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- Publisher Website: 10.3201/eid2610.201702
- Scopus: eid_2-s2.0-85090793045
- PMID: 32692648
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Article: Impact of social distancing measures on coronavirus disease healthcare demand, central Texas, USA
Title | Impact of social distancing measures on coronavirus disease healthcare demand, central Texas, USA |
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Authors | |
Issue Date | 2020 |
Citation | Emerging Infectious Diseases, 2020, v. 26, n. 10, p. 2361-2369 How to Cite? |
Abstract | Social distancing orders have been enacted worldwide to slow the coronavirus disease (COVID-19) pandemic, reduce strain on healthcare systems, and prevent deaths. To estimate the impact of the timing and intensity of such measures, we built a mathematical model of COVID-19 transmission that incorporates age-stratified risks and contact patterns and projects numbers of hospitalizations, patients in intensive care units, ventilator needs, and deaths within US cities. Focusing on the Austin metropolitan area of Texas, we found that immediate and extensive social distancing measures were required to ensure that COVID-19 cases did not exceed local hospital capacity by early May 2020. School closures alone hardly changed the epidemic curve. A 2-week delay in implementation was projected to accelerate the timing of peak healthcare needs by 4 weeks and cause a bed shortage in intensive care units. This analysis informed the Stay Home-Work Safe order enacted by Austin on March 24, 2020. |
Persistent Identifier | http://hdl.handle.net/10722/296276 |
ISSN | 2023 Impact Factor: 7.2 2023 SCImago Journal Rankings: 2.117 |
PubMed Central ID |
DC Field | Value | Language |
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dc.contributor.author | Wang, Xutong | - |
dc.contributor.author | Pasco, Remy F. | - |
dc.contributor.author | Du, Zhanwei | - |
dc.contributor.author | Petty, Michaela | - |
dc.contributor.author | Fox, Spencer J. | - |
dc.contributor.author | Galvani, Alison P. | - |
dc.contributor.author | Pignone, Michael | - |
dc.contributor.author | Johnston, S. Claiborne | - |
dc.contributor.author | Meyers, Lauren Ancel | - |
dc.date.accessioned | 2021-02-11T04:53:13Z | - |
dc.date.available | 2021-02-11T04:53:13Z | - |
dc.date.issued | 2020 | - |
dc.identifier.citation | Emerging Infectious Diseases, 2020, v. 26, n. 10, p. 2361-2369 | - |
dc.identifier.issn | 1080-6040 | - |
dc.identifier.uri | http://hdl.handle.net/10722/296276 | - |
dc.description.abstract | Social distancing orders have been enacted worldwide to slow the coronavirus disease (COVID-19) pandemic, reduce strain on healthcare systems, and prevent deaths. To estimate the impact of the timing and intensity of such measures, we built a mathematical model of COVID-19 transmission that incorporates age-stratified risks and contact patterns and projects numbers of hospitalizations, patients in intensive care units, ventilator needs, and deaths within US cities. Focusing on the Austin metropolitan area of Texas, we found that immediate and extensive social distancing measures were required to ensure that COVID-19 cases did not exceed local hospital capacity by early May 2020. School closures alone hardly changed the epidemic curve. A 2-week delay in implementation was projected to accelerate the timing of peak healthcare needs by 4 weeks and cause a bed shortage in intensive care units. This analysis informed the Stay Home-Work Safe order enacted by Austin on March 24, 2020. | - |
dc.language | eng | - |
dc.relation.ispartof | Emerging Infectious Diseases | - |
dc.rights | This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License. | - |
dc.title | Impact of social distancing measures on coronavirus disease healthcare demand, central Texas, USA | - |
dc.type | Article | - |
dc.description.nature | published_or_final_version | - |
dc.identifier.doi | 10.3201/eid2610.201702 | - |
dc.identifier.pmid | 32692648 | - |
dc.identifier.pmcid | PMC7510701 | - |
dc.identifier.scopus | eid_2-s2.0-85090793045 | - |
dc.identifier.volume | 26 | - |
dc.identifier.issue | 10 | - |
dc.identifier.spage | 2361 | - |
dc.identifier.epage | 2369 | - |
dc.identifier.eissn | 1080-6059 | - |
dc.identifier.issnl | 1080-6040 | - |