Anonymized Cell Phone Location Data can Help Monitor COVID-19 Growth Rates

In March 2020, federal officials declared the COVID-19 outbreak a national emergency. Around the same time, most states implemented stay-at-home advisories - to different degrees and at different times. Publicly available cell phone location data - anonymized at the county-level - showed marked reductions in cell phone activity at the workplace and at retail locations, as well as increased activity in residential areas. However, it was not known whether these data correlate with the spread of COVID-19 in a given region.

In a new study published in JAMA Internal Medicine, researchers from Mount Auburn Hospital and the University of Pennsylvania analyzed anonymous, county-level cell phone location data, made publicly available via Google, and incidence of COVID-19 for more than 2,500 U.S. counties between January and May 2020. The researchers found that changes in cell phone activity in workplaces, transit stations, retail locations, and at places of residence were 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, as well as help identify areas at greatest risk for more rapid spread of COVID-19.

"This study demonstrates that anonymized cell phone location can help researchers and public health officials better predict the future trends in the COVID-19 pandemic," said corresponding author Shiv T. Sehra, MD, Director of the Internal Medicine Residency Program at Mount Auburn Hospital. "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."

Sehra and colleagues, including senior author Joshua F. Baker, MD, MSCE, of the University of Pennsylvania, incorporated publicly available cell phone location data and daily reported cases of COVID-19 per capita in majority of U.S. counties (made available by Johns Hopkins University), and adjusted the data for multiple county- and state- level characteristics including population density, obesity rates, state spending on health care, and many more. Next, the researchers looked at the change in cell phone use in six categories of places over time: workplace, retail locations, transit stations, grocery stores, parks and residences.

The location data showed marked reductions in cell phone activity in public places with 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, suggesting waning adherence to the orders over time, information that may potentially 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 place of residence and a greater increase in residential activity. 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 highest percentage of reduction in retail location cell phone activity - reflecting greater adherence to stay-at-home advisories - demonstrated 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, who is also an Assistant Professor of Medicine at Harvard Medical School. "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."

Sehra ST, George M, Wiebe DJ, Fundin S, Baker JF.
Cell Phone Activity in Categories of Places and Associations With Growth in Cases of COVID-19 in the US.
Intern Med. Published online August 31, 2020. doi: 10.1001/jamainternmed.2020.4288

Most Popular Now

MEDICA 2024 + COMPAMED 2024: Adapted Hal…

11 - 14 November 2024, Düsseldorf, Germany. The final preparations for MEDICA 2024 and COMPAMED 2024 in Düsseldorf have begun. A total of more than 5,500 exhibitors from approximately 70 countries...

AI does Not Necessarily Lead to more Eff…

The use of artificial intelligence (AI) in hospitals and patient care is steadily increasing. Especially in specialist areas with a high proportion of imaging, such as radiology, AI has long...

Commission Joins Forces with Venture Cap…

The Commission has launched a Trusted Investors Network bringing together a group of investors ready to co-invest in innovative deep-tech companies in Europe together with the EU. The Union's investment...

Why the NHS is Seeking to Make Media Ser…

Opinion Article by Dean Moody, Healthcare Services Director, Airwave Healthcare. Tim Kelsey and Martha Lane Fox called for WiFi to be made available free of charge throughout the NHS back in...

An AI-Powered Pipeline for Personalized …

Ludwig Cancer Research scientists have developed a full, start-to-finish computational pipeline that integrates multiple molecular and genetic analyses of tumors and the specific molecular targets of T cells and harnesses...

Philips and Medtronic Advocacy Partnersh…

Royal Philips (NYSE: PHG, AEX: PHIA), a global leader in health technology, and Medtronic Neurovascular, a leading innovator in neurovascular therapies, today announced a strategic advocacy partnership. Delivering timely stroke...

Wearable Cameras Allow AI to Detect Medi…

A team of researchers says it has developed the first wearable camera system that, with the help of artificial intelligence (AI), detects potential errors in medication delivery. In a test whose...

AI could Transform How Hospitals Produce…

A pilot study led by researchers at University of California San Diego School of Medicine found that advanced artificial intelligence (AI) could potentially lead to easier, faster and more efficient...

New AI Tool Predicts Protein-Protein Int…

Scientists from Cleveland Clinic and Cornell University have designed a publicly-available software and web database to break down barriers to identifying key protein-protein interactions to treat with medication. The computational tool...

AI for Real-Rime, Patient-Focused Insigh…

A picture may be worth a thousand words, but still... they both have a lot of work to do to catch up to BiomedGPT. Covered recently in the prestigious journal Nature...

Start-Ups will Once Again Have a Starrin…

11 - 14 November 2024, Düsseldorf, Germany. The finalists in the 16th Healthcare Innovation World Cup and the 13th MEDICA START-UP COMPETITION have advanced from around 550 candidates based in 62...

G-Cloud 14 Makes it Easier for NHS to Bu…

NHS organisations will be able to save valuable time and resource in the procurement of technologies that can make a significant difference to patient experience, in the latest iteration of...