Social Distancing Metrics and Estimates of SARS-CoV-2 Transmission Rates: Associations between mobile telephone data tracking and R

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dc.contributor.author Morley, Christopher P.
dc.contributor.author Anderson, Kathryn B.
dc.contributor.author Shaw, Jana
dc.contributor.author Stewart, Telisa
dc.contributor.author Thomas, Stephen J.
dc.contributor.author Wang, Dongliang
dc.date.accessioned 2020-05-20T12:26:56Z
dc.date.available 2020-05-20T12:26:56Z
dc.date.issued 2020-05-20
dc.identifier.uri http://hdl.handle.net/2027.42/155389
dc.description.abstract Background: Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is the causative agent of coronavirus disease 2019 (COVID-19). In the absence of robust preventive or curative strategies, the implementation of social distancing has been a key component of limiting the spread of the virus. Methods: Daily estimates of R(t) were calculated, and compared with measures of social distancing made publicly available by Unacast. Daily-generated variables representing an overall grade for distancing, changes in distances traveled, encounters between individuals, and daily visitation, were modeled as predictors of average R value for the following week, using linear regression techniques for eight counties surrounding the city of Syracuse, NY. Supplementary analysis examined differences between counties. Results: A total of 225 observations were available across the 8 counties, with 166 meeting the Mean R(t)<3 outlier criterion for the regression models. Measurements for Distance (β=1.002, p=.001), Visitation (β=.887, p=.012), and Encounters (β=1.070, p=.001) were each predictors of R(t) for the following week. Mean R(t) drops when overall distancing grades move from D+ to C-. These trends were significant (p<.001 for each). Conclusions: Social distancing, when assessed by free and publicly available measures such as those shared by Unacast, has an impact on viral transmission rates. The Scorecard may also be useful for public messaging about social distance, in hospital planning, and in the interpretation of epidemiological models. en_US
dc.language.iso en_US en_US
dc.relation.ispartofseries Annals of Family Medicine, COVID-19 Collection en_US
dc.subject Social Distancing, SARS-CoV-2, COVID-19, Mobile Phone tracking data, R, en_US
dc.title Social Distancing Metrics and Estimates of SARS-CoV-2 Transmission Rates: Associations between mobile telephone data tracking and R en_US
dc.type Preprint en_US
dc.subject.hlbsecondlevel Epidemiology
dc.subject.hlbtoplevel Health Sciences
dc.contributor.affiliationother Department of Public Health & Preventive Medicine, SUNY Upstate Medical University, Syracuse, NY en_US
dc.contributor.affiliationother Department of Family Medicine & Department of Psychiatry & Behavioral Sciences, SUNY Upstate Medical University, Syracuse, NY en_US
dc.contributor.affiliationother Department of Internal Medicine, Division of Hospital Medicine, SUNY Upstate Medical University, Syracuse, NY en_US
dc.contributor.affiliationother Department of Microbiology and Immunology, SUNY Upstate Medical University, Syracuse, NY en_US
dc.contributor.affiliationother Department of Pediatrics, Division of Pediatric Infectious Disease, SUNY Upstate Medical University, Syracuse, NY en_US
dc.contributor.affiliationother Department of Urology & Department of Geriatrics, SUNY Upstate Medical University, Syracuse, NY en_US
dc.contributor.affiliationother Department of Medicine, SUNY Upstate Medical University, Syracuse, NY Institute for Global Health & Translational Science, SUNY Upstate Medical University, Syracuse, NY en_US
dc.contributor.affiliationumcampus Ann Arbor en_US
dc.description.bitstreamurl https://deepblue.lib.umich.edu/bitstream/2027.42/155389/1/Uncast_by_R_manuscript_Final_watermarked.pdf
dc.description.filedescription Description of Uncast_by_R_manuscript_Final_watermarked.pdf : Main Article
dc.owningcollname COVID-19: Annals of Family Medicine
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