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Mathematics of Epidemics on Networks pp 273–301Cite as

Dynamic and adaptive networks

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Part of the book series: Interdisciplinary Applied Mathematics ((IAM,volume 46))

Abstract

An important feature of many real-world networks is the transient nature of some interactions. Thus far, our models have explicitly assumed that the network is static. That is, we assume that the rate of partner turnover is so slow that we can ignore its impact on epidemic dynamics.Over the past decade, there has been tremendous progress in modelling and analysing disease spread in non-static networks, i.e. networks whose structure changes due to endogenous or exogenous factors, or because of the disease dynamics unfolding on the network. The terminology used to describe such networks is not standardised. We summarise some common terminology and link it to the relation between the time scales of the dynamics on the network and the dynamics of the network. Ordered from static to networks that change quickly, we have:

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Author information

Authors and Affiliations

  1. Department of Mathematics, University of Sussex, Falmer, Brighton, UK

    István Z. Kiss

  2. Applied Mathematics, Institute for Disease Modeling, Bellevue, WA, USA

    Joel C. Miller

  3. Institute of Mathematics, Eötvös Loránd University, Budapest, Hungary

    Péter L. Simon

Authors
  1. István Z. Kiss
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  2. Joel C. Miller
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  3. Péter L. Simon
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Kiss, I.Z., Miller, J.C., Simon, P.L. (2017). Dynamic and adaptive networks. In: Mathematics of Epidemics on Networks. Interdisciplinary Applied Mathematics, vol 46. Springer, Cham. https://doi.org/10.1007/978-3-319-50806-1_8

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