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Contact Network Modeling of Flu Epidemics

  • Conference paper
Cellular Automata (ACRI 2008)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 5191))

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Abstract

Using actual census, family and age structure, land-use and population-mobility data, we develop a stochastic cellular automata on a social contact network to study the propagation of influenza epidemics in the UK. In particular, we address age dependency and obtain the contact networks through the analysis of location co-presence. We analyze infection propensities as well as vaccination techniques. The results indicate the relative merits of different vaccination strategies combined with early detection without resorting to mass vaccination of a population.

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Authors and Affiliations

  1. The Computer Laboratory, University of Cambridge, 15 JJ Thomson Avenue, Cambridge, CB3 0FD, U.K.

    Ian X. Y. Leung, Gareth Gibbs, Anil Sorathiya & Pietro Liò

  2. Department of Energy, University of Florence, Via S. Marta 3, 50139 Firenze, Italy; also CSDC and INFN, sez. Firenze,  

    Franco Bagnoli

Authors
  1. Ian X. Y. Leung
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  2. Gareth Gibbs
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  3. Franco Bagnoli
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  4. Anil Sorathiya
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  5. Pietro Liò
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Editor information

Hiroshi Umeo Shin Morishita Katsuhiro Nishinari Toshihiko Komatsuzaki Stefania Bandini

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© 2008 Springer-Verlag Berlin Heidelberg

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Leung, I.X.Y., Gibbs, G., Bagnoli, F., Sorathiya, A., Liò, P. (2008). Contact Network Modeling of Flu Epidemics. In: Umeo, H., Morishita, S., Nishinari, K., Komatsuzaki, T., Bandini, S. (eds) Cellular Automata. ACRI 2008. Lecture Notes in Computer Science, vol 5191. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-79992-4_45

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  • DOI: https://doi.org/10.1007/978-3-540-79992-4_45

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-79991-7

  • Online ISBN: 978-3-540-79992-4

  • eBook Packages: Computer ScienceComputer Science (R0)

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