Individual identity and movement networks for disease metapopulations

Matt J. Keeling, Leon Danon, Matthew C. Vernon, Thomas A. House

Research output: Contribution to journalArticle (Academic Journal)peer-review

110 Citations (Scopus)


The theory of networks has had a huge impact in both the physical and life sciences, shaping our understanding of the interaction between multiple elements in complex systems. In particular, networks have been extensively used in predicting the spread of infectious diseases where individuals, or populations of individuals, interact with a limited set of others - defining the network through which the disease can spread. Here for such disease models we consider three assumptions for capturing the network of movements between populations, and focus on two applied problems supported by detailed data from Great Britain: the commuter movement of workers between local areas (wards) and the permanent movement of cattle between farms. For such metapopulation networks, we show that the identity of individuals responsible for making network connections can have a significant impact on the infection dynamics, with clear implications for detailed public health and veterinary applications.

Original languageEnglish
Pages (from-to)8866-8870
Number of pages5
JournalProceedings of the National Academy of Sciences of the United States of America
Issue number19
Publication statusPublished - 11 May 2010


  • Epidemic
  • Individuality
  • Influenza
  • Model
  • Smallpox


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