Spatial distribution and predictors of drug‐resistant tuberculosis incidence in Mozambique: A nationwide Bayesian disease mapping study.

Introduction: Mozambique is among the highest‐burden countries for drug‐resistant tuberculosis in the world. However, the spatial distribution of drug‐resistant tuberculosis, in the country is unknown. Therefore, we aimed to analyse the spatial distribution, predictors, and hotspot districts for drug‐resistant tuberculosis incidence in Mozambique. Method: We carried out an ecological study using the district as the unit of analysis where we included all cases of drug‐resistant tuberculosis diagnosed in Mozambique from 2016 to 2020. We obtained the data from the Minister of Health and other open sources. Parameters of interest were estimated through a spatial Bayesian Poisson regression model using Markov Chain Monte Carlo simulation. Results: A total of 5092 people with drug‐resistant tuberculosis in Mozambique were diagnosed during our study period. We found heterogeneity in the spatial distribution of drug‐resistant tuberculosis incidence across the country. Higher incidence rates were mainly observed in the south and central regions, and 26 (16.9%) districts out of 154 were identified as hotspot areas. The incidence of drug‐resistant tuberculosis increased with an increase in the HIV prevalence (Relative risk [RR]: 1.53; 95% Credibility Interval [CrI]: 1.32 to 1.76), electricity coverage rate (RR: 1.59; 95% CrI: 1.19 to 2.09), and population density (RR: 1.36; 95% CrI: 1.08 to 1.69) and decreased with an increase in the proportion of people with a bank account per district (RR: 0.71; 95% Crl: 0.51 to 0.96). Conclusion: The incidence of drug‐resistant tuberculosis was not homogeneous, and it was associated with social determinants of health. Targeting interventions in hotspot districts and addressing social determinants is crucial for tuberculosis elimination in Mozambique. [ABSTRACT FROM AUTHOR]