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Networks and the ecology of parasite transmission: A framework for wildlife parasitology()

Social network analysis has recently emerged as a popular tool for understanding disease transmission in host populations. Although social networks have most extensively been applied to modelling the transmission of diseases through human populations, more recently the method has been applied to wil...

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Autor principal: Godfrey, Stephanie S.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2013
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3862525/
https://www.ncbi.nlm.nih.gov/pubmed/24533342
http://dx.doi.org/10.1016/j.ijppaw.2013.09.001
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author Godfrey, Stephanie S.
author_facet Godfrey, Stephanie S.
author_sort Godfrey, Stephanie S.
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description Social network analysis has recently emerged as a popular tool for understanding disease transmission in host populations. Although social networks have most extensively been applied to modelling the transmission of diseases through human populations, more recently the method has been applied to wildlife populations. The majority of examples from wildlife involve modelling the transmission of contagious microbes (mainly viruses and bacteria), normally in context of understanding wildlife disease epidemics. However, a growing number of studies have used networks to explore the ecology of parasite transmission in wildlife populations for a range of endemic parasites representing a diversity of life cycles and transmission methods. This review addresses the application of network models in representing the transmission of parasites with more complex life cycles, and illustrates the way in which this approach can be used to answer ecological questions about the transmission of parasites in wildlife populations.
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spelling pubmed-38625252014-02-11 Networks and the ecology of parasite transmission: A framework for wildlife parasitology() Godfrey, Stephanie S. Int J Parasitol Parasites Wildl Invited Review Social network analysis has recently emerged as a popular tool for understanding disease transmission in host populations. Although social networks have most extensively been applied to modelling the transmission of diseases through human populations, more recently the method has been applied to wildlife populations. The majority of examples from wildlife involve modelling the transmission of contagious microbes (mainly viruses and bacteria), normally in context of understanding wildlife disease epidemics. However, a growing number of studies have used networks to explore the ecology of parasite transmission in wildlife populations for a range of endemic parasites representing a diversity of life cycles and transmission methods. This review addresses the application of network models in representing the transmission of parasites with more complex life cycles, and illustrates the way in which this approach can be used to answer ecological questions about the transmission of parasites in wildlife populations. Elsevier 2013-09-18 /pmc/articles/PMC3862525/ /pubmed/24533342 http://dx.doi.org/10.1016/j.ijppaw.2013.09.001 Text en © 2013 The Author http://creativecommons.org/licenses/by-nc-nd/3.0/ This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/3.0/).
spellingShingle Invited Review
Godfrey, Stephanie S.
Networks and the ecology of parasite transmission: A framework for wildlife parasitology()
title Networks and the ecology of parasite transmission: A framework for wildlife parasitology()
title_full Networks and the ecology of parasite transmission: A framework for wildlife parasitology()
title_fullStr Networks and the ecology of parasite transmission: A framework for wildlife parasitology()
title_full_unstemmed Networks and the ecology of parasite transmission: A framework for wildlife parasitology()
title_short Networks and the ecology of parasite transmission: A framework for wildlife parasitology()
title_sort networks and the ecology of parasite transmission: a framework for wildlife parasitology()
topic Invited Review
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3862525/
https://www.ncbi.nlm.nih.gov/pubmed/24533342
http://dx.doi.org/10.1016/j.ijppaw.2013.09.001
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