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Addressing mechanism bias in model-based impact forecasts of new tuberculosis vaccines

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  • M. Tovar

    (University of Zaragoza
    University of Zaragoza)

  • Y. Moreno

    (University of Zaragoza
    University of Zaragoza
    Centai Institute S.p.A)

  • J. Sanz

    (University of Zaragoza
    University of Zaragoza)

Abstract

In tuberculosis (TB) vaccine development, multiple factors hinder the design and interpretation of the clinical trials used to estimate vaccine efficacy. The complex transmission chain of TB includes multiple routes to disease, making it hard to link the vaccine efficacy observed in a trial to specific protective mechanisms. Here, we present a Bayesian framework to evaluate the compatibility of different vaccine descriptions with clinical trial outcomes, unlocking impact forecasting from vaccines whose specific mechanisms of action are unknown. Applying our method to the analysis of the M72/AS01E vaccine trial -conducted on IGRA+ individuals- as a case study, we found that most plausible models for this vaccine needed to include protection against, at least, two over the three possible routes to active TB classically considered in the literature: namely, primary TB, latent TB reactivation and TB upon re-infection. Gathering new data regarding the impact of TB vaccines in various epidemiological settings would be instrumental to improve our model estimates of the underlying mechanisms.

Suggested Citation

  • M. Tovar & Y. Moreno & J. Sanz, 2023. "Addressing mechanism bias in model-based impact forecasts of new tuberculosis vaccines," Nature Communications, Nature, vol. 14(1), pages 1-12, December.
    • Handle: RePEc:nat:natcom:v:14:y:2023:i:1:d:10.1038_s41467-023-40976-6
    DOI: 10.1038/s41467-023-40976-6
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    References listed on IDEAS

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    1. Mario Tovar & Sergio Arregui & Dessislava Marinova & Carlos Martín & Joaquín Sanz & Yamir Moreno, 2019. "Bridging the gap between efficacy trials and model-based impact evaluation for new tuberculosis vaccines," Nature Communications, Nature, vol. 10(1), pages 1-10, December.
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    Cited by:

    1. Davide Pisu & Luana Johnston & Joshua T. Mattila & David G. Russell, 2024. "The frequency of CD38+ alveolar macrophages correlates with early control of M. tuberculosis in the murine lung," Nature Communications, Nature, vol. 15(1), pages 1-19, December.

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