Urbanization influences hemorrhagic fever with renal syndrome transmission: 34-year evidence from China's national surveillance.

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 sharply from a peak of 10.99 cases/105 in 1986 to fewer than 0.98 cases/105 after 2010, with the top four highest annual averaged HFRS incidence cases reported at the provinces of Heilongjiang, Shandong, Shaanxi and Zhejiang. Bayesian models demonstrated excellent predictive performance (R2 = 0.8722 and 0.8592 for early/late periods, i.e., 1985-2004 and 2005-2018, respectively). Before 2005, impervious surfaces, population and wetlands emerged as the top three dominant transmission predictors. After 2005, however, the key predictors shifted, with wetlands, the Palmer Drought Severity Index (PDSI), and impervious surfaces having the highest relative importance. Interpretation: The quantification of urbanization is provided through impervious surface expansion and wetlands changes, which represent the primary predictors of HFRS transmission in China, likely operating through rodent habitat modification and altered human-wildlife contact patterns. The emerging wetland influence suggests that environmental policies are reshaping disease dynamics. Our findings support urbanization-targeted prevention strategies across the Western Pacific region and highlight integrating land use surveillance into regional infectious disease monitoring systems.