Browsing by Author "Awosanya, E. J."

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Prevalence and correlates of influenza-a in piggery workers and pigs in two communities in Lagos, Nigeria
(2013) Awosanya, E. J.; Ogundipe, G.; Babalobi, O.; Omilabu, S.
Introduction: Worldwide, three Influenza-A virus subtypes (H1N1, H1N2 and H3N2) in swine are major public health issues. In Nigeria, the existence of these subtypes in pigs has not been well studied. This study aimed at determining the prevalence and correlates of Influenza-A viruses circulating in piggery workers and pigs in Oke-aro and Goshen communities in Lagos, Nigeria. Methods: Nasal swabs were taken from 197 consenting piggery workers and 281 randomly selected pigs to determine the prevalence of Influenza-A (H1, H3, H5) using Reverse Transcriptase Polymerase Chain Reaction test (gene M). An interviewer administered questionnaire was used to collect information on demography, Influenza-A related symptoms experienced, personal hygiene and management practices from the piggery workers. Descriptive statistics was used and chi square test performed at 5% significant level. Results: All piggery workers and pigs' nasal swabs tested negative for Influenza-A viruses, hence, association could not be tested. Mean age of piggery workers was 41 ± 13.6 years and 60% were females. Forty two percent were farm attendants, 38.0% were pig farmers and the rest butchers. Nineteen percent had history of headache; 14.0% had catarrh and cough; 4.0% had sore-throat; 5.0% had diarrhea; while 48.0% had muscle pain at the time of data collection. The mean body temperature for the pig workers was 36.5 ± 0.5 °C. A significant difference (p<0.05) existed among piggery workers who had muscle pains. Conclusion: Piggery workers and pigs in study area were free of Influenza-A (H1, H3, H5) viruses. The current practices of the piggery workers should be encouraged.
Situation assessment and natural dynamics of COVID-19 pandemic in Nigeria, 31 May 2020
(Elsevier B.V., 2021) Adebowale, S.; Fagbamigbe, A. F.; Akinyemi, J. O.; Obisesan, K. O.; Awosanya, E. J.; Afolabi, R. F.; Alarape, S. A.; Obabiyi, S. O.
Background: The coronavirus disease (COVID-19) remains a global public health issue due to its high transmission and case fatality rate. There is apprehension on how to curb the spread and mitigate the socio-economic impacts of the pandemic, but timely and reliable daily confirmed cases’ estimates are pertinent to the pandemic’s containment. This study therefore conducted a situation assessment and applied simple predictive models to explore COVID-19 progression in Nigeria as at 31 May 2020. Methods: Data used for this study were extracted from the websites of the European Centre for Disease Control (World Bank data) and Nigeria Centre for Disease Control. Besides descriptive statistics, four predictive models were fitted to investigate the pandemic natural dynamics. Results: The case fatality rate of COVID-19 was 2.8%. A higher number of confirmed cases of COVID-19 was reported daily after the relaxation of lockdown than before and during lockdown. Of the 36 states in Nigeria, including the Federal Capital Territory, 35 have been affected with COVID-19. Most active cases were in Lagos (n = 4064; 59.2%), followed by Kano (n = 669; 9.2%). The percentage of COVID-19 recovery in Nigeria (29.5%) was lower compared to South Africa (50.3%), but higher compared to Kenya (24.1%). The cubic polynomial model had the best fit. The projected value for COVID-19 cumulative cases for 30 June 2020 in Nigeria was 27,993 (95% C.I: 27,001–28,986). Conclusion: The daily confirmed cases of COVID-19 are increasing in Nigeria. Increasing testing capacity for the disease may further reveal more confirmed cases. As observed in this study, the cubic polynomial model currently offers a better prediction of the future COVID-19 cases in Nigeria.
The spread of COVID-19 outbreak in the first 120 days: a comparison between Nigeria and seven other countries
(BioMed Central, 2021) Adebowale, A. S.; Fagbamigbe, A. F.; Akinyemi, J. O.; Obisesan, O. K.; Awosanya, E. J.; Afolabi, R. F.; Alarape, S. A.; Obabiyi, S. O.
Background: COVID-19 is an emerging public health emergency of international concern. The trajectory of the global spread is worrisome, particularly in heavily populated countries such as Nigeria. The study objective was to assess and compare the pattern of COVID-19 spread in Nigeria and seven other countries during the first 120 days of the outbreak. Methods: Data was extracted from the World Bank’s website. A descriptive analysis was conducted as well as modelling of COVID-19 spread from day one through day 120 in Nigeria and seven other countries. Model fitting was conducted using linear, quadratic, cubic and exponential regression methods (α=0.05). Results: The COVID-19 spread pattern in Nigeria was similar to the patterns in Egypt, Ghana and Cameroun. The daily death distribution in Nigeria was similar to those of six out of the seven countries considered. There was an increasing trend in the daily COVID-19 confirmed cases in Nigeria. During the lockdown, the growth rate in Nigeria was 5.85 (R2 =0.728, p< 0.001); however, it was 8.42 (R2 =0.625, p< 0.001) after the lockdown was relaxed. The cubic polynomial model (CPM) provided the best fit for predicting COVID-19 cumulative cases across all the countries investigated and there was a clear deviation from the exponential growth model. Using the CPM, the predicted number of cases in Nigeria at 3-month (30 September 2020) was 155,467 (95% CI:151,111-159,824, p< 0.001), all things being equal. Conclusions: Improvement in COVID-19 control measures and strict compliance with the COVID-19 recommended protocols are essential. A contingency plan is needed to provide care for the active cases in case the predicted target is attained.