{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,2]],"date-time":"2026-10-02T19:38:07Z","timestamp":1790969887854,"version":"4.1.0"},"reference-count":54,"publisher":"Public Library of Science (PLoS)","issue":"7","license":[{"start":{"date-parts":[[2025,7,24]],"date-time":"2025-07-24T00:00:00Z","timestamp":1753315200000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"National Key Research and Development Program of China","award":["2023YFC2604400"],"award-info":[{"award-number":["2023YFC2604400"]}]}],"content-domain":{"domain":["www.plosntds.org"],"crossmark-restriction":false},"short-container-title":["PLoS Negl Trop Dis"],"abstract":"<jats:sec id=\"sec013\">\n<jats:title>Background<\/jats:title>\n<jats:p>Hemorrhagic fever with renal syndrome (HFRS) is a rodent-borne zoonotic disease with a case fatality rate ranging from 1% to 15%. Long-term evidence regarding its association with local hydrometeorological conditions remain limited. This study aimed to assess the non-linear and lagged effects of extreme hydrometeorological conditions on HFRS risk and examine the modifying effects of regional characteristics in Shandong Province, China.<\/jats:p>\n<\/jats:sec>\n<jats:sec id=\"sec014\">\n<jats:title>Methods<\/jats:title>\n<jats:p>Data from January 1, 2005 to December 31, 2019 across 136 counties in Shandong Province were collected. The Standardized Precipitation Evapotranspiration Index (SPEI), calculated from temperature, precipitation and evaporation, was used to represent local hydrometeorological conditions (dry and wet). A spatiotemporal Bayesian hierarchical model combined with distributed lag non-linear model was applied to explore the association between climate indicators and HFRS risk over a 6-month lag. Modification effects were quantified using linear interaction terms.<\/jats:p>\n<\/jats:sec>\n<jats:sec id=\"sec015\">\n<jats:title>Results<\/jats:title>\n<jats:p>Over the 15-year period, annual HFRS incidence declined from 2.62\/100,000 to 0.72\/100,000, with two minor peaks observed. The cumulative association between SPEI and HFRS over 6-month lag appeared U-shaped. The relative risk (RR) of HFRS under extreme wet conditions increased at 4\u20136 months lag, peaking at the 6-month lag (RR\u2009=\u20091.49, 95% confidence interval (CI): 1.37-1.63). Extreme dry conditions had a persistent impact, also peaking at the 6-month lag (RR\u2009=\u20091.05, 95% CI: 1.01-1.09). Areas with low per capita Gross Domestic Product, Normalized difference vegetation index, Total power of agricultural machinery and annual temperature, as well as high elevation, exhibited higher risks of HFRS under extreme wet conditions. The modification effects under extreme dry conditions were similar but weaker.<\/jats:p>\n<\/jats:sec>\n<jats:sec id=\"sec016\">\n<jats:title>Conclusions<\/jats:title>\n<jats:p>Both extreme wet and dry conditions increase the risk of HFRS, with county characteristics further modifying these associations. These findings provide a scientific foundation for policymakers to develop targeted and effective HFRS prevention and control strategies, particularly in high-risk regions, while considering hydrometeorological conditions.<\/jats:p>\n<\/jats:sec>","DOI":"10.1371\/journal.pntd.0013306","type":"journal-article","created":{"date-parts":[[2025,7,24]],"date-time":"2025-07-24T17:34:06Z","timestamp":1753378446000},"page":"e0013306","update-policy":"https:\/\/doi.org\/10.1371\/journal.pntd.corrections_policy","source":"Crossref","is-referenced-by-count":3,"title":["Association between hydrometeorological conditions and hemorrhagic fever with renal syndrome in Shandong Province, China, from 2005 to 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