ArticleBMC public health2023
Epidemiological and spatiotemporal analysis of severe fever with thrombocytopenia syndrome in Eastern China, 2011-2021.
Article in BMC public health, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers.
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Who cites it
18 citing papers in PubMed, 22 citations in OpenAlex.
- Hyper-activated low-density neutrophil-derived NGAL predicts fatal SFTS: a multi-cohort and single-cell study.Infection · 2026Article
- Epidemiological characteristics of severe fever with thrombocytopenia syndrome (SFTS) in China, 2010-2024: a fifteen-year national surveillance analysis.BMC infectious diseases · 2026Article
- Ecological signature on the epidemiological dynamics of severe fever with thrombocytopenia syndrome.PLoS neglected tropical diseases · 2026Article
- The effect of meteorological factors on severe fever with thrombocytopenia syndrome: Evidence from 34 Chinese cities.One health (Amsterdam, Netherlands) · 2026Article
- Spatiotemporal dynamics and environmental factors of human brucellosis in mainland China, 2004-2022.BMC infectious diseases · 2026Article
- Epidemiological Characteristics of Severe Fever with Thrombocytopenia Syndrome.The American journal of tropical medicine and hygiene · 2025Review
- Epidemiological characteristics and risk distribution prediction of severe fever with thrombocytopenia syndrome in Zhejiang Province, China.PLoS neglected tropical diseases · 2025Article
- Epidemiological characteristics of severe fever with thrombocytopenia syndrome and the relationship with meteorological factors in Jiangsu Province, China.Frontiers in public health · 2025Article
- Focal persistence and phylodynamics of Heartland virus in Georgia.Virus evolution · 2025Article
- Epidemiology and spatiotemporal analysis of acute hemorrhagic conjunctivitis in Zhejiang province, China (2004-2023).Frontiers in public health · 2025Article
- Biomarkers for Early Predicting In-Hospital Mortality in Severe Fever with Thrombocytopenia Syndrome and Differentiating It from Hemorrhagic Fever with Renal Syndrome.Infection and drug resistance · 2025Article
- Advances in research on severe fever with thrombocytopenia syndrome virus.Frontiers in microbiology · 2025Review
- Adenovirus type 5-expressing Gn induces better protective immunity than Gc against SFTSV infection in mice.NPJ vaccines · 2024Article
- Spatial and Temporal Analysis of Severe Fever with Thrombocytopenia Syndrome in Anhui Province from 2011 to 2023.Journal of epidemiology and global health · 2024Article
- Spatiotemporal distribution and environmental influences of severe fever with thrombocytopenia syndrome in Shandong Province, China.BMC infectious diseases · 2023Article
- Epidemiological characteristics and spatio-temporal aggregation of severe fever with thrombocytopenia syndrome in Jinan City, China, 2018-2022.PLoS neglected tropical diseases · 2023Article
- Severe fever with thrombocytopenia syndrome virus induces platelet activation and apoptosis via a reactive oxygen species-dependent pathway.Redox biology · 2023Article
- Analysis of the spatial-temporal distribution characteristics of hepatitis E in Jiangsu province from 2005 to 2020.Frontiers in public health · 2023Article
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Authors and funding
8 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundSevere fever with thrombocytopenia syndrome (SFTS) is an emerging infectious disease, which is caused by severe fever with thrombocytopenia syndrome virus (SFTSV) with high fatality. Recently, the incidence of SFTS increased obviously in Jiangsu Province. However, the systematic and complete analysis of spatiotemporal patterns and clusters coupled with epidemiological characteristics of SFTS have not been reported so far.
methodsData on SFTS cases were collected during 2011-2021. The changing epidemiological characteristics of SFTS were analyzed by adopting descriptive statistical methods. GeoDa 1.18 was applied for spatial autocorrelation analysis, and SaTScan 10.0 was used to identify spatio-temporal clustering of cases. The results were visualized in ArcMap.
resultsThe annual incidence of SFTS increased in Jiangsu Province from 2011 to 2021. Most cases (72.4%) occurred during May and August with the obvious peak months. Elderly farmers accounted for most cases, among which both males and females were susceptible. The spatial autocorrelation and spatio-temporal clustering analysis indicated that the distribution of SFTS was not random but clustered in space and time. The most likely cluster was observed in the western region of Jiangsu Province and covered one county (Xuyi county) (Relative risk = 8.18, Log likelihood ratio = 122.645, P < 0.001) located in southwestern Jiangsu Province from January 1, 2017 to December 31, 2021. The Secondary cluster also covered one county (Lishui county) (Relative risk = 7.70, Log likelihood ratio = 94.938, P < 0.001) from January 1, 2017 to December 31, 2021.
conclusionsThe annual number of SFTS cases showed an increasing tendency in Jiangsu Province from 2011 to 2021. Our study elucidated regions with SFTS clusters by means of ArcGIS in combination with spatial analysis. The results demonstrated solid evidences for the orientation of limited sanitary resources, surveillance in high-risk regions and early warning of epidemic seasons in future prevention and control of SFTS in Jiangsu Province.
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