影响新型冠状病毒肺炎省际传播与发展的因素:基于30个省市的数据分析

The influencing factors of interprovincial transmission and development of COVID-19:Data analysis based on 30 provinces and cities in China

目的探讨新型冠状病毒肺炎(新冠肺炎)省际传播与发展的影响因素,以期在重大传染病疫情暴发时,为各地区地域性防控策略的制定提供依据。方法回顾性收集截至2020年2月25日24时我国30个省市的新冠肺炎确诊病例数,各省市距湖北省的距离、武汉人口迁出比、GDP、人口密度、城镇人口数、交通客运量、旅客周转量等数据。以截至1月29日24时的以输入病例为主的累计确诊病例作为第一阶段病例集群,以1月30日0时至2月25日24时的以续发病例为主的累计新增确诊病例作为第二阶段病例集群,分别采用Pearson相关性分析与线性拟合回归评估人口迁徙、交通、经济等因素与新冠肺炎传播与发展的关联,在线性拟合回归中采用多因素最优子集模型方法筛选与各省市新冠肺炎关联最密切的影响因素。结果各省市距湖北省的距离,与以输入病例为主的第一阶段病例集群和以续发病例为主的第二阶段病例集群均呈负线性关联(t=-3.654、t=-3.679,P均<0.05)。武汉人口迁出比、GDP、城镇人口数、人口密度、交通客运量、旅客周转量,均与第一阶段、第二阶段病例集群呈正线性关联(t均>2.760,P均<0.05)。GDP、武汉人口迁出比与以输入病例为主的第一阶段病例集群关联最为密切(t=4.173、t=7.851,P均<0.05);第一阶段病例集群、武汉人口迁出比、城镇人口数与以续发病例为主的第二阶段病例集群关联最为密切(t=4.734、t=3.491、t=2.855,P均<0.05)。结论各省市GDP、武汉人口迁出比对以输入病例为主的疫情阶段影响最大;而输入病例、武汉人口迁出比、城镇人口数对以续发病例为主的疫情阶段影响最大。在以输入病例为主的疫情暴发初期,应考虑对高GDP和疫区迁出人口高比例地区,加强疫情防控力度,尽早、更加严格地限制该类地区的人口流动,有效遏制疫情的暴发;在以续发病例为主的疫情后期,应重点依据各省市的输入病例、自疫区人口迁出比、城镇人口数指标,分区域制定管制政策,合理限制人群接触,阻断疫情进一步发展。

Objective To explore the factors affecting the interprovincial transmission and development ofcoronavirus disease 2019 (COVID-19) in China, with a view to providing recommendations for the formulation of preventive and control measures according to the actual conditions in different regions during the outbreak of the severe infectious disease. Methods We collected the total number of confirmed cases of COVID-19 in 30 provinces and cities in China by the end of 24:00 February 25, 2020. Then we also collected the distance from each region to Hubei province, the proportion of population moving out from Wuhan city from January 1 to January 23, population density, urban population, traffic passenger volume, passenger turnover volume and other relevant data of each region.The cumulative confirmed cases including the most of imported cases by the end of 24:00 January 29, 2020 were taken as the first-stage cases cluster, and the cumulative newly confirmed cases including the most of secondary cases from 0:00 January 30 to 24:00 February 25, 2020 were taken as the second-stage cases cluster. Pearson bivariate correlation and linear fitting regression method were adopted to analyze the effects of population migration, transportation, economy and other factors on the transmission and development of COVID-19 in different regions. In the linear fitting regression, the multi-factor optimal subset model was used to screen the factors most closely related to COVID-19. Results The distance from each region to Hubei province was negatively correlated with the first-stage cases cluster with the most of imported cases and the second-stage cases cluster with the most of secondary cases( t =-3.654, t =-3.679, both P <0.05). The proportion of population moving out from Wuhan, GDP, urban population, traffic passenger volume, and passenger turnover volume were positively correlated with the first-stage and second-stage cases cluster (all t >2.760, all P <0.05). GDP and the proportion of population moving out from Wuhan were most closely related to the first-stage cases cluster with the most of imported cases ( t =4.173, t =7.851, all P <0.05). The first-stage cases cluster, the proportion of population moving out from Wuhan, and urban population were most closely related to the second-stage cases cluster with the most of secondary cases ( t =4.734, t =3.491, t =2.855, all P <0.05). Conclusion GDP and the proportion of population moving out from Wuhan city had the greatest impact on the stage with the most of imported cases. The imported cases, the proportion of population moving out from Wuhan and the urban population had the greatest impact on the stage with the most of secondary cases. In the early stage of epidemic outbreak with the most of imported cases,we should consider strengthening the prevention and control of the epidemic in areas with high level of GDP and high proportion of population moving out from the epidemic area.The flow of population should be restricted more strictly as soon as possible in order to effectively curb the outbreak of the epidemic.In the later-stage of epidemic with the most of secondary cases, regionalized control policies should be formulated mainly according to the indicators of imported cases, the population proportion fromtheepidemic area, and the urban population. Finally, the contact of population should be restricted reasonably to prevent further development of the epidemic.