Modeling the Daily Number of Reported Cases of Infection from the COVID-19 Pandemic in Nigeria: A Stochastic Approach
Abstract
The focus of this paper is to present a stochastic model to capture the random behavior of the number of reported daily infections due to the Corona Virus (COVID-19) in Nigeria. The model expressed in form of a distribution function has five parameters. The model was fitted to the logarithm of the reported daily number of infection cases for the time period March 18th - June 11th, 2020. While the results obtained established the adequacy of the model in fitting and explaining the random behavior of the number of reported daily infections, it was also possible to use the model to study the situation of the number of infections exceeding certain thresholds. The procedure for the determination of these thresholds was established and a number of them were estimated for some given return periods.
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