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Networks in Epidemiology

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Bio-Inspired Computing and Communication (BIOWIRE 2007)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 5151))

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Abstract

We discuss the uses of networks as epidemiological tools to describe the interactions taking place within populations. The difficulties of accurate measurement of real-world social networks are discussed, along with modelling approaches designed to require only incomplete data. Properties of human contact networks such as clustering and variable strengths of interactions are seen to be important factors in the spread of an epidemic. We consider the evolution of a pathogen spreading through a dynamic network and show that the pattern of contacts within a host population determines the evolutionary pressures that a pathogen experiences.

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Author information

Authors and Affiliations

  1. DAMTP, Centre for Mathematical Sciences, Wilberforce Road, Cambridge, CB3 0WA, UK

    Ken T. D. Eames

  2. Faculty of Veterinary Science, University of Liverpool, Leahurst Campus, The Wirral, CH64 7TE, UK

    Jonathan M. Read

Authors
  1. Ken T. D. Eames
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  2. Jonathan M. Read
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Editor information

Editors and Affiliations

  1. The Computer Laboratory, University of Cambridge, William Gates Building, 15 JJ Thomson Avenue, CB3 0FD,, Cambridge, UK

    Pietro Liò

  2. Cambridge, UK

    Eiko Yoneki

  3. Cambridge University, UK

    Jon Crowcroft

  4. IBM TJ Watson Research Center, 704 Yorktown Heights, NY 10598, USA

    Dinesh C. Verma

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© 2008 Springer-Verlag Berlin Heidelberg

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Eames, K.T.D., Read, J.M. (2008). Networks in Epidemiology. In: Liò, P., Yoneki, E., Crowcroft, J., Verma, D.C. (eds) Bio-Inspired Computing and Communication. BIOWIRE 2007. Lecture Notes in Computer Science, vol 5151. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-92191-2_8

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  • DOI: https://doi.org/10.1007/978-3-540-92191-2_8

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-92190-5

  • Online ISBN: 978-3-540-92191-2

  • eBook Packages: Computer ScienceComputer Science (R0)

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