人口流动与新冠病毒传播——基于向量自回归模型的实证分析

Population mobility and the spread of COVID-19 An empirical analysis based on Vector Autoregressive Model

利用美国2020年1月22日至8月16日的人口流动指数与COVID-19感染人数增长率数据,构建向量自回归模型,系统分析人口流动与新冠病毒传播之间的内在关联。结果表明:驾车出行指数、乘坐公共交通出行指数和步行出行指数分别与COVID-19感染人数增长率之间具有长期均衡关系;观察期间乘坐公共交通出行指数和步行出行指数对COVID-19感染人数增长率的累积效应为正,驾车出行指数对COVID-19感染人数增长率的累积效应为负。因此,控制城市公共交通和步行出行的防控措施有助于拉平“疫情曲线”,鼓励居民选择私家车出行可以减弱新冠病毒传播的风险和趋势。新冠病毒传播在一定程度上对人口流动的变化产生影响,但人口流动的变化主要受其自身的影响,即驾车出行指数、乘坐公共交通出行指数和步行出行指数均具有明显的正反馈作用。

This paper uses the population mobility index and the growth rate of COVID-19 infections in the United States from January 22nd to August 16th,2020 to construct a Vector Autoregressive Model and systematically analyzes the internal relationship between population mobility and the spread of COVID-19.The results show that there is a long-term equilibrium relationship among driving index,public transport index and walking index and the growth rate in the number of COVID-19 infection respectively.It is observed that the cumulative effect of public transport and walking index on the growth rate of COVID-19 in-fection is positive,and the cumulative effect of driving index on that is negative.Therefore,the prevention and control measures of urban public transport and walking helps to flatten the“epidemic curve”,and driving can also reduce the risks and slow trend of the spread of COVID-19.To some extent,the spread of COVID-19 has an impact on changes in population mobility,but the changes in population mobility are mainly affected by itself,that is,the driving index,public transport index and walking index all have obvious positive feedback effects.