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Quantifying human mobility behaviour changes during the COVID-19 outbreak in the United States
Yixuan Pan1, Aref Darzi1, Aliakbar Kabiri1
1Department of Civil and Environmental Engineering, University of Maryland, 1173 Glenn Martin Hall, College Park, MD, 20742, USA.
Scientific Reports
|November 27, 2020
Summary
Government orders and COVID-19 severity drive social distancing. People reduce distancing when local cases fall, increasing outbreak risks. This study introduces a Social Distancing Index to track mobility changes.
Area of Science:
- Epidemiology
- Public Health
- Data Science
Background:
- Social distancing was a key strategy during the COVID-19 pandemic.
- Limited understanding existed on public response to distancing measures and behavior changes post-relaxation.
Purpose of the Study:
- To evaluate public reaction to social distancing mandates.
- To analyze mobility pattern changes using real-time data.
- To develop a Social Distancing Index (SDI) for risk assessment.
Main Methods:
- Utilized a dataset of 100 million mobile devices across the US (Feb-May 2020).
- Constructed a Social Distancing Index (SDI) based on human mobility metrics.
- Analyzed the correlation between government orders, outbreak severity, and social distancing.
Main Results:
- Government mandates and local COVID-19 severity significantly influenced social distancing.
- A tendency for reduced distancing was observed following signs of local mitigation.
- Identified high-risk areas for continuous transmission and potential second outbreaks.
Conclusions:
- The Social Distancing Index (SDI) provides real-time insights into public mobility.
- Findings highlight the dynamic interplay between policy, public behavior, and disease spread.
- The SDI can aid policymakers in monitoring behavior and assessing outbreak risks.
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