Please use this identifier to cite or link to this item: http://localhost:8080/xmlui/handle/123456789/1825
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dc.contributor.authorAZUABA, Emmanuel-
dc.contributor.authorBIMBA, John Samson-
dc.contributor.authorESEIGBE, Edwin Ehi-
dc.contributor.authorTAMBER, Jighjigh Abraham-
dc.contributor.authorMUSA, Yusuf-
dc.contributor.authorAKUDE, Christian-
dc.contributor.authorISAH, Omeiza Haroun-
dc.contributor.authorONIORE, Jonathan Ojarikre-
dc.date.accessioned2024-06-11T13:15:40Z-
dc.date.available2024-06-11T13:15:40Z-
dc.date.issued2021-07-28-
dc.identifier.citationAzuaba 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/10.23937/2469-5831/1510039en_US
dc.identifier.issn2469-5831-
dc.identifier.urihttp://localhost:8080/xmlui/handle/123456789/1825-
dc.descriptionBiomathematicsen_US
dc.description.abstractCOVID-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.sponsorshipBingham University Karu, Nasarawa State, Nigeriaen_US
dc.publisherInternational Journal of Clinical Biostatistics and Biometricsen_US
dc.relation.ispartofseriesdoi. org/10.23937/2469-5831/1510039;-
dc.subjectCOVID-19en_US
dc.subjectCoronavirusen_US
dc.subjectPandemicen_US
dc.subjectBingham University (BHU)en_US
dc.subjectRisk Assessmenten_US
dc.subjectStatistics Modelsen_US
dc.titleModeling the Risk Assessment of COVID-19 Pandemic in Bingham University of Nigeriaen_US
dc.typeArticleen_US
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