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预防医学  2026, Vol. 38 Issue (1): 55-59,65    DOI: 10.19485/j.cnki.issn2096-5087.2026.01.010
  疾病控制 本期目录 | 过刊浏览 | 高级检索 |
2011—2024年淮安市发热伴血小板减少综合征流行特征和时空聚集性分析
夏文玲1, 高强1, 李阳2, 蔡奔1, 万春雨1, 崔志贞1, 张正1, 潘恩春1
1.淮安市疾病预防控制中心,江苏 淮安 223001;
2.盱眙县疾病预防控制中心,江苏 盱眙 211700
Epidemiological characteristics and spatial-temporal clustering of severe fever with thrombocytopenia syndrome in Huai'an City from 2011 to 2024
XIA Wenling1, GAO Qiang1, LI Yang2, CAI Ben1, WAN Chunyu1, CUI Zhizhen1, ZHANG Zheng1, PAN Enchun1
1. Huai'an Center for Disease Control and Prevention, Huai'an, Jiangsu 223001, China;
2. Xuyi County Center for Disease Control and Prevention, Xuyi, Jiangsu 211700, China
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摘要 目的 分析2011—2024年江苏省淮安市发热伴血小板减少综合征(SFTS)流行特征和时空聚集性,为优化本地SFTS防控策略,识别高风险区域和重点人群提供依据。方法 通过中国疾病预防控制信息系统传染病报告管理系统收集2011—2024年淮安市SFTS发病和死亡病例资料,计算报告发病率、死亡率和病死率,描述性分析时间分布、人群分布和地区分布。采用平均年度变化百分比(AAPC)分析SFTS报告发病率的变化趋势。采用全局空间自相关和局部空间自相关分析SFTS发病的空间分布模式和空间关联模式,采用时空扫描分析SFTS发病时空聚集性。结果 2011—2024年淮安市累计报告SFTS发病337例,报告发病率从0.17/10万上升至1.88/10万;死亡20例,年均死亡率为0.03/10万,病死率为5.93%。发病呈明显季节性,5—6月为发病高峰,148例占43.92%;春季和夏季分别报告发病107和159例,占31.75%和47.18%。SFTS发病病例以男性、农民和≥41岁人群为主,分别占56.38%、79.23%和96.74%,死亡病例与发病病例人群分布特征基本一致。盱眙县为高发地区,累计报告发病332例,占98.52%,死亡病例均为该县。空间自相关分析结果显示,2019—2024年SFTS发病存在空间正相关,Moran's I值为0.214~0.336(均P<0.05),盱眙县河桥镇、天泉湖镇和桂五镇为高-高聚集区域。时空扫描分析结果显示,聚集簇1与高-高聚集区域一致,聚集时间为2019年第二季度至2022年第二季度。结论 2011—2024年淮安市SFTS报告发病率呈上升趋势,春夏季高发,男性、农民和中老年人为防控重点人群,盱眙县为防控重点区域。
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夏文玲
高强
李阳
蔡奔
万春雨
崔志贞
张正
潘恩春
关键词 发热伴血小板减少综合征流行特征时空聚集性    
AbstractObjective To investigate the epidemiological characteristics and spatial-temporal clustering of severe fever with thrombocytopenia syndrome (SFTS) in Huai'an City, Jiangsu Province from 2011 to 2024, so as to provide a basis for optimizing local SFTS prevention and control strategies, and identifying high-risk areas and key populations. Methods Data on SFTS incidence and deaths in Huai'an City from 2011 to 2024 were collected from the Infectious Disease Reporting Information System of the Chinese Disease Prevention and Control Information System. The reported incidence, mortality, and fatality rates were calculated. Descriptive analysis was performed on temporal, population, and regional distribution. The average annual percent change (AAPC) was used to analyze the trend in the reported incidence of SFTS. Global and local spatial autocorrelation analyses were employed to examine the spatial distribution patterns and spatial association patterns of SFTS incidence while spatio-temporal scanning analyses was used to assess the spatial-temporal clustering of SFTS. Results A total of 337 SFTS cases were reported in Huai'an City from 2011 to 2024, with the reported incidence rising from 0.17/105 to 1.88/105. There were 20 deaths, with an average annual mortality of 0.03/105, and a fatality rate of 5.93%. The incidence showed obvious seasonality, with a peak in May and June (148 cases, accounting for 43.92%). Spring and summer accounted for 107 cases (31.75%) and 159 cases (47.18%), respectively. The reported SFTS cases were mainly male, farmers, and individuals aged ≥41 years, accounting for 56.38%, 79.23%, and 96.74%, respectively. The population distribution of death cases was basically consistent with that of incident cases. Xuyi County was a high-incidence area, with a total of 332 reported cases, accounting for 98.52%. All death cases were reported in this county. Spatial autocorrelation analyses revealed a positive spatial correlation in SFTS incidence from 2019 to 2024, with Moran's I values ranging from 0.214 to 0.336 (all P<0.05). Heqiao Town, Tianquanhu Town, and Guiwu Town in Xuyi County were identified as high-high clustering areas. Spatio-temporal scanning analyses showed that cluster 1 was consistent with the high-high clustering areas, with an aggregation time from the second quarter of 2019 to the second quarter of 2022. Conclusions From 2011 to 2024, the reported incidence of SFTS in Huai'an City showed an upward trend, with a high incidence in spring and summer. Males, farmers, and the middle-aged and elderly population were the key populations for prevention and control. Xuyi County was the key area for prevention and control.
Key wordssevere fever with thrombocytopenia syndrome    epidemiological characteristics    spatial-temporal clustering
收稿日期: 2025-09-17      修回日期: 2025-12-30      出版日期: 2026-01-10
中图分类号:  R512.8  
基金资助:国家自然科学基金项目(12571531)
作者简介: 夏文玲,硕士,主管医师,主要从事疾病控制及公共卫生管理工作
通信作者: 潘恩春,E-mail:hypec@163.com   
引用本文:   
夏文玲, 高强, 李阳, 蔡奔, 万春雨, 崔志贞, 张正, 潘恩春. 2011—2024年淮安市发热伴血小板减少综合征流行特征和时空聚集性分析[J]. 预防医学, 2026, 38(1): 55-59,65.
XIA Wenling, GAO Qiang, LI Yang, CAI Ben, WAN Chunyu, CUI Zhizhen, ZHANG Zheng, PAN Enchun. Epidemiological characteristics and spatial-temporal clustering of severe fever with thrombocytopenia syndrome in Huai'an City from 2011 to 2024. Preventive Medicine, 2026, 38(1): 55-59,65.
链接本文:  
https://www.zjyfyxzz.com/CN/10.19485/j.cnki.issn2096-5087.2026.01.010      或      https://www.zjyfyxzz.com/CN/Y2026/V38/I1/55
[1] YU X J,LIANG M F,ZHANG S Y,et al.Fever with thrombocytopenia associated with a novel bunyavirus in China[J].N Engl J Med,2011,364(16):1523-1532.
[2] 岳玉娟,任东升,伦辛畅.2010—2023年中国发热伴血小板减少综合征死亡病例流行特征分析[J].热带病与寄生虫学,2024,22(5):257-261,300.
[3] 杜珊珊,师悦,陈曦,等.2010—2023年我国发热伴血小板减少综合征流行特征分析[J].中国血吸虫病防治杂志,2025,37(4):371-379.
[4] 中国疾病预防控制中心.发热伴血小板减少综合征防控技术指南(2024版)[Z].北京:中国疾病预防控制中心,2024.
[5] SHORTRIDGE A.Practical limits of Moran's autocorrelation index for raster class maps[J].Comput Environ Urban Syst,2007,31(3):362-371.
[6] ZHANG T L,LIN G.Spatial scan statistics in loglinear models[J].Comput Stat Data Anal,2009,53(8):2851-2858.
[7] ANSELIN L.Local indicators of spatial association—LISA[J].Geogr Anal,1995,27(2):93-115.
[8] 陈秋兰,朱曼桐,陈宁,等.2011—2021年全国发热伴血小板减少综合征流行特征分析[J].中华流行病学杂志,2022,43(6):852-859.
[9] 张乾通,孙继民,凌锋,等.浙江省2021年发热伴血小板减少综合征报告病例及蜱媒监测结果分析[J].中国媒介生物学及控制杂志,2022,33(4):485-488.
[10] 段青,逄博,张晓梅,等.2011—2020年山东省发热伴血小板减少综合征流行特征及空间聚集性[J].中华疾病控制杂志,2022,26(7):790-797.
[11] 杨锟,吴起乐,赵志荣,等.2013—2022年安徽省马鞍山市发热伴血小板减少综合征流行特征及时空聚集性分析[J].疾病监测,2024,39(7):831-835.
[12] 陈康,吴爱兰,马婧婧,等.东阳市发热伴血小板减少综合征病例特征分析[J].预防医学,2024,36(1):47-50.
[13] CASEL M A,PARK S J,CHOI Y K.Severe fever with thrombocytopenia syndrome virus:emerging novel phlebovirus and their control strategy[J].Exp Mol Med,2021,53(5):713-722.
[14] 齐上,庞为,邢俊,等.2011—2023年大连市发热伴血小板减少综合征流行病学特征及空间分析[J].中国公共卫生,2024,40(9):1052-1058.
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