Regional and Seasonal Dynamics of Leptospirosis in Ukraine, 2023-2025.

Background: Ukraine has substantial regional differences in climate, landscape, forest cover, and river networks, which may influence leptospirosis transmission. However, recent monthly oblast-level variation in leptospirosis incidence has not been systematically described. We used newly available surveillance data for 2023-2025 to assess seasonal and regional patterns of leptospirosis and their associations with weather, climatic zone, forest cover, and river network density. Methods: We analyzed surveillance data from 23 Ukrainian oblasts. Incidence was assessed by month, oblast, and climatic zone. Weather data were aggregated monthly; forest cover and river network density were included as predictors. Associations were assessed using correlation, cross-correlation, and Random Forest ML models. Results: Incidence showed a clear seasonal increase, reaching its highest levels in late summer and autumn, approximately one to three months after seasonal peaks in temperature and precipitation. The highest incidence was observed in Zakarpattia, Chernihiv, and Ternopil oblasts, while incidence by climatic zone was highest in the Carpathian group and lowest in the Steppe zone. Among weather variables, average temperature showed the clearest delayed association with leptospirosis incidence. River network density was the leading ecological predictor in the adjusted models. The positive unadjusted association between forest cover and incidence became negative after adjustment for river network density, suggesting that these variables captured overlapping ecological characteristics. In the Random Forest analysis, river network density was the top-ranked predictor, and the best-performing model achieved an AUC of 0.795. Conclusions: Leptospirosis incidence in Ukraine varied substantially by season and region. Delayed temperature effects, river network density, and forest cover were associated with regional risk. Monthly oblast-level surveillance with climatic and ecological data may help monitor leptospirosis risk, but war-related disruption to diagnosis and reporting should be considered.