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

Epidemiological characteristics and spatiotemporal clustering of severe fever with thrombocytopenia syndrome in Maanshan, Anhui, 2013−2022

  • 摘要:
    目的  通过分析2013—2022年安徽省马鞍山市发热伴血小板减少综合征(SFTS)流行特征及时空聚集性,为在重点地区科学制定综合防控策略和干预措施提供依据。
    方法  通过中国疾病预防控制信息系统收集数据资料,采用流行病学分析、空间自相关分析、时空扫描统计分析方法,分析马鞍山市SFTS流行特征及时空聚集性。
    结果  2013—2022年马鞍山市累计报告SFTS病例286例,年均报告发病率为1.27/10万,年度变化百分比为28.95%(95%置信区间:18.33%~40.51%,P<0.01);累计报告死亡32例,平均病死率为11.19%。 每年4—10月为发病高峰,病例年龄为66(56,73)岁,≥45岁的占91.96%,女性发病率(1.43/10万)高于男性(1.11/10万)(χ2=4.470,P=0.030),病例职业以农民为主(84.27%)。 全局空间自相关分析显示,各年SFTS发病率均存在空间聚集性(均P<0.05);局部空间自相关和时空扫描统计分析显示,“高–高”聚集区主要集中在含山县部分乡镇,2021—2022年存在4个时空聚集区。
    结论  马鞍山市SFTS发病呈上升趋势,存在季节性和时空聚集性,中老年农民为发病主要人群,建议在流行季节高效开展重点人群疾病监测管理,在重点地区探索制定综合防控策略以有效控制SFTS疫情。

     

    Abstract:
    Objective To understand the epidemiological characteristics and spatiotemporal clustering of severe fever with thrombocytopenia syndrome (SFTS) in Maanshan, Anhui province, from 2013 to 2022 and provide evidence for the development of comprehensive prevention and control strategies and intervention measures in key areas.
    Methods The incidence data of SFTS in Maanshan during this period were obtained from Chinese Disease Control and Prevention System for an epidemiological analysis, and spatial autocorrelation analysis and spatiotemporal scanning statistical analysis were conducted.
    Results From 2013 to 2022, a total of 286 cases of SFTS were reported in Maanshan, including 32 deaths. The annual average reported incidence was 1.27/100 000 with an annual percent change of 28.95% (95% confidence interval: 18.33%–40.51%, P<0.01), and the average case fatality rate was 11.19%. The annual incidence peak of SFTS occurred during April-October. The median age of the cases was 66 years (56, 73), the cases aged ≥45 years accounted for 91.96%. The incidence was higher in women (1.43/100 000) than in men (1.11/100 000) (χ2=4.470, P=0.030). The cases in farmers accounted for 84.27%. Global spatial autocorrelation analysis showed that spatial clustering existed in the annual incidence of SFTS (all P<0.05). Local spatial autocorrelation analysis and spatiotemporal scanning statistical analysis showed that “high-high” clustering areas were mainly in some townships in Hanshan county, and there were 4 spatiotemporal clustering areas from 2021 to 2022.
    Conclusion The incidence of SFTS in Maanshan showed an upward trend with seasonal and spatiotemporal clustering, and middle-aged and elderly farmers were mainly affected. It is suggested to effectively carry out disease surveillance and management in key populations during the epidemic season, and develop comprehensive prevention and control strategies in key areas to effectively control the epidemic of SFTS.

     

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