Daily COVID-19 Data, Socio-Economic and Governance Indices, and Statistical Analysis Results for 54 African Countries (14 February – 12 June 2020)

The datasets described in this article capture the early epidemiological dynamics of the COVID-19 pandemic across all 54 African countries during the first 120 days of the outbreak (14 February – 12 June 2020), together with a comprehensive set of socio-economic and governance indices and a suite of statistical analysis results. The primary epidemiological data originate from the World Health Organization (WHO) Global COVID-19 Data Repository and were subsetted to African countries by the authors. The Africa subset contains 4,691 daily records across 54 countries, with variables comprising new cases, cumulative cases, new deaths, and cumulative deaths. Derived COVID-19 outcome variables comprising infection rate, infection per million persons, infection rate per million persons, recovery rate, and case fatality rate, were computed and merged with five socio-economic indices sourced from the United Nations Development Program (Human Development Index), the International Monetary Fund (Gross National Income per capita), and the World Bank (GDP per capita, physicians per 1,000 population, and percentage of the population aged above 65 years), as well as six governance dimensions from the World Bank World Governance Indicators (WGI): Government Effectiveness, Voice and Accountability, Political Stability and Absence of Violence, Regulatory Quality, Rule of Law, and Control of Corruption. Together, these 11 indices and five COVID-19 outcome variables constitute the analysis-ready dataset for all 54 countries. A fourth file presents the outputs of a seven-component analytical pipeline: Pearson and Spearman correlations with Benjamini-Hochberg false discovery rate (BH-FDR) correction across 120 unique variable pairs, ordinary least squares (OLS) regression with variance inflation factor (VIF) diagnostics, principal component analysis (PCA) with Varimax rotation, K-means cluster analysis, Global Moran's I and Local Indicators of Spatial Association (LISA), Geographically Weighted Regression (GWR), and a sensitivity analysis excluding suspected under-reporters. These datasets support research on pandemic preparedness, spatial epidemiology, health system performance, and governance–health linkages in Africa.