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河南省新型冠状病毒肺炎时空聚集性
引用本文:张延炀,肖占沛,杨凯朝,赵东阳,李军,张明瑜,张肖肖,马雅婷,王长双,王燕,陈帅印.河南省新型冠状病毒肺炎时空聚集性[J].中华疾病控制杂志,2020,24(5):534-538.
作者姓名:张延炀  肖占沛  杨凯朝  赵东阳  李军  张明瑜  张肖肖  马雅婷  王长双  王燕  陈帅印
作者单位:1.450016 郑州, 河南省疾病预防控制中心免疫预防规划所
基金项目:新型冠状病毒感染肺炎流行病学规律及防控措施研究
摘    要:   目的   利用地理信息系统(geographic information systems, GIS)探索河南省新型冠状病毒肺炎(coronavirus disease 2019, COVID-19)空间分布规律。   方法   收集河南省新型冠状病毒肺炎报告数据, 建立GIS数据库, 应用空间相关分析软件(GeoDa 1.8.12)和时空扫描软件(SaTScan 9.4)对数据进行空间自相关分析和时空扫描统计分析。   结果   河南省COVID-19存在空间聚集性; 5个时段共探测到50个高-高聚集区; 时空扫描统计分析共识别到5个时空聚集区。   结论   河南省COVID-19传播风险经历了弱-强-弱的变化过程, 采取的应急防控策略不但阻止了疫情在时间上的增长, 还有效遏止了其在空间上的扩散。

关 键 词:新型冠状病毒肺炎    时空统计    空间分析    地理信息系统
收稿时间:2020-03-04

Study on the spatiotemporal clusters of coronavirus disease 2019 in Henan Province
Institution:1.Immunization Planning Institute, Henan Provincial Center for Disease Control and Prevention, Zhengzhou 4500J6, ChinaHenan Provincial Center for Disease Control and Prevention, Zhengzhou 450016, ChinaDepartment of Epidemiology, School of Public Health, Zhengzhou University, Zhengzhou 450001, China
Abstract:   Objective   To explore the spatiotemporal distribution pattern of coronavirus disease 2019(COVID-19) in Henan Province using geographic information systems(GIS).   Methods   Epidemiological data of COVID-19 were collected, and relevant GIS data bases were established. The global and local indicators of spatial autocorrelation analysis was carried out by GeoDa 1.8.12 software, and SaTScan 9.4 software was used to describe the spatiotemporal scan statistics.   Results   A total of 50 regions of high-high aggregation by local spatial association analysis observed in in Henan Province; five statically significant COVID-19 clusters were identified by the retrospective spatiotemporal scan.   Conclusions   The risk of COVID-19 transmission in Henan Province has experienced a process: from weak to strong, then to weak. The emergency strategies not only prevent the growth in time, but also effectively prevent its spread in space.
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