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社交距离、流动性和预防政策如何影响 COVID-19 结果:来自哥伦比亚特区-马里兰州-弗吉尼亚州(DMV)大都市地区的大数据驱动证据。

How social distancing, mobility, and preventive policies affect COVID-19 outcomes: Big data-driven evidence from the District of Columbia-Maryland-Virginia (DMV) megaregion.

机构信息

Maryland Transportation Institute, Department of Civil and Environmental Engineering, University of Maryland, College Park, Maryland, United States of America.

Shock Trauma Anesthesiology Research Center, School of Medicine, University of Maryland, Baltimore, Maryland, United States of America.

出版信息

PLoS One. 2022 Feb 17;17(2):e0263820. doi: 10.1371/journal.pone.0263820. eCollection 2022.

Abstract

Many factors play a role in outcomes of an emerging highly contagious disease such as COVID-19. Identification and better understanding of these factors are critical in planning and implementation of effective response strategies during such public health crises. The objective of this study is to examine the impact of factors related to social distancing, human mobility, enforcement strategies, hospital capacity, and testing capacity on COVID-19 outcomes within counties located in District of Columbia as well as the states of Maryland and Virginia. Longitudinal data have been used in the analysis to model county-level COVID-19 infection and mortality rates. These data include big location-based service data, which were collected from anonymized mobile devices and characterize various social distancing and human mobility measures within the study area during the pandemic. The results provide empirical evidence that lower rates of COVID-19 infection and mortality are linked with increased levels of social distancing and reduced levels of travel-particularly by public transit modes. Other preventive strategies and polices also prove to be influential in COVID-19 outcomes. Most notably, lower COVID-19 infection and mortality rates are linked with stricter enforcement policies and more severe penalties for violating stay-at-home orders. Further, policies that allow gradual relaxation of social distancing measures and travel restrictions as well as those requiring usage of a face mask are related to lower rates of COVID-19 infections and deaths. Additionally, increased access to ventilators and Intensive Care Unit (ICU) beds, which represent hospital capacity, are linked with lower COVID-19 mortality rates. On the other hand, gaps in testing capacity are related to higher rates of COVID-19 infection. The results also provide empirical evidence for reports suggesting that certain minority groups such as African Americans and Hispanics are disproportionately affected by the COVID-19 pandemic.

摘要

许多因素在新发高度传染性疾病(如 COVID-19)的结果中发挥作用。在这些公共卫生危机期间,识别和更好地理解这些因素对于规划和实施有效的应对策略至关重要。本研究的目的是检验与社交距离、人口流动、执法策略、医院容量和检测能力相关的因素对哥伦比亚特区以及马里兰州和弗吉尼亚州各县 COVID-19 结果的影响。在分析中使用了纵向数据来模拟县级 COVID-19 感染和死亡率。这些数据包括基于大位置的服务数据,这些数据是从匿名移动设备中收集的,用于描述大流行期间研究区域内各种社交距离和人口流动措施。结果提供了经验证据,表明较低的 COVID-19 感染和死亡率与更高水平的社交距离和减少的旅行(尤其是通过公共交通模式)相关。其他预防策略和政策也被证明对 COVID-19 的结果有影响。最值得注意的是,更严格的执法政策和对违反居家令的更严厉处罚与较低的 COVID-19 感染和死亡率相关。此外,允许逐步放宽社交距离措施和旅行限制以及要求使用口罩的政策与较低的 COVID-19 感染和死亡人数相关。此外,增加呼吸机和重症监护病房(ICU)床位的供应,这代表医院容量,与较低的 COVID-19 死亡率相关。另一方面,检测能力的差距与 COVID-19 感染率较高相关。结果还为报告提供了经验证据,表明某些少数群体(如非裔美国人和西班牙裔)不成比例地受到 COVID-19 大流行的影响。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7f27/8853552/adfcb6bc9457/pone.0263820.g001.jpg

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