Modelling COVID-19 infection with seasonality in Zimbabwe

Meshach Ndlovu; Rodwell Moyo; Mqhelewenkosi Mpofu

doi:10.1016/j.pce.2022.103167

Modelling COVID-19 infection with seasonality in Zimbabwe

Phys Chem Earth (2002). 2022 Oct:127:103167. doi: 10.1016/j.pce.2022.103167. Epub 2022 May 25.

Authors

Meshach Ndlovu¹, Rodwell Moyo¹, Mqhelewenkosi Mpofu¹

Affiliation

¹ Gwanda State University, Zimbabwe.

Abstract

This paper presents evidence and the existence of seasonality in current existing COVID-19 datasets for three different countries namely Zimbabwe, South Africa, and Botswana. Therefore, we modified the SVIR model through factoring in the seasonality effect by incorporating moving averages and signal processing techniques to the disease transmission rate. The simulation results strongly established the existence of seasonality in COVID-19 dynamics with a correlation of 0.746 between models with seasonality effect at 0.001 significance level. Finally, the model was used to predict the magnitude and occurrence of the fourth wave.

Keywords: COVID-19; Dynamics; Environmental factors; Mathematical modelling; Seasonality effect; Zimbabwe.