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Related Experiment Videos

Evolutionary trade-offs at two time-scales: competition versus persistence.

M Keeling1

  • 1Department of Zoology, University of Cambridge, UK. matt@zoo.cam.ac.uk

Proceedings. Biological Sciences
|March 18, 2000
PubMed
Summary

This study models disease strain evolution, showing that a trade-off between rapid reproduction and long-term survival impacts population dynamics. Understanding these evolutionary dynamics is key for disease control.

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Area of Science:

  • Mathematical Biology
  • Evolutionary Dynamics
  • Epidemiology

Background:

  • Natural systems often exhibit complex dynamics across multiple timescales.
  • Trade-offs between reproductive rate and long-term persistence are common, particularly in disease modeling.
  • Metapopulation models are crucial for understanding disease spread in fragmented habitats.

Purpose of the Study:

  • To develop a mathematical model for the evolutionary dynamics of two competing disease strains in a metapopulation.
  • To analyze the evolutionary behavior when one strain excels in short-term competition and the other in long-term persistence.
  • To derive analytical expressions for evolutionary dynamics in cases of close phenotypic similarity between strains.

Main Methods:

  • Formulation of a simple partial differential equation model.

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  • Analysis of the behavior of means and higher-order moments of the system.
  • Derivation of analytical expressions for evolutionary trajectories.

    • Main Results:

    • The model captures the trade-off between rapid reproduction and long-term persistence in disease strains.
    • Analytical solutions are obtained for the evolutionary dynamics of phenotypically close strains.
    • The interplay between competition and persistence dictates the overall evolutionary outcome.

    Conclusions:

    • The study provides a framework for understanding evolutionary dynamics in metapopulations with competing strains.
    • The findings highlight the importance of considering multiple timescales in disease evolution.
    • The analytical results offer insights into the conditions favoring different evolutionary strategies in pathogens.