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美国 COVID-19 大流行早期的人口流动趋势。

Human mobility trends during the early stage of the COVID-19 pandemic in the United States.

机构信息

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

出版信息

PLoS One. 2020 Nov 9;15(11):e0241468. doi: 10.1371/journal.pone.0241468. eCollection 2020.


DOI:10.1371/journal.pone.0241468
PMID:33166301
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC7652287/
Abstract

In March of this year, COVID-19 was declared a pandemic, and it continues to threaten public health. This global health crisis imposes limitations on daily movements, which have deteriorated every sector in our society. Understanding public reactions to the virus and the non-pharmaceutical interventions should be of great help to fight COVID-19 in a strategic way. We aim to provide tangible evidence of the human mobility trends by comparing the day-by-day variations across the U.S. from January 2020 to early April 2020. Large-scale public mobility at an aggregated level is observed by leveraging mobile device location data and the measures related to social distancing. Our study captures spatial and temporal heterogeneity as well as the sociodemographic variations and teleworking trends regarding the pandemic propagation and the non-pharmaceutical mobility interventions. All metrics adapted capture decreased public movements after the national emergency declaration. The population staying home has increased in all states before the stay-at-home mandates implemented and becomes more stable after the order with a smaller range of fluctuation. The public had been taking active responses, voluntarily staying home more, to the in-state confirmed cases while the stay-at-home orders stabilize the variations. As the estimated teleworking rates also continue to incline throughout the study period, the teleworking trend can be another driving factor for the growing stay-at-home population. We confirm that there exists overall mobility heterogeneity between the income or population density groups. The study suggests that public mobility trends are in line with the government message urging to stay home. We anticipate our data-driven analysis offers integrated perspectives and serves as evidence to raise public awareness and, consequently, reinforce the importance of social distancing while assisting policymakers.

摘要

今年 3 月,COVID-19 被宣布为大流行,它继续威胁着公共健康。这场全球卫生危机对日常行动造成了限制,使我们社会的各个部门都受到了影响。了解公众对病毒的反应以及非药物干预措施应该有助于我们以战略方式抗击 COVID-19。我们旨在通过比较 2020 年 1 月至 2020 年 4 月初美国每天的变化,为人类流动趋势提供切实的证据。通过利用移动设备位置数据和与社会隔离相关的措施,可以观察到大规模的公共移动。我们的研究捕捉到了空间和时间异质性以及与大流行传播和非药物流动性干预措施相关的社会人口变化和远程工作趋势。所有适应的指标都表明,在宣布国家紧急状态后,公众的流动减少了。在实施居家令之前,所有州的居家人数都有所增加,并且在命令实施后变得更加稳定,波动范围更小。公众对州内确诊病例采取了积极的反应,自愿更多地待在家里,而居家令则稳定了变化。随着在整个研究期间估计的远程工作率也继续上升,远程工作趋势可能是在家人数不断增加的另一个驱动因素。我们确认,收入或人口密度群体之间存在整体流动性异质性。该研究表明,公众的流动趋势与政府敦促民众留在家中的信息一致。我们预计,我们的数据驱动分析将提供综合观点,并作为证据,提高公众意识,从而在协助政策制定者的同时,加强社会隔离的重要性。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9d1c/7652287/3dafe6824516/pone.0241468.g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9d1c/7652287/90aec2f7d1ff/pone.0241468.g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9d1c/7652287/c80bbc7f63a4/pone.0241468.g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9d1c/7652287/9f28db302e26/pone.0241468.g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9d1c/7652287/64f1c30fc090/pone.0241468.g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9d1c/7652287/63e2793b26ce/pone.0241468.g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9d1c/7652287/65082554ae16/pone.0241468.g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9d1c/7652287/97f9bf55d7a9/pone.0241468.g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9d1c/7652287/3dafe6824516/pone.0241468.g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9d1c/7652287/90aec2f7d1ff/pone.0241468.g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9d1c/7652287/c80bbc7f63a4/pone.0241468.g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9d1c/7652287/9f28db302e26/pone.0241468.g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9d1c/7652287/64f1c30fc090/pone.0241468.g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9d1c/7652287/63e2793b26ce/pone.0241468.g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9d1c/7652287/65082554ae16/pone.0241468.g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9d1c/7652287/97f9bf55d7a9/pone.0241468.g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9d1c/7652287/3dafe6824516/pone.0241468.g008.jpg

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[10]
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本文引用的文献

[1]
Interactive COVID-19 Mobility Impact and Social Distancing Analysis Platform.

Transp Res Rec. 2023-4

[2]
Assessing the risks of 'infodemics' in response to COVID-19 epidemics.

Nat Hum Behav. 2020-10-29

[3]
Attitudes and Psychological Factors Associated With News Monitoring, Social Distancing, Disinfecting, and Hoarding Behaviors Among US Adolescents During the Coronavirus Disease 2019 Pandemic.

JAMA Pediatr. 2020-12-1

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Early epidemiological analysis of the coronavirus disease 2019 outbreak based on crowdsourced data: a population-level observational study.

Lancet Digit Health. 2020-2-20

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Science. 2020-4-14

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