2016—2020年湖南省手足口病时空聚集性分析

Spatial-temporal clustering analysis of hand,foot and mouthdisease in Hunan Province in 2016-2020

目的分析2016—2020年湖南省手足口病时空聚集性特点,为手足口病疫情防控提供科学依据。方法在中国疾病预防控制信息系统收集2016—2020年湖南省手足口病数据,以县区为单位采用ArcGIS 10.2软件对手足口病发病数据进行空间自相关分析,采用SaTScan 9.7软件对手足口病发病数据进行时空聚集性分析。结果2016—2020年湖南省累计报告手足口病714157例,年均发病率208.36/10万。全局空间自相关显示,2016—2020年湖南省手足口病在县区尺度上存在空间正相关。局部空间自相关显示,热点区域主要集中在湘中偏北、湘中部偏东和湘西地区。时空扫描分析探测到一类聚集区(RR=6.65,P<0.001)覆盖湘北、湘中34个县区,主要分布在岳阳市、长沙市、株洲市、益阳市和湘潭市,聚集时间为2018年5月至2018年6月;二类聚集区(RR=3.02,P<0.001)覆盖大湘西地区及湘中、湘西南40个县区,聚集时间为2016年4月至2016年6月。结论湖南省手足口病的发病有季节性和地区高发特点,应结合时空聚集性特点,指导手足口病防控工作。

Objective To analyze the spatial and temporal characteristics of hand,foot and mouth disease(HFMD)in Hunan Province from 2016 to 2020.Methods The data of HFMD in Hunan Province from 2016 to 2020 were collected from China′s Disease Prevention and Control Information System.HFMD spatial autocorrelation analysis was conducted by ArcGIS 10.2 software at county level,and spatial-temporal scan statistical analysis was performed by SaTScan 9.7 software.Results A total of 714157 cases was reported in Hunan Province during 2016-2020,with an average annual incidence rate of 208.36/100000.Global spatial autocorrelation showed that HFMD had a positive spatial correlation on the county scale in Hunan Province during this period.Local spatial autocorrelation indicated that the hot spots were mainly concentrated in the north of central Hunan,the east of central Hunan and the west of Hunan.Spatial-temporal scanning analysis revealed the first class clusters(RR=6.65,P<0.001)covering 34 counties in northern and central Hunan,mainly distributed in Yueyang City,Changsha City,Zhuzhou City,Yiyang City and Xiangtan City from May 2018 to June,and the second class clusters(RR=3.02,P<0.001)covering 40 counties in western Hunan and central and southwest Hunan from April 2016 to June 2016.Conclusion HFMD incidence exhibits seasonal and regional characteristics in Hunan Province.The prevention and control of HFMD should be guided by combining the characteristics of spatial-temporal clustering.