摘要
利用手机定位大数据识别和监测新冠肺炎高危人群,既是流行病学调查方法的创新,也是疫情防控的重要支撑.本文聚焦于构造基于手机定位大数据的捕获再捕获模型,估计特定区域新冠肺炎传染高危人群总量,并利用互联网企业提供的,经脱敏处理的天津市手机APP定位大数据验证了方法的实践有效性.数据分析结果显示,2020年1月24日至1月31日期间天津每日传染高危人群规模约为12500人.本文的研究为当前疫情防控与复产复工中传染高风险人群的识别与监测提供了大数据方法支持.
Using mobile phone positioning big data to infer the characteristics of population activities,identify and monitor high-risk groups of new coronary pneumonia is not only an innovation of epidemiological investigation methods,but also an important support for epidemic prevention and control.This paper focuses on constructing a capture and recapture model based on mobile phone positioning big data,estimating the total number of high-risk groups of COVID-19 infection in a specific region.Taking Tianjin positioning big data with apps as an example,the method is verified to be effective in practice.Results from data analysis show that from January 24 to January 31,2020,the scale of daily high-risk groups in Tianjin was about 13,500.The value of the research lies in the fact that it not only clarifies the key directions for the identification and monitoring of high-risk contagious people in the current epidemic prevention and control, and resumes production,, but also provides big data method support for the future construction of a major epidemic prevention and control system in China.The research in this paper provides big data method support for the identification and monitoring of high-risk groups infectious in the current epidemic prevention and control and resumption of production.
作者
孟杰
杨贵军
乔婷婷
刘全利
MENG JIE;YANG Guijun;QIAO Tingting;LIU Quanli(School of Statistics,Tianjin University of Finance and Economics,Tianjin 300222,China;Big Data Laboratory of Population Statistics,Intelli Global Corporation Limited-Tianjin University of Finance and Economics,Tianjin 300222,China)
出处
《应用数学学报》
CSCD
北大核心
2020年第2期251-264,共14页
Acta Mathematicae Applicatae Sinica
基金
国家社科基金(17CTJ002)
国家自然科学基金(11471239)资助项目.
关键词
传染高危人群
捕获再捕获模型
手机定位大数据
COVID-19
Capture-Recapture Model
Phone Positioning Big Data multivariate statistical analysis
作者简介
通讯作者:孟杰,E-mail:mengjie0919@sina.com。
