Representing the UK's cattle herd as static and dynamic networks

Network models are increasingly being used to understand the spread of diseases through sparsely connected populations, with particular interest in the impact of animal movements upon the dynamics of infectious diseases. Detailed data collected by the UK government on the movement of cattle may be r...

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Published inProceedings of the Royal Society. B, Biological sciences Vol. 276; no. 1656; pp. 469 - 476
Main Authors Vernon, Matthew C, Keeling, Matt J
Format Journal Article
LanguageEnglish
Published London The Royal Society 07.02.2009
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ISSN0962-8452
1471-2954
DOI10.1098/rspb.2008.1009

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Summary:Network models are increasingly being used to understand the spread of diseases through sparsely connected populations, with particular interest in the impact of animal movements upon the dynamics of infectious diseases. Detailed data collected by the UK government on the movement of cattle may be represented as a network, where animal holdings are nodes, and an edge is drawn between nodes where a movement of animals has occurred. These network representations may vary from a simple static representation, to a more complex, fully dynamic one where daily movements are explicitly captured. Using stochastic disease simulations, a wide range of network representations of the UK cattle herd are compared. We find that the simpler static network representations are often deficient when compared with a fully dynamic representation, and should therefore be used only with caution in epidemiological modelling. In particular, due to temporal structures within the dynamic network, static networks consistently fail to capture the predicted epidemic behaviour associated with dynamic networks even when parameterized to match early growth rates.
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ArticleID:rspb20081009
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ISSN:0962-8452
1471-2954
DOI:10.1098/rspb.2008.1009