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Quantifying human mobility behaviour changes during the COVID-19 outbreak in the United States.
Pan, Yixuan; Darzi, Aref; Kabiri, Aliakbar; Zhao, Guangchen; Luo, Weiyu; Xiong, Chenfeng; Zhang, Lei.
  • Pan Y; Department of Civil and Environmental Engineering, University of Maryland, 1173 Glenn Martin Hall, College Park, MD, 20742, USA.
  • Darzi A; Department of Civil and Environmental Engineering, University of Maryland, 1173 Glenn Martin Hall, College Park, MD, 20742, USA.
  • Kabiri A; Department of Civil and Environmental Engineering, University of Maryland, 1173 Glenn Martin Hall, College Park, MD, 20742, USA.
  • Zhao G; Department of Civil and Environmental Engineering, University of Maryland, 1173 Glenn Martin Hall, College Park, MD, 20742, USA.
  • Luo W; Department of Civil and Environmental Engineering, University of Maryland, 1173 Glenn Martin Hall, College Park, MD, 20742, USA.
  • Xiong C; Department of Civil and Environmental Engineering, University of Maryland, 1173 Glenn Martin Hall, College Park, MD, 20742, USA.
  • Zhang L; Department of Civil and Environmental Engineering, University of Maryland, 1173 Glenn Martin Hall, College Park, MD, 20742, USA. lei@umd.edu.
Sci Rep ; 10(1): 20742, 2020 11 26.
Article in English | MEDLINE | ID: covidwho-947554
ABSTRACT
Since the first case of the novel coronavirus disease (COVID-19) was confirmed in Wuhan, China, social distancing has been promoted worldwide, including in the United States, as a major community mitigation strategy. However, our understanding remains limited in how people would react to such control measures, as well as how people would resume their normal behaviours when those orders were relaxed. We utilize an integrated dataset of real-time mobile device location data involving 100 million devices in the contiguous United States (plus Alaska and Hawaii) from February 2, 2020 to May 30, 2020. Built upon the common human mobility metrics, we construct a Social Distancing Index (SDI) to evaluate people's mobility pattern changes along with the spread of COVID-19 at different geographic levels. We find that both government orders and local outbreak severity significantly contribute to the strength of social distancing. As people tend to practice less social distancing immediately after they observe a sign of local mitigation, we identify several states and counties with higher risks of continuous community transmission and a second outbreak. Our proposed index could help policymakers and researchers monitor people's real-time mobility behaviours, understand the influence of government orders, and evaluate the risk of local outbreaks.
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Full text: Available Collection: International databases Database: MEDLINE Main subject: Travel / Quarantine / Pandemics / Physical Distancing / SARS-CoV-2 / COVID-19 Type of study: Experimental Studies / Observational study / Prognostic study Limits: Humans Country/Region as subject: North America Language: English Journal: Sci Rep Year: 2020 Document Type: Article Affiliation country: S41598-020-77751-2

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Full text: Available Collection: International databases Database: MEDLINE Main subject: Travel / Quarantine / Pandemics / Physical Distancing / SARS-CoV-2 / COVID-19 Type of study: Experimental Studies / Observational study / Prognostic study Limits: Humans Country/Region as subject: North America Language: English Journal: Sci Rep Year: 2020 Document Type: Article Affiliation country: S41598-020-77751-2