Abstract
The first case of the novel coronavirus (COVID–19) in sub–Saharan Africa was confirmed by Nigeria and the figure has since then been on the rise. Current global efforts are geared towards getting effective vaccine for the cure of the disease. The hope of accessing the relieve offered by the arrival of such vaccine will obviously take significant amount of time. In the face of the resurgence of the disease, the need to slow the spread and flatten the curves is currently a priority of both governmental and non–governmental organisations in Nigeria. If the dynamics of the disease can be determined, then it becomes easier to strategize and make suitable preventive policies that will slow the spread and ultimately flatten the curves. Here, the goal is to develop a compartmental–based model for analysing the dynamics of the pandemic in Nigeria. Considering the control policies currently in place - social distancing, mask usage, personal hygiene and quarantine, and using data provided by Nigeria Centre for Disease Control (NCDC), World Health Organization (WHO) and Wolfram Data Repository on COVID–19, the proposed model is fitted to the available data using the Quasi-Newton algorithm. The infection rate, average latent time, average infective time and average mortality rate are estimated. Also, the overall effectiveness of the current control policies is measured. Predictions on the turning points and possible vanishing time of the virus in Nigeria are made. Recommendations on how to manage the resurgence of the disease in Nigeria are also suggested.
Highlights
Standard epidemiological models provide comprehensive pathway into the understanding of the dynamics of an epidemic outbreak [1]
Considering the control policies currently in place - social distancing, mask usage, personal hygiene and quarantine, and using data provided by Nigeria Centre for Disease Control (NCDC), World Health Organization (WHO) and Wolfram Data Repository on COVID–19, the proposed model is fitted to the available data using the Quasi-Newton algorithm
To analyse the dynamics of the COVID–19 pandemics in Nigeria, we propose a compartmental model consisting of five states - Susceptible (S), Exposed (E), Infective (I), Recovered (R) and Deceased (D)
Summary
Standard epidemiological models provide comprehensive pathway into the understanding of the dynamics of an epidemic outbreak [1]. The meteoric rise in the rate of spread of CoronaVirus in Nigeria has raised some social and health measures such as social distancing, lockdown, border closure, total stoppage of air-flights and banning of social gatherings among others [4]. These measures aim at reducing the contact paramter(s) [5, 6]. In the efforts to estimate some parameters that can be used to project the severity of the outbreak, its duration, and the mortality rate, several epidemiological models [20, 21, 22, 23, 14] have been proposed. Recommendations on how to manage the resurgence of a second wave of the disease in Nigeria are suggested
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
