Factors associated with COVID-19 infections and mortality in Africa: A cross-sectional study using publicly available data
Data files
Oct 21, 2020 version files 15.86 KB
Abstract
Introduction
The current COVID-19 pandemic is a global threat. This elicits questions on the level of preparedness and capacity of health systems to respond to emergencies. Relative to other parts of the world, Africa has poorly developed health systems with limited capacity to respond to health crises. Africa is particularly disadvantaged.
Methods
This cross-sectional study uses publicly available core health data for 53 African countries, to determine risk factors for cumulative COVID-19 deaths and cases per million in all countries in the continent. Descriptive statistics were determined for the indicators and a negative binomial regression was used for modelling the risk factors.
Results
In Sub-Saharan Africa, an increase in the number of nursing and midwifery personnel decreased the risk of COVID-19 deaths (p=0.0178) while a unit increase in UHC index of service coverage and prevalence of insufficient physical activity among adults increased the risk of COVID-19 deaths (p=0.0432 and p=0.0127). An increase in the proportion of infants initiating breastfeeding reduced the number of cases per million (p<0.0001) while an increase in higher healthy life expectancy at birth increased the number of cases per million (p=0.0340).
Conclusion
Despite its limited resources, Africa’s preparedness and response to the COVID-19 pandemic can be improved by identifying and addressing specific gaps in the funding of health services delivery. These gaps impact negatively on service delivery but appear to have received limited funding and policy priority.
Methods
Data for selected indicators were extracted from the 2018 Global Reference List of 100 Core Health Indicators. The 12 thematic areas are Mortality by Age and Sex, Mortality by Cause, Morbidity, Nutrition, Environmental Risk Factors, Non-Communicable Diseases, Immunization, Essential health services, Utilization and access, Health workforce, Health Information and Health financing.
Data were extracted in .xls format for each variable and imported into STATA 15.0 software (StataCorp LLC College Station, TX). For each variable, the most recent data for all countries included in the study was retained with the corresponding year and country name and saved in .dta format. The different variables were merged using the country name as the unique identifier to obtain the final data set used for the analysis. The countries were further categorized into their assigned WHO region and World Bank income group.
Usage notes
The data is freely available and COVID-19 cases and deaths are changing by the day.