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Estimating spatial coupling in epidemiological systems: a mechanistic approach
Authors:Matt J. Keeling,&   Pejman Rohani
Affiliation:Department of Zoology, University of Cambridge, Downing Street, Cambridge CB2 3EJ, U.K. Tel./Fax: +44 1223 330110. E-mail:;, Institute of Ecology, University of Georgia, Athens, GA 30602, U.S.A.
Abstract:In recent years, ecologists and epidemiologists have paid increasing attention to the influence of spatial structure in shaping the dynamics and determining the persistence of populations. This is fundamentally affected by the concept of 'coupling'—the flux of individuals moving between separate populations. In this paper, we contrast how coupling is typically implemented in epidemic models with more detailed approaches. Our aim is to link the popular phenomenological formulations with the results of mechanistic models. By concentrating on the behaviour of simple epidemic systems, we relate explicit movement patterns with observed levels of coupling, validating the standard formulation. The analysis is then extended to include a brief study of how the correlation between stochastic populations is affected by coupling, the underlying deterministic dynamics and the relative population sizes.
Keywords:Disease models    movement    stochasticity    correlation    dispersal    synchrony    seasonality    population dynamics
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