Anonymized cell phone location data can help monitor COVID-19 growth at the county level, study suggests
By JACQUELINE MITCHELL | Mount Auburn Hospital
This article is part of Harvard Medical School’s continuing coverage of medicine, biomedical research, medical education and policy related to the SARS-CoV-2 pandemic and the disease COVID-19.
In March, federal officials declared the COVID-19 outbreak a national emergency. Around the same time, most states implemented stay-at-home advisories.
Publicly available data suggested that cell phone activity fell at workplaces and retail locations and rose in residential areas, but it hasn't been clear whether this correlated with the spread of COVID-19 in a given region.
Now, an analysis of public, anonymous, county-level cell phone location data and the incidence of COVID-19 for more than 2,500 U.S. counties between January and May 2020 shows that changes in cell phone activity in workplaces, transit stations, retail locations and residences were, indeed, associated with COVID-19 incidence.
The findings are among the first to demonstrate that cell phone location data can help public health officials better monitor adherence to stay-at-home advisories and help identify areas at greatest risk for rapid spread of COVID-19.
The study was published Aug. 31 in JAMA Internal Medicine and led by researchers from Harvard Medical School and the University of Pennsylvania.
“To our knowledge, our study is among the first to evaluate the association of cell phone activity with the rate of growth in new cases of COVID-19 while considering regional confounding factors,” said corresponding author Shiv Sehra, HMS assistant professor of medicine and program director of internal medicine residency at Mount Auburn Hospital.
The work does not address individual risk of disease at any of the counties analyzed, the authors emphasized.
Sehra and colleagues, including senior author Joshua Baker of the University of Pennsylvania, incorporated the location data and daily reported cases of COVID-19 per capita in a majority of U.S. counties. They adjusted the data for multiple county- and state-level characteristics including population density, obesity rates and state spending on health care.
The researchers looked at changes in cell phone use in six categories of places over time: workplaces, retail locations, transit stations, grocery stores, parks and residences.
The location data showed marked reductions in cell phone activity in public places and an increase in activity in residences—even before stay-at-home advisories were rolled out.
The data also showed an increase in workplace and retail location activity as time passed after stay-at-home advisories were implemented. This suggestsa waning adherence to the orders over time—information that may be useful at a public health level.
The study showed that urban counties with higher populations and a higher density of cases saw a larger relative decline in activity outside places of residence and a greater increase in places of residence.
Higher activity at the workplace, in transit stations and retail locations was associated with a higher increase in COVID-19 cases 5, 10 and 15 days later. For example, at 15 days, counties with the greatest reduction in retail location cellphone activity—reflecting greater adherence to stay-at-home advisories—demonstrated a 45.5 percent lower rate of growth of new cases, compared to counties with a lesser decline in retail location activity.
“Some of the factors affecting cell phone activity are quite intuitive,” said Sehra. “But our analysis helps demonstrate the use of anonymous county-level cell phone location data as a way to better understand future trends of the pandemic. Also, we would like to stress that these results should not be used to predict the individual risk of disease at any of these locations.”
The authors report no sources of funding and no conflicts of interest.