STeCC: Smart Testing with Contact Counting Enhances Covid-19 Mitigation by Bluetooth App Based Contact Tracing

  1. Hossein Gorji
  2. Markus Arnoldini
  3. David F. Jenny
  4. Alexandre Duc
  5. Wolf-Dietrich Hardt
  6. Patrick Jenny

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Abstract

Covid-19 mitigation commonly involves social distancing. Due to its high economic toll and its impact on personal freedom, we need to ease social distancing and deploy alternative measures, while preventing a second wave of infections. Bluetooth app-based contact tracing has been proposed, focusing on symptomatic cases and isolating their contacts. However, this approach would miss many transmissions by asymptomatic cases. To improve effectiveness of app-based mitigation, we propose to complement contact tracing with Smart Testing relying on Contact Counting (STeCC). STeCC focuses virus RNA testing to people with exceptionally high numbers of contacts. These people are at particularly high risk to become infected (with or without symptoms) and transmit the virus. Mathematical modeling shows that a mitigation strategy combining STeCC and contact tracing in one app will be more efficient than contact tracing and works when ≈50% (instead of ≥60%) of the total population participate. Similarly, it requires 50-100 fold less tests than randomized virus testing alone. These gains in efficiency may be critical for success. STeCC could be integrated in the current Bluetooth tracing apps. Thus, STeCC is technically feasible and can reduce the pandemic’s reproduction number by 2.4-fold (e.g. from R 0 =2.4 to R eff =1) with realistic test numbers (≈166 per 100’000 people per day), when a realistic fraction of the population would use the app (i.e. ≈50% in total population). Thereby, STeCC efficiently complements the portfolio of mitigation strategies, which allow easing social distancing without compromising public health.

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  1. Version published to 10.1101/2020.03.27.20045237v3 on medRxiv
  2. ScreenIT

    SciScore for 10.1101/2020.03.27.20045237: (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

    Software and Algorithms
    SentencesResources
    The calculations for mass testing, contact tracing and smart testing were implemented with MATLAB and the Statistics Toolbox Release 2018b.
    MATLAB
    suggested: (MATLAB, RRID:SCR_001622)

    Results from OddPub: Thank you for sharing your code.

    Results from LimitationRecognizer: We detected the following sentences addressing limitations in the study:
    What are the limitations of STeCC? First, we cannot exclude that some assumptions used in our model may be too optimistic or that more precise information might be derived later from alternative, more detailed simulation approaches. The percentage and infectiousness of asymptomatic cases, and the distribution of contacts in the population would have the biggest impact. However, modeling the impact with less favorable parameters verified that STeCC would still provide substantial benefits (Fig. S7, Fig. S8). Second, false positive virus tests might dilute the ability to detect positive cases if the virus prevalence is very low. Third, contact counting has not been a focus during the development of Bluetooth-based proximity testing applications. Thus, small, but doable adaptations might be needed, in order to enable efficient detection and notification of high-contact individuals (supplementary text, section 7). Strict social distancing has been successful in achieving Reff<1 in many countries, but at a high economical and societal cost. Easing of these measures is presently being discussed or implemented. However, if a large fraction of the population has remained susceptible, a second wave of disease is bound to occur in the absence of effective alternative mitigation strategies. We suggest using a combination of contact tracing and STeCC, as a simple mitigation approach which relies on identifying high-contact individuals, testing them for infection, and quarantining positiv...

    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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  3. Version published to 10.1101/2020.03.27.20045237v2 on medRxiv
  4. Version published to 10.1101/2020.03.27.20045237v1 on medRxiv