article · BMC Public Health
Multidrug-resistant and rifampicin-resistant tuberculosis continues to pose a major public health challenge in Uganda. Using routine national surveillance data from the District Health Information System 2 covering 2014 to 2023, notification rates across administrative districts were analysed to understand geographic clustering. Applying spatial statistical methods, including Local Moran's I and Empirical Bayes smoothing, the study identified significant patterns of disease burden across districts over time. Persistent hotspot clusters with high notification rates were consistently identified in urban and peri-urban locations, particularly across the Kampala metropolitan area including Kampala, Wakiso, and neighbouring districts. In contrast, several districts consistently formed low-notification clusters, alongside occasional spatial outliers showing localised variation. These changing spatial patterns over the ten-year period indicate that incorporating routine geographic analysis into national tuberculosis programmes could enhance surveillance and direct targeted public health resources to high-burden locations.
Tuberculosis strains resistant to standard medications are difficult and expensive to manage. Pinpointing exactly where drug-resistant cases concentrate helps health authorities move beyond uniform national policies. By revealing persistent infection hotspots in urban centres such as Kampala, this spatial approach allows public health agencies to direct diagnostic equipment, specialist medical care, and containment programmes precisely where disease transmission is most concentrated.
This work demonstrates an analytical approach applied directly to routine national health information system data. The primary beneficiaries are national public health programmes, international funders, and health informatics providers developing spatial analytics modules for platforms such as DHIS2. Having been applied and tested on a decade of operational data, the approach is ready for integration into routine surveillance software to support geographic resource allocation and intervention targeting.
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Multidrug-resistant and rifampicin-resistant tuberculosis (MDR/RR-TB) remains a major public health challenge in Uganda. Although geographic heterogeneity in MDR/RR-TB burden has been reported, little is known about the spatial dependence and clustering of MDR/RR-TB at district level. This study assessed spatial clustering dynamics of multidrug-resistant/rifampicin-resistant tuberculosis in Uganda between 2014 and 2023. We conducted a national ecological study using routinely collected MDR/RR-TB surveillance data obtained from Uganda’s District Health Information System 2 (DHIS2). Annual district-level MDR/RR-TB notification rates were calculated and spatially linked to administrative boundary data. Empirical Bayes smoothing was applied to stabilize rates. Local Moran’s I (LISA) was used to identify statistically significant hotspots, cold spots, and spatial outliers of MDR/RR-TB notifications. Statistical significance was assessed using 9,999 Monte Carlo permutations, with districts exhibiting p-values < 0.05 considered statistically significant. District-level analyses demonstrated statistically significant spatial clustering of MDR/RR-TB notifications during multiple years of the study period. Persistent High–High clusters were observed within and around urban and peri-urban districts, particularly the Kampala metropolitan area, including Kampala, Wakiso, and neighboring districts. Several districts consistently appeared as Low–Low clusters during the study period. Spatial outliers were also observed, suggesting localized heterogeneity in notification patterns. Temporal variation in clustering indicated evolving spatial dynamics over the ten-year period. MDR/RR-TB notifications in Uganda exhibit significant district-level spatial clustering. Persistent hotspots identified in Kampala, Wakiso, and Mukono districts highlight areas that may benefit from intensified surveillance, diagnostic strengthening, and targeted interventions. Routine incorporation of district-level spatial analysis into national tuberculosis surveillance systems could improve prioritization of resources and support more geographically targeted MDR/RR-TB control strategies.
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DOI: 10.1186/s12889-026-29029-x
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