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审视人类流动与新冠疫情健康结果方面种族/族裔差异的时空演变:来自美国本土的证据

Examining spatiotemporal evolution of racial/ethnic disparities in human mobility and COVID-19 health outcomes: Evidence from the contiguous United States.

作者信息

Hu Songhua, Xiong Chenfeng, Younes Hannah, Yang Mofeng, Darzi Aref, Jin Zhiyu Catherine

机构信息

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

Shock Trauma and Anesthesiology Research (STAR) Center, School of Medicine, University of Maryland, Baltimore, United States.

出版信息

Sustain Cities Soc. 2022 Jan;76:103506. doi: 10.1016/j.scs.2021.103506. Epub 2021 Oct 29.

Abstract

Social distancing has become a key countermeasure to contain the dissemination of COVID-19. This study examined county-level racial/ethnic disparities in human mobility and COVID-19 health outcomes during the year 2020 by leveraging geo-tracking data across the contiguous US. Sets of generalized additive models were fitted under cross-sectional and time-varying settings, with percentage of mobility change, percentage of staying home, COVID-19 infection rate, and case-fatality ratio as dependent variables, respectively. After adjusting for spatial effects, built environment, socioeconomics, demographics, and partisanship, we found counties with higher Asian populations decreased most in travel, counties with higher White and Asian populations experienced the least infection rate, and counties with higher African American populations presented the highest case-fatality ratio. Control variables, particularly partisanship and education attainment, significantly influenced modeling results. Time-varying analyses further suggested racial differences in human mobility varied dramatically at the beginning but remained stable during the pandemic, while racial differences in COVID-19 outcomes broadly decreased over time. All conclusions hold robust with different aggregation units or model specifications. Altogether, our analyses shine a spotlight on the entrenched racial segregation in the US as well as how it may influence the mobility patterns, urban forms, and health disparities during the COVID-19.

摘要

社交距离已成为遏制新冠病毒传播的关键对策。本研究利用美国本土的地理追踪数据,调查了2020年县级层面人类流动情况以及新冠疫情健康结果方面的种族/族裔差异。在横断面和随时间变化的设定下,分别拟合了多组广义相加模型,将流动变化百分比、居家百分比、新冠病毒感染率和病死率作为因变量。在对空间效应、建成环境、社会经济状况、人口统计学特征和党派倾向进行调整后,我们发现亚洲人口比例较高的县出行减少最多,白人和亚洲人口比例较高的县感染率最低,非裔美国人人口比例较高的县病死率最高。控制变量,尤其是党派倾向和教育程度,对建模结果有显著影响。随时间变化的分析进一步表明,人类流动方面的种族差异在疫情初期变化巨大,但在疫情期间保持稳定,而新冠疫情结果方面的种族差异总体上随时间有所减少。所有结论在不同的汇总单位或模型设定下都很稳健。总之,我们的分析突出了美国根深蒂固的种族隔离现象,以及它在新冠疫情期间可能如何影响流动模式、城市形态和健康差异。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c5c9/8639208/6a48b22e4f6a/gr1_lrg.jpg

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