Number of tests required to flatten the curve of coronavirus disease-2019

  1. Seogwon Hwang
  2. Jong-Hoon Kim
  3. Young June Choe
  4. Dong-hyun Oh

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Abstract

We developed a mathematical model to quantify the number of tests required to stop the spread of coronavirus disease 2019 (COVID-19). Our model analyses performed using the data from the U.S. suggest that the infection coefficient increases by approximately 47% upon relaxing the lockdown policy. To offset the effect of lockdown relaxation, the number of tests should increase by 2.25 times, corresponding to approximately 280,000–360,000 tests per day in April 2020.

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  1. ScreenIT

    SciScore for 10.1101/2020.12.26.20248818: (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: We detected the following sentences addressing limitations in the study:
    The limitations of our model and estimation, such as strong mathematical assumptions and the endogeneity of the number of tests, would be interesting topics for follow-up studies. Furthermore, some of subsequent studies may extend our model to complete epidemic models by including hospitalization and recovery. Despite this, our study provides quantified evidence to the public policy regarding resource allocation for suppressing the spread of COVID-19. In the circumstance that many countries have gradually relaxed social distancing only with the expectation for herd immunity to be built-up, this study is believed to help policy-makers develop policy tools for the relaxation through the increase in the number of testing (7). Although the optimal number of testing is different across countries, the figures estimated in this study are expected to pave the road for suppressing the spread of COVID-19 (8). In summary, we present a trade-off relationship between social distancing and mass testing, suggesting the additional mass-testing of at least 2.25 times in the case of the relaxation of social-distancing norms in the U.S. These approaches can disseminate the information regarding the decisions made by public health bodies of other countries, especially those planning to relax lockdown norms, thereby enabling both the selective adoption of policies that have proved effective in curtailing the spread of COVID-19 and additional mass testing.

    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 10.1101/2020.12.26.20248818v1 on medRxiv