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Medical costs of keeping the US economy open during COVID-19.
Chen, Jiangzhuo; Vullikanti, Anil; Hoops, Stefan; Mortveit, Henning; Lewis, Bryan; Venkatramanan, Srinivasan; You, Wen; Eubank, Stephen; Marathe, Madhav; Barrett, Chris; Marathe, Achla.
  • Chen J; Network Systems Science and Advanced Computing Division, Biocomplexity Institute, University of Virginia, Charlottesville, VA, 22904, USA.
  • Vullikanti A; Network Systems Science and Advanced Computing Division, Biocomplexity Institute, University of Virginia, Charlottesville, VA, 22904, USA.
  • Hoops S; Department of Computer Science, University of Virginia, Charlottesville, USA.
  • Mortveit H; Network Systems Science and Advanced Computing Division, Biocomplexity Institute, University of Virginia, Charlottesville, VA, 22904, USA.
  • Lewis B; Network Systems Science and Advanced Computing Division, Biocomplexity Institute, University of Virginia, Charlottesville, VA, 22904, USA.
  • Venkatramanan S; Department of Engineering Systems and Environment, University of Virginia, Charlottesville, USA.
  • You W; Network Systems Science and Advanced Computing Division, Biocomplexity Institute, University of Virginia, Charlottesville, VA, 22904, USA.
  • Eubank S; Network Systems Science and Advanced Computing Division, Biocomplexity Institute, University of Virginia, Charlottesville, VA, 22904, USA.
  • Marathe M; Department of Public Health Sciences, University of Virginia, Charlottesville, USA.
  • Barrett C; Network Systems Science and Advanced Computing Division, Biocomplexity Institute, University of Virginia, Charlottesville, VA, 22904, USA.
  • Marathe A; Department of Public Health Sciences, University of Virginia, Charlottesville, USA.
Sci Rep ; 10(1): 18422, 2020 10 28.
Article in English | MEDLINE | ID: covidwho-894412
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ABSTRACT
We use an individual based model and national level epidemic simulations to estimate the medical costs of keeping the US economy open during COVID-19 pandemic under different counterfactual scenarios. We model an unmitigated scenario and 12 mitigation scenarios which differ in compliance behavior to social distancing strategies and in the duration of the stay-home order. Under each scenario we estimate the number of people who are likely to get infected and require medical attention, hospitalization, and ventilators. Given the per capita medical cost for each of these health states, we compute the total medical costs for each scenario and show the tradeoffs between deaths, costs, infections, compliance and the duration of stay-home order. We also consider the hospital bed capacity of each Hospital Referral Region (HRR) in the US to estimate the deficit in beds each HRR will likely encounter given the demand for hospital beds. We consider a case where HRRs share hospital beds among the neighboring HRRs during a surge in demand beyond the available beds and the impact it has in controlling additional deaths.
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Full text: Available Collection: International databases Database: MEDLINE Main subject: Pneumonia, Viral / Health Care Costs / Coronavirus Infections / Pandemics Type of study: Observational study Limits: Humans Country/Region as subject: North America Language: English Journal: Sci Rep Year: 2020 Document Type: Article Affiliation country: S41598-020-75280-6

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Full text: Available Collection: International databases Database: MEDLINE Main subject: Pneumonia, Viral / Health Care Costs / Coronavirus Infections / Pandemics Type of study: Observational study Limits: Humans Country/Region as subject: North America Language: English Journal: Sci Rep Year: 2020 Document Type: Article Affiliation country: S41598-020-75280-6