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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...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
2014
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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? |
format | Online Article Text |
id | pubmed-4996665 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2014 |
record_format | MEDLINE/PubMed |
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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