Evidence map›Paper›PMID 34931196›Full record

ArticlemedRxiv : the preprint server for health sciences2021

Simple decision rules to predict local surges in COVID-19 hospitalizations during the winter and spring of 2022.

Reza Yaesoubi, Shiying You, Qin Xi, Nicolas A Menzies, Ashleigh Tuite, Yonatan H Grad, Joshua A Salomon

Abstract readPreprint
In one paragraph

Article in medRxiv : the preprint server for health sciences, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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1 · What the graph read from it

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2 · The registry

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

7 authors.

Reza YaesoubiDepartment of Health Policy and Management, Yale School of Public Health, New Haven, CT, USA.
Shiying YouDepartment of Health Policy and Management, Yale School of Public Health, New Haven, CT, USA.
Qin XiDepartment of Epidemiology of Microbial Diseases, Yale School of Public Health, New Haven, CT, USA.
Nicolas A MenziesDepartment of Global Health, Harvard T.H. Chan School of Public Health, Boston, MA, USA.
Ashleigh TuiteEpidemiology Division, University of Toronto Dalla Lana School of Public Health, Toronto, Ontario, Canada.
Yonatan H GradDepartment of Immunology and Infectious Diseases, Harvard T. H. Chan School of Public Health, Boston, MA.
Joshua A SalomonDepartment of Health Policy, Stanford University School of Medicine, Palo Alto, CA, USA.

Funding

Making Better Decisions: Policy Modeling for AIDS and Drug AbuseR37DA015612 · NIDA · STANFORD UNIVERSITY · PI DOUGLAS K OWENS · 2019 to 2026
$6.3M
Enhancing surveillance systems to slow the spread of antimicrobial-resistant gonorrhea in the United StatesR01AI153351 · NIAID · YALE UNIVERSITY · PI YAESOUBI, REZA · 2020 to 2024
$2.1M
NIAID NIH HHS R01 AI153351NIDA NIH HHS R37 DA015612
6 · The paper itself

Abstract

Low rates of vaccination, emergence of novel variants of SARS-CoV-2, and increasing transmission relating to seasonal changes leave many U.S. communities at risk for surges of COVID-19 during the winter and spring of 2022 that might strain hospital capacity, as in previous waves. The trajectories of COVID-19 hospitalizations during this period are expected to differ across communities depending on their age distributions, vaccination coverage, cumulative incidence, and adoption of risk mitigating behaviors. Yet, existing predictive models of COVID-19 hospitalizations are almost exclusively focused on national- and state-level predictions. This leaves local policymakers in urgent need of tools that can provide early warnings about the possibility that COVID-19 hospitalizations may rise to levels that exceed local capacity. In this work, we develop simple decision rules to predict whether COVID-19 hospitalization will exceed the local hospitalization capacity within a 4- or 8-week period if no additional mitigating strategies are implemented during this time. These decision rules use real-time data related to hospital occupancy and new hospitalizations associated with COVID-19, and when available, genomic surveillance of SARS-CoV-2. We showed that these decision rules present reasonable accuracy, sensitivity, and specificity (all ≥80%) in predicting local surges in hospitalizations under numerous simulated scenarios, which capture substantial uncertainties over the future trajectories of COVID-19 during the winter and spring of 2022. Our proposed decision rules are simple, visual, and straightforward to use in practice by local decision makers without the need to perform numerical computations. SIGNIFICANCE STATEMENT: In many U.S. communities, the risk of exceeding local healthcare capacity during the winter and spring of 2022 remains substantial since COVID-19 hospitalizations may rise due to seasonal changes, low vaccination coverage, and the emergence of new variants of SARS-CoV-2, such as the omicron variant. Here, we provide simple and easy-to-communicate decision rules to predict whether local hospital occupancy is expected to exceed capacity within a 4- or 8-week period if no additional mitigating measures are implemented. These decision rules can serve as an alert system for local policymakers to respond proactively to mitigate future surges in the COVID-19 hospitalization and minimize risk of overwhelming local healthcare capacity.

Identifiers

PMID34931196
PMCPMC8687467

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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.