Mobile Phone GPS Data and Prevalence of COVID-19 Infections: Quantifying Parameters of Social Distancing in the U.S.

Document Type : RESEARCH PAPER

Authors

1 1 Adjunct Faculty University of Minnesota, Twin Cities Orthopedics, Edina, MN, USA 2 Oslo Sports Trauma Research Institute, Oslo, Norway

2 Midwest Orthopaedics at Rush, Chicago, IL, USA

3 Stockton University, Galloway, NJ, USA

4 Adjunct Faculty University of Minnesota, Twin Cities Orthopedics, Edina, MN, USA

Abstract

Background: To evaluate the association between social distancing quantified by mobile phone data and the current prevalence of COVID-19 infections in the U.S. per capita. Methods: Data were accessed on April 4, 2020, from Centers for Disease Control and Prevention, Google COVID-19 Community Mobility Report, and the United States Census Bureau to report prevalence of COVID-19 infections, mobility data, and population per state, respectively. Mobility data points were defined as daily length of visit or time spent in a single location based on mobile phone users shared locations from February 7 – March 29, 2020. Multivariable linear regression was used to evaluate relationships between normalized per capita infection prevalence and six parameters of social distancing. Results: Mobility data indicated the following percent changes compared to median values of baseline activity: -50% in transit stations, -45% in retail/recreation, -36% in workplaces, -23% in grocery/pharmacy, -19% in parks, and +12% in residential living areas. Multivariable linear regression revealed significant correlation between prevalence of infection per capita and parameters of social distancing (R= 0.604, P= 0.002). Time at home was not an independent predictor for prevalence of infection per capita (beta= 0.016; 95% CI, -0.003 to 0.036; P= 0.09). Conclusion: Based on mobility reports from mobile phone GPS data and six characteristics of social distancing, significant associations were identified between geographic activity and prevalence of COVID-19 infections in the U.S. per capita. Mobile phone data utilizing ‘location history’ may be warranted to monitor the effectiveness of social distancing parameters on reducing prevalence of COVID-19 in the U.S. Level of evidence: IV

Keywords

References

1. Adalja AA, Toner E, Inglesby TV. Priorities for the US
Health Community Responding to COVID-19. JAMA
: the journal of the American Medical Association.
2020.
2. Haffajee RL, Mello MM. Thinking Globally, Acting
Locally - The U.S. Response to Covid-19. The New
England journal of medicine. 2020.
3. Lurie N, Saville M, Hatchett R, Halton J. Developing
Covid-19 Vaccines at Pandemic Speed. The New
England journal of medicine. 2020.
4. Maharaj S, Kleczkowski A. Controlling epidemic
spread by social distancing: do it well or not at all.
BMC Public Health. 2012;12:679.
5. Shim E. Optimal strategies of social distancing and
vaccination against seasonal influenza. Math Biosci
Eng. 2013;10(5-6):1615-34.
6. Stephenson J. Social distancing helpful in Mexico
during flu pandemic. JAMA : the journal of the
American Medical Association. 2011;305(24):2509.
7. Yu D, Lin Q, Chiu AP, He D. Effects of reactive social
distancing on the 1918 influenza pandemic. PloS one.
2017;12(7):e0180545.
8. Mahase E. Covid-19: UK starts social distancing after
new model points to 260 000 potential deaths. Bmj. 
2020;368:m1089.
9. Rao A, Vazquez JA. Identification of COVID-19 Can
be Quicker through Artificial Intelligence framework
using a Mobile Phone-Based Survey in the Populations
when Cities/Towns Are Under Quarantine. Infect
Control Hosp Epidemiol. 2020:1-18.
10. Goh KT, Cutter J, Heng BH, Ma S, Koh BK, Kwok C, et al.
Epidemiology and control of SARS in Singapore. Ann
Acad Med Singapore. 2006;35(5):301-16.
11. Wilder-Smith A, Freedman DO. Isolation, quarantine,
social distancing and community containment:
pivotal role for old-style public health measures in
the novel coronavirus (2019-nCoV) outbreak. J Travel
Med. 2020;27(2).
12. Herrera-Valdez MA, Cruz-Aponte M, Castillo-Chavez
C. Multiple outbreaks for the same pandemic: Local
transportation and social distancing explain the
different “waves” of A-H1N1pdm cases observed in
Mexico during 2009. Math Biosci Eng. 2011;8(1):21-48.
13. Kleczkowski A, Maharaj S, Rasmussen S, Williams L,
Cairns N. Spontaneous social distancing in response
to a simulated epidemic: a virtual experiment. BMC
Public Health. 2015;15:973.
14. Hou C, Chen J, Zhou Y, Hua L, Yuan J, He S, et al. The 
effectiveness of the quarantine of Wuhan city against
the Corona Virus Disease 2019 (COVID-19): wellmixed
SEIR model analysis. J Med Virol. 2020.
15. Wu Z, McGoogan JM. Characteristics of and Important
Lessons From the Coronavirus Disease 2019
(COVID-19) Outbreak in China: Summary of a Report
of 72314 Cases From the Chinese Center for Disease
Control and Prevention. JAMA : the journal of the
American Medical Association. 2020.
16. McKendry RA, Rees G, Cox IJ, Johnson A, Edelstein M,
Eland A, et al. Share mobile and social-media data to
curb COVID-19. Nature. 2020;580(7801):29.
17. Centers for Disease Control and Prevention [Available
from: https://www.cdc.gov/coronavirus/2019-ncov/
cases-updates/cases-in-us.html.
18. Caley P, Philp DJ, McCracken K. Quantifying social
distancing arising from pandemic influenza. J R Soc
Interface. 2008;5(23):631-9.
19. Glass RJ, Glass LM, Beyeler WE, Min HJ. Targeted social
distancing design for pandemic influenza. Emerg
Infect Dis. 2006;12(11):1671-81.
20. Ahmed F, Zviedrite N, Uzicanin A. Effectiveness of
workplace social distancing measures in reducing
influenza transmission: a systematic review. BMC
Public Health. 2018;18(1):518.
21. Desai AN, Patel P. Stopping the Spread of COVID-19.
JAMA : the journal of the American Medical
Association. 2020.
22. Gostin LO, Wiley LF. Governmental Public Health
Powers During the COVID-19 Pandemic: Stayat-
home Orders, Business Closures, and Travel
Restrictions. JAMA : the journal of the American
Medical Association. 2020.
23. Lipsitch M, Swerdlow DL, Finelli L. Defining the
Epidemiology of Covid-19 - Studies Needed. The New
England journal of medicine. 2020;382(13):1194-6.
24. Tang B, Xia F, Tang S, Bragazzi NL, Li Q, Sun X, et al. The
effectiveness of quarantine and isolation determine
the trend of the COVID-19 epidemics in the final phase
of the current outbreak in China. Int J Infect Dis. 2020.
25. Lewnard JA, Lo NC. Scientific and ethical basis for
social-distancing interventions against COVID-19.
Lancet Infect Dis. 2020.
26. Parodi SM, Liu VX. From Containment to Mitigation
of COVID-19 in the US. JAMA : the journal of the
American Medical Association. 2020.
27. Parmet WE, Sinha MS. Covid-19 - The Law and Limits
of Quarantine. The New England journal of medicine.
2020.
28. Wang CJ, Ng CY, Brook RH. Response to COVID-19
in Taiwan: Big Data Analytics, New Technology, and
Proactive Testing. JAMA : the journal of the American
Medical Association. 2020.
29. Fenichel EP. Economic considerations for social
distancing and behavioral based policies during an
epidemic. J Health Econ. 2013;32(2):440-51.
The Archives of Bone and Joint Surgery
Volume 9, Issue 2
March 2021
Pages 217-223

Files

History

  • Receive Date: 05 May 2020
  • Accept Date: 11 July 2020

Share

How to cite

Statistics