Spatiotemporal distribution and environmental impact of severe fever with thrombocytopenia syndrome in Zibo City, Shandong Province，2010-2024
10.3969/j.issn.1006-2483.2026.01.013
- VernacularTitle:2010—2024年山东省淄博市发热伴血小板减少综合征的时空分布及环境影响
- Author:
Rongtao ZHAO
1
;
Ruixuan SUN
1
;
Yan ZHANG
1
Author Information
1. Zibo Center for Disease Control and Prevention, Zibo, Shandong 255000, China
- Publication Type:Journal Article
- Keywords:
Severe Fever with thrombocytopenia syndrome;
Spatiotemporal distribution;
Spatiotemporal scan analysis;
Maximum entropy model
- From:
Journal of Public Health and Preventive Medicine
2026;37(1):63-67
- CountryChina
- Language:Chinese
-
Abstract:
Objective To describe the spatiotemporal distribution characteristics of Severe Fever with Thrombocytopenia Syndrome (SFTS) in Zibo City and identify its environmental influencing factors and potential high-risk areas, and to propose targeted strategies for SFTS prevention and control. Methods Data on SFTS incidence from 2010 to 2024 were collected. Spatiotemporal scan statistics were used to identify the time and area of SFTS clustering. The maximum entropy (MaxEnt) model was used to analyze environmental influencing factors and predict high-risk areas. Results From 2010 to 2024, a total of 459 cases of SFTS were reported in Zibo. 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 class I cluster and one class II cluster areas in Zibo. The class I cluster was in Yiyuan District and southern Boshan District, from April to September 2024. The class II cluster was in the center of Zichuan District, from July to September 2024. The MaxEnt model showed that yearly average atmospheric pressure (PRS), yearly average evaporation (EVP), yearly average sunshine duration (SSD) and goat density (Goat) were the key factors influencing the occurrence of SFTS. The predicted risk map showed that the area of high prevalence was 1116 km2, accounting for 18.71% of the total area of the city. Conclusion The spatiotemporal distribution of SFTS exhibits heterogeneity and is influenced by multidimensional environmental factors. This should be considered as a basis for delineating SFTS risk areas and developing SFTS prevention and control measures.
