Epidemiological and spatiotemporal analysis of severe fever with thrombocytopenia syndrome in Eastern China, 2011-2021

Severe 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 analysi...

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Bibliographic Details
Published in:BMC public health 2023-03, Vol.23 (1), p.508-508, Article 508
Main Authors: Liang, Shuyi, Li, Zhifeng, Zhang, Nan, Wang, Xiaochen, Qin, Yuanfang, Xie, Wei, Bao, Changjun, Hu, Jianli
Format: Article
Language:English
Subjects:
Aged
Arachnids
Autocorrelation
Care and treatment
China - epidemiology
Cluster analysis
Clustering
Complications and side effects
Development and progression
Epidemiology
Epidemiology characteristic
Female
Fever
Humans
Hyperthermia
Incidence
Infectious diseases
Information systems
Likelihood ratio
Male
Males
Methods
Parasitic diseases
Public health
R&D
Research & development
Risk
Seasons
Severe fever with thrombocytopenia syndrome (SFTS)
Severe Fever with Thrombocytopenia Syndrome - complications
Software
Space-time scanning
Spacetime
Spatial analysis
Spatial analysis (Statistics)
Spatio-Temporal Analysis
Statistical methods
Thrombocytopenia
Thrombocytopenia - complications
Thrombocytopenia - epidemiology
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Summary:Severe 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. Data 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. The 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 
ISSN:1471-2458
1471-2458
DOI:10.1186/s12889-023-15379-3