PuSH - Publikationsserver des Helmholtz Zentrums München

Zhang, D.* ; Zhu, Z.* ; Wang, Y. ; Zhu, L.* ; Zheng, Z.* ; Qu, R.* ; Shao, F.* ; Chen, Q.* ; Xu, Y.* ; Zhang, W.*

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

Parasit. Vectors, DOI: 10.1186/s13071-026-07631-7 (2026)
Postprint Forschungsdaten DOI
Open Access Green
BackgroundHemorrhagic fever with renal syndrome (HFRS) poses a substantial public health burden in China. With its complex topography and rich biodiversity, Southwest China has historically been an endemic area for this natural focal disease. Currently, traditional environmental factors associated with transmission here are increasingly outweighed  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 primary factors associated with HFRS prevalence amid the complex interplay of natural environments and human activities.MethodsSurveillance 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.ResultsThe 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 and U-shaped relationships, constraining the spatial boundaries of transmission.ConclusionsThe spatial heterogeneity of HFRS in Southwest China is jointly driven by anthropogenic activities and natural environmental constraints. Human population density is identified as a primary factor associated with amplified transmission risk, which may reflect 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.
Altmetric
Weitere Metriken?
[➜Einloggen]
Zusatzinfos bearbeiten [➜Einloggen]
Publikationstyp Artikel: Journalartikel
Dokumenttyp Wissenschaftlicher Artikel
Schlagwörter Environmental Niche Modelling ; Population ; Ecological Niche ; Niche ; Receiver Operating Characteristic ; China ; Beijing ; Distribution (mathematics) ; Predictive Modelling
e-ISSN 1756-3305
Zeitschrift Parasites and Vectors
Verlag Springer
Begutachtungsstatus Peer reviewed
Institut(e) Institute of Epidemiology (EPI)