%0 Journal Article %T Mobile Phone GPS Data and Prevalence of COVID-19 Infections: Quantifying Parameters of Social Distancing in the U.S. %J The Archives of Bone and Joint Surgery %I Mashhad University of Medical Sciences, Iranian Society of Knee Surgery, Arthroscopy and Sports Tramatology,Iranian Orthopaedic Association %Z 2345-4644 %A DePhillipo, Nicholas N. %A Chahla, Jorge %A Busler, Michael %A LaPrade, Robert F. %D 2021 %\ 03/01/2021 %V 9 %N 2 %P 217-223 %! Mobile Phone GPS Data and Prevalence of COVID-19 Infections: Quantifying Parameters of Social Distancing in the U.S. %K Coronavirus %K contact tracing %K social distancing %R 10.22038/abjs.2020.48515.2404 %X 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 %U https://abjs.mums.ac.ir/article_16561_6e7e5cb2ef040ae6a546c21e26678837.pdf