Predicting the potential distribution of hemorrhagic fever with renal syndrome in Southwest China using the ecological niche modeling

Background Hemorrhagic fever with renal syndrome (HFRS) severely burdens China's public health. With its complex topography and rich biodiversity, Southwest China has historically incubated this natural focal disease. Currently, traditional environmental drivers of transmission here are increasingly eclipsed by anthropogenic forces, notably population agglomeration. Driven by these shifting dynamics, HFRS incidence and endemic ranges are expanding, yet systematic, regional-scale assessments remain scarce. Consequently, this study employs ecological niche modeling to map potential high-risk zones. Ultimately, we aim to explore the core mechanisms driving HFRS prevalence amid the complex interplay of natural environments and human activities. Methods Surveillance data of HFRS cases in Southwest China from 2014 to 2023 were obtained from the China Information System for Disease Control and Prevention (CISDCP). A Maximum Entropy (MaxEnt) model was constructed by integrating occurrence records with multisource environmental variables, including meteorological, socioeconomic, and land cover factors. Model performance was evaluated using the Area Under the Curve (AUC) of the Receiver Operating Characteristic (ROC), and the Jackknife test was employed to quantify the contribution of each variable. Results The MaxEnt model demonstrated robust predictive performance with a mean AUC of 0.902. Population density was identified as the predominant predictor (73.5% contribution), followed by the Normalized Difference Vegetation Index (NDVI) in May (9.2%) and annual mean temperature (5.8%). The spatial distribution of risk exhibited a core aggregation with sporadic dispersion pattern, with high-risk zones concentrated in the Chengdu-Chongqing urban agglomeration and localized clusters in Yunnan Province. Response curves revealed a sigmoidal positive correlation between population density and disease risk. Meteorological factors, such as temperature and precipitation, exhibited non-linear inverted U-shaped or U-shaped relationships, constraining the spatial boundaries of transmission. Conclusions The spatial heterogeneity of HFRS in Southwest China is jointly driven by anthropogenic activities and natural environmental constraints. Human population density acts as the primary amplifier of transmission risk, supporting the human behavior amplification effect in natural focal diseases. These findings suggest a strategic shift from blanket prevention to precision control, prioritizing active surveillance in densely populated urban fringes and areas undergoing infrastructure development.