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Impact of Social Distancing Measures on Coronavirus Disease Healthcare Demand, Central Texas, USA
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 incorpor...
Autores principales: | , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Centers for Disease Control and Prevention
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7510701/ https://www.ncbi.nlm.nih.gov/pubmed/32692648 http://dx.doi.org/10.3201/eid2610.201702 |
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author | Wang, Xutong Pasco, Remy F. Du, Zhanwei Petty, Michaela Fox, Spencer J. Galvani, Alison P. Pignone, Michael Johnston, S. Claiborne Meyers, Lauren Ancel |
author_facet | Wang, Xutong Pasco, Remy F. Du, Zhanwei Petty, Michaela Fox, Spencer J. Galvani, Alison P. Pignone, Michael Johnston, S. Claiborne Meyers, Lauren Ancel |
author_sort | Wang, Xutong |
collection | PubMed |
description | 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. |
format | Online Article Text |
id | pubmed-7510701 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Centers for Disease Control and Prevention |
record_format | MEDLINE/PubMed |
spelling | pubmed-75107012020-10-02 Impact of Social Distancing Measures on Coronavirus Disease Healthcare Demand, Central Texas, USA Wang, Xutong Pasco, Remy F. Du, Zhanwei Petty, Michaela Fox, Spencer J. Galvani, Alison P. Pignone, Michael Johnston, S. Claiborne Meyers, Lauren Ancel Emerg Infect Dis Research 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. Centers for Disease Control and Prevention 2020-10 /pmc/articles/PMC7510701/ /pubmed/32692648 http://dx.doi.org/10.3201/eid2610.201702 Text en https://creativecommons.org/licenses/by/4.0/This is a publication of the U.S. Government. This publication is in the public domain and is therefore without copyright. All text from this work may be reprinted freely. Use of these materials should be properly cited. |
spellingShingle | Research Wang, Xutong Pasco, Remy F. Du, Zhanwei Petty, Michaela Fox, Spencer J. Galvani, Alison P. Pignone, Michael Johnston, S. Claiborne Meyers, Lauren Ancel 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 |
title_full | Impact of Social Distancing Measures on Coronavirus Disease Healthcare Demand, Central Texas, USA |
title_fullStr | Impact of Social Distancing Measures on Coronavirus Disease Healthcare Demand, Central Texas, USA |
title_full_unstemmed | Impact of Social Distancing Measures on Coronavirus Disease Healthcare Demand, Central Texas, USA |
title_short | Impact of Social Distancing Measures on Coronavirus Disease Healthcare Demand, Central Texas, USA |
title_sort | impact of social distancing measures on coronavirus disease healthcare demand, central texas, usa |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7510701/ https://www.ncbi.nlm.nih.gov/pubmed/32692648 http://dx.doi.org/10.3201/eid2610.201702 |
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