The speed of vaccination rollout and the risk of pathogen adaptation

Vaccination is expected to reduce disease prevalence and to halt the spread of epidemics. Pathogen adaptation, however, may erode the efficacy of vaccination and limit our ability to control disease spread. Here, we examine the influence of the rate of vaccination of the host population on the overall risk of pathogen adaptation to vaccination. We extend the framework of evolutionary epidemiology theory to account for demographic stochasticity in the different steps leading to the adaptation to vaccination: (i) the introduction of a vaccine-escape variant by mutation from an endemic wild-type pathogen, (ii) the invasion of this vaccine-escape variant in spite of the risk of early extinction, (iii) the spread and fixation of the vaccine-escape variant in the pathogen population. We introduce a novel and versatile hybrid analytical-numerical method that allows fast computation of the probabilities associated with these steps. Using it, we show that increasing the rate of vaccination can reduce both the number of cases and the likelihood of pathogen adaptation. Our work clarifies the influence of vaccination policies-a major ecological perturbation of the environment of a pathogen-on different steps of pathogen adaptation. The model provides a useful theoretical framework to account for the interplay between epidemiology, selection and genetic drift and to anticipate the effects of public-health interventions on pathogen evolution.

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Publication Details

Journal
Journal of The Royal Society Interface
Published
2025-07-01
DOI
https://doi.org/10.1098/rsif.2025.0060
Citations
2
Primary Topic
Evolution and Genetic Dynamics
Type
article
Field-Weighted Citation Impact
3.63

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article

The speed of vaccination rollout and the risk of pathogen adaptation

Troy Day, Todd L. Parsons, Marina Voinson, Amaury Lambert et al.
2 citations
Journal of The Royal Society Interface
Evolution and Genetic Dynamics
3.63
article

The speed of vaccination rollout and the risk of pathogen adaptation

Troy Day, Todd L. Parsons, Marina Voinson, Amaury Lambert, Sylvain Gandon
article en
2 citations

Abstract

Vaccination is expected to reduce disease prevalence and to halt the spread of epidemics. Pathogen adaptation, however, may erode the efficacy of vaccination and limit our ability to control disease spread. Here, we examine the influence of the rate of vaccination of the host population on the overall risk of pathogen adaptation to vaccination. We extend the framework of evolutionary epidemiology theory to account for demographic stochasticity in the different steps leading to the adaptation to vaccination: (i) the introduction of a vaccine-escape variant by mutation from an endemic wild-type pathogen, (ii) the invasion of this vaccine-escape variant in spite of the risk of early extinction, (iii) the spread and fixation of the vaccine-escape variant in the pathogen population. We introduce a novel and versatile hybrid analytical-numerical method that allows fast computation of the probabilities associated with these steps. Using it, we show that increasing the rate of vaccination can reduce both the number of cases and the likelihood of pathogen adaptation. Our work clarifies the influence of vaccination policies-a major ecological perturbation of the environment of a pathogen-on different steps of pathogen adaptation. The model provides a useful theoretical framework to account for the interplay between epidemiology, selection and genetic drift and to anticipate the effects of public-health interventions on pathogen evolution.

Journal of The Royal Society InterfaceVol. 22(228)
Centre National de la Recherche Scientifique (FR), Inserm (FR), Collège de France (FR), Université de Montpellier (FR), Queen's University (CA), Université Paris Cité (FR), Université Paris Sciences et Lettres (FR), Centre d'Écologie Fonctionnelle et Évolutive (FR), Centre Interdisciplinaire de Recherche en Biologie (FR), Institut de Biologie de l'École Normale Supérieure (FR), Institut de Recherche pour le Développement (FR), Laboratoire de Probabilités, Statistique et Modélisation (FR)
Agence Nationale de la Recherche
Good health and well-being
Openalex Percentile: Top 7%
Evolution and Genetic Dynamics
3.63
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