基于空间计量的COVID-19区域分布影响因素分析

Analysis of Influencing Factors of Covid-19 Regional Distribution Based on Spatial Measurement

2020年初,COVID-19爆发席卷全国,根据2022年底的新冠疫情实时大数据显示,从全国的COVID-19患者累计数量空间分布情况来看,各省确诊的COVID-19患者数与区域经济发育度呈正相关,长三角和大湾区等沿海区域经济发育度越高,COVID-19患者的确诊率越高,这些经济重镇因疫情反弹,区域产业均受到严重冲击。城市及区域总人口基数越高,确诊的新冠病例比例越小,两者呈负相关。沿海发达经济带的COVID-19发病率与确诊数量均存在正向空间自相关,具体表现在接触大都市圈的人群更易患新冠肺炎,存在显著的正向空间溢出效应,佐证了COVID-19的发病率会对区域经济环境造成负向影响。研究分析发现,空间杜斌模型优于普通最小二乘回归模型,为后续COVID-19确诊病例的累计数的开展有效的空间统计分析提供了理论支撑。

At the beginning of 2020, the outbreak of COVID-19 swept the country. According to the COVID-19real time big data at the end of 2022, the number of COVID-19 patients in the province was positively correlated with the regional economic development from the cumulative spatial distribution of COVID-19 patients in the whole country. The higher the economic development of the coastal areas such as the Yangtze River Delta and the Greater Bay area, the higher the diagnostic rate of COVID-19 patients. Regional industries have been seriously impacted. The higher the total population base of cities and regions, the smaller the proportion of newly diagnosed coronavirus cases, and the two are negatively correlated. However, in the past two years,with the repeated changes of COVID-19, there are many characteristics such as long incubation period, strong infectivity and wide spread of the epidemic. COVID-19 It is found that the spatial Dubin model is better than the ordinary least squares regression model, which provides theoretical support for the effective spatial statistical analysis of the cumulative number of subsequent covid-19 confirmed cases.