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1Deborah O. Daniel1), Shola A. Akinboboye2)
)Department of Mathematics and Computer Science – Southwestern University (Nigeria)
2)Department of Biological Sciences – Southwestern University (Nigeria)
Abstract. The emergence of the Coronavirus Disease 2019 (COVID-19) pandemic, as reported by the World Health Organisation (WHO), originating from Wuhan, China in late 2019, poses a significant and formidable challenge to worldwide public health. As a result, more than 20 nations experienced the impact of this lethal illness. This research introduces a mathematical model, namely SEIQRV, which incorporates the SEIR model to analyse the ongoing COVID-19 epidemic in Nigeria. The model incorporates nonlinear forces of infection. The present model takes into account the many modes of transmission involved in the dynamics of infection, as well as the influence of the environmental reservoir on the dissemination of this particular illness to human populations. The establishment of the area in which the model is epidemiologically viable has been confirmed. A comprehensive numerical simulation of the model was performed using the data given by the Nigeria Centre for Disease Control (NCDC). The findings from our analysis and simulation suggest that administering an inadequate dose of vaccination will result in an elevated number of persons who are exposed to and infected by the virus. Additionally, this incomplete dosage is also likely to contribute to an increase in the concentration of the virus within the environmental reservoir. Hence, the need for effective vaccination with a zero-wane-off vaccine and compliance with vaccination dose, which can be achieved through educational campaign and public awareness of the need to be vaccinated, and not to be vaccinated alone but to complete the dose as incomplete dosage is dangerous to the community and the country at large. This will help a great deal in eradicating the spread of the COVID-19.
Keywords: COVID-19; Vaccination; Infection dynamics; Mathematical model; SEIQRV model; Transmission; Basic reproduction number