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

Shuyi Liang; Zhifeng Li; Nan Zhang; Xiaochen Wang; Yuanfang Qin; Wei Xie; Changjun Bao; Jianli Hu

doi:10.1186/s12889-023-15379-3

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

BMC Public Health. 2023 Mar 16;23(1):508. doi: 10.1186/s12889-023-15379-3.

Authors

Shuyi Liang^#¹, Zhifeng Li^#¹, Nan Zhang¹, Xiaochen Wang¹, Yuanfang Qin¹, Wei Xie², Changjun Bao¹, Jianli Hu³

Affiliations

¹ Acute Infectious disease control and prevention institute, Jiangsu Provincial center for disease control and prevention, Nanjing, China.
² Institute of Food Safety and Assessment, Jiangsu Provincial center for disease control and prevention, Nanjing, China.
³ Acute Infectious disease control and prevention institute, Jiangsu Provincial center for disease control and prevention, Nanjing, China. 59139316@qq.com.

^# Contributed equally.

Abstract

Background: 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.

Methods: 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.

Results: 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 < 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.

Conclusions: The 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.

Keywords: Clustering; Epidemiology characteristic; Severe fever with thrombocytopenia syndrome (SFTS); Space-time scanning.

MeSH terms

Aged
China / epidemiology
Female
Humans
Incidence
Male
Seasons
Severe Fever with Thrombocytopenia Syndrome* / complications
Spatio-Temporal Analysis
Thrombocytopenia* / complications
Thrombocytopenia* / epidemiology