High-resolution ecological niche maps identify population-density hot-spots for Ebola disease spill-over in Uganda.

Background Uganda experiences recurrent Ebola disease (EBOD) outbreaks, but the only available risk maps pool virus species and resolve five-kilometre grids insufficient for district-level preparedness. Therefore, this study aimed to generate one-kilometre, species-resolved MaxEnt risk surfaces for Uganda (2000–2024) and quantify the population living in predicted spill-over hotspots. Methods We compiled 71 laboratory-confirmed spill-over localities for Sudan, Bundibugyo and imported Zaire ebolaviruses and paired them with eleven minimally collinear environmental and anthropogenic predictors. Species-specific MaxEnt models were tuned with ENMeval (feature classes = L, Q, H; β = 0.5-3.0) and evaluated by four-fold spatial block cross-validation. A 10% training-presence threshold converted continuous suitability to binary maps; the union surface was stratified into four risk tiers. WorldPop 2023 provided population counts. Results Models showed excellent discrimination: the pooled model achieved a spatially validated AUC of 0.927, while species-specific AUCs ranged from 0.961 to 0.999. Human population density dominated permutation importance (median 77%), followed by precipitation seasonality (7%) and bat-roost probability (8%). Tier 1 pixels (highrisk, cloglog ≥ 0.65) occupied only 58 % of Uganda’s land but contained 13.7 million residents (9 % of the national population), clustering along the Kampala-Hoima corridor and the Albertine Rift escarpment. All 15 historical outbreak epicentres fell within 8 km of Tier 1 or Tier 2 pixels. An alternative checkerboard partition raised mean AUC by Δ = +0.006 and preserved identical tier rankings, confirming robustness. Conclusions One-kilometre, species-resolved MaxEnt maps pinpoint compact geographic targets where intensified One-Health surveillance, GeneXpert diagnostics and future vaccine rings could most effectively curb EBOD emergence in Uganda.