Please use this identifier to cite or link to this item: http://hdl.handle.net/2440/68436
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Type: Journal article
Title: Networks and the epidemiology of infectious disease
Author: Danon, L.
Ford, A.
House, T.
Jewell, C.
Keeling, M.
Roberts, G.
Ross, J.
Vernon, M.
Citation: Interdisciplinary Perspectives on Infectious Diseases, 2011; 2011(284909):284909-1-284909-28
Publisher: Hindawi Publishing Corporation
Issue Date: 2011
ISSN: 1687-708X
1687-7098
Statement of
Responsibility: 
Leon Danon, Ashley P. Ford, Thomas House, Chris P. Jewell, Matt J. Keeling, Gareth O. Roberts, Joshua V. Ross, and Matthew C. Vernon
Abstract: The science of networks has revolutionised research into the dynamics of interacting elements. It could be argued that epidemiology in particular has embraced the potential of network theory more than any other discipline. Here we review the growing body of research concerning the spread of infectious diseases on networks, focusing on the interplay between network theory and epidemiology. The review is split into four main sections, which examine: the types of network relevant to epidemiology; the multitude of ways these networks can be characterised; the statistical methods that can be applied to infer the epidemiological parameters on a realised network; and finally simulation and analytical methods to determine epidemic dynamics on a given network. Given the breadth of areas covered and the ever-expanding number of publications, a comprehensive review of all work is impossible. Instead, we provide a personalised overview into the areas of network epidemiology that have seen the greatest progress in recent years or have the greatest potential to provide novel insights. As such, considerable importance is placed on analytical approaches and statistical methods which are both rapidly expanding fields. Throughout this review we restrict our attention to epidemiological issues.
Description: Extent: 28p.
Rights: Copyright © 2011 Leon Danon et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
RMID: 0020109180
DOI: 10.1155/2011/284909
Appears in Collections:Mathematical Sciences publications

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