ArticlePLoS neglected tropical diseases2022
Meteorological factors and tick density affect the dynamics of SFTS in jiangsu province, China.
Article in PLoS neglected tropical diseases, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers, 2 of them syntheses that pooled it.
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18 citing papers in PubMed, 2 syntheses or guidelines pooled it, 19 citations in OpenAlex.
- Systematic review of environmental factors associated with severe fever with thrombocytopenia syndrome occurrences.Epidemiologic reviews · 2026Pooled it
- Relationship between meteorological factors and the incidence of severe fever with thrombocytopenia syndrome: a systematic review and meta-analysis.BMC public health · 2025Pooled it
- Meteorological and environmental factors associated with the spatiotemporal risk of severe fever with thrombocytopenia syndrome in Japan: A prefecture-level time-series modeling study.One health (Amsterdam, Netherlands) · 2026Article
- From qualitative prediction to quantitative insight: combined meteorological patterns and regional dynamics of severe fever with thrombocytopenia syndrome in Liaoning Province, China, 2010-2024.Infectious Disease Modelling · 2026Article
- Ecological signature on the epidemiological dynamics of severe fever with thrombocytopenia syndrome.PLoS neglected tropical diseases · 2026Article
- Modeling the role of environmental and socioeconomic factors in endemic SFTS risk using a multicomponent framework.One health (Amsterdam, Netherlands) · 2026Article
- The effect of meteorological factors on severe fever with thrombocytopenia syndrome: Evidence from 34 Chinese cities.One health (Amsterdam, Netherlands) · 2026Article
- Environmental, climatic, and social risk factors of severe fever with thrombocytopenia syndrome and the implications of climate change.One health (Amsterdam, Netherlands) · 2026Article
- Short-Term Effects of Meteorological Factors on Severe Fever With Thrombocytopenia Syndrome Incidence in Xinyang, China.GeoHealth · 2025Article
- Multiscale environmental drivers of human brucellosis transmission in Xinjiang: A spatiotemporal analysis integrating GAM and MaxEnt modeling (2015-2023).PLoS neglected tropical diseases · 2025Article
- Alarming implications: severe fever with thrombocytopenia syndrome and its biological vectors in the context of climate change.Frontiers in microbiology · 2025Review
- Epidemiological characteristics of severe fever with thrombocytopenia syndrome and the relationship with meteorological factors in Jiangsu Province, China.Frontiers in public health · 2025Article
- Development and Comparison of Time Series Models in Predicting Severe Fever with Thrombocytopenia Syndrome Cases - Hubei Province, China, 2013-2020.China CDC weekly · 2024Article
- Time series models in prediction of severe fever with thrombocytopenia syndrome cases in Shandong province, China.Infectious Disease Modelling · 2024Article
- Analysis of Differences in Characteristics of High-Risk Endemic Areas for Contracting Japanese Spotted Fever, Tsutsugamushi Disease, and Severe Fever With Thrombocytopenia Syndrome.Open forum infectious diseases · 2024Article
- Risk assessment of human-to-human transmission of severe fever with thrombocytopenia syndrome virus based on 10-year clustered analysis.Frontiers in public health · 2024Article
- The influence of forest habitat type onCurrent research in parasitology & vector-borne diseases · 2024Article
- The ecological and etiological investigation of ticks and rodents in China: results from an ongoing surveillance study in Zhejiang Province.Frontiers in veterinary science · 2023Article
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25 authors at 2 institutions in 1 country.
Funding
Abstract
backgroundThis study aimed to explore whether the transmission routes of severe fever with thrombocytopenia syndrome (SFTS) will be affected by tick density and meteorological factors, and to explore the factors that affect the transmission of SFTS. We used the transmission dynamics model to calculate the transmission rate coefficients of different transmission routes of SFTS, and used the generalized additive model to uncover how meteorological factors and tick density affect the spread of SFTS.
methodsIn this study, the time-varying infection rate coefficients of different transmission routes of SFTS in Jiangsu Province from 2017 to 2020 were calculated based on the previous multi-population multi-route dynamic model (MMDM) of SFTS. The changes in transmission routes were summarized by collecting questionnaires from 537 SFTS cases in 2018-2020 in Jiangsu Province. The incidence rate of SFTS and the infection rate coefficients of different transmission routes were dependent variables, and month, meteorological factors and tick density were independent variables to establish a generalized additive model (GAM). The optimal GAM was selected using the generalized cross-validation score (GCV), and the model was validated by the 2016 data of Zhejiang Province and 2020 data of Jiangsu Province. The validated GAMs were used to predict the incidence and infection rate coefficients of SFTS in Jiangsu province in 2021, and also to predict the effect of extreme weather on SFTS.
resultsThe number and proportion of infections by different transmission routes for each year and found that tick-to-human and human-to-human infections decreased yearly, but infections through animal and environmental transmission were gradually increasing. MMDM fitted well with the three-year SFTS incidence data (P<0.05). The best intervention to reduce the incidence of SFTS is to reduce the effective exposure of the population to the surroundings. Based on correlation tests, tick density was positively correlated with air temperature, wind speed, and sunshine duration. The best GAM was a model with tick transmissibility to humans as the dependent variable, without considering lagged effects (GCV = 5.9247E-22, R2 = 96%). Reported incidence increased when sunshine duration was higher than 11 h per day and decreased when temperatures were too high (>28°C). Sunshine duration and temperature had the greatest effect on transmission from host animals to humans. The effect of extreme weather conditions on SFTS was short-term, but there was no effect on SFTS after high temperature and sunshine hours.
conclusionsDifferent factors affect the infection rate coefficients of different transmission routes. Sunshine duration, relative humidity, temperature and tick density are important factors affecting the occurrence of SFTS. Hurricanes reduce the incidence of SFTS in the short term, but have little effect in the long term. The most effective intervention to reduce the incidence of SFTS is to reduce population exposure to high-risk environments.
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