Medical costs of keeping the US economy open during COVID-19
This article has been Reviewed by the following groups
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- Evaluated articles (ScreenIT)
- Evaluated articles (Rapid Reviews Infectious Diseases)
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.
Article activity feed
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SciScore for 10.1101/2020.07.17.20156232: (What is this?)
Please note, not all rigor criteria are appropriate for all manuscripts.
Table 1: Rigor
NIH rigor criteria are not applicable to paper type.Table 2: Resources
No key resources detected.
Results from OddPub: We did not detect open data. We also did not detect open code. Researchers are encouraged to share open data when possible (see Nature blog).
Results from LimitationRecognizer: An explicit section about the limitations of the techniques employed in this study was not found. We encourage authors to address study limitations.Results from TrialIdentifier: No clinical trial numbers were referenced.
Results from Barzooka: We did not find any issues relating to the usage of bar graphs.
Results from JetFighter: We did not find any issues relating to colormaps.
Results from rtransparent:- Thankβ¦
SciScore for 10.1101/2020.07.17.20156232: (What is this?)
Please note, not all rigor criteria are appropriate for all manuscripts.
Table 1: Rigor
NIH rigor criteria are not applicable to paper type.Table 2: Resources
No key resources detected.
Results from OddPub: We did not detect open data. We also did not detect open code. Researchers are encouraged to share open data when possible (see Nature blog).
Results from LimitationRecognizer: An explicit section about the limitations of the techniques employed in this study was not found. We encourage authors to address study limitations.Results from TrialIdentifier: No clinical trial numbers were referenced.
Results from Barzooka: We did not find any issues relating to the usage of bar graphs.
Results from JetFighter: We did not find any issues relating to colormaps.
Results from rtransparent:- Thank you for including a conflict of interest statement. Authors are encouraged to include this statement when submitting to a journal.
- Thank you for including a funding statement. Authors are encouraged to include this statement when submitting to a journal.
- No protocol registration statement was detected.
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Christine Eibner, Raffaele Vardavas
Review 1: "Medical Costs of Keeping the US Economy Open During COVID-19"
A major benefit of this analysis is that it presents a credible, flexible model for estimating the costs of COVID-19, although models will require updating with valid evidence. Sufficient compliance with lockdown guidelines could substantially reduce the medical costs of COVID-19
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Mehdi Shiva
Review 2: "Medical Costs of Keeping the US Economy Open During COVID-19"
A major benefit of this analysis is that it presents a credible, flexible model for estimating the costs of COVID-19, although models will require updating with valid evidence. Sufficient compliance with lockdown guidelines could substantially reduce the medical costs of COVID-19
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Strength of evidence
Reviewers: Christine Eibner, Raffaele Vardavas (RAND) | ππππ β»οΈ
Mehdi Shiva (Blavatnik School of Government) | πππ β»οΈ β»οΈ -
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