Assessing Sub-Regional-Specific Strengths of Healthcare Systems Associated with COVID-19 Prevalence, Deaths and Recoveries in Africa

Background: The coronavirus 2019 (COVID-19) has overwhelmed the health systems of several countries, particularly those within the African region. Notwithstanding, the relationship between health systems and the magnitude of COVID-19 in African countries have not received research attention. In this study, we investigated the relationship between the pervasiveness of the pandemic across African countries and their Global Health Security Index (GHSI) scores. Methods: The study included 54 countries in 5 regions viz Western (16); Eastern (18); Middle (8); Northern (7); and Southern (5) of Africa. The outcome variables in this study were the total Confirmed COVID-19 Cases (Confirmed Positive); the total number of recoveries (Recovered); and the total number of deaths (Deaths). The data were analyzed using Stata 14 MP (StataCorp, College Station, TX, USA) software and Microsoft Excel 2016 and ArcGIS 10.6. Spearman’s rank-order (Spearman’s rho) correlation was first used to determine the monotonic relationship between each of the predictor variables and the outcome variables. The predictor variables that showed a monotonic relationship with the outcome were used to predict respective outcome variables using multiple regression. The statistical analysis was conducted at a significance level of 0.05. Results: Significant strong correlations existed between overall GHSI, population, the ability of detection and reporting, prevention and control, rapid response, and sufficient and robust health system and commitments. The R-squared value obtained for the model was 0.9967 (P<0.001) signifying that about 99.7 % of the variance in the COVID-19 recovered cases, is accounted for by the predictor variables in the regression model. The predictor variables, therefore, had high predictive power. Using the beta coefficients of the generated model, the order of increasing prediction of COVID-19 recovered cases include a rapid response (0.8%), overall risk environment (1.1%), sufficient and robust HS (1.3%), prevention (1.9%), overall GHSI (2.9%), detection and reporting (3.3%) and confirmed positive cases (96.3%). Interpretation: Findings suggest that several determinants (e.g., population density, capacity to detect, prevent and control) affect the COVID-19 disease prevalence, deaths and recoveries within countries, and between sub-regions in Africa. The GHS index serves as a useful framework that can positively impact the development of appropriate interventions that offer stronger guarantees for health security concerning the current pandemic and perhaps future infectious outbreaks. The pattern of the virus on the continent requires improvements in health capacity building and collaboration between countries for optimal improvement in infectious disease management. Funding Statement: This study did not benefit from any funding. Declaration of Interests: All authors declare no competing interest.