Evidence map›Paper›PMID 34145252›Full record

ArticleNature communications2021

Design of COVID-19 staged alert systems to ensure healthcare capacity with minimal closures.

Haoxiang Yang, Özge Sürer, Daniel Duque, David P Morton, Bismark Singh, Spencer J Fox, Remy Pasco, Kelly Pierce, Paul Rathouz, Victoria Valencia and 6 more

Abstract read
In one paragraph

Article in Nature communications, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 papers.

0numbers the graph read from it
0cells of the map it votes in
22citing papers in PubMed
–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

22 citing papers in PubMed.

  1. Article
  2. Article
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  4. Coordinating collaborative infectious disease modeling projects with the hubverse.medRxiv : the preprint server for health sciences · 2025
    Article
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  8. Review
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  15. Article
  16. Article
  17. Article
  18. Real-time pandemic surveillance using hospital admissions and mobility data.Proceedings of the National Academy of Sciences of the United States of America · 2022
    Article
  19. Article
  20. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

16 authors.

Haoxiang YangLos Alamos National Laboratory, Los Alamos, NM, USA.
Özge SürerIndustrial Engineering and Management Sciences, Northwestern University, Evanston, IL, USA.ORCID 0000-0003-4854-9759
Daniel DuqueIndustrial Engineering and Management Sciences, Northwestern University, Evanston, IL, USA.
David P MortonIndustrial Engineering and Management Sciences, Northwestern University, Evanston, IL, USA.ORCID 0000-0001-6001-9078
Bismark SinghDepartment of Mathematics, Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Germany.ORCID 0000-0002-6943-657X
Spencer J FoxIntegrative Biology, The University of Texas at Austin, Austin, TX, USA.
Remy PascoOperations Research and Industrial Engineering, The University of Texas at Austin, Austin, TX, USA.ORCID 0000-0002-9321-6876
Kelly PierceTexas Advanced Computing Center (TACC), The University of Texas at Austin, Austin, TX, USA.
Paul RathouzDell Medical School, The University of Texas at Austin, Austin, TX, USA.
Victoria ValenciaDell Medical School, The University of Texas at Austin, Austin, TX, USA.ORCID 0000-0001-5250-5359
Zhanwei DuIntegrative Biology, The University of Texas at Austin, Austin, TX, USA.
Michael PignoneDell Medical School, The University of Texas at Austin, Austin, TX, USA.
Mark E EscottThe City of Austin, Austin, TX, USA.
Stephen I AdlerThe City of Austin, Austin, TX, USA.
S Claiborne JohnstonDell Medical School, The University of Texas at Austin, Austin, TX, USA.
Lauren Ancel MeyersIntegrative Biology, The University of Texas at Austin, Austin, TX, USA. laurenmeyers@austin.utexas.edu.ORCID 0000-0002-5828-8874

Funding

Accelerating viral outbreak detection in US cities using mechanistic models, machine learning and diverse geospatial dataR01AI151176 · NIAID · YALE UNIVERSITY · PI GALVANI, ALISON P, MEYERS, LAUREN ANCEL · 2020 to 2024
$3.9M
NIAID NIH HHS R01 AI151176
6 · The paper itself

Abstract

Community mitigation strategies to combat COVID-19, ranging from healthy hygiene to shelter-in-place orders, exact substantial socioeconomic costs. Judicious implementation and relaxation of restrictions amplify their public health benefits while reducing costs. We derive optimal strategies for toggling between mitigation stages using daily COVID-19 hospital admissions. With public compliance, the policy triggers ensure adequate intensive care unit capacity with high probability while minimizing the duration of strict mitigation measures. In comparison, we show that other sensible COVID-19 staging policies, including France's ICU-based thresholds and a widely adopted indicator for reopening schools and businesses, require overly restrictive measures or trigger strict stages too late to avert catastrophic surges. As proof-of-concept, we describe the optimization and maintenance of the staged alert system that has guided COVID-19 policy in a large US city (Austin, Texas) since May 2020. As cities worldwide face future pandemic waves, our findings provide a robust strategy for tracking COVID-19 hospital admissions as an early indicator of hospital surges and enacting staged measures to ensure integrity of the health system, safety of the health workforce, and public confidence.

Indexed as

Computer SimulationCOVID-19Delivery of Health CareHospitalizationHumansIntensive Care UnitsQuarantineSARS-CoV-2Texas

Identifiers

PMID34145252
PMCPMC8213780

What OpenQuestion holds

Textmetadata
LicenceCC BY
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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.