[Skip to Content]
[Skip to Content Landing]

Cell Phone Activity in Categories of Places and Associations With Growth in Cases of COVID-19 in the US

Educational Objective
To understand how cell phone activity can help us understand how and when COVID-19 is spreading
1 Credit CME
Key Points

Question  Are county-level cell phone location data associated with the rate of change of coronavirus disease 2019 (COVID-19) cases?

Finding  In this cohort study, greater reductions in cell phone activity in the workplace, transit stations, and retail locations and greater increases in activity at the residence were associated with a lower incidence of COVID-19 cases 5, 10, and 15 days later.

Meaning  Using county-level cell phone location data may aid in assessing activities that may presage increases or decreases in COVID-19 cases.


Importance  It is unknown how well cell phone location data portray social distancing strategies or if they are associated with the incidence of coronavirus disease 2019 (COVID-19) cases in a particular geographical area.

Objective  To determine if cell phone location data are associated with the rate of change in new COVID-19 cases by county across the US.

Design, Setting, and Participants  This cohort study incorporated publicly available county-level daily COVID-19 case data from January 22, 2020, to May 11, 2020, and county-level daily cell phone location data made publicly available by Google. It examined the daily cases of COVID-19 per capita and daily estimates of cell phone activity compared with the baseline (where baseline was defined as the median value for that day of the week from a 5-week period between January 3 and February 6, 2020). All days and counties with available data after the initiation of stay-at-home orders for each state were included.

Exposures  The primary exposure was cell phone activity compared with baseline for each day and each county in different categories of place.

Main Outcomes and Measures  The primary outcome was the percentage change in COVID-19 cases 5 days from the exposure date.

Results  Between 949 and 2740 US counties and between 22 124 and 83 745 daily observations were studied depending on the availability of cell phone data for that county and day. Marked changes in cell phone activity occurred around the time stay-at-home orders were issued by various states. Counties with higher per-capita cases (per 100 000 population) showed greater reductions in cell phone activity at the workplace (β, −0.002; 95% CI, −0.003 to −0.001; P < 0.001), areas classified as retail (β, −0.008; 95% CI, −0.011 to −0.005; P < 0.001) and grocery stores (β, −0.006; 95% CI, −0.007 to −0.004; P < 0.001), and transit stations (β, −0.003, 95% CI, −0.005 to −0.002; P < 0.001), and greater increase in activity at the place of residence (β, 0.002; 95% CI, 0.001-0.002; P < 0.001). Adjusting for county-level and state-level characteristics, counties with the greatest decline in workplace activity, transit stations, and retail activity and the greatest increases in time spent at residential places had lower percentage growth in cases at 5, 10, and 15 days. For example, counties in the lowest quartile of retail activity had a 45.5% lower growth in cases at 15 days compared with the highest quartile (SD, 37.4%-53.5%; P < .001).

Conclusions and Relevance  Our findings support the hypothesis that greater reductions in cell phone activity in the workplace and retail locations, and greater increases in activity at the residence, are associated with lesser growth in COVID-19 cases. These data provide support for the value of monitoring cell phone location data to anticipate future trends of the pandemic.

Sign in to take quiz and track your certificates

Buy This Activity

JN Learning™ is the home for CME and MOC from the JAMA Network. Search by specialty or US state and earn AMA PRA Category 1 Credit(s)™ from articles, audio, Clinical Challenges and more. Learn more about CME/MOC

CME Disclosure Statement: Unless noted, all individuals in control of content reported no relevant financial relationships. If applicable, all relevant financial relationships have been mitigated.

Article Information

Accepted for Publication: July 8, 2020.

Corresponding Authors: Shiv T. Sehra, MD, Mount Auburn Hospital, 330 Mount Auburn St, Cambridge, MA 02138 (ssehra1@mah.harvard.edu); Joshua F. Baker MD, MSCE, Hospital of the University of Pennsylvania, 3400 Spruce St, 5 White Bldg, Philadelphia, PA 19104 (joshua.baker@pennmedicine.upenn.edu).

Published Online: August 31, 2020. doi:10.1001/jamainternmed.2020.4288

Author Contributions: Drs Sehra and Baker had full access to all the data in the study and take responsibility for the integrity of the data and the accuracy of the data analysis.

Concept and design: Sehra, Wiebe, Baker.

Acquisition, analysis, or interpretation of data: Sehra, George, Fundin, Baker.

Drafting of the manuscript: Sehra, George, Baker.

Critical revision of the manuscript for important intellectual content: All authors.

Statistical analysis: Baker.

Administrative, technical, or material support: Sehra, Fundin.

Supervision: Sehra, Wiebe.

Conflict of Interest Disclosures: Dr George reported grants from Bristol-Myers Squibb and personal fees from AbbVie outside the submitted work. Dr Baker reported personal fees from Gilead and Bristol-Myers Squibb outside the submitted work. No other disclosures were reported.

Funding/Support: Dr Baker receives funding through a Veterans Affairs Clinical Science Research & Development Merit Award (I01 CX001703).

Role of the Funder/Sponsor: The funders had no role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; and decision to submit the manuscript for publication.

Disclaimer: The contents of this work do not represent the views of the US Department of the Veterans Affairs or the United States government.

Additional Contributions: We thank Criswell Lavery, BA, University of Pennsylvania, for her help with acquiring data. She did not receive any monetary compensation for her help with this article.

Lau  H , Khosrawipour  V , Kocbach  P ,  et al.  The positive impact of lockdown in Wuhan on containing the COVID-19 outbreak in China.   J Travel Med. 2020;27(3):taaa037. doi:10.1093/jtm/taaa037PubMedGoogle Scholar
Lai  CC , Shih  TP , Ko  WC , Tang  HJ , Hsueh  PR .  Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and coronavirus disease-2019 (COVID-19): The epidemic and the challenges.   Int J Antimicrob Agents. 2020;55(3):105924. doi:10.1016/j.ijantimicag.2020.105924PubMedGoogle Scholar
Pew Research Center. Pew Research Center mobile fact sheet. Accessed May 15, 2020. https://www.pewresearch.org/internet/fact-sheet/mobile/
Zhang  L , Ghader  S , Pack  ML   et al.  An interactive COVID-19 mobility impact and social distancing analysis platform.   medRxiv. Preprint posted on May 5, 2020. doi:10.1101/2020.04.29.20085472Google Scholar
Gao  S , Rao  J , Kang  Y , Liang  Y , Kruse  J . Mapping county-level mobility pattern changes in the United States in response to COVID-19. Accessed June 22, 2020. https://arxiv.org/abs/2004.04544
Center for Systems Science and Engineering. CSSEGISandData/COVID-19. Accessed May 11, 2020. https://github.com/cssegisanddata/covid-19
Google. Covid-19 community mobility reports. Accessed May 14, 2020. https://www.google.com/covid19/mobility/
US Centers for Disease Control and Prevention. 2013 NCHS urban-rural classification scheme for counties. Accessed May 15, 2020. https://www.cdc.gov/nchs/data_access/urban_rural.Htm#data_files_and_documentation
US Census Bureau. 2018 ACS 1-year estimates. U.S. Accessed May 1, 2020. https://www.census.gov/programs-surveys/acs/news/data-releases/2018/release.html#par_textimage_copy
US Census Bureau. State population by characteristics: 2010-2019. Accessed April 20, 2020. https://www.census.gov/data/datasets/time-series/demo/popest/2010s-state-detail.html?#
US Centers for Disease Control and Prevention. Weight classification by body mass index (BMI) (variable calculated from one or more BRFSS questions) (crude prevalence). Accessed April 20, 2020. https://nccd.cdc.gov/brfssprevalence/rdpage.aspx?rdreport=dph_brfss.explorebytopic&irblocationtype=statesandmmsa&islclass=class14&isltopic=topic09&islyear=2018&rdrnd=63137
US Census Bureau. Income and poverty in the United States: 2018. U.S. Census Bureau. Accessed June 19, 2020. https://www.census.gov/data/tables/2019/demo/income-poverty/p60-266.html
National Center for Education Statistics. Public high school 4-year adjusted cohort graduation rate (ACGR), by selected student characteristics and state: 2010-11 through 2016-17. Accessed May 13, 2020. https://nces.ed.gov/programs/digest/d18/tables/dt18_219.46.Asp
Kaiser Family Foundation. State health facts. Accessed May 15, 2020. https://www.kff.org/statedata/
The Atlantic Monthly Group. The COVID Tracking Project. Accessed June 1, 2020. https://covidtracking.com/
Lauer  SA , Grantz  KH , Bi  Q ,  et al.  The Incubation period of coronavirus Disease 2019 (COVID-19) from publicly reported confirmed cases: estimation and application.   Ann Intern Med. 2020;172(9):577-582. doi:10.7326/M20-0504PubMedGoogle ScholarCrossref
AMA CME Accreditation Information

Credit Designation Statement: The American Medical Association designates this Journal-based CME activity activity for a maximum of 1.00  AMA PRA Category 1 Credit(s)™. Physicians should claim only the credit commensurate with the extent of their participation in the activity.

Successful completion of this CME activity, which includes participation in the evaluation component, enables the participant to earn up to:

  • 1.00 Medical Knowledge MOC points in the American Board of Internal Medicine's (ABIM) Maintenance of Certification (MOC) program;;
  • 1.00 Self-Assessment points in the American Board of Otolaryngology – Head and Neck Surgery’s (ABOHNS) Continuing Certification program;
  • 1.00 MOC points in the American Board of Pediatrics’ (ABP) Maintenance of Certification (MOC) program;
  • 1.00 Lifelong Learning points in the American Board of Pathology’s (ABPath) Continuing Certification program; and
  • 1.00 CME points in the American Board of Surgery’s (ABS) Continuing Certification program

It is the CME activity provider's responsibility to submit participant completion information to ACCME for the purpose of granting MOC credit.

Want full access to the AMA Ed Hub?
After you sign up for AMA Membership, make sure you sign in or create a Physician account with the AMA in order to access all learning activities on the AMA Ed Hub
Buy this activity
Want full access to the AMA Ed Hub?
After you sign up for AMA Membership, make sure you sign in or create a Physician account with the AMA in order to access all learning activities on the AMA Ed Hub
Buy this activity
With a personal account, you can:
  • Access free activities and track your credits
  • Personalize content alerts
  • Customize your interests
  • Fully personalize your learning experience
Education Center Collection Sign In Modal Right

Name Your Search

Save Search
With a personal account, you can:
  • Access free activities and track your credits
  • Personalize content alerts
  • Customize your interests
  • Fully personalize your learning experience

Lookup An Activity


My Saved Searches

You currently have no searches saved.


My Saved Courses

You currently have no courses saved.