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Traffic-driven epidemic outbreak on complex networks: How long does it take?

Recent studies have suggested the necessity to incorporate traffic dynamics into the process of epidemic spreading on complex networks, as the former provides support for the latter in many real-world situations. While there are results on the asymptotic scope of the spreading dynamics, the issue of...

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Detalles Bibliográficos
Autores principales: Yang, Han-Xin, Wang, Wen-Xu, Lai, Ying-Cheng
Formato: Online Artículo Texto
Lenguaje:English
Publicado: American Institute of Physics 2012
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7112479/
https://www.ncbi.nlm.nih.gov/pubmed/23278081
http://dx.doi.org/10.1063/1.4772967
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author Yang, Han-Xin
Wang, Wen-Xu
Lai, Ying-Cheng
author_facet Yang, Han-Xin
Wang, Wen-Xu
Lai, Ying-Cheng
author_sort Yang, Han-Xin
collection PubMed
description Recent studies have suggested the necessity to incorporate traffic dynamics into the process of epidemic spreading on complex networks, as the former provides support for the latter in many real-world situations. While there are results on the asymptotic scope of the spreading dynamics, the issue of how fast an epidemic outbreak can occur remains outstanding. We observe numerically that the density of the infected nodes exhibits an exponential increase with time initially, rendering definable a characteristic time for the outbreak. We then derive a formula for scale-free networks, which relates this time to parameters characterizing the traffic dynamics and the network structure such as packet-generation rate and betweenness distribution. The validity of the formula is tested numerically. Our study indicates that increasing the average degree and/or inducing traffic congestion can slow down the spreading process significantly.
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spelling pubmed-71124792020-04-02 Traffic-driven epidemic outbreak on complex networks: How long does it take? Yang, Han-Xin Wang, Wen-Xu Lai, Ying-Cheng Chaos Regular Articles Recent studies have suggested the necessity to incorporate traffic dynamics into the process of epidemic spreading on complex networks, as the former provides support for the latter in many real-world situations. While there are results on the asymptotic scope of the spreading dynamics, the issue of how fast an epidemic outbreak can occur remains outstanding. We observe numerically that the density of the infected nodes exhibits an exponential increase with time initially, rendering definable a characteristic time for the outbreak. We then derive a formula for scale-free networks, which relates this time to parameters characterizing the traffic dynamics and the network structure such as packet-generation rate and betweenness distribution. The validity of the formula is tested numerically. Our study indicates that increasing the average degree and/or inducing traffic congestion can slow down the spreading process significantly. American Institute of Physics 2012-12 2012-12-28 /pmc/articles/PMC7112479/ /pubmed/23278081 http://dx.doi.org/10.1063/1.4772967 Text en Copyright © 2012 American Institute of Physics 1054-1500/2012/22(4)/043146/5/$30.00 All article content, except where otherwise noted, is licensed under a Creative Commons Attribution (CC BY) license ( http://creativecommons.org/licenses/by/4.0/).
spellingShingle Regular Articles
Yang, Han-Xin
Wang, Wen-Xu
Lai, Ying-Cheng
Traffic-driven epidemic outbreak on complex networks: How long does it take?
title Traffic-driven epidemic outbreak on complex networks: How long does it take?
title_full Traffic-driven epidemic outbreak on complex networks: How long does it take?
title_fullStr Traffic-driven epidemic outbreak on complex networks: How long does it take?
title_full_unstemmed Traffic-driven epidemic outbreak on complex networks: How long does it take?
title_short Traffic-driven epidemic outbreak on complex networks: How long does it take?
title_sort traffic-driven epidemic outbreak on complex networks: how long does it take?
topic Regular Articles
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7112479/
https://www.ncbi.nlm.nih.gov/pubmed/23278081
http://dx.doi.org/10.1063/1.4772967
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