摘要
基于网上公开数据,本文采用主成分分析方法研究中国累计确诊人数与密切接触者、疑似者关系.当前境外输入性病例明显增多,防境外输入已经成为我国疫情防控重点.本文通过聚类分析方法研究各国当前2019新型冠状病毒肺炎疫情发展严重程度,将国外新冠疫情国家分为3类:主要疫区、重点疫区、分散疫区,其中意大利属于主要疫区,伊朗、西班牙、法国、德国、美国属于重点疫区,日本、马来西亚等国属于分散疫情区.我国边检可根据风险等级对出入境人员进行分批次检查和严格检测,并做好输入病例的追踪管理工作.通过对境外疫情的研究,预测各国风险等级,以期为疫情防控工作提供依据.
Based on publicly available data online,this article uses the principal component analysis method to study the relationship between the cumulative number of confirmed diagnoses and close contacts and suspects in China.At present,the number of imported diseases has increased significantly,and prevention of imported diseases has become the focus of epidemic prevention and control in China.This paper uses cluster analysis to study the severity of the 2019 novel coronavirus pneumonia epidemic in various countries,and divides foreign countries with novel coronavirus pneumonia epidemic into three categories:major epidemic areas,key epidemic areas,and scattered epidemic area,of which Italy belongs to the main epidemic area,Iran,Spain,France,Germany,and The United States belong to key epidemic area,Japan,Malaysia and other countries are scattered epidemic areas.According to the risk level,China’s border inspection can conduct batch inspection and strictly detect of entry and exit personnel,and do a good job of tracking and managing imported cases.Through the study of overseas epidemics,the risk levels of various countries are predicted in order to provide a basis for China’s epidemic prevention and control work.
作者
郑丽晖
陈建宝
陈晓平
ZHENG Lihui;CHEN Jianbao;CHEN Xiaoping(College of Mathematics and Informatics and FJKLMAA,Fujian Normal University,Fuzhou 350117,China)
出处
《应用数学学报》
CSCD
北大核心
2020年第2期324-334,共11页
Acta Mathematicae Applicatae Sinica
基金
国家自然科学基金“不完全数据下半参数单调转移模型的统计推断及其应用”(11601083)
福建省自然科学基金“新型冠状病毒感染的肺炎流行规律和病原学特征研究”(2020Y0005)资助项目.
关键词
COVID-19
确诊人数
风险预测
多元统计分析
COVID-19
number of confirmed diagnoses
risk prediction
multivariate statistical analysis
