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Communication dans un congrès

Competition processes, a tool to model pathogen adaptation time

Abstract :

In many biological contexts, humans try to control harmful populations by introducing resistance into their habitat. However, this strategy is rarely durable because of swift pathogen adaptation to a new hostile environment. Multi-resistance is thought to be a way to delay pathogen adaptation. To understand the population adaptation to multi-resistance environment on the waiting time before emergence of a multi-virulent mutant. We formulated a stochastic population model based on the competition processes with mutation, migration and recombination. We included a fitness cost for mutants overcoming resistance. To estimate the emergence time, we permormed numerical simulations in which we vary pathogens life history traits and the environment structure. The numerical simulation showed the strong dependence of the emergence time on the environment structure. In the case of diversified environment including mono-resistant and susceptible areas, emergence time is a parabolic function of the fraction of resistant area. The emergence time was longer for low and high resistant area fractions, because of induced low migration and mutation probabilities. For multi-resistant environment, emergence time increases with the increase of number of resistances and with the decrease of the transition environments proportion. The results of the model provide insight into our understanding the interplay between used disease control strategy and the pathogen evolution rate to overcome the resistance. The model can be used for designing control strategies preventing rapid adaptation of harmful populations.

Type de document :
Communication dans un congrès
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https://hal.univ-angers.fr/hal-03038373
Contributeur : Okina Université d'Angers <>
Soumis le : jeudi 3 décembre 2020 - 14:33:08
Dernière modification le : vendredi 4 décembre 2020 - 03:26:14

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  • HAL Id : hal-03038373, version 1
  • OKINA : ua12487

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Citation

Romain Bourget. Competition processes, a tool to model pathogen adaptation time. Mathematical Models in Ecology and Evolution, 2011, Groningen, Netherlands. ⟨hal-03038373⟩

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