Exploring national COVID-19 variability across sub-Saharan Africa

Abstract

Background In early March 2020, coronavirus disease (COVID-19), an infectious disease caused by a novel coronavirus, was declared a pandemic by the World Health Organization. Since its emergence and global spread, the pandemic has been one of the greatest global crises in modern human history. Notably, in Sub-Saharan Africa (SSA), COVID-19-related burden and outcomes have been generally lower than many other parts of the world and substantially better than were initially feared. At the same time, there has been great heterogeneity in COVID-19 burden and outcomes between countries in the region, with some reporting particularly high incidence and death figures compared to others. What accounts for the significant cross-country variability apparent in SSA and why have some countries performed better than others? The present study investigates country-specific factors that may help to explain differences in COVID-19 outcomes across 48 countries in SSA. Methods A novel cross-sectional dataset, comprising a wide array of socio-demographic, political, economic, and health-related variables, is constructed through gathering data from publicly available sources. Descriptive statistics, correlation analyses, and multiple regression analyses are performed to reveal important country-level factors associated with COVID-19 deaths in SSA. Results Findings from statistical analyses show that in SSA COVID-19 deaths per million is positively associated with income inequality and median age, and negatively associated with population density. In contrast, a number of other variables, including gross national income (GNI) per capita, global connectivity, diphtheria, tetanus and pertussis (DTP) immunization coverage, the proportion of seats in parliament held by women, and political system or regime type, are not statistically significant. Conclusions Although findings from recent studies conducted in various settings around the world indicate that a range of socio-economic, demographic, political, and health-related factors may be linked with COVID-19 burden, the present investigation finds that COVID-19 deaths in SSA are associated with population density, median age, and income inequality.