Complex exposure–response relationships between meteorological factors and severe fever with thrombocytopenia syndrome risk

Severe fever with thrombocytopenia syndrome (SFTS) is an emerging tick-borne infectious disease influenced by meteorological factors. This study aimed to characterize the complex exposure–response relationships between multiple meteorological factors and SFTS risk in Anhui Province, China. Monthly SFTS cases and meteorological data from 2011 to 2023 were analyzed. Candidate lag structures were evaluated using negative binomial generalized additive models (NB-GAM), followed by Bayesian kernel machine regression (BKMR) to assess the joint and individual effects of meteorological factors. Pairwise interactions were quantified using posterior BKMR interaction contrasts and pooled across cities using random-effects meta-analysis. Regional subgroup analyses were also performed. A total of 5,715 SFTS cases were reported, with 84.74% occurring among farmers, and eight cities accounted for 95.56% of all cases. The lag01 showed the best overall model performance and was selected for BKMR analyses. BKMR revealed heterogeneous joint and individual exposure–response patterns across cities, with average temperature and atmospheric pressure showing prominent contributions. However, formal interaction analyses provided no clear evidence of pairwise interactions, and all ten pooled interaction contrasts had 95% confidence intervals including zero. Regional subgroup analysis suggested a stronger joint meteorological effect in the Jianghuai hilly area [0.27 (95% CI 0.03–0.50)] than in the Southern Mountains Region [0.03 (95% CI −0.08–0.15)]. Meteorological factors showed complex joint exposure–response relationships with SFTS risk, with substantial geographic variation across Anhui Province. Although no clear pairwise interactions were identified, regional differences in joint meteorological effects highlight the importance of considering local ecological and climatic conditions in SFTS early warning and prevention strategies.

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Publication Details

Journal
Tropical Medicine and Health
Published
2026-09-21
DOI
https://doi.org/10.1186/s41182-026-01077-4
Primary Topic
Viral Infections and Vectors
Type
article
Field-Weighted Citation Impact
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article

Complex exposure–response relationships between meteorological factors and severe fever with thrombocytopenia syndrome risk

Guangju Mo, Chunyue Ai, Huaiping Zhu, Shengping Dou et al.
Tropical Medicine and Health
Viral Infections and Vectors
article

Complex exposure–response relationships between meteorological factors and severe fever with thrombocytopenia syndrome risk

Guangju Mo, Chunyue Ai, Huaiping Zhu, Shengping Dou, Wenyu Wang, Qiyong Liu, Haoqiang Ji, Meng Shang
article en

Abstract

Severe fever with thrombocytopenia syndrome (SFTS) is an emerging tick-borne infectious disease influenced by meteorological factors. This study aimed to characterize the complex exposure–response relationships between multiple meteorological factors and SFTS risk in Anhui Province, China. Monthly SFTS cases and meteorological data from 2011 to 2023 were analyzed. Candidate lag structures were evaluated using negative binomial generalized additive models (NB-GAM), followed by Bayesian kernel machine regression (BKMR) to assess the joint and individual effects of meteorological factors. Pairwise interactions were quantified using posterior BKMR interaction contrasts and pooled across cities using random-effects meta-analysis. Regional subgroup analyses were also performed. A total of 5,715 SFTS cases were reported, with 84.74% occurring among farmers, and eight cities accounted for 95.56% of all cases. The lag01 showed the best overall model performance and was selected for BKMR analyses. BKMR revealed heterogeneous joint and individual exposure–response patterns across cities, with average temperature and atmospheric pressure showing prominent contributions. However, formal interaction analyses provided no clear evidence of pairwise interactions, and all ten pooled interaction contrasts had 95% confidence intervals including zero. Regional subgroup analysis suggested a stronger joint meteorological effect in the Jianghuai hilly area [0.27 (95% CI 0.03–0.50)] than in the Southern Mountains Region [0.03 (95% CI −0.08–0.15)]. Meteorological factors showed complex joint exposure–response relationships with SFTS risk, with substantial geographic variation across Anhui Province. Although no clear pairwise interactions were identified, regional differences in joint meteorological effects highlight the importance of considering local ecological and climatic conditions in SFTS early warning and prevention strategies.

Tropical Medicine and HealthVol. 54(1)
Weifang Medical University (CN), Shandong University (CN), Chinese Center For Disease Control and Prevention (CN), York University (CA), National Institute for Communicable Disease Control and Prevention (CN)
Openalex Percentile: Top 11%
Viral Infections and Vectors
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