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Dangerous connections: on binding site models of infectious disease dynamics

We formulate models for the spread of infection on networks that are amenable to analysis in the large population limit. We distinguish three different levels: (1) binding sites, (2) individuals, and (3) the population. In the tradition of physiologically structured population models, the formulatio...

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Autores principales: Leung, Ka Yin, Diekmann, Odo
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer Berlin Heidelberg 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5591628/
https://www.ncbi.nlm.nih.gov/pubmed/27324477
http://dx.doi.org/10.1007/s00285-016-1037-x
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author Leung, Ka Yin
Diekmann, Odo
author_facet Leung, Ka Yin
Diekmann, Odo
author_sort Leung, Ka Yin
collection PubMed
description We formulate models for the spread of infection on networks that are amenable to analysis in the large population limit. We distinguish three different levels: (1) binding sites, (2) individuals, and (3) the population. In the tradition of physiologically structured population models, the formulation starts on the individual level. Influences from the ‘outside world’ on an individual are captured by environmental variables. These environmental variables are population level quantities. A key characteristic of the network models is that individuals can be decomposed into a number of conditionally independent components: each individual has a fixed number of ‘binding sites’ for partners. The Markov chain dynamics of binding sites are described by only a few equations. In particular, individual-level probabilities are obtained from binding-site-level probabilities by combinatorics while population-level quantities are obtained by averaging over individuals in the population. Thus we are able to characterize population-level epidemiological quantities, such as [Formula: see text] , r, the final size, and the endemic equilibrium, in terms of the corresponding variables.
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spelling pubmed-55916282017-09-19 Dangerous connections: on binding site models of infectious disease dynamics Leung, Ka Yin Diekmann, Odo J Math Biol Article We formulate models for the spread of infection on networks that are amenable to analysis in the large population limit. We distinguish three different levels: (1) binding sites, (2) individuals, and (3) the population. In the tradition of physiologically structured population models, the formulation starts on the individual level. Influences from the ‘outside world’ on an individual are captured by environmental variables. These environmental variables are population level quantities. A key characteristic of the network models is that individuals can be decomposed into a number of conditionally independent components: each individual has a fixed number of ‘binding sites’ for partners. The Markov chain dynamics of binding sites are described by only a few equations. In particular, individual-level probabilities are obtained from binding-site-level probabilities by combinatorics while population-level quantities are obtained by averaging over individuals in the population. Thus we are able to characterize population-level epidemiological quantities, such as [Formula: see text] , r, the final size, and the endemic equilibrium, in terms of the corresponding variables. Springer Berlin Heidelberg 2016-06-20 2017 /pmc/articles/PMC5591628/ /pubmed/27324477 http://dx.doi.org/10.1007/s00285-016-1037-x Text en © The Author(s) 2016 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.
spellingShingle Article
Leung, Ka Yin
Diekmann, Odo
Dangerous connections: on binding site models of infectious disease dynamics
title Dangerous connections: on binding site models of infectious disease dynamics
title_full Dangerous connections: on binding site models of infectious disease dynamics
title_fullStr Dangerous connections: on binding site models of infectious disease dynamics
title_full_unstemmed Dangerous connections: on binding site models of infectious disease dynamics
title_short Dangerous connections: on binding site models of infectious disease dynamics
title_sort dangerous connections: on binding site models of infectious disease dynamics
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5591628/
https://www.ncbi.nlm.nih.gov/pubmed/27324477
http://dx.doi.org/10.1007/s00285-016-1037-x
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