ArticleJAMIA open2020
An interactive tool to forecast US hospital needs in the coronavirus 2019 pandemic.
Article in JAMIA open, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
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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.
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.
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Who cites it
9 citing papers in PubMed.
- The utility of infectious disease modelling in informing decisions for outbreak response: A scoping review.PLOS global public health · 2025Article
- Assessing the reliability of medical resource demand models in the context of COVID-19.BMC medical informatics and decision making · 2024Article
- The Pandemic Response Commons.JAMIA open · 2024Article
- Wastewater surveillance provides 10-days forecasting of COVID-19 hospitalizations superior to cases and test positivity: A prediction study.Infectious Disease Modelling · 2023Article
- A multistate model and its standalone tool to predict hospital and ICU occupancy by patients with COVID-19.Heliyon · 2023Article
- Associations between the COVID-19 Pandemic and Hospital Infrastructure Adaptation and Planning-A Scoping Review.International journal of environmental research and public health · 2022Article
- COVID-19 outbreak and the role of digital twin.Multimedia tools and applications · 2022Article
- An interactive tool to forecast US hospital needs in the coronavirus 2019 pandemic.JAMIA open · 2020Article
- Impact of lockdowns on the spread of COVID-19 in Saudi Arabia.Informatics in medicine unlocked · 2020Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
objectiveWe developed an application (https://rush-covid19.herokuapp.com/) to aid US hospitals in planning their response to the ongoing Coronavirus Disease 2019 (COVID-19) pandemic. MATERIALS AND
methodsOur application forecasts hospital visits, admits, discharges, and needs for hospital beds, ventilators, and personal protective equipment by coupling COVID-19 predictions to models of time lags, patient carry-over, and length-of-stay. Users can choose from 7 COVID-19 models, customize 23 parameters, examine trends in testing and hospitalization, and download forecast data.
resultsOur application accurately predicts the spread of COVID-19 across states and territories. Its hospital-level forecasts are in continuous use by our home institution and others. DISCUSSION: Our application is versatile, easy-to-use, and can help hospitals plan their response to the changing dynamics of COVID-19, while providing a platform for deeper study.
conclusionEmpowering healthcare responses to COVID-19 is as crucial as understanding the epidemiology of the disease. Our application will continue to evolve to meet this need.
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Registered trials
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.