Evidence map›Paper›PMID 33116179›Full record

ArticleScientific reports2020

Medical costs of keeping the US economy open during COVID-19.

Jiangzhuo Chen, Anil Vullikanti, Stefan Hoops, Henning Mortveit, Bryan Lewis, Srinivasan Venkatramanan, Wen You, Stephen Eubank, Madhav Marathe, Chris Barrett and 1 more

Abstract read
In one paragraph

Article in Scientific reports, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
18citing papers in PubMed, 1 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

18 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
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  13. Deciphering the COVID-19 Health Economic Dilemma (HED): A Scoping Review.International journal of environmental research and public health · 2021
    Article
  14. Article
  15. Article
  16. Considerations for diagnostic COVID-19 tests.Nature reviews. Microbiology · 2021
    Review
  17. Article
  18. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

11 authors.

Jiangzhuo ChenNetwork Systems Science and Advanced Computing Division, Biocomplexity Institute, University of Virginia, Charlottesville, VA, 22904, USA.
Anil VullikantiNetwork Systems Science and Advanced Computing Division, Biocomplexity Institute, University of Virginia, Charlottesville, VA, 22904, USA.
Stefan HoopsNetwork Systems Science and Advanced Computing Division, Biocomplexity Institute, University of Virginia, Charlottesville, VA, 22904, USA.
Henning MortveitNetwork Systems Science and Advanced Computing Division, Biocomplexity Institute, University of Virginia, Charlottesville, VA, 22904, USA.
Bryan LewisNetwork Systems Science and Advanced Computing Division, Biocomplexity Institute, University of Virginia, Charlottesville, VA, 22904, USA.
Srinivasan VenkatramananNetwork Systems Science and Advanced Computing Division, Biocomplexity Institute, University of Virginia, Charlottesville, VA, 22904, USA.
Wen YouDepartment of Public Health Sciences, University of Virginia, Charlottesville, USA.
Stephen EubankNetwork Systems Science and Advanced Computing Division, Biocomplexity Institute, University of Virginia, Charlottesville, VA, 22904, USA.
Madhav MaratheNetwork Systems Science and Advanced Computing Division, Biocomplexity Institute, University of Virginia, Charlottesville, VA, 22904, USA.
Chris BarrettNetwork Systems Science and Advanced Computing Division, Biocomplexity Institute, University of Virginia, Charlottesville, VA, 22904, USA.
Achla MaratheNetwork Systems Science and Advanced Computing Division, Biocomplexity Institute, University of Virginia, Charlottesville, VA, 22904, USA. achla@virginia.edu.

Funding

Systems Analysis of Social Pathways of Epidemics to Reduce Health DisparitiesR01GM109718 · NIGMS · VIRGINIA POLYTECHNIC INST AND ST UNIV · PI MARATHE, ACHLA, VULLIKANTI, ANIL · 2014 to 2022
$3.6M
NIGMS NIH HHS R01 GM109718U.S. Department of Health & Human Services | NIH | National Institute of General Medical Sciences (NIGMS) R01GM109718
6 · The paper itself

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.

Indexed as

Capacity BuildingCoronavirus InfectionsCOVID-19Health Care CostsHealth FacilitiesHumansInfection ControlModels, StatisticalPandemicsPneumonia, ViralUnited States

Identifiers

PMID33116179
PMCPMC7595181

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.