An in-depth statistical analysis of the COVID-19 pandemic's initial spread in the WHO African region

James, A.; Dalal, J.; Kousi, T.; Vivacqua, D.; Camara, D. C. P.; Reis, I. C. d.; Botero-Mesa, S.; Stoll, B.; Hofer, C. B.; Coelho, F. C.; Keiser, O.; Abbate, J. L.

Objective: To quantify the initial spread of COVID-19 in the WHO African region, and to investigate the possible drivers responsible for variation in the epidemic among member states. Design: A cross-sectional study. Setting: COVID-19 daily case and death data from the initial case through 29 November 2020. Participants: 46 countries comprising the WHO African region. Main outcome measures: We used five pandemic response indicators for each country: speed at which the pandemic reached the country, speed at which the first 50 cases accumulated, maximum monthly attack rate, cumulative attack rate, and crude case fatality ratio (CFR). We studied the effect of 13 predictor variables on the country-level variation in them using a principal component analysis, followed by regression. Results: Countries with higher tourism activities, GDP per capita, and proportion of older people had higher monthly (p < 0.001) and cumulative attack rates (p < 0.001) and lower CFRs (p = 0.052). Countries having more stringent early COVID-19 response policies experienced greater delay in arrival of the first case (p < 0.001). The speed at which the first 50 cases occurred was slower in countries whose neighbors had higher cumulative attack rates (p = 0.06). Conclusions: While global connectivity and tourism could facilitate the spread of airborne infectious agents, the observed differences in attack rates between African countries might also be due to differences in testing capacities or age distribution. Wealthy countries managed to minimize adverse outcomes. Further, careful and early implementation of strict government policies, such as restricting tourism, could be pivotal to controlling the COVID-19 pandemic. Evidently, good quality data and sufficient testing capacities are essential to unravel the epidemiology of an outbreak. We thus urge decision-makers to reduce these barriers to ensure rapid responses to future threats to public health and economic stability.