Forecasting PPE Consumption during a Pandemic: The Case of Covid-19

  1. Kristian Lum
  2. James Johndrow
  3. April Cardone
  4. Barry Fuchs
  5. Cody E. Cotner
  6. Olivia Jew
  7. Ravi B. Parikh
  8. Michael Draugelis
  9. ThaiBinh Luong
  10. Asaf Hanish
  11. Gary E. Weissman
  12. Christian Terwiesch
  13. Kevin G. Volpp

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Abstract

Due to the global shortage of PPE caused by increasing number of COVID-19 patients in recent months, many hospitals have had difficulty procuring adequate PPE for the clinicians who care for these patients. Faced with a shortage, hospitals have had to implement new PPE conservation policies. In this paper, we describe a tool to help hospitals better project PPE needs under various conservation policies. Though this tool is built on top of projections of the number of hospitalized COVID-19 patients, it is agnostic as to which model—of which many are available—provides these projections. The tool combines COVID-19 patient census projections with information like staffing ratios and frequency of patient contact to provide projections of the number of items of key types of PPE needed under three built-in conservation scenarios: standard, contingency, and crisis. Users are also able to customize the tool to the specifics of their hospital and design custom conservation policies.

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  1. ScreenIT

    SciScore for 10.1101/2020.08.20.20178780: (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: We did not detect open data. We also did not detect open code. Researchers are encouraged to share open data when possible (see Nature blog).

    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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  2. Version published to 10.1101/2020.08.20.20178780 on medRxiv