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社会经济环境及其与中国大陆 COVID-19 初始传播的相互作用的影响。

Impact of socio-economic environment and its interaction on the initial spread of COVID-19 in mainland China.

机构信息

School of Geography and Ocean Science, Nanjing University, Nanjing; Collaborative Innovation Centre of South China Sea Studies, Nanjing University.

School of Geography and Ocean Science, Nanjing University, Nanjing.

出版信息

Geospat Health. 2022 Mar 18;17(s1). doi: 10.4081/gh.2022.1060.

DOI:10.4081/gh.2022.1060
PMID:35735947
Abstract

Coronavirus disease 2019 (COVID-19) has strongly impacted society since it was first reported in mainland China in December 2020. Understanding its spread and consequence is crucial to pandemic control, yet difficult to achieve because we deal with a complex context of social environment and variable human behaviour. However, few efforts have been made to comprehensively analyse the socio-economic influences on viral spread and how it promotes the infection numbers in a region. Here we investigated the effect of socio-economic factors and found a strong linear relationship between the gross domestic product (GDP) and the cumulative number of confirmed COVID-19 cases with a high value of R2 (between 0.57 and 0.88). Structural equation models were constructed to further analyse the social-economic interaction mechanism of the spread of COVID-19. The results show that the total effect of GDP (0.87) on viral spread exceeds that of population influx (0.58) in the central cities of mainland China and that the spread mainly occurred through its interplay with other factors, such as socio-economic development. This evidence can be generalized as socio-economic factors can accelerate the spread of any infectious disease in a megacity environment. Thus, the world is in urgent need of a new plan to prepare for current and future pandemics.

摘要

2019 年冠状病毒病(COVID-19)自 2020 年 12 月在中国大陆首次报告以来,对社会产生了强烈影响。了解其传播和后果对于控制大流行至关重要,但由于我们应对复杂的社会环境和多变的人类行为背景,因此难以实现。然而,我们很少努力全面分析社会经济因素对病毒传播的影响,以及它如何在一个地区促进感染人数的增加。在这里,我们调查了社会经济因素的影响,发现国内生产总值(GDP)与确诊的 COVID-19 病例累计数量之间存在很强的线性关系,R2 值很高(在 0.57 到 0.88 之间)。构建了结构方程模型,以进一步分析 COVID-19 传播的社会经济互动机制。结果表明,GDP(0.87)对病毒传播的总效应超过了中国内地中心城市人口流入(0.58)的效应,并且传播主要通过与其他因素(如社会经济发展)的相互作用发生。这一证据可以概括为社会经济因素可以加速大都市环境中任何传染病的传播。因此,世界迫切需要一个新的计划来为当前和未来的大流行做准备。

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