Agent-based modelling reveals feedback loops and non-linearity between mating system evolution and disease dynamics

Despite its potential for providing a deeper understanding of both evolutionary processes and epidemic dynamics, the reciprocal interrelationship between mating system evolution and sexually transmitted diseases remains largely unexplored. Here we developed an agent-based model simulating the evolution of two different female mating strategies (monandry versus polyandry) under the spread of a hypothetical sexually transmitted disease implying reproductive costs. Our results strongly support the existence of feedback loops between the pathogen's transmissibility and the evolution of mating strategies. Importantly, we found several unexpected, non-linear emerging behaviours of the system, as well as tipping points which were undocumented under the conditions we considered here: i) medium-high/high probabilities of disease transmission per sexual contact reveal switches between disease-free and endemic outcomes, ii) counterintuitively, the disappearance of the pathogen might be a good indicator and predictor of the imminent extinction of the polyandrous genotype/phenotype/strategy from the population, and iii) probabilities of transmission above a medium-low threshold can offset the spread of polyandry even when this behaviour entails pronounced benefits. More broadly, our results illustrate that research into reciprocal influences between the dynamics of disease spread and sexual behaviour can provide valuable insights into disease transmission and the evolution of reproductive strategies, as well as into the sensitivity of mating systems' evolution to small variations in ecological and disease contexts.

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Publication Details

Journal
PLoS ONE
Published
2025-12-18
DOI
https://doi.org/10.1371/journal.pone.0336020
Primary Topic
Evolution and Genetic Dynamics
Type
article
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article

Agent-based modelling reveals feedback loops and non-linearity between mating system evolution and disease dynamics

Riccardo Tarantino, Francisco García–González
PLoS ONE
Evolution and Genetic Dynamics
article

Agent-based modelling reveals feedback loops and non-linearity between mating system evolution and disease dynamics

Riccardo Tarantino, Francisco García–González
article en

Abstract

Despite its potential for providing a deeper understanding of both evolutionary processes and epidemic dynamics, the reciprocal interrelationship between mating system evolution and sexually transmitted diseases remains largely unexplored. Here we developed an agent-based model simulating the evolution of two different female mating strategies (monandry versus polyandry) under the spread of a hypothetical sexually transmitted disease implying reproductive costs. Our results strongly support the existence of feedback loops between the pathogen's transmissibility and the evolution of mating strategies. Importantly, we found several unexpected, non-linear emerging behaviours of the system, as well as tipping points which were undocumented under the conditions we considered here: i) medium-high/high probabilities of disease transmission per sexual contact reveal switches between disease-free and endemic outcomes, ii) counterintuitively, the disappearance of the pathogen might be a good indicator and predictor of the imminent extinction of the polyandrous genotype/phenotype/strategy from the population, and iii) probabilities of transmission above a medium-low threshold can offset the spread of polyandry even when this behaviour entails pronounced benefits. More broadly, our results illustrate that research into reciprocal influences between the dynamics of disease spread and sexual behaviour can provide valuable insights into disease transmission and the evolution of reproductive strategies, as well as into the sensitivity of mating systems' evolution to small variations in ecological and disease contexts.

PLoS ONEVol. 20(12)
The University of Western Australia (AU), Estación Biológica de Doñana (ES), University of Palermo (IT)
Openalex Percentile: Top 57%
Evolution and Genetic Dynamics
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Agent-based modelling reveals feedback loops and non-linearity between mating system evolution and disease dynamics — Riccardo Tarantino, Francisco García–González · PLoS ONE (2025) | TGRS Research Map | TGRS