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Unveiling Time in Dose-Response Models to Infer Host Susceptibility to Pathogens

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Listed:
  • Delphine Pessoa
  • Caetano Souto-Maior
  • Erida Gjini
  • Joao S Lopes
  • Bruno Ceña
  • Cláudia T Codeço
  • M Gabriela M Gomes

Abstract

The biological effects of interventions to control infectious diseases typically depend on the intensity of pathogen challenge. As much as the levels of natural pathogen circulation vary over time and geographical location, the development of invariant efficacy measures is of major importance, even if only indirectly inferrable. Here a method is introduced to assess host susceptibility to pathogens, and applied to a detailed dataset generated by challenging groups of insect hosts (Drosophila melanogaster) with a range of pathogen (Drosophila C Virus) doses and recording survival over time. The experiment was replicated for flies carrying the Wolbachia symbiont, which is known to reduce host susceptibility to viral infections. The entire dataset is fitted by a novel quantitative framework that significantly extends classical methods for microbial risk assessment and provides accurate distributions of symbiont-induced protection. More generally, our data-driven modeling procedure provides novel insights for study design and analyses to assess interventions.Author Summary: While control options for plant, animal, and human pathogens are emerging rapidly, reliable assessment of the effect of interventions in biological systems presents many challenges. A major question is how to connect laboratory experiments and measurements with the relevant process in natural settings, where hosts are subject to pathogen exposures that vary in time and geographical location. With this aim, measures of protection that are invariant under varying exposure intensity need to be developed and integrated with mathematical models. In this article, we introduce a method to assess host susceptibility to pathogens, and apply it to survival of Drosophila melanogaster challenged with different doses of Drosophila C virus. By replicating the procedure in groups of flies that carry the symbiont Wolbachia, we are able to estimate how the viral protection induced by this intracellular bacterium is distributed in the host population. Our results disentangle host infection status from observed mortality, accounting naturally for time since exposure. The multiple-dose design proposed challenges traditional study designs to assess interventions.

Suggested Citation

  • Delphine Pessoa & Caetano Souto-Maior & Erida Gjini & Joao S Lopes & Bruno Ceña & Cláudia T Codeço & M Gabriela M Gomes, 2014. "Unveiling Time in Dose-Response Models to Infer Host Susceptibility to Pathogens," PLOS Computational Biology, Public Library of Science, vol. 10(8), pages 1-9, August.
    • Handle: RePEc:plo:pcbi00:1003773
    DOI: 10.1371/journal.pcbi.1003773
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    References listed on IDEAS

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    1. Ira M. Longini & M. Elizabeth Halloran, 1996. "A Frailty Mixture Model for Estimating Vaccine Efficacy," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 45(2), pages 165-173, June.
    2. P. F. M. Teunis & A. H. Havelaar, 2000. "The Beta Poisson Dose‐Response Model Is Not a Single‐Hit Model," Risk Analysis, John Wiley & Sons, vol. 20(4), pages 513-520, August.
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