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Modeling the Risk Assessment of COVID-19 Pandemic in Bingham University of Nigeria

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dc.contributor.author AZUABA, Emmanuel
dc.contributor.author BIMBA, John Samson
dc.contributor.author ESEIGBE, Edwin Ehi
dc.contributor.author TAMBER, Jighjigh Abraham
dc.contributor.author MUSA, Yusuf
dc.contributor.author AKUDE, Christian
dc.contributor.author ISAH, Omeiza Haroun
dc.contributor.author ONIORE, Jonathan Ojarikre
dc.date.accessioned 2024-06-11T13:15:40Z
dc.date.available 2024-06-11T13:15:40Z
dc.date.issued 2021-07-28
dc.identifier.citation Azuaba E, Samson BJ, Eseigbe EE, Abraham TJ, Musa Y, et al. (2021) Modeling the Risk Assessment of COVID-19 Pandemic in Bingham University of Nigeria. Int J Clin Biostat Biom 7:039. doi. org/10.23937/2469-5831/1510039 en_US
dc.identifier.issn 2469-5831
dc.identifier.uri http://localhost:8080/xmlui/handle/123456789/1825
dc.description Biomathematics en_US
dc.description.abstract COVID-19 virus has spread everywhere in Africa and to the 36 states of Nigeria, including the Federal Capital Territory (FCT), Abuja. The outbreak of COVID-19 in Lagos, since February 27, 2020 has generated 158,506 confirmed cases, including 1,969 deaths, as of 8 March 2021. In most cases, community transmission is the prime factor in which the viruses are fast spreading. Fortunately, there has never been a reported incidence of COVID-19 infection on any of the Nigerian university campuses. We assess the risk of sustained transmission at the Bingham University of Nigeria whenever the Coronavirus arrives on our university campus. Risk assessment is achieved through data describing the interaction amongst human-to-human and used facilities on the campus. The data analysis involves a fitted combination of 11 statistical models including inter alia logistic model presented by equation (12). Parameter estimation shows the probability of incidence rates and percentage for coefficient of determination at each level of individual interactions. The cubic regression model of Zankli visitors, Zankli Staff and the inverse regression model of Security Staff yield the highest coefficient of determination with the percentages of 82%, 79% and 74% respectively. This emphasizes the probability that an imported case through the Zankli visitors, Zankli Staff and Security Staff may cause COVID-19 outbreak on the University campus if the Coronavirus protocols are not properly maintained. Under the assumptions that the imported case is a threshold of an index number in the University community, and that the Coronavirus spread through human-to-human and facilities interaction. However, we found that strict compliance to Coronavirus prevention guidelines, which includes regular washing of hands with soap and water, cleaning of hands with alcohol-based hand rub, maintaining of at least 1 metre distance when coughing or sneezing, practicing of physical distancing by avoiding unnecessary travel, staying away from large groups of people, refrain from smoking and other activities that weaken the lungs, staying home whenever you feel unwell and avoid frequent touching of your face are tips for non-pharmaceutical preventive measures. en_US
dc.description.sponsorship Bingham University Karu, Nasarawa State, Nigeria en_US
dc.publisher International Journal of Clinical Biostatistics and Biometrics en_US
dc.relation.ispartofseries doi. org/10.23937/2469-5831/1510039;
dc.subject COVID-19 en_US
dc.subject Coronavirus en_US
dc.subject Pandemic en_US
dc.subject Bingham University (BHU) en_US
dc.subject Risk Assessment en_US
dc.subject Statistics Models en_US
dc.title Modeling the Risk Assessment of COVID-19 Pandemic in Bingham University of Nigeria en_US
dc.type Article en_US


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