江苏省2016—2022年输入性疟疾空间流行特征及热点分布变化规律  

Spatial epidemiological characteristics and hotspots distribution changing of imported malaria in Jiangsu,2016-2022

作　　者：刘凯旋 曹园园[2] 崇泽银 柴丽莹 赵理 卢艳 朱国鼎[2,4] 曹俊 卢光玉[1,5] LIU Kaixuan;CAO Yuanyuan;CHONG Zeyin;CHAI Liying;ZHAO Li;LU Yan;ZHU Guoding;CAO Jun;LU Guangyu(School of Public Health,Medical College of Yangzhou University,Yangzhou,Jiangsu 225007,China;National Health Commission of Key Laboratory for Parasitic Disease Prevention and Control,Jiangsu Provincial Key Laboratory on Parasite and Vector Control Technology,Jiangsu Institute of Parasitic Diseases,Nanjing,Jiangsu 211166,China;Health and Quarantine Office,Nanjing Customs,Nanjing,Jiangsu 211166,China;Center for Global Health,School of Public Health,Nanjing Medical University,Nanjing,Jiangsu 211166,China;Jiangsu Key Laboratory of Zoonoses,Yangzhou University,Yangzhou,Jiangsu 225007,China)

机构地区：[1]扬州大学公共卫生学院,江苏扬州225007 [2]国家卫生健康委员会寄生虫病预防和控制技术重点实验室,江苏省寄生虫与媒介控制技术重点实验室,江苏省血吸虫病防治研究所,江苏南京211166 [3]南京海关卫生检疫处,江苏南京211166 [4]南京医科大学公共卫生学院全球健康中心,江苏南京211166 [5]江苏省人兽共患病学重点实验室,江苏扬州225007

出　　处：《中国热带医学》2025年第1期9-14,共6页China Tropical Medicine

基　　金：国家自然科学基金面上项目(No.72374178,No.71904165);国家卫生健康委员会寄生虫病预防与控制技术重点实验室/江苏省寄生虫与媒介控制技术重点实验室开放课题(No.wk023-007);江苏省博士后科研基金(No.2020Z003);江苏省研究生科研与实践创新计划项目(No.KYCX22-3572,No.KYCX23-3625)。

摘　　要：目的分析江苏省输入性疟疾时空流行特征及热点地区的分布变化规律,为识别输入性疟疾高风险输入区域,防止疟疾输入再传播提供科学依据。方法在中国疾病预防控制中心传染病报告信息管理系统和寄生虫病防治信息管理系统中,收集2016—2022年江苏省各县区报告的输入性疟疾病例数据。在国家地理信息测绘局获取江苏省县域电子矢量地图数据。利用ArcGIS 10.7软件,在县级区域尺度上绘制江苏省输入性疟疾病例分布专题地图并进行全局和局部自相关分析,探索疟疾输入热点县区时空变化规律。结果2016—2022年,江苏省77个县区(81.05%,77/95)报告输入性疟疾病例1189例。空间自相关分析显示仅2020年存在空间聚集性(Moran′s I=0.46,Z=4.37,P<0.01);局部空间自相关分析发现2016—2022年均存在热点县区共计60个,其中23个分布在苏中地区(38.33%),20个分布在苏南地区(33.33%),17个分布在苏北地区(28.33%)。部分热点县区的分布具有连续性,如南通市所辖的崇川区2016—2021年均作为热点县区重复出现。2020年以来,苏北及苏南地区出现新发且重复出现的热点县区,分别为连云港市所辖的赣榆区及南京市所辖的溧水区。结论江苏省输入性疟疾分布存在时空聚集性,热点县区的分布具有连续性。加强维持新发及连续出现的热点县区的输入性疟疾的监测与响应能力,对于维护当前疟疾消除成果,防止疟疾输入再传播至关重要。Objective To identify the temporal-spatial distribution patterns and changing of hotspot areas of malaria importations,and high-risk importation areas for imported malaria in Jiangsu Province,in order to provide the scientific evidence for prevention of malaria reintroduction in China.Methods Cases with imported malaria in Jiangsu Province from 2016 to 2022 were accessed from the National Notifiable Disease Report System and the Information Management System for Parasitic Disease Control in China.The county-level vector map of Jiangsu Province was obtained from the National Fundamental Geographic Information System,China.ArcGIS 10.7 software was utilized to create a thematic map depicting the distribution of imported malaria cases in Jiangsu Province at the county level.Global and local autocorrelation analysis was then conducted to investigate the spatiotemporal changes in malaria import hotspot counties.Results There were a total of 1189 cases with imported malaria reported in 77 counties(81.05%,77/95)of Jiangsu Province from 2016 to 2022.The global spatial autocorrelation analysis showed that a global spatial cluster of imported malaria in Jiangsu was only identified in 2020(Moran's I=0.46,Z=4.37,P<0.01),but local spatial autocorrelation analysis found that a total 60 hotspot counties existed from 2016 to 2022.There are 23 counties in central Jiangsu(38.33%),and 20 counties in southern Jiangsu(33.33%),17 counties in northern Jiangsu(28.33%).The distribution of hotspot counties exhibits continuity.For instance,Chongchuan District,which falls under the jurisdiction of Nantong City,has consistently emerged as a hotspot county for 2016-2021.Since 2020,two recurring hotspot counties emerged in northern Jiangsu and southern Jiangsu.These counties are Ganyu District,under the jurisdiction of Lianyungang City,and Lishui District,under the jurisdiction of Nanjing City.Conclusions The spatial-temporal cluster of cases with imported malaria was identified at the county level in Jiangsu,that hotspot counties were consiste

关 键 词：输入性疟疾 时空分布 空间自相关 热点分析 疾病监测 江苏 

分 类 号：R531[医药卫生—内科学]