Ontology highlight
ABSTRACT: Background
Mainland China accounts for over 90 % of the global hemorrhagic fever with renal syndrome (HFRS) cases, yet quantitative relationships between climate, urbanization and transmission dynamics remain poorly understood across national scales.Methods
We analyzed 34 years of HFRS surveillance data (1985-2018) from 31 provincial-level administrative divisions in China to examine the associations with climatic variables, socioeconomic indicators, and land use types using Bayesian nonlinear mixed-effects models. Dominance analysis was conducted to quantify the relative importance of each predictor. Additionally, linear mixed-effects and generalized additive models were implemented for comparative and validation purposes.Findings
Annual HFRS incidence declined sha
SUBMITTER: He J
PROVIDER: S-EPMC12765435 | biostudies-literature | 2026 Jun
REPOSITORIES: biostudies-literature