Spatial-temporal distribution characteristics of haemorrhagic fever with renal syndrome (HFRS) in 31 provinces and municipalities of P.R. China and multi-factorial prediction of incidence

Objective: To integrate multi-source spatiotemporal data and construct an HFRS incidence prediction model using XGBoost with SHAP, exploring factors associated with HFRS incidence in China. Methods: Collected HFRS case data from 31 provinces in China (2005–2020) and multi-source data on climate, land use, and population. Used MaxEnt to analyze rodent distribution and key environmental variables. Constructed an XGBoost model integrating climate, land use, host, and socio-economic features, with SHAP values assessing feature contributions. Dataset divided into training (70%), validation (15%), and test (15%) sets, with higher weights for high-incidence provinces. Results: The reported HFRS cases in mainland China decreased from 2005 to 2020 but showed seasonal peaks. Cases were mainly among adults aged 20–60 years. The distribution of virus-carrying rodents was mainly affected by minimum temperature of the coldest month and elevation. After removing temporal features, land-use types (forest, cropland, shrub) showed greater relative importance than climate variables. Conclusion: Forest, shrub, and cropland may affect disease transmission via host distribution and food availability. Climate factors act indirectly on HFRS risk. Temporal features remain critical for incidence prediction, while land use and rodent habitats are key exogenous drivers. These findings support targeted public health strategies. Author summary: Hemorrhagic fever with renal syndrome (HFRS) is a serious rodent-borne infectious disease that remains an important public health concern in China. Although the number of reported HFRS cases has generally declined, the disease continues to show clear seasonal and geographical differences, making it difficult to identify areas and periods of increased risk. In this study, we combined HFRS surveillance data from 31 provincial-level regions in mainland China between 2005 and 2020 with information on climate, land use, population, and the distribution of virus-carrying rodents. We found that HFRS cases were concentrated mainly among adults aged 20–60 years and showed distinct seasonal peaks. We also identified important differences in the distribution of the two major rodent groups associated with HFRS. Our prediction analysis showed that recent HFRS case patterns were the strongest predictors of future incidence. When previous case information was excluded, land-use characteristics, particularly forest and cropland, became the most important factors, while climate factors appeared to influence HFRS risk partly by shaping rodent habitats. These findings highlight the importance of combining disease surveillance with environmental and rodent monitoring to improve early warning and support more targeted HFRS prevention and control in China.