ArticleBMC infectious diseases2023
Spatiotemporal distribution and environmental influences of severe fever with thrombocytopenia syndrome in Shandong Province, China.
Article in BMC infectious diseases, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers, 3 of them syntheses that pooled it.
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Who cites it
9 citing papers in PubMed, 3 syntheses or guidelines pooled it.
- 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
- Comprehensive meta-analysis of severe fever with thrombocytopenia syndrome virus infections in humans, vertebrate hosts and questing ticks.Parasites & vectors · 2024Pooled it
- The effect of meteorological factors on severe fever with thrombocytopenia syndrome: Evidence from 34 Chinese cities.One health (Amsterdam, Netherlands) · 2026Article
- Long-term ecological surveillance of hard ticks (Acari: Ixodidae) and SFTSV in Dangjin, South Korea (2018-2024).Parasites & vectors · 2026Article
- Spatiotemporal pattern of hemorrhagic fever with renal syndrome and driving factors in Shandong Province of China, 2018-2024.PLoS neglected tropical diseases · 2026Article
- [Surveillance of Tick Populations in the Republic of Korea in 2024].Jugan geon-gang gwa jilbyeong · 2025Article
- Article
- Alarming implications: severe fever with thrombocytopenia syndrome and its biological vectors in the context of climate change.Frontiers in microbiology · 2025Review
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Authors and funding
10 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundSevere fever with thrombocytopenia syndrome (SFTS) is an emerging infectious disease discovered in China in 2009. The purpose of this study was to describe the spatiotemporal distribution of SFTS and to identify its environmental influencing factors and potential high-risk areas in Shandong Province, China.
methodsData on the SFTS incidence from 2010 to 2021 were collected. Spatiotemporal scan statistics were used to identify the time and area of SFTS clustering. The maximum entropy (MaxEnt) model was used to analyse environmental influences and predict high-risk areas.
resultsFrom 2010 to 2021, a total of 5705 cases of SFTS were reported in Shandong. The number of SFTS cases increased yearly, with a peak incidence from April to October each year. Spatiotemporal scan statistics showed the existence of one most likely cluster and two secondary likely clusters in Shandong. The most likely cluster was in the eastern region, from May to October 2021. The first secondary cluster was in the central region, from May to October 2021. The second secondary cluster was in the southeastern region, from May to September 2020. The MaxEnt model showed that the mean annual wind speed, NDVI, cattle density and annual cumulative precipitation were the key factors influencing the occurrence of SFTS. The predicted risk map showed that the area of high prevalence was 28,120 km
conclusionsThe spatiotemporal distribution of SFTS was heterogeneous and influenced by multidimensional environmental factors. This should be considered as a basis for delineating SFTS risk areas and developing SFTS prevention and control measures.
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