Spatial autocorrelation and hotspot dynamics of multidrug-resistant tuberculosis in Uganda: a district-level LISA analysis

Background Spatial clustering of MDR/RR-TB may indicate focal transmission or inequities in diagnostic access, but such patterns are often obscured by analyses conducted at aggregated geographic scales. Limited evidence exists on the spatial autocorrelation of MDR/RR-TB in Uganda. This study aimed to assess spatial dependence and identify geographic clustering of MDR/RR-TB notifications. Methods We conducted a national ecological spatial analysis using MDR/RR-TB surveillance data from Uganda (2014–2023). Global and local spatial autocorrelation statistics were applied at regional and district levels to assess spatial dependence and identify clusters. Results Limited and inconsistent spatial autocorrelation was observed at the regional level. In contrast, district-level analyses demonstrated statistically significant spatial clustering in several years. Persistent high-notification clusters were identified in urban and peri-urban districts, particularly within the Kampala metropolitan area, while several districts consistently appeared as low-notification areas. Conclusions MDR/RR-TB in Uganda exhibits spatial clustering at fine geographic scales that is not apparent at broader administrative levels. District-level spatial analysis is critical for identifying priority areas for targeted surveillance and intervention.