Cargando…

Estimating the epidemic threshold on networks by deterministic connections

For many epidemic networks some connections between nodes are treated as deterministic, while the remainder are random and have different connection probabilities. By applying spectral analysis to several constructed models, we find that one can estimate the epidemic thresholds of these networks by...

Descripción completa

Detalles Bibliográficos
Autores principales: Li, Kezan, Fu, Xinchu, Small, Michael, Zhu, Guanghu
Formato: Online Artículo Texto
Lenguaje:English
Publicado: AIP Publishing LLC 2014
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7112486/
https://www.ncbi.nlm.nih.gov/pubmed/25554044
http://dx.doi.org/10.1063/1.4901334
_version_ 1783513485000310784
author Li, Kezan
Fu, Xinchu
Small, Michael
Zhu, Guanghu
author_facet Li, Kezan
Fu, Xinchu
Small, Michael
Zhu, Guanghu
author_sort Li, Kezan
collection PubMed
description For many epidemic networks some connections between nodes are treated as deterministic, while the remainder are random and have different connection probabilities. By applying spectral analysis to several constructed models, we find that one can estimate the epidemic thresholds of these networks by investigating information from only the deterministic connections. Nonetheless, in these models, generic nonuniform stochastic connections and heterogeneous community structure are also considered. The estimation of epidemic thresholds is achieved via inequalities with upper and lower bounds, which are found to be in very good agreement with numerical simulations. Since these deterministic connections are easier to detect than those stochastic connections, this work provides a feasible and effective method to estimate the epidemic thresholds in real epidemic networks.
format Online
Article
Text
id pubmed-7112486
institution National Center for Biotechnology Information
language English
publishDate 2014
publisher AIP Publishing LLC
record_format MEDLINE/PubMed
spelling pubmed-71124862020-04-02 Estimating the epidemic threshold on networks by deterministic connections Li, Kezan Fu, Xinchu Small, Michael Zhu, Guanghu Chaos Regular Articles For many epidemic networks some connections between nodes are treated as deterministic, while the remainder are random and have different connection probabilities. By applying spectral analysis to several constructed models, we find that one can estimate the epidemic thresholds of these networks by investigating information from only the deterministic connections. Nonetheless, in these models, generic nonuniform stochastic connections and heterogeneous community structure are also considered. The estimation of epidemic thresholds is achieved via inequalities with upper and lower bounds, which are found to be in very good agreement with numerical simulations. Since these deterministic connections are easier to detect than those stochastic connections, this work provides a feasible and effective method to estimate the epidemic thresholds in real epidemic networks. AIP Publishing LLC 2014-12 2014-11-12 /pmc/articles/PMC7112486/ /pubmed/25554044 http://dx.doi.org/10.1063/1.4901334 Text en © 2014 AIP Publishing LLC 1054-1500/2014/24(4)/043124/9/$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
Li, Kezan
Fu, Xinchu
Small, Michael
Zhu, Guanghu
Estimating the epidemic threshold on networks by deterministic connections
title Estimating the epidemic threshold on networks by deterministic connections
title_full Estimating the epidemic threshold on networks by deterministic connections
title_fullStr Estimating the epidemic threshold on networks by deterministic connections
title_full_unstemmed Estimating the epidemic threshold on networks by deterministic connections
title_short Estimating the epidemic threshold on networks by deterministic connections
title_sort estimating the epidemic threshold on networks by deterministic connections
topic Regular Articles
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7112486/
https://www.ncbi.nlm.nih.gov/pubmed/25554044
http://dx.doi.org/10.1063/1.4901334
work_keys_str_mv AT likezan estimatingtheepidemicthresholdonnetworksbydeterministicconnections
AT fuxinchu estimatingtheepidemicthresholdonnetworksbydeterministicconnections
AT smallmichael estimatingtheepidemicthresholdonnetworksbydeterministicconnections
AT zhuguanghu estimatingtheepidemicthresholdonnetworksbydeterministicconnections