Model for evaluating cost-effectiveness of surveillance testing for SARS-CoV2

  1. Jonathan Silver

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Abstract

Testing people without symptoms for SARS-CoV-2 followed by isolation of those who test positive could mitigate the covid-19 epidemic pending arrival of an effective vaccine. Key questions for such programs are who should be tested, how often, and when should such testing stop. Answers to these questions depend on test and population characteristics. A cost-effectiveness model that provides answers depending on user-adjustable parameter values is described. Key parameters are the value ascribed to preventing a death and the reproduction number (roughly, rate of spread) at the time surveillance testing is initiated. For current rates of spread, cost-effectiveness usually requires a value per life saved greater than $100,000 and depends critically on the extent and frequency of testing.

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    SciScore for 10.1101/2020.12.02.20242644: (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 10.1101/2020.12.02.20242644v1 on medRxiv