Background: Tuberculosis (TB) is the leading cause of death from an infectious disease worldwide and in Ethiopia. Understanding the impacts of climatic conditions on the geographical distribution and treatment outcomes of TB is crucial for effective control of TB in high TB burden countries such as Ethiopia. This presentation consists of findings from two different studies that investigated the effects of socio-climatic factors on spatial destitution (paper I) and treatment outcomes (paper II) of TB in Ethiopia.

Methods: Geospatial analyses were conducted on TB and TB treatment outcomes using data reported to the zonal and national health management information system (HMIS). District level socio-economic and demographic variables were obtained from the Central Statistics Agency of Ethiopia, and climatic data were obtained from the Worldclim database. Spatial autocorrelation was explored using global and local Moran's I statistics, and the Getis-Ord statistic. Multivariate spatial analyses were performed using a Bayesian framework with a conditional autoregressive (CAR) prior structure, and with posterior parameters estimated using a Markov chain Monte Carlo (MCMC) simulation.

Results: A total of 223 244 TB patients reported from 722 districts in Ethiopia were included in the analysis. Spatial clustering of TB was observed in districts located in the Ethiopia-Sudan and Ethiopia-Eritrea border regions, where large numbers of seasonal migrants live and work. Hot-spots and clustering of poor TB treatment outcomes were detected in districts near the international borders in Afar, Gambelia, and Somali regions and cold spots were detected in Oromia and Amhara regions.  District level socio-climatic factors such as lower educational status (RR: 1.5; 95% CrI: 1.0, 2.1), a high percentage of internal migration (RR: 1.3; 95% CrI: 1.0, 1.6), high mean annual temperature (RR: 1.3; 95% CrI: 1.0, 1.7) and high rainfall (RR: 1.5; 95% CrI: 1.1, 2.0) were positively associated with spatial clustering of TB. Similarly, the proportion of the population with low wealth index (OR: 1.01; 95%CI: 1.0, 1.01), the proportion of the population with poor knowledge about TB (OR: 1.02; 95%CI: 1.01, 1.03), and higher annual mean temperature (OR: 1.15; 95% CI: 1.08, 1.21) were positively associated with spatial clustering of poor TB treatment outcomes in Ethiopia.

Conclusion: Spatial clustering of TB and poor TB treatment outcomes, fully explained by socio-climatic factors (wealth index, migration, temperature, rainfall and knowledge of TB), were detected in the border regions of Ethiopia.  Clinical and public health interventions should be targeted in hot spot areas, and cross-border initiatives including options for mobile TB treatment and follow should be strengthened in the border region of Ethiopia to reduce the burden of TB and to achieve the national End-TB Strategy targets.