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Structured Modeling and Analysis of Stochastic Epidemics with Immigration and Demographic Effects

Stochastic epidemics with open populations of variable population sizes are considered where due to immigration and demographic effects the epidemic does not eventually die out forever. The underlying stochastic processes are ergodic multi-dimensional continuous-time Markov chains that possess uniqu...

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Detalles Bibliográficos
Autores principales: Baumann, Hendrik, Sandmann, Werner
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4806999/
https://www.ncbi.nlm.nih.gov/pubmed/27010993
http://dx.doi.org/10.1371/journal.pone.0152144
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author Baumann, Hendrik
Sandmann, Werner
author_facet Baumann, Hendrik
Sandmann, Werner
author_sort Baumann, Hendrik
collection PubMed
description Stochastic epidemics with open populations of variable population sizes are considered where due to immigration and demographic effects the epidemic does not eventually die out forever. The underlying stochastic processes are ergodic multi-dimensional continuous-time Markov chains that possess unique equilibrium probability distributions. Modeling these epidemics as level-dependent quasi-birth-and-death processes enables efficient computations of the equilibrium distributions by matrix-analytic methods. Numerical examples for specific parameter sets are provided, which demonstrates that this approach is particularly well-suited for studying the impact of varying rates for immigration, births, deaths, infection, recovery from infection, and loss of immunity.
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spelling pubmed-48069992016-03-25 Structured Modeling and Analysis of Stochastic Epidemics with Immigration and Demographic Effects Baumann, Hendrik Sandmann, Werner PLoS One Research Article Stochastic epidemics with open populations of variable population sizes are considered where due to immigration and demographic effects the epidemic does not eventually die out forever. The underlying stochastic processes are ergodic multi-dimensional continuous-time Markov chains that possess unique equilibrium probability distributions. Modeling these epidemics as level-dependent quasi-birth-and-death processes enables efficient computations of the equilibrium distributions by matrix-analytic methods. Numerical examples for specific parameter sets are provided, which demonstrates that this approach is particularly well-suited for studying the impact of varying rates for immigration, births, deaths, infection, recovery from infection, and loss of immunity. Public Library of Science 2016-03-24 /pmc/articles/PMC4806999/ /pubmed/27010993 http://dx.doi.org/10.1371/journal.pone.0152144 Text en © 2016 Baumann, Sandmann http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Baumann, Hendrik
Sandmann, Werner
Structured Modeling and Analysis of Stochastic Epidemics with Immigration and Demographic Effects
title Structured Modeling and Analysis of Stochastic Epidemics with Immigration and Demographic Effects
title_full Structured Modeling and Analysis of Stochastic Epidemics with Immigration and Demographic Effects
title_fullStr Structured Modeling and Analysis of Stochastic Epidemics with Immigration and Demographic Effects
title_full_unstemmed Structured Modeling and Analysis of Stochastic Epidemics with Immigration and Demographic Effects
title_short Structured Modeling and Analysis of Stochastic Epidemics with Immigration and Demographic Effects
title_sort structured modeling and analysis of stochastic epidemics with immigration and demographic effects
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4806999/
https://www.ncbi.nlm.nih.gov/pubmed/27010993
http://dx.doi.org/10.1371/journal.pone.0152144
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