Socio-Economic and Demographic Factors Associated with the Spatial Distribution of COVID-19 in Africa

Abstract

Corona is a disease that affects the whole world. Countries with weak economies are specifically more vulnerable. A proper understanding of COVID-19 spreading, identifying the high-risk areas, and discovering factors influencing the spread of the disease are crucial to improving disease control. This study evaluates the geo-statistical distribution of COVID-19 to identify critical areas of Africa using spatial clustering pattern analysis. In addition, the spatial correlation between infected cases and variables such as the unemployment rate, gross domestic product (GDP), population, and vaccination rate is calculated using Geographically Weighted Regression (GWR) analysis. The hot-spot map showed a statistically significant cluster of high values in southern and northern Africa. Moreover, the outcome of the GWR analysis revealed the GDP and population had the most significant correlation with the spreading of COVID-19, with Local R2 values of (0.01–0.99) and (0–0.89), respectively.