An interactive tool to forecast US hospital needs in the coronavirus 2019 pandemic

  1. Kenneth J Locey
  2. Thomas A Webb
  3. Jawad Khan
  4. Anuja K Antony
  5. Bala Hota

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Abstract

Objective

We 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 Methods

Our 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.

Results

Our 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.

Conclusion

Empowering 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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  1. Version published to 10.1093/jamiaopen/ooaa045
  2. ScreenIT

    SciScore for 10.1101/2020.04.20.20073031: (What is this?)

    Please note, not all rigor criteria are appropriate for all manuscripts.

    Table 1: Rigor

    Institutional Review Board Statementnot detected.
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.
    Sex as a biological variablenot detected.

    Table 2: Resources

    No key resources detected.

    Results from OddPub: Thank you for sharing your code and data.

    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.

    About SciScore

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  3. Version published to 10.1101/2020.04.20.20073031 on medRxiv