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

• Published in: PloS one 2020-11, Vol.15 (11), p.e0241468
• Main Authors: Lee, Minha, Zhao, Jun, Sun, Qianqian, Pan, Yixuan, Zhou, Weiyi, Xiong, Chenfeng, Zhang, Lei
• Format: Article
• Language: English
• Subjects: Algorithms; Betacoronavirus - isolation & purification; Big Data; Biology and Life Sciences; Cell Phone Use - statistics & numerical data; Computer and Information Sciences; Control; Coronavirus Infections - epidemiology; Coronavirus Infections - pathology; Coronavirus Infections - virology; Coronaviruses; COVID-19; Data integration; Disease control; Earth Sciences; Electronic Data Processing; Electronic devices; Engineering; Environmental engineering; Epidemics; Health aspects; Health risks; Heterogeneity; Human locomotion; Humans; Impact analysis; Medical research; Medicine and Health Sciences; Mobility; Movement; Pandemics; Pharmaceuticals; Physical Sciences; Pneumonia, Viral - epidemiology; Pneumonia, Viral - pathology; Pneumonia, Viral - virology; Population; Population density; Population studies; Public awareness; Public health; Quarantine; SARS-CoV-2; Shelter in place; Social aspects; Social distancing; Social Sciences; Sociodemographics; Spatio-Temporal Analysis; Statistics; Telecommuting; Travel; Trends; United States; United States - epidemiology; Variation; Viruses
• ISSN: 1932-6203; 1932-6203
• DOI: 10.1371/journal.pone.0241468

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.