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Five challenges for stochastic epidemic models involving global transmission

The most basic stochastic epidemic models are those involving global transmission, meaning that infection rates depend only on the type and state of the individuals involved, and not on their location in the population. Simple as they are, there are still several open problems for such models. For e...

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Detalles Bibliográficos
Autores principales: Britton, Tom, House, Thomas, Lloyd, Alun L., Mollison, Denis, Riley, Steven, Trapman, Pieter
Formato: Online Artículo Texto
Lenguaje:English
Publicado: 2014
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4996665/
https://www.ncbi.nlm.nih.gov/pubmed/25843384
http://dx.doi.org/10.1016/j.epidem.2014.05.002
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author Britton, Tom
House, Thomas
Lloyd, Alun L.
Mollison, Denis
Riley, Steven
Trapman, Pieter
author_facet Britton, Tom
House, Thomas
Lloyd, Alun L.
Mollison, Denis
Riley, Steven
Trapman, Pieter
author_sort Britton, Tom
collection PubMed
description The most basic stochastic epidemic models are those involving global transmission, meaning that infection rates depend only on the type and state of the individuals involved, and not on their location in the population. Simple as they are, there are still several open problems for such models. For example, when will such an epidemic go extinct and with what probability (questions depending on the population being fixed, changing or growing)? How can a model be defined explaining the sometimes observed scenario of frequent mid-sized epidemic outbreaks? How can evolution of the infectious agent transmission rates be modelled and fitted to data in a robust way?
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spelling pubmed-49966652016-08-24 Five challenges for stochastic epidemic models involving global transmission Britton, Tom House, Thomas Lloyd, Alun L. Mollison, Denis Riley, Steven Trapman, Pieter Epidemics Article The most basic stochastic epidemic models are those involving global transmission, meaning that infection rates depend only on the type and state of the individuals involved, and not on their location in the population. Simple as they are, there are still several open problems for such models. For example, when will such an epidemic go extinct and with what probability (questions depending on the population being fixed, changing or growing)? How can a model be defined explaining the sometimes observed scenario of frequent mid-sized epidemic outbreaks? How can evolution of the infectious agent transmission rates be modelled and fitted to data in a robust way? 2014-06-05 2015-03 /pmc/articles/PMC4996665/ /pubmed/25843384 http://dx.doi.org/10.1016/j.epidem.2014.05.002 Text en This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/3.0/).
spellingShingle Article
Britton, Tom
House, Thomas
Lloyd, Alun L.
Mollison, Denis
Riley, Steven
Trapman, Pieter
Five challenges for stochastic epidemic models involving global transmission
title Five challenges for stochastic epidemic models involving global transmission
title_full Five challenges for stochastic epidemic models involving global transmission
title_fullStr Five challenges for stochastic epidemic models involving global transmission
title_full_unstemmed Five challenges for stochastic epidemic models involving global transmission
title_short Five challenges for stochastic epidemic models involving global transmission
title_sort five challenges for stochastic epidemic models involving global transmission
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4996665/
https://www.ncbi.nlm.nih.gov/pubmed/25843384
http://dx.doi.org/10.1016/j.epidem.2014.05.002
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