Hemorrhagic fever with renal syndrome (HFRS) continued to affect human health across Eurasia, which complicated by climate change has posed a challenge for the disease prevention measures. Nation-wide surveillance data of HFRS cases were collected during 2008-2020.The seasonality and epidemiological features were presented by combining the HFRS incidence and the endemic types data. Factors potentially involved in affecting incidence and shaping disease seasonality were investigated by generalized additive mixed model, distributed lag nonlinear model and multivariate meta-analysis. A total of 76 cities that reported totally 111,054 cases were analyzed. Three endemic types were determined, among them the Type I cities (Hantaan virus-dominant) were related to higher incidence level, showing one spike every year in Autumn-Winter season; Type II (Seoul virus-dominant) cities were related to lower incidence, showing one spike in Spring, while Type III (Hantaan/Seoul-mixed type) showed dual peaks with incidence lying between. Persistently heavy rainfall had significantly negative influence on HFRS incidence in Hantaan virus-dominant endemic area, while a significantly opposite effect was identified when continuously heavy rainfall induced floods, where temperature and relative humidity affected HFRS incidence via an approximately parabolic or linear manner, however few or no such effects was shown in Seoul virus-dominant endemic areas, which was more vulnerable to temperature variation. Dual seasonal pattern of HFRS was depended on the dominant genotypes of hantavirus, and impact of climate on HFRS was greater in Hantaan virus-dominant endemic areas, than in Seoul virus-dominant areas.
Keywords: DLNM; Factors; Flood; GAMM; HFRS; Seasonality.
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