摘要
本文收集铜陵地区2020年1月25日至2020年2月29日防控卡口人口流动数据、全国卫健委公布的疫情数据、互联网公开数据,采用层次分析法、Fisher最优分割、线性回归模型等方法构建人员输入性流动量、本地的确诊病例数、疑似病例数、人口密度等疫情影响因素的量化指标,建立Cox风险模型统计分析铜陵地区41个乡镇连续13天的新冠肺炎疫情风险指数,评估风险等级并可视化风险,给出风险分级分区精准防控的具体建议,为疫情分级分区精准防控提供方法上的参考。
This paper collects data of the population mobility at the prevention and control checkpoint in Tongling,the National Health and Health Commission and Internet from January 25,2020 to February 29,2020.The Analytic Hierarchy Process,Fisher Optimal Segmentation and Linear Regression were used to structure quantitative indicators of the input population,local confirmed cases,suspected cases and population density.Cox proportional risk model was used to analyze the risk indicators of COVID-19 epidemic in 41 towns and townships in Tongling for 13 consecutive days.The risk level was assessed by the model,and some suggestions of precise disease prevention were propused.Our results can provide a method reference for accurate prevention and control of epidemic situation.
作者
郜文灿
蒋剑军
王福成
齐平
王晨辉
GAO Wencan;JIANG Jianjun;WANG Fucheng;QI Ping;WANG Chenhui(Mathematics and Computer College of Tongling University,Tongling,China,244000)
出处
《福建电脑》
2020年第10期22-25,共4页
Journal of Fujian Computer
基金
安徽省重点研究与开发计划项目(No.202004a05020010)
2020年国家级大学生创新创业训练计划项目(No.202010383061)资助。
关键词
COX风险模型
新冠肺炎疫情
风险指数
风险等级
疫情防控
Cox Regression Model
COVID-19 epidemic
Risk Index
Risk Level
Disease Prevention and Control
