摘要
目的·探讨中国各省级行政区新型冠状病毒肺炎(coronavirus disease 2019,COVID-19)疫情早期的关联模式,并预测之后的疫情发展。方法·回顾性分析2020年1月13日—2月13日中华人民共和国国家卫生健康委员会公布的关于全国各省级行政区COVID-19疫情的数据,采用肘聚类分析法对全国各省级行政区进行聚类分析,利用SEIR(susceptible-exposed-infectious-recovered)模型计算不同聚集区基本传染数(R0),预测各类聚集区疫情变化趋势。结果·根据患病率从低到高将全国34个省级行政区分为4类聚集区:Ⅰ类聚集区(22个省级行政区)、Ⅱ类聚集区(9个省级行政区)、Ⅲ类聚集区(2个省级行政区)、Ⅳ类聚集区(湖北)。湖北的患病率显著高于其他3类聚集区(P=0.000),但各类聚集区之间的治愈率和病死率差异无统计学意义。4类聚集区的R0值分别为2.764、3.056、3.899、3.984。截至2020年2月13日,除湖北外,其他聚集区的累积患病率曲线趋于平稳,治愈率曲线上升;湖北的患病率和病死率仍较高,治愈率较低。结论·2020年1月13日—2月13日,中国34个省级行政区根据COVID-19疫情严重程度可分为4类,Ⅳ类聚集区的患病率显著高于其他3类聚集区;且截至2020年2月13日,Ⅰ、Ⅱ、Ⅲ类聚集区疫情有所缓解,Ⅳ类聚集区疫情仍较为严峻。
Objective·To explore the correlation patterns of the new coronavirus disease 2019(COVID-19)epidemic in various provincial administrative regions in China at the early stage of the epidemic,and forecast the following development of epidemic situation.Methods·The data on the COVID-19 epidemic situation in various provincial administrative regions in China published by National Health Commission of People's Republic of China from Jan.13 to Feb.13,2020,were retrospectively analyzed.The elbow cluster analysis method was used to cluster the provincial administrative regions.The SEIR(susceptible-exposed-infectious-recovered)model was used to calculate the basic infection number(R0)of different clusters,whose changing trends were also predicted.Results·According to the prevalence rates,the 34 provincial administrative regions were divided into four types of clusters:ClusterⅠ(22 provincial administrative regions),ClusterⅡ(9 provincial administrative regions),ClusterⅢ(2 provincial administrative regions)and ClusterⅣ(Hubei).The prevalence rate of Hubei was higher than those of other clusters(P=0.000),but the differences in the cure rate and the case-fatality rate among the four clusters were not statistically significant;the R0 values based on the SEIR model of them were 2.764,3.056,3.899 and 3.984,respectively.By Feb.13,2020,except for Hubei,the cumulative prevalence curves of the other clusters tended to be stable and the cure rates increased.The prevalence rate and case-fatality rate of Hubei were still higher,and the cure rate was lower.Conclusion·From Jan.13 to Feb.13,2020,34 provincial administrative regions in China can be divided into four clusters according to the severity of the COVID-19 epidemic,and the prevalence rate of ClusterⅣwas significantly higher than those of other three clusters;by Feb.13,2020,the epidemic situations in the ClusterⅠ,ⅡandⅢhas been alleviated,and the epidemic situation in ClusterⅣareas were still severe.
作者
李蔷
孙喆
钱碧云
冯铁男
LI Qiang;SUN Zhe;QIAN Bi-yun;FENG Tie-nan(Shanghai Jiao University School of Public Health,Shanghai 200025,China;Clinical Research Institute,Shanghai Jiao Tong University School of Medicine,Shanghai 200025,China;Clinical Research Promotion and Development Center,Shanghai Shenkang Hospital Development Center,Shanghai 200041,China;Second Affiliated Hospital of Chengdu Medical College,China National Nuclear Corporation 416 Hospital,Chengdu 610057,China)
出处
《上海交通大学学报（医学版）》
CAS
CSCD
北大核心
2020年第6期713-718,共6页
Journal of Shanghai Jiao tong University:Medical Science
基金
上海交通大学医工交叉项目(YG2017QN70)
上海交通大学医学院科技处技术转移项目(ZT201919)。
关键词
新型冠状病毒肺炎
肘聚类分析
SEIR模型
回顾性分析
coronavirus disease 2019(COVID-19)
elbow cluster analysis
SEIR(susceptible-exposed-infectious-recovered)model
retrospective analysis
