Browsing by Author "Taiwo, O."

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Determining the vulnerability of states in Nigeria to COVID-19
(2020) Addie, O.; Taiwo, O.; Seun-Addie, K.
The impact of the coronavirus disease 2019 (COVID-19) pandemic has been felt globally. However, against the backdrop of the uncertainties surrounding the pandemic, and the pronouncement of the World Health Organization that the virus may never go away, it has become pertinent for nations to identify and protect the most vulnerable of their citizens. This study determined the states with the highest vulnerability to the pandemic in Nigeria. The 2006 population data for each state of the federation was obtained from the National Population Commission (NPC) Nigeria, and was projected to the year 2020. Data on: Nigerians aged 60 years and older, the percentage population in the lowest and second wealth quantiles, percentage population without fixed handwashing and moderate handwashing facilities, and percentage population of male and female without exposure to mass media, were obtained from the 2018 Nigeria Demographic and Health Survey report. Prevalence rates of High Blood Pressure, Diabetes Mellitus, Cardiovascular Disease, and Asthma were extracted from literature. These were used to estimate a vulnerability score for each state of the federation and the Federal Capital Territory. Kebbi had the highest score (39.82), followed by Zamfara (39.27) and Sokoto (39.24), respectively. Osun (11.45), Abia (12.53), and Lagos (15.47), have the least scores, respectively. The most vulnerable geo-political zone was the Northwest, while the least vulnerable was the Southwest. Regression analysis was carried out to model the data. Appropriate steps should be taken to reduce likely mortalities due to high vulnerability to COVID-19 in the identified States.
Inland habitat environmental sensitivity index mapping and modeling using geographic information systems and remote sensing technology
(2007) Taiwo, O.; Areola, O.
This study applies the Inland ESI mapping model developed by ERML and ESRI for the Niger Delta to the southeastern coastal region of Nigeria. Traditionally ESI mapping had been applied to shoreline areas and the maps typically contain three types of information: shoreline classification in terms of sensitivity to oiling, human-use resources, and biological resources. The ESI shoreline classification scheme is a numeric characterization of the sensitivity of coastal environments and wildlife to spilled oil. ESI was developed to reduce the environmental consequences of a spill and help prioritize the placement and allocation of resources during cleanup efforts. An improvement to the traditional ESI atlas has further been added through the development of ESI for inland/interior areas. This is particularly significant in the Nigeria context where many oil and gas facilities are located in the inland/interior habitats. This study shows that the model developed for the Niger delta is equally applicable to southeast coastal environment. The modeling is done using satellite imagery followed by rigorous field data collection and modeling within Arcview GIS environment. The GIS approach is quite ideal for ESI modeling because of its capability to sequentially overlay different data layers for various kinds of spatial statistical analysis and spatial modeling. The most critical element is the construction of the database: the relational database structure adopted greatly facilitates data search and analytical operations.
Sexually Transmitted Infections (STh) in Lagos State
(NISER, 2002) Olokesusi, F; Olapegba, P.O.; Taiwo, O.