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

ABSTRACT

ObjectiveTo 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. DesignA cross-sectional study. SettingCOVID-19 daily case and death data from the initial case through 29 November 2020. Participants46 countries comprising the WHO African region. Main outcome measuresWe 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. ResultsCountries 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). ConclusionsWhile 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. Summary BoxO_ST_ABSWhat is already known on this topicC_ST_ABSO_LIThe diversity in the COVID-19 trajectories across Africa. C_LIO_LIThe heterogeneity in the reporting and testing capacities among countries. C_LI What this study addsO_LIThe heterogeneities in the attack rates during the first wave of COVID-19 in Africa could have emerged due to tourism and connectivity, the variations in age distribution, and the testing facilities between nations. Although richer countries, having a higher fraction of older people and more tourism activities, documented higher attack rates, they succeeded in reducing mortalities. C_LIO_LIAfrican countries that had more stringent early COVID-19 response policies managed to delay the onset of the outbreak at the national level. Moreover, the speed at which the first 50 cases occurred was slower in nations whose neighbors had higher cumulative attack rates. C_LIO_LIGood quality data and timely reporting are essential in understanding and controlling a public health crisis. C_LI