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Stochastic evolution of pathogen virulence

Banff International Research Station for Mathematical Innovation and Discovery

Life history theory provides a powerful framework to understand the evolution of pathogens in both epidemic and endemic situations. This framework, however, relies on the assumption that pathogen populations are very large and that one can neglect the effects of demographic stochasticity. Here we explore the effects of finite population size on the evolution of pathogen virulence and transmission. We show that demographic stochasticity introduces additional evolutionary forces that can affect qualitatively the dynamics and the evolutionary outcome. We discuss the importance of the shape of pathogen fitness landscape and host heterogeneity on the balance between mutation, selection and genetic drift. In particular, we discuss scenarios where finite population size can either select for lower or higher virulence. This analysis reconciles adaptive dynamics with population genetics in finite populations and provides a new theoretical framework to study life-history evolution. (Todd L. Parsons, Amaury Lambert, Troy Day and Sylvain Gandon)

Mathematics; Partial differential equations; Probability theory and stochastic processes; Mathematical biology

video/mp4

Author affiliation: Centre national de la recherche scientifique

2017-02-06

Attribution-NonCommercial-NoDerivatives 4.0 International

http://hdl.handle.net/2429/60471

Unreviewed

http://creativecommons.org/licenses/by-nc-nd/4.0/