Superspreaders help covid-19 elimination

  1. David Kault

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Abstract

There seems to be widespread pessimism regarding the ability of a nation to eliminate covid. One factor in this pessimism seems to be concern that covid might always be able to re-emerge because of the ongoing presence of unrecognised asymptomatic cases. However, it is shown here that it should be possible to eliminate covid more easily than anticipated, for a reason that at first glance seems paradoxical - the presence of superspreaders. If superspreaders are responsible for most of the spread, then, with the average number of secondary cases fixed at say R 0 = 2.5, we have to conclude that superspreaders are relatively rare. When towards the end of an elimination program, there are very few infected people, whether symptomatic or asymptomatic, that small number of people may well not include any superspreaders. As a result, chance effects may make extinction likely. Nevertheless it is clear an attempt at elimination will require a rather onerous “lockdown”. In this paper we use a branching processes model to look at the tradeoff between risk of disease re-emergence and the length of “lockdown” required after a program of elimination has dropped the number of symptomatic cases in a region to just one.

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  1. ScreenIT

    SciScore for 10.1101/2020.04.19.20071761: (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: We detected the following sentences addressing limitations in the study:
    There are some clear limitations to this study. No sensitivity analysis has been done beyond calculations for the two specific distributions described. In particular, there is no sensitivity analysis for likely different values for the proportion asymptomatic pa. However, the fortran programs below could facilitate such a sensitivity analysis if there was more knowledge about the range of plausible values. The calculations and simulations also assume discrete time steps and a different analysis will be required to account for a more realistic model in continuous time.[9] However, one might reasonably hope that more realistic simulations in continuous time will yield fairly similar results to these simpler simulations - but this would need to be checked. There are some assumptions that are too pessimistic. Some assumptions that are likely too conservative have been mentioned above, but there are others. For example, many asymptomatic cases may be detected by contact tracing. There is also implicitly some assumptions that may be too optimistic. For example, it is assumed that there are not cases of prolonged infectious periods or human carrier states or animal reservoirs of the virus in the region. Nevertheless this study gives cause for optimism about the length of lockdown required for any region attempting to eliminate this disease.

    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.

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  2. Version published to 10.1101/2020.04.19.20071761v2 on medRxiv
  3. Version published to 10.1101/2020.04.19.20071761v1 on medRxiv