ArticlePLoS neglected tropical diseases2025
Epidemiological characteristics and risk distribution prediction of severe fever with thrombocytopenia syndrome in Zhejiang Province, China.
Article in PLoS neglected tropical diseases, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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Who cites it
2 citing papers in PubMed.
- Environmental, climatic, and social risk factors of severe fever with thrombocytopenia syndrome and the implications of climate change.One health (Amsterdam, Netherlands) · 2026Article
- Modeling the role of environmental and socioeconomic factors in endemic SFTS risk using a multicomponent framework.One health (Amsterdam, Netherlands) · 2026Article
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7 authors.
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Abstract
backgroundSevere fever with thrombocytopenia syndrome (SFTS) is an emerging infectious disease, garnering increasing attention due to rising case numbers and expanding geographical reach. However, there is limited research on the potential factors influencing the distribution of SFTS.
methodsData on SFTS cases in Zhejiang province were obtained from 2011 to 2022. Data on ecoclimatic factors, land cover, and human population density at the county level were also collected. Spatial autocorrelation analysis was used to analyze the epidemic characteristics and spatial clustering. A boosted regression tree (BRT) model was used to assess ecoclimatic and socioenvironmental drivers for the distributions of SFTS.
resultsThe SFTS cases increased from 9 in 2011-1,103 in 2022 with an average incidence rate of 0.099 per 100,000. There is an obvious seasonality to SFTS cases, primarily occurring between April and August. We detected global spatial autocorrelation of SFTS cases in all years (P < 0.05) except 2011, 2012 and 2014. Local spatial autocorrelation analysis suggested that the "High-high" agglomeration areas are mainly distributed in the hilly terrain of the east coast of Zhejiang province. Furthermore, factors such as mean temperature of wettest quarter (relative contribution, RC = 18.51%) and annual precipitation (9.29%) were found to have significantly contribution to the occurrence of SFTS. The model-predicted risk areas, particularly in Daishan County (predicted probability of cases: 0.986), Linhai city (0.972), and Tiantai County (0.971), align with reported cases.
conclusionsThese findings suggested that SFTS incidence has increased and spatially expanded over the past few years. It is necessary to expand the scope and improve the sensitivity of surveillance, especially in western, southern and northern Zhejiang.
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