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Spatiotemporal heterogeneity and its determinants of COVID-19 transmission in typical labor export provinces of China

机译:中国典型劳工出口省份Covid-19传播的时空异质性及其决定因素

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Previous studies have indicated that the risk of infectious disease spread is greatest in locations where a population has massive and convenient access to the epicenter of an outbreak. However, the spatiotemporal variations and risk determinants of COVID-19 in typical labor export regions of China remain unclear. Understanding the geographical distribution of the disease and the socio-economic factors affecting its transmission is critical for disease prevention and control. A total of 2152 COVID-19 cases were reported from January 21 to February 24, 2020 across the 34 cities in Henan and Anhui. A Bayesian spatiotemporal hierarchy model was used to detect the spatiotemporal variations of the risk posed by COVID-19, and the GeoDetector q statistic was used to evaluate the determinant power of the potential influence factors. The risk posed by COVID-19 showed geographical spatiotemporal heterogeneity. Temporally, there was an outbreak period and control period. Spatially, there were high-risk regions and low-risk regions. The high-risk regions were mainly in the southwest areas adjacent to Hubei and cities that served as economic and traffic hubs, while the low-risk regions were mainly in western Henan and eastern Anhui, far away from the epicenter. The accessibility, local economic conditions, and medical infrastructure of Wuhan in Hubei province all played an important role in the spatiotemporal heterogeneity of COVID-19 transmission. The results indicated that the q statistics of the per capita GDP and the proportion of primary industry GDP were 0.47 and 0.47, respectively. The q statistic of the population flow from Wuhan was 0.33. In particular, the results showed that the q statistics for the interaction effects between population density and urbanization, population flow from Wuhan, per capita GDP, and the number of doctors were all greater than 0.8. COVID-19 showed significant spatiotemporal heterogeneity in the labor export regions of China. The high-risk regions were mainly located in areas adjacent to the epicenter as well as in big cities that served as traffic hubs. Population access to the epicenter, as well as local economic and medical conditions, played an important role in the interactive effects of the disease transmission.
机译:以前的研究表明,在人口大规模和方便地进入爆发的震中的地方,传染病的风险是最大的。然而,中国典型劳动力出口地区Covid-19的时空变化和风险决定簇仍然尚不清楚。了解疾病的地理分布和影响其传播的社会经济因素对疾病预防和控制至关重要。从1月21日至2月24日举行了2152份Covid-19案件,2020年2月24日在河南和安徽的34个城市。使用贝叶斯时空层次结构模型来检测Covid-19带来的风险的时空变化,地理传道Q统计器用于评估潜在影响因素的决定性力量。 Covid-19带来的风险显示了地理时滞的异质性。暂时,存在爆发期和控制期。在空间上,有高风险的地区和低风险地区。高风险地区主要是毗邻湖北和担任经济和交通枢纽的城市的西南地区,而低风险地区主要是位于河南西部和安徽省东部,远离震中。湖北省武汉的无障碍,地方经济条件和医疗基础设施在Covid-19传播的时空异质性中发挥着重要作用。结果表明,人均GDP的Q统计和主要产业GDP的比例分别为0.47和0.47。武汉人口流量统计为0.33。特别是,结果表明,Q统计人口密度与城市化与城市化之间的互动效应,人均GDP人均武汉人口流量和医生人数大于0.8。 Covid-19在中国的劳动力出口地区显示出显着的时尚异质性。高风险地区主要位于震中等地区以及作为交通枢纽的大城市。人口进入震中,以及地方经济和医疗条件,在疾病传播的互动影响中发挥着重要作用。

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