Association of COVID-19 spread with on-demand testing

  1. Leon S. Robertson

Reviewed by

Read the full article See related articles

Listed in

Log in to save this article

Abstract

Comparisons of COVID-19 testing policies in 99 countries indicate that testing on demand is associated with an increase in cases 14 days after the tests. Adjusted for number of new cases and the positivity rate, for each 10,000 negative tests on a given day there were 90-110 new cases in 14 days that would not have otherwise occurred. Approximately 3.1 million or 21 percent of new cases in periods of on-demand testing are likely due to that policy through early November 2020. During periods in a given country when only persons with symptoms were tested, or persons with symptoms and key vulnerable populations were tested, negative tests were associated with fewer new cases 14 days out. Apparently when tests are available on demand, those who test negative are engaging in activities that increase the risk of exposure.

Article activity feed

  1. ScreenIT

    SciScore for 10.1101/2020.12.04.20244079: (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

    SciScore is an automated tool that is designed to assist expert reviewers by finding and presenting formulaic information scattered throughout a paper in a standard, easy to digest format. SciScore checks for the presence and correctness of RRIDs (research resource identifiers), and for rigor criteria such as sex and investigator blinding. For details on the theoretical underpinning of rigor criteria and the tools shown here, including references cited, please follow this link.

  2. Version published to 10.1101/2020.12.04.20244079v1 on medRxiv