A study of COVID-19 data from African countries

TL;DR

This paper analyzes COVID-19 data from African countries, deriving time-dependent reproduction numbers to understand the pandemic's spread considering socio-economic factors and policy measures.

Contribution

It introduces a method to calculate time-dependent reproduction numbers tailored to African countries, accounting for unique socio-economic and policy contexts.

Findings

Reproduction numbers vary across African countries.

Socio-economic factors influence COVID-19 spread.

Policy measures impact transmission dynamics.

Abstract

COVID-19 is a new pandemic disease that is affecting almost every country with a negative impact on social life and economic activities. The number of infected and deceased patients continues to increase globally. Mathematical models can help in developing better strategies to contain a pandemic. Considering multiple measures taken by African governments and challenging socio-economic factors, simple models cannot fit the data. We studied the dynamical evolution of COVID-19 in selected African countries. We derived a time-dependent reproduction number for each country studied to offer further insights into the spread of COVID-19 in Africa.