The Determinants of the Low COVID-19 Transmission and Mortality Rates in Africa: A Cross-Country Analysis

Abstract

Background: More than 1 year after the beginning of the international spread of coronavirus 2019 (COVID-19), the reasons explaining its apparently lower reported burden in Africa are still to be fully elucidated. Few studies previously investigated the potential reasons explaining this epidemiological observation using data at the level of a few African countries. However, an updated analysis considering the various epidemiological waves and variables across an array of categories, with a focus on African countries might help to better understand the COVID-19 pandemic on the continent. Thus, we investigated the potential reasons for the persistently lower transmission and mortality rates of COVID-19 in Africa. Methods: Data were collected from publicly available and well-known online sources. The cumulative numbers of COVID-19 cases and deaths per 1 million population reported by the African countries up to February 2021 were used to estimate the transmission and mortality rates of COVID-19, respectively. The covariates were collected across several data sources: clinical/diseases data, health system performance, demographic parameters, economic indicators, climatic, pollution, and radiation variables, and use of social media. The collinearities were corrected using variance inflation factor (VIF) and selected variables were fitted to a multiple regression model using the R statistical package. Results: Our model (adjusted R-squared: 0.7) found that the number of COVID-19 tests per 1 million population, GINI index, global health security (GHS) index, and mean body mass index (BMI) were significantly associated (P < 0.05) with COVID-19 cases per 1 million population. No association was found between the median life expectancy, the proportion of the rural population, and Bacillus Calmette-Guérin (BCG) coverage rate. On the other hand, diabetes prevalence, number of nurses, and GHS index were found to be significantly associated with COVID-19 deaths per 1 million population (adjusted R-squared of 0.5). Moreover, the median life expectancy and lower respiratory infections rate showed a trend towards significance. No association was found with the BCG coverage or communicable disease burden. Conclusions: Low health system capacity, together with some clinical and socio-economic factors were the predictors of the reported burden of COVID-19 in Africa. Our results emphasize the need for Africa to strengthen its overall health system capacity to efficiently detect and respond to public health crises.

Keywords: Africa; COVID-19; cross-country analysis; mortality; transmission.

Figure 1

Health system, socio-economic, and clinical factors' profile of eight African countries with a wide range of COVID-19 cases per 1 million populations. Standardized values of variables significantly associated with COVID-19 cases per 1 million populations (test per millions, GINI, global health security [GHS], and body mass index [BMI]) are plotted for eight countries having the lowest (upper-left) to highest (lower-right) COVID-19 cases per million. CPM, Cases per 1 million population.

Figure 2

Health system and clinical factors' profile of eight African countries with a wide range of COVID-19 deaths per 1 million populations. Standardized values of variables significantly associated with COVID-19 deaths per 1 million populations (GHS index and diabetes) are plotted for eight countries having the lowest (upper-left) to highest (lower-right) COVID-19 DPM. DPM, Deaths per one million population.