Evaluating the trade-off between transmissibility and virulence of SARS-CoV-2 by mathematical modeling

  1. Hyun Mo Yang
  2. Luis Pedro Lombardi Junior
  3. Ariana Campos Yang

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Abstract

Background

At the beginning of 2020, SARS-CoV-2 spread to all continents, and since then, mutations have appeared in different regions of the world. The appearance of more virulent mutations leads to asseverate that they are also more transmissible. We analyzed the lower and higher virulent SARS-CoV-2 epidemics to establish a relationship between transmissibility and virulence based on a mathematical model.

Methods

A compartmental mathematical model based on the CoViD-19 natural history encompassing the age-dependent fatality was applied to evaluate the SARS-CoV-2 transmissibility and virulence. The transmissibility was measured by the basic reproduction number R 0 and the virulence by the proportion of asymptomatic individuals. The model parameters were fitted considering the observed data from São Paulo State.

Results

The numbers of severe CoViD-19 and deaths are three times higher, but R 0 is 25% lower in more virulent SARS-CoV-2 transmission than in a less virulent one. However, the number of more virulent SARS-CoV-2 transmitting individuals is 25% lower, mainly due to symptomatic individuals’ isolation, explaining the increased transmission in lower virulence.

Conclusions

The quarantine study in São Paulo State showed that the more virulent SARS-CoV-2 resulted in a higher number of fatalities but less transmissible than the less virulent one. One possible explanation for the number of deaths surpassing that predicted by the low virulent SARS-CoV-2 infection could be the transmission of more virulent variant(s).

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  1. ScreenIT

    SciScore for 10.1101/2021.02.27.21252592: (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.

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    Results from Barzooka: We did not find any issues relating to the usage of bar graphs.

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    Results from rtransparent:
    • 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 10.1101/2021.02.27.21252592v1 on medRxiv