The impact of socio-economic indicators on COVID-19: an empirical multivariate analysis of sub-Saharan African countries

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Abstract
The COVID-19 pandemic has triggered an unprecedented social and economic crisis. This study aims at investigating the impact of socio-economic indicators on the levels of COVID-19 (confirmed and death cases) in sub-Saharan Africa. The investigation makes use of the readily accessible public data: we obtain COVID-19 data from Johns Hopkins and socio-economic indicators from the World Bank. The socio-economic indicators (independent variables) used in the multilinear regression were GDP per capita, gross national income per capita, life expectancy, population density (people per sq. km of land area), the population aged 65 and above, current health expenditure per capita and total population. The dependent variables used were the COVID-19 confirmed and death cases. Amongst the seven socio-economic indicators, only 4 showed a statistically significant impact on COVID-19 cases: population density, gross national income per capita, population aged 65 and above and total population. The obtained R2 of 69% and 63% indicated that the socio-economic indicators captured and explained the variation of COVID-19 confirmed cases and COVID-19 death cases, respectively. The startling results obtained in this study were the negative but statistically significant relationship between COVID-19 deaths and population density and the positive and statistically significant relationship between gross national income per capita and COVID-19 cases (both confirmed and deaths). Both these results are at odds with literature investigating these indicators in Europe, China, India and the UK.

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