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How is the instantaneous reproduction number of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) associated with social distancing, wet-bulb temperature, and population density in counties across the United States?
In this cohort study of 211 counties in 46 states, social distancing, temperate weather, and lower population density were associated with a decrease in the instantaneous reproduction number of SARS-CoV-2. Of these county-specific factors, social distancing appeared to have the most substantial association with a reduction in SARS-CoV-2 transmission.
In this study, the instantaneous reproduction number of SARS-CoV-2 varied substantially among counties; the associations between the reproduction number and county-specific factors could inform policies to reduce SARS-CoV-2 transmission in selective and heterogeneous communities.
Local variation in the transmission of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) across the United States has not been well studied.
To examine the association of county-level factors with variation in the SARS-CoV-2 reproduction number over time.
Design, Setting, and Participants
This cohort study included 211 counties, representing state capitals and cities with at least 100 000 residents and including 178 892 208 US residents, in 46 states and the District of Columbia between February 25, 2020, and April 23, 2020.
Social distancing, measured by percentage change in visits to nonessential businesses; population density; and daily wet-bulb temperatures.
Main Outcomes and Measures
Instantaneous reproduction number (Rt), or cases generated by each incident case at a given time, estimated from daily case incidence data.
The 211 counties contained 178 892 208 of 326 289 971 US residents (54.8%). Median (interquartile range) population density was 1022.7 (471.2-1846.0) people per square mile. The mean (SD) peak reduction in visits to nonessential business between April 6 and April 19, as the country was sheltering in place, was 68.7% (7.9%). Median (interquartile range) daily wet-bulb temperatures were 7.5 (3.8-12.8) °C. Median (interquartile range) case incidence and fatality rates per 100 000 people were approximately 10 times higher for the top decile of densely populated counties (1185.2 [313.2-1891.2] cases; 43.7 [10.4-106.7] deaths) than for counties in the lowest density quartile (121.4 [87.8-175.4] cases; 4.2 [1.9-8.0] deaths). Mean (SD) Rt in the first 2 weeks was 5.7 (2.5) in the top decile compared with 3.1 (1.2) in the lowest quartile. In multivariable analysis, a 50% decrease in visits to nonessential businesses was associated with a 45% decrease in Rt (95% CI, 43%-49%). From a relative Rt at 0 °C of 2.13 (95% CI, 1.89-2.40), relative Rt decreased to a minimum as temperatures warmed to 11 °C, increased between 11 and 20 °C (1.61; 95% CI, 1.42-1.84) and then declined again at temperatures greater than 20 °C. With a 70% reduction in visits to nonessential business, 202 counties (95.7%) were estimated to fall below a threshold Rt of 1.0, including 17 of 21 counties (81.0%) in the top density decile and 52 of 53 counties (98.1%) in the lowest density quartile.2
Conclusions and Relevance
In this cohort study, social distancing, lower population density, and temperate weather were associated with a decreased Rt for SARS-CoV-2 in counties across the United States. These associations could inform selective public policy planning in communities during the coronavirus disease 2019 pandemic.
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Accepted for Publication: June 25, 2020.
Published: July 23, 2020. doi:10.1001/jamanetworkopen.2020.16099
Open Access: This is an open access article distributed under the terms of the CC-BY License. © 2020 Rubin D et al. JAMA Network Open.
Corresponding Author: David Rubin, MD, MSCE, Department of Pediatrics, Children’s Hospital of Philadelphia, Roberts Building, 2716 South Street, Suite 10123, Philadelphia, PA (firstname.lastname@example.org).
Author Contributions: Dr Rubin had full access to all of the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis.
Concept and design: Rubin, Huang, Gasparrini, Tam, Griffis, Crammer, Tasian.
Acquisition, analysis, or interpretation of data: All authors.
Drafting of the manuscript: Rubin, Huang, Fisher, Gasparrini, Song, Wang, Kaufman, Fitzpatrick, Jain, Griffis, Tasian.
Critical revision of the manuscript for important intellectual content: Rubin, Huang, Fisher, Gasparrini, Tam, Griffis, Crammer, Morris, Tasian.
Statistical analysis: Rubin, Huang, Gasparrini, Song, Wang, Crammer, Morris.
Obtained funding: Huang.
Administrative, technical, or material support: Rubin, Huang, Fisher, Tam, Wang, Kaufman, Jain, Griffis, Tasian.
Supervision: Rubin, Huang, Fisher, Tasian.
Conflict of Interest Disclosures: Dr Fisher reported receiving grants from Pfizer and Merck and receiving personal fees from Astellas outside the submitted work. Dr Crammer reported receiving grants from the Israel Science Foundation outside the submitted work. No other disclosures were reported.
Funding/Support: Dr Gasparrini is supported by grant MR/M022625/1 from the Medical Research Council UK, grant NE/R009384/1 from the Natural Environment Research Council UK, and grant 820655 from the European Union Horizon 2020 Project Exhaustion. Dr. Huang is supported by the National Institutes of Health under award number 1R01HD099348 and the Patient-Centered Outcomes Research Institute under award number ME-2018C3_14899. Dr. Morris is supported through grant R01-CA-178744 from the National Institutes of Health.
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.
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