expansion are evolving at geometrical progression, the economic intervention and 
infrastructural facilities and services to support the growth were emerging at arithmetic 
progression. Hence, there is a visible delay in responding to the infrastructural needs of 
the growing population and the expanding Lagos city frontiers. 
As shown in Figure 4.1, the declining population growth areas (Lagos Island, Mushin, 
Surulere, Apapa and Eti-Osa, Victoria Island) decreased from 76.8 % to 5.5 % of the 
total population between 1911 and 2010. However, in 2010, the population of the 
urban fringes (Alimosho Ikorodu, Agege, Ojo, Kosofe, Ifako-Ijaiye, Ajeromi-Ifelodun, 
Epe) increased geometrically to accommodate 73.9 % of the total population of Lagos 
State. In other words, population of Lagos mainland increased by only 32.3 % while 
that of Lagos suburb increased by 87.4% between 1911 and 2010. Without the 
burgeoning contributions, in terms of migration for employment opportunity 
occasioned by the attractive principle and natural increase in population of the urban 
fringe, the urban dynamics of the study area would have maintained a stable 
equilibrium supported by economic growth as postulated by Forrester (1969).  
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Lagos Island Lagos Mainland Lagos Outskirts
 
Figure 4.1 Population trend in Lagos State 1911 -2010 
Sources: Sources: Mabogunje et al, 1978, Mabogunje, 2003; United Nations 
Population Fund (UNFPA) 2007; FGN 2007 census figures (Projection 2010) 
 
 
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4.3 Urban dynamics and vulnerability to disaster:  The nexus 
The research into urban dynamics by Forrester (1969), Alfeld (1995), among other 
urban dynamics proponents, has shown that depressed areas, the most vulnerable to 
disasters in cities, are triggered by low-income housing rather than commonly 
presumed housing shortage. The targeted low income housing and pro-poor urban 
policy without corresponding progressive economic development have combined to 
give incentives to overstretch the existing facilities and services, increase in-migration 
of unskilled workers and expansion of informal settlements to accommodate the 
migrants. Deducing from the examples of the low-income high density housing in 
Lagos State and elsewhere in the developing countries, the low-income groups, by 
default, always use available housing at higher population densities (Alfeld, 1995; 
Ramroth, 2007).  Housing at higher population density, as noted by Myers (2010), 
accommodates more low-income urban population which, in the long run, will have 
direct deleterious effects on economic growth, industrialization and sustainable 
development. 
A social trap is created where low-cost housing and the associated informal settlement 
beckon additional low-income people. Consequently, unemployed people will continue 
to migrate to the city until their numbers sufficiently exceed the available jobs while 
the standard of living declines below the sustainable average (Forrester, 2009). Income 
to the area is significantly low to maintain and support the existing residential 
structures leading to decline in infrastructural facilities and services, overcrowding and 
vulnerability to disasters. Excess low income residential buildings threaten an area in 
two ways: they occupy land so it cannot be used for job - creating buildings, and they 
attract a population that needs jobs (Forrester, 1969). Any change, which would 
otherwise raise the standard of living, only triggered the urban dynamics by taking off 
the economic pressure momentarily and causes population to rise enough that the 
standard of living again falls to the barely tolerable level. Without a self-regulating 
system in place, the condition of the depressed area is further compounded by its 
vulnerability to disasters as shown schematically in Figure 4.2. 
  
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Figure 4.2 Process of urban dynamics and vulnerability to disaster.  
Sources: Adopted from Forrester (1969), Alfeld (1995) 
 
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A powerful dynamic force such as: urban renewal, establishment of industrial estate, 
proactive programme for crime control, will establish equilibrium between all areas in 
total attractiveness as highlighted in Figure 4.2. As used here, attractiveness is the 
composite effect of all factors that cause population movement toward or away from 
an area. If a programme, for instance, the low income housing production makes some 
urban area more attractive, population to the area rises until the component of 
attractiveness is driven down far enough to establish equilibrium. All other things 
being equal, an increase in population of a city will crowd housing, overload job 
opportunities, cause congestion, increase pollution, encourage crime, and reduce every 
component of the quality of life (Agbola, 2005a). Efforts to improve some conditions 
of a city, as shown by the FHA and Jakande Estates programmes, resulted temporarily 
in improved standard of living until other conditions required to sustain the improved 
standard deteriorate to re-establish equilibrium. Thus, the overall condition of urban 
life, for any particular economic class of population, cannot be appreciably better or 
worse than that of the remainder of the country to and from which people may come. 
Therefore, programmes aimed at improving a city can succeed only if they result, 
eventually, in raising the average quality of life for the country as a whole. 
Concentration of population in an urban location undermines cohesiveness and 
inclusiveness of communities and makes government bureaucracy too large. The 
combination of all these, in the long haul, will reduce the quality of life and increase 
vulnerability to disaster. Any proposed programme aimed at improving the quality of 
life and standard of living should, as priority; deal with both the quality of life and the 
factors affecting population growth. For instance, raising the quality of life means 
releasing stress from crowding, reducing pollution, alleviating hunger, and providing 
health facilities and services. But these pressures are the influences that control 
population movement. Therefore, to raise one component of quality of life without 
intentionally creating compensating counter-pressures to prevent a rise in population 
will be self-defeating. 
There are many possible combinations of forces that an urban area can exert. The 
particular combination will determine the population mix and the economic health of a 
city. The depressed areas in Lagos, from available evidence, are created by 
combination of forces in which economic depression (oil glut) that stagnate the overall 
economic development of Nigeria and the attraction syndrome created by provision of 
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excess low income housing in the 1970 to early 1980 led to increasing migration, 
population increase, unemployment coupled with the burgeoning of informal 
settlements as shown in Figure 4.2. To address the situation the civilian government 
(1979 – 1983) introduced Austerity Measures in 1981 while the military government 
implemented the Structural Adjustment Programme (SAP) in 1986. The SAP had a 
negative effect on urban growth and development. The programme led to reduction in 
investments in the urban sector as government drastically reduced the amount spent on 
the provision of social infrastructures. It led to the closure and collapse of many 
industries either due to lack of foreign exchange to import raw materials or inability to 
compete favourably with imported goods due to high cost of production. There was 
also a fall in real urban income, for instance, as noted by Potts (2012) the real wage fell 
by 90 per cent in Nigerian cities especially in Lagos from 1981–1990. However, the 
availability of low income housing (Jakande estates) draws the lowest income group to 
Lagos state, primarily as construction workers including other allied workers (for mass 
housing production) and later as settlers until the migrants exceed the economic 
opportunities of the State that the low standard of living, the frustration, the crime rate, 
expansion to marginal land and vulnerability to disaster counterbalance the housing 
availability.  
  
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Table 4.4 Perception of urban dynamics as a product of low income housing 
LGAs Driven by low income Not driven by low Total  
housing income housing 
Alimosho  176 (62.2) 107 (37.8) 283 (100) 
Mushin  57(38.1) 91 (61.9) 148 (100) 
Oshodi – Isolo 112 (58.6) 79 (41.4) 191 (100) 
Ajeromi – Ifelodun 141(62.7) 84 (37.3) 225 (100) 
Surulere  43 (42.2) 59 (57.8) 102 (100) 
Lagos Mainland 29(45.3) 35 (54.7) 64 (100) 
Kosofe  34 (43.0) 45 (57.0) 79 (100) 
Ikorodu  143 (62.9) 84 (37.1) 227  (100) 
Shomolu 114 (54.5) 95 (45.5) 209 (100) 
Total  849(55.5) 679 (44.5) 1528 (100) 
Source: Field survey, 2011. 
 
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In analysing urban dynamics perception, Table 4.4 shows that 55.5% of the 
respondents were attracted to their present neighbourhood due to the availability of 
low income housing while 44.5 % did not. The first hypothesis which stated that urban 
dynamics is influenced by the availability of low income housing was analysed using 
2 2 
chi square (  ) two-sample text. The calculated  is shown in Table 4.5. As 
2 2 
highlighted in the Table, the calculated   value is 48.4. The table  value at 0.05 
significant level is 15.51. The result of the analysis shows that the association between 
attraction component of urban dynamics and low income housing is significant at 0.05 
confidence level with 8 degree of freedom. This means that the odd of the table 
2
value occurring accidentally is less than 0.05. Therefore, the research hypothesis 
which states that urban dynamics in the study area is significantly influenced by the 
availability of low income housing is accepted 
 
  
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Table 4.5 Test of association between urban dynamics and low income housing 
2 
LGAs O – E / E 
Expected Observed 
Alimosho  157.0 126.0 
Mushin  82.3 65.7 
Oshodi – Isolo 106.2 84.8 
Ajeromi – Ifelodun 125.2 99.8 
Surulere  56.7 45.3 
Lagos Mainland 35.6 28.4 
Kosofe  43.9 35.1 
Ikorodu  126.0 101.0 
Shomolu 116.3 92.7 
Total 48.4 
 2 = 48.4, degrees of freedom = 8, probability = (table value) at 0.05 significant 
level = 15.51 
Source: Derived from Table 4.4 
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Low income housing programmes, done with the best of intentions, as highlighted 
without feasible and functional economic interventions and population control moves 
exactly in the opposite and depressing direction. It draws more low-income people. It 
makes the area differentially more attractive to the poor who need jobs and less 
attractive to those who create jobs. Unfortunately, as the area becomes more destitute, 
pressures rise for still more adjoining low-cost housing as highlighted in chapter 5 on 
land use and land cover change. The consequence is a downward spiral that draws in 
the low-income population, depresses their economic condition, prevents escape, and 
reduces hope. To escape from the social trap created, Ramroth (2007), Myer (2010) 
and Martinez-Viveros and Lopez-Caloca (2010)) the new population equilibrium that 
will develop, with the present political dispensation as epitomized by the present 
administration in Lagos State, should endeavour to differentiate between social and 
economic goods and make some characteristics of the social system to counterbalance 
the additional attractiveness inherent in the State. 
From this development, it is important to note that feasible urban development and 
urban dynamics catalyst should discourage provision of spot low cost - low income 
housing without corresponding replication in other parts of the country, coupled with 
sound economic growth to aid sustainable development and economic viability of any 
given urban environment. For instance, the significance of Eti-Osa and the emergence 
of Lekki to the economy of Lagos State compared to Alimosho, Ikorodu, Amuwo 
Odofin and Kosofe presuppose that pro-poor policy will not only affect the socio-
economic sustainability but will also influence vulnerability patterns and exposure to 
disasters. It may be argued that, in terms of vulnerability to disaster; Eti-Osa and 
Lekki, by virtue of geographic locations, are more vulnerable to flooding and ocean 
surge than the mainland LGAs. However, as discussed in the conceptual framework 
section, disaster risk is a product of hazards and the vulnerability of the community in 
relation to the capacity of the community to cope with the disaster. Thus, the risk of a 
disaster happening depends on: what the hazard is; how vulnerable the community is; 
and how well the community can limit the damage by being prepared and forewarned. 
From all indications, available evidence has shown that high income residential 
districts have higher capacity (socio-economically, politically and psychologically) to 
cope with disasters than the low-income residential neighbourhoods as illustrated in 
subsequent sections. 
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4.4 Conclusion 
The chapter provided an insight into the urban dynamic process. Findings of the 
chapter revealed that the pro poor urban policy of the 1970s – 1980s that provided 
huge amount of housing units for the low income earners. The associated benefits of 
the policy was truncated by the oil glut of early 1980s and further sapped by the 
structural adjustment programme (SAP) of the late 1980s. The inability of successive 
governments to spread the programme across the nooks and crannies of the country 
triggered the present urban dynamics in the State. The association between low income 
2 2 
housing and urban dynamics was tested using chi square (  ). The calculated  48.4 
at 8 degree of freedom is significant at 95 % confidence level (0.5 level). Therefore, 
areas that are losing population happen to be where the larger percentage of 
contemporary housing provision is being developed. The inability of the urban 
manager to meet the demands of the ever increasing population predisposed and 
increases the vulnerability of informal households to disaster. Also, availability off low 
income housing attract more low income earners with in the long run will affects 
economic growth, industrialization and sustainable development. Due to demand for 
urban land and the burgeoning urban expansion, the next chapter, using GIS, captures 
the extent to which land use and land cover have changed, vegetation to urban, from 
1984 – 2010 
  
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CHAPTER FIVE 
LAND USE LAND COVER CHANGE AND FLOOD RISK ASSESSMENT: 
SCENARIO SIMULATION FOR VULNERABILITY ANALYSIS 
5.1 Introduction 
Flood is among the most devastating nature induced hazards in the world claiming 
lives and properties more than other natural phenomena (Ologunorisa and Abawua, 
2005; Khan et al, 2011). In the past decade in Nigeria, thousands of lives and 
properties worth millions of Naira have been lost directly or indirectly to flood yearly. 
In most urban centres of the country, most especially in fast growing towns such as 
Lagos, human population increase, coupled with urban concretisation, streams and 
channel obstruction due to bad waste disposal habit and other human activities in flood 
plains are considered to be the major causes of floods (Ishaya et al, 2011). 
In analyzing extreme events such as flood, many of the critical problems that arise are 
inherently spatial. Whether an analyst is assessing the potential impact of a hazard, or 
an emergency manager is identifying the best evacuation routes during a disaster, or a 
civil engineer is planning a rebuilding effort following a disaster, or an urban planner 
is analyzing the trend in land use and land cover change and associated disasters over 
time, all of these individuals undertake tasks with a strong spatial component. For this 
reason, geographical space is a valuable framework for analyzing and evaluating many 
problems that arise in the context of emergency management. GIS were designed to 
support geographical inquiry and, ultimately, spatial decision making. The value of 
GIS in emergency management arises directly from the benefits of integrating a 
technology designed to support spatial decision making into afield with a strong need 
to address numerous critical spatial decisions. For this reason, new applications of GIS 
in emergency management have flourished in recent years (Cova and Church, 1997). 
5.2 Land use and land cover change 
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There are various techniques for the assessment of flood risk such as assessing 
meteorological parameters, hydrological parameters, socioeconomic factors, and a 
combination of hydro-meteorological and socioeconomic factors along with 
assessment based on geographical information system (Khan et al, 2011). 
Geographical Information System (GIS) is a useful tool to assess flood risk in flood-
prone areas. Recently, GIS technique has been able to unite all the known procedures 
and factors for predicting flood risk (Ologunorisa and Abawua, 2005). Flood risk 
assessment was done to highlight the vulnerability component of the study area. 
The Land Use/Land Cover maps of the study area for 1984 and 2010 were generated 
from the false colour composite imageries. As shown in Figures 5.1 and 5.2, 
Alimosho, Kosofe and Ikorodu Local Government Areas lost a lot of vegetation 
(78.3%) to urban land use as presented in Figure 5.3. Ikorodu and Kosofe Local 
Government Areas also lost some water (8.3%) to urban land use as shown in Figure 
6.4. The Land Use and Land Cover Change trend in the Figures also corroborate the 
impact of the urban dynamics highlighted in Chapter Four. From the trend it could be 
inferred that prior to FESTAC and the 1979 – 1983 Civilian Administration decisions 
to locate Housing Estates in some of the LGAs of interest (Alimosho, Kosofe, Ikorodu, 
and Oshodi-Isolo) a larger chunks of these LGAs were under vegetation as illustrated 
in Figures 5.1 and 5.3. The implementation of the pro-poor housing scheme increases 
the rate of intra- and inter-migration to these LGAs. The increasing population could 
be said to be associated with the attraction principle (provision of housing and 
employment opportunities) of urban dynamics process that in the long haul draws 
more low income household into the LGAs. At this period, availability of open-virgin 
land coupled with inefficiency in the enforcement of Urban and Regional Planning 
Law increase the lateral expansion and compounded deforestation.  
As the pace of growth quickens, each newly constructed building depicts the 
vegetation and fuels more growth. Today, the choice sites have been developed while 
competitions for the remaining land by the medium and high income households has 
pushed price of the remaining land beyond the reach of the poor households. Thus, the 
available land that could be developed by the poor is, more or less, marginal land at 
flood plains. The available flood plains for the poor, due to scarcity of land for 
development are currently being developed by the rich through reclamation of flood 
plain for residential development. This explains the perennial flood of River Ogun 
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destroying lives and property at Kosofe LGA. Also Oke-Afa and Ipaja in Oshodi-Isolo 
and Alimosho LGAs have been experiencing yearly flooding at an increasing rate due 
mainly to settlements encroachment into flood plains and swamps.  
  
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Figure 5.1 Land use and land cover as at 1984 
Source: Author, 2012 
 
 
 
 
 
 
 
 
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Figure 5.2 Land use and land cover as at 2010 
Source: Author, 2012 
  
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Figure 5.3 Loss of vegetation to urban land (1984 -2010) 
Source: Author, 2012 
 
 
 
 
 
 
 
 
 
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Figure 5.4 Reclamation of wetland (1984 -2010) 
Source: Author, 2012 
 
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Land has been reclaimed in these areas to accommodate urban expansion and spatial 
development. Overall, as indicated in Figure 5.5, about 8 % of water bodies were lost 
to urban land use and 55 % of vegetation was also lost to urban land use. This can be 
attributed to the urban dynamic process, the associated attraction and rapid 
urbanization that have taken place in Lagos over the last 30 years. A cursory look at 
Tables 5.1 reveals that the study area has  changed from vegetation - having the 
greatest percentage of the total land use at 46.5 % in 1984 - to urban at 51.2 % within 
30 years. The present situation as relates to land use and land cover change is more 
precarious due largely to human desire for accommodation, ineffective development 
control and inability of government‟s agencies to manage the expansion of 
development into flood plains and natural vegetation zones. 
 
  
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Table 5.1 Statistics of the land use land cover change of the study area 1984 - 2010 
2 2
Land cover 1984 Area (km ) Percentage  2010 Area (km ) Percentage  
Vegetation 393.53 46.5 225.14 26.6 
Built up area  243.72 28.8 432.84 51.2 
Water  208.26 24.7 187.53 22.2 
Total  845.51 100.00 845.51 100.00 
Source: Derived from Figures 5.1 and 5.2 
 
 
  
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Contributors to Urban Land Use 
 
Figure 5.5: Contributors to net change in urban land use 
Derived from Figures 5.3 and 5.4 
 
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5.3 Simulations  
Taking into consideration the elevation and gradient of the study area (Figure 3.1), the 
study developed and simulated flood risk in the advent of a sea level rise of 1 metre 
equivalence of the flood disaster experience in 2011 in Lagos State, and areas with a 
high likelihood to be affected by flood were calculated. Areas with elevation lower 
than 1m were characterized as high risk while areas with elevation higher than 1m 
were characterized as low risk areas for both 1984 and 2010 as presented in Figures 
5.6 and 5.7.  From the analysis, Kosofe, Surulere, Ikorodu and Ajeromi-Ifelodun are 
the most flood prone Local Government Areas. The projected population of these four 
high risk LGAs as at 2010 is 2,671244. The population is more than the total 
population for Bayelsa State which is 1,704515. A substantial number of people would 
be at risk in 2010 than in 1984 due to the change in land use most especially in Kosofe 
and Ikorodu Local Government Areas: the areas that are flood prone were mainly 
covered by vegetation and water in 1984, as highlighted in Figures 5.1 – 5.3, but have 
been urban conurbated and reclaimed in 2010. The trend in urban conurbation still 
exists unabated till date. Currently, more people would be vulnerable to flood in 2012 
than in 2010.  
To simulate another scenario, a sea level rise of 2 metres, similar to excess water 
release from Lagdo Dam, Cameroun induced flood in 2012 affecting 14 States in the 
country was projected. In this case, the elevation used for delineating flood prone areas 
was changed to 2m as shown in Figures 5.8 and 5.10. Oshodi and Alimosho Local 
Government Areas would have had less population at risk in 1984 (Figure 5.8), but by 
2010, the population at risk had increased due to the change in land use form 
vegetation to urban (Figure 5.9). 
Finally, the 2 flood risk layers, 1m and 2m of 2010 were combined by multiplying the 
risk score of each layer and classifying the risk into 3 flood-risk categories: high, 
moderate and low risk as shown in Figure 6.10). In the study area, Kosofe, Ikorodu, 
Ajeromi – Ifelodun, Lagos Mainland and Surulere Local Government Areas are the 
most susceptible to flood while Alimosho is the least susceptible to flood. 
 
  
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Figure 5.6 One metre sea rise flood risk 1984 
Source: Author, 2012 
  
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Figure 5.7 One metre sea rise flood risk 2010 
Source: Author, 2012 
 
  
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Figure 5.8 Two metres sea rise flood risk 1984 
Source: Author, 2012 
 
  
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Figure 5.9 Two metres sea rise flood risk 2010 
Source: Author, 2012 
 
  
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Figure 5.10 Flood risk zone profile 
Source: Author, 2012 
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5.4 Conclusion 
Using Geographic Information Systems to analyse the land use and land cover change 
from 1984 to 2010, the study has shown that about 8% and 45% of water and 
vegetation respectively have been converted to urban land use. Also, vegetation that 
accounted for the greater percentage of the land cover at 46.5% in 1984 has been 
converted urban at 51.2% in 2010. The simulation of flood risk at 1 metre by the study 
indicated that in 1984, most areas at risk were under vegetation. However, by 2010 
Kosofe, Surulere, Ikorodu and Ajeromi-Ifelodun were the most flood-prone Local 
Government Areas. Simulation at 2 metres of flood water indicated that Kosofe, 
Ikorodu, Shomolu. Lagos Mainland, Surulere, Ajeromi–Ifelodun and a larger part of 
Mushin, Oshodi – Isolo and Alimosho due to land use and land cover change would be 
submerged. The next chapter looks at socio-economic indices of respondents, 
household characteristics and available housing facilities and services as predictor of 
vulnerability to disaster. 
  
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CHAPTER SIX 
SOCIO-ECONOMIC STATUS OF RESPONDENTS AND VULNERABILITY 
TO DISASTER 
6.1 Socio-economic status of the respondents 
This chapter highlights the socio-economic status of the respondents, household and 
housing characteristics and the basic infrastructural facilities and services available. 
The variables considered include: neighbourhoood density, age, marital status, gender, 
educational attainment, occupation, income level, household size, type of dwelling 
unit, physical characteristics of building, water, sanitation and hygiene (WASH) and 
waste management strategies.  
A cursory view of the Table 6.1 reveals that Lagos North Senatorial District (Alimosho 
18.5%, Mushin 9.7% and Oshodi Isolo 12.5%) represented 40.7% (622) of the 
respondents while Lagos West Senatorial District (Ajeromi-Ifelodun 14.7%, Surulere 
6.7% and Lagos Mainland 4.3%) accounted for 25.7% (391) of the respondents. The 
remaining 33.6% (515) of the respondents resided in Lagos East Senatorial District 
(Ikorodu14.8 %, Kosofe 5.2% and Shomolu 13.6%). 
In terms of density, as measured by number of houses per square kilometre, 35.7% 
(546) of the respondents disaggregated into 41.9% (296) in Lagos Mainland (LM) and 
30.4% (250) in Lagos Suburb (LS) were living in low density area. About 55.0% (833) 
resided in medium density area representing 43.6% (308) in LM and 63.9% (525) in 
LS; while 9.8% (149) of the respondents, 14.4% (102) in LM and 5.7% (47) were 
residing in the low density area (Table 6.1). To validate the responses of the 
respondents with the study area, Table 6.1 shows that 31.9% (488) of those 
interviewed have been residing in the study area for up to 20 years.  
  
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Additionally, 30.8% (463) of the respondents have been living in the study areas for 
close to 30 years while 22.0% (336) resided in the study area for up to 10 years. Those 
that have been residing in the enumerated areas for close to 40 years were represented 
by 8.6% (135) while those living in the enumerated areas for more than 40 years 
accounted for 6.7% (106). Inferring from the number of years the respondents have 
been residing in the enumerated area, it could be deduced that information given by 
them should be a fair representation of the actual situation on ground. 
 
  
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Table 6.1 Questionnaire distribution, respondents’ density and residency status 
Items Respondents (%) 
LGA Lagos Mainland Lagos Suburb 
Alimosho 0(0) 288(18.5) 
Mushin 148(9.7) 0(0) 
Oshodi/Isolo 196(12.5) 0(0) 
Ajeromi-Ifelodun 0(0) 229(14.7) 
Surulere 106(6.7) 0(0) 
Lagos Mainland 64(4.3) 0(0) 
Kosofe 0(0) 79(5.2) 
Ikorodu 0(0) 226(14.8) 
Shomolu 192(15.6) 0(0) 
Total 706(100) 822(100) 
Density of the area Respondents (%)   
High density 546 (35.7) 296(41.9) 250(30.4) 
Medium density 833 (54.5) 308(43.6) 525(63.9) 
Low density 149 (9.8) 102(14.4) 47(5.7) 
Total 1528 (100) 706 (100) 822(100) 
Duration of residency?    
Up to 10 336 (22.0) 220(31.2) 243(29.6) 
11 – 20 488 (31.9) 245(34.7) 243(29.6) 
21 – 30 463 (30.8) 152(21.5) 184(22.4) 
31 – 40 135 (8.6) 53(7.5) 82(10) 
Above 41 106 (6.7) 36(5.1) 70 (8.6) 
Total 1528 (100.0) 706(100) 822(100) 
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Important social attributes of the socio-economic indices of the respondents considered 
are age, gender, marital status, educational qualification, occupation and income 
classifications. As presented in Table 6.2, the age classifications show that up to 30 
years old were represented by 5.7% (87) with 3.8% (27) and 7.3% (60) in LM and LS 
respectively. Twenty four per cent (368) were 30-40 years old, 20.1% (142) in LM and 
27.5% (226) in LS; 41.3% (631) constituted the 41 – 50 years classification  with 
49.6% (350) in LM and 34.2% (281) in LS.  
The age cohort of while 51 and above accounted for 28.9% (442) classified into 26.5% 
(187) in LM and 31.0% (255) in LS. Also, from the total population sampled, 59.4% 
(908) were male and the remaining 40.6% (442) were female. The marital status of the 
respondents, as shown in Table, shows that 6.7% (103) were single, 6.1% (43) in LM 
and 7.3 (60) in LS; married were represented by 87.8% (1342)  with the percentage 
share in LM and LS represented by 88.0% (621) and 87.7% (721) respectively. The 
widowed, divorced and separated accounted for 2.8% (43), 1.4% (21) and 1.2% (19) 
representing 2.4% (17), 1.8% (13), 1.7% (12) in LM and 3.2% (26), 1.0% (8), 0.9% (7) 
in LS respectively. The inference of the age classifications and the marital status is that 
majority of those sampled were the heads of the family. This further gave credence to 
the quality and reliability of the data obtained from the respondents. 
  
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Table 6.2 Socio-economic indices: age, gender and marital status of respondents 
Items  All respondents (%)  Lagos mainland Lagos suburb 
Age of respondent    
up to 30 87 (5.7) 27(3.8) 60(7.3) 
31-40 368 (24,1) 142(20.1) 226(27.5) 
41-50 631 (41.3) 350(49.6) 281(34.2) 
51-60 287 (18.8) 119(16.9) 168(20.4) 
abv. 60 155 (10.1) 68(9.6) 87(10.6) 
Total 1528 (100) 706(100) 822(100) 
Gender    
Male 908 (59.4) 396(56.1) 512(62.3) 
Female 620 (40.6) 310(43.9) 310(37.7) 
Total 1528 (100) 706(100) 822(100) 
Marital status    
Single 103 (6.7) 43(6.1) 60(7.3) 
Married 1342 (87.8) 621(88) 721(87.7) 
Widowed 43 (2.8) 17(2.4) 26(3.2) 
Divorced 21 (1,4) 13(1.8) 8(1) 
Separated 19 (1.2) 12(1.7) 7(0.9) 
Total 1528 (100) 706(100) 822(100) 
Source: Field Survey, 2011. 
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Analyzing the socio-economic characteristics of the respondent further, Table 6.3 
shows that 3.9% (60) categorised into 3.7% (26) in LM and 4.1% (34) in LS of those 
interviewed had no formal education; 22.1% (337), 20.7% (146) in LM and 24.5% 
(201) in LS had primary/adult education; 10.2% (156) with 6.5% (46) in LM and 
13.4% (110) in LS obtained secondary school certificates. As submitted by the 
respondents, 3.2% (965), 69.1% (488) in LM and 58.0% (477) had obtained post-
secondary school education. This structure of educational attainment shows that the 
literacy level of the respondents is high and majority of those interviewed have 
adequate knowledge to comprehend what the study is all about. Also the education 
profile presupposed that the majority of the respondents should be living in low 
density neighbourhoods as against the housing density observed in Table 6.1.  
Naturally in Nigeria, employment/occupation structure, to a larger extent, is a function 
of education level attained. However, as shown in Table 6.3, from the people 
interviewed, 3.4% (52) disaggregated into 3.0% (21) in LM and 3.8% (31) in LS were 
unemployed, 0.8% (12), 0.7% (5) in LM and 0.9% (7) in LS were artisans; farming 
constituted 4.8% (73), 1.3% (9) in LM and 7.8% (64) in LS were farmers. A higher 
percentage of the respondents (38.3%) 585 break up into 28.8% (203) in LM and 
46.5% (382) in LS engaged in business/trading activities; professionals in different 
fields of human endeavours accounted for 36.1% (552), 48.4% (342) in LM and 25.5% 
(210) in LS. about 10.0% (155) classified into 12.9% (91) in LM and 7.8% (64) in LS 
were public/civil servants; 4.1%  (63), 3.4% (24) in LM and 4.7% (39) in LS were 
retirees while the remaining 2.4% (36) accounted for others activities ranging from 
informal activities to semi-formal occupation classifications.  
However, in terms of income of the respondents as shown in Table 6.3, majority of the 
respondents , 92.1% (1407) with 93.5% (660) in LM and 90.9% (747) in LS earned 
less than N80,000 per month while a fraction, 7.9% (121), 6.5% (46) in LM and 9.1% 
(75)  in LS earned above N80,000 monthly. The consequences of the education, 
occupation and income strata are that majority of the respondents were under 
employed based on the comparison between the number of persons with post-
secondary education and the nature of occupation the respondents were engaged in. 
Also, the income accruing to the respondents monthly could hardly meet the daily 
needs of the majority of the respondents bearing in mind the high cost of living. This 
could have an adverse bearing on the disposable capital and overall standard of living 
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of the respondents while capacity to cope with disasters could also be compromised 
leading to increasing poverty and vulnerability to disasters. 
 
  
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Table 6.3 Socio-economic indices: educational qualification, occupation and 
income 
Items  All respondents (%) Lagos mainland Lagos suburb 
Educational qualification    
None 60 (3.9) 26(3.7) 34(4.1) 
primary/adult education 347 (22.8) 146(20.7) 201 (24.5) 
secondary education 156 (10,2) 46(6.5) 110(13.4) 
post-secondary education 965 (63,2) 488(69.1) 477(58) 
Total 1528 (100) 706(100) 822(100) 
Occupation    
Unemployed 52 (3.4) 21(3) 31(3.8) 
trading/business 585 (38.3) 203(28.8) 382(46.5) 
Artisan 12 (0.8) 5(0.7) 7(0.9) 
Farming 73 (4.8) 9(1.3) 64(7.8) 
civil servant 155 (10.1) 91(12.9) 64(7.8) 
Professional 552 (36.1) 342(48.4) 210(25.5) 
Retired 63 (4.1) 24(3.4) 39(4.7) 
other (specify) 36 (2.4) 11(1.6) 25(3) 
Total 1528 706(100) 822(100) 
Monthly income (Naira)    
Less than 20,000 443 (29.0) 194(27.5) 249(30.3) 
20,001-40,000 435 (28.5) 225(31.9) 210(25.5) 
40,001-60,000 315 (20.6) 154(21.8) 161(19.6) 
60,001-80,000 214 (14.0) 87(12.3) 127(15.5) 
Above 80,001 121 (7.9) 46(6.5) 75(9.1) 
Total 1528 (100) 706(100) 822(100) 
Source: Field Survey, 2011. 
 
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6.2 Housing and household characteristics 
Impact of disaster is significantly related to inherent vulnerability and risk factors in a 
given environment. Therefore, the housing and household characteristics of the 
respondents are expected to play a vital role in determining how safe or unsafe a 
specific environment is for habitation, work and recreation. The housing and 
household features are highlighted in Tables 6.4 and 6.5. 
Table 6.4 reveals that 26.6% (407) of the houses under review, 30.7% (217) in LM and 
23.1% (190) in LS were 0 - 10 years old, 24.1% (263) of the buildings, 24.2% (171) in 
LM and 24.0% (197) in LS were between 11-20 years old. Twenty one to thirty (21-
30) years accounted for 14.6% (223) of the houses, 18.1% (128) in LM and 11.6% (95) 
in LS; 21.7% (332) houses, 18.1% (128) in LM and 24.8% (204) in LS were 31-40 
years ago while 13.0% (198) of the structures, 8.8% (62) in LM and 16.5% (136) in LS 
were erected over 41 years ago. This shows that houses in the study area conformed to 
the successive Lagos State Governments continuous decongestion policy of Lagos 
Island and the attraction of the mainland and the city fringe to intra- and inter-migrants 
due to the availability of land for low income housing as postulated by urban dynamics 
theory. 
Due to the relatively young age of the buildings in the study area, majority of the 
houses were constructed using sandcrete block representing 88.0% (1343) classified 
into 83.9% (592) in LM and 91.4% (751) in LS; 3.8% (59) of the buildings, 5.5% (39) 
in LM an 2.4% (18) in LS were built using stone while 3.8% (59) with 3.9% (28) in 
LM and 3.8% (31) in LS were built with burnt bricks. Mud structures accounted for 
only 2.0% (31) of the buildings, while other materials such as wooden plank, 
corrugated iron sheet among others, were represented by the remaining 0.9% (14). 
Also, the type of housing tenure system indicated that 17.5% (268) of the respondents, 
11.5% (81) in LM and 22.7% (187) were living in their own apartments Owner 
occupiers). A higher  proportion of the respondents 76.8% (1174), disaggregated into 
86.3% (609) in LM and 68.7% (565) were living in rented apartments Thirty-five 
(2.3%), 1.1% (8) in LM and 3.3% (27) were  institutional building while those living 
or squatting in family houses were accounted for only 3.3% (51) of the respondents, 
1.1% (8) in LM and 5.2% (43) in LS. 
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Table 6.4, also, shows that 80.2% (1225) of the houses, 85.7% (605) in LM and 75.4% 
(620) in LS were Brazilian rooming apartment popularly called face-me-I-face you; 
18.4% (281) classified  into 13.3% (94) in LM and 22.7% ( 187) in LS were flat; 
duplex accounted for 0.9% (14), 0.7% (5) in LM and  1.1% (9) in LS while the 
remaining 0.5% (8) were compound buildings/structures.  
The type of dwelling unit identified in the study area had a significant relationship with 
the number of rooms in a given structure. As documented in Table 6.4, the least 
number of rooms in a building could either be found in duplex or flat structures which 
jointly accounted for 19.3% (295) of the dwelling units. Therefore, less than 5 rooms 
were accounted for by 2.2% (34) of the buildings, 0.7% (5) in LM and 3.5% (29) in 
LS; 43.0% (657) of the houses, 35.7% (252) in LM and 49.3% (405) had between 6-10 
rooms. Up to 15 rooms accounted for 19.0% (291) with 15.4% (109) in LM and 22.1% 
(182) in LS; 16-20 rooms were represented by 18.3% (279), 18.8% (133) in LM and 
17.8% (146) in LS. The percentage for 21-25 rooms was 14.7% (215), 27.1% (191) in 
LM and 4.1% (34) in LS while above 25 rooms were represented by 2.7% (42) 
classified into 2.3% (16) in LM and 3.2% (26) in LS. With this high number of rooms 
available in each building especially in LM coupled with the high population density 
inherent in the study area, the carrying capacity of such buildings could be 
compromised leading to building collapse as captured in chapter seven of this study.  
 
 
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Table 6.4 Housing and household characteristics 
Items  All respondents Lagos mainland Lagos suburb 
Age of building    
up to 10 407 (26.6) 217(30.7) 190(23.1) 
11 – 20 368 (24.1) 128(18.1) 95(11.6) 
21 – 30 223 (14.6) 171(24.2) 197(24) 
31 – 40 332 (21.7) 128(18.1) 204(24.8) 
41 and above 198 (13.0) 62(8.8) 136(16.5) 
Total 1528 (100) 706(100) 822(100) 
Material used for wall    
Block 1343 (88.0) 592 (83.9) 751(91.4) 
Mud 59 (3.8) 39(5.5) 20(2.4) 
plank and iron sheets 18 (1.2) 16(2.3) 2(0.2) 
Stone 49 (3.2) 31(4.4) 18(2.2) 
burnt brick 59 (3.8) 28(3.9) 31(3.8) 
Total 1528 (100) 706(100) 822(100) 
Type of house tenure    
owner-occupier 268 (17.5) 81(11.5) 187(22.7) 
Rented 1174 (76.8) 609(86.3) 565(68.7) 
institutional property 51 (3.3) 8(1.1) 27(3.3) 
family house 35 (2.3) 8(1.1) 43(5.2) 
Total 1528 (100) 706(100) 822(100) 
Types of dwelling unit    
rooming apartment 1225 (80.2) 605(85.7) 620(75.4) 
Flat 281 (18.4) 94(13.3) 187(22.7) 
Duplex 14 (0.9) 5(0.7) 9(1.1) 
Compound 8 (0.3) 2(0.3) 6(0.7) 
Total 1528 (100) 706(100) 822(100) 
Number of rooms     
up to 5 34 (2.2) 5(0.7) 29(3.5) 
6-10 657 (43.0) 252(35.7) 405(49.3) 
11-15 291 (19.0) 109(15.4) 182(22.1) 
16-20 279 (18.3) 133(18.8) 146(17.8) 
21-25 215 (14.7) 191(27.1) 34(4.1) 
Above 25 42 (2.7) 16(2.3) 26(3.2) 
Total 1528 (100) 706(100) 822(100) 
Number of households     
up to 5 431 (28.2) 120 (17.0) 311(37.8) 
6-10 704 (46.1) 316(44.6) 388(47.2) 
11-15 204 (13.4) 144(20.4) 60(7.3) 
16-20 172 (11.3) 119(16.9) 53(6.4) 
21-25 12 (0.8) 4(0.6) 8(1.0) 
Above 25 5 (0.3) 3(0.4) 2(0.2) 
Total 1528 (100) 706(100) 822(100) 
Source: Field survey, 2011. 
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Due to the existing high population and higher demand for housing in the enumerated 
area, it is expected that the higher the number of rooms available in a building, the 
higher the number of persons occupying such buildings. This is in consonance with the 
study area‟s evolving urban dynamics process characterized by increasing population 
growth, stagnant economy, high unemployment and pressure on existing 
infrastructural facilities and services. As noted by Torres et al (2007), the ever-
increasing population in the urban low income residential neighbourhood further 
aggravated the existing vulnerability components of the low income high density urban 
suburb. This effect is illustrated succinctly in Table 6.5. From this development, one of 
the key implications of these indices is that the achievement of Millennium 
Development Goal 7, Target 11, especially availability of sufficient living area is 
threatened. In addition to this, the physical condition of the buildings as illustrated, 
also, shows that only 5.8% (88) of the houses, 2.8% (20) in LM and 8.3% (68) in LS 
were in sound/good condition, 86.6% (1324) of the buildings, 92.9% (656) in LM and 
81.3% (668) in LS were in need of minor renovation and maintenance, 7.4% (113), 
4.2% (30) in LM and 10.1%  (83) in LS were due for major renovation and 
maintenance while the remaining 0.2% (3) were in need of one form of renovation or 
another as a result of pressure on the carrying capacity of the buildings. The vivid 
example of this precarious condition could be seen in the majority of the Low Cost and 
or Low Income Housing Estates.    
The setbacks (left, right, rear and front) among buildings peaked at 2-4 metres. In 
terms of drainage to support free flow of storm water, it was observed that 41.3% (631) 
of the respondents‟ buildings sampled, 56.9% (402) in LM and 27.7% (229) in LS 
were provided with drainage channels for surface run off while 58.7% (897) of the 
buildings, 43.1% (304) in LM and 72.3% (593) in LS were without drainage channel. 
Deducing from the buildings that were provided with drainage facility, 46.1% (291) of 
such buildings, 36.1% (145) in LM and 63.8% (146) in LS could facilitate free flow of 
storm water, 53.9% (340) disaggregated into 63.9% (257) in LM and 36.2% (83) in LS 
were totally blocked while 3.5% (23) could hardly allow water to flow through it due 
to siltation by refuse and sand. In summary, majority of the buildings sampled did not 
have optimal and or functional storm water drainage system. The implication of this 
condition is that when it rains, most parts of the study area experienced flooding 
ranging from flash flood to total inundation as a result of inadequate drainage. The 
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stagnant water within most of the existing drainage networks in the study area also acts 
as breeding ground for diseases carrying vectors thereby increasing the vulnerability 
component of the areas to disasters. 
 
  
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Table 6.5 Number of persons per room and housing conditions 
Items  All respondents Lagos mainland Lagos suburb 
Persons per room  
Up to 3 162 (10.6) 5 66(80.2)  788(95.9) 
4 – 6 1354(88.6) 136(19.3) 26(3.2) 
7- 10 9(0.6) 3(0.4) 6(0.7) 
10-13 1(0.1) 0(0) 1(0.1) 
Above 14 2(0.1) 1(0.1) 1(0.1) 
Total 1528(100) 706(100) 822(100) 
Building condition     
Good 88(5.8) 20(2.8) 68(8.3) 
needs minor repair 1324(86.6) 656(92.9) 668(81.3) 
major repair 113(7.4) 30(4.2) 83(10.1) 
others (specify) 3(0.2) 0(0) 3(0.4) 
Total 1528(100) 706(100) 822(100) 
Drainage channel     
Available 631(41.3) 402(56.9) 229(27.7) 
not available 897(58.7) 304(43.1) 593(72.3) 
Total 1528(100) 706(100) 822(100) 
Condition of available  
drainage    
Free and flowing 291(46.1) 145(36.1) 146(63.8) 
Blocked 340(53.9) 257(63.9) 83(36.2) 
Total 631(100) 402(100) 229(100) 
Source: Field survey, 2011. 
 
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6.3 Housing infrastructural facilities and services 
Housing, according to Egunjobi and Alabi (2007), encompasses houses and its 
immediate environment. Therefore, a healthy and well planned residential housing 
neighbourhood should be characterized by functional network of drainage, road, refuse 
disposal system, sanitation, improved and regular water and electricity supply, 
recreational ground among other infrastructural facilities and services. Thus, the 
concept of housing recognizes that occupancy of housing involved the consumption of 
housing facilities and utility services. It is against this backdrop that the data for 
housing facilities and services of the studied area were analysed and presented in 
Tables 6.6 and 6.7 
6.3.1 Water, Sanitation and Hygiene (WASH)  
Almost fifty per cent of the developing world‟s population – 2.5 billion people – lack 
improved sanitation facilities, and over 884 million people still use unsafe drinking 
water sources. Inadequate access to safe water and sanitation services, coupled with 
poor hygiene practices, kills and sickens thousands of children every day, and leads to 
impoverishment and diminished opportunities for thousands more (Brocklehurst, 
2011). Poor sanitation has many other serious repercussions. Children – and 
particularly girls – are denied their right to education because their schools lack private 
and decent sanitation facilities. Women are forced to spend large parts of their day 
fetching water. Poor farmers and wage earners are less productive due to illness, health 
systems are overwhelmed and national economies suffer (UN-Habitat, 2010). Without 
adequate WASH (water, sanitation and hygiene), sustainable development is 
impossible (Brocklehurst, 2011). 
A cursory look at Table 6.6 shows that only 6.9% (105) of those interviewed were 
connected to public pipe borne water. Majority 85.6% (1308) classified into 91.1% 
(643) in LM and 80.9% (665) in LS had overtly or covertly usurped the function of the 
municipal authority by supplying their water needs through personal wells and 
boreholes. About 6.0% (95) with 2,4% (17) in LM and 9.5% (78) in LS accessed water 
needs by patronising street water hawkers (from questionable sources), 1.2% (18) 
sourced water from pond/stream, 0.7% (5) in LM and 1.6% (13) while 0.1% (2) of the 
respondents used a combination of sources to get water for domestic purposes. This is 
in line with the tenet of urban dynamics process which stated that as population 
increases and city expands laterally without corresponding economic growth, the 
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capacity of the urban managers to provide portable water is usually overstressed 
(Martinez-Viveros and Lopez-Caloca 2010).  
As noted by UN-Habitat (2003b), a household is considered to have access to 
improved drinking water if it has sufficient amount of water (50 litres per person per 
day) for family use, at an affordable price (less than 10% of the total household 
income) available to household members without being subjected to extreme effort 
(less than one hour a day for the minimum sufficient quantity). From Table 6.6, most 
of the respondents, 92.3% (1411) disaggregated into 94.1% (651) in LM and 90.8% 
(747) in LS fetched water for domestic needs within their neighbourhood while 7.7% 
(117) break up into 5.9% (42) in LM and 9.1% (75) in LS met their water needs 
outside the neighbourhood. 
From the earlier analysis, majority of the respondents met their water needs 
individually through wells and boreholes. However, to determine the portability of the 
water supplied individually, the distance of well and or boreholes from soak-away or 
refuse dump; as potential contaminant through underground seepage was analysed. 
From Table 6.6, 0.7% (9) of the respondents, 0.6% (4) in LM and 0.6% (5) in LS had 
their wells/boreholes about 10 metres away from either septic tank (soak-away) or 
refuse dump, 51.5%  (787) of the respondents‟, 64.2% (453) in LM and 40.6% (334) 
wells/boreholes were located 11-20 metres away from septic tanks, 10.6% (162) of the 
boreholes and wells, 9.3% (66) in LM and 11.7% (96) in LS were located  21-30 
metres away from contaminants. About 10.0% (152) of the respondents‟ 
wells/boreholes, 6.1% (42) in LM and 13.3% (109) in LS were sited 31-40 metres 
away from contaminants. The wells/boreholes that were located above 40 metres away 
from refuse dump and or soak-away accounted for 27.3% (418) with 19.8% (140) in 
LM and 33.95 (278) in LS.  
The minimum standard from septic tanks (soak-away) and refuse dump according to 
Centres for Disease Control and Prevention (2009) and Advanced Purification 
Engineering Corp (APEC) (2013), ranges between 50 – 100 feet approximately 15.24 
– 30.48 metres. The implication of this is that water from wells/boreholes could be 
contaminated by underground seepage from soak-away or refuse dump taken into 
consideration the distance and the location of such contaminant either uphill or 
downhill in relation to the wells/boreholes as shown in Table 6.6. Thus, contaminated 
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water by soak-away pits and or pit toilets in relation to distance, location and gradient 
of water sources could further increase vulnerability to disease infection and other 
water related maladies. 
Table 6.6 further indicates that 15.1% (231) of the respondents, 11.6% (82) in LM and 
18.1% (149) in LS were using water closets en-suite, 80.6% (1231) were using shared 
water closets among and between households, 85.0% (600) in Lm and 76.8% (631) in 
LS among and between households; 2.8% (43) of the respondents 1.4% (10) in LM 
and 4.0% (33) in LS were using Ventilated Improved pit (VIP) latrine. About 1.0% 
(10) were using pit latrine while the remaining 0.8% (13) did not have sanitary 
facilities. In terms of access and usage of the sanitary facilities, 7.5% (115) of the 
available facilities, 3.8% (27) in LM and 10.7% (88) in LS were shared by 1-2 persons; 
49.4% (755) of the facilities, 54.8% (387) in LM and 44.8% (368) in LS were shared 
by 3-4 persons, 38.2% (583) of the facilities, 39.9% (282) in LM and 36.6% (301) 
were shared by 5-6 persons; while the remaining 4.9% (75) facilities, 1.4% (10) in LM 
and 7.9% (65) in LS were shared by 7 and above persons. The implications of the high 
ratio of persons to facilities as noted by Habitat (2003b), Nwaka (2005) and Agbola, et 
al (2007) include severe and acute public health and sanitation hazards coupled with 
emotional stress and rapid spread of infectious diseases leading to high national health 
care cost and health burden. 
  
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Table 6.6 Water supply, sanitation and hygiene 
Items  All respondents Lagos mainland Lagos suburb 
Main source of water   
tap/piped water 105(6.9)  39(5.5) 6 6(8) 
well/borehole 1308(85.6) 643(91.1) 665(80.9) 
stream/pond 18(1.2) 5(0.7) 13(1.6) 
street hawkers 95(6.2) 17(2.4) 78(9.5) 
Combined sources 2(0.1) 2(0.3) 0(0) 
Total 1528(100) 706(100) 822(100) 
Distance to source of water    
within the compound 165(10.8) 48(6.8) 117(14.2) 
outside neighborhood 117(7.7) 42(5.9) 75(9.1) 
within the neighborhood 1336(81.5) 611(86.5) 624(75.9) 
Total 1528(100) 706(100) 822(100) 
Well distance to contaminants     
0-10m 9(0.7) 4(0.6) 5(0.6) 
11-20m 787(51.5) 453(64.2) 334(40.6) 
21-30m 162(10.6) 66(9.3) 96(11.7) 
31-40m 152(9.9) 43(6.1) 109(13.3) 
41-50m 360(23.6) 126(17.8) 234(28.5) 
above 50m 58(3.7) 14(2) 44(5.4) 
Total 220(14.4) 706(100) 822(100) 
Well location to contaminants    
up hill 203(13.3) 52(7.4) 151(18.4) 
down hill 1025(67.1) 528(74.8) 497(60.5) 
same level 92(6.0) 40(2.6) 52(6.3) 
No response 208(13,6) 86(5.6) 122(14.8) 
Total 1528(100) 706(100) 822(100) 
Toilet facility    
water closet (separated) 231(15.1) 82(11.6) 149(18.1) 
water closet (shared) 1231(80.6) 600(85) 631(76.8) 
VIP latrine 43(2.8) 10(1.4) 33(4) 
Pit latrine 10(0.7) 5(0.7) 5(0.6) 
Bush 13(0.8) 9(1.3) 4(0.2) 
Total 1528(100) 706(100) 822(100) 
Person(s) per toilet facility    
1-2 115(7.5) 27(3.8) 88(10.7) 
3-4 755(49.4) 387(54.8) 368(44.8) 
5-6 583(38.2) 282(39.9) 301(36.6) 
7-8 75(4.9) 10(1.4) 65(7.9) 
Total 1528(100) 706(100) 822(100) 
Source: Field survey, 2011. 
 
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6.3.2 Waste generation and management 
One of the most indispensable but intractable urban services in the developing and 
developed countries is the management of waste generated in cities. The problem is 
further compounded especially in the developing countries by the increasing rate of 
urbanisation. Consequently, the immense and ever-increasing amount of solid waste 
generated have long outstripped the capacity of nature to deal with it naturally and of 
city authorities to collect and dispose waste safely, efficiently and scientifically 
(Agbola and Kasim 2009). 
From the respondents as highlighted in Table 6.7, the waste generated consists mainly 
of bio-degradable household/domestic waste as represented by 89.9% (1367) of the 
respondents classified into 88.0% (621) in LM and 90.8% (746) in LS. Other types of 
waste accounted for 10.1% (155). The wastes generated were collected by both the 
government and private sector agencies. As illustrated in Table 6.7, government 
agencies were responsible for the collection of 81.8% (1250) of the waste, 87.4% (617) 
in LM and 77.0% (633) in LS; 14.2% (217) of the waste were collected by organized 
private collectors, 8.2% (58) in LM and 19.3% (159) in LS. Local cart pushers 
collected 3.7% (56), 4.0% (28) in LM and 3.4% (28) in LS while the remaining 0.3% 
(5) were burnt, converted to compost and or reused. 
The holistic management of solid waste is a major challenge waiting for proactive 
solution from municipal authorities in Nigeria (Agbola and Kasim, 2009). The 
challenge is often manifested mainly at the point of collection and in the frequency of 
collection and disposal methods. As highlighted in Table 6.7, only 1.4% (21) of the 
respondents had their waste collected daily, 1.6% (11) in LM and 1.2% (10) in LS; 
3.2% (49) admitted that the waste was collected twice a week, 87.0% (1330) of the 
waste generated by the respondents, 89.1% (629) in LM and 85.3% (701) in LS was 
collected weekly while 8.3% (128) of the respondents 5.5% (39) in LM and 10.2% 
(84) in LS had their waste collected irregularly without a fixed pattern or duration of 
collection. The implication of this for urban vulnerability, as noted by Veenhuizen 
(2006), is that solid waste is population dependent, therefore, the general consensus is 
that as the urban population continues to grow rapidly, the heap of wastes generated 
will lower the aesthetic value of the urban environment, pollute land, air and water, 
serve as breeding ground for disease-bearing vectors thereby increasing the 
vulnerability component of the urban environment to disasters 
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When the wastes generated were not collected or there were delays in collection, the 
people interviewed had their waste disposed using the following methods: 3.6% (55), 
4.5% (32) in LM and 2.8% (23) in LS of the waste generated were dumped it in mostly 
illegal communal dumps; 64.9% (992) disaggregated into 75.1% (530) in LM and 
56.2% (462) in LS used any available bush or unprotected open spaces, 7.2% (110) 
with 8.6% (61) in LM and 6.0% (49) in LS deposited waste in the drainage and or 
stream channels; 19.4% (296) of the respondents 10.2% (72) in LM and 27.3% (224) 
in LS burnt the waste in communal open space. The remaining 5.0% (75) of the 
respondents adopted the use of road kerbs and shoulders as waste dump sites. 
Accordingly and due to the shortcoming to effectively manage waste generated, urban 
waste remains a serious problem that could, on one hand contaminate the soil and 
water bodies, encourage disease outbreak and endanger human health and the 
environment. On the other hand, those dumped within the drainage and stream 
channels compounded the perennial flooding experienced in the study area 
(Osuntokun, 1997).  
  
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Table 6.7 Waste generation and management 
Items  All respondents Lagos mainland Lagos suburb 
Types of waste generated   
Household waste/domestic waste  1367(89.9) 6 21(88)  746(90.8) 
Others (non-biodegradable) 161(10.1) 85(12.0) 76(9.2) 
Total 1528(100) 706(100) 751(100) 
Method of waste collection    
government agency 1250(81.8) 617(87.4) 633(77) 
organized private collector 217(14.2) 58(8.2) 159(19.3) 
local chart pushers 56(3.7) 28(4) 28(3.4) 
others (specify) 5(0.3) 3(0.4) 2(0.2) 
Total 1528(100) 706(100) 822(100) 
Frequency of collection    
Daily 21(1.4) 11(1.6) 10(1.2) 
twice a week 49(3.2) 22(3.1) 27(3.3) 
Weekly  1330(87.0) 629(89.1) 701(85.3) 
Irregularly  128(8.3) 44(6.2) 84(10.2) 
Total 1528(100) 706(100) 822(100) 
Disposal of wastes not collected    
Communal dumps 55(3.6) 32(4.5) 23(2.8) 
In the bush/open space 992(64.9) 530(75.1) 462(56.2) 
Water drainage/stream/canal  110(7.2) 61(8.6) 49(6) 
burnt in a communal open space 296(19.4) 72(10.2) 224(27.3) 
road side or median 75(5.0) 8(1.1) 54(6.6) 
Total 1528(100) 706(100) 822(100) 
Source: Field survey, 2011. 
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The second hypothesis which stated that vulnerability to disasters is not a function of 
socio-economic indices, housing characteristics and provision of infrastructural 
facilities and services; was analyzed using multivariate logistic regression model. 
Table 6.8 presents the result of the logistic regression predicting vulnerability with 
respondents‟ socio-economic indices, housing characteristics and provision of 
2 
infrastructural facilities and services. The result R shows that about 40% of the 
vulnerability to disaster attributes can be explained by socio-economic indices, 
housing characteristics and provision of infrastructural facilities and services. The 
analysis shows that the model‟s fit is acceptable while the overall model fit is 
significant at the 1% level of confidence. Therefore the hypothesis: vulnerability to 
disasters is a function of socio-economic indices, housing characteristics and provision 
of infrastructural facilities and services is significant at 95% confidence level. 
From Table 6.9, it can be deduced that socio-economic indices of the respondents play 
important role in determining the vulnerability to disaster. Analysis from the Table 
shows that as age of respondents‟ increases, occurrence of flood increases by 1% while 
occurrence of building collapse and fire outbreak significantly reduce 6% and 3% 
respectively. For disease outbreak, as age increases; the occurrence of disease 
significantly increases by 3%. All these could be attributed to lack of safety-nets and 
social security package for the elderly, reduced opportunity for employment and 
capacity to undertake arduous job by the aged and unsustainable pension returns for 
the retirees. Thus, the elderly have a decreased ability to engage in livelihood activities 
and this creates a reliance on family and kinship networks, though due to sheer poverty 
and lack of material resources, the support these networks provide can be weak and 
can lead to destitution.  From this development, it is possible to infer that as age 
increases, the capacity for sustainable economic opportunity decreases, therefore, the 
capacity to inhabit choice location not liable to disaster reduced while the most viable 
options available are areas and or locations vulnerable to disaster.  
Analyzing the marital status and its effects, it is observed that singles whether 
widowed, divorced or separated are more exposed to disaster than married. For 
instance, from Table 6.9, the probability for a widowed and divorced/separated to 
inhabit building liable to collapse increase significantly by 370% and 240% 
respectively compared to the base category. Also, respondents that are either divorced 
or separated marital status have increased odd of experiencing flood and disease 
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outbreak by 587% and 620% respectively in relation to married, that base group. This 
observation is attributable to lower socio-economic status of most single-headed poor 
households. Evaluating the analysis on employment characteristics using business men 
and women as base, the Table shows that the odd for professional to inhabit area 
vulnerable to flood increases significantly by 85%, retired persons susceptibility to fire 
outbreak increases by 1000%. However, the likelihood of disease outbreak 
significantly reduces for artisan, civil servant and retired by 55%, 42% and 48% 
respectively as shown in Table 6.8. Also from the regression analysis, the number of 
person in a household has both negative and positive relationship with occurrence of 
disaster. For instance, as household number increases, the likelihood of occurrence of 
flood increases significantly by 9%, the probability for fire outbreak increases by 82% 
while occurrence of building collapse increases by 12%. Therefore, one can infer that 
as the number of persons per household, the disposable income available to household 
decreases.  
Education is also found to influence hazard and disaster patterns. In term of disasters 
occurrence, the likelihood of flood increases significantly by 53% for those with 
primary education and reduces for those with secondary education by 76% compared 
to those with tertiary qualification. Also, the probability for fire outbreak and building 
collapse decreases with education attainment. For instance, it is shown that those with 
no education are about 3 times more likely to experience building collapse than those 
in the base category (tertiary); in other words, no education raises the odd of building 
collapse by about 300%. Equally, from the analysis, the probability of those with 
secondary education experiencing fire outbreak increases by 473% over those with 
tertiary qualification, the base category. Furthermore, evaluating the impact of income 
on vulnerability to disaster, it is observed that as household‟s income increases 
probability of it residing in area liable to flooding decreases by 57% and the odd for 
disease outbreak reduces by 31%. This established strong relationship between 
household‟s income and choice of place of residence in relation to flood occurrence.  
With increasing population, exposure to hazards is, also, increasing. This phenomenon 
is compounded by dense concentration of population in often-unsafe human 
settlements. Urban centres were usually built on accessible locations with inherent 
risks such as coastlines to facilitate transport, or flood plains. Urbanization and 
increasing competition for land, results in unregulated construction that invariably 
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spills into adjacent high-risk areas such as hillsides, low laying areas, industrial areas 
or right off ways. Thus, in Lagos State it is observed that there is positive correlation 
between the socio economic characteristics and vulnerability to disaster. The poor 
tends to live in disaster prone areas, which are the least expensive, and the only 
residential site available to them (Ojo, 2013). 
As noted in Chapter 4, the inability of the State to effectively enforce development 
control component of the Urban and Regional Planning Law in the 1980s to 1990s 
coupled with increasing population, predisposed the study area to disasters. Therefore, 
with reference to age of building as determinant of vulnerability, it is shown from the 
regression analysis that as age of building increases, the occurrence of disaster 
increases by 5% and 7% for flood and building collapse respectively due to the 
inability of the urban managers to maintain the existing drains that have been silted up 
with wastes and pressure on carrying capacity of aging buildings.  
 
 
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 Table 6.8 Logistic regression diagnostic tests for socio-economic indices, household characteristics and housing facilities 
and services 
 Flooding Fire outbreak Building collapse Disease outbreak 
2
Wald (X ) 650.420*** 462.663*** 335.817*** 518.453*** 
2
Pseudo-R  0.473 0.706 0.524                0.384 
-2 Log Likelihood 1365.056 243.655 386.749               159.297 
Percent correctly classified 79.5 97.3 95.5                  74.5 
  Source: Field survey, 2011. 
 
  
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  Table 6.9 Logistic regression results predicting disasters on socio-economic indices  
 Flooding Fire outbreak Building collapse Disease outbreak 
Coeff. (B) Odd Ratio Coeff. (B) Odd Ratio Coeff. (B) Odd Ratio Coeff. (B) Odd Ratio 
 Age     0.005** 1.005 -0.066*** 0.936 -0.039** 0.961 0.026*** 1.026 
Male (Female)  0.217 1.243 0.199 1.22 0.967*** 2.63 0.202 1.224 
Single (Married)  -0.446 0.64 -1.927** 0.146 -0.153 0.858 0.023 1.023 
Widowed  0.896 2.451 1.122 3.071 1.547** 4.7 -0.503 0.605 
Divorced/Separated  1.928*** 6.874 0.735 2.086 1.176* 3.242 1.976*** 7.214 
Unemployed (Business)  0.383 1.467 1.28 3.598 -0.686 0.504 -0.672 0.511 
Artisan/Farming  0.196 1.216 0.086 1.09 0.254 1.289 -0.787*** 0.455 
Civil Servant  -0.338 0.713 -0.873 0.418 0.897 2.451 -0.559** 0.572 
Professional  0.616** 1.851 0.411 1.509 0.459 1.583 -0.352 0.703 
Retired  -0.435 0.647 2.405** 11.081 0.264 1.302 -0.652* 0.521 
Persons Per Household  0.088** 1.092 0.202* 1.817 0.114** 1.121 0.025 1.025 
Education None (Tertiary)  0.297 1.346 1.242 3.463 1.299* 3.665 0.783 0.457 
Education Primary  0.423* 1.526 1.072* 2.92 0.769 2.158 0.248 1.281 
Education Secondary  - 1.448*** 0.235 1.746*** 5.732 0.822 2.275 -1.156*** 0.315 
Income  -0.84*** 0.432 -0.201 0.818 0.409 1.505 -0.368** 0.692 
Note: *, **, *** Depict sig nificance at 10 %, 5 % and 1 % respectively. Reference category in brackets 
 Source: Field survey, 2011. 
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From the results on types of dwelling units, as shown in Table 6.10, using rooming 
apartment as base, it is observed that the occurrence or odd of fire outbreak is about 3 
times more likely to occur in flat apartment than those in the base category (rooming 
apartment).  Smith, (2004), opines that as socio-economic status increases, the allure of 
residing in area liable to flood also increases. Therefore, the results from the analysis 
show that flood disaster increases significance by 27,830% for those households 
residing in duplex than those residing in rooming apartment. The explanation of this is 
that most of the high income residential neighbourhoods are built in reclaimed flood 
plain thereby increasing the vulnerability component of such environment to flood. 
There is also significant reduction in the likelihood of building collapse in flat 
apartment by 60% than those in rooming apartment. However, residing in block of 
flats increases the likelihood of disease outbreaks by 50% over those in the base 
category (rooming apartment). The outcomes of this analysis validate the importance 
of attraction of water bodies for human settlement and the significant contribution of 
inundating water as a major causal factor of other hazard such as disease outbreak, 
flooding, building collapse, erosion, and general land degradation. 
The analysis also captures the number of rooms in a building and the number of 
persons per room and their effects on disasters. From the results, as number of rooms 
increases, flooding reduce by 3% while likelihood of disease outbreak increases by 2% 
with increasing number of rooms. From the Table it is shown that as the number of 
persons per room increases, the probability of flood disasters decreases significantly by 
16% and also increases significantly by 89% for disease outbreak. In terms of material 
used for construction, using sandcrete block as base, it is observed that other building 
materials like mud, iron sheet, plank and tarpaulin double the probability for flood, fire 
out break and disease outbreak significantly by 53%, 49% and 43% respectively. The 
listed building materials are, most often than not, associated with informal housing and 
are seen as relic of poverty, hence, there is an observed strong relationship between 
such materials and disaster occurrence. It is also important to note that non-sandcrete 
block building materials has no significant effect on building collapse. This infers that 
when makeshift building or structure collapsed it is seldom a disaster but a normal and 
expected occurrence. 
Availability of functional and adequate drainage network contributes to outcome and 
impact of disaster. From Table 6.10, taken non-availability of drainage as base free 
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flowing drainage reduces the probability of flood significance by 63%. Blocked 
drainage also reduces the likelihood of flood significantly by 42% compared to where 
there is no drainage. The stagnant water dammed by the blocked drainage created a 
breeding ground for mosquito and other related water borne disease. From the analysis, 
therefore, blocked drainage significantly increases the occurrence of disease outbreak 
by 2% in relationship to the base category. Furthermore, evaluating the result of 
setback to water bodies, it can be deduced that as set back increases (in metre) the 
probability of occurrence of flood decreases significantly by 40%. 
The import of basic infrastructural and housing facilities as physical planning 
requirement in vulnerability analysis in line with the MDGs position on sustainable 
development cannot be over emphasized. It is from this background that the impact of 
improved water, sanitation and hygiene (WASH) and solid waste management on 
disaster vulnerability is presented as follows. Using pipe borne water source as the 
base category, it is observed that odd of disease outbreak increases about 8 times for 
those using boreholes than those in the base category. Furthermore, for disease 
outbreak, the disaster that is most associated with poor hygiene, using water closet en-
suite as base, it is observed that using shared water closet and ventilated improved pit 
latrine (VIP) reduces disease outbreak significantly by 68% while ordinary pit latrine 
increases the probability of disease outbreak significantly by 43% over the base 
category. From this analysis, it could be inferred that ventilated improved pit latrine is 
better than open pit latrine as viable sanitation and hygiene strategy. It is also observed 
that availability of all the types of toilet facilities decreases occurrence of disease 
outbreak. In terms of number of person per toilet facility, it can be deduced that as 
number of persons in a household increases, the odd for disease outbreak also 
increases significantly by 76%. 
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 Table 6.10 Logistic regression results predicting disasters on household and housing characteristics 
 Flooding Fire outbreak Building collapse Disease outbreak 
Coeff. (B) Odd Ratio Coeff. (B) Odd Ratio Coeff. (B) Odd Ratio Coeff. (B) Odd Ratio 
 
Building Age 0.044*** 1.045 0.03 1.031 0.071*** 1.074 0.009 1.009 
Dwelling Flat (Room) -0.258 0.773 1.255** 3.507 -0.924** 0.397 0.407** 1.502 
Dwelling Duplex 3.361** 28.828 -0.008 0.992 -0.786 0.456 0.828 2.288 
Dwelling Compound -0.238 0.789 -19.003 0 -18.093 0 0.342 1.408 
Building Rooms -0.031** 0.97 0.002 1.002 0.001 1.001 0.028** 1.028 
Person Per Room -0.171*** 0.842 0.096 1.1 -0.133 0.875 1.116*** 1.891 
Material Non-Block (Block) 0.427*** 1.533 0.398** 1.488 -0.63 0.533 0.337** 1.431 
Drainage Free (Semi Blocked) -1.127*** 0.324 -0.818 0.441 0.38 1.463 0.251 1.286 
Drainage Blocked -0.551*** 0.577 0.834 2.303 0.726 2.067 1.106*** 3.023 
Setbacks -0.518*** 0.595 -0.093 0.912 0.19 1.209 -0.098 0.907 
Note: *, **, *** Depict significance at 10 %, 5 % and 1 % respectively. Reference category in brackets 
 Source: Field survey, 2011. 
 
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From Table 6.11, the analysis from waste generation and management shows that 
using government collection of waste as base category, private collection of waste 
increases disease outbreak significantly by 150% while cart pusher as manager of 
waste reduces significantly the odd of flood and disease outbreak by 72% and 41% 
respectively in relation to the base category. This highlighted the importance of cart 
pushers as viable scavenging agents that reduces the quantum of waste along the waste 
management spectrum through recovery of reusable and salvageable items from the 
waste generated.   
Explicitly, the likelihood of disease outbreak increases by 51% when waste is managed 
by private sector compared to government. The likelihood of disease outbreak 
decreases also by 59% when managed by cart pusher in relation to government. 
Moreover, the impact of collection arrangement varies for flood and disease outbreak. 
It is noted that daily collection of household waste significantly reduces likelihood of 
flood by 147% while irregular collection increases the likelihood of flood by 62% in 
relation to base category. The result for disease outbreak indicates that daily collection 
decreases the probability of disease outbreak significantly by 66% while irregular 
collection increases probability of disease outbreak significantly by 400% in relation to 
the base category. The implication of this is that as household wastes accumulated 
within a given settlement, without functional management strategy, the vulnerability to 
disaster of such environment increases  
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     Table 6.11 Logistic regression results predicting disasters on housing facilities and services 
 Flooding Fire outbreak Building collapse Disease outbreak 
Coeff. (B) Odd Ratio Coeff. (B) Odd Ratio Coeff. (B) Odd Ratio Coeff. (B) Odd Ratio 
 
Water Tap (Well/Borehole)  0.986** 2.682 0.686 1.985 -0.141 0.868 2.272*** 9.694 
Water Stream -0.1 0.904 -0.364 0.695 -18.749 0  0 1 
Water Hawkers -1.043*** 0.352 -1.139 0.32 0.593 1.809  0.342 1.407 
Toilet Water Separated (En-suite) -0.219 0.803  0.968** 2.633     0.911** 2.486 -0.964*** 0.382 
Toilet Pit -1.615*** 0.199 1.649* 5.201 0.418 1.519 -0.966* 0.381 
Toilet Pail/Bush -1.317** 0.268 1.231 3.426   1.423* 4.151  1.207** 0.436 
Person Per Toilet  0.523*** 1.686 -0.695** 0.499      -0.068 0.934 1.273*** 0.761 
Waste Private (Government) 0.209 1.232 0.827   2.286 0.832 2.297 0.919** 2.506 
Waste Chart -1.291*** 0.275 -0.235 0.79 -0.403 0.668 -0.523*** 0.593 
Waste Collection Daily (Weekly) -0.904    2.47** -0.654 0.52 -0.284 0.752 -0.064** 1.660 
Irregular Collection 0.469 0.626*** 0.948* 2.581 0.7 2.014 1.61*** 5.001 
Note: *, **, *** Depict significance at 10%, 5% and 1% respectively. Reference category in brackets 
 Source: Field survey, 2011. 
 
 
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6.4  Conclusion 
This chapter highlighted the point that vulnerability to disaster is a function of several 
factors and these include socio-economic indices, housing characteristics, availability 
of infrastructural facilities and services and the attendant urban dynamics processes.  
The findings show that the low-income groups, by default, always use available 
housing at higher population densities (Alfield, 1995; Ramroth, 2007).  Deducing from 
the Chapter, 88.6% of the respondents observed that 4 – 6 persons were living in a 
room. This negates the Millennium Development Goals 7 Target 11 recommendation 
of 2 - 3 persons for the ideal number of persons per room to avoid overcrowding.  
The result of the logistic regression analysis revealed that the model‟s fit is significant 
at 0.05 confidence level. In disaggregating some of the results of the regression 
analysis, the study revealed that the probability of flooding increases significantly by 
53% for those with primary education and reduces for those with secondary education 
certificate by 76% compared to those with tertiary qualification (the base category). 
Also, the probability of fire outbreak and building collapse decreases with educational 
attainment. Equally, evaluating the impact of income on vulnerability to disaster, it is 
observed that as income increases, the probability for flood reduces by 57% and the 
odd for disease outbreak reduces by 31%. The inference from the study depicted that 
the higher the household‟s socio-economic status, the lower the probability of being 
housed in a disaster-prone areas. Thus, there is inverse relationship between the 
household‟s socio-economic status and the probability of being accommodated in 
disaster-prone areas 
The availability of functional and adequate drainage networks contribute to the 
outcome and impact of disaster. From the logistic regression analysis, free flowing 
drainage reduces the probability of flood by 63% while blocked drainage also 
increases the occurrence of disease outbreak by 2% in relationship to the base 
category. Furthermore, evaluating the result of setback to water bodies, it can be 
deduced that as the setback increases (in metre), the probability of occurrence of flood 
decreases significantly by 40%. The next chapter presents the prevailing hazards and 
vulnerability pattern in Lagos State. 
  
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CHAPTER SEVEN 
PREVAILING HAZARDS AND VULNERABILITY TO DISASTERS 
7.1 Introduction 
Although damaging events are classified according to natural and human causes, they 
have to reach certain human effects thresholds, such as death, injury and economic 
loss, before they are identified as disaster. The world has experienced dramatic 
environmental and socio-economic changes in recent decades. Consequently, as noted 
by Yodmani (2001), there has been an exponential increase in human and material 
losses from disaster events, although there were no clear evidences that the frequency 
of disastrous events had increased. However, according to Makoka and Kaplan (2005), 
phenomena such as population growth, rapid urbanization processes, increasing 
poverty, environmental degradation and climate change have affected the social and 
economic development in many parts of the world.  
These phenomena indicate that the rise in disasters and its impact are functions of the 
vulnerability of people all over the world that were induced by the human determined 
path and justified quest for development (Ojo, 2013). It is important to note that 
increase in vulnerability is not uniform (Quarantelli, 2005). There are large variations 
across regions, nations, provinces, cities, communities, socio-economic classes, ages, 
castes and genders. For instance, Yodmani (2001), gives a classic example of 
earthquakes in San Francisco, United States of America and Managua, Nicaragua. 
Earthquake of magnitude 6.4 in San Francisco, California in 1971, a city of over 7 
million people, reported only 58 deaths.  In 1973, an earthquake of magnitude 6.2 in 
Managua, Nicaragua reduced the centre of the city into rubble and killed over 6,000 
people. Similar patterns can be seen in other recent disasters occurrence. 
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7.2 Perception on vulnerability to disasters 
Vulnerability to hazards is a function of several factors including the level of poverty, 
population growth and distribution and the attendant urban dynamics. The conditions 
of human settlements and infrastructure therein, the level of environmental 
degradation, the level of public awareness and public policy on disaster management 
should also be taken into consideration. However, one of the most challenging urban 
planning issues in urban studies and allied disciplines is the increasing rates of growth 
of towns and cities, especially in the developing countries where less planning and 
proactive intervention are done to accommodate such growth in a sustainable manner 
(Agbola, 2005a). 
It is obvious that nature and human induced disasters abound in Lagos State and a 
number of individuals are living in harms ways as manifested in the impact and level 
of destruction associated with yearly flooding and incessant building collapse and fire 
outbreaks as shown in Tables 7.7 and 7.9. However, Table 7.1 elicits reactions from 
the respondents to determine if there was prior information by agencies of government 
prohibiting them from living in any specific part of their neighbourhood. As expected, 
going by the general inefficiency of government‟s Ministries, Departments and 
Agencies (MDAs), only 2.6% (40) of the respondents had prior information while 
97.4% (1488) did not.  
Furthermore, to ascertain if the respondents had an understanding of what constitutes 
hazard or disaster, they were asked to define hazard/disaster. The definitions were 
given as follows: 9.6% (146) defined disaster as something that is risky or misfortune 
like diseases outbreak.  Almost 11% (162) saw it as an unexpected and unpleasant bad 
incidence causing damage to property or suffering to human while 79.8% (1219) 
defined disaster as destruction of lives and properties by natural or human activities. 
However, in terms of vulnerability to disasters, 13.9% (213) people interviewed agreed 
that their environment/locality/houses were vulnerable to one form of disaster or 
another while 86.1% (1341) disagreed. Deducing from the responses, it could be 
argued that the level of public awareness and sensitization campaign about what 
constitute a disaster by MDAs is generally low. 
Table 7.1 shows that only 12.2% (187) of the respondents had experienced disaster 
personally while 87.8% (1341) had not and this is contrary to recorded evidence and 
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physical observations. From this development, it can be deduced that: there is no 
public awareness on the part of governments to educate the inhabitants of hazard prone 
areas about the prevailing hazard; people have short memories of hazard while others 
believed that the prevailing hazard would not turn to disaster in their life time. In 
addition, majority of the people living in hazard-path would hardly give the correct 
position in relation to disaster due to deep skepticism towards researchers; seeing them 
as agent of government especially from the backdrop of recent stance of Lagos State 
Government to demolish houses on flood plain and right of ways to mitigate disaster 
impacts and to reverse the current urban dynamics process. For the purpose of this 
study, prevailing hazards in Lagos State that were analyzed include the following: 
flood, fire, building collapse and diseases outbreak. 
  
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Table 7.1 Perception of respondents on vulnerability to disaster 
Items  All respondents Lagos mainland Lagos suburb 
Vulnerability information    
Information available 40(2.6) 3(0.4) 37(4.5) 
Information not available 1488(97.4) 703(99.6) 785(95.5) 
Total 1528(100) 706(100) 822(100) 
Definition of a disaster    
Something that is risky 147(9.6) 46(6.5) 101(12.3) 
Unpleasant or damaging event 162(10.6) 65(9.2) 95(11.6) 
Destruction of lives/properties  1219(79.8) 595(84.3) 626(76.2) 
Total 1528(100) 706(100) 822(100) 
Is your area vulnerable     
Vulnerable to disaster 213(13.9) 86(12.2) 127(15.5) 
Not vulnerable 1315(86.1) 620(87.8) 695(84.5) 
Total 1528(100) 706(100) 822(100) 
Experienced disasters     
Experienced disaster 187(12.2) 74(10.5) 113(13.7) 
Have not experienced disaster 1341(87.8) 632(89.5) 709(86.3) 
Total 1528(100) 706(100) 822(100) 
Source: Field survey, 2011. 
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7.3  Flood hazard 
Flooding, as noted by Smith (2004), is the most common environmental hazard 
worldwide, after disease and transport accidents. Every year, floods claim around 
20,000 lives and adversely affecting at least 20 million people worldwide, mostly 
through displacement and homelessness (Smith 2004; Hoyois et al 2007). However, in 
addition to deaths from drowning, flood-related mortality includes epidemics; outbreak 
of gastro-intestinal diseases especially in developing countries where sanitation 
standards are low and or not inexistence. Also, the incidence of water-related diseases 
such as typhoid and or malaria could double the initial endemic mortality rate. Hence, 
owing to geographical location and low lying (plain) and coastal nature of Lagos, the 
study area is highly vulnerable to flood associated with both nature and human induced 
hydrological hazard as shown in Table 7.2. 
2
Table 7.2 indicates that close to two-third ( /3) representing 62.9% (961) of the 
respondents, 70.3% (496) in LM and 56.6% (465) in LS had been affected by flood 
while 37.1% (567) were safe from the menace of flood. In terms of frequency of 
occurrence from the total number of respondents that had experienced flood, 14.5% 
(139) experienced flood every time it rains, 85.2% (819) with 85.5% (424) in LM and 
84.9% (395) occasionally experienced flood when it rains while 0.3% (3) of those who 
had experienced flood in their neighbourhoods submitted that the occurrence did not 
follow any defined pattern. As shown in the Table, the impact of the flood to affected 
persons includes injury or death (27.4%), hindrance to mobility (21.1%), destruction of 
property (15.8%), traumatization (12.6%), stagnant foul-smelling water (12.3%), and 
outbreak of diseases (10.8%). 
  
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Table 7.2 Perception of respondents on flood hazard 
Items  All respondents Lagos mainland Lagos suburb 
Occurrence of flooding    
Flood has occurred  961(62.9) 496(70.3) 465(56.6) 
It has not occurred 567(37.1) 210(29.7) 357(43.4) 
Total 1528(100) 706(100) 822(100) 
Frequency of occurrence    
Every time it rains  139(14.5) 72(14.5) 67(14.5) 
Occasionally when it rains  819(85.2) 424(85.5) 395(84.9) 
Without regular pattern  3(0.3) 0(0) 3(0.6) 
Total  961(100) 496(100) 465(100) 
Impact of  flooding    
Traumatic and bad experience  121(12.6) 67(14.8) 54(10.6) 
Caused injury and death 263(27.4) 127(20.0) 136(26.8) 
Destruction of properties 152(15.8) 56(12.4) 96(18.9) 
Stagnant foul-smelling water  118(12.3) 76(16.8) 42(8.3) 
No movements  203(21.1) 84(18.5) 119(23.4) 
Diseases outbreaks 104(10.8) 43(9.5) 61(12.0) 
Total 961(100) 453(100) 508(100) 
Source: Field survey, 2011. 
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Presenting the respondents perception on causes of flood in Table 7.3, natural causes 
such as excessive rainfall ranked highest with 97.0% (932) of the respondents 
affirming it as major cause, human activities such as inadequate drainage network, 
deforestation, building on flood plains, among others ranked second with 91.7% (917), 
act of God ranked third with 20.4% (196) while other causes accounted for 0.1% (1). 
Also, while ranking the vulnerability indices of the study area, location of property in 
hazard prone area (river floodplain, right of way of drainage network) ranked first with 
58.3% (891), this was followed by improper planning or building design with 56.5% 
(863) while inadequacy in the enforcement of flood related laws and policies was 
ranked by 52.2% (797) of the respondents. 
 
  
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Table 7.3 Perception of respondents on causes of flood  
Items  All respondents Lagos mainland Lagos suburb 
Flood as natural disaster    
Natural causes 932(97.0) 489(98.6) 443(95.3) 
Not natural 29(3.0) 7(1.4) 22(4.7) 
Total 961(100) 496(100) 465(100) 
Flood as human induced disaster     
Human induced 881(91.7) 449(90.5) 432(92.9) 
Not human induced 80(8.3) 47(9.5) 33(7.1) 
Total 961(100) 496(100) 465(100) 
Flood as act of God    
Act of God 196(20.4) 81(16.3) 85(18.3) 
Not act of God 765(79.6) 415(83.7) 380(81.7) 
Total 961(100) 496(100) 465(100) 
Other caused of flood    
Others 1(0.1) 1(0.1) 0(0) 
Natural, Human and Act of God 960(99.9) 495(99.9) 465(100) 
Total 961(100) 496(100) 465(100) 
Human induced vulnerability     
Property in hazard prone area 891(58.3) 459(65.0) 432(52.6) 
Improper planning or design 863(56.5) 537(76.1) 326(39.7) 
Inadequacy of laws and policies 797(52.2) 440(62.3) 357(43.4) 
Source: Field survey, 2011. 
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As opined by Blaikie et al (1994) and Wu, et al (2002), vulnerability conditions are 
rooted in historical, cultural, social and economic processes that impinge on 
individual‟s or society‟s ability to cope with disasters and to respond to them. This 
assertion was buttressed when the respondents were asked the reasons why they were 
still living in the house or locality despite the occurrence of flood. As highlighted in 
Table 7.4, 6.7% (64) of the respondents 6.0% (30) in LM and 7.3% (34) in LS 
submitted that nearness to place of work influenced their decision to stay, 10.8% had 
cheap rent, 8.6% (43) in LM and 13.2% (61) in LS as factor influencing their decision 
to inhabit flood prone localities. One hundred and seventeen representing 12.2%, 
10.8% (54) in LM and 13.5% (63) in LS submitted that the houses vulnerable to flood 
they were inhabiting were either to include family or personal house, while 69.7% 
gave reasons ranging from affinity to the neighbourhood, no alternative 
accommodation, nearness to place of worship among others. This is disaggregated into 
74.4% (369) in LM and 66.0% (307) in LS  
As precarious as the vulnerability attributes of the respondents were, only 7.6% of 
them had witnessed measured and interventions by government agencies to prevent 
and mitigate flooding. The interventions include: demolition of building on floodplain, 
clearing of silted drains, repair of roads and construction of drainage by the community 
or government, aimed at combating the menace of flood. About Ninety-three per cent 
of them had been living with the flood hazard without any measure either by 
government or community to ameliorate the vulnerability components of the 
inhabitants and the general environment. Similarly, while some of the respondents said 
that flood could not be mitigated, others gave a list of what could be done to prevent 
the reoccurrence of flood in their neighbourhoods to include: demolition/relocation of 
building from the floodplain 0.9% (13); 91.5% (877) break up into 92.3% (458) in LM 
and 90.1%  (419) in LS affirmed that construction of functional drainage network 
would help to prevent flood and 4.3% (40) of the respondents, 3.6% (18) in LM and 
4.7% (22) in LS voted for non-structural planning methods through development 
control and functional management of the environment such as: flood plain zoning, 
flood plain building code and flood plain buyout programme to prevent the 
reoccurrence of flood. 
  
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Table 7.4 Respondents’ reasons for residing in flood prone area and mitigation 
strategies 
Items  All respondents Lagos mainland Lagos suburb  
Reasons for tenancy     
Nearness to place of work 64(6.6) 30(4.2) 34(4.1) 
Cheaper rent 104(10.8) 43(6.1) 61(7.4) 
Family house 90(9.3) 34(4.8) 56(6.8) 
Personal house 27(2.8) 20(2.8) 7(0.2) 
others (religion, no alternative) 676(70.3) 369(74.4) 307(66.0) 
Total 961(100) 496(100) 465(100) 
Measures to combat flood     
Available measures 73(7.6) 42(8.5) 31(6.7) 
No measure 888(92.4) 454(91.5) 434(93.3) 
Total 961(100) 496(100) 465(100) 
Prevent the reoccurrence    
cannot be prevented 31(3.3) 12(2.5) 19(4.1) 
property relocation 13(0.9) 8(1.6) 5(1.1) 
adequate drainage network 877(91.5) 458(92.3) 419(90,1) 
Planning and management 40(4.3) 18(3.6) 22(4.7) 
Total 961(100) 496(100) 465(100) 
Source: Field survey, 2011. 
 
  
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Plate 7.1 Flood inundated Apapa – Oshodi Express way 
Source: Field survey, 2011. 
 
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7.4     Fire hazard 
It is noted that the four elements that shape cities in the world are: water, air, land and 
fire. Destructive as it may be, fire has been a fundamental force in determining the 
form of cities and the way buildings should be arranged within the cities. For instance, 
today‟s modern city building codes and zoning ordinances contain regulations to 
prevent fire and control its spread (Ramroth, 2007). However, in the study area, a good 
representation of fire situation in the country, incidence of fire would hardly contribute 
to the improvement and or adherence to building codes to prevent the outbreak or 
minimize its impact. The analysis from response on fire outbreaks is given in Table 
7.5. 
Table 7.5 shows that 6.2% (94) of the respondents, 6.7% (47) in LM and 5.7% (47) in 
LS had witnessed fire outbreak in their neighbourhoods while 93.8% (1434), 93.3% 
(659) in LM and 94.3% (775) in LS had no prior experience of fire outbreak. Almost 
10% (9) of such outbreaks occurred in the houses they were residing in, 13.8% (13) 
occurred in close proximity, while 76.6% (72) of the fire outbreaks occurred within the 
localities or neighbourhoods where the respondents resided. The causes of fire in the 
study area were classified into two: human mistakes and natural occurrence. The 
human mistake which accounted for 62.8% (59) and include: mishandling of fire or 
electrical appliances, careless handling of combustible materials especially in the 
kitchens, power surge/high voltage from the Power Holding Company of Nigeria 
(PHCN), faulty power generating sets, improper planning or design, inappropriate and 
or fake building materials and building in close proximity to one another. The natural 
causes represented 37.2% (35) was seen as fire outbreak induced by mostly lightening. 
In addition to this, the frequency of occurrence of fire outbreaks over the years was 
given as once 42.6% (40), twice 8.5% (8) and more than twice 48.9% (46). Also from 
Table 7.5, only 6.6% (101) could recall measures by either the community or 
government to combat fire outbreaks, 87.2% (1332) did not know of any measure 
while the remaining 6.2% (95) of the respondents did not respond to the question. 
 
  
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Table 7.5 Perception of respondents on fire hazard 
Items  All respondents Lagos mainland Lagos suburb 
Occurrence of  fire-outbreak     
It has occurred  94(6.2) 47(6.7) 47(5.7) 
Not occurred 1434(93.8) 659(93.3) 775(94.3) 
Total 1528(100) 706(100) 822(100) 
Location of occurrence    
My house/environment 9(9.6) 6(12.8) 3(6.4) 
Close building/proximity 13(13.8) 0(0) 13(27.7) 
In the neighbourhood 72(76.6) 41(87.2) 31(65.9) 
Total 94(100) 47(100) 47(100) 
Frequency of occurrence?    
Once  40(42.6) 14(29.8) 26(55.3) 
Twice  8(8.5) 5(10.6) 3(6.4) 
More than twice 46(48.9)  28(59.6) 18(38.3) 
Total 94(100) 47(100) 47(100) 
Causes of the fire-out breaks     
Human mistakes 59(62.8) 37(78.7) 22(46.8) 
Natural occurrence (lightening) 35(37.2) 10(21.3) 25(53.2) 
Total  94(100) 47(100) 47(100) 
Measures to combat fire    
Fire extinguisher, fire service 101(6.6) 67(9.5) 34(4.1) 
No measure 1332(87.2) 607(86.0) 725(88.2) 
No response 95(6.2) 32(4.5) 63(7.7) 
Total 1528(100) 706(100) 822(100) 
Source: Field survey, 2011. 
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Analyzing the vulnerability attributes of the respondents to fire outbreak, as shown in 
Table 7.6, 13.5% (207) of the respondents, 13.2% (93) in LM and 13.9% (114) in LS 
agreed that their houses were vulnerable to fire outbreak while 86.5% (1321) of them, 
86.8% (613) in LM and 86.1% (708) in LS did not agree. The response to fire 
outbreak, outside the day-to-day public awareness on preventive measure through the 
mass media, is usually the establishment of Fire Service Stations. By law, each of the 
774 Local Government Areas in Nigeria is expected to establish at least a fire station. 
Table 7.6 reveals that the established Fire Service Stations were in close proximity to 
most of the respondents. Ninety one per cent (1389) of the houses enumerated, 87.3% 
(616) in LM and 94.0% (773) in LS have Fire Stations located between 0 – 2km away 
from them. Within 2 to 4km from Fire Service Stations were represented by 8.3% 
(127) with 12.3% (87) in LM and 4.9% (40) in LS. 0.8% (12) of the houses has the 
Fire Service Stations located outside 4km radius from the respondents‟ buildings.   
However, in terms of response time to fire incidence, 93.8% (1434) disaggregated into 
92.2% (651) in LM and 94.3% (775) in LS affirmed that the response rate/time was 
slow, 4.2% (63) submitted that the response time was appropriate while 2.5% (39) of 
the respondents, 4.3% (30) in LM and 1.1% (9) in LS were indifference to the response 
time. According to them, the response time was not an issue but what was done after 
the arrival of the Fire Service was more important than speed of arrival at the fire 
scene. Comparing the response time to what is obtainable in, for instance, Israel with 
international acclaimed proactive policy and structure on emergency response 
capacity, Lagos state and to a larger extent, the country still has a long way to go. In 
Israel, it had been empirically tested that response time to any emergency had always 
been less than 4 minutes. The country is further working fervently to reduce the 
response time to less than 2 minutes of any emergency incident. This is achievable 
through the principle of neighbourhood emergency response plan. In every 
neighbourhood, there is a specially trained Emergency Response Term (ERT) 
equipped emergency response vehicle to provide the minimum level of response to 
save lives and protects properties immediately an emergency occurred.   
In Nigeria, according to the National Emergency Management Agency (NEMA) 
(2010), the average response time to fire emergency ranges between 1 – 4 hours. This 
is due mainly to the chaotic nature of the Nigerian roads and inaccessibility of most of 
the informal settlements where significant percentage of fire outbreak occurred. 
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However, from the interview conducted with the Lagos State Fire Services, the 
respondent claimed that most of the responses to fire outbreaks in the State were more 
of rescue call rather than actual call to put-off fire outbreak. Thus, Fire Services are 
called when fire outbreak has overwhelmed the capacity of the local volunteers to 
control it. By that time, the impact of the fire would have escalated beyond the ability 
of Fire Services.   
From the percentage of those that agreed that their houses were vulnerable to fire 
outbreak as shown in Table 7.6, 36.2% (75) classified into 30.5% (29) in LM and 
41.1% (46) in LS submitted that nearness to work places informed the continuation of 
their tenancy in the houses, 28.5% (59) of the respondents, 34.7% (33) in LM and 
23.2% (26) in LS represented those that chose cheaper rent; family and or personal 
houses were represented by 22.7% (47) with 22.1% (21) in LM and 23.2% (26) in LS. 
The remaining 12.6% (26) of the respondent chose a combination of stated factors as 
determinant of their residency in areas vulnerable to fire outbreak. 
  
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Table 7.6: Respondents’ response to fire outbreak 
Items  All respondents Lagos mainland Lagos suburb 
Vulnerability to fire hazard?    
Vulnerable  207(13.5) 93(13.2) 114(13.9) 
Not vulnerable 1321(86.5) 613(86.8) 708(86.1) 
Total 1528(100) 706(100) 822(100) 
Distance to Fire Stations     
0 – 2000 metres 1389(90.9) 616(87.3) 773(94.0) 
2001 – 4000 metres 127(8.3) 87(12.3) 40(4.9) 
4001 metres and above 12(0.8) 3(0.4) 9(1.1) 
Total 1528(100) 706(100) 822(100) 
Response time     
Slow 1426(93.3) 651(92.2) 775(94.3) 
Fast 63(4.2) 25(3.5) 38(4.6) 
Indifference  39(2.5) 30(4.3) 9(1.1) 
Total 1528(100) 706(100) 822(100) 
Reasons continued tenancy     
Nearness to place of work 75(36.2) 29(30.5) 46(41.1) 
Cheaper rent 59(28.5) 33(34.7) 26(23.2) 
Family house 28(13.5) 11(11.6) 17(15.2) 
Personal house 19(9.2) 10(10.5) 9(8.0) 
Others: religious, no alternative   26(12.5) 10(10.8) 16(14.0) 
Total 207(100) 93(100) 114(100) 
Fire-outbreak be prevented     
Handling combustible items 371(24.3) 191(27.1) 180(21.9) 
Switched off appliances  347(22.7) 152(21.5) 195(23.7) 
Using fire-resistant material 379(24.8) 138(19.4) 241(29.3) 
Better design of infrastructure  212(13.9) 96(13.6) 116(14.1) 
Adherence of building code  219(14.3) 129(18.3) 90(10.9) 
Total  1528(100) 706(100) 822(100) 
Source: Field survey, 2011. 
 
  
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Plate 7.2 Fire disaster at Euroasia Plaza, 10/12 Breadfruit Street, Lagos 
Source: NEMA, 2012 
  
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Plate 7.3: Newly procured fire tender vehicles and equipment by Lagos State 
Government 
Source: Lagos State Fire Services, 2012 
 
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Table 7.7: Recorded fire outbreaks and number of deaths and properties affected in Lagos State (2008 – June 2012) 
No Location of buildings Local Number of lives and properties Date of incidence 
Government affected 
1 Ladejobi Street, College Road, Ijora Badia Lagos Mainland 1 Building 21st January, 2008 
2 34 Road, 3rd Avenue, Gowon Estate Alimosho 1 Building 21st January, 2008 
3 17, Olu Aina Street Mushin  1 Person Dead and a Building Burnt 6th April, 2008 
4 Alarape Market, Bajulaiye Shomolu  25 shops 8th April, 2008 
5 59, Owodunni Street, Palm Groove Shomolu 3 Buildings 27th April, 2008 
6 Agric Bus Stop, Lagos Road Ikorodu  1 Person Dead, 16 Injured, 7 Vehicles 3rd May, 2008 
and I Motorcycle Burnt 
7 Ojelade Street, Off Ikorodu Road, Fadeyi Mushin 3 Buildings and 31 Vehicles 7th May, 2008 
8 Park E, Nigerian Railway Corporation Lagos Mainland 7 Persons Dead and a Building Burnt 28th June, 2009 
9 341, Oloko Crescent, Ogba Ikeja  1 Person Dead and a Building Burnt 30th May, 2009 
10 Olososun Bus Stop, Kudirat Abiola Way, Ikeja 3 Persons Dead, 10 Injured and 3 3rd July, 2009 
Oregun Vehicles Burnt 
11 113, Isolo Road Ikotun Egbe Alimosho  2 Persons Dead a Building and 25th July, 2009 
Motorcycle Burnt 
12 Afprint Plc, Mile 2, Oshodi Express Way Oshodi – Isolo 10 Persons Dead, 4 Injured and 5th Sept, 2009 
Buildings Burnt 
13 Alinson Close, Agric, Ikorodu Ikorodu 2 Persons Dead and a Building Burnt 22nd Dec., 2009 
14 Shogunle Bus Stop, Shogunle Oshodi – Isolo 1 Person Dead and 3 Vehicles Burnt 19th Feb. 2010 
15 9, Oloje Street, Papa Ajao Mushin  5 Persons Dead and a Building Burnt 5th May, 2010 
16 Near Phoenix Steel Ltd, Ogijo Ikorodu 3 Persons Dead, a Vehicle and 3 11th May, 2010 
Motorcycles Burnt 
17 Bola Ahmed International Truck Terminal Sari- Apapa  8 Tankers 25th May, 2010 
Iganmu 
18 B Close, 21 Road, FESTAC Town Amuwo - Odofin 2 Persons Dead 31st May, 2010 
 
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19 Lagos Ibadan Express Way Close to Otedola Kosofe  25 Persons Dead and 21 Vehicles 15th August, 2010 
Housing Estate Burnt 
20 Mowo Bus Stop, Ikoga, Badagry Badagry 1 Person Dead and a Vehicle Burnt 5th Sept, 2010 
21 17, Owokoniran Street, Ijegun-Egba, Satellite Amuwo – 2 Person Dead and a Building Burnt 15th April, 2011 
Town Odofin 
22 Yaba Access Bridge, Jibowu Lagos Mainland 3 Persons Dead, 13 Injured and 4 21st April, 2011 
Vehicles Burnt 
23 43, Orile Iganmu Apapa 2 Person Dead and a Building Burnt 22nd July, 2011 
24 Durojaiye Street, Off Sowemimo Street, Ojo  2 Person Dead and a building Burnt 8th August, 2011 
Ajangbadi Road, Okokomaiko 
25 1A, Ade Omoruibi Street, Off Ayetoro Street, Surulere 2 Person Dead and a Building Burnt 26th August, 2011 
Aguda, Surulere 
26 44, Ijaiye Street, Off Olayinka Street, Apapa Apapa 2 Person Dead and a Building Burnt 14th October, 2011 
27 86, Dagbolu Street, Idi-Iroko Bus Stop, Ikorodu 3 Person Dead and a Building Burnt 7th December, 2011 
Ogolonto 
28 Apapa – Oshodi Express Way, Mile 2 Oshodi – Isolo 2 Person Dead, a Vehicle and 17th January, 2012 
Motorcycle Burnt 
29 Mile 2 Garage Mile 2 Oshodi – Isolo 3 Persons Dead and 39 Vehicles 17th February, 2012 
Burnt 
30 6A, Fasasi Street, Ashapo, Olodi Apapa Apapa 2 persons Dead and a Building Burnt 21st March, 2012 
31 12/14 Olanuji/Popoola Street, Toyin, Iju Ishaga Ifako-Ijaiye 168 Persons Dead, 12 Injured, a 3rd June, 2012 
Aircraft, 3 Buildings Burnt 
32 44B, Central Mosque Street, Ikota Town, Ajah Eti – Osa 2 Person Dead and a Building Burnt 5th June, 2012 
Source: Lagos State Fire and Safety Services, 2012 
 
 
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 High Density Medium Density  Low Density
Years 
 
Figure 7.1 Analysis of recorded fire outbreaks in neighbourhoods 2008 – 2012 
Source: Derived from Table 7.7 
 
 
 
 
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Number Dead Number  Injured Building Affected Vehicle Affected
 
Figure 7.2 Analysis of fire outbreak and impact 
Source: Derived from Table 7.7 
 
 
 
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From the available data from the Lagos State Fire Services, 32 cases of fire outbreaks 
have been recorded from 2008 to June 2012. It is important to note that the Lagos State 
Fire Services started systematic data recording with the establishment of Lagos State 
Emergency Management Agency (LASEMA) in 2008. As shown in Table 7.7 and 
Figure 7.1, in terms of spatial distribution of fire outbreaks, the frequency of 
occurrence, in the years under review, is highest in the high density neighbourhoods 
which accounted for 81.3% of the incidence, the occurrence at the medium density 
neighbourhoods represented 15.6% while the low density neighbourhood only 
recorded 3.1% incidence of fire outbreak. Figure 7.2 shows the impact of fire outbreak 
in Lagos State. Inferring from the Figure, averagely per year, 52 persons have died, 11 
persons injured, 10 buildings and 25 vehicles were burnt from fire related incidences 
since 2008. 
 
7.5     Building collapse 
Structural disasters are as old as the act of building itself. Architects and urban 
designers have learnt to build through trial and error. Over the centuries, there have 
been improvement but there is still much to learn (Ramroth, 2007). Structural failure in 
buildings, in broad terms, comes in various forms and degrees of severity; the worst of 
which is a collapse. Deterioration or decay, especially of vigour or usefulness of a 
building, can be categorized as a failure of some sort but a total loss of bearing strength 
resulting in a sudden breakdown, physical depletion and or falling apart is termed a 
collapse. Several causes of building failure had been attributed to either natural or 
man-induced phenomena. Human-induced phenomena consist of collapse borne out of 
human‟s negligence in areas such as soil type, building design and planning, 
foundation works, quality of building materials and quality of workmanship. All 
contractors are expected to consider all these points while laying the foundation of a 
building.  
The challenge in most cases is the human error of poor monitoring of works on site. 
The cause of a building failure is unique to each building. Falobi, (2009), summarizes 
the various causes of building collapse to include: the quality of the blocks used, 
quality of concrete used, poor compaction and consolidation of foundation soil and 
weak soil. Other causes are factors such as greed, incompetence, corruption, poor 
planning, inadequate public awareness and education, and limited financial and 
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technical resources while the existing Urban and Regional Planning Laws and 
Building Codes, meant to guide builders were rendered ineffective because of lack of 
political will to enforce same by the Town Planning Authorities. 
A cursory look at Table 7.8 indicates that 6.3% (97) of the respondents had seen 
building collapse in their neighbourhoods while 93.7% (1431) had not witnessed it in 
their localities. The causes of the collapse included sub-standard and or inferior 
building materials accounting for 75.3% (73) of the causes, age of building as a factor 
influencing collapse was given by 14.4% (14) of the respondents while structural 
default, re-modification of building especially adding floors that the original structural 
capacity of the building could not withstand and building on floodplain accounted for 
10.3% (10) of the causes. Furthermore, from the total respondents that had experienced 
building collapse, 55.7% (54) affirmed that it frequently occurred while 44.3% (43) did 
not agree to this. However, in terms of yearly frequency of occurrence, 26.8% (26) 
indicated that it occurred only once in a year, twice per year were represented by 
16.5% (16), 12.4% (12) agreed that building collapsed more than twice in a year while 
44.3% (43) stated that there was no definite pattern to the occurrence of building 
collapse in their neighbourhoods. 
Also, from Table 7.8, only 6.4% (98) had heard of or witnessed any intervention by 
either the communities or government to curb and or prevent the occurrence of 
building collapse. However, to significantly reduce or eradicate the incidence of 
building collapse in the study area, the following suggestion were proffered by the 
respondents: 2.0% (31) highlighted retrofitting and reconstruction using standardized 
building materials; demolition of aged and or structural defective building (urban 
renewal) before they collapse were accounted for by 0.7% (11) of the respondents; 
40.1% (612) submitted that eradication of quack in the building production industry 
would go a long way in eradicating incessant building collapse; adherence to the 
provisions of the building codes were represented by 3.4%; (52) supervision of 
building construction activities by relevant professionals constituted 28.4% (434) 
while monitoring and enforcing adherence to approved building plans were listed by 
25.4% (388) of the respondents as measures to prevent building collapse. For effective 
disaster management, communities must be saddled with stronger role to reduce 
vulnerability to hazard. This would help in merging the disaster reduction strategies 
defined by policy makers with the needs and resources of the local community, where 
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eventually the success and failures of disaster management activities will be tested 
(Yodmani, 2001). 
  
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Table 7.8 Perception of respondents on building collapse 
Items  All Respondents Lagos mainland Lagos suburb 
Building collapse in the locality     
Witness building collapse  97(6.3) 48(6.8) 49(6) 
Has not witness building collapse 1431(93.7) 658(93.2) 773(94) 
Total 1528(100) 706(100) 822(100) 
Causes the collapse    
Materials used was substandard  73(75.3) 41(0.1) 32(0) 
The building is too old 14(14.4) 10(0.6) 4(0.6) 
Others (default, modification) 10(10.3) 4(1.3) 6(0.6) 
Total 97(100) 48(100) 49(100) 
Frequency of building collapse     
Frequently  54(55.7) 33(68.8) 21(42.9) 
Not frequent 43(44.3) 15(31.2) 28(57.1) 
Total 97(100) 48(100) 49(100) 
Frequency of occurrence yearly    
Once  26(26.8) 11(22.9) 15(30.6) 
Twice 16(16.5) 8(16.7) 8(16.3) 
More than twice 12(12.4) 10(20.8) 2(4.1) 
Occurred with no definite pattern 43(44.3)  19(39.6) 24(49.0) 
Total  97(100) 48(100) 49(100) 
Existing measures/intervention    
Interventions have been done 98(6.4) 53(7.5) 45(5.5) 
No intervention 1430(93.6) 653(92.5) 777(94.5) 
Total 1528(100) 706(100) 822(100) 
Curbing building collapse    
Retrofitting and reconstructions 31(2.0) 19(2.7) 12(1.6) 
Demolition defective buildings 11(0.7) 7(1.0) 4(0.5) 
Eradication of quacks 612(40.1) 381(54.0) 231(28.1) 
Adherence to building code  52(3.4) 13(1.8) 39(4.7) 
Supervision by professionals 434(28.4) 176(24.9) 258(31.4) 
Adherence to approved plans 388(25.4) 110(15.6) 278(33.7) 
Total 1528(100) 706(100) 822(100) 
Source: Field survey, 2011. 
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Also from Appendix II, out of 138 buildings that collapsed in Lagos State between 
1978 to July 2013, 77.6% were residential buildings; commercial buildings accounted 
for 13.0% while the remaining 4.9% were institutional buildings and the remaining 
4.5% collapsed buildings were used for religious purposes. In terms of spatial 
distribution of the collapsed buildings, the occurrences of building collapse were 
highest in high density low income neighbourhood. Thus, as indicated in Table 7.9, out 
of the recorded cases of building collapse incidences in Lagos State, 62.3% (86) 
occurred in low income neighbourhood, 29.2% (40) occurred in medium income 
neighbourhoods while 8.5% (12) occurred in high income district. In relation to urban 
dynamics, it could be deduced that as the population of the study area increases, the 
number of collapsed buildings increases. For instance, the numbers of recorded 
collapsed buildings from 1978 – 1990, 1991 – 2000 and 2001 – June 2012 were 31, 38 
and 63 respectively. From this analysis, it could be inferred that as population 
increases, the carrying capacity, the standard of building materials used and expected 
time for completion were compromised leading to increasing rate of building collapse. 
 
It is must be stated that every incidence is unique and must so be treated by adopting 
unique approach and thorough investigation to discover hidden causative factors for 
each occurrence. That structural defects have accounted for greatest number of 
collapses requires further investigation to ascertain the remote causes of such defects. 
High occurrences of collapsed buildings in Lagos Island, Surulere, and Lagos 
Mainland Local Government Areas of the metropolis should not be treated as mere 
coincidence; they were swampy, sand-filled, and reclaimed terrains close to the 
Lagoon. As noted by Oni (2010) detailed study of the geophysical characteristics of 
the soils in all locations of the study area must be carried out urgently to establish their 
compositions and appropriate measures taken if the seemingly stunning prediction in 
this study is to be averted 
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Table 7.9 Analysis of recorded building collapse by residential neighbourhoods 
Year   High density Medium density  Low  density Yearly frequency of collapse 
1983 2 1 0 3 
1984 0 1 0 1 
1985 4 2 1 7 
1986 2 3 0 5 
1987 6 1 0 7 
1988 0 0 0 0 
1989 2 2 0 4 
1990 3 0 0 3 
1991 0 1 1 2 
1992 2 1 0 3 
1993 1 0 0 1 
1994 5 0 0 5 
1995 2 5 1 8 
1996 2 1 0 3 
1997 0 0 0 0 
1998 1 1 0 2 
1999 3 1 1 5 
2000 5 3 1 9 
2001 5 0 0 5 
2002 6 2 1 9 
2003 5 3 0 8 
2004 2 1 0 3 
2005 2 4 0 6 
2006 9 3 2 14 
2007 1 0 0 1 
2008 4 1 1 6 
2009 2 1 1 4 
2010 1 1 1 3 
2011 2 0 0 2 
2012 3 1 0 4 
2013 2 1 1 4 
Total  86 40 12 138 
Source: Derived from Appendix II 
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Plate 7.4 Collapsed residential building at Jakande Estate, Oke Afa, Oshodi Isolo, 
LGA. 
Source: NEMA, 2012 
 
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The third hypothesis was analysed using analysis of variance (ANOVA) technique. 
The hypothesis states as follows: occurrence of disasters differs significantly between 
residential neighbourhoods. The ANOVA technique compared outcome measurement 
(means) between multiple groups. These observed differences are represented by F 
Statistic. After ensuring that the assumptions of ANOVA were satisfied (independence 
of data and approximation of normal distribution for the sampled population) the data 
set for fire outbreak and building collapse contained in Tables 7.7 and Table 7.9 were 
analysed focusing on three groups – low, medium and high densities residential 
neighbourhoods 
The means and standard deviations for the fire outbreak and building collapse are 
shown in Table 7.10. The between and within sample sum of squares as well as 
appropriate degrees of freedom are shown in Table 7.10. From the Table of F 
distribution, the residual degrees of freedom for fire outbreak and building collapse 
give a value of 5.79 at 5% level. The calculated F for fire outbreak and building 
collapse were 77.29 and 17.88 respectively (Table 7.11). Consequently, the hypothesis 
which states that occurrence of disasters differs significantly between residential 
neighbourhoods is accepted. 
  
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Table 7.10 Fire outbreak and building collapse descriptive 
 95% confidence interval for 
mean 
 Std. Std. 
N Mean Deviation Error Lower Bound Upper Bound Minimum Maximum 
Fire outbreak descriptive 
High 5 5.20 .837 .374 4.16 6.24 4 6 
Medium 5 1.00 .707 .316 .12 1.88 0 2 
Low 5 .20 .447 .200 -.36 .76 0 1 
Total 15 2.13 2.356 .608 .83 3.44 0 6 
Building collapse descriptive 
High 29 2.72 2.170 .403 1.90 3.55 0 9 
Medium 29 1.34 1.317 .245 .84 1.85 0 5 
Low 29 .38 .561 .104 .17 .59 0 2 
Total 87 1.48 1.771 .190 1.11 1.86 0 9 
Source: Computed from Tables 7.7 and 7.9 
 
  
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Table 7.11 Fire outbreak and building collapse ANOVA 
 Sum of Squares Df Mean Square F Sig. 
Fire outbreak      
Between Groups 72.133 2 36.067 77.286 0.000 
Within Groups 5.600 12 .467   
Total 77.733 14    
Building Collapse  
Between Groups 80.552 2 40.276 17.884 0.000 
Within Groups 189.172 84 2.252   
Total 269.724 86    
Source: Computed from Table 7.10 
 
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Sequel to the initial analysis of variance, however, it is important to determine whether 
any two groups within the analysis are similar or different. The examination of 
differences between pairs of groups after the global ANOVA analysis is called Post 
Hoc Analysis (least significant differences). In this study, the Tukey‟s Honestly 
Significant Difference was used to determine the minimum difference between the 
means of interest. From Table 7.12 the difference between the means of low and 
medium densities, low and high densities and medium and high densities residential 
neighbourhoods are greater than the least significant differences. The study concludes 
that the difference in mean ranks for building collapse and fire outbreak in the 
residential neighbourhoods differ significantly in virtue at 5% level 
 
  
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Table 7.12 Least significant difference (multiple comparisons) for building 
collapse and fire outbreak 
95% Confidence Interval 
 (I) Density (J) Density Mean Difference (I-J) Std. Error Sig. Lower Bound Upper Bound 
*
High Medium 4.200  .432 .000 3.26 5.14 
*
 Low 5.000  .432 .000 4.06 5.94 
*
Medium High -4.200  .432 .000 -5.14 -3.26 
 Low .800 .432 .089 -.14 1.74 
*
Low High -5.000  .432 .000 -5.94 -4.06 
 Medium -.800 .432 .089 -1.74 .14 
Fire outbreak 
*
High Medium 1.379  .394 .001 .60 2.16 
*
Low 2.345  .394 .000 1.56 3.13 
*
Medium High -1.379  .394 .001 -2.16 -.60 
*
Low .966  .394 .016 .18 1.75 
*
Low High -2.345  .394 .000 -3.13 -1.56 
*
Medium -.966  .394 .016 -1.75 -.18 
*. The mean difference is significant at the 0.05 level. 
Source: Computed from Table 7.10 
 
 
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7.6     Biophysical hazards: Disease epidemics 
As opined by Smith (2004), biophysical hazard covers a wide spectrum of 
environmental risk created by interactions between the geophysical environment and 
biological organisms, including humans. In many developing countries, human disease 
is the most common and also the most deadly environmental hazard. However, in 
Africa, several hazards underlie biophysical disasters with the most common being 
epidemics, mainly vector-borne (particularly malaria) and communicable diseases 
(mainly HIV/AIDS). The OFDA/CRED International Disaster Database (EM-DAT 
2003) show that from 1975 to 2002, epidemics accounted for 32% of the disaster 
occurrences in Africa, followed by flood (27%), drought (21%) and windstorm (9%). 
Other disasters were: insect infestation, famine, earthquake, landslide, wildfire, 
volcano, and, extreme temperature. 
Over the years, as noted by Nuhu (2012), epidemics had killed more persons than other 
disaster agents in Nigeria. Epidemics of infectious disease are easily triggered when 
polluted floods water contaminate drinking water supplies or destroy sewerage 
systems. It is important to note that according to the 1948 Universal Declaration of 
Human Right, everyone has the right to a standard of living adequate for the health and 
well-being of himself and of his family. Today, available evidence shows that in spite 
of overall progress in health field, good housing and healthy living elude billions of 
people (Agbola, et al 2007). Hence, the great equation: “Medical Care Equal to Good 
Health” has been proved wrong. More often than not, availability of medical care does 
not necessarily boil down to better health care delivery. The best estimate is that the 
medical system (doctor, nurse, drug, equipment and hospital) affects about 10% of the 
usual indices for measuring health. These indices include: whether one lives at all 
(infant mortality), how well one lives (morbidity rate) and how long one lives (life 
expectancy). The remaining 90% is determined by factors over which the medical 
system has little or no control on. These factors include individual lifestyle, socio-
economic conditions and physical environment. 
As with other environmental hazards, the effective mitigation of diseases depend on 
replacing public apathy and emergency responses with a strategy aimed at long-term 
control and prevention. Such a strategy as noted by Smith (2004) has several key 
features that include surveillance, disease prevention, treatment and education. Table 
7.13 indicates that only 5.2% (79) of the respondents, 4.1% (29) in LM and 6.1% (50) 
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had benefitted from health related policies, programmes and laws. A huge percentage 
of the respondents, represented by 94.8% (1449) disaggregated into 95.9% (677) in 
LM and 93.9% (772) in LS did not.  Also, in terms of sanitation and other health 
regulations within individual households, 95.2% (1455) of the respondents, 94.1% 
(664) in LM and 96.2% (791) in LS were not aware of day-to-day personal hygiene 
principles that could positively enhanced healthy living as indicated in the Table. 
Due to lack of information to proactively promote diseases surveillance, prevention, 
treatment and education, 72.9% (1114) of the respondents‟ households had suffered 
from one form of ailment or another. In listing the ailments; of the total number of 
households affected, 34.0% (379) had had cholera/diarrhoea, 37.4% (202) in LM and 
30.9% (177) in LS; malaria accounted for 36.2% (403), 39.8% (216) in Lm and 32.7% 
(187) in LS; 22.8% (254) had typhoid break up into 18.4% (100) in Lm and 26.9% 
(154) in LS; measles (chicken and small pox) were represented by 7.0% (78) 
disaggregated into 4,4% (240 in LM and 9.5% (54) in LS. In furtherance to this, Table 
7.13 highlights the rate and or frequency of occurrence of ailments. From the analysis, 
4.9% (55) of the households interviewed, 5.0% (27) in LM and 4.9% (28) in LS 
experienced the ailment frequently; 61.5% (685) with 67.0% (363) in LM and 56.3% 
(322) in LS had it occasionally, while 33.6% (374) classified into 28.0% (152) in LM 
and 38.8% (222) in LS responded that the ailment did not have a definite pattern. 
The high prevalence of diseases notwithstanding, the respondents gave reasons for the 
continuation of tenancy within the neighbourhoods to include: nearness to place of 
work represented by 5.6% (63) with 5.9% (32) in LM and 5.4% (31) in LS; cheaper 
rent accounted for 6.4% (71), 11.4% (62) in LM and 1.6% (9) in LS; family house and 
personal house were represented by 15.6% (173), 14.8% (80) in LM and 16.3% (93) in 
LS; no alternative accommodation accounted for 7.0% (78) with 5.4% (29) in LM and 
8.5% (49) in LS while combination of all the listed reasons accounted for 65.4% (729) 
disaggregated into 62.5% (339) in LM and 68.2% (390) in LS as indicated in Table 
7.13. The spread of disease in recent times has been facilitated by a general breakdown 
in public health operations and facilities. As noted by Arimah (2002), the implication 
of the pattern of development in the developing countries is hinged on assumed 
provision of basic infrastructural facilities and services. The pace of urbanization in 
these countries would pre-suppose an increase in the provision of infrastructures. This 
has not been the case as many cities lack the financial, political and institutional 
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capacity to provide the most basic of the basic infrastructural facilities and services. 
The shortage is widely represented by inadequate supply of potable water, sanitation 
facilities and housing which contribute enormously to risk of ill health and degradation 
of the environment as shown in Table 7.13 
 
  
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Table 7.13 Perception of respondents on disease epidemics 
Items  All respondents Lagos mainland Lagos suburb 
Availability of health policies/laws    
Health related policy is available 79 (5.2) 29(4.1) 50(6.1) 
Not available 1449(94.8) 677(95.9) 772(93.9) 
Total 1528(100) 706(100) 822(100) 
Sanitation or health regulations     
Regulation available 73(4.8) 42(5.9) 31(3.8) 
Regulation not available 1455(95.2) 664(94.1) 791(96.2) 
Total 1528(100) 706(100) 822(100) 
Household members affected     
Affected by disease 1114(72.9) 542(76.4) 572(69.6) 
Not affected by disease 414(27.1) 164(23.6) 250(30.4) 
Total 1528(100) 706(100) 822(100) 
List of diseases experienced     
Cholera/diarrhoea 379(34.0) 202(37.3) 177(21.5) 
Malaria 403(36.2) 216(39.8) 187(22.7) 
Typhoid 254(22.8) 100(18.5) 154(18.7) 
Measles 78(7.0) 24(3.4) 54(6.6) 
Total  1114(100) 542(100) 572(100) 
Frequency of ailment occurrence     
Frequently 55(4.9) 27(3.8) 28(3.4) 
Occasionally 685(61.5) 363(51.4) 322(39.2) 
Does not follow a pattern 374(33.6) 152(44.8) 222(57.4) 
Total 1114(100) 542(100) 572(100) 
Reason for continuation tenancy    
Nearness to place of work 63(5.6) 32(6.1) 31(5.4) 
Cheaper rent 71(6.4) 62(11.4) 9(1.6) 
Family house 72(6.5) 40(7.4) 32(3.9) 
Personal house 101(9.1) 39(7.2) 62(5.6) 
No other alternative 78(7.0) 29(5.4) 49(8.6) 
Others: religious, no alternative  729(65.4) 340(62.7) 389(68.0) 
Total 1114(100) 542(100) 572(100) 
Source: Field survey 2011 
 
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In the survey, as highlighted in Table 7.14, the reasons adduced to influence outbreak 
of diseases include: poor sanitation and blocking of drainage network represented by 
27.0% (412), inadequate personal hygiene accounted for 4.3% (66), overcrowding was 
captured by 0.6% (9), poor general environmental conditions was seen by 27.4% (419) 
as causes of diseases while combinations of the listed caused were recorded by 40.7% 
(622) of the respondents. As opined by World Bank (2001), in African alone, malaria 
associated with standing water and clogged storm drains is responsible for about 
800,000 deaths annually. 
The conditions necessary for disease epidemics often exist before a pathogen is 
introduced into a suitable environment. A disease outbreak can be triggered by various 
events such as over-crowding and poor sanitation but the underlying pre-disposing 
factor is poverty (Smith 2004). Because the pre-conditions for disease epidemics 
abound in the study area, the respondents were asked to proffer prevention and 
mitigation strategies to combat future diseases outbreak. Their submission from Table 
7.14 are given as improved personal hygiene was represented by 27.2% (416); 
improved sanitation accounted for 22.1% (337); reduction in the number of persons per 
room took 27.8% (425); frequent drainage clearing to enhance free flow of water also 
accounted for 12.7% (194). Other strategies which include combination of measures; 
adherence to planning law and building code; fumigation of disease vector breeding 
sites were recommended by 10.2% (156). It is important to note that for effective 
disease control, the government and the community has a lot to do. However, in the 
study area, only 7.9% (120) of the respondents had either heard or seen community 
and or government interventions to mitigate disease hazards through immunization, 
regular sanitation, enactment of health related environmental laws and establishment of 
diseases control agencies. 
  
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Table 7.14 Causes and measures to curb diseases outbreak 
Items  All respondents Lagos mainland Lagos suburb 
Main cause of disease outbreak    
Poor sanitation/blocked drains  412(27.0) 235(33.3) 177(21.5) 
Inadequate hygiene conditions 66(4.3) 29(4.1) 37(4.5) 
Overcrowding 9(0.6) 6(0.8) 3(0.4) 
Environmental factors 419(27.4) 120(17.0) 299(36.4) 
All of the listed causes 622(40.7) 316(44.8) 306(37.2) 
Total  1528(100) 706(100) 822(100) 
Strategies to mitigate outbreak     
Improved personal hygienic 416(27.2) 182(25.8) 234(28.5) 
Improve sanitation 337(22.1) 163(23.0) 174(21.2) 
Reduction in persons per room 425(27.8) 208(29.5) 217(26.4) 
Frequent drainage clearance 194(12.7) 81(11.5) 113(13.7) 
Adherence to planning laws 156(10.2) 72(10.2) 84(10.2) 
Total 1528(100) 706(100) 822(100) 
Measures to combat outbreak     
Immunization 4(0.3) 1(0.1) 3(0.4) 
Regular sanitation 60(3.9) 23(3.3) 37(4.5) 
Enactment of  health related laws  1(0.1) 0(0.0) 1(0.1) 
No response 1463(95.7) 682(96.6) 781(95.0) 
Total 1528(100) 706(100) 822(100) 
Source: Field survey, 2011. 
 
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7.7     Hazards prevention and mitigation approaches 
In the past, disasters were seen as “Act of God” (Zebrowski, 1997; Twigg, 2001; 
Smith, 2004). This perspective suggests that damaging events are divine punishment 
for moral misbehaviour, rather than the consequence of humans‟ improper use and 
exploitation of the earth. This school of thought encouraged a general acceptance of 
disasters as external and inevitable events. However, by 1950 and till date, natural 
hazards analysis had undertaken a paradigm shift. Contemporary study sees disaster as 
physical phenomena linked to countless individuals‟ decision to settle in and develop 
hazard-prone land. Thus, apparent paradox exists between relentless human progress 
and an increased feeling of insecurity. This is because economic development and 
environmental hazards are rooted in the same ongoing progress of change.  As the 
world population grows, more people are exposed to hazard. As urbanization 
intensifies and spreads, more complex and expensive infrastructure can be damaged by 
extreme events. Also, as people and property become concentrated in large cities, the 
chance of very large-scale losses increases. These trends, underpinned by higher per-
capital consumption, impose heavy burdens on precious natural assets, such as land, 
forest and water (Smith, 2004). 
It is impossible to live in a hazard and or risk free environment. Therefore, in theory, 
the safest response to environmental disaster is to avoid all hazards. In practice, 
however, this is impossible largely due to the developmental pressure on land. From 
this development, as noted by Smith (2004), hazard reducing adjustments fall into 
three groups: Mitigation (modify the loss burden through disaster aid and insurance 
programme); protection (modify the event through structural measures in order to exert 
some control over the processes involved) and adaptation (modify human 
vulnerability). Adaptation, as non-structural response, promotes changes in human 
behaviour towards hazards and it also covers community preparedness programmes, 
forecasting and early warning schemes and land use planning. In Nigeria, a plethora of 
Ministries, Departments and Agencies (MDAs) are saddled with the responsibility of 
responding to disaster from the pre-disaster phase (risk assessment, prevention, 
mitigation, preparedness and emergency or contingency plans) to post-disaster phase 
(relief, rehabilitation, reconstruction and learning review). Table 7.15 highlights the 
institutional provision to reduce impact of disaster in Lagos State. 
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Inferring from Table 7.15, only 15.3% (234) of the respondents were aware of existing 
disaster management MDAs in the country while 84.7% (1294) were not aware of any. 
And of the total number of respondents that had heard about disaster management 
MDAs, 28.6% (67) gave the names of the MDAs as National Emergency Management 
Agency (NEMA), Nigerian Security and Civil Defense Corps (NSCDC) accounted for 
0.4% (1), Federal Road Safety Corps (FRSC) was named by 9.8% (23), State 
Emergency Management Agencies (SEMAs) had 0.9% (2), Nigerian Red Cross 
Society (NRS) accounted for 15.4%, (36) while the remaining 44.9% (105) of the 
respondents could not name the responsible MDAs for emergency management in their 
localities. In addition, to the identification of MDAs with disaster management 
mandates, only 37.2% (87) of the respondents affirmed that the MDAs had done some 
activities (distribution of relief materials), relating to disaster management within their 
localities while 62.8% (147) submitted that the MDAs were largely inactive. The lack 
of visibility of most of the MDAs to disaster management is due largely to the failure 
on the part of the MDAs to build disaster management into their yearly budget. Thus, 
rather than been proactive in disaster management most of the MDAs are reactive, 
therefore, when disaster occurs there is less capacity, in terms of financial resource to 
respond speedily and adequately. 
In terms of the MDAs efficiency and effectiveness in carrying out disaster 
management responsibility; 6.7% (102) of the respondents adjudged the MDAs as not 
efficient, 4.5% (69) submitted that they were fairly efficient; efficient and very 
efficient were represented by 3.5% (53) and 0.7% (10) respectively while 84.7% of the 
respondents were indifferent to the efficiency level of the MDAs. Furthermore, 
adjudging from Table 7.15 respondents‟ account of intervention from the MDAs 
during and after disasters; of the total number of persons affected, 66.3% (189) had 
received relief interventions while 33.7% (96) had not. The intervention received, as 
submitted by the respondents, were from individuals and community association 
29.6% (56), NGOs 11.1% (21), Federal Government through NEMA 27.0% (51), State 
Government through LASEMA 22.2% (42), Local Governments 9.0% (17) and 1.1% 
(2) from foreign governments and international organizations.  
From the analysis, it could be deduced that the local community‟s interventions in all 
disaster are always higher than other sources of intervention. This trend could only 
change when the host government declares a state of emergency as a result of disaster 
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to pave way for foreign interventions. Foreign interventions are always huge and in 
most instances higher than what could be provided by the host community and 
government as corroborated by the India ocean tsunami of 2005 and the earthquake 
disaster in Haiti in 2010 with the resulting international assistance. The respondents 
concluded that, to reduce hazards and disasters in their localities individuals and 
community organization as represented by 56.9% (868) had to play important role; 
those that believed it was government responsibility were represented by 37.6% (575), 
NGOs accounted for 5.0% (77) while international organizations accounted for 0.5% 
(2).
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Table 7.15 Institutionalisation of disaster management 
Items  All respondents  Lagos mainland Lagos suburb 
Disasters management agency    
Aware of management agencies 234(15.3) 114(16.1) 120(14.6) 
Not aware of any 1294(84.7) 592(83.9) 702(85.4) 
Total 1528(100) 706(100) 822(100) 
Name of the agency    
NEMA 67(28.6) 38(33.3) 29(24.2) 
NSCDC 1(0.4) 0(0) 1(0.8) 
FRSC  23(9.8) 8(7.0) 15(12.5) 
LASEMA 2(0.9) 1(0.9) 1(0.8) 
Nigerian Red Cross Society 36(15.4) 12(10.5) 24(20.0) 
Could not Name Them 105(44.9) 55(48.2) 50(41.7) 
Total 234(100) 114(100) 120(100) 
disasters managed     
Agencies have intervened  87(37.2) 54(47.4) 33(27.5) 
Agencies have not intervened  147(62.8) 60(52.6) 87(72.5) 
Total 234(100) 114(100) 120(100) 
Efficient/effective of agency     
Very efficient  10(0.7) 4(0.6) 6(0.7) 
Average efficiency 69(4.5) 35(5) 34(4.1) 
Efficient  53(3.5) 23(3.3) 30(3.6) 
Not efficient 102(6.7) 52(7.4) 50(6.1) 
Indifference  1294(84.7) 592(83.9) 702(85.4) 
Total  1528(100) 706(100) 822(100) 
Types of response    
Distribution of relief materials 163(66.3) 75(65.8) 88(73.3) 
No support 71(33.7) 39(34.2) 32(26.7)  
Total 234(100) 114(100) 120(100) 
List of organization    
Individuals/residents and CBOs  56(23.9) 27(23.7) 19(15.8) 
NGOs 21(8.8) 12(10.5) 9(7.5) 
Federal Government of  Nigeria 75(32.1) 31(27.2) 44(36.6) 
State Government 63(26.9) 22(19.3) 41(34.2) 
L.G.A 17(7.3) 12(10.5) 5(4.2) 
International Organization  2(0.9) 0(0) 2(1.7) 
Total  234(100) 114(100) 120(100) 
Stakeholders in prevention    
Individuals  782(51.1) 364(51.6) 418(50.9) 
Community organization  88(5.8) 41(5.8) 47(5.7) 
Government disaster agencies 575(37.6) 237(33.6) 338(41.1) 
NGOs 77(5.0) 63(8.9) 14(1.7) 
International organization 6(0.5) 1(0.1) 5(0.6) 
Total  1528(100) 706(100) 822(100) 
Source: Field survey, 2011. 
 
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7.8 Conclusion 
The chapter highlighted vulnerability to flood, fire outbreak, building collapse and 
disease epidemic. Gleaning from the analysis, it was observed that all residential 
neighbourhoods are vulnerable to disasters but the degree differs Thus It is important 
to note that vulnerability to disaster is a function of capacity to anticipate, cope with, 
resist and recover from the impact of hazard. Consequently households with means of 
production (land, capital and labour) and specialized skills as characterized by low 
density neighbourhoods are the most resilient when disaster strikes. Also, the Chapter 
revealed that out of 32 cases of fire outbreaks recorded from 2008 high density 
neighbourhoods accounted for 81.3% the medium density neighbourhoods represented 
15.6% while the low density neighbourhood only recorded. For building collapse 
incidence from 1970s to 2012, 132 cases have been recorded. Out of the recorded 
cases, 62.3% occurred in low income neighbourhood, 29.2% occurred in medium 
income neighbourhoods while 8.5% occurred in high income district. 
The third hypothesis was analysed using analysis of variance (ANOVA) technique. 
The hypothesis states as follows: occurrence of disasters differs significantly between 
residential neighbourhoods. The calculated F for fire outbreak and building collapse 
were 77.29 and 17.88 respectively. Consequently, the hypothesis which states that 
occurrence of disasters differs significantly between residential neighbourhoods is 
accepted. 
It is impossible to live in a hazard and or disaster free environment due to the 
developmental pressure on land. Therefore, the next chapter documents the plans, 
programmes and activities of the institutionalized disaster management agencies in 
Nigeria and Lagos State with a view to examine their effectiveness in disaster 
management in the study area. 
 
  
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CHAPTER EIGHT 
DISASTER MANAGEMENT INSTITUTIONS IN LAGOS STATE  
 
8.1 Introduction  
Prior to the establishment of the National Emergency Management Agency, 
institutional response to disaster in Nigeria dated back to 1906 when the Fire Brigade 
(now Federal Fire Services) was established. The Fire Brigade functions were beyond 
fire-fighting to saving of lives, property and provision of humanitarian services during 
emergencies. Between 1972 and 1973, Nigeria experienced a devastating drought with 
socio-economic consequences including loss of lives and property worth millions of 
Naira. This made it important for the Government to consider a response body to take 
care of disaster issues. Thus, the National Emergency Relief Agency (NERA) was 
established by Act 48 of 1976. NERA was charged with the task of collecting and 
distributing relief materials to persons affected by disaster. However, the function of 
NERA with regards to Disaster Management was very limited due to its scope. 
To address the narrow scope of NERA, in November 1997, a national workshop was 
organized involving major stakeholders in disaster management in Nigeria including 
oil companies, construction companies, Government and non-governmental 
organizations and representatives of the United Nations Development Programme 
(UNDP).  A communiqué issued at the end of the workshop triggered a paradigm shift 
that stressed the need for restructuring NERA from purely relief activities to total 
management of disasters in the country.  The acceptance of this recommendation led to 
the establishment of the National Emergency Management Agency by the Federal 
Government in 1999 to manage disaster in all ramifications in Nigeria. 
The focus of this section is to x-ray disaster management institutions in Nigeria and 
Lagos State using Disaster Risk Reduction (DRR) and Capacity Assessment (CA). The 
DRR and CA are adopted to identify high points, gaps and challenges the nation and 
Lagos State is facing preventing, mitigating and reducing in natural and man-induced 
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disasters. The assessment is entrenched in the Hyogo Framework for Action (HFA) 
2005 – 2015, could be seen as opportunity to clearly identify existing capacities both at 
national and state levels, to understand desired capacities, and to propose 
recommendations on how they can be further developed and strengthened for effective 
and proactive disaster management in Lagos State. 
8.2 Institutional framework 
The significance of institutional framework in projecting into the future in disaster 
abatement is crucial. The federal government has established several ministries, 
agencies and parastatals with specific purpose in addition to the existing disaster 
networks like non-governmental organisations, private concern and international 
bodies. However, one of the key successes made by the Federal Government of 
Nigeria and Lagos State Government to address disaster management issues in the 
country and at the State level is the creation of NEMA and Lagos State Emergency 
Management Agency (LASEMA). NEMA was established by Act 12 as amended by 
Act 50 of 1999. Currently, with a staff strength of 496 (2012 nominal-roll), NEMA is 
saddled with the mandate of managing, coordinating and formulating policies in all 
related activities of disaster management. NEMA also coordinates plans and 
programmes of relevant stakeholders for efficient and effective response to disasters as 
well as promoting research and development activities as they relate to disaster 
management in Nigeria. NEMA is funded statutorily by the Federal Government, in 
addition, to the mandatory release of 20% of Ecology Fund to the Agency yearly. The 
Ecology Fund is statutorily constituted as 1% of the national budget. The same funding 
arrangement is domesticated at the States level 
Although, LASEMA came into existence in February 2007 but the legal framework 
establishing LASEMA was signed into Law on 22nd July, 2008 to perform the 
activities of NEMA for effective disaster management at the State. LASEMA is 
expected by law, to supervise the functions of the Local Emergency Management 
Committee (LEMC) where they exist. However, according to the interview conducted, 
the Executive Secretary/Director General Lagos State Emergency Management 
Agency, Dr. Femi Oke-Osanyintolu, observed that it has been disheartening to note 
that contrary to the stipulation of LASEMA Established Act, none of the 18 Federal 
Government recognised LGAs and the Development Areas created by the State 
Government has established LEMC as at 2013. Consequently, by default, the 
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emergency management at the LGAs is still being undertaking by LASEMA thereby 
stretching the limited capacity of the Agency to mitigate and respond efficiently to 
disasters.    
Disaster Management is the coordination and integration of all activities necessary to 
build, sustain and improve the capability to prepare for, protect against, respond to and 
recover from threatening or actual natural or human-induced disasters. It is a multi-
jurisdictional, multi-sectoral, multi-disciplinary and multi-resource initiative as shown 
in Figure 8.1. Disaster Management is also the coordination and integration of all 
activities necessary to build, sustain and improve the capability for disaster prevention, 
mitigation, preparedness, response and recovery. (NEMA, 2012a) 
  
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Figure 8.1 Disaster management coordination systems in Nigeria 
Source: NEMA: National Disaster Management Framework (2012b) 
 
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8.3 The agencies and disaster management 
Disaster management being a multi-jurisdictional, multi-stake holding, multi-
disciplinary, multi- resource endeavour, requires elaborate policy, procedures, systems 
and guidelines to ensure seamless coordination and collaboration. The Agency 
deriving its legitimacy from its enabling law, in collaboration with relevant 
stakeholders, has developed policies, procedures and systems for disaster management 
in Nigeria, in line with global best practices.  
Since the Hyogo Conference in 2005, the Agency as part of her mandate to manage 
disasters has been in the fore front in integrating the principle of disaster risk reduction 
into the developmental agenda of Nigeria. In addition to this, series of initiatives had 
been proposed that focus on the need for pre-disaster analysis. In Nigeria, pilot 
programmes for VCA in Kaduna, Benue, Adamawa, Akwa Ibom, Imo, Lagos States 
and Abuja were done to determine how these States could limit the damage occasioned 
by disaster by preparing and be forewarned. Plan is underway to conduct VCA in the 
remaining 30 states of the federation. The study allows the Agency across the country 
and by extension in Lagos State to: 
i. Assess and address major risks affecting communities. 
ii. Determine people‟s vulnerability to those risks, their capacity to cope and 
recover from a disaster. 
iii. help the communities to understand the hazards they face; 
iv. Assist them in taking the necessary measures to improve the situation, based 
on their own skills, knowledge and initiatives. 
v. Enable the people to prepare for hazards and prevent them from turning into 
disasters. 
It is from this development that NEMA in conjunction with SEMAs collaborates with 
the Federal Ministry of Environment and Nigeria Meteorological Agency (NIMET) to 
integrated Disaster Risk Reduction and Climate Change adaptation as early warning 
mechanism. Early warning system is the provision of timely and effective information 
that allows individuals exposed to disaster to take action to avoid or reduce risk and 
prepare for effective response. Early warning systems include a chain of concerns, 
namely: understanding and mapping the hazard (VCA), monitoring and forecasting 
impending events (Early Warning), processing and disseminating understandable 
warnings to political authorities and the population (Public Awareness), and 
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undertaking appropriate and timely actions in response to the warnings (Contingency 
Planning) (ISDR, 2002). 
Early warning systems such as the NIMET seasonal rainfall predictions and daily 
weather forecasts empower individuals and communities threatened by hazards to act 
in sufficient time and in an appropriate manner to reduce the possibility of personal 
injury, loss of life, damage to property and the environment, and loss of livelihoods. 
Early warning is more than just a prediction it should be should be a prompt attention 
and response to information given. From the interview conducted, NEMA and 
LASEMA have been collaborating with all stakeholders in Disaster Management with 
the view to developing proper early warning mechanism for certain confirmed hazards 
such as epidemics, flood, drought and road accident as contained in the National 
Disaster Management Framework and the National Contingency Plan. Also, in the face 
of onslaught from climate change related extreme events, the use of NIMET weather 
forecast for early warning and early action is no longer an option but a compelling 
necessity. Yearly after the release of rainfall prediction and pattern by NIMET, NEMA 
and LASEMA have always been holding meeting with stakeholders‟ to deliberate on 
the effects of the forecast on human settlements and the general environment. This is 
done to obtain a consensus warning message for responsible agencies, bodies and 
communities at risk in line with the paradigm shift from disaster response to disaster 
mitigation and preparedness. 
It is important to note that disaster mitigation policies and measures will not stop a 
disaster especially a natural one from occurring and persisting. What mitigation 
policies and measures seek to do is to reduce vulnerability to, or increase resilience to, 
the effects of the inevitable disasters to which a community is vulnerable. The goal of 
emergency preparedness programmes is to achieve a satisfactory level of readiness to 
respond to any emergency situation through programmes that strengthen the technical 
and managerial capacity of governments, organizations, and communities.  
At the preparedness phase, NEMA and LASEMA have developed plans to save lives, 
minimize disaster damage, and enhance disaster response operations. Preparedness 
measures that have been developed include: Contingency Plans, Simulation, 
Evacuations Plans and Training, Capacity Building and development, Geographic 
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Information System (GIS), Emergency Personnel/Contact Lists, Public 
Information/Education, and Volunteerism. 
The National Contingency Plan (NCP) has been developed in collaboration with 
SEMAs, the UN Bodies, Ministries, Department and Agencies (MDAs) and other 
critical stakeholders in disaster management to provide a basis for coordination of 
humanitarian minimum response in the event of a major/catastrophic disaster for an 
initial 10 (ten) days by the Federal Government of Nigeria to be coordinated by 
NEMA and SEMA at national and state level respectively. The document adopts the 
multi-risk approach and identified flood, crises, epidemic, drought and collapse of 
artificial and natural impoundments for water, as probable disasters that can cause high 
level impact and displacement of persons. A population of 10,000 was used as the 
benchmark for planning assumptions. The geographical area covered the whole 
country based on identified hazards. Meteorological predictions, monitoring of dams 
and rivers, as well as, socio and ethno-religious activities by relevant agencies were 
used as the basis for Early Warnings and triggers for the probability of occurrence of 
the identified disasters. 
The multi hazard scenario approach has been adopted to ensure the accommodation of 
forecasted hazards, as well as those that have not been forecasted, bearing in mind the 
recent global happenings, climate change and climate variability and other 
uncertainties that determine the occurrence of disasters and their impacts. While some 
of the effects of climate change are apparent as witnessed by extreme weather changes, 
it has been difficult to adequately model the complete range of changes to accurately 
anticipate its impacts for Nigeria. Though National and Regional weather agencies 
predicts that weather changes such as high temperatures and irregular rainfall patterns 
are likely, it should be anticipated, that the effects would vary from region to region. 
The multi-hazard contingency plan, therefore, is a first step towards mitigating the 
impact of quick onset disasters when the level of forecast cannot be ascertained. 
Furthermore, a multi-hazard contingency plan creates the platform to bring several 
humanitarian players together as a framework for developing contingency 
arrangements for disaster response. Relevant stakeholders can also use the National 
Contingency Plan as justification for organisational preparedness using the roles that 
have been assigned to them in the plan as shown in Table 8.1 
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Table 8.1 Established clusters and designated lead agencies/organizations for 
NCP 
 Cluster Lead Ministries/Agencies  Lead UN Agency 
1 Camp Coordination and NEMA/SEMA UNHCR 
Camp Management. 
2 Food and Nutrition. FMoAgric/SMoAgric/SEMA WFP/FAO 
3 Health and Sexual FMoH/SMoH/NACA/SACA/LA WHO/UNFPA/ 
Reproductive Health/HIV CA UNAIDS 
AIDS. 
4 Protection. NHRC/MWASD/ UNICEF/UNHCR 
 Security. Law Enforcement Agencies UNDSS 
5 Basic Education. FMoEdu/SMoEdu/SUBEC UNICEF and SC 
6 Water and Sanitation. FMoWR/SMoWR/RUWASA UNICEF 
7 Emergency Shelter and NEMA/SEMA IFRC and IOM 
NFI. 
8 Logistics and NEMA/SEMA/FMoIC/SMoIC/ WFP/UNDP 
Telecommunication. NCC/State Mass Transit 
Source: NEMA, 2011b  
 
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For smooth inter-agency operations during emergency, the simulation of existing 
plans, procedures, programmes to bring together relevant networks is apt.. This will go 
a long way to spell out specific roles, enhance efficiency and better use of resources 
both human and material and to determine the efficiency or otherwise of the plan for 
possible review. Thus, simulation is a useful way of helping teams come together to 
develop and test plans. Quarterly, NEMA in collaboration with Military, SEMA and 
other stakeholders has been stimulating disaster response drill at the Military Training 
School, Jaji, Kaduna State, to effectively manage disaster occurrence. Also, NEMA 
has been organizing simulation exercises for its Emergency Response Teams (ERT) in 
conjunction with other stakeholders for disaster such as: fire, crisis, road crashes and 
air accidents and boat mishaps. The March 2010 Nigerian Air Force plane with 
registration Number NAF: 950GG222-8 Series simulation exercise that turned to real 
life crash in Port Harcourt is a reference point on the drive of NEMA to use simulation 
to ascertaining its level of preparedness and that of other relevant stakeholders 
involved in disaster management. 
NEMA at the national scale is fully aware of the usefulness of training and human 
resources development that in 2009 Memorandum of Understanding (MOU) was 
signed with six Nigerian Universities (University of Ibadan; University of Nigeria, 
Nsukka; University of Port Harcourt; Federal University of Technology Minna; 
Ahmadu Bello University, Zaria; and University of Maiduguri) in the Six Geo-Political 
Zone to train and award postgraduate degree in Disaster Risk Reduction and 
Development Studies. The programme is focused mainly in developing the capacity 
off NEMA and SEMA staff for efficient and effective disaster management across the 
country. The sum of 15million Naira ($100,000.00) is earmarked as annual grant from 
the Agency to each of the Universities for the next three years. Already, 10million 
Naira ($67,000) was released to each university for the programme take off. The 
programme has started in all the Universities with an overarching objective of building 
capacity nationally for disaster management due to observed lacuna in this area of 
human endeavour in Nigeria.  
Effective disaster management depends on the informed participation of all 
stakeholders. The exchange of information and easily accessible communication 
practices play key roles in disaster abatement. Data is crucial for ongoing research, 
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national planning and monitoring vulnerability. The widespread and consistent 
availability of current and accurate data is fundamental to all aspects of disaster 
management. Increased public awareness about hazard is an indispensable element in 
any comprehensive strategy for disaster risk reduction and mitigation process.  
The responsibility of the Agency, SEMAs and the Six Zonal Offices located in Lagos, 
Maiduguri, Jos, Enugu, Kaduna and Port Harcourt including the Abuja Operations 
Office is to promote public awareness of natural and man-induced/technological 
disasters on a continuous for effective disaster management. The Emergency 
management agencies must involve local communities in the dissemination process of 
information. In this regard, considerable scope should be created to inform and advise 
the public about hazards and the risks they pose. Within this development, risk 
reductive measures are most successful when they involve the direct participation of 
the people most likely to be exposed to hazard; local leaders including men and 
women drawn from political, social and economic sectors need to be given primary 
responsibility to protection of their own community (Okech 2007; Fagbemi 2011).  
It is crucial for people to understand that they have a responsibility towards their own 
survivals and not simply wait for government to find and provide solution. In addition, 
there is a need for more frequent and better-informed media coverage about disaster 
mitigation before a disaster occurs. Disaster mitigation programmes of the Agency are 
always attended by large retinue of media representatives to ensuring a well-informed 
and concerned media. Desirably, it is vital that the Agency and journalist interact 
regularly before a disaster occurs in order to lay the groundwork for effective working 
relationship during and in the aftermath of a disaster. 
Disaster response is the sum total of actions taken by people and institutions in the face 
of disaster. These actions commence with the warning of an oncoming threatening 
event or with the event itself if it occurs without warning. The aim of emergency 
response is to provide immediate assistance to maintain life, improve health, and to 
support the morale of the affected population. Such assistance may range from 
providing specific but limited aid, such as assisting Internally Displaced Persons 
(IDPs) and refugees with transportation, temporary shelter, and food and non-food 
items (NFI), to establishing semi-permanent settlement in camps and other locations. It 
also may involve initial repairs to damaged infrastructure. The focus in the response 
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phase is on meeting the basic needs of the people until more permanent and sustainable 
solutions can be found. 
One of the focal equipment for response in Nigeria is satellite technology called the 
COSPAS-SARSAT located at the Headquarters of the NEMA, in Abuja. The 
COSPAS-SARSAT System provides distress alert and location information to search 
and rescue services anywhere in the world for maritime, aviation and land users in 
distress. The system was originally designed to operate with satellite in low-attitude 
earth orbit and it has been in operation since 1982 and improved upon in 1998 with 
geostationary satellites (GEOSAR). Thus, with an accurate Doppler positioning, 
beacons identification, and global coverage, it has the unique advantage of providing 
an independent Doppler location capability and a complete coverage of the globe.  
This hi-tech system cum facility is a satellite system installed in March 2001 by the 
Agency to provide distress alert and locational data to assist search and rescue 
operations using spacecraft and ground facilities to detect and locate the signal of 
distress beacons operating on 121.5 and 406.0 Megahertz. Therefore, when there is a 
distress alert from the beacon located on a ship or aircraft, the satellite system 
transmits the signal to the geo-stationary terminals on the earth from where the data is 
processed and transmitted to the appropriate mission control centre (MCC). The MCC 
in turn alerts the nearest Reaction Coordinating Centre (RCC) or Disaster Reaction 
Unit (DRU) whether the Army, Air Force or Navy for appropriate and immediate 
action. Tables 6.2, 6.3 and 6.4 represent the location of Nigerian Army, Navy and Air 
Force DRUs controlling formations respectively 
COSPAS-SARSAT System has been used to identify crash locations of a number of 
airlines and helicopters such as the Pan Africa Airline helicopter crash as Escravos, 
Delta State on 26th July, 2004; the Nigerian Air Force Fighter Plane crash at Yar 
Kanya, Kano State on 28th January, 2005; Bellview Airline crash at Lisa Village, 
Ogun State on 22nd October, 2005; Basita Sugar Company Helicopter crash at 
Ikonifin,  Ejigbo LGA, Osun State and the Naval Helicopter crash at Okoroba Village, 
Bayelsa State on 15th December, 2012 
 
 
  
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Table 8.2 Nigerian Army Disaster Reaction Units: Areas of responsibility 
DRU State covered  Unit location Controlling formations 
26 Bn Sokoto and Zamfara Sokoto HQ 1 Bde 
1Bn Kebbi Birin Kebbi HQ 1 Bde 
212 Bn Borno and Yobe Maiduguri HQ 21 Armd Ede 
29 Bn Kaduna Kaduna HQ 1 Div 
82 Bn Plateau and Nasarawa Jos HQ 3 Div 
AHQ Gar FCT Abuja AHQ  GAR 
5 Bn Kano and Jigawa Kano HQ 3 Bde 
35 Bn Katsina Katsina HQ 3 Bde 
211 Bn Bauchi Bauchi HQ 33 Bde 
301 FAR(GS) Gombe Gombe HQ 301 FAR (GS) 
313 AR Niger Minna HQ 31 FAD 
222 Bn Kwara Ilorin HQ 22 Armd Bde 
19 Bn Ondo and Ekiti Okitipupa HQ 4 Bde 
321 FAR Ogun Abeokuta HQ 32 FAB 
322 FAR Edo Benin HQ 32 FAB 
93 Bn Delta Warri HQ 4 Bde 
103 Bn Enugu Enugu HQ 82 Div 
24 SER Ebonyi Abakaliki HQ 82 Div 
72 Bn Benue Markurdi HQ 82 Div 
342 FAR Imo and Abia Owerri HQ 34 FAB 
2 Bn Rivers Port Harcourt HQ 2 Bde 
73 Bn Bayelsa Elele HQ 2 Bde 
146 Bn Cross River Calabar HQ 13 Bde 
6 Bn Akwa-Ibom Abak HQ 2 Bde 
232 Bn Adamawa Yola HQ 23 Armd Bde 
20 Mech Bn Taraba Serti HQ 23 Armd Bde 
65 Bn Lagos Bonny Camp HQ 2 Div 
81 Bn Oyo Ibadan HQ 2 Div 
221 Bn Kogi Kainji HQ 22 Armd Bde 
12 FER Osun Ijebu Ode HQ 2 Div 
221 Bn Anambra Onitsha HQ 22 Armd Bde 
Source: NEMA 2012 
 
 
  
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Table 8.3 Nigerian Navy and Air Force Disaster Reaction Units: Areas of 
responsibility 
Geographical Zone State Covered Controlling Military Units 
Nigerian Navy   
Lagos Lagos, Ogun NNS Olokun 
Delta Delta Egwa-Ama (FOB) 
Calabar Cross River, Akwa Ibom NNS Victory 
Port Harcourt Bayelsa and Rivers NNS Pathfinder 
Port Harcourt Rivers NW FOB Bonney 
Warri Ondo, Delta NNS Umalokun 
Akwa Ibom Akwa Ibom Ibaka (FOB) 
Ondo Ondo Igbokoda (FOB) 
Lagos NAS Ojo 
Delta Delta Escrcavos (FOB) 
Nigerian Air Force 
Lagos Lagos, Ogun and Ekiti 88 MAG Ikeja 
P/Harcout Rivers, Bayelsa and Ebony 97 SOG, P/Harcourt 
Benin Edo, Delta, Ondo 81 AMG, NAF, Benin 
Makurdi Benue, Taraba TAC(ADG), NAF, Kaduna 
Kaduna Kaduna, Katsina 301 FTS, NAF, Kaduna 
Kainji Sokoto, Kebbi and Zamfara 99 AWS-NAF Kainji 
Kano Kano, Jigawa 303 FTS, NAF Kano 
Yola Adamawa, Gombe 75 STG NAF,  Yola 
Maiduguri Borno, Yobe 204 WG Maiduguri 
Ibadan Oyo, Osun NAF DET Ibadan 
Ilorin Kwara, Kogi 227 WG Ilorin 
Calabar Cross River,  Akwa Ibom NAF DET Calabar 
Minna Niger NAFDET Minna 
Enugu Enugu, Imo and Abia 305 FTS Enugu 
Jos Plateau, Bauchi 303 NAF STN Jos 
Abuja FCT, Nassarawa NAF Camp Abuja 
Source: NEMA 2012 
 
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8.4 Direct distribution of relief materials 
Today, distribution of relief material to people affected by disaster is the most visible 
aspect of the Agency. The Agency has seven warehouses strategically located in the 
Six Geo-Political Zone and Abuja that stock pilled relief materials for immediate 
distribution to affected persons in their homes or at Internally Displaced Persons 
(IDPs) camps. Figures 8.2, 8.3 and 8.4 show the distribution of relief materials to 
persons affected by disaster in 2012. Appendix III shows the comprehensive data for 
relief intervention in the country from 2010 to 2012. 
 
 
 
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ZINC (BUNDLES)
CEMENT (BAGS)
PLANKS 2x3x12 (PCS)
PLANKS 2x4x12 (PCS)
ZINC NAILS (PKTS)
ROOFING NAILS (BAGS)
 
Figure 8.2 Distributions of building materials as relief interventions to states, 2012 
Source: Compilations from NEMA’s yearly relief interventions to state, 2012 
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RICE
MAIZE
MAIZE FLOUR
G/CORN
MILLET
BEANS
SUGAR
SALT
GARRI
PALM OIL
VEG OIL
YAM FLOUR
PAP
 
Figure 8.3 Distributions of raw food as relief interventions to states, 2012 
Source: Compilations from NEMA’s yearly relief interventions to state, 2012 
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G/BROCADE
WAX PRINT
CLOTHE
TOWELS
S/PAD
BLANKETS
NYLON MATS
DETERGENT
SOAPS
MATTRESS
BUCKETS
PLATES
SPOONS
CUPS
M/NET
 
Figure 8.4 Distributions of household materials as relief interventions to states, 2012 
Source: Compilations from NEMA’s yearly relief interventions to state, 2012 
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8.5 Identified capacities and gaps at national and state level 
Since its establishment, NEMA has been putting a lot of effort into supporting various 
States across the country to set-up disaster management institutional frameworks. 
Through the Agency‟s Seven Zonal Offices located in the six Geopolitical zones and 
FCT (Lagos, Enugu, Port Harcourt, Kaduna, Jos, Maiduguri and Abuja), NEMA has 
been advocating and providing support to many States to facilitate the establishment of 
State Emergency Management Agencies (SEMAs). The NEMA Act mandated all 
states to establish State Emergency Management Agencies while local governments 
are to establish Local Emergency Management Committees. The assessment of the 
activities of established SEMAs from NEMA has shown that the Lagos State 
Emergency Management Agency has the highest capacity to mitigate, prepare and 
respond to emergency in the country. 
With the establishment of NEMA and LASEMA, it was obvious from the interviews 
conducted that there is no concrete disaster management legislation at the State level. 
Given the effort made at the federal level through NEMA, disaster management is yet 
to be seen as a national priority and decision makers lack or have limited knowledge of 
disaster reduction issues. Despite the establishment of LASEMA at the State level 
disaster management has not been integrated and factored into the day to day activities 
of the State. 
In terms of budget, the Federal Government allocates one percent (1%) of its national 
budget (GDP) to the Ecological Fund and twenty (20%) of this is allocated to NEMA. 
The remaining 80% of the Ecological Fund are utilized by the Federal Ministries, 
Department and Agencies (MDAs) such as Environment, Health and others that 
contribute to disaster risk reduction and mitigation, as well as States and Local 
Governments. However, in case of a disaster, if more funds are needed based on an 
assessment by NEMA, the Office of the Vice President (Chairman of NEMA Board of 
Governing Council) could approve further expenditure from the Environment Fund. 
For possible assistance from international communities, the National Planning 
Commission facilitates the resource mobilization with international partners. Similarly 
at the State level, when there is an emergency, SEMA sends its assessment to the 
Board of the Ministry of Economic Planning which decides on funding.  
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The budget allocation is relatively small to meet the ever increasing demand of disaster 
management and disaster risk reduction. More of the statutory allocation to disaster 
institutions at the Federal and State level from the Ecological Fund is more applied 
towards disaster response than prevention and mitigation of hazards and risks. Hence, 
the most visible activity of disaster management in the country is the distribution of 
relief materials to people affected by disaster rather than disaster prevention and 
mitigation component of the disaster management cycle (Appendix III). It has been 
argued by the Director General/Executive Secretary of LASEMA that a number of 
prevention and mitigation activities have been carried out which include drainage 
clearance, sensitization campaign awareness creation among others in collaboration 
with disaster management institutions in Lagos State. However, the perennial flood 
disaster, fire out break and frequent building collapse in the State underscored the 
significant of prevention and mitigation programmes. 
Also, at the state level, there is knowledge and awareness about responding to 
emergency but efforts to instigate proactive prevention and mitigation measures are 
very limited. This is due to unavailable resources and lack of understanding of the 
issues. The interviews conducted highlighted that very few individuals were familiar 
with the concept of reducing disaster risk and disaster management. Due to this lack of 
knowledge, disaster management is not explicitly mentioned in Lagos State charters, 
and usually disaster management issues are passed on to SEMA. Therefore, the Lagos 
State MDAs rarely ask for disaster prevention and recovery funding as part of their 
regular budget allocations through the Ministry of Economic Planning. From the 
interview conducted it was observed that employees of LASEMA and the State 
Ministries are yet to undergo comprehensive training on disaster management except 
for the quarterly simulation exercise organized by NEMA in conjunction with the 
Nigerian Military. 
The lateral and vertical relationship between and among MDAs as expected in disaster 
management parlance, as shown in Figure 6.1, is lacking in Lagos State. In other 
words, there is no formal platform or coordination mechanism between stakeholders 
engaging in activities and programmes related to disaster management issues at the 
state level. There is no evidence of horizontal interaction between MDAs, as disaster 
management issues are not on the agenda of their meetings. The only disaster related 
issues at such meetings are focused on response after the occurrence of disasters. 
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Organizations external to the state governments indicated that the state government 
bureaucracy is one of the main challenges hindering the successful implementation of 
disaster risk reduction measures. Furthermore, lack of guidance and clear mandates on 
disaster management and disaster risk reduction related methodologies and tools were 
also highlighted as significant weaknesses. 
The country has never been engaged in comprehensive risk identification or risk 
assessment activities. There are some scattered efforts carried out by various 
institutions (universities, research institutions) but not in a coordinated approach for 
common interest. Although the Lagos SEMA indicated that a comprehensive 
Vulnerability and Capacity Assessment/Analysis (VCA) was undertaken for Lagos 
State in 2009, with support from NEMA, UNICEF and WHO; there is no continuous 
execution of state-based comprehensive risk assessments and little recognition of the 
importance of risk mapping. The State MDAs interviewed do not conduct structured 
assessments of hazards, vulnerability or capacity. They are not aware of risk 
assessments that may have been conducted by outside organizations due to inadequate 
vertical and horizontal coordination.  
Other factors hampering coordinated response is the general lack of a common, toll 
free emergency number and the lack of standard operating procedures that are known 
within each organisation as well as among the various responders. Currently, most 
responders rely solely on GSM communication for alerts, with different numbers for 
each GSM operator, and GSM is also used for interagency communication without 
access to radio communication. At the peak of disaster, experience has shown that the 
GSM, as means of communication, during disaster is not effective largely due to 
congestion of the network. However, progress is being made towards installing 
common, toll free emergency numbers and establishing joint call centres. For example, 
two emergency numbers as well as toll free numbers for disaster reporting is in place 
in Lagos and NEMA is currently working on setting up a nationwide call centre. The 
latter is yet to become operational and its capacity cannot be assessed. 
Many examples from Lagos State level demonstrate scattered capacities in risk 
assessment. For example, many local governments in Lagos State have resident 
engineers tasked with monitoring the drainage and runoff situation, and report 
systematically to local government authorities as early warning in order to take 
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appropriate measures. Also, the report of a joint project called “Reducing the impact of 
flooding in Lagos, Nigeria” conducted by the Nigerian Institute for Oceanography and 
Marine Research, Lagos State Ministry of Environment and Physical Planning 
(Department of Drainage), the United Nations Educational, Scientific and Cultural 
Organization (UNESCO), and the Coastal Regions and Small Islands (CSI) platform 
addressed the problem of flooding in Lagos.  
The project was aimed at determining the causes of flooding and the implications of 
tidal and sea level changes as well as societal impact on the efficiency of drainage 
channels to discharge flood waters. The report of the project released in August 2000, 
highlighted two factors responsible for the problems of drainage blockage and flooding 
as: engineering problems, whereby some of the canals have reverse flows due to sea 
level rise. The other factor is attitudinal, evident in the dumping of refuse in canals and 
other drain channels by Lagos inhabitants. The study revealed several additional 
problems such as clogging of the drainage channels by domestic waste and blocking of 
some channels by buildings, low gradient of the channels and variable channel width 
from head to outfall, collapsed drainage channel walls, reverse gradients in most 
channels. Therefore, when flash flood from heavy rains coincide with high tides and 
blocked drainage flood waters flow back into the channels through the outlets causing 
excessive flooding.  
Although the results from the report were submitted to the Lagos State Ministry of 
Environment and Physical Planning and several recommendations were made 
including rerouting, repairing, fencing and screening of several channels, construction 
of new channels, increasing beach height, and a public awareness campaign to 
discourage dumping of solid refuse in the drainage channels, only few 
steps(structurally and non-structurally) such as canel screening, enforcement of 
environmental edicts  have been undertaken by the State and Local Government to 
combat the menace of flood. 
The status of hydrometeorology data collection and monitoring for disaster early 
warning is grossly inadequate in Lagos State and by extension in the country. The 
information management of existing risks and data is not systematic. Historical 
information on disaster incidents and losses are recorded in decentralized ways. 
Records of previous disaster events are not stored in a database by coordinating 
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government body such as NEMA and SEMAs. On the existing data aggregation or 
analysis is not done, and detailed hazard maps do not exist. Baseline data on disaster 
incidents and vulnerability are not available to measure improvement. For example, the 
Lagos Fire Service investigates the cause of each fire, but no statistics are tallied. 
While the State ministries are working diligently to assess new building projects and 
deal with existing problems, historical statistics on high-risk buildings or 
neighbourhoods are not available.  
In Lagos State, physical planning,  building codes and a number of legal and policy 
provisions to support and ensure proper land use and physical planning have been put 
in place and are being implemented. These included: the Land Use Act of 1978; Urban 
Development Policy of 1992; Urban and Regional Planning Act 1992 as well as the 
Housing and Urban Development Policy of 2002. In addition, control measures have 
been introduced to improve land use planning and development. To combat the urban 
disaster risk of building collapse, the Lagos Physical Planning Development Authority 
monitors and inspects buildings on an ongoing basis, and passes this information onto 
the Ministry of Physical Planning and Urban Development. It is, however, unclear how 
often buildings are inspected. Also, the Lagos State Ministry of Water Resources 
routinely monitors and tests surface water at the source in order to evaluate possible 
danger to the public. These tests have not resulted in flood early warning dissemination 
to the public to avert the yearly flood disaster. 
8.6 The Lagos State Fire Services 
In terms of fire service, despite the strategic importance of Fire Service as lead agency 
in terms of fire outbreak, flood and building collapse the situation of the Nigerian Fire 
Service including that of Lagos State is alarming and degraded to a level that requires a 
comprehensive study.  It was observed from the study that, in general, the Fire Service 
does not have sufficient means to carry out its tasks properly and respond to the needs 
of the population. Between 2008 and 2012, with the establishment of LASEMA, it was 
on record that the Lagos State fire-fighters carried out 109 operations with 32 of them 
on fire incidents. This shows the importance of Fire Service in ensuring sustainable 
disaster management. 
The structures of fire-fighters, despite a clear desire to move forward, as clearly stated 
by laws, the Service does not have the minimum requirement to carry out their tasks. 
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Therefore, they are not able to respond to emergencies or to exceptional situations, like 
some recurring floods, urban fires and market fires. This situation is compounded by 
the lack of adequate training of the fire fighters and the deficiencies in the training 
field. There is currently no training programme for Fire Fighters in Lagos States. The 
standard operational procedures, and other instructional materials required to educate 
fire fighters in prevention and preparedness are insufficient. The continuing 
professional education programme normally intended to develop reflexes and make the 
fire fighter operational is very limited. In general, training devices are inefficient and 
poorly adapted, and the quality of initial training is very low. Hence, the transmission 
of knowledge and culture, specific to the job of fire fighter, is too poor to develop a 
good quality service. 
The level of basic technical equipment for Fire fighters is dramatically low; this 
include lack of vehicles, equipment and materials; poor maintenance culture, lack of 
water supply system for the urban fire defence. Beyond the current risks, it is clear that 
the Fire fighters do not have enough specialized equipment as breathing apparatus, 
bunker gear, rescue material. To respond to the specific risks they need appropriate 
vehicles and special materials as aerial ladders, foam tender, water supply trucks which 
are lacking. These significant deficiencies have real impact on the success of response 
operations.  
Nigerians are known for fire-brigade service approach to things, but unfortunately the 
fire service is not working well. For it to function effectively, the Federal and States 
Fires Services need general overhauling, re-engineering and re-packaging to win the 
confidence of the public to which they are responsible. Moreover, importance of the 
tasks performed by the Fire Services are not sufficiently known, understood and 
integrated by other partner services, the highest administrative authorities and the 
politicians. Therefore, with few exceptions, the fire response capacity is inadequate 
and virtually not inexistence in some Local Government Areas. There is a common 
need for maintenance and procurement of equipment. The number of Fire fighters does 
not match the needs and size of populations to be covered. Fire fighters are employed 
but not provided with adequate training. The command and control system and the 
operational management are still very limited. There is no hazmat, decontamination or 
containment response capacity. 
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The highlighted lacunas, notwithstanding, the emergency management authorities in 
Lagos State are increasingly aware of the importance of the role of a Fire Service at 
State and Local Government levels. Also, efforts to improve local fire fighting 
capacity are being undertaken at Federal and Lagos State level as shown by the newly 
procured specialised vehicles and other technical equipment by the Lagos State 
Government. There is an increased public awareness in collaboration with media 
houses and other critical stakeholders through initiatives in fire prevention in schools, 
markets, motor parks and other areas sensitive to fire outbreak. 
8.7 Disaster management stakeholders in Lagos State  
Compared to other State of the Federation as noted by NEMA; LASEMA has done a 
lot in prevention and response to disaster situation in the State. Disaster management is 
a daring task that requires a lot of efforts from all stakeholders to improve on the 
existing status. In achieving this, the State as highlighted in the preceding sections has 
the following under listed strengths: 
i. Focal Institutions (LASEMA) 
ii. Relevant MDAs   
iii. National and International NGOs (Nigerian Red Cross Society, Oxfam, Farmer 
Early Warning System Network (FEWSNET), Save the Children, Catholic 
Relief Agency,   
iv. United Nations System 
v. Development Partners (Japan International Cooperation Agency, USAID, 
DFID) 
vi. Media (Print and Electronic) 
vii. Community Groups (CBOs, CDAs CDCs) 
8.8  Challenges to disaster management  
The strengths highlighted in the previous section, notwithstanding, both the National 
and State Agencies are bedevilled with a plethora of challenges which can be 
summarised to include the following: confused and poor coordination; lack of 
collaboration; response rather than mitigation focused; poor communication 
horizontally and vertically between and among stakeholders; weak public education 
and advocacy; ineffective response; disconnect between jurisdictions (turf protection); 
lack of accompanying plans, procedures and systems at state, local government and 
community levels; poor risk transfer mechanism: insurance and reinsurance policy; 
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weak emergency services – weakness of fire services, absence of ambulance service, 
poorly equipped police, poorly equipped hospitals; low technical/manpower capacity 
in government MDAs; poor funding of disaster management activities in relevant 
MDAs; poor/lack of data management; poor funding of SEMAs; LEMC, the local 
government emergency management apparatus not in existence in all the LGA‟s of the 
State; poor/absence of technical/manpower capacity at all levels of governance; 
virtually nothing concrete on disaster management at the Local Government Level. 
8.9 Conclusion  
Institutionalization of response to disaster in Nigeria dated back to 1906 when the Fire 
Brigade (now Federal Fire Services) was established. This chapter focused attention on 
the National Emergency Management Agency (NEMA) and the Lagos State 
Emergency Management Agency (LASEMA) NEMA and LASEMA were established 
by Act 12 as amended by Act 50 of 1999 and LASEMA Act of establishment 2008. 
NEMA and LASEMA are funded statutorily by the Federal and State Governments, in 
addition, to the mandatory release of 20% of Ecology Fund to the Agency yearly. The 
Ecology Fund is statutorily constituted as 1% of the national budget. The same funding 
arrangement is domesticated at the States level 
The Agencies have developed plans and programmes to aid disaster management in 
the country but the impact of such plans and programmes were not felt due to poor 
coordination; poor horizontally and vertically communication between and among 
Stakeholders; weak emergency; low technical/manpower capacity; and poor funding. 
 
  
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CHAPTER NINE 
SUMMARY OF FINDINGS, RECOMMENDATIONS AND CONCLUSION 
 
9.1 Introduction 
The extent and impact of potential disasters are changing exponentially. Therefore, the 
world is increasingly characterised by uncertainty, complexity and rapid change. 
Although causal factors and consequences are increasing globally, human vulnerability 
is intensifying in distinctly different ways at local and regional levels. The scale of 
crisis impacts is also intensifying with more and more disasters undermining economic 
and political systems, destroying infrastructures and eroding the fabrics for future 
development. The aim of this research is to examine the evolving urban dynamics 
process and associated vulnerability to hazards and disasters in Lagos State. The nature 
and intensity of natural and human-induced disasters impact on the environment have 
multifarious effects on the inhabitants. The extent to which the study area will be 
inhabitable and resilient to disaster will no doubt depend on the evolving urban 
dynamics process triggered and implemented covertly or overtly in the 1970 to early 
1980. 
9.2 Summary of findings 
The study revealed that Lagos State is losing population exactly in areas where real 
estate investment is growing significantly (Torres, et al 2007). Population growth, 
from all indications, is happening in areas vulnerable to disasters and with low 
investment in real estate. For example, in 1911, the highbrow district of Lagos State 
comprises Lagos Island, Ikoyi and Victoria Island accommodated 76.8% of the State‟s 
total population. Today, as a result of urban dynamics process occasioned by the 
provision of low cost housing, the urban fringe accounted for 73.9% of Lagos State 
population. The massive population shift notwithstanding, as noted by Alabi 2011, the 
spatial distribution of organized private sector housing estates indicated that significant 
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number of the estates are located in areas that lost a significant share of their 
population as evidence in the1991 and 2006 census figures. 
The finding of this study discovered that contrary to the benefits expected from the 
housing-for-all policy of the second republic administration, the demographic growth 
associated with provision of affordable housing resulted into expansion of existing 
poor and informal housing in most parts of Lagos State. Additionally, the benefits 
accruing from the economic expansion of the second republic era to drive 
developmental agenda were truncated by the oil glut of early 1980s and further sapped 
by the Structural Adjustment Programme (SAP) of late 1980s. Therefore, there is a 
visible delay in responding to the housing and infrastructural needs of the growing 
population and the expanding Lagos city frontier. 
The research into urban dynamics has shown that depressed areas in cities are triggered 
by low-income housing rather than commonly presumed housing shortage. The low 
income targeted housing and pro-poor urban policy without corresponding progressive 
economic development have combined to give incentives to overstretch the existing 
facilities and services, increase in-migration of unskilled workers and expansion of 
informal settlements to accommodate the migrants. The association between low 
2
income housing and urban dynamics was analysed using chi square (  ) two-sample 
2
test. The calculated  48.4 at 8 degree of freedom is significant at 95% confidence 
level (0.5 level). Therefore, the hypothesis which states that urban dynamics in the 
study area, is significantly influenced by the availability of low income housing is 
accepted. 
The low-income groups, by default, always use available housing at higher population 
densities (Alfeld 1995 and Ramroth 2007).  Deducing from the response from the Field 
Survey, 88.6% of the respondents submitted that 4 – 6 persons were living in a room. 
This negates the Millennium Development Goals 7 Target 11 recommendation of 2 -3 
person for ideal number of persons per room to avoid overcrowding. Housing at higher 
population density as noted by Myers (2010), accommodates more low-income urban 
population which, in the long run will have direct deleterious effects on economic 
growth, industrialization and sustainable development. The ever increasing population 
in the urban low income residential neighbourhood further aggravated the existing 
vulnerability components of the low income high density urban settlements. This is 
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because the urban poor are affected by the “double vulnerability” namely: disaster and 
poverty (Agbola, 2011). Therefore, they are disproportionately affected in terms of 
their exposure to risks and in terms of the limited resources at their disposal to respond 
to such risks (Jabeen, et al 2010). 
This assertion was corroborated by available data on the number of building collapse 
and fire outbreak used in analyzing the hypothesis which states that occurrence of 
disasters differs significantly between residential neighbourhoods. The result of the 
ANOVA shows that F value of 77.29 and 17.88 are significant for fire outbreak and 
building collapse respectively at 0.05 level. The study noted that the vulnerability is 
greater in high density residential neighbourhood than low density district. This was 
logically analysed using the Post Hoc Analysis (least significant differences). The 
difference between the means of low and medium densities, low and high densities and 
medium and high densities residential neighbourhoods are greater than the least 
significant differences. From the analysis, the study consented that the difference in 
mean ranks in the residential neighbourhoods differs significantly in virtue at 5% level.  
Vulnerability to hazards is a function of several factors which include socio-economic 
indices, housing characteristics and availability of infrastructural facilities and services 
and the attendance urban dynamics process.  The result of the logistic regression 
analysis revealed that the model‟s fit is significant at 0.05 confidence level and on the 
average, 88% of the model is correctly classified (predicted). In disaggregating some 
of the results of the regression analysis, the study revealed that the probability of 
flooding increases significantly by 53% for primary education and reduces for those 
with secondary education certificate by 76% compared to those with tertiary 
qualification. Also, probability for fire outbreak and building collapse decreases with 
education attainment. For instance, it is shown that those with no education are about 3 
times more likely to experience building collapse than those in the base category 
(tertiary); in other words, people without education are 300% likely to reside in 
building that will collapse. Equally, evaluating the impact of income on vulnerability 
to disaster, it is observed that as income increases probability for flood reduces by 57% 
and the odd for disease outbreak reduces by 31%. 
Availability of functional and adequate drainage network contributes to outcome and 
impact of disaster. From the logistic regression analysis, taking non-availability of 
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drainage as base, free flowing drainage reduces the probability of flood significance by 
63%. Blocked drainage also reduces the likelihood of flood significantly by 42% 
compared to where there is no drainage. However, blocked drainage also significantly 
increases the occurrence of disease outbreak by 2% in relationship to the base 
category. Furthermore, evaluating the result of setback to water bodies, it can be 
deduced that as set back increases (in metre) the probability of a building being 
flooded decreases significantly by 40%.  
Another implication of the analysis is that generally, all residential neighbourhoods are 
vulnerable to disasters in the study area but the degree differs. For instance, people 
living in low density area are as vulnerable to hazard as those living in high density 
areas. This is mainly due to the attraction of water bodies for human settlement and the 
significant contribution of water as a major causal factor in other hazards such as 
disease outbreak, flooding, building collapse, erosion, and general land degradation. It 
is important to note that vulnerability to disaster is a function of capacity to anticipate, 
cope with, resist and recover from the impact of hazard. Consequently households with 
means of production (land, capital and labour) and specialized skills as characterized 
by low density neighbourhoods are the most resilient when disaster strikes. In addition 
to this, as noted by Smith (2004), access to early warning information and the 
availability of a social network to mobilize support, especially government support, is 
also important in vulnerability analysis. However, the poor and those otherwise 
disadvantaged by age, gender, ethnicity, employment opportunity or health status are 
comparatively defenceless and highly vulnerable to hazards.  
Using Geographic Information Systems to analyse the land use and land cover change 
from 1984 to 2010, the study has shown that about 8% and 45% of water and 
vegetation respectively have been converted to urban land use. Also, the study 
revealed that within 32 years, the study area has changed from vegetation - having the 
greatest percentage of the total land use at 46.5% in 1984 - to urban at 51.2% in 2010. 
The simulation of flood risk at 1 metre by the study indicated that in 1984 most areas 
at risk were under vegetation. However, by 2010 Kosofe, Surulere, Ikorodu and 
Ajeromi-Ifelodun were the most flood prone Local Government Areas. It is instructive 
to note that the sum total of the four Local Government Areas population (2,671244) is 
more than the entire population of Bayelsa State (1,704515). Simulation of 2 metres of 
flood water, similar to the impact of 2012 nationwide flood disaster, indicated that in 
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the study area, Kosofe, Ikorodu, Shomolu. Lagos Mainland, Surulere, Ajeromi – 
Ifelodun and a larger part of Mushin, Oshodi – Isolo and Alimosho would be 
submerged.  
Currently, there is a wide spread awareness of risk in the environment and the growing 
recognition that the toll exerted by disaster is unacceptable. It will be defeatist not to 
bring hazard awareness into development planning because continuing disaster losses 
simply reinforce poverty and vulnerability. It is from this backdrop that the National 
Emergency Management Agency (NEMA) was established by Act 12 as amended by 
Act 50 of 1999. The Agency is saddled with the mandate of managing, coordinating 
and formulating policies in all related activities of disaster management. Also, in 
Lagos State Emergency Management Agency (LASEMA) was established to 
domesticate the activities of NEMA for effective disaster management in Lagos State. 
The establishment of disaster management organs notwithstanding, the National and 
the State Agencies are bedeviled with a plethora of challenges which include the 
followings: confused and poor coordination; response rather than mitigation focused; 
poor communication horizontally and vertically between and among stakeholders; 
weak public education and advocacy; ineffective response; disconnect between 
jurisdictions (turf protection); lack of accompanying plans, procedures and systems at 
state, local government and community levels; poor risk transfer mechanism: insurance 
and reinsurance policy; weak emergency services – weakness of Fire Services, absence 
of ambulance service, poorly equipped Police and National Security and Civil Defense 
Corps (NSCDC), poorly equipped hospitals; low technical/manpower capacity in 
Government MDAs; poor funding of Disaster Management activities in relevant 
MDAs; poor/lack of data management; poor funding of SEMAs; LEMC, the Local 
Government Emergency apparatus not in existence in all the LGA‟s of the State; 
poor/absence of technical/manpower capacity at all levels of governance and virtually 
nothing concrete on disaster management at the Local Government Level. 
9.3 Theoretical and practical implications of the study 
The intuitively obvious "solutions" to social problems, as shown by the housing 
provision programme of 1970s to 1980s, are apt to fall into one of several traps set by 
the character of complex systems. First, an attempt to relieve one set of symptoms 
(inadequate housing for the low income households) may also create a new mode of 
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system behaviour that also has unpleasant consequences. Second, the attempt to 
produce short-term improvement often sets the stage for a long-term degradation. 
Third, the local goals of a part of a system often conflict with the objectives of the 
larger system. Fourth, people are often led to intervene at points in a system where 
little leverage exists and where effort and money have but slight effect. Thus, as noted 
by Alfeld (1995) and Forester (2009), a control of growth and migration has been 
exerted at all times, but it has often been guided by short-term considerations, with 
unexpected and undesirable long-term results. The issue is not one of control or no 
control. The issue is the kind of control and toward what end. For instance, if a 
sufficient number of cities find new ways of controlling their own destinies in spite of 
national policy and what other cities do, then pressures to work toward the long-term 
well-being of the country will be quickly generated. This in the long haul will establish 
equilibrium with cities‟ natural surroundings and maintain a viable and proper internal 
balance of population and industry. 
As migration is increasing, the poor families, who should not be blamed for moving to 
these least-structured suburbs, are the first to be affected by the degradation of the 
environment (Figure 2.1; page 20). This is not only through their exposure to 
environmental hazards and vectors of contagious diseases but also because their places 
of residence are less protected in terms of facilities and/or construction patterns that 
could avoid such hazards thereby validating the tenets of urban dynamics as shown in 
Figure 9.1. Therefore, the most significant issue here is how to change such 
unfortunate trends. The idea that restrictions on land use alone could cope with such 
problems is quite naïve. So far Town Planners have not been able to properly regulate 
the illegal settlements in Lagos State. The 2012 flood disaster in Nigeria, occasioned 
by release of excess water from Lagdo Dam in Cameroon and the unusual increased 
precipitation across the country indicated that disasters can be amplified by 
demographic and socio-economic factors. The devastating results of the flood disaster 
– and, to be sure, any disaster – were a result of the intersection of poverty, decades of 
neglect and years of ineffective planning regulation, exacerbated by the climate change 
and climate variability impact. Economic, cultural and social capital, as well as human 
ecological trends, held equal hands in placing some population groups at greater risk. 
  
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Figure 9.1 Integrated urban management strategy to reduce vulnerability 
Source: Author, 2014 
 
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Theoretically, however, the problem is much more complex and, at times, vulnerability 
resulted from a multiple forms of social capital deficiency. As urbanization is driving 
the need for new industrial and commercial sectors, people were forced to live in 
hazard prone areas. More importantly, it is often the poor who live in such regions, 
making the problem as much an issue of human ecology as economic capital. It is also 
important to note that it is only in rare cases that a single dimension of the social 
structure is responsible for vulnerability. In the context of disasters, social forces are 
multidimensional. The complexities of these interactions must be taken into account in 
future studies.  
Vulnerability is a multifaceted phenomenon. As such, solutions, too, must be 
multifaceted, addressing the range of social, cultural, demographic and economic 
conditions – often interacting in complex ways – that culminate in population 
vulnerability. Population changes also require the frequent and thoughtful revision of 
existing policies, plans, urban and disaster management options. Therefore, emergency 
managers, planners, and other policymakers (NEMA, LASEMA, Fire Service, Nigeria 
Police Force, NSCDC) should strive to develop effective disaster policy, the policy‟s 
fingers should also centre on the socio-economic and demographic characteristics 
(social inclusiveness) of the communities that required policy interventions. Failing to 
do so will undoubtedly have significant and long-term deleterious public health effects 
as well as devastating livelihood, social and economic consequences for the 
populations that are vulnerable to disasters and are living in high risk areas.  
As noted by (Donner and Rodríguez 2008), individual preparedness and response to 
disasters is generally influenced by factors that have little to do with the hazard agent 
or the disaster event itself, such as social class, education, gender, race/ethnicity, 
cultural background and language proficiency, among others. It is important to note 
that population growth, composition, distribution and economic variability, the major 
factors influencing urban dynamics, are the primary driving forces in the context of 
exposure to disasters and disaster vulnerability. As such, social science disaster 
researchers and other academia need to pay closer attention to population and 
economic shifts and their implications for disaster risk and vulnerability analysis as a 
paradigm shift in disaster management. 
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9.4 Disaster management strategies and facilitators 
Strategies to manage disaster risk and vulnerability must begin by identifying the 
hazards and areas in the community that are particularly vulnerable. Uncoordinated 
planning in Lagos brought about chaotic growth and the generation of irregular 
proliferation of informal settlement. Immediate demands for services (streets, 
sidewalks, transport, water, electricity, drainage) are not met by the city‟s managers 
and policy markers thereby heightening the existing vulnerability indices of the 
inhabitants (Martínez-Viveros and López-Caloca 2010). Fortunately, planning driven 
by science and technology has been adopted as management tools to reduce or at least 
manage uncertainty through simulation of disaster scenarios to determine expected and 
estimated impact. These estimations can steer the processes of planning and it is within 
this framework that GIS exists. Application of GIS to aid urban planning, especially in 
the area of flood plain management, should be given required attention by urban 
managers and policy maker in the hope of fashioning sustainable development path for 
the State. The federal government, Nigerian Institute of Town Planners (NITP) and 
Town Planner Registration Council (TOPREC) should drive the process of actualizing 
this strategy. 
In recent decades, urban communities have adopted more regulatory rather than 
structural approaches to disaster mitigation. This involved the employment of land use 
management to restrict further encroachment to vulnerable land especially flood plain 
development. Flood plain mapping, which include water depth, flow velocity and flood 
duration, an important planning tool, has not been systematically done in the study 
area. In addition to this, flood plain buy-back has been used by Governments‟ 
Agencies to purchase flood prone property with the overarching motive of promoting 
public safety. Other benefits of this strategy include the conversion of flood plains for 
urban agriculture, parkland preservation of wetland habitats and the improvement of 
waterfront access. The flood plain buy-back strategy according to Smith (2004), is a 
cost effective use of public funds because in return for the one-off purchase cost, the 
property becomes ineligible for any future assistance following disaster. The state 
government should take the lead and facilitate the process 
There is also need to review the 1992 and 1999 as amended Urban and Regional 
Planning Law to reflect the prevailing circumstances in Nigeria. Innovative urban 
planning for rapidly expanding cities has shown the need for flexibility in applying 
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planning regulations, but also there is a greater need to apply planning guidance 
quickly as cities grow. However, as necessary as legislative reform is, on its own term 
it is not a sufficient tool for increasing functionality, equity and participation. 
Legislation can set standards and boundaries for action, for example, by defining 
development control, building codes or training requirements and basic responsibilities 
for key actors in disaster management. But legislation on its own cannot induce people 
to follow these rules. Legislation has its strength in societies where most activities take 
place in the formal sector and are visible to administrative oversight. In many disaster 
prone environment and locations, monitoring and enforcement - and even widespread 
knowledge - of legislation is not achievable in the short- to medium-term because of 
financial and human resource constraints. Fortunately, the principles of equity and 
participation in disaster management are not solely dependent on legislative reform. 
The strategies to be adopted should describe ways in which inclusive decision-making 
could be encouraged to integrate the knowledge and views of all stakeholders in 
development and disaster management. The federal and state government should 
support the process 
Another proactive disaster management strategy is insurance. For instance, in the 
developed world, insurance is an important loss-sharing strategy to cushion the adverse 
effects of disaster. A property or business insurance arises when a risk is perceived and 
the owner pays a fee (premium), usually on an annual basis, to buy a contract 
(insurance policy) that transfers the risk to a financial partner (insurer). The insurer 
guarantees to meet specified costs in the event of damage through disaster to the 
property. By this means, the policy holder is able to spread the cost of a potentially 
unaffordable disaster over many years. Insurance mechanism is still weak in the 
developing country, especially in Nigeria, where poverty and other socio-economic 
disadvantage indices prevent the individual from taking insurance policy and the 
insurer is not predisposed to encourage individuals to insure their property due largely 
to premium default. Further studies should be done to ensure that property insurance is 
adopted as viable option in disaster management is Nigeria as the norm in the 
developed countries. The insurance companies facilitate this process while the federal 
and state government should provide the enabling environment for the implementation 
of the strategy 
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Efficient infrastructure contributes to efficient economies. It is upon functional basic 
infrastructure that economy viability depends (Smith, 1997). Provision of basic 
infrastructural facilities and services is apt and could be seen as practical planning 
intervention to prevent and mitigate Lagos State from disaster vulnerability. For 
instance, adequate supply of power and electricity can influence the urban morphology 
of the State. With electricity to support the powering of lifts and escalators in place, the 
urban managers and policy makers can advocate for vertical expansion of Lagos State 
rather than adopting the prevailing lateral expansion. This practical strategy had been 
adopted in most developed cities of the world that had similar terrains and land 
inadequacy to accommodate the increasing population like Lagos State. The federal 
and state government should provide the needed infrastructural facilities and services 
to support the workability of the strategy 
Disaster abatement and management must be the responsibility of government. 
However, its success also depends on widespread decision-making and the 
participation of many other stakeholders (Figure 9.2). Policy direction and legal 
foundations assure legitimacy but it is the political motivated professional and human 
resource available that are true measures of success. Furthermore, comprehensive 
disaster risk reduction covers a wide range of discipline, sectors and institution, calling 
for diverse and expanded forms of partnership. The achievements from networking and 
partnership coupled with information management can be far more powerful than 
individual or specialist contributions. With the improvement in global communication; 
creating networks between government agencies, the public, the private sector and 
professional bodies is technically easy; however, these networks can only be 
successful if participants display the same commitment to share available information 
and experience openly. The major challenges are to stimulate networks of shared 
commitment and partnership at local, national, regional and international levels across 
professional interest. A need for cohesion in achieving these partnerships is a challenge 
to be addressed and facilitated by disaster management MDAs in Lagos State and by 
extension in the country. 
Priority must be given to education in disaster management. Various and complex 
dimension of disaster risk within a community need to be taught, continuously 
reinforced through structured educational programme and professional training. 
Similarly, the increased public awareness about hazards and inherent vulnerability is a 
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vital element in any comprehensive strategy for disaster risk reduction. Thus, public 
awareness campaigns should be conducted in school, through the media, public 
official, professional and commercial channels. It has been documented (Okech, 2007), 
that disaster abatement measures are most successful when they involve the direct 
participation of the people most likely to be exposed to hazard; local leaders, including 
women and men drawn from political, social and economic sectors in vulnerable areas 
need to assume primary responsibility for the protection of their community. The 
government (federal, state and local), the communities and individuals have major role 
to play in facilitating inclusive and participatory disaster management strategies 
  
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Figure 9.2 Disaster management strategies for safer community development 
Source: Author, 2014 
 
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The integration of disaster management with environmental policy and land use 
planning is crucial to disaster pre-emptiveness and management. The planning 
agencies and the National Emergency Management Agency (NEMA) should be fully 
aware of the challenges posed by the spate of urban planlessness and vulnerability 
inherent in it. Consequently, NEMA at the national level and LASEMA at the state 
level should recognize Ministry of Housing and Urban Development as important 
collaborator and work together to develop plan and action for disaster management. 
Also, as a necessity and point of duty, NEMA and LASEMA should be represented in 
the Development Control Department of Planning Authority to enable the disaster 
management agencies to effectively discourage the erection of structures in areas 
vulnerable to disasters and for it to be proactive in disaster mitigation and 
management. Desirably, there is the need for NEMA to develop a National 
Comprehensive Mitigation Plan that is crucial and a fundamental component in 
emergency management. The importance of continuity in disaster management 
strategies is very critical, as gains obtained in the short-run can easily be lost by the 
failure to follow through with needed action by key actors. It is, therefore, pertinent to 
evolve feasible disaster mitigation strategies that will stand the test of time. This 
should be facilitated by federal and state MDAs in active collaboration with NEMA 
and LASEMA 
9.5 Areas of future research  
In addition to future areas of further study stated earlier (complexity of interaction in 
vulnerability analysis, population and economic shift and insurance), that people (poor 
and rich) are living in disaster prone areas has been studied and documented by various 
scholars in Lagos State and Nigeria at large. However, it is important to note that 
giving the current trend of development coupled with economic challenges people will 
continue to reside in vulnerable areas. It is from this development that future research 
should focus on coping (adaptation) and mitigation strategies adopted by people to 
respond and recover from disasters in order to build the communities resilience. 
Similarly, disaster management stands on five interconnected pedestals (prevention, 
mitigation, preparedness, response and recovery), however, in Lagos State, response 
pedestal is the most visible. At this stage of disaster management, relief materials are 
giving to persons affected by disaster as knee-jerk palliative measure to cushion the 
impact of the disasters at the detriment of other stages of disaster management. For 
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disaster management to be more enduring there is need to look, especially into, the 
non-structural prevention and mitigation components of disaster management by 
enforcing the existing planning laws and regulations, due largely to obvious 
shortcoming of structural measures that are rigid and very expensive to implement.  
9.6 Conclusion 
In most cases, it is difficult to establish the consequences of urban change (dynamic) 
on inhabitants of a given environment because cause and effect relationship which is a 
function of environmental, economic, political and social disposition of the people 
between different phenomena are often too complex to ascertain. However, what is 
certain from this study is that urban growth and expansion is permeating the urban 
morphology and form of Lagos State. For example, due to population increase and the 
resultant quest to accommodate the population, there is enormous pressure to reclaim 
and convert the available vegetation and water body to land for residential purposes. 
The conversion, in the absence of proactive urban land use and disaster management 
strategies, exposes people to disasters. 
It is important to note that due to its geographical location and socio-economic indices 
of Lagos State, nearly all residential neighbourhoods are vulnerable to disasters but 
coping capacity differs across the socio-economic ladder. The rich has higher capacity 
to anticipate, cope with, resist and recover from the impact of hazard coupled with 
availability of a social network to mobilize government support during emergency. 
The urban poor by virtue of housing choice and other poverty features are often 
defenseless and highly vulnerable to hazards leading to disasters. Therefore, to reduce 
the frequency and effects/impacts of natural and human-induced disasters on human 
and environment involve proactive strategies that will address and tackle development 
challenges that lead to the accumulation of hazard and human vulnerability.  
Vulnerability to disaster prompts a questioning of the development paths that have 
been taken by cities that are at risk from disaster. Disasters destroy development gains, 
but development processes themselves play a role in driving disaster risk. Unless 
disaster risk considerations are factored into all developmental projects, efforts to 
increase social and economic development might inadvertently increase disaster risk as 
manifested in the Lagos State pro poor policy of late 1970s to early 1980s 
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compounded by the Structural Adjustment Programme (SAP) of the late 1980s to early 
1990s in Nigeria.  
9.7 Contributions to knowledge 
This study investigated the relationship between urban dynamics and vulnerability to 
disaster in Lagos state against the set objectives which included identification of the 
nature and contributing factors to urban dynamics and vulnerability to  disasters in 
addition to land use and land cover change from 1984 – 2010 and simulate flood risk 
using Geographic Information System (GIS). The study also, examined the 
relationship between urban dynamics, socio-economic indices and vulnerability to 
disasters. The legislative and institutional policies enacted and programmes 
implemented to abate disasters by stakeholders in disaster management were 
discussed. Having satisfied the objectives of this study it is important to note that 
occurrence of disaster can significantly aid developmental process if effectively 
managed. However, in Lagos, the devastating effect of disasters is as a result of the 
intersection of: poverty, decades of neglect and years of ineffective planning 
regulation. This is compounded by climate change and climate variability effects in 
addition to socio-cultural capital and unsustainable human ecological trends and 
population growth that is not supported by sustainable and concrete economic growth 
that could translate to employment opportunities and economic empowerment. Due to 
financial constraint and severe competition for available resource by different sector of 
the urban sphere, it was observed that enduring disaster management strategy should 
adopt regulatory rather than structural approaches to aid disaster risk reduction. This 
involved the employment of land use planning and management technique to restrict 
further encroachment to vulnerable area especially flood plain encroachment. The 
study observed that flood plain mapping, which include water depth, flow velocity, 
flood duration and the simulation of the expected impact could be achieved by the 
application of GIS. This should be given required attention by urban managers and 
policy maker in the hope of fashioning a sustainable development path for Nigerian 
cities. 
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Appendix I 
Household Questionnaire (Type A) 
Dear Respondents,  
This questionnaire is designed as part of PhD research instrument to seek information on 
Urban Dynamics and Vulnerability to Disasters in Metropolitan Lagos. Your honest 
response will be highly appreciated. Instruction: Please provide or tick the options in the 
column that suits your condition   
A. Socio–Economic Characteristics   
1 Geographical  Location 
(i)       Name of Locality ……………………….. [ii] Ward………………………… 
[iii] Street Name………………………… [iv] House Identification Number………….  
[v] Density of the area    (a) High density  (b) Medium density      (c) Low density  
2 For how long you been living in this area ……………………………………… 
3 Age of respondent ……………………………………………………………… 
4 Gender: Male…………………....................  Female…………………………… 
5 Religion …………………………………………………………………………… 
6 Ethnicity…………………………………………………………………………… 
7 Marital Status: (a) Single     (b) Married     (c) Widower      (d) Divorced      (e) 
Separated 
8 Number of person(s) in the household …………………………………………… 
9 Highest Level of Education qualification (a) None (b) Primary /Adult Education 
(c) Secondary Education (d) Post Secondary Education (e) Others 
Specify…………… 
10 Occupation  (a) Unemployed (b) Trading/Business (c) Artisan (d) Farming (f) 
Civil Servant (g) Professional  (h) Retired (i) other (specify)…………………… 
11 Income per month ………………………………………………………………… 
 
B. Housing and Household Characteristics  
12 Age of building ………………………………………………………………… 
13 Type of house tenure (a) Owner-Occupier (b) Rented (c) Institutional Property 
(d) Family    House (e) Squatter (f) Others Specify ……………………………… 
14 Types of dwelling unit (a) Rooming Apartment (b) Flat (c) Duplex (d) 
Compound 
15 Total number of rooms in the building…………………………………………… 
16 Total number of household in the building ……………………………………… 
17 Average number of people per room……………………………………………… 
18 Distance of building (in metres) to the adjacent structure on the (a) Right ……… 
(b) Left ……………........ (c) Rear …………………… (d) Front ……………… 
19 Material used for wall (a) Block  (b) Mud (c) Plank and Iron Sheets (d) Stone (e) 
Burnt Brick (f) Others (Specify)…………………………………………………. 
20 Is the wall plastered? .............................................................................................. 
21 Roof material (a) Interlocking Tile (b) Corrugated Iron Sheet (c) Thatched Roof 
(d) Reinforced Concrete Block (e) Others (Specify)………………...…………… 
22 Door and window material (a) Modern Frame and Wooden Panel (b)Wooden 
Frame and Glass/ Louvres  (c) Metal Frame and Glass Panel/Louvres  (d) 
Aluminum Doors and Window (e) Metal Sheet (f) Others (Specify)…………… 
23 Height of building (a) High-Rise Building (No of floors)…… (b) Storey Building 
(c) Bungalow (d) Others (Specify)………………………… 
24 Drainage channel for water flow around building (a) Available (b) Not  Available  
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25 If available, in what condition (a) Free and Flowing (b) Blocked (c) Others 
(specify)…….. 
26 Setback of property from water bodies (streams, rivers, ponds) (a) 0-10m (b) 11-
20m (c) 21-30M (d) 31-40m  (e) 41-50m (f) Above 50m  
27 Physical condition of the building (a) Good (b) Needs Minor Repair (c) Major 
Repair (d) Others (specify)…………………………………………………….… 
 
C. Housing Facilities, Convenience and Sanitation 
28 Source of water for domestic use: (a) Tap/Piped Water (b) Well/Borehole (c) 
Stream / Pond (d) Street Hawkers (e) Others (specify)…………………………… 
29 Distance to source of water (a) Within the compound (b)  Outside 
Neighbourhood (c) Within the Neighbourhood (d) Others (specify)…………… 
30 Distance of well or other sources of water to soak-away or refuse dump etc. (a) 0-
10m (b) 11-20m (c) 21-30m (d) 31-40m (e) 41-50m (f) Above 50m 
31 Location of well or other sources of water in relation to soak away or refuse 
dump (a) Up Hill (b) down Hill (c) Same Level (d) Others 
(Specify)…………………………………… 
32 Toilet facility (a) Water Closet (Separated) (b) Water Closet (Shared) (c) Pit 
Latrine (d) Pail Latrine (e) Bush (f) None (g) Other (Specify) ……………… 
33 Number of person(s) per toilet facility (a) 1-2 (b) 3-4 (c) 5-6 (d) 7-8 (e) above 9 
34 Kitchen facility (a) Open Space (b) In Built, Within the House (c) In Built, 
Within the House but Shared (d) None (e) Other (Specify) ……………………… 
35 What are the types of waste generated in the house ……………………………… 
36 Method of waste collection (a) Government Agency (b) Organized Private 
Collector (c) Local Cart Pushers (d) Other (Specify)…………………………… 
37 Frequency of collection: (a) Daily (b) Twice a Week (c) Every Other Day (d) 
Weekly (e) Other (Specify)…………………………………………… ……. 
38 If waste are not collected by: government agency; organized private collector and 
or local cart pushers, how do you dispose waste (a) Communal Dumps (b) In the 
Bush/Open Space (c) Dump in Water Drainage/Channel or Stream (d) Burnt in a 
Communal Open Space (e) Road Side or Medium (f) Other (Specify)………… 
39 What are the effects of non collection of waste in your neighbourhold ………… 
…..………………………………………………………………………………… 
40 Class or types of road servicing your locality: (a) Ring Road (Outer by-pass) (b) 
Primary Arterial Road (c) Secondary Arterial Road (d) Distributor Road (e) 
Service (Access) Road 
41 Condition of road: (a) Good (b) Fair (c) Poor 
42 What is/are the major means of transportation: (a) Walking (b) Okada 
(Motorcycle) (c) Car (Private) (d) Taxi (e) Bus (f) Other (Specify)……………… 
43 Do you have difficulty in accessing your locality: …………………………… 
44 If yes, what is responsible for the inaccessibility: ……………………………… 
45 Situation of traffic congestion in the neighbourhood: (a) Frequently (b) 
Occasionally on Most      Roads (c) Frequently on Few Roads (d) Occasionally 
on Few Roads (e) Does not Occur at All     
 
D. Vulnerability and Disaster Related Information 
46 Do you have information prohibiting living in any specific part of your locality 
………………………………………………………………………………… 
47 If yes, from which agency or organization ……………………………………… 
48 What is your definition of a disaster......................................................................... 
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49 Is your area vulnerable to any form hazard or disaster (a) Yes (b) No   
50 If yes, list them …………………………………………………………………… 
51 Have you ever experienced any form of hazards /disasters in your locality (a) Yes 
(b) No   
52 If yes list them ……………………………………………………………… 
 
Information on Flood 
53 Has your area/house experience flooding ever? (a) Yes   (b) No 
54 If yes, how often? (a) Every Time it Rains Heavily (b) Occasionally When it 
Rains Heavily (c) Anytime it Rains (d) Others (Specify) ………………………… 
55 When was the last flood? …………………………………………………… 
56 It lasted for how long ………………………………………………………… 
57 Personally, what was the experience of flood like …………………………… 
58 What do you think caused the flood  (a) Natural Causes (b) Human Induce 
Causes (c) Act of God  (d) Other (Specify) ……………………………………… 
59 If human induced, which of the following(s) is/are correct? (a) Location of 
Property in Hazard Prone Area (River Flood Plain) (b) Improper Planning or 
Design (c) Inadequacy of Flood related laws (d) Others (Specify)….…………… 
60 Despite the occurrence of flood, give reason(s) why you still live in this house or 
locality (a) Nearness to Place of Work (b) Cheaper Rent (c) Family House (d) 
Personal House (e) Others (Specify) …………………………………………… 
61 Has there been any measure by the community or government to combat flood in 
this locality? (a) Yes (b) No    
62 If yes, by which agency and or community …………………………………… 
63 Please list the measures…………………………………………………………… 
64 What can be done to prevent the reoccurrence of flood? (a) Cannot be Prevented 
(b) Property Relocation (c) Adequate Drainage Network  (d) Better Planning and 
Management (e) Adherence to Building Set Back (f) Others (Specify) ………… 
 
Information on Fire 
65 Have you ever experienced or witnessed incidence of fire-outbreak before (a) 
Yes  (b) No 
66 If „yes‟ when and where………………………….................................................. 
67 Can you give a vivid recollection what you witnessed ..……………………… 
……………………………………………………………………………………
…………..………………………………………………………………………… 
68 Were the adjacent buildings affected during the fire incident in the locality.…… 
69 When last did any fire-outbreak occur …………………………………………… 
70 From your experience, what was the frequency of occurrence over the years (a) 
Once (b) Twice (c) More than Twice (d) Others (Specify)……………………… 
71 What do you think was the cause of the fire-out breaks? (a) Human Mistakes (b) 
Natural     Occurrence (c) Others (Specify)……...…………………………… 
72 If fire-outbreak is caused by human activities and or mistake, which of the 
following is/are the predominant causes? (a) Careless Handling of Fire or 
Electrical Appliances (b) Careless Handling of Combustible Materials (c) Sudden 
High Voltage by PHCN (d) Improper Planning or Design (e) Inappropriate 
Building Materials (f) Buildings in Close Proximity (g) Others (Specify)………. 
73 What is the estimated distance of Federal Fire Services to your locality ……… 
74 What is the response time to your observed fire incident …………………… 
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75 Has there been any measures by the community or government to combat fire- 
outbreak in the locality (a) Yes  (b)  No 
76 If yes, list the measures………………………...………………………………..... 
…………………………………………………………………………………… 
77 Is your building vulnerable to fire hazard (a) Yes (b) No 
78 If yes, and despite vulnerability to fire-outbreak give reason(s) for the 
continuation of tenancy (a) Nearness to Place of Work (b) Cheaper Rent (c) 
Family House (d) Personal House (e) Others (Specify) ...……………………… 
79 How can fire-outbreak be prevented from occurring in your environment (a) 
Careful Handling of Combustible Materials (b) Electrical  Appliances Should be 
Switched of When not  in Used (c) Using Fire-Resistant Building Material (d) 
Better Design of Infrastructure (e) Adherence to Building Code and Regulations 
(f) Others (Specify)………………..…….. 
 
Information on Building Collapse 
80 Have you ever experienced or witnessed building collapse before (a) Yes  (b) No 
81 If „yes‟ can you recollect the experience of what you witnessed……………… 
.…………………………………………………………………………………… 
82 Is building collapse frequent in your locality (a) Yes  (b) No 
83 If yes, how frequent is the occurrence yearly (a) Once (b) Twice (c) More than 
Twice  
84 What is responsible for building collapse (a) Natural Causes  (b) Human Failure 
or Mistake (c) Age of the Building (d) Structural Defects (e) Substandard 
Building Materials Location of Building (f) Others (Specify) …………………… 
85  Has there been any measure by the community or government to curb collapse 
of building in    Lagos (a) Yes (b) No  
86 If „yes‟ what is/are the measure(s) ……………………………………………… 
87 What can be done to prevent future occurrence of building collapse be? (a) Use 
of Appropriate Building Materials (b) Employment of Qualify Professionals to 
Supervise the Project (c) Proper Design of Building (d) Demolition of Structural 
Inadequate Buildings (e) Others (Specify)…………………………………….. 
 
Information on Land Subsidence 
88 Is any building affected by land-subsidence in your locality (a) Yes  (b) No  
89 If yes, where is/are the building(s) located ………………………………… 
90 What do you think is the cause of the land-subsidence? (a) Natural Causes (b) 
Human Mistake (c) Incessant Bore Hole for Water (d) Structural Defects (e)  
Nature of Soil (f) Others (Specify)………………….............................................. 
91 If land-subsidence is caused by human mistake, which of the following actions 
influenced it? (a) Sinking of Bore Hole  (b) Improper Planning or Design  (c) 
Structurally Defective Building (d) Others (Specify)………………………… 
92 What can be done to avert land subsidence (a) Abolition of Bore Hole (b) 
Provision of Piped Borne Water Network in the Neighbourhood (c) Proper 
Planning  (d) Construction of Structurally Sound Buildings (e) Others 
(Specify)…………………………………. 
93 Has there been any measure by the community or government to combat land 
subsidence in your locality (a) Yes (b) No 
94 If yes what is/are the measure(s)………………………………………………… 
 …..………………………………………………………………………………… 
 
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Information on Diseases Outbreak 
95 Do you know about any health related policies, programmes or law in Lagos state  
(a) Yes (b) No 
96 If yes, are you aware of any sanitation or health regulations affecting your 
household…............................................................................................................... 
97 List the diseases that are link to poor environmental conditions………………… 
98 Have you and any household member suffered from any of the diseases listed (a) 
Yes (b) No 
99 If „yes‟ which of the diseases listed   (a) Cholera (b) Malaria (c) Typhoid Fever (d) 
Measles (e) Others (Specify)………...…………………………… …. 
100 How often is the occurrence of the ailment (a) Frequently (b) Occasionally  
101 When last did the household experience the ailment …………………………… 
102 Despite the ailment give reason for your continuation of tenancy in the present 
housing unit  (a) Nearness to place of work (b) Cheaper Rent (c) Family House (d)  
Personal House  (e) No Other Alternative (f) Others (Specify)……………………. 
103  What do you think was the cause of the disease outbreak (a) Poor Sanitation and 
Inadequate Hygiene Conditions (b) Overcrowding  (c)  Environmental Factors (d) 
Others (Specify)……...................……………………………………………… 
104 What can be done to militate future diseases outbreak in your vicinity (a) Improved 
Personal Hygienic Condition (b) Improve Sanitation (c) Decongestion of Dwelling 
(d) Frequent Drainage Clearance (e) Others (Specify)………………..…………….. 
105 Has there been any measure by the community or government to combat outbreak 
of disease  in your locality (a) Yes (b) No 
106 If yes what is/are the measure(s)………………………………………….……… 
  
E  Disaster Mitigation Measures 
107 Do you know of any disasters management agency in Nigeria? (a) Yes  (b) No 
108 If yes what is the name of the agency?........................................................................ 
109 Has the agency done anything relating to disasters prevention and or management 
within your locality before? (a) Yes  (b) No 
110 If yes, list what the agency had done…………………………………………… 
111 In your own assessment, how efficient/effective is the agency in carrying out her 
responsibility? (a) Not Efficient (b) Averagely efficient (c) Efficient (d) Very 
Efficient  
112 From the disaster or hazard events you had witnessed or affected, did the affected 
populace   receive help from any organization (a) Yes  (b) No 
113 If yes, from which organization (a) Individual/Residents Association (b) 
NGO/Philanthropist Organization (c) Community (d) L.G.A. (e) State Government 
(f) Federal Government (g) International Organization/Foreign Government (h) 
Others (Specify)……………………….. 
114 Who do you think will help in militating or reduce the danger of hazard /disaster in 
your locality (a) Individuals (b) Community Organizations (c) Government 
Disaster Agencies (d) NGOs (e) International Organization (f) Others (specify)….. 
115 Personally, what can be done to improve on disaster management in your 
neighbourhood………………………………………………………………………
……………………………………………………………………………………… 
                                                     
Thank you 
 
 
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Interview Guide for the National and State Emergency Management Agency 
Official(s)  
(Type B Questionnaire) 
Dear Respondents,  
This questionnaire is designed as part of PhD research instrument to seek information on 
Urban Dynamics and Vulnerability to Disasters in Metropolitan Lagos. Your honest 
response will be highly appreciated. Instruction: Please provide or tick the options in the 
column that suits your condition   
General Information of Responsible Officer 
1. Age …...................................…………… 2. Gender …….…………… 
3. Marital Status ………………………….. 4. Religion …………………… 
5. Grade Level / Position Held …………….. 6. Monthly income ………… 
7. Highest Level of Education………............ 8 Ethnic Group ……………… 
Section A: General and Statutory Obligation of the Agency 
8. Location of the Agency ………………………………………… 
9. When was the Agency established?.............................................................. 
10. Please provide the Agency‟s organogram in the space provided………………… 
11. What are the statutory obligations of the Agency…………………………… 
12. Is there any policy framework put in place by the Agency to actualize the 
statutory obligations above………………………………………………… 
13. If yes, please provide the policy ………………………………………………… 
 To what extent has the policy been implemented?.................................................. 
14. Is the Agency enjoying government support to implement the policy?.................. 
15. If yes, how?.............................................................................................................. 
16. What are the Agency‟s sources of funding …………………………………… 
17. What are the statutory allocations and expenditure profile of the agency since 
inception? 
Year Allocations Expenditure 
   
   
   
   
   
   
   
   
   
   
 
Section B Disaster Management and Mitigation 
18. What is the Agency‟s definition of a hazard/disaster?............................................ 
19. How are disasters categorized by the Agency?........................................................ 
20. Give reasons for the categorization above……………………………………… 
21. How many of each category has the Agency managed since its inception? 
................................................................................................................................. 
22. Please give a time series view of each category handled……………………… 
23. Are there specific mitigating measures for each category of disaster?.................... 
24. If yes, what are the mitigating measures for each category?................................... 
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25. How effective are the mitigating measures adopted above to cater for the specific 
disaster………………………………………………………………………… 
26. Is there contingency plan for disaster management in Nigeria? ……………… 
27. If yes, list the types of contingency plans used by the Agency since its inception. 
………………………………………………………………………………… 
28. Is there contingency stock of relief material for disaster victims?........................... 
29. On the average, how much is expended on each type of disaster per 
annum……………… 
30. Has the Agency done disaster simulation to determine the effectiveness of its 
contingency plan and policy?.................................................................................. 
Section C: The Agency and Other Disaster Networks 
31. Are there other networks (public, private and NGOs) affiliated to the Agency in 
disaster management in Nigeria………………………………………………… 
32. Please list the networks………………………………………………………… 
33. Are there specific types of disaster associated with each network?........................ 
34. If yes, please list the types given to each network……………………………… 
………………………………………………………………………………… 
35. How efficient is the Agency in coordinating the activities of other networks in 
pre-, during, and post-disaster phases…………………………………………… 
36. What are the policies put in place to ensure the effective coordination of other 
networks………………………………………………………………………… 
37. What are the impediments militating against the Agency in achieving optimal 
coordination of other disaster networks?................................................................. 
Section D Vulnerability Study 
38. Has the Agency done vulnerability study and disaster mapping of the country…. 
39. If yes, when was the study and mapping carried out…………………………… 
40. What are the vulnerability status of the country before and after the study had 
been carried out……………………………………………………………… 
41. List the types of disasters that are associated with each geo-political zone in 
Nigeria...............………………………………………………………………… 
42. For each zone, what categories of people are the most vulnerable to disasters?..... 
…………………………………………………………………………………… 
43. Is there any relationship between the socio-economic characteristics of the 
inhabitants of each identified vulnerable zone and disasters?................................. 
44. If yes, what has the Agency done to palliate the effects of disasters in such 
environments?......................................................................................................... 
45. List the number of public enlightenment programmes and workshops that the 
Agency had done since its inception…………………………………………. 
46. Are there direct participation of the inhabitants of vulnerable areas to the 
management of disasters in their environments?..................................................... 
 
Section E: Problems of the Agency 
47. What are the problems of the Agency in mitigating disaster in Nigeria since its 
inception?................................................................................................................ 
48. What can be done to solve the stated problems?...................................................... 
49. In general, is the Agency effective to proactively and pre-emptively abate 
disasters in Nigeria………………………………………………… 
50. How do you define efficiency in this regard?.......................................................... 
51. How is the agency well funded to achieve its mission….……………………… 
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52. Is the funding from the ecological fund and other sources used for and or 
sufficient to meet the financial requirements of the Agency?................................. 
53. Does the Agency has adequate manpower (Professionals) to functionally militate 
and manage disasters?.............................................................................................. 
54. Please give an account of a typical day in a disaster response 
period………………………………………………………………………………
……………………………………………………………………………………
…………………………………………………………………………………… 
55. State other relevant comments to this study. ……………………………………. 
 ……………………………………………………………………………………
……….…………………………………………………………………………… 
 …………………………………………………………………………………… 
          
                                                  Thank you. 
  
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Interview Guide for other Disaster Management Networks (Fire Services, Red 
Cross, State and Federal Ministries Construction Companies)  Officials (Type C 
Questionnaire) 
Dear Respondents,  
This questionnaire is designed as part of PhD research instrument to seek information on 
Urban Dynamics and Vulnerability to Disasters in Metropolitan Lagos. Your honest 
response will be highly appreciated. Instruction: Please provide or tick the options in the 
column that suits your condition   
Socio – Economic Characteristics 
1. Age …...............................………….….. 2. Gender ...………………… 
3. Marital Status ………………………….. 4. Religion …………………… 
5. Grade Level / Position Held …………… 6. Monthly income ………… 
7. Highest Level of Education……….......... 8 Ethnic Group ……………… 
Section A: General Information 
8. Location of the Network ……………………………………………………… 
9. When was the network established …………………………………………… 
10. Type of network: Public ……………Private……………….NGO….................. 
11. Please provide the network organogram in the space provided 
12. What are the statutory obligations of the network……………………………… 
 ……………………………………………………………………………………
………….………………………………………………………………………… 
13. Is there any framework adopted by the network to actualize her statutory 
obligations……...………………………………………………………………… 
14. If yes, list the framework…………………………………………………………. 
 …………………………………………………………………………………… 
15. Is the network affiliated to any other international organizations?......................... 
16. If yes, name the organizations…………………………………… 
17. Is the network aware of the activities of the National Emergency Management 
Agency (NEMA) in Nigeria………………………………………....................... 
18. Sources of finance to the network …………………………………………… 
Section B Disasters Management and Mitigation 
19. What is the network‟s definition of a typical disaster?............................................ 
 ……………………………………………………………………………………. 
 What are the types of disaster handled by the network?......................................... 
 …………………………………………………………………………………… 
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20. Does the network has contingency plan for disaster mitigation………………… 
21. If yes, list the contingency plan………………………………………………… 
 …………………………………………………………………………………… 
22. Are the local inhabitants of vulnerable areas and NEMA/SEMA involved in 
drawing up the plan…………………………………………………………… 
23. Has the network given relief materials to disaster victims before?.......................... 
24. If yes, is it given through NEMA/SEMA or directly by the network to the 
victims?........................................... 
25. What types of materials and how are these disbursed to victims?........................... 
 ……………………………………………………………………………………
What can be done to improve the effectiveness of NEMA/SEMA and other 
disaster networks in managing disaster in Nigeria?................................................ 
 ……………………………………………………………………………………
…………………………………………………………………………………… 
26. In general what can be done to proactively and pre-emptively abate disaster in 
the country …...………………………………………………………………….... 
27. What are the shortcomings of the network in mitigating disasters in 
Nigeria?........................…...………………………………………………………
…………………………………………...……………………………………… 
 
Section C Relationship Between Disaster Networks and the Agency 
28. Does the network react to disasters on humanitarian ground or strictly by 
NEMA/SEMA‟s invitation?.................................................................................... 
29. Is the network associated with some specific disaster response?............................ 
30. If yes, list such disasters response…………………………………………….. 
31. Are there specific disaster mandate given to the network by NEMA/SEMA in 
managing disaster in Nigeria…………………………………………………….... 
32. If yes, what are the mandates…………………………………………………….. 
 ………………………………………………………………………………….. 
33. How many disasters have the network responded to under the supervision of 
NEMA…………………………………………………………………………… 
34. Please give a time-series view of disasters handled on your own or in conjunction 
with NEMA since the inception of the Agency………………………………… 
 ……………………………………………………………………………………
….............................................................................................................................. 
35. Is there a cordial relationship between NEMA and other network during disaster 
phases (Pre-, during- and post – disaster)………………………………………… 
………………………………………………………………………………… 
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36. Please give an insight into the significant of NEMA as the institution legally 
responsible for disasters management and coordination of other networks in 
Nigeria since its inception …………………………………………………….. 
37. State other relevant comments to this study.…………………………………. 
 
 
 
 
         Thank You 
 
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Appendix II 
        Building collapse and suspected causes of collapse in Lagos State 1978 - 2013 
No Location of buildings Location of Year of Building types Suspected causes of 
collapse incident collapse 
1 74, western Avenue Surulere 1978 Residential  Structural Defects 
2 38 Lewis Street. Lagos Island Lagos Island 1983 Residential Structural Defects 
3 31, Legeda Street, Iponri, Lagos Lagos Mainland 1983 Residential Structural Defects 
4 27, Ojuelegba Road Surulere 1983 Residential Structural Defects 
5 67, Beecroft Island Lagos Island 1984 Residential Structural Defects 
6 160, Western Avenue, Iponri Surulere 1985 Residential Structural Defects 
7 30, Ojuna  Road, Lagos Island Lagos Island 1985 Residential Structural Defects 
8 64, Ojuelegba Road Surulere 1985 Residential Structural Defects 
9 92, Allen Avenue, Ikeja Ikeja 1985 Residential Structural Defects 
10 112, Bereka Lane, Off Tokunbo street, Lagos Lagos Island 1985 Residential Structural Defects 
11 66, Adeniji Adele, Lagos Lagos Island 1985 Residential Structural Defects 
12 102, Ojuelegba Junction, Ayilara Surulere 1985 Residential Structural Defects 
13 86, Western Avenue, Iponri  Surulere 1986 Residential Structural Defects 
14 44, Usabi, Maryland Ikeja 1986 Residential Structural Defects 
15 112, Orile Iganmu Odunade Bus-stop Ajeromi Ifelodun 1986 Residential Structural Defects 
16 32, Berkley Lane Lagos Island Lagos Island 1986 Residential Structural Defects 
17 41, Idunsagbe Lane, Lagos Island Lagos Island 1986 Residential Structural Defects 
18 115, Agege Way, Lagos Agege 1987 Residential Structural Defects 
19 92, Ikorodu Road, Ketu, Lagos Kosofe 1987 Commercial  Structural Defects 
20 63, Akinade Village, Ikeja Ikeja 1987 Residential Structural Defects 
21 104, Ipetu St. Ikorodu Ikorodu 1987 Residential Structural Defects 
22 20, Idusagbe Lagos Island Lagos Island 1987 Residential Structural Defects 
23 94, Idumagbo Area Lagos Island Lagos Island 1987 Residential Structural Defects 
24 160, Agege Motor Way, Lagos Agege 1987 Residential Structural Defects 
25 77, Adeniji Adele Lagos Island Lagos  Island 1989 Residential Structural Defects 
26 38, Akinwumi Street, Mende Maryland. Ikeja 1989 Commercial (Hotel) Structural Defects 
27 77, Idumota lane,Lagos Island Lagos Island 1989 Commercial (Hotel) Structural Defects 
28 99, Beecroft Lane, Lagos Island Lagos Island 1989 Institutional (School)  Structural Defects 
29 176, Idi-Oro Mushin Mushin 1990 Residential Structural Defects 
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30 201, Idumota Lane Lagos Island Lagos Island 1990 Residential Structural Defects 
31 63, Idumagbo Lane, Lagos Island Lagos Island 1990 Residential Structural Defects 
32 41, Mayosore Close Gbagada Shomulu 1991 Residential Structural Defects 
33 Unilag Akoka Shomulu 1991 Institutional (School) Structural Defects 
34 39, Hawley Road Sabo. Lagos Shomulu 1992 Residential Structural Defects 
35 113,Oyadiran Estate Sabo, Lagos Shomulu 1992 Residential Structural Defects 
36 24, Alfia St. Mushin, Lagos Mushin 1992 Residential Structural Defects 
37 17, Adeniji Close, Bariga, Lagos Shomulu 1993 Residential Structural Defects 
38 103, Airpot Road, Mafoluku Oshodi Oshodi-Isolo 1994 Residential Structural Defects 
39 98, Okesuna Road, Oshodi Oshodi-Isolo 1994 Commercial (Hotel)  Structural Failure 
40 119, Idumagbo Area, Lagos Island Lagos Island 1994 Residential Structural Defects 
41 Block 4, Jakande Estate, Aja Lagos Eti-Osa 1994 Residential Structural Defects 
42 193 Airport Road, Oshodi Oshodi-Isolo 1994 Residential Structural Defects 
43 78, Ayoade street, Ajao Estate Lagos Oshodi-Isolo 1995 Residential Structural Defects 
44 87, Wale Ajose, Mende, Maryland Ikeja 1995 Residential Structural Defects 
45 69, Maryland, Ikeja Ikeja 1995 Residential Structural Defects 
46 67, WAEC Office Road, Ogba Ikeja, Lagos Agege 1995 Religious  Structural Defects 
47 176, Agege Motor Way, Lagos Agege 1995 Residential Structural Defects 
48 161, Maryland, Ikorodu Road Ikeja 1995 Residential Structural Defects 
49 17, Aleyinto street, Agege, Lagos Agege 1995 Residential Structural Defects 
50 16, Gbolahan Street, Iponri Lagos Surulere 1995 Commercial  Structural Defects 
51 17, Iponri, Lagos Lagos Mainland 1996  Residential Structural Defects 
52 112, Alapere Road, Ketu Lagos Kosofe 1996 Institutional (School) Structural Defects 
53 20, Olowokere Str. Oshodi Oshodi-Isolo 1996 Residential Structural Defects 
54 113, Mafoluku Street, Oshodi Oshodi-Isolo 1998 Religious  Structural Defects 
55 63, Igbobi College Way, Igbobi Lagos Shomulu 1998 Residential Structural Failure 
56 41, Olowokere Oshodi Oshodi-Isolo 1999 Religious  Structural Defects 
57 38, Oke Igbala Street, Mushin Mushin 1999 Residential Structural Defects 
58 104, Idusagbe Lane, Lagos Lagos Island 1999 Residential Structural Defects 
59 78, Idumota Lane, Lagos Island Lagos Island 1999 Residential Structural Defects 
60 43, Ikota Way, Ajah Lagos Eti Osa  1999 Commercial  Structural Failure 
61 St Denis Catholic Church,  Akoka Road, Shomulu 2000  Religious  Structural Failure 
Bariga  
62 40, Sanni Street, Itire Lagos Shomulu 2000  Residential Structural Defects 
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63 38, Adeseun Str. Itire Lagos Shomulu 2000 Residential Structural Defects 
64 56A, Adeniji Adele, Lagos Lagos Island 2000 Residential Structural Defects 
65 State High School, Alimosho Alimosho 2000 Institutional (School) Structural Failure 
66 14, Semi Sarumi Street, Itire  Surulere 2000 Residential Structural Defects 
67 Folami Primary School, Atunrase Surulere  2000 Institutional (School) Unreinforced Walls 
68 10/12, Suenu Street, Lagos Island Lagos Island 2000 Residential Deterioration of 
Structural Slabs 
69 Isako Village, Off Lekki-Epe Highway Ibeju-Lekki 2000 Residential Structural Failure 
70 Karunwi Central Mosque, 24, Buhari Street Mushin 2001 Religious  Structural Defects 
71 15, Akewusola Street, Oworonsoki Somolu 2001 Residential Structural Failure 
72 53, Igbosere Lagos Island Lagos Island 2001 Residential  Structural Defects 
73 26, Buari Street Mushin 2001 Residential  Flood 
74 46, Idusagba Lane, Lagos Lagos Island 2001 Residential Structural Defects 
75 20, Otigba Street, Off Pepple Street, Ikeja Ikeja  2002 Mixed Use Structural Defects 
76 3 Storey Building at Mosadolohun Street, Iba  Ojo 2002 Residential Structural Failure 
77 12, Fredrick faseun Avenue, Okota, Isolo Oshodi-Isolo 2002 Residential Structural Failure 
78 18, Agege Road Agege  2002 Commercial  Structural Defects 
79 29, Allen Avenue Ikeja Ikeja  2002 Commercial  Structural Failure 
80 14, Ishiaka Street, Agege Motor Way, Agege Agege 2002 Residential Structural Defects 
81 10, Jones Street, Ebute –Meta West Lagos Mainland 2002 Residential Structural Defects 
82 8, Abeokuta Str, Ebute –Meta West Lagos Mainland 2002 Residential Structural Defects 
83 49, Olonode Str, Yaba Shomulu 2002 Residential Structural Defects 
84 50, Wiloughby Str, Ebute-Meta Lagos Mainland 2003 Residential Structural Defects 
85 31, Tapa Street, Coker Road, Orile-Iganmu Surulere 2003 Residential Structural Failure 
During Construction 
86 57, Bereka Lane, off Tokunbo Street, Lagos Lagos Island 2003 Residential Structural Defects 
87 101, Adeniji Adele Way, Lagos Lagos Island 2003 Residential Structural Defects 
88 31, Shakili Street, Off Ajisomo Street  2003  Structural Failure 
89 61, Ojuelegba Road, Ojuelegba Surulere  2003 Commercial  Construction Defects 
90 28, Idumagbo Street  Lagos Island 2003 Commercial  Explosion from Storage 
of Pyrotechnic Devices 
Used for Fire Work  
91 10 Pedro Street, Lagos Island Lagos Island 2003 Residential Impact of Explosion at 
28, Idumagbo Building  
260 
 
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92 22, Makurdi Street Ebute –Meta Lagos Mainland 2004 Residential Structural Defects 
93 51, Ilasamaja Road, Mushin Lagos. Mushin 2004 Residential Sub-Standard Building 
Materials 
94 10, Eliaqs Street, Lagos Island Lagos Island 2004 Residential Dilapidation/Lack of 
Maintenance 
95 40, Market Street, Somolu Shomulu 2005 Commercial  Structural Defects 
96 73, Kodensoh/B. Anthony Way Ikeja Ikeja 2005 Residential Structural Defects 
97 132, Adeniji Adele Way, Lagos Lagos Island 2005 Residential Structural Defects 
98 6, Princess Street, Lagos Lagos Island 2005 Residential Sub-Standard Building 
Materials 
99 40, Mende Road, Maryland, Ikeja Ikeja  2005 Residential Structural Defects 
100 32, Okesuna Street, Lagos Mushin 2005 Residential Structural Defects 
101 53, Cemetary Road Amukoko Ajeromi Ifelodun 2006 Residential Structural Defects 
102 81, Ijora Way Ajegunle Ajeromi Ifelodun 2006 Residential Structural Defects 
103 17, NIDB Building, Broad Street, Lagos Lagos Island 2006 Institutional  Fire Incidence 
104 71, Ibadan Str, Ebute-Metta West Lagos Mainland 2006 Residential Structural Defects 
105 42, Ibadan Str, E-Metta West Lagos Mainland 2006 Residential Structural Defects 
106 1, Muritala Muhammed  International Airport Oshodi-Isolo 2006 Residential Structural Defects 
Road, Oshodi 
107 6A Milverton Close, Ikoyi Lagos Island 2006 Residential Dilapidation  
108 118, Ojuelegba Road,  Surulere  2006 Residential Structural Defects 
109 38, LASU-Iba Rd, Opp Rosellas Alimosho 2006 Residential Structural Defects 
110 48, Adams street, Okota Lagos Oshodi-Isolo 2006 Residential Structural Defects 
111 38, Idumagbo Avenue, Lagos Lagos Island 2006 Commercial  Structural Defects 
112 32B Edgerton Lane, Oke Arin Lagos Island 2006 Mixed Use Structural Defects 
113 71, Fola Agoro Street, Lagos Shomulu 2006 Residential Structural Defects 
114 8, Ashaka Street, Abule Nla, Ebute-Metta Lagos Mainland 2006 Residential Structural Defects 
115 Ebute-Metta, Lagos Lagos Mainland 2007 Residential Unauthorized 
Conversion/Sub-
Standard Materials 
116 19, Ijaotun Street, Alapere Ketu Kosofe   2008 Residential Structural Defects 
117 13, Ojuelegba Intersection Shomulu 2008 Commercial  Structural Defects 
118 14, Miltivek Road, Ajah Multi -millionaire Etiosa 2008 Residential Structural 
Building Defects/Overloading 
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119 24, Okepopo Area, Lagos Lagos Island 2008 Residential Structural Defects 
120 17, Alasaro Central Mosque Mushin Olosa Mushin 2008 Religious  Structural Defects 
121 Under Construction Building at Ikeja behind Ikeja 2008 Mixed Use Weak Structure and 
Juli Pharmacy Sub-Standard Building 
Materials 
122 42, Ojerinde Street, Mushin Mushin 2009 Residential Structural Defects 
123 14, Fasasi Street, Ajegunle Apapa Lagos Ajeromi Ifelodun 2009 Residential Structural Defects 
124 4, Goddy‟s Park Railway Terminus, Ido Lagos Mainland 2009 Commercial  Dilapidation/Lack of 
Lagos Maintenance  
125 4, Bada Street, Lagos Lagos Island 2009 Residential Weak Structure 
126 Building Under Construction, Isopakodowo, Oshodi-Isolo 2010 Commercial  Sub-Standard Building 
Cairo Oshodi Materials 
127 Uncompleted Building at Adenike Street, Off Eti-Osa 2010 Residential Weak Structure and 
New Market, Oniru Estate, Victoria Island Sub-Standard Building 
Materials 
128 24, Ali Street, Off Tinubu Street, Victoria Eti-Osa 2010 Commercial  Structural 
Island Defects/Overloading 
129 Mogaji Lane, Idunshagbe Street, Off John Lagos Island 2011 Residential Overloading/Structural 
Street, Idumota Defects 
130 20, Doyin Street Omololu Street, Obanlearo, Kosofe  2011 Residential Land Subsidence 
Alapere, Ketu 
131 12, Olanuji Street, Iju-Ishaga Ifako-Ijaiye 2012 Residential Dana Air Crash Impact 
132 14, Popoola, Street, Iju-Ishaga Ifako-Ijaiye 2012 Residential Dana Air Crash Impact 
133 No. 3 Anikantamo street, Lagos Island Lagos Island 2012 Residential Dilapidated 
Pillar/Structural Defects 
134 Church Street, Jakande Estate, Oke-Afa, Oshodi-Isolo 2012 Residential Weak Structure and  
Isolo. Sub-Standard Materials 
135 Layeni Primary School, Ajegunle. Ajeromi Ifelodun 2013 Institutional (School) Weakened Blocks 
136 14, Bashiru Street, Ojodu Berger. Ikeja  2013 Residential Defective structural 
137 29b,  Oloto Street, Off Cemetery Road, Ebute Lagos Mainland 2013 Residential Overloading and 
Metta defective Structure 
138  29, Onasanya Street, Off Ishaga Road, Siurulere 2013 Residential Structural degeneration 
Surulere 
Sources: Lagos State Physical Development Planning Authority (LASPDA) (2010) and Ayedun, et al. (2012 
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Appendix III 
NEMA Summary of Relief Materials Interventions to State Affected by Disasters 2010, 2011 and 2012 
TYPES OF 
S/N States LGAs EFFECTS MATERIALS GIVEN 
DISASTERS 
1.  Abia Amaekpu-Item Windstorm 180 Houses and other (i) 300 bags of rice 
community in Properties Destroyed. (ii) 300 bags of beans 
Bende LGA (iii) 300 bags of maize 
(iv) 600 bags of cement 
(v) 500 bundles of roofing sheets 
(vi) 2,000 pcs of 2x3x12 planks 
(vii) 2000 pcs of 2x4x12 planks 
(viii) 100 bags of roofing nails 
(ix) 100 packets of zinc nails 
(x) 350 pcs of bath towels 
(xi) 200 pcs of plastic buckets 
(xii) 350 pcs of wax prints  
(xiii) 200 pcs of mattresses  
2.  Adamawa Patara, Saminaka, Windstorm 1,562 families displaced (i) 1,200 bundles of roofing sheets  
Dadinkowa and and destructions of (ii) 1,200 bags of cement 
Song wards of properties (iii) 100 packets of zinc 
Bagani of Lamurde (iv) 100 bags of 3" nails  
(v) 1500 pieces of 2x3x12 planks 
(vi) 1500 pieces of 2x4x12 planks 
3.  Akwa-Ibom Idua and Eyo Abasi Communal crisis 429 families were (i) 800 bundles of roofing sheets  
in Oron LGA displaced (ii) 1,200  pieces of 2x3x12 planks 
(iii) 1,200  pieces of 2x4x12 planks 
(iv) 800 bags of cement 
(v) 100 packets of zinc 
(vi) 100 bags of 3" nails  
4.  Akwa-Ibom  Itak Abasi Ocean surge Destruction of (i) 50 pieces of sewing machines (butterfly) 
community in Ibeno properties, 5000 persons (ii) 50 pieces of grinding machines (Honda) 
LGA affected and loss of 5 (iii) 5 Almarine A19 Utility Canoes Powered by Yamaha 40HP 
lives (iv) 5 Almarine A19 Utility Canoes Powered by Yamaha 75HP 
(v) 100 bundles of stroke 45 deep fishing nets 
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(vi) 100 bundles of stroke 9 deep fishing nets 
(vii) 500 bags of garri 
(viii) 200 cartons of 3-in-1 tea 
(ix) 100 cartons of bath soaps 
(x) 1500 pieces of bath towels 
(xi) 1000 pieces of blankets 
(xii) 2000 pieces of wax prints 
(xiii) 300 pieces of mattresses 
(xiv) 500 pieces of nylon mats 
(xv) 4 bales of used cloths 
(xvi) 400 pieces of cooking pots 
(xvii) 500 pieces of kegs 
(xviii) 400 pieces of kerosene stoves 
(xix) 1000 pieces of plastic cups 
(xx) 1000 pieces of plastic buckets 
(xxi) 1200 bags of cement 
(xxii) 790 bundles of roofing sheets 
(xxiii) 1500 bags of rice 
(xxiv) 500 bags of garri 
(xxv) 400 bags of beans  
(xxvi) 100 kegs of vegetable oil 
(xxvii) 100 kegs of palm oil 
(xxviii) 200 bags of salt 
(xxix) 200 bags of sugar 
5.  Akwa - Ibom Uyo, Itu and Etim- Heavy downpour  Affected 3 LGAs, (i) 400 bundles of roofing sheets 
Ekpo LGAs displaced 1,105 persons, (ii) 336 bags of cement 
livestock and farm land (iii) 168 pieces of mattresses 
affected with 168 houses (iv) 376 pieces of blankets 
destroyed. (v) 336 pieces of bath towel 
(vi) 100 cartons of bath soap 
(vii) 168  pieces of buckets  
(viii) 20 cartons of 3-in-1 tea 
(ix) 2,550 pieces of 2x3x12 planks 
(x) 2,550 pieces  of 2x4x12 planks 
(xi) 1,200 pieces of plastic plates 
(xii) 1200 pieces of plastic cups  
(xiii) 200 bags of garri 
(xiv) 200 bags of beans 
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(xv) 200 kegs of vegetable oil  
6.  Akwa-Ibom / Ntan Obu in Cross- Communal clash Loss of 3 lives, (i) 600 bags of cement  
Cross River  River and Ikpanyah destruction of 800 (ii) 600 bundles of roofing sheets 
Ibiono in Akwa- houses and displacement (iii) 100 packets of zinc nails 
Ibom LGAs of 3000 persons. (iv) 100 bags of 3" nails 
(v) 1200 pieces of 2x3x12 planks 
(vi) 1200 pieces of 2x4x12 planks 
(vii) 600 bags of rice 
(viii) 500 pieces of blankets 
(ix) 200 pieces of nylon mats 
(x) 500 pieces of plastic buckets 
(xi) 500 pieces of plastic plates 
(xii) 500 pieces of plastic spoons 
(xiii) 500 pieces of plastic cups 
(xiv) 200 cartons of detergent 
(xv) 500 bags of garri 
(xvi) 300 pieces of mattresses  
(xvii) 100 bundles of stroke 45 fishing nets 
(xviii) 100 bundles of stroke 9 fishing nets 
7.  Anambra Oyi, Ekwusigo and Flood/ 1,010 Persons (i) 1000 pcs of 2x3x12 planks 
Ihiala LGAs Windstorm Displaced (ii) 1000 pcs of 2x4x12 planks 
(iii) 250 bundles of roofing sheets 
(iv) 50 bags of roofing nails 
(v) 50 packets of zinc nails 
(vi) 300 bags of cement 
(vii) 150 bags of rice 
(viii) 100 bags of beans 
(ix) 150 bags of garri 
(x) 100 jerry cans of palm oil 
(xi) 100 jerry cans of v. Oil 
(xii) 200 pieces of mattresses  
(xiii) 1000 pcs of plastic buckets 
(xiv) 1000 pcs of wax prints 
(xv) 1000 pcs of bath towels 
(xvi) 1000 pcs of blankets 
(xvii) 50 bags of salt 
8.  Anambra Onitsha, Anambra Flood disaster Destruction of 25 (i) 300 bags of rice 
East and West LGA residential houses and (ii) 300 bags of beans 
properties worth millions (iii) 300 bags of maize 
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of naira. (iv) 300 bags of garri 
(v) 100 kegs of vegetable oil 
(vi) 100 kegs of palm oil 
(vii) 1000 pieces of blankets 
(viii) 1000 pieces of bathing towel 
(ix) 1000 pieces of plastic buckets 
(x) 500pieces of wax print 
(xi) 100 carton of bath soap 
(xii) 300 pieces of mattresses 
(xiii) 50 cartons of detergent 
(xiv) 100 cartons of 3-in-1 tea 
(xv) 5 bales of second hand cloths 
(xvi) 600 bags of cement 
(xvii) 500 bundled of roofing sheets 
(xviii) 2500 pieces of 2x3x12 planks 
(xix) 2500 pieces of 2x4x12 planks 
(xx) 100 packets of zinc nails 
(xxi) 100 bags of 3” nails 
9.  Bauchi  Das, Shira, Religious crisis Displacement of 10,000 (i) 2000 pieces of blankets 
Gaujuwa, Gamawa, persons (ii) 1000 pieces of nylon mats 
Towa and Tafawa (iii) 100 cartons of toilet soap 
Balewa LGAs (iv) 100 cartons of detergent 
(v) 1000 pieces of plastic plates 
(vi) 1500 pieces of plastic cups 
(vii) 1200 pieces of plastic spoons 
(viii) 700 bags of rice 
(ix) 500 bags of millet 
(x) 400 bags of guinea corn 
(xi) 50 bags of salt 
(xii) 400 cartons of 3-in-1 tea 
(xiii) 3 bales of children‟s wear 
(xiv) 250 bags of maize 
(xv) 100 bags of garri 
(xvi) 100 kegs of palm oil 
(xvii) 100 kegs of vegetable oil 
10.  Bauchi  Lere  Jos religious 10,000 IDPs (i) 5,976 bags of cement 
mayhem (ii) 340 bundles of roofing sheets 
(iii) 4,080 pieces of 2x3x12 planks 
(iv) 4,080 pieces of 2x4x12 planks 
(v) 136 packets of zinc nails 
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(vi) 34 bags of 3" roofing nails 
11.  Bayelsa  Ekeki and Yenago Bakassi 2000 families displaced (i) 50 sewing machines (Butterfly) 
LGA Returnees (ii) 50 grinding machines (Honda) 
(iii) 50 standing hair dryers (Cerriotic)  
(iv) 100 barbing clippers (Whal) 
(v) 200 bundles of stroke 9 deep fishing nets 
(vi) 200 bundles of stroke 45 deep fishing nets 
(vii) 300 bags of garri 
(viii) 50 kegs of vegetable oil 
(ix) 50 kegs of palm oil 
(x) 50 bags of sugar 
(xi) 50 bags of salt 
(xii) 200 cartons of omo 
(xiii) 400 bags of rice 
(xiv) 300 bags of beans 
(xv) 150 cartons of soap 
12.  Bayelsa  Sagbama, Flood disaster Displacement of 70,000 (i) 1800 bags of rice 
Kolokuma persons (ii) 1200 bags of garri 
Opokuma, (iii) 600 bags of beans 
Yenegoa, Southern (iv) 300 kegs of vegetable oil 
Ijaw, Brass, (v) 500 bags of salt 
Ekeremor, Nembe (vi) 500 bags of sugar 
and Ogbia LGAs (vii) 300 kegs of palm oil 
(viii) 500 cartons of 3-in-1 tea 
(ix) 500 cartons of bath soap 
(x) 500 cartons of omo 
(xi) 1000 pieces of bath towels 
(xii) 2000 pieces of buckets  
(xiii) 2000 pieces of plates 
(xiv) 2000 pieces of spoons 
(xv) 2000 pieces of cups 
(xvi) 2000 pieces of blankets 
(xvii) 2000 pieces of mattresses 
(xviii) 2000 pieces of wax prints 
(xix) 2000 pieces of nylon mats 
nd
(xx) 6 bales of 2  hand cloths 
(xxi) 1500 pieces of cooking pots 
(xxii) 1000 pieces of water cans 
(xxiii) 1000 pieces of kerosene stoves 
(xxiv) 1000 bags of cements 
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(xxv) 1000 bundles of roofing sheet 
(xxvi) 600 bags of roofing nails 
(xxvii) 1000 packets of zinc nails 
(xxviii) 5000  pieces of 2x3x12 planks 
(xxix) 5000  pieces of 2x3x12 planks 
 
13.  Benue Otukpo, Odugbo, Flood/ Displacement of People, (i) 600 bags of cement 
and Kwade LGA Rainstorm Schools and Properties (ii) 500 bundles of roofing sheets 
were Destroyed (iii) 1000 pcs of 2x3x12 planks 
(iv) 1000 pcs of 2x4x12 planks 
(v) 50 bags of roofing nails 
(vi) 100 packets of zinc nails 
(vii) 500 pcs of blankets 
(viii) 500 pcs of bath towels 
(ix) 30 cartons of bath soap 
(x) 100 pcs of mattresses  
(xi) 500 pcs of nylon mats 
(xii) 500 pcs of plastic buckets 
(xiii) 500 pcs of plastic plates 
(xiv) 500 pcs of plastic cups 
(xv) 300 pcs of wax prints 
(xvi) 300 bags of rice 
(xvii) 150 bags of beans 
(xviii) 150 bags of maize 
(xix) 150 bags of millets 
(xx) 50 bags of salt 
(xxi) 50 bags of garri     
 
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14.  Benue Vandeikys LGA Rain/ Windstorm Collapsed buildings and (i) 300 bags of cement 
Disaster falling of economic (ii) 200 bundles of roofing sheets 
trees, 119 People (iii) 500 pcs of 2x3x12 planks 
Displaced. (iv) 500 pcs of 2x4x12 planks 
(v) 100 bags of roofing nails 
(vi) 100 packets of zinc nails 
(vii) 150 bags of rice 
(viii) 100 bags of beans 
(ix) 100 bags of millets 
(x) 100 bags of maize 
(xi) 50 bags of garri 
(xii) 150 pcs of mattresses  
(xiii) 150 pcs of plastic buckets 
(xiv) 150 pcs of plastic plates 
(xv) 150 pcs of plastic spoons 
(xvi) 150 pcs of plastic cups 
(xvii) 30 cartons of bath soap 
(xviii) 30 packets of bath towels 
(xix) 30 kegs of v/oil      
(xx) 30 kegs of palm oil 
(xxi) 180 pcs of wax prints 
15.  Borno Shettimah, Abogu Civil Loss of two (2) lives, (i) 300 bags of cement 
village in Damba disturbances  destruction of 102 (ii) 750 pieces of 2x3x12 planks 
LGA houses & displacement (iii) 750 pieces of 2x4x12 planks 
of about 1000 (iv) 20 bags of 3 roofing nails 
households (v) 20 packets of zinc nails 
(vi) 100 bags of maize 
(vii) 100 bags of guinea corn 
(viii) 100 bags of millet 
(ix) 200 bags of rice 
(x) 100 pieces of mattresses 
(xi) 300 bundles of roofing sheets 
 
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16.  Borno  Kala, Balge, Pest invasion and Destruction of 200 (i) 100 bags of guinea corn 
Magulmeri LGA flood houses and destruction (ii) 100 bags of maize 
of farm lands (iii) 100 bags of beans 
 (iv) 150 bags of rice 
(v) 50 kegs of vegetable oil 
(vi) 300 bags of cement 
(vii) 1200 pieces of 2x3x12 planks 
(viii) 1200 pieces of 2x4x12 planks 
(ix) 50 bags of 3 “ nails 
(x) 300 bundles of roofing sheets 
17.  Cross River Agwagune and Flood, landslide, Displacement of 1132 (i) 500 bundles of roofing sheets 
Boki LGAs windstorm and persons, destruction of (ii) 150 bags of 3” nails 
fire 383 houses (iii) 1500 pieces of 2x3x12 planks 
(iv) 1500 pieces of 2x4x12 planks 
(v) 150 packets of zinc nails 
(vi) 400 bags of rice 
(vii) 500 pieces of blankets 
(viii) 300 cartons of bath soap 
(ix) 1000 pieces of plastic buckets 
(x) 1000 pieces of plastic plates 
(xi) 1000 pieces of plastic spoons 
(xii) 200 cartons of omo 
(xiii) 200 pieces of iron beds 
(xiv) 600 bags of cement 
18.  Cross River Yala, Bekwarra, Flood Destruction of 1,005 (i) 3000 pieces of 2x3x12 planks 
Obudu, Ogoja, houses and displacement (ii) 3000 pieces of 2x4x12 planks 
Obaniku and Boki of 1,885 persons (iii) 1200 bags of cement 
LGAs (iv) 100 bags of 3” nails 
(v) 100 packets of zinc nails 
(vi) 500 pieces of blankets 
(vii) 400 pieces of mattresses 
(viii) 1000 bundles of roofing sheets 
(ix) 500 pieces of spoons 
(x) 500 pieces of cups 
(xi) 500 pieces of plates 
(xii) 500 pieces of buckets 
(xiii) 200 pieces of iron beds 
(xiv) 100 cartons of omo 
(xv) 100 cartons of bath soaps 
(xvi) 500 pieces of nylon mats 
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(xvii) 500 pieces of bath towels 
 
 
19.  Cross River Boki LGA Communal clash Loss of 30 lives and (i) 100 bags of rice 
destruction of 343 (ii) 100 bags of beans 
houses (iii) 200 pieces of mattresses 
(iv) 100 cartons of bath soap 
(v) 100 cartons of detergent 
(vi) 500 pieces of bath towels 
(vii) 500 pieces of wax prints 
(viii) 500 pieces of plastic spoons 
(ix) 500 pieces of plastic plates 
(x) 250 pieces of nylon mats 
(xi) 100 pieces of plastic buckets 
(xii) 100 pieces of blankets 
20.  Delta  Isoko north, Isoko Flood and Destruction of 500  (i) 400 bundles of roofing sheets 
south, Burutu, windstorm  houses and displacement (ii) 100 packets of zinc nails 
Bomadi LGA of 1225 persons (iii) 100 bags of 3” nails 
(iv) 1000 pieces of 2x3x12 planks 
(v) 1000 pieces of 2x4x12 planks 
(vi) 300 bags of cement  
(vii) 200 pieces of mattresses 
(viii) 300 pieces of blankets 
(ix) 500 pieces of wax prints 
(x) 500 pieces of bath towels 
(xi) 300 bags of rice 
(xii) 300 bags of garri 
(xiii) 150 bags of beans 
(xiv) 100 cartons of 3-in-1 tea 
(xv) 100 bags of sugar 
(xvi) 100 bags of salt 
(xvii) 50 jerry cans of palm oil 
(xviii) 600 pieces of plastic buckets 
21.  Ebonyi Ezza and Ezillo Communal Clash 571 People Displaced, (i) 300 bags of rice 
Ishielu LGA and Properties (ii) 300 bags of beans 
Destroyed. (iii) 300 bags of maize 
(iv) 400 bags of garri 
(v) 50 jerry cans of palm oil 
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(vi) 50 jerry cans of v/oil 
(vii) 1,500 pcs of plastic plates 
(viii) 100 bags of salt 
(ix) 1,500 pcs of plastic cups  
(x) 1,500 pcs of plastic spoons 
(xi) 500 pcs of blankets 
(xii) 500 pcs of bath towels 
(xiii) 500 pcs of plastic buckets 
(xiv) 500 pcs of wax prints 
(xv) 50 cartons of omo detergent  
(xvi) 50 cartons of bath soap 
(xvii) 500 pcs of nylon mats 
(xviii) 200 pcs of mattresses  
 
22.  Ekiti  Gbonyin, Ise Orun, Flood   (i) 400 bundles of roofing sheets 
Ado Ekiti, Ekole, (ii) 100 packets of zinc nails  
Ekiti East, Ijero (iii) 100 bags of 3‟‟ nails  
LGA (iv) 250 pieces of blankets 
(v) 1000 pieces of 2x3x12 planks 
(vi) 1000 pieces of 2x4x2 planks 
(vii) 250 pieces of mats  
(viii) 150 kegs  of vegetable oil 
(ix) 2 bales of second hand clothes 
(x) 300 bags of rice 
23.  Ekiti  Flood  A life was lost, buildings (i) Roofing sheets: 300 bundles 
collapsed, about 500 (ii) 2x3x12 planks:200 pieces   
persons displaced. (iii) 2x4x12 planks: 200 pieces 
Cash/food crops worth (iv) Cement:300 bags 
millions of naira were (v) Zinc nails: 20 packets 
also lost (vi) 3” nails: 20 bags 
(vii) Rice: 150 bags 
(viii) 3-in-1 tea:50 cartons 
(ix) Blankets: 100 pieces 
(x) Wax prints: 100 pieces. 
24.  Enugu Agwu LGA Windstorm 480 Houses affected and (i) 2,000 pcs of 2x3x12 planks 
231 Families Displaced. (ii) 2,000 pcs of 2x4x12 planks 
(iii) 300 bundles of roofing sheets 
(iv) 100 bags of roofing nails 
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(v) 100 packets of zinc nails 
(vi) 600 bags of cement 
(vii) 200 bags of rice 
(viii) 150 bags of beans 
(ix) 50 jerry cans of v/oil 
(x) 50 jerry cans of palm oil 
(xi) 150 bags of maize 
25.  Enugu  Udi LGA Flood   (i) 200 bags of rice  
Destruction of  (ii) 150 bags of beans 
residential houses, farm (iii) 150 bags of maize 
lands and properties (iv) 150 bags of garri 
worth millions of naira. (v) 50 kegs of vegetable oil 
2 lives lost and 1,253  
(vi) 50 kegs of palm oil 
people displaced. 
(vii) 50 bags of salt 
(viii) 50 bags of granulated sugar 
(ix) 500 pcs of blankets 
(x) 500 pcs of bathing towels 
(xi) 500 pcs of plastic buckets 
(xii) 500 pcs of nylon mats 
(xiii) 50 cartons of bath soap 
(xiv) 50 cartons of omo detergent 
(xv) 50 cartons of 3-in-1 tea 
(xvi) 500 pcs of waxprints 
(xvii) 500 pcs of mattresses 
26.  Gombe  Denga-Gamawa, Communal clash Displacement of 870 (i) 200 bags of rice 
Garin Laman, persons and loss of (ii) 150 bags of guinea corn 
Dumdadu LGA properties  (iii) 100 bags of millet 
(iv) 200 bags of maize 
(v) 400 pieces of nylon mats 
(vi) 1500 pieces of blankets 
(vii) 50 bags of salt 
(viii) 20 kegs of vegetable oil 
(ix) 10 kegs of palm oil 
(x) 50 cartons of detergent 
27.  Gombe  Gombe Petroleum tanker Loss of 17lives,  injuries (i) 600 bags of cement 
metropolitan  incidence  of few persons and (ii) 2,000 pieces of 2x3x12 planks 
destruction of 120 (iii) 2,000 pieces of 2x4x12 planks 
houses (iv) 1,000 bundles of roofing sheets 
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(v) 100 packets of zinc nails 
(vi) 100 bags of 3" roofing nails 
(vii) 120 bags of rice 
(viii) 60 bags of maize 
(ix) 60 bags of guinea corn 
(x) 60 bags of millet 
(xi) 60 bags of beans 
28.  Imo State  Communal 1,562 Persons Displaced, (i) 200 bags of rice 
Clashes and Properties (ii) 200 bags of beans 
Destroyed. (iii) 200 bags of maize 
(iv) 400 bags of garri 
(v) 50 kegs of palm  
(vi) 600 bags of cement 
(vii) 500 pcs of mattresses  
(viii) 1,500 pcs of 2x3x12 planks 
(ix) 1,500 pcs of 2x4x12 planks 
(x) 300 bundles of roofing sheets 
(xi) 50 packets of zinc nails 
(xii) 50 bags of roofing nails 
(xiii) 10 bales os used cloths 
(xiv) 500 pcs of wax prints  
(xv) 500 pcs of bath towels 
(xvi) 1,000 pcs of blankets 
(xvii) 1,500 pcs of plastic buckets 
(xviii) 100 bags of salt 
(xix) 1,000 pcs of nylon mats 
29.  Imo State Owerri North and Flood 111 houses were (i) 300 bags of rice 
Ehima Mbano destroyed and 500 (ii) 300 bags of beans 
LGAs families displaced (iii) 300 bags of maize 
(iv) 200 bags of garri 
(v) 100 cartons of tea 
(vi) 100 bags of salt 
(vii) 100 kegs of palm oil 
(viii) 100 kegs of vegetable oil 
(ix) 600 bags of cement 
(x) 200 bundles of roofing sheets 
(xi) 1500 pieces of 2x3x12 planks 
(xii) 1500 pieces of 2x4x12 planks 
(xiii) 100 packets of zinc nails 
(xiv) 100 bags of 3” nails 
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(xv) 1000 pieces of wax print 
(xvi) 300 pieces of mattresses 
(xvii) 1000 pieces of blankets 
(xviii) 1000 pieces of plastic buckets 
(xix) 1000 pieces of plastic cups 
(xx) 1000 pieces of plastic plates 
(xxi) 200 pieces of spring beds 
30.  Jigawa Hadejia, Buji, Flood Displacement of 194 (i) Rice: 100 bags    
Jahun, Ringim, men, 233 women and (ii) Beans: 25 bags   
Dutse, Babura and 562 children making a (iii) 3-in-1 tea:50 carton  
Gagarawa LGA total of 989 registered (iv) Mattress:100 pieces  
persons. (v) Nylon mat: 200 piece 
(vi) Blankets: 300 pieces 
(vii) Soap:25 cartons  
(viii) Detergent: 25 cartons  
31.  Kaduna Chukun  LGA Flood The damage caused by (i) 600 bags of cement 
this disaster has brought (ii) 100 bundles of roofing sheet 
untold hardship to about (iii) 50 bags of zinc nails 
54 families (about 270 (iv) 20 bags of roofing nails 
inhabitants) (v) 1,000 pieces of 2x3x12 planks 
(vi) 1,000 pieces of 2x4x12 planks 
(vii) 75 bags of  beans 
(viii) 50 bags of rice 
(ix) 20 bags of maize 
(x) 20 bags of millets 
(xi) 20 bags of 100kg guinea corn 
(xii) 100 pieces of blankets 
32.  Kano Kumbo, Wosarana, Fire and flood The rainstorm led to the (i) 400 bundles of roofing sheets 
Kiru and Dambatta disasters destruction of properties (ii) 100 packets of zinc nails 
LGAs worth 20 million Naira (iii) 100 bags of 3” nails 
and displacement of 500 (iv) 1000 pieces of 2x2x12 planks 
people (v) 1000 pieces of 2x4x12 planks 
(vi) 500 pieces of blankets 
(vii) 600 bags of cement 
(viii) 600 bags of rice 
(ix) 300 bags of maize 
(x) 200 pieces plastic buckets 
(xi) 300 bags of millet 
33.  Kano Ungogo LGA Windstorm The disaster resulted in (i) 400 bundles of roofing sheets 
275 
 
UNIVERSITY OF IBADAN LIBRARY
the displacement of 478 (ii) 100 packets of zinc nails 
persons and destruction (iii) 100 bags of 3” nails 
of properties of the (iv) 1000 pieces of 2x3x12 planks 
inhabitants (v) 1000 pieces of 2x4x12 planks 
(vi) 500 pieces of blankets 
(vii) 300 bags of cement 
(viii) 300 bags of rice 
(ix) 150 bags of maize 
(x) 200 pieces of plastic buckets 
(xi) 150 bags of millet  
34.  Kano   Donation of 719 inmates at the (i) 719 matresses 
relief items rehabilitation centers (ii) 719 blankets 
35.  Kano  Relief items to -do- (i) 981 pieces of mattresses 
inmates of 14 (ii) 981 pieces of blankets 
numbers 0f Kano (iii) 1000 pieces of wax prints 
Rehab. Centers (iv) 500 pieces of mosquito nets 
(v) 300 bags of rice 
(vi) 300 bags of beans 
(vii) 300 bags of maize 
36.  Katsina Dandume, Kastina, Flood 1 person died, 889 (i) Cement:600 bags  
Batagarawa, Baure, houses were destroyed, (ii) Roofingsheets:400 bundles  
Danja, Funtua, 1,066 households were (iii) Zincnails:100 packets  
Kusada, Rimi, affected, and properties (iv) Roofingnails:100 bags  
Ingea, Zango LGAs worth millions of naira (v) 2x3x12 planks:1,000pieces 
were lost (vi) 2x4x12 planks:1,000 pieces  
(vii) Rice:300 bags  
(viii) Beans:150 bags  
(ix) Corn flour:300 bags  
(x) Guinea corn: 150 bags  
(xi) Blankets:500 pieces  
(xii) Plastic buckets: 500 pieces  
(xiii) Palm oil: 200 kegs  
37.  Katsina Dutsin-macharanchi Flood Displacement of about (i) Rice:  200 bags  
LGA 1,400 household. (ii) Maize:200 bags  
(iii) Millet:100 bags  
(iv) Guinea corn:100 bags  
(v) Palm oil: 20 jerry cans 
(vi) Vegetable oil: 20 kegs 
276 
 
UNIVERSITY OF IBADAN LIBRARY
(vii) 3-in-1 tea:70 cartons  
(viii) Plastic spoons:170 pieces  
(ix) Plastic cups:170 pieces 
(x) Plastic plates:170 pieces  
(xi) Sugar: 20 bags  
(xii) 70 cartons of soap 
 
(i) Rice: 100 bags  
(ii) Maize:100 bags  
(iii) Millet: 50 bags millet 
(iv) guinea corn:50 bags  
(v) Palm oil:10 jerry cans 
(vi) Vegetable oil: 10 kegs 
(vii) 3-in-1 tea:30 cartons  
(viii) plastic spoons:80 pieces  
(ix) Plastic cups:80 pieces  
(x) plastic cups:80 pieces  
(xi) Sugar:10 bags  
(xii) Soap: 30 cartons  
38.  Kebbi Birnin Kebbi, Jega, flood No of affected (i) Guinea corn: 300 bag  
Maiyams, Koko, household: 194,No of (ii) Millet: 150 bags  
Gwandu, Suru, affected women and (iii) Maize:150 bags  
Yuri, Arewa, children:7711,No of (iv) Rice: 200 bags  
Akaigo, Bunza, and deaths:6, No of IDPs:19, (v) Nylon mats: 1,500 pieces  
Kalgo LGAs total no of victims: 9763. (vi) Mattress:300 pieces  
(vii) 3-in-1 tea:200 cartons  
(viii) Blankets:1,500 pieces  
(ix) Soap:100 cartons  
(x) Omo: 25 cartons  
(xi) Sugar: 50 bags  
39.  Kogi Bassa LGA Communal Clash Loss of 400 lives, and (i) 200 bags of cement 
Destruction of (ii) 100 bundles of roofing sheets 
Properties. (iii) 300 pcs of 2x3x12 planks 
(iv) 300 pcs of 2x4x12 planks 
(v) 40 packets of roofing nails 
(vi) 40 bags of zinc nails 
(vii) 50 kegs of vegetable oil  
(viii) 50 bags of rice 
(ix) 50 bags of beans 
277 
 
UNIVERSITY OF IBADAN LIBRARY
(x) 50 bags of maize 
(xi) 50 bags of guinea corn 
(xii) 100 pcs of plastic buckets 
(xiii) 100 pcs of plastic plates 
(xiv) 100 pcs of plastic cups 
(xv) 100 pcs of blankets 
(xvi) 100 pcs of bath towels 
(xvii) 100 pcs of mattresses  
(xviii) 100 pcs of wax prints  
(xix) 100 pcs of nylon mats 
(xx) 10 bags of salt 
40.   Kogi Kabba Bunu LGA Flood Disaster 76 Families were (i) 76 pcs of mattresses  
Affected and Properties (ii) 150 bags of rice 
Destroyed. (iii) 150 bags of beans 
(iv) 150 bags of maize 
(v) 76 pcs of blankets 
(vi) 76 pcs of wax prints  
(vii) 76 pcs of plastic buckets  
41.  Kogi  Kogi LGA Flood  1,500 persons displaced (i) 250 bags of rice 
with properties destroyed (ii) 250 bags of beans 
(iii) 200pcs of mattresses 
(iv) 500 pcs of nylon mat 
(v) 500 pcs of blankets 
(vi) 500 pcs of plastic buckets 
(vii) 150 pcs of fishing nets 
42.  Kwara Assa, Moro, Fire/ Rainstorm 9,000 People Displaced, (i) 300 bags of millet 
Ifelodun and Iiorin and Properties Destroyed (ii) 300 bags of beans 
LGAs (iii) 300 bags of maize 
(iv) 300 bags of rice 
(v) 600 bags of cement 
(vi) 600 bundles of roofing sheets 
(vii) 1,500 pcs of 2x3x12 planks 
(viii) 1,500 pcs of 2x4x12 planks 
(ix) 150 packets of zink nails 
(x) 150 bags of roofing nails 
(xi) 500 pcs of wax prints 
(xii) 200 pcs of mattresses 
(xiii) 300 pcs of plastic buckets 
278 
 
UNIVERSITY OF IBADAN LIBRARY
43.  Lagos Kosofe LGA Flood  The destruction of (i) 250 pieces of wax prints 
properties and (ii) 500 pieces of towels 
displacement of 1,053 (iii) 1000 pieces of plates 
persons (iv) 1000 pieces of cups 
(v) 1000 pieces of spoons 
(vi) 500 pieces of blankets 
(vii) 500 pieces of mats 
(viii) 300 bags of rice 
(ix) 250 pieces of mattresses 
(x) 300 pieces of plastic buckets 
(xi) 150 bags of beans 
(xii) 300 bags of garri 
(xiii) 50 kegs of vegetable oil 
(xiv) 20 cartons of detergent 
(xv) 20 cartoons of bathing soap 
(xvi) 20 cartoons of washing soap 
(xvii) 100 cartons of tea 
(xviii) 3 bales of second hand clothes  
 
44.  Nasarawa Nasarawa North Communal Clash Loss of 400 lives, (i) 300 bags of cement 
LGA Destruction of houses   (ii) 50 bundles of roofing sheets 
(iii) 500 pcs of 2x3x12 planks 
(iv) 500 pcs of 2x4x12 planks 
(v) 100 bags of roofing nails 
(vi) 100 packets of zinc nails 
(vii) 150 bags of rice 
(viii) 150 bags of beans 
(ix) 150 bags of millets 
(x) 150 bags of maize 
(xi) 150 pcs of plastic buckets 
(xii) 150 pcs of plastic plates 
(xiii) 150 pcs of plastic spoons 
(xiv) 150 pcs of plastic cups 
(xv) 150 pcs of blankets 
(xvi) 150 pcs of bath towels 
(xvii) 50 cartons of bath soap  
(xviii) 5 bales of second hand clothing   
(xix) 150 pcs of mattresses   
45.  Niger Borgu LGA Fire Disaster 535 Houses were (i) 1,000 pcs of 2x3x12 planks 
279 
 
UNIVERSITY OF IBADAN LIBRARY
affected and 668 People (ii) 1,000 pcs of 2x4x12 planks 
Displaced. (iii) 400 bundles of roofing sheets 
(iv) 60 bags of roofing nails 
(v) 120 pcs of mattresses  
(vi) 600 bags of cement 
(vii) 100 bags of rice 
(viii) 100 bags of beans 
(ix) 100 kegs of v/oil 
(x) 100 bags of guinea corn 
(xi) 100 bags of maize 
(xii) 500 pcs of blankets 
(xiii) 100 bags of millets 
(xiv) 500 pcs of plastic buckets 
46.  Niger Mokwa LGA Flood and Displacement of 3,101 (i) 300 bags of rice 
erosion persons and destruction (ii) 300 bag of guinea corn 
of 487 houses (iii) 300 bag of maize flour 
(iv) 300 bag of salt 
(v) 300 kegs of palm oil 
(vi) 800 bundles of roofing sheets 
(vii) 600 bags of cement 
(viii) 1000 pieces of blankets 
(ix) 500 pieces of mosquito nets 
(xix) 2000 pieces of 2x3x12 planks 
(xx) 2000 pieces of 2x4x12 planks 
(x) 200 packets of roofing nails 200 bags of zinc nails 
(xi) 500 pieces of wax print 
(xii) 400 pieces of mattresses 
47.  Ogun Abeokuta North flood The destruction of (i) Cement: 300 bags  
and Abeokuta properties and (ii) Rice: 300 bags  
South LGAs displacement of 1,000 (iii) Blanket:500 pieces  
persons (iv) 500 pieces of nylon mat 
(v) 100 cartons of detergent 
(vi) 50 cartons of tea 
(vii) 500 pieces of bath towel 
(viii) 500 pieces of wax print 
(ix) 20 bags of 25kg of salt 
(x) 500 pieces of plastic spoon 
(xi) 500 pieces of plastic plate 
(xii) 250 pieces of bucket 
280 
 
UNIVERSITY OF IBADAN LIBRARY
(xiii) 500 pieces of plastic  cup 
(xiv) 50 cartons of bathing soap 
(xv) 50 cartons of washing soap 
(xvi) 100 bags of beans  
(xvii) 200 bags of garri 
48.  Ondo Akure South, Ose, Flood 1,095 houses were (i) Cement:600 bags  
Odigbo, Ese Odo, affected, 1,066 (ii) Roofing sheets:400 bundles  
Akoko South East, households were (iii) Zinc nails:100 packets  
Akoko South West, displaced (iv) Roofing nails:100 bags  
Indanre, Akoko (v) 2x3x12 planks:1,000 pieces  
North West and (vi) 2x4x12:1,000 pieces  
Akoko North East (vii) Rice:300 bags  
LGAs (viii) Beans:150 bags  
(ix) Garri:300 bags  
(x) Detergent:50 cartoons  
(xi) Blankets:500 pieces  
(xii) Plastic buckets:500 pieces  
(xiii) Palmoil:200 kegs  
(xiv) Tea:250 cartoons  
(xv) Wax prints: 500 pieces  
(xvi) Mats:500 pieces  
 
49.  Osun Ifelodun, Ood-Otin, Flood The destruction of (i) Roofing sheets;600 bundles  
Atakumosa East, properties and (ii) 2x3x12 planks:1000 pieces  
Iwo, Oriade, displacement of 2,583 (iii) 2x4x12 planks: 1000 pieces 
Egbedore, Ila, persons (iv) Cement; 600 bags  
Irepondu LGAs (v) Zinc nails: 100 packets  
(vi) 3” nails; 100 bags  
(vii) Parboiled rice; 600 bags  
(viii) 600 pieces of nylon mats  
(ix) Wax prints: 400 pieces  
(x) Blankets:700 pieces  
(xi) Beans: 300 bags  
(xii) Palm oil: 100 kegs 
(xiii) Garri:300 bags  
50.  Oyo Ona-Ara and flood 2000 persons displaced (xiv) Cement:300 bags  
Oluyole LGAs (xv) Rice: 400 bags  
(xvi) Garri: 200 bags                   
(xvii) Plates:1000 pieces  
281 
 
UNIVERSITY OF IBADAN LIBRARY
(xviii) Cups: 1000 pieces  
(xix) Spoons:1000 pieces 
(xx) Plastic buckets: 300 pieces  
(xxi) Wax prints:250 pieces  
(xxii) Salt: 70 bags  
(xxiii) Palm oil: 50 kegs  
(xxiv) Mattress:200 pieces  
51.  Plateau Jos, Wase Religious Crises  Loss of 400 lives, and (i) 620 bags of rice 
Destruction of (ii) 305 bags of maize 
Properties. (iii) 305 bags of guinea corn 
(iv) 1000 pcs of blankets 
(v) 2 bales of used cloths 
(vi) 10,800 pcs of plastic buckets 
(vii) 11,200 pcs of plastic buckets 
(viii) 10,350 pcs of plastic cups 
(ix) 90 cartons of omo detergent 
(x) 70 cartons of toilet soap 
(xi) 1000 pcs of bath towels 
(xii) 50 cartons of milo 
(xiii) 50 cartons of milk 
(xiv) 11,000 pcs of nylon mats 
(xv) 50 cartons of pampers 
(xvi) 50 cartons of sanitary pads 
(xvii) 10,000 pcs of plastic plates 
(xviii) 300 bags of garri 
(xix) 200 bags of beans 
52.  Plateau Jos, Dogo-Nahauwa Renewed Loss of lives, destruction (i) 150 bags of rice 
LGAs Violence on of properties and (ii) 50 bags of beans 
Religious Crises. displacement of 2,500 (iii) 100 bags of maize 
persons. (iv) 50 bags of garri 
(v) 25 bags of salt  
(vi) 2,500 pcs of blankets 
(vii) 2,500 pcs of wax prints 
(viii) 2,500 pcs of nylon mats 
(ix) 250 cartons of milo  
(x) 2,000 pcs of plastic buckets 
(xi) 5 bales of used (Children) cloths 
(xii) 50 jerry cans of palm oil 
(xiii) 50 jerry cans of v/oil 
282 
 
UNIVERSITY OF IBADAN LIBRARY
(xiv) 2,000 pcs of plastic plates 
(xv) 2,000 pcs of plastic cups 
(xvi) 2,000 pcs of plastic cups …… 
(xvii) 50 cartons of bath soap 
(xviii) 50 cartons of omo 
53.  Rivers  Rumuobia-kani, Flood and Destruction of 120 (i) 300 bags of rice 
Woji, Emeka, communal building, displacement (ii) 500 bundles of roofing sheets 
Mgbwoba dispute of 2000 persons and 15 (iii) 600 bags of cement  
communities in loss of lives (iv) 400 pieces of mattresses 
Obio/Akpor LGAs (v) 500 pieces of blankets 
(vi) 1500 pieces of 2x3x12 planks 
(vii) 1500 pieces of 2x4x12 planks 
(viii) 150 packets of zinc nails 
(ix) 150 bags of 3" nails 
(x) 1000 pieces of wax prints 
(xi) 100 kegs of vegetable oil 
(xii) 200 cartons of soap 
(xiii) 85 cartons of 3-in-1 tea 
(xv) 1000 pieces of plastic buckets 
(xvi) 1000 pieces of plastic plates 
(xvii) 1000 pieces of plastic spoons 
54.  Rivers                         Bakassi Displacement of 421 (i) 300 bags of garri 
Khana, Andoni, Returnees IDPs (ii) 300 bags of rice 
Gokana, (iii) 300 bags of beans 
Oobo/Nkoro, (iv) 50 bags of salt 
Okrika, and (v) 100 kegs of vegetable oil 
Akukutoru LGAs                                                                                       ( v  i )      2  0  0   c  a  r t o  n  s   o  f   p  a  l m     o  i l                                                                                                                   
(vii) 450 cartons of bath soap 
(viii) 500 pieces of blankets 
(ix) 100 pieces of kerosene stove 
(x) 100 pieces of bath towels 
(xi) 100 cartons of 3-in-1 tea 
(xii) 150 wax prints 
(xiii) 50 pieces of sewing machines 
(xiv) 50 pieces of grinding machines 
(xv) 50 standing driers  
(xvi) 200 bundles of stroke 9 deep fishing nets 
(xvii) 200 bundles of stroke 45 deep fishing nets 
55.  Sokoto Sokoto LGA Flood No of affected (i) 300 bags of maize 
283 
 
UNIVERSITY OF IBADAN LIBRARY
household: 6,905, No of (ii) 300 bags of guinea corn 
women: 7703, no of (iii) 300 bags of rice 
affected of children: (iv) 50 bags of salt 
31120, no of deaths 6, (v) 142 pieces of mattresses 
No of IDPs in the camp: (vi) 2,400 pieces of towels 
19, total no of victims: (vii) 500 pieces of buckets 
9763. (viii) 3,000 plastic cups 
(ix) 261 nylon mats 
(x) 3,000 plastic spoons 
(xi) 3,000 plastic plates 
(xii) 50 jerry-cans of vegetable oil 
(xiii) 50 jerry-cans of palm oil 
(xiv) 1,125 pieces of blankets 
56.  Sokoto Goronyo, Gada, Flood The incident resulted to (i) Rice:400 bags 
Robeh, Isa, Wurno, displacement of over (ii) Maize:200 bags  
Kware, and 20,000 persons; loss of (iii) Millet: 200 bags  
Wamakko LGAs lives, destruction of (iv) Palm oil: 45 jerry can s 
houses, farmlands, food (v) Vegetable oil: 45 jerry cans 
crops, other means of (vi) 3-in-1 tea:170 cartons  
livelihood and (vii) Plastic spoon:650 pieces  
infrastructure like (viii) plastic cups:650 pieces  
bridges were also (ix) plastic plate: 650 pieces  
damaged. (x) sugar:45 bags  
(xi) Soap: 130 cartons  
 
(i) Rice: 200 bags  
(ii) Maize: 100 bags  
(iii) Millet:100 bags 
(iv) Palm oil: 25 jerry can  
(v) Vegetable oil: 25 kegs 
(vi) 3-in-1 tea:80 cartons  
(vii) plastic spoons:350 pieces  
(viii) Plastic cups:350 pieces  
(ix) plastic plates:350 pieces  
(x) Sugar:25 bags  
(xi) Soap:70 cartons  
57.  Taraba  Wukari, Gassol and Religious crisis Destruction of 119 (i) 300 bags of cement 
Ardo Kola LGAs and flood houses and farmlands. (ii) 400 bundles of roofing sheets 
displacement of 80 (iii) 35 packets of zinc nails 
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UNIVERSITY OF IBADAN LIBRARY
families and lost of 10 (iv) 35 bags 0f roofing nails 
lives  (v) 1500 pcs of 2x3x12 planks 
(vi) 1500 pcs of 2x4x12 planks 
(vii) 150 bags of maize 
(viii) 200 bags of millet 
(ix) 150 bags of beans 
(x) 300 bags of rice 
(xi) 300 pieces of bath towels 
(xii) 500 pcs of wax prints 
(xiii) 500 pcs of nylon mats 
(xiv) 500 pcs of plastic buckets 
(xv) 3 bales of second hand cloths 
58.  Yobe  Bursari, Geidam, Drought  Loss of about 3,142 (i) 1500 bags of rice 
Yunsari, Yusufari, metric tons of expected (ii) 900 bags of guinea corn 
Karasuwa and harvest. Virtually all the (iii) 900 bags of millet 
Machina LGAs LGAs were affected (iv) 600 bags of maize 
(v) 600 bags of beans 
(vi) 100 kegs of vegetable oil 
(vii) 100 kegs of palm oil 
59.  Yobe  Gujba, Fika and Flood and 800 households and (i) 300 bundles of roofing sheets 
Nguru LGAs windstorm destruction of properties (ii) 300 bags of cement 
(iii) 25 packets of zinc nails 
(iv) 25 packets of roofing nails 
(v) 500 pieces of 2x3x12 planks 
(vi) 500 pieces of 2x4x12 planks 
(vii) 150 bags of maize 
(viii) 150 bags of millet 
(ix) 150 bags of beans 
(x) 200 bags of rice 
(xi) 10 bags of salt 
(xii) 150 pieces of wax prints 
(xiii) 300 pieces of nylon mats 
(xiv) 200 pieces of plastic buckets 
60.  Yobe  Yunusari and Flood  Displacement of 2,344 (i) 300 bags of cement 
Nguru LGAs persons, destruction of (ii) 300 bundles of roofing sheets 
586 houses and public (iii) 1200 pieces of 2x3x12 planks 
properties  (iv) 1200 pieces of 2x4x12 planks 
(v) 50 bags of roofing nails 
285 
 
UNIVERSITY OF IBADAN LIBRARY
(vi) 50 bags of 3”nails 
(vii) 100 bags of rice 
(viii) 50 bags of maize 
(ix) 50 bags of beans 
(x) 50 bags of guinea corn 
(xi) 50 bags of millet 
(xii) 140 bags of biski 
(xiii) 300 pieces of blankets 
(xiv) 1000 pieces of plates 
(xv) 1000 pieces of cups 
(xvi) 1000 pieces of spoon 
(xvii) 300 pieces of nylon mats 
(xviii) 500 pieces of wax print 
(xix) 50 cartons of detergents 
(xx) 100 bags of salt 
(xxi) 50 kegs of vegetable oil 
61.  Zamfara Anka and Lead poisoning  The disaster led to the (i) 150 pieces of bath towels 
Bukkuyum LGAs death of 175, children (ii) 150 pieces of nylon mats 
while 157 women and (iii) 100 bags of sugar 
100 children were (iv) 50 bags of salt 
hospitalized.  (v) 200 pieces of blankets 
(vi) 300 of plastic buckets 
(vii) 300 pieces of plastic plates 
(viii) 300 pieces of plastic spoons 
(ix) 200 pieces of mattresses 
(x) 200 pieces of wax prints 
(xi) 100 cartons of milo 
(xii) 100 cartons of milk 
(xiii) 100 cartons of soap 
(xiv) 200 pieces of mosquito nets 
(xv) 100 cartons of soap 
 
    
286 
 
UNIVERSITY OF IBADAN LIBRARY
Distribution of Relief Materials to State in 2011 
   Building Materials 
State Zinc (Bundles) Cement (Bags) Planks (Pieces) Zinc Nails Cartons Roofing Nails Cartons 
Adamawa 100 150 500 20 20 
Bauchi 6,030 18,090 132,660 4,824 1,200 
Benue 550 1,400 6,130 1,500 1,500 
Borno   760 6200 102  
Cross River 350 1,400 3,000 100 100 
Ebonyi 700 - - 150 150 
Edo 4,950 900 3,000 50 50 
Ekiti 300 300 800 50 50 
Enugu 450 600 2,000 50 50 
Imo 200 300 1,500 50 50 
Jigawa  300 600 4,000 100 100 
Kaduna 6,028 5,100 11,250 674 420 
Kano 2,400 1,600 5,730 625 625 
Katsina - 1,200 - - - 
Kogi 800 1,200 2,000 600 600 
Kwara 1,000 1,200 5,000 1,000 1,000 
Lagos   1,200    
Nasarawa       
Niger      
Ondo 600 600 - 200 200 
Osun 300 600 2,000 100 100 
Oyo 500 700 - 100 - 
Plateau 450 600 3,000 200 50 
Rivers 50   20 30 
Sokoto  200 300 4,000 100  100 
Zamfara 4000 5,600 8,000 200 3,200 
 
287 
 
UNIVERSITY OF IBADAN LIBRARY
Distribution of Building Materials on Zonal Basis in 2011 
Zones Zinc (Bundles) % Cement (Bags) % Planks % Zinc Nail (Pkts) % Roofing Nails % 
Abuja Operation 1,800 8 2,400   7 7,000   4 1,600 16 1,600 26 
North-Central 1,000 4 2,000   6 9,130   5 1,700 17 1,550 25 
North-East 6,130 26 18,240 51 133,160 76 4,844 47 1,220 20 
North-West 6,200 27 7,900 22 16,980 10 1,299 13 1,045 17 
South-East 1,350 6 900   3 3,500   2 250   2 250   4 
South-South 5,000 22 2,300   6 3,000   2 120   1 180   3 
South-West 1,700 7 2,200   6 2,800   2 450   4 350   6 
Total 23180 100 35940 100 175570 100 10263 100 6195 100 
 
Distribution of Food Stuffs to States in 2011 
States Rice Maize Flour  G/Corn Millet Sugar  Salt Garri Palm Oil Beans Veg. Oil 
(Bags) (Bags) (Bags) (Bags) ( ags) (Bags) (Bags) (Kegs) (Bags) (Kegs) 
Adamawa 50 50 50 50 10 10 - - - - 
Akwa-Ibom 100 - - - - - 200 - 100 - 
Anambra 150 - - - - 50 - 50 150 50 
Bauchi 580 485 210 110 180 150 - 375 311 415 
Bayelsa - - - - - - 100 - - - 
Benue 350 300 300 300 - - - - 300 - 
Borno 850 50 200 300 170 20   50  
Cross River 250 - - - - 150 200 100 175 150 
Delta 300 - - - - - - - - - 
Ebonyi 500 - - - - - - - 100 - 
Edo 600 - - - 100 200 400 200 400 200 
Ekiti 300 - - - - - - - - - 
288 
 
UNIVERSITY OF IBADAN LIBRARY
Enugu 300 100 - - 50 50 200 20 300 20 
Gombe 230 230 230 100 50 45 - - 165 - 
Imo 100 50 - - - - - - 50 - 
Jigawa 300 150 150 100     150  
Jigawa 300 150 150 150     150  
Kaduna 3,050 931 1,060 960 322 152 248 261 455 95 
Kano 800 700 500 300 - - - - 400 - 
Katsina 600 - 300 300 - - - 150 600 150 
Kogi 600 - - - - - - - 300 - 
Kwara 600 - - - - - - 100 300 - 
Lagos 900 - - - - - 50 175 50 95 
Nasarawa  200 150  150     150  
Niger 45 45    15  30 10 30 
Ogun 250 100 - - - - 100 50 100 50 
Ondo 600 50 - - 40  50 - 100 - 
Osun 750 100 - - - - 350 250 100 50 
Oyo 100 - - - - - - 50 50 50 
Plateau 4,250 1,100 1,550 1,650 - 75 350 50 920 311 
Rivers 850 - - - - 10 250 - - 100 
Sokoto 300 100 100      100  
Taraba 100 100 100 100 100 100 - - - - 
Yobe 50 50 50 - 50 25 - - - - 
Zamfara 7,200 3,600 600 3600 200 50  100 3600 100 
 
 
289 
 
UNIVERSITY OF IBADAN LIBRARY
 
Distribution of Food Stuff on Zonal Basis 
Zones Rice (Bags) % Maize (Bags) % G/Corn (Bags) % Millet (Bags) % Sugar (Bags) % 
Abuja Operation 1,200 6 0 0 0 0 0 0 0 0 
North-Central 6,045 23 1,595 20 1,850 39 2100 28 0 0 
North-East 930 4 480 6 410 9 350 5 270 27 
North-West 11,950 45 5,331 68 2,460 52 5160 68 522 53 
South-East 1,050 4 150 2 0 0 0 0 50 5 
South-South 2,200 8 0 0 0 0 0 0 100 10 
South-West 2,900 7 250 3 0 0 0 0 40 4 
Total  26,275 100 7,806 100 4,720 100 7,610 100 982 100 
 
Zones  Salt (Bags) % Garri (Bags) % Palm Oil % Beans (Bag) % Veg. Oil % 
Abuja Operation 0 0 0 0 100 6 600 6 0 0 
North-Central 90 11 350 14 180 11 1,980 20 341 18 
North-East 90 11 0 0 0 0 365 4 415 22 
North-West 202 24 248 10 511 32 5155 53 345 18 
South-East 100 12 200 8 70 4 500 5 70 4 
South-South 360 43 1150 47 300 19 675 7 450 24 
South-West 0 0 500 20 450 2 400 4 245 13 
Total 842 100 2,448 100 1,611 100 9,675 100 1,866 100 
 
 
 
290 
 
UNIVERSITY OF IBADAN LIBRARY
 
 
     Distribution of Children’s Requirements and beverages to States in 2011 
States Kunu Tsamiya 3-In-1 Tea & Mix Milo Pampers Children Powdered Indomie Water 
(Cartons) Tea (Cartons) (Cartons) (Pieces) Milk (Cartons) (Cartons) (Cartons) 
Adamawa 100 - - - - - - 
Akwa-Ibom - 100      
Anambra - 200      
Bauchi 1,015 2,017 100 240 150   
Enugu  50      
Gombe 150  35  75   
Kaduna 100 - - 50 - 600 525 
Kano 500       
Nasarawa  500      
Ogun  50      
Osun  100      
Oyo  20      
Plateau 1,050 900 300 50 600   
Rivers  30      
Sokoto        
Taraba 100 100      
Yobe 400  75  150   
Zamfara 1000       
 
 
 
291 
 
UNIVERSITY OF IBADAN LIBRARY
     Distribution of Beverages on Zonal Basis 
Zones Kunu % Mix-Tea/3-In-1 % Milo % Children Powder % Water % 
(Carton) Tea (Cartons)  (Cartons) Milk (Cartons)  (Cartons) 
Abuja Operation     0 0 0  0 0 0 0 0 0 
North-Central     1,050 36 900 26 300 63 600 62 0 0 
North-East     1,750 59 2,117 60 175 37 370 38 0 0 
North-West     150 5 0 0 0 0 0 0 525 100 
South- 
    0 0 200 5 0 0 0 0 0 0 
East 
South-South     0 0 130 4 0 0 0 0 0 0 
South-West     0 0 170 5 0 0 0 0 0 0 
Total 2,950 100 3517 100 475 100 970 100 525 100 
292 
 
UNIVERSITY OF IBADAN LIBRARY
    Distribution of Household Items/Clothings to States in 2011 
Guinea Detergent 
Sanitary Nylon 
Brocade Used Clothes Towels Blankets & Bath 
States Pads Mats 
& Wax Print (Bales) (Pieces) (Pieces) Soaps 
(Packets) (Pcs) 
(Pcs) (Cartons) 
Adamawa 30 5 50  50 50 - 
Akwa-
- - 300  200 - 50 
Ibom 
Anambra - - 1,000  500 1,000 150 
Bauchi 500 56 4,310 40 10,950 5,700 400 
Bayelsa 500 - - - 500 - - 
Benue 3,000 - 1,000  1,250 250 1,050 
Cross 
500 - 1,150 - 1,500 - 20 
River 
Delta - - - - 1,000 - - 
Ebonyi 800 - 800 - 300 200 - 
Edo 1,500 - 600 - 1,000 - 350 
Ekiti - - 200 - 250 250 - 
Enugu 500 - 400 - 627 627 100 
Gombe                               -                                 -                          -                - - - - 
Imo - - - - 500 500 40 
Jigawa     100   
Jigawa     100   
Kaduna 5,370 - 2,430 650 8,360 5,700 466 
Kano 1,400  - - 1,081 - 750 
Katsina 2,000 - 300 - 2,500 1,000 340 
293 
 
UNIVERSITY OF IBADAN LIBRARY
Kogi - - - - 600 - - 
Kwara     1,000   
Lagos     3,000   
Nasarawa  2 1000 200 3000   
Niger 60  60  60  30 
Ogun   500   500 100 
Ondo 1,000    500 1,000  
Osun 1,500    1,500 1,600 70 
Oyo 500 - - -- - - - 
Plateau 4,650 12 1,400 50 11,400 5,800 1,115 
Rivers 1,900 - - - 700  100 
Sokoto     100   
Taraba 500 - - - 700 700 200 
Yobe 500 3 200 - 400 400 80 
Zamfara 1000 500   200 2000 100 
 
  
294 
 
UNIVERSITY OF IBADAN LIBRARY
States Mattresses Metal Beds Buckets Plates Spoons Cups Mosquito Nets Pampers 
Adamawa 50 30 50 50 50 50   
Akwa-Ibom 100 - - - - -   
Anambra 250 - 500 1,000 1,000 1,000   
Bauchi 3,900 - - - - 1,000 2,000  
Bayelsa - - 500 - - -   
Benue 1,000  1,000 1,000 1,092    
Cross River 150 - 700 500 - - 500  
Delta 600 - - - 2,000 -   
Ebonyi - - - - - - -  
Edo 500 - 1,000 - - - -  
Ekiti - - - - - - -  
Enugu 50 - 50 - - - -  
Gombe                                  3  0  0                                 -                        -           - - - -  
Imo - - 500 200 200 - -  
Jigawa   100      
Jigawa   100      
Kaduna 5,150 500 3,050 2,700 3,130 1,830 874  
Kano 734 - 500 - - - 300  
Katsina 500 - - - - - -  
Kogi 200 - - - - - -  
Kwara 100        
Lagos       500  
Nasarawa   1000 400 400 1000  100 
Niger 80 20 30  60    
295 
 
UNIVERSITY OF IBADAN LIBRARY
Ogun         
Ondo         
Osun 200 - - - -    
Oyo 100 - 500 1,000 1,000 1,000 500  
Plateau 1,300 - 19,250 - 13450 16,250 -  
Rivers 500  1,007 200 200 - 300  
Sokoto   100      
Taraba 200 - 700 500 500 600 200  
Yobe 250 - 500 300 200 200 400  
Zamfara 800      5000  
 
Note: A cash sum of N19,000,000.00 and N900,000.00 was donated for hospital bills and accommodation in respect of displaced widows and 
children in Madalla bomb blast Niger State. Also, 60 pillows, 20 bed side lockers and 30 plastic chairs were provided as hospital materials to the 
people affected 
 
 
 
 
 
 
 
 
 
296 
 
UNIVERSITY OF IBADAN LIBRARY
Distribution of Bedding Items on Zonal Basis 
Zones Blankets % Nylon Mats % Mattresses % Metal Bed % 
Abuja  
1,600 3 0 0 0 0 0  
Operations 
North-Central 12,650 26 6,050 25 2,300 15 0  
North-East 11,700 24 6,150 25 4,700 31 30 100 
North-West 11,941 24 6,700 27 6,380 42 0  
South-East 1,927 4 2,327 9 300 2 0  
South-South 3,900 8 0 0 1,350 9 0  
South-West 5,250 11 3,350 14 300 2 0  
Total 48,968 100 24,577 100 15,330 100 30 100 
 
297 
 
UNIVERSITY OF IBADAN LIBRARY
Distribution of Building Materials to States in 2012 
Zinc Cement Planks 2x3x12 Planks 2x4x12 Zinc Nails Roofing Nails 
State 
(Bundles) (Bags) (Pcs) (Pcs) (Pkts) (Bags) 
Abia 200 300 2500 2500 100 100 
Abuja       
Adamawa 500 1400 3200 3200 400 370 
Akwa-Ibom  200 1000 1000   
Anambra  100 500 1000 1000 50 50 
Bauchi 200 300 2700 2700 100 130 
Benue 700 1300 1500 1500 135 135 
Borno  870 1180 3100 3100 200 100 
Bayelsa - - - - - - 
Cross River 2380 2000 6000 6000 400 300 
Delta 300 550 1250 1250 250 250 
Ebonyi 200 500 2000 2000 100 50 
Edo 300 600 1000 1000 100 100 
Ekiti 380 350 1000 1000 150 50 
Enugu  200 200 200 20 20 
Gombe  300 600 1500 1500 60 30 
Imo  750 1550 1800 140 140 
Jigawa  200 1400 3000 3000 60 60 
Kaduna 595 2050 7350 6450 620 353 
Kano 550 1700 2500 2500 80 100 
Katsina 100 300 1500 1500 50 150 
Kebbi 550 2000 2000 2000 1050 150 
Kogi 900 1200 2000 2000 190 190 
Kwara 300 900 1000 1000 50 50 
Lagos  500 900 2000 2000 300 300 
Nasarawa  1700 1800 2857 2500 600 750 
Niger  1150 2800 5100 5100 1200 1020 
Ogun  300 300 1000 1000 50 50 
Ondo 1000 1100 2800 2800 250 250 
Osun 100 300 1500 1500 100 100 
Oyo 200 300 1000 1000 100 100 
Plateau 1330 1500 2000 2000 620 620 
298 
 
UNIVERSITY OF IBADAN LIBRARY
Rivers 245 1100 3500 2000 60 80 
Sokoto  450 500 1500 1500 100 100 
Taraba 150 500 1300 1300 80 45 
Yobe  1200 800 2000 2000 200 120 
Zamfara 430 1800 4500 4500 200 50 
Totals       18,380 33,980 79,907 79,400 8,165 6,463 
 
 
 
Distribution of Building Items on Zonal Basis 
Zonals Zinc Cement Planks 2x3x12 Planks 2x4x12 Zinc Nails Roofing Nails 
  (Bundles) (Bags) (Pcs) (Pcs) (Pkts) (Bags) 
Abuja Operation 2300 4900 8100 8100 1440 1260 
North-Central 3730 4600 6357 6000 1355 1505 
North-East 3220 4580 12800 12800 990 675 
North-West 2875 9750 22350 21450 2160 963 
South-East 500 2250 7250 7500 410 360 
South-South 3225 4450 12750 11250 810 730 
South-West 2480 3250 9300 9300 950 850 
Total 18,330 33,780 78,907 76,400 8,115 6,343 
 
299 
 
UNIVERSITY OF IBADAN LIBRARY
Distribution of Food Stuffs to States in 2012 
Maize  Maize  Palm Veg. Yam  
Rice G/Corn Millet Beans Sugar Salt Garri 
States  Flour Oil Oil Flour Pap 
(Bags) (Bags) (Bags) (Bags) (Bags) (Bags) (Bags) 
(Bags) (Bags) (Kegs) (Kegs) (Bag) (Bag) 
Abia 590 120    314  150 340 150 150   
Abuja 330     220 30 60 130 80 15   
Adamawa 850 950 200 400 550 350  60  20 20   
Akwa-Ibom 400     450   550 150 150   
Anambra 973 300    350 100  600 300 250   
Bauchi 450 400  400 400   70      
Bayelsa 2955     1650 718 800 2535 1130 1140   
Benue 882 90  290 290 190  10 350 220 150   
Borno 726 390  210 310  120 40  40 40   
Cross River 1150     900 25 175 650 80 205   
Delta 980     770  190 1150 240 200   
Ebonyi 900 320    470 60  400 135 135   
Edo 900     600 50 50 600 150 150   
Ekiti 250 100       300 30 30   
Enugu 559  300   350 50  300 150 170   
Gombe 200 200  200 150 150  50      
Imo 680 250    450 30 30 630 150 175   
Jigawa 1150 417  383 350  30       
Kaduna 860 710  650 320  10   145 145   
Kano 800   250 200  80   20 20   
Katsina 300 300   300  200       
Kebbi 100 100  300 100 200        
Kogi 1611 864 50 620 90 570 190 150 50 50 40 50 50 
Kwara 950 160   200 391 170   180 150   
Lagos 550     100 10  150     
Nasarawa  850 410  410 550 200 220  320 20  200 200 
Niger 1490 100  350 450 280 50 70  155 105   
Ogun 100         20 20   
Ondo 550     150        
Osun 300         50 50   
300 
 
UNIVERSITY OF IBADAN LIBRARY
Oyo 500     150   150 50 50   
Plateau 3660 1020  771 1115 940 60 180 50 250 220   
Rivers 850 100    240 90 240 490 95 175   
Sokoto 300 200  200 100 100   100 110 110   
Taraba 500 500 100 200 500 100 50 20  10 10   
Yobe 560 420    200 200       
Zamfara              
TOTAL 29,756    8,421       650      5,634    5,975  10,835    2,543   2,345   9,845    4,180    4,075  250 250 
 
 
Distribution of Food Stuffs in Zonal Basis  
Maize Palm Veg Yam 
Zones Rice Maize G/Corn Millet Beans Sugar Salt Garri Pap 
Flour Oil Oil Flour 
Abuja Operation    4,231      1,074            970       690   1,291       440  275         80      450       295        50      50  
North-Central    7,465      1,430         1,181    2,665    2,790       998        980    2,905    1,400    1,360      200    200  
North-East    3,342      2,570         300       1,490    2,840       940       250        210       350       250       180      
North-West    3,510      1,727         1,783       300       300       320       100       275       275      
 
South-East   3,702         990         300          1,934       240        180    2,270       885       880      
South-South    5,006         490            210       310    2,960       285        695    3,440       755       920      
South-West    2,250         100               400         20         600       150       150      
Total 29,506 8,381 600 5,634 6,805 10,615 2,553 2,340 9,745 4,165 4,060 250 250 
301 
 
UNIVERSITY OF IBADAN LIBRARY
Distribution of Children’s Requirements and beverages to States in 2012 
Kunu 3-In-1 Tea Milo Powdered Indomie Water Tin Maggi Children 
States Pampers  
Tsamiya & Mix Tea (Cartons Milk (Ctts) (Cartons) Tomatoes  (Pkts) Wears  
Adamawa 30  100 50 100   40 40  
Akwa-Ibom  300         
Bauchi     20      
Bayelsa  600         
Benue      100    100 
Borno   110  110 113  1100 50  
Cross River  400  50       
Delta   890   100  100  50 
Edo   50   100 100 50   
Enugu      50     
Gombe 300 20 150        
Imo      150     
Jigawa   30  30      
Kaduna   10        
Kano   20  20      
Katsina     50      
Kogi   50 200 50 100 100    
Kwara       150    
Lagos  100         
Nasarawa 200     200  20   
Niger   50  50 50 50    
Plateau 50     1200  270   
Rivers   70        
Sokoto           
Taraba 50  50  80 50   70  
Yobe   200  200 800  100 50  
Zamfara           
Total 630 1,420 1,780 300 710 3,013 400 1,680 210 150 
 
302 
 
UNIVERSITY OF IBADAN LIBRARY
 
Distribution of Children’s Requirements and beverages in Zonal Basis 
Kunu 3-In-1   
Milo Pamper Powdered 
Tsamiya Tea & Indomie Water Tin Maggi Children 
States (Cartons s Milk 
(Cartons Mix Tea (Ctts) (Cartons) Tomatoes (Pkts) Wears 
) (Pieces) (Cartons) 
) (Cartons) (Cts) (Pairs) 
Abuja Operation 30 - 200 250 200 180 400 40 40 - 
North-Central 250  - - - 1500 - 290 - 100 
North-East 350 20 400 - 280 850 - 100 120 - 
North-West - - 60 - 100 - - - - - 
South-East - - - - - 200 - - - - 
South-South - 1000 - 50 - 200 100 150 - 150 
South-West - 100 - - - - - - - - 
Total 630 1120 11660 300 580 2930 500 580 160 250 
 
  
303 
 
UNIVERSITY OF IBADAN LIBRARY
Distribution of Household Items/Clothing to States in 2012 
States Guinea Wax Print Used Clothe Bath SanitaryPads Blankets Nylon Mats 
Brocade/Shadda (Pcs) (Bales) Towels (Pkts) (Pcs) (Pcs) 
Abia  600  1100  800  
Abuja  800  500  1300 800 
Adamawa  900    1700 1600 
Akwa-Ibom    1300  1000  
Anambra 800 900  2700  2500 2200 
Bauchi 200 200    1000 900 
Bayelsa  1500  2100  4500 1500 
Benue 900 1700  1900  2100 1100 
Borno 40 500  1000  820 1050 
Cross River  3800  2600 100 2200 1000 
Delta 1000 1840  2800 1000 5600  
Ebonyi 500 1600  1500  2500 1500 
Edo  300 6 2100 1000 1300 1000 
Ekiti 100   400  300 300 
Enugu 180 800  600  200 450 
Gombe                                                                 2  0  0                                        300 200 
Imo  1400  1200  1650 800 
Jigawa 270 270    2800 1500 
Kaduna 240 550  80  1600 1000 
Kano  50  200  200 100 
Katsina 100 100    700 500 
Kebbi       200 
Kogi 1000 1500 5 1500 200 3600 3400 
Kwara 1000   1200  900  
Lagos 550 500 100 2000  1400 1900 
Nasarawa 1200 1700  1340  3500 1800 
Niger 500 900 2 700 100 1560 1000 
Ogun      100  
Ondo 100 400    700 200 
Osun    500  500 500 
304 
 
UNIVERSITY OF IBADAN LIBRARY
Oyo  100    600  
Plateau 3700 3770  1400  9700 3156 
Rivers 200 990  1300  1100 200 
Sokoto  100  100  200  
Taraba  200    1200 100 
Yobe    1000  1000 1000 
TOTAL 12,580 28,170 113 33,120 2,400 61,130 30,956 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
305 
 
UNIVERSITY OF IBADAN LIBRARY
 
States  Omo Detergent Bath Soaps Mattresses Mosquito 
Buckets Plates Spoons Cups 
(Cartons) (Cartons)  Nets 
Abia 170 250 350 1400     
Abuja 180 170 210 800 1000 1000 1000 1050 
Adamawa 110 170 100 1000 1000 1000 1000 1400 
Akwa-Ibom  250 600      
Anambra 200 200 850 2000 2500 2500 2500 1100 
Bauchi 100 150  400 400 400 400 900 
Bayelsa 1400  2800 6000 500 500 500 3500 
Benue 100 180 350 1500 500 500 500 1100 
Borno  200 60 1450 1000 1200 1000 1600 
Cross River 60 130 2800 1630 300 300 300 100 
Delta 420 440 2800     3650 
Ebonyi 250 280 250 1700 3000 3000 3000 600 
Edo  100 1700 500 500 500 500 2300 
Ekiti   200 500     
Enugu 200 200 350 650 900 1100 900 450 
Gombe                                        2  0                        2  0                                      100 200 200 200 150 
Imo 175 205 150 1300 1600 1600 1400 200 
Jigawa 40 50 1400 200    1200 
Kaduna 160 60  100    270 
Kano 30 20 230     50 
Katsina 50  600 300     
Kebbi 100 80 100      
Kogi 400 500 850 2100 1000 1000 500  
Kwara 290  1350 1400 1000  1600  
Lagos 200 150 550 750 1500 1500 1500 900 
Nasarawa 220 120 600 1500 1500 1500 1562 1500 
Niger 200 100 960 950 700 500 700 500 
Ogun         
Ondo 25 60 600     450 
Osun         
306 
 
UNIVERSITY OF IBADAN LIBRARY
Oyo 200 50 200     350 
Plateau 1000 1010 1522 5800 1700 2500 3200 2510 
Rivers 140 181 400 700 300 300  1700 
Sokoto 100 20 50     100 
Taraba 50 40 200 200 200 200 200 420 
Yobe 50 100  1000 1000 1000 1000 1000 
TOTAL 6,640 5,486 23,182 35,930 22,300 22,300 23,462 29, 050 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
307 
 
UNIVERSITY OF IBADAN LIBRARY
 
Distribution of Household Items/Clothing in Zonal Basis 
Guinea Brocade Wax Print Used Clothe Bath Towels Sanitary Blankets Nylon Mats 
Zones 
/Shadda (Pcs) (Bales) (Pieces) Pads (Pkts (Pcs) (Pcs) 
Abuja Operation     2,500  3,200         7    3,400       300        6,460    4,400  
North-Central          4,900      6,980    4,840   17,700  6,456  
  
North-East            1,100     3,200         2,900          7,200  4,900  
North-West               610    1,070            380          5,500   3,300  
South-East            1,480      5,300         7,100          7,650   4,950  
South-South            1,281     7,430           6  11,100    2,100      12,020  3,250  
South-West               750     1,000       100       2,900          3,600  2,900  
Total          12,621   28,180       113   32,620    2,400      60,130  30,156  
 
Distribution of Household Items/Non Food Items in Zonal Basis 
Omo Detergent Bath Soaps Mattresses Mosquito 
Zones Buckets Plates Spoons Cups 
(Cartons) (Cartons) (Pieces) Nets 
Abuja Operation          1,050  700     3,070        4,750    2,700      1,500    2,800    1,100  
North-Central          2,620  1,130  4,922      13,300  3,700      4,500   5,262    7,510  
North-East             430    660        550        4,200  3,300      3,300   3,300    4,970  
North-West             480     230     2,380           600          1,620  
South-East             995  1,135     1,950        7,050   8,000      8,200   7,800    2,350  
South-South             620  1,301     8,360        4,280   2,100      2,300   1,800    9,350  
South-West             425    260     1,550        1,250  1,500      1,500   1,500    1,700  
Total           6,620   5,416   22,782      35,430  21,300    21,300  22,462  28,600  
 
308 
 
UNIVERSITY OF IBADAN LIBRARY
Distribution of household items to States in 2012 cont’d 
States Cooking Cooking Mobile Life Sewing Grinding Jerry Iron Tissue Stroke 45 Units Spring 
Stove Pots Toilets Jacket Machine Machine Cans Woods Papers Fishing Nets ofTents Beds 
Bayelsa 700    200 390     50  
Delta 2000 2000 22      100    
Katsina            200 
Kogi          50   
Niger    5         
Ondo        1000     
Plateau           5  
Rivers   10    150   10 2  
Total 2,700 2,000 32 5 200 390 150 1,000 100 60 57 200 
309 
 
UNIVERSITY OF IBADAN LIBRARY
310 
 
UNIVERSITY OF IBADAN LIBRARY
 
 
 
cccxi 
 
UNIVERSITY OF IBADAN LIBRARY