Social Distancing Metrics and Estimates of SARS-CoV-2 Transmission Rates: Associations Between Mobile Telephone Data Tracking and R.
Journal
Journal of public health management and practice : JPHMP
ISSN: 1550-5022
Titre abrégé: J Public Health Manag Pract
Pays: United States
ID NLM: 9505213
Informations de publication
Date de publication:
Historique:
pubmed:
23
7
2020
medline:
3
10
2020
entrez:
23
7
2020
Statut:
ppublish
Résumé
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. 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 8 counties surrounding the city of Syracuse, New York. Supplementary analysis examined differences between counties. 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 = .012), visitation (β = .887, P = .017), 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). 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.
Sections du résumé
BACKGROUND
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
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 8 counties surrounding the city of Syracuse, New York. Supplementary analysis examined differences between counties.
RESULTS
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 = .012), visitation (β = .887, P = .017), 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
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.
Identifiants
pubmed: 32694481
doi: 10.1097/PHH.0000000000001240
pii: 00124784-202011000-00017
doi:
Types de publication
Journal Article
Langues
eng
Pagination
606-612Références
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