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A fully coupled, mechanistic model for infectious disease dynamics in a metapopulation: movement and epidemic

M Jesse1, P Ezanno, S Davis

  • 1Faculty of Veterinary Medicine, Utrecht University, Yalelaan 7, 3584 CL Utrecht, The Netherlands. M.Jesse@uu.nl

Journal of Theoretical Biology
|June 26, 2008
PubMed

Insights

This study introduces a fully coupled, accessible mathematical model for infectious disease spread in metapopulations. The model reveals a non-linear relationship between movement rates and epidemic duration, with peaks at low and high movement rates.

Area of Science:

  • Epidemiology
  • Mathematical Biology
  • Population Dynamics

Background:

  • Understanding infectious disease dynamics in structured populations is crucial for public health.
  • Existing mathematical models for pathogen spread in metapopulations are often not fully coupled or biologically accessible.
  • Fully coupled models, where within- and between-subpopulation transmission are interdependent, are rare.

Purpose of the Study:

  • To present a novel, fully coupled, and biologically accessible mathematical model for infectious disease dynamics in metapopulations.
  • To investigate the relationship between inter-subpopulation movement rates and epidemic duration.
  • To elucidate the mechanisms driving epidemic duration patterns.

Main Methods:

  • Development of a fully coupled mathematical model for pathogen dynamics in metapopulations.
  • The model is designed to be accessible to biologists, with clear parameter meanings and explained assumptions.
  • Analysis of the model to determine the relationship between movement rates and epidemic duration.

Main Results:

  • The duration of an epidemic exhibits a highly non-linear relationship with the rate of movement between subpopulations.
  • A peak in epidemic duration is observed at small movement rates, linked to asynchronous infection dynamics and successful invasion across subpopulations.
  • A global maximum in epidemic duration occurs at large movement rates, where the metapopulation behaves like a single, larger well-mixed population.

Conclusions:

  • Accessible, fully coupled mathematical models can provide significant insights into infectious disease spread.
  • Inter-subpopulation movement rates critically influence epidemic duration through complex, non-linear mechanisms.
  • Understanding these dynamics is essential for predicting and managing infectious disease outbreaks in structured populations.

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