tetano
Editor, Senior Moderator
Sci Rep
. 2020 Nov 26;10(1):20742.
doi: 10.1038/s41598-020-77751-2.
Quantifying human mobility behaviour changes during the COVID-19 outbreak in the United States
Yixuan Pan[SUP] 1 [/SUP], Aref Darzi[SUP] 1 [/SUP], Aliakbar Kabiri[SUP] 1 [/SUP], Guangchen Zhao[SUP] 1 [/SUP], Weiyu Luo[SUP] 1 [/SUP], Chenfeng Xiong[SUP] 1 [/SUP], Lei Zhang[SUP] 2 [/SUP]
Affiliations
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.
. 2020 Nov 26;10(1):20742.
doi: 10.1038/s41598-020-77751-2.
Quantifying human mobility behaviour changes during the COVID-19 outbreak in the United States
Yixuan Pan[SUP] 1 [/SUP], Aref Darzi[SUP] 1 [/SUP], Aliakbar Kabiri[SUP] 1 [/SUP], Guangchen Zhao[SUP] 1 [/SUP], Weiyu Luo[SUP] 1 [/SUP], Chenfeng Xiong[SUP] 1 [/SUP], Lei Zhang[SUP] 2 [/SUP]
Affiliations
- PMID: 33244071
- DOI: 10.1038/s41598-020-77751-2
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.