Can age-distribution be an indicator of the goodness of COVID-19 testing?

  1. Amirhoshang Hoseinpour Dehkordi
  2. Reza Nemati
  3. Pouya Tavousi

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Abstract

It has been evident that the faster, more accurate, and more comprehensive testing can help policymakers assess the real impact of COVID-19 and help them with when and how strict the mitigation policies should be. Nevertheless, the exact number of infected ones could not be measured due to the lack of comprehensive testing. In this paper, first of all, we will investigate the relation of transmission of COVID-19 with age by observing timed data in multiple countries. Then, we compare the COVID-19 CFR with the age-demography data. and as a result, we have proposed a method for estimating a lower bound for the number of positive cases by using the reported data on the oldest age group and the regions’ population age-distributions. The proposed estimation method improved the expected similarity between the age-distribution of positive cases and regions’ populations. Thus, using the publicly accessible data for several developed countries, we show how the improvement of testing over the course of several months has made it clear for the community that different age groups are equally prone to becoming COVID positive. The result shows that the age demography of COVID-19 gets similar to the age-demography of the population, together with the reduction of CFR over time. In addition, countries with less CFR have more similar COVID-19’s age-distribution, which is caused by more comprehensive testing, than ones who have higher CFR. This leads us to a better estimation for positive cases in different testing strategies. Having knowledge of this fact helps policymakers enforce more effective policies for controlling the spread of the virus.

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    SciScore for 10.1101/2020.12.21.20248690: (What is this?)

    Please note, not all rigor criteria are appropriate for all manuscripts.

    Table 1: Rigor

    NIH rigor criteria are not applicable to paper type.

    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.

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    • Thank you for including a conflict of interest statement. Authors are encouraged to include this statement when submitting to a journal.
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    • No protocol registration statement was detected.

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  2. Version published to 10.1101/2020.12.21.20248690v1 on medRxiv