2018-2021年中国发热伴血小板减少综合征流行特征分析
Epidemiological characteristics of severe fever with thrombocytopenia syndrome in China,2018-2021
黄晓霞 1杜珊珊 1李阿茜 1李川 1田婷婷 1刘铁柱 1王芹 1梁米芳 1王世文 1李建东 1李德新1
作者信息
- 1. 中国疾病预防控制中心病毒病预防控制所/国家卫生健康委员会医学病毒和病毒病重点实验室,北京 102206
- 折叠
摘要
目的 分析我国发热伴血小板减少综合征(SFTS)流行现状及趋势.方法 采集中国疾病预防控制信息系统2018-2021年全国SFTS病例数据,采用Excel 2016、Joinpoint 5.0.2、SPSS 26.0和GraphPad Prism 8.0等软件进行统计学和描述流行病学分析,尤其重点省份按月报告SFTS病例情况.结果 2018-2021年,全国共有25个省份累计报告病例8 835例,年报告发病率呈上升趋势,病例具有一定的区域聚集性,但以散发为主,报告病例数自3月开始逐渐增多,主要集中在4-10月(96.79％,8 551/8 835),一般在5-7月达高峰;人群分布以中老年农民为主,女性略多于男性,平均病死率为5.38％,不同地区差异较大,病死率随年龄增长而增加.结论 2018-2021年,我国SFTS流行特征虽维持稳定,但报告病例数逐渐增多,分布范围呈扩大趋势,应予以关注.
Abstract
Objective To understand the epidemiological characteristics and incidence trend of severe fever with thrombocytopenia syndrome(SFTS)in China.Methods The incidence data of SFTS in China from 2018 to 2021 were collected from Chinese Disease Prevention and Control Information System for a statistical and descriptive epidemiological analysis by using software such as Excel 2016,Joinpoint 5.0.2,SPSS 26.0,and GraphPad Prism 8.0,especially,the SFTS cases reported monthly by key provinces were analyzed.Results From 2018 to 2021,a total of 8 835 SFTS cases were reported in 25 provinces and the annual incidence showed an upward trend.The distribution of SFTS cases showed clustering,but the cases were mainly sporadic ones.The cases began to increase in March,mainly occurred during April to October(96.79％,8 551/8 835),and peaked during May to July.The cases were mainly distributed in middle-aged and old farmers,and slight more cases were women.The average case fatality rate was 5.38％,which varied greatly with areas.The case fatality rate tended to increase with age.Conclusion From 2018 to 2021,the epidemiological characteristics of SFTS in China remained stable,but the number of reported cases gradually increased and the distribution showed an expanding trend,to which close attention should be paid.
关键词
发热伴血小板减少综合征/流行特征/监测Key words
Severe fever with thrombocytopenia syndrome/Epidemiological characteristic/Surveillance引用本文复制引用
基金项目
国家科技重大专项(2018ZX10711-001-001)
出版年
2024
NETL
NSTL
维普
万方数据