tetano
Editor, Senior Moderator
Emerg Infect Dis
. 2020 Jul 21;26(10).
doi: 10.3201/eid2610.201702. Online ahead of print.
Impact of Social Distancing Measures on Coronavirus Disease Healthcare Demand, Central Texas, USA
Xutong Wang, Remy F Pasco, Zhanwei Du, Michaela Petty, Spencer J Fox, Alison P Galvani, Michael Pignone, S Claiborne Johnston, Lauren Ancel Meyers
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 change 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.
Keywords: COVID-19; SARS-CoV-2; Texas; United States; coronavirus; coronavirus disease; epidemiology; healthcare demand; hospital bed capacity; mathematical model; measures; pandemics; respiratory infections; severe acute respiratory syndrome coronavirus 2; social distancing; viruses; zoonoses.
. 2020 Jul 21;26(10).
doi: 10.3201/eid2610.201702. Online ahead of print.
Impact of Social Distancing Measures on Coronavirus Disease Healthcare Demand, Central Texas, USA
Xutong Wang, Remy F Pasco, Zhanwei Du, Michaela Petty, Spencer J Fox, Alison P Galvani, Michael Pignone, S Claiborne Johnston, Lauren Ancel Meyers
- PMID: 32692648
- DOI: 10.3201/eid2610.201702
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 change 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.
Keywords: COVID-19; SARS-CoV-2; Texas; United States; coronavirus; coronavirus disease; epidemiology; healthcare demand; hospital bed capacity; mathematical model; measures; pandemics; respiratory infections; severe acute respiratory syndrome coronavirus 2; social distancing; viruses; zoonoses.