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Numerical identification of epidemic thresholds for susceptible-infected-recovered model on finite-size networks

Epidemic threshold has always been a very hot topic for studying epidemic dynamics on complex networks. The previous studies have provided different theoretical predictions of the epidemic threshold for the susceptible-infected-recovered (SIR) model, but the numerical verification of these theoretic...

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Autores principales: Shu, Panpan, Wang, Wei, Tang, Ming, Do, Younghae
Formato: Online Artículo Texto
Lenguaje:English
Publicado: AIP Publishing LLC 2015
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7112466/
https://www.ncbi.nlm.nih.gov/pubmed/26117098
http://dx.doi.org/10.1063/1.4922153
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author Shu, Panpan
Wang, Wei
Tang, Ming
Do, Younghae
author_facet Shu, Panpan
Wang, Wei
Tang, Ming
Do, Younghae
author_sort Shu, Panpan
collection PubMed
description Epidemic threshold has always been a very hot topic for studying epidemic dynamics on complex networks. The previous studies have provided different theoretical predictions of the epidemic threshold for the susceptible-infected-recovered (SIR) model, but the numerical verification of these theoretical predictions is still lacking. Considering that the large fluctuation of the outbreak size occurs near the epidemic threshold, we propose a novel numerical identification method of SIR epidemic threshold by analyzing the peak of the epidemic variability. Extensive experiments on synthetic and real-world networks demonstrate that the variability measure can successfully give the numerical threshold for the SIR model. The heterogeneous mean-field prediction agrees very well with the numerical threshold, except the case that the networks are disassortative, in which the quenched mean-field prediction is relatively close to the numerical threshold. Moreover, the numerical method presented is also suitable for the susceptible-infected-susceptible model. This work helps to verify the theoretical analysis of epidemic threshold and would promote further studies on the phase transition of epidemic dynamics.
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spelling pubmed-71124662020-04-02 Numerical identification of epidemic thresholds for susceptible-infected-recovered model on finite-size networks Shu, Panpan Wang, Wei Tang, Ming Do, Younghae Chaos Regular Articles Epidemic threshold has always been a very hot topic for studying epidemic dynamics on complex networks. The previous studies have provided different theoretical predictions of the epidemic threshold for the susceptible-infected-recovered (SIR) model, but the numerical verification of these theoretical predictions is still lacking. Considering that the large fluctuation of the outbreak size occurs near the epidemic threshold, we propose a novel numerical identification method of SIR epidemic threshold by analyzing the peak of the epidemic variability. Extensive experiments on synthetic and real-world networks demonstrate that the variability measure can successfully give the numerical threshold for the SIR model. The heterogeneous mean-field prediction agrees very well with the numerical threshold, except the case that the networks are disassortative, in which the quenched mean-field prediction is relatively close to the numerical threshold. Moreover, the numerical method presented is also suitable for the susceptible-infected-susceptible model. This work helps to verify the theoretical analysis of epidemic threshold and would promote further studies on the phase transition of epidemic dynamics. AIP Publishing LLC 2015-06 2015-06-04 /pmc/articles/PMC7112466/ /pubmed/26117098 http://dx.doi.org/10.1063/1.4922153 Text en © 2015 AIP Publishing LLC 1054-1500/2015/25(6)/063104/8/$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
Shu, Panpan
Wang, Wei
Tang, Ming
Do, Younghae
Numerical identification of epidemic thresholds for susceptible-infected-recovered model on finite-size networks
title Numerical identification of epidemic thresholds for susceptible-infected-recovered model on finite-size networks
title_full Numerical identification of epidemic thresholds for susceptible-infected-recovered model on finite-size networks
title_fullStr Numerical identification of epidemic thresholds for susceptible-infected-recovered model on finite-size networks
title_full_unstemmed Numerical identification of epidemic thresholds for susceptible-infected-recovered model on finite-size networks
title_short Numerical identification of epidemic thresholds for susceptible-infected-recovered model on finite-size networks
title_sort numerical identification of epidemic thresholds for susceptible-infected-recovered model on finite-size networks
topic Regular Articles
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7112466/
https://www.ncbi.nlm.nih.gov/pubmed/26117098
http://dx.doi.org/10.1063/1.4922153
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