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

The drive to understand the invasion, spread and fade out of infectious disease in structured populations has produced a variety of mathematical models for pathogen dynamics in metapopulations. Very rarely are these models fully coupled, by which we mean that the spread of an infection within a subp...

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Bibliographic Details
Published inJournal of theoretical biology Vol. 254; no. 2; pp. 331 - 338
Main Authors Jesse, M., Ezanno, P., Davis, S., Heesterbeek, J.A.P.
Format Journal Article
LanguageEnglish
Published England Elsevier Ltd 21.09.2008
Elsevier
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Summary:The drive to understand the invasion, spread and fade out of infectious disease in structured populations has produced a variety of mathematical models for pathogen dynamics in metapopulations. Very rarely are these models fully coupled, by which we mean that the spread of an infection within a subpopulation affects the transmission between subpopulations and vice versa. It is also rare that these models are accessible to biologists, in the sense that all parameters have a clear biological meaning and the biological assumptions are explained. Here we present an accessible model that is fully coupled without being an individual-based model. We use the model to show that the duration of an epidemic has a highly non-linear relationship with the movement rate between subpopulations, with a peak in epidemic duration appearing at small movement rates and a global maximum at large movement rates. Intuitively, the first peak is due to asynchrony in the dynamics of infection between subpopulations; we confirm this intuition and also show the peak coincides with successful invasion of the infection into most subpopulations. The global maximum at relatively large movement rates occurs because then the infectious agent perceives the metapopulation as if it is a single well-mixed population wherein the effective population size is greater than the critical community size.
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ISSN:0022-5193
1095-8541
DOI:10.1016/j.jtbi.2008.05.038