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Related Experiment Videos

Modelling pathogen transmission: the interrelationship between local and global approaches.

Joanne Turner1, Michael Begon, Roger G Bowers

  • 1Department of Mathematical Sciences, The University of Liverpool, M&O Building, Peach Street, Liverpool L69 7ZL, UK. j.turner@liv.ac.uk

Proceedings. Biological Sciences
|February 20, 2003
PubMed
Summary

This study introduces two spatial host-pathogen models (fixed contact area and fixed contact number) that simulate local transmission. The fixed contact area model better reflects real-world epidemics by slowing spread and reducing infection prevalence.

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Area of Science:

  • Epidemiology
  • Mathematical Biology
  • Computational Science

Background:

  • Host-pathogen dynamics are often modeled using global transmission terms.
  • Local transmission mechanisms are crucial for realistic epidemic simulations.
  • Spatial models offer a more nuanced understanding of disease spread.

Purpose of the Study:

  • To introduce and compare two spatial host-pathogen models (FCA and FCN) based on local interactions.
  • To evaluate the performance of global transmission terms against these local models.
  • To determine the most appropriate global transmission term for varying population sizes.

Main Methods:

  • Development of two spatial cellular automaton models: Fixed Contact Area (FCA) and Fixed Contact Number (FCN).
  • Comparison of model outputs with each other and with global density-dependent (betaSI) and frequency-dependent (beta'SI/N) transmission terms.

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  • Utilizing generalized linear modeling to analyze transmission patterns under different population conditions.

    • Main Results:

    • The FCA model impedes pathogen spread in unoccupied cells, prolonging epidemics and reducing persistent infection prevalence compared to FCN.
    • Global terms (betaSI and beta'SI/N) accurately describe transmission in both FCA and FCN models under homogeneous distribution and constant population size.
    • The global frequency-dependent term (beta'SI/N) is superior to the density-dependent term (betaSI) when population size (N) varies.

    Conclusions:

    • Spatial host-pathogen models with local transmission provide biologically realistic insights.
    • The choice of global transmission term is critical and depends on population dynamics.
    • This framework allows for the comparison of local contact structures and selection of appropriate global transmission terms for epidemiological modeling.