Mapping tuberculosis prevalence in Africa using a Bayesian geospatial analysis

Worldwide, tuberculosis (TB) remains the leading cause of death from infectious diseases. Africa is the second most-affected region, accounting for a quarter of the global TB burden, but there is limited evidence whether there is subnational variation of TB prevalence across the continent. Therefore, this study aimed to estimate sub-national and local TB prevalence across Africa. We compiled geolocated data from 50 population-based surveys across 14 African countries. A total of 212 data points were identified and linked to covariates assembled from publicly available sources. Bayesian geostatistical modelling was used to predict TB prevalence across Africa, and results were aggregated to estimate number of TB cases at national and subnational levels. Here we estimate 1.28 million TB cases (95% uncertainty interval [UI] 0.14–4.87) across 14 countries, with marked spatial variations. The highest cases are estimated in Nigeria (460,247 95% UI 7954–1,783,106), and Mozambique (120,622 95%UI 20,027–321,177) while the lowest in Guinea-Bissau (1952 95%UI 154-7365) and Rwanda (2207 95% UI 1050–9225). National TB prevalence range from 0.25 to 7.32 per 1000 with significant variation at higher spatial resolution. Temperature (°C) (OR = 1.27; 95% CrI: 1.20–1.35), precipitation (mm) (OR = 1.34; 95% CrI: 1.26–1.40), and access to city (minute) (OR = 1.21; 95% CrI: 1.14–1.25) are positively associated with TB prevalence, while altitude (m) (OR = 0.83; 95% CrI: 0.78–0.87) is negatively associated. We find substantial variations in TB prevalence at national, sub-national, and local levels in Africa. These considerable spatial variations suggest the need for geographically targeted interventions to control TB in Africa. Tuberculosis (TB) is a bacterial infection that mostly affects the lungs and can lead to death if untreated. It is common in Africa and the national incidence is well-documented. We examined subnational and local TB prevalence across the continent. Our findings show significant variations in TB prevalence, not only between countries but also within regions of the same country. The subnational and local variations in TB prevalence identified in this study suggest the importance of targeted interventions, especially in resource-limited settings. These findings could be used to direct resources more efficiently towards high-risk areas. Liyew et al. predict the subnational and local-level prevalence of tuberculosis (TB) in Africa. The findings reveal significant variations in TB prevalence across different local areas.