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Parasite evolution in an age-structured population.

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  • 1Institute of Biology, University of Neuchâtel, Rue Emile-Argand 11, 2000 Neuchâtel, Switzerland.

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Summary
This summary is machine-generated.

Parasite evolution models often ignore host aging. This study shows that incorporating senescence, or host aging, predicts higher parasite virulence and reveals complex evolutionary feedbacks influencing transmission dynamics.

Keywords:
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Area of Science:

  • Evolutionary biology
  • Epidemiology
  • Gerontology

Background:

  • Host mortality typically increases with age, a phenomenon known as senescence.
  • Existing models of parasite evolution often overlook the impact of host senescence.
  • Understanding parasite evolution requires considering host age-specific mortality patterns.

Purpose of the Study:

  • To investigate the role of host senescence in shaping parasite virulence evolution.
  • To explore epi-evolutionary feedbacks between host aging and parasite transmission.
  • To determine how age-structured host populations influence the evolution of parasite virulence.

Main Methods:

  • Developed an age-structured epidemiological model incorporating parasite evolution.
  • Extended traditional models by including senescence-driven mortality rates.
  • Analyzed the impact of host density- and frequency-dependent infection forces on virulence evolution.

Main Results:

  • Stronger host senescence drives the evolution of higher parasite virulence.
  • Evolved virulence is influenced by the average age at infection, creating an evolutionary feedback loop.
  • The mode of infection (density- vs. frequency-dependent) affects equilibrium virulence due to altered average infection ages.

Conclusions:

  • Host senescence significantly impacts parasite virulence evolution, contrary to models assuming constant mortality.
  • Age-specific host effects, particularly senescence, are crucial for accurate predictions in parasite evolution.
  • Ignoring host aging can lead to misleading conclusions about parasite-host dynamics.