State variation in effects of state social distancing policies on COVID-19 cases
BACKGROUND: The novel coronavirus disease 2019 (COVID-19) sickened over 20 million residents in the United States (US) by January 2021. Our objective was to describe state variation in the effect of initial social distancing policies and non-essential business (NEB) closure on infection rates early in 2020.
METHODS: We used an interrupted time series study design to estimate the total effect of all state social distancing orders, including NEB closure, shelter-in-place, and stay-at-home orders, on cumulative COVID-19 cases for each state. Data included the daily number of COVID-19 cases and deaths for all 50 states and Washington, DC from the New York Times database (January 21 to May 7, 2020). We predicted cumulative daily cases and deaths using a generalized linear model with a negative binomial distribution and a log link for two models.
RESULTS: Social distancing was associated with a 15.4% daily reduction (Relative Risk = 0.846; Confidence Interval [CI] = 0.832, 0.859) in COVID-19 cases. After 3 weeks, social distancing prevented nearly 33 million cases nationwide, with about half (16.5 million) of those prevented cases among residents of the Mid-Atlantic census division (New York, New Jersey, Pennsylvania). Eleven states prevented more than 10,000 cases per 100,000 residents within 3 weeks.
CONCLUSIONS: The effect of social distancing on the infection rate of COVID-19 in the US varied substantially across states, and effects were largest in states with highest community spread.
| Medienart: |
E-Artikel |
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| Erscheinungsjahr: |
2021 |
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| Erschienen: |
2021 |
| Enthalten in: |
Zur Gesamtaufnahme - volume:21 |
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| Enthalten in: |
BMC public health - 21(2021), 1 vom: 28. Juni, Seite 1239 |
| Sprache: |
Englisch |
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| Beteiligte Personen: |
Kaufman, Brystana G [VerfasserIn] |
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| Links: |
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| Themen: |
COVID-19 |
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| Anmerkungen: |
Date Completed 01.07.2021 Date Revised 07.11.2023 published: Electronic Citation Status MEDLINE |
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| doi: |
10.1186/s12889-021-11236-3 |
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| funding: |
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| Förderinstitution / Projekttitel: |
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| PPN (Katalog-ID): |
NLM327299770 |
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| 500 | |a Citation Status MEDLINE | ||
| 520 | |a BACKGROUND: The novel coronavirus disease 2019 (COVID-19) sickened over 20 million residents in the United States (US) by January 2021. Our objective was to describe state variation in the effect of initial social distancing policies and non-essential business (NEB) closure on infection rates early in 2020 | ||
| 520 | |a METHODS: We used an interrupted time series study design to estimate the total effect of all state social distancing orders, including NEB closure, shelter-in-place, and stay-at-home orders, on cumulative COVID-19 cases for each state. Data included the daily number of COVID-19 cases and deaths for all 50 states and Washington, DC from the New York Times database (January 21 to May 7, 2020). We predicted cumulative daily cases and deaths using a generalized linear model with a negative binomial distribution and a log link for two models | ||
| 520 | |a RESULTS: Social distancing was associated with a 15.4% daily reduction (Relative Risk = 0.846; Confidence Interval [CI] = 0.832, 0.859) in COVID-19 cases. After 3 weeks, social distancing prevented nearly 33 million cases nationwide, with about half (16.5 million) of those prevented cases among residents of the Mid-Atlantic census division (New York, New Jersey, Pennsylvania). Eleven states prevented more than 10,000 cases per 100,000 residents within 3 weeks | ||
| 520 | |a CONCLUSIONS: The effect of social distancing on the infection rate of COVID-19 in the US varied substantially across states, and effects were largest in states with highest community spread | ||
| 650 | 4 | |a Journal Article | |
| 650 | 4 | |a Research Support, Non-U.S. Gov't | |
| 650 | 4 | |a COVID-19 | |
| 650 | 4 | |a Health policy | |
| 650 | 4 | |a Outcomes research | |
| 650 | 4 | |a Public health | |
| 650 | 4 | |a Social distancing | |
| 700 | 1 | |a Whitaker, Rebecca |e verfasserin |4 aut | |
| 700 | 1 | |a Mahendraratnam, Nirosha |e verfasserin |4 aut | |
| 700 | 1 | |a Hurewitz, Sophie |e verfasserin |4 aut | |
| 700 | 1 | |a Yi, Jeremy |e verfasserin |4 aut | |
| 700 | 1 | |a Smith, Valerie A |e verfasserin |4 aut | |
| 700 | 1 | |a McClellan, Mark |e verfasserin |4 aut | |
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