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基于时空统计方法分析温州市2020年1~3月新型冠状病毒肺炎的聚集性分布
引用本文:刘利利,贾艳,齐畅,朱雨辰,李春雨,佘凯丽,刘廷轩,李秀君.基于时空统计方法分析温州市2020年1~3月新型冠状病毒肺炎的聚集性分布[J].山东大学学报(医学版),2020,58(10):82-88.
作者姓名:刘利利  贾艳  齐畅  朱雨辰  李春雨  佘凯丽  刘廷轩  李秀君
作者单位:山东大学齐鲁医学院公共卫生学院生物统计学系, 山东 济南 250012
基金项目:山东大学新冠肺炎应急攻关科研专项(2020XGC01);国家自然科学基金(81673238);国家重点研发计划(2019YFC1200500,2019YFC1200502)
摘    要:目的 通过时空统计分析探索温州市新型冠状病毒肺炎(COVID-19)的时空分布特征,为政府制定相应的防控策略提供理论依据。 方法 收集2020年1月21日至3月1日温州市12个县区武汉返温病例与接触过确诊患者的本地继发COVID-19病例疫情监测资料进行分析,运用ArcGIS 10.5制作发病数地图进行可视化,利用SaTScan 9.6进行时空聚类分析,比较武汉返温病例与本地继发病例的时空分布特征并分析本地继发病例聚集的原因。 结果 截至2020年3月1日,温州市COVID-19累计发病数为504例,发病率为6.08/10万。累计出院数为447例,其中武汉返温病例为168例,接触过COVID-19确诊患者的本地继发病例为221例,两类病例时空聚类分析结果均存在明显时空聚集性,聚类结果基本一致,主要聚集区为乐清市、瑞安市与永嘉县。 结论 温州市COVID-19发生存在时空聚集性,武汉返温人员较多的县区,本地继发病例相对较多。因此,有关部门应针对性加强武汉返温病例重点聚集区的防控与人员管理,加强来温人员排查和服务工作,降低一切可能导致疾病发生的风险。

关 键 词:新型冠状病毒肺炎  时空聚类  空间分析  空间流行病学  温州市  

Clustering distribution of COVID-19 in Wenzhou from January to March 2020 based on spatiotemporal analysis
LIU Lili,JIA Yan,QI Chang,ZHU Yuchen,LI Chunyu,SHE Kaili,LIU Tingxuan,LI Xiujun.Clustering distribution of COVID-19 in Wenzhou from January to March 2020 based on spatiotemporal analysis[J].Journal of Shandong University:Health Sciences,2020,58(10):82-88.
Authors:LIU Lili  JIA Yan  QI Chang  ZHU Yuchen  LI Chunyu  SHE Kaili  LIU Tingxuan  LI Xiujun
Institution:Department of Biostatistics, School of Public Health, Cheeloo College of Medicine, Shandong University, Jinan 250012, Shandong, China
Abstract:Objective To explore the spatiotemporal distribution of COVID-19 in Wenzhou and to provide theoretical basis for the formulation of preventive and control measures. Methods The epidemic data of COVID-19 cases returning from Wuhan and local secondary cases who contacted with the confirmed cases from 21 January 2020 to 1 March 2020 were collected and analyzed. ArcGIS 10.5 was used to produce a map of the number of cases. Spatiotemporal clustering analysis was performed with SaTScan 9.6 to explore the epidemic characteristics of returning and local cases and to investigate the causes of local cases. Results As of 1 March 2020, the cumulative number of COVID-19 cases was 504, with an incidence of 6.08/100 000. The cumulative number of discharged cases was 447. Of all cases, 168 returned from Wuhan and 221 local secondary cases contacted with the confirmed cases. The spatial-temporal cluster analysis of the two types of cases showed obvious clustering, and the clustering results were basically consistent. Clusters occurred mainly in Yueqing City, Ruian City and Yongjia County. Conclusion There is a spatialtemporal aggregation of COVID-19 in Wenzhou. Counties with more COVID-19 cases returning from Wuhan had more local secondary cases. Prevention and control measures should be taken especially in regions where a large number of people migrated to reduce the risk of COVID-19.
Keywords:Coronavirus disease 2019  Spatiotemporal clustering  Spatial analysis  Space epidemiology  Wenzhou City  
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