Meteorological drivers of hemorrhagic fever with renal syndrome in China's Jiaodong Peninsula: an ecological time-series study from 2020 to 2024.

Background: Hemorrhagic Fever with Renal Syndrome (HFRS) is a naturally occurring zoonotic disease significantly influenced by meteorological factors, with rodents serving as the primary reservoir. It imposes a substantial global disease burden. This study aims to investigate the non-linear and interactive effects of meteorological factors on HFRS, as well as the exposure-lag-response patterns on the Jiaodong Peninsula in China. Method: Daily meteorological data for the Jiaodong Peninsula from 2020 to 2024 were collected from the China Meteorological Data Sharing Service System. Daily incidence data for HFRS cases were collected from the China Disease Prevention and Control Information System. A generalized additive model with quasi-Poisson regression was conducted to examine the non-linear relationships and interactive effects between meteorological factors and HFRS. A distributed lag non-linear model was constructed to investigate the exposure-lag effects of meteorological factors on HFRS. Model analysis was conducted using R 4.5.1 software, and visualization was performed using ArcGIS 10.7 software. Result: From 2020 to 2024, a cumulative total of 1,121 cases of HFRS were reported in China's Jiaodong Peninsula. Among these, Qingdao reported 594 cases, Yantai reported 438 cases, and Weihai reported 89 cases. HFRS exhibits a distinct seasonal pattern, with the peak incidence occurring annually from October to December. Spearman correlation analysis and random forest regression analysis were employed to screen the original meteorological factors. Ultimately, weekly average air pressure was excluded, while weekly average temperature, weekly average wind speed, weekly average humidity, and weekly average precipitation were incorporated into subsequent modeling. The results indicate that all four meteorological factors influence the occurrence of HFRS, exhibiting a pronounced non-linear relationship. Interaction analysis indicates that within an appropriate temperature range, increases in precipitation, relative humidity, and wind speed within certain thresholds can synergistically heighten the risk of HFRS incidence. Using the median meteorological factor as the baseline, the risk of HFRS significantly increased after a 13-week lag (RR = 1.185, 95% CI: 1.016-1.381) during periods of extremely high temperature (the 95th percentile of WAT, 27 °C). Under extremely low temperature (the 5th percentile of WAT, -1 °C), the risk of HFRS significantly increased after a 15-week lag period (RR = 1.189, 95% CI: 1.014-1.394). Under extremely high humidity (the 95th percentile of WAH, 88%), the risk of HFRS significantly increased after a 14-week lag period (RR = 1.262, 95% CI: 1.023-1.557). However, no statistically significant effect was observed at extremely low humidity (the 5th percentile of WAH, 50%). Conclusion: The prevalence of HFRS on China's Jiaodong Peninsula exhibits a significant non-linear association with meteorological factors, accompanied by pronounced interaction effects and complex exposure lag effects. The findings of this study provide quantitative evidence for regional precision-based early warning and tiered prevention and control measures. Public health authorities should formulate disease prevention and control strategies based on these results to reduce the burden of HFRS.