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面向COVID-19传播模式的多因素影响分析
引用本文:谭宏卫.面向COVID-19传播模式的多因素影响分析[J].数理统计与管理,2022,41(1):37-49.
作者姓名:谭宏卫
作者单位:贵州财经大学数统学院,贵州贵阳550025;贵州省大数据统计分析重点实验室,贵州贵阳550025
基金项目:贵州省教育厅创新群体项目(黔教合KY字[2021]015);贵州省大数据统计分析重点实验室(黔科合平台人才[2019]5103号).
摘    要:目前,新型冠状病毒肺炎(COVID-19)的传播仍在持续,其传播模式以及影响传播行为的主要因素仍有待深入挖掘。鉴于此,本文从数据分析的角度,通过构造一个特殊的多源数据集(包括COVID-19历史数据、气象数据、人口迁徙数据和空间地理信息数据),以此建立多元Poisson.回归模型(类Poisson回归)来着重分析国内疫情的病毒传播模式及其影响因素。分析结果显示,湿度、平均每日风速、每日的降雨量等气象因素与COVID-19的传播模式显著相关,但与每日温度变化显著不相关。除此之外,COVID-19的传播速度及传播范围与武汉迁出目的地的人口比例、迁入武汉来源地的人口比例以及武汉与其他城市的空间距离均有一定的关联性。全文可视化及模型分析的R代码见:https://github.com/thwgithub/COVID-19 Rcodes.

关 键 词:新型冠状病毒肺炎  多因素影响分析  可视化  Poisson回归模型

Multi-factor Influence Analysis for COVID-19 Transmission Patterns
TAN Hong-Wei.Multi-factor Influence Analysis for COVID-19 Transmission Patterns[J].Application of Statistics and Management,2022,41(1):37-49.
Authors:TAN Hong-Wei
Institution:(School of Mathematics and Statistics,Guizhou University of Finance and Economics,Guiyang 550025,China;Guizhou Key Laboratory of Big Data Statistical Analysis,Guiyang 550025,China)
Abstract:At present,COVID-19 is still spreading,and its transmission patterns and the main factors for affecting transmission behavior need to be further mined.To this end,from the perspective of data analysis,a multivariate Poisson regression model(Quasi-Poisson)based on an elaborate multi-source dataset(including COVID-19 historical data,meteorological data,population migration and spatial ge-ographic information data),is established,whice focuses on analyzing the transmission patterns and exploring some impact factors for the COVID-19 outbreak in China.The analysis results showed that meteorological factors such as humidity,average daily wind speed,and daily rainfall are significantly correlated with the transmission patterns of COVID-19,but not with the daily temperature change.In addition,the transmission speed and transmission range of COVID-19 are related to the proportion of the population for the destination of Wuhan out migration,the origin of in-migration Wuhun and the spatial distance between Wuhan and other cities.All of the R codes for this paper are available on the site https://github.com/thwgithub/COVID-19-Rcodes.
Keywords:COVID-19  mmulti-factor influence analysis  visualization  Poissoll regressiun udel
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