Agunloye, Emmanuel; Usman, Mohammed A; (2020) Predictive Modelling of COVID-19 Pandemic Evolution in Nigeria. In: Proceedings of the IORMS 2020 International Virtual Conference. (pp. pp. 1-17). IORMS: Lagos, Nigeria.

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Abstract

COVID-19 is a pandemic that has defined human life, shutting down economic activities. Various measures have been implemented to curb its spread. However, in many places, confirmed cases have continued to increase. Many believe that unless its vaccine is discovered, the pandemic has come to stay. This article aims to develop a model for the evolution of the total confirmed cases, which in the early stage increase exponentially and in the later stage flatten out. Following the balance equation modelling and employing assumptions similar to the typical pandemic modelling, an exponential model was developed. In order to describe the whole trajectory of the pandemic, following the general trend of COVID-19 data, the exponential model was modified with an inverse exponential expression, comparable to the Arrhenius Equation in chemical reaction engineering. After parameter estimation, the resulting model was validated using data from Italy and Nigeria. The model predictions compare reasonably well with the data. The model was then employed to predict the future of COVID-19 in Nigeria. The final equilibrium total confirmed cases would be 81,292 and the time for the country to record very low new daily cases would be in March 2021.

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