Simulation model for productivity, risk and GDP impact forecasting of the COVID-19 portfolio vaccines

  1. Vladimir Shnaydman

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Abstract

The paper presents the methodology and modeling results for COVID-19 vaccines portfolio forecasting, including R&D output (rate and likelihood of approvals at a vaccine technology platform level) and manufacturing production output to meet worldwide demand.

In order to minimize the time and risk of global vaccination, scaling up of Operation Warp Speed (OWS) and other programs could be very beneficial, leading to increased financing for additional vaccine development programs, in both Phase III clinical trials and in manufacturing. It would also lead to a reduction of the global production time for world vaccination, from 75 months for a baseline scenario to 36 months, reducing potential global GDP loss by as much as US$4.2 trillion (US ∼ $1 trillion) when compared to the baseline scenario.

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  1. ScreenIT

    SciScore for 10.1101/2020.11.01.20214122: (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 10.1101/2020.11.01.20214122v1 on medRxiv