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      Network Models: An Underutilized Tool in Wildlife Epidemiology?

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          Abstract

          Although the approach of contact network epidemiology has been increasing in popularity for studying transmission of infectious diseases in human populations, it has generally been an underutilized approach for investigating disease outbreaks in wildlife populations. In this paper we explore the differences between the type of data that can be collected on human and wildlife populations, provide an update on recent advances that have been made in wildlife epidemiology by using a network approach, and discuss why networks might have been underutilized and why networks could and should be used more in the future. We conclude with ideas for future directions and a call for field biologists and network modelers to engage in more cross-disciplinary collaboration.

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          Most cited references121

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          Emergence of scaling in random networks

          Systems as diverse as genetic networks or the world wide web are best described as networks with complex topology. A common property of many large networks is that the vertex connectivities follow a scale-free power-law distribution. This feature is found to be a consequence of the two generic mechanisms that networks expand continuously by the addition of new vertices, and new vertices attach preferentially to already well connected sites. A model based on these two ingredients reproduces the observed stationary scale-free distributions, indicating that the development of large networks is governed by robust self-organizing phenomena that go beyond the particulars of the individual systems.
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            Modeling Survival and Testing Biological Hypotheses Using Marked Animals: A Unified Approach with Case Studies

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              Emergence of scaling in random networks

              Systems as diverse as genetic networks or the World Wide Web are best described as networks with complex topology. A common property of many large networks is that the vertex connectivities follow a scale-free power-law distribution. This feature was found to be a consequence of two generic mechanisms: (i) networks expand continuously by the addition of new vertices, and (ii) new vertices attach preferentially to sites that are already well connected. A model based on these two ingredients reproduces the observed stationary scale-free distributions, which indicates that the development of large networks is governed by robust self-organizing phenomena that go beyond the particulars of the individual systems.
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                Author and article information

                Journal
                Interdiscip Perspect Infect Dis
                IPID
                Interdisciplinary Perspectives on Infectious Diseases
                Hindawi Publishing Corporation
                1687-708X
                1687-7098
                2011
                10 March 2011
                : 2011
                : 676949
                Affiliations
                1Boyd Orr Centre for Population and Ecosystem Heath, College of Medical, Veterinary and Life Sciences, University of Glasgow, Glasgow G12 8QQ, UK
                2Section of Integrative Biology, University of Texas, Austin, TX 78712, USA
                Author notes

                Academic Editor: Lauren Meyers

                Article
                10.1155/2011/676949
                3063006
                21527981
                1c3e7673-0517-41a6-991f-c28bfa9dcefc
                Copyright © 2011 M. E. Craft and D. Caillaud.

                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.

                History
                : 20 October 2010
                : 14 December 2010
                Categories
                Review Article

                Infectious disease & Microbiology
                Infectious disease & Microbiology

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