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Extinction Times of Epidemic Outbreaks in Networks

In the Susceptible–Infectious–Recovered (SIR) model of disease spreading, the time to extinction of the epidemics happens at an intermediate value of the per-contact transmission probability. Too contagious infections burn out fast in the population. Infections that are not contagious enough die out...

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Autor principal: Holme, Petter
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2013
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3873427/
https://www.ncbi.nlm.nih.gov/pubmed/24386377
http://dx.doi.org/10.1371/journal.pone.0084429
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author Holme, Petter
author_facet Holme, Petter
author_sort Holme, Petter
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description In the Susceptible–Infectious–Recovered (SIR) model of disease spreading, the time to extinction of the epidemics happens at an intermediate value of the per-contact transmission probability. Too contagious infections burn out fast in the population. Infections that are not contagious enough die out before they spread to a large fraction of people. We characterize how the maximal extinction time in SIR simulations on networks depend on the network structure. For example we find that the average distances in isolated components, weighted by the component size, is a good predictor of the maximal time to extinction. Furthermore, the transmission probability giving the longest outbreaks is larger than, but otherwise seemingly independent of, the epidemic threshold.
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spelling pubmed-38734272014-01-02 Extinction Times of Epidemic Outbreaks in Networks Holme, Petter PLoS One Research Article In the Susceptible–Infectious–Recovered (SIR) model of disease spreading, the time to extinction of the epidemics happens at an intermediate value of the per-contact transmission probability. Too contagious infections burn out fast in the population. Infections that are not contagious enough die out before they spread to a large fraction of people. We characterize how the maximal extinction time in SIR simulations on networks depend on the network structure. For example we find that the average distances in isolated components, weighted by the component size, is a good predictor of the maximal time to extinction. Furthermore, the transmission probability giving the longest outbreaks is larger than, but otherwise seemingly independent of, the epidemic threshold. Public Library of Science 2013-12-26 /pmc/articles/PMC3873427/ /pubmed/24386377 http://dx.doi.org/10.1371/journal.pone.0084429 Text en © 2013 Petter Holme http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited.
spellingShingle Research Article
Holme, Petter
Extinction Times of Epidemic Outbreaks in Networks
title Extinction Times of Epidemic Outbreaks in Networks
title_full Extinction Times of Epidemic Outbreaks in Networks
title_fullStr Extinction Times of Epidemic Outbreaks in Networks
title_full_unstemmed Extinction Times of Epidemic Outbreaks in Networks
title_short Extinction Times of Epidemic Outbreaks in Networks
title_sort extinction times of epidemic outbreaks in networks
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3873427/
https://www.ncbi.nlm.nih.gov/pubmed/24386377
http://dx.doi.org/10.1371/journal.pone.0084429
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