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Suppression of epidemic spreading in complex networks by local information based behavioral responses
The interplay between individual behaviors and epidemic dynamics in complex networks is a topic of recent interest. In particular, individuals can obtain different types of information about the disease and respond by altering their behaviors, and this can affect the spreading dynamics, possibly in...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
AIP Publishing LLC
2014
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7112481/ https://www.ncbi.nlm.nih.gov/pubmed/25554026 http://dx.doi.org/10.1063/1.4896333 |
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author | Zhang, Hai-Feng Xie, Jia-Rong Tang, Ming Lai, Ying-Cheng |
author_facet | Zhang, Hai-Feng Xie, Jia-Rong Tang, Ming Lai, Ying-Cheng |
author_sort | Zhang, Hai-Feng |
collection | PubMed |
description | The interplay between individual behaviors and epidemic dynamics in complex networks is a topic of recent interest. In particular, individuals can obtain different types of information about the disease and respond by altering their behaviors, and this can affect the spreading dynamics, possibly in a significant way. We propose a model where individuals' behavioral response is based on a generic type of local information, i.e., the number of neighbors that has been infected with the disease. Mathematically, the response can be characterized by a reduction in the transmission rate by a factor that depends on the number of infected neighbors. Utilizing the standard susceptible-infected-susceptible and susceptible-infected-recovery dynamical models for epidemic spreading, we derive a theoretical formula for the epidemic threshold and provide numerical verification. Our analysis lays on a solid quantitative footing the intuition that individual behavioral response can in general suppress epidemic spreading. Furthermore, we find that the hub nodes play the role of “double-edged sword” in that they can either suppress or promote outbreak, depending on their responses to the epidemic, providing additional support for the idea that these nodes are key to controlling epidemic spreading in complex networks. |
format | Online Article Text |
id | pubmed-7112481 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2014 |
publisher | AIP Publishing LLC |
record_format | MEDLINE/PubMed |
spelling | pubmed-71124812020-04-02 Suppression of epidemic spreading in complex networks by local information based behavioral responses Zhang, Hai-Feng Xie, Jia-Rong Tang, Ming Lai, Ying-Cheng Chaos Regular Articles The interplay between individual behaviors and epidemic dynamics in complex networks is a topic of recent interest. In particular, individuals can obtain different types of information about the disease and respond by altering their behaviors, and this can affect the spreading dynamics, possibly in a significant way. We propose a model where individuals' behavioral response is based on a generic type of local information, i.e., the number of neighbors that has been infected with the disease. Mathematically, the response can be characterized by a reduction in the transmission rate by a factor that depends on the number of infected neighbors. Utilizing the standard susceptible-infected-susceptible and susceptible-infected-recovery dynamical models for epidemic spreading, we derive a theoretical formula for the epidemic threshold and provide numerical verification. Our analysis lays on a solid quantitative footing the intuition that individual behavioral response can in general suppress epidemic spreading. Furthermore, we find that the hub nodes play the role of “double-edged sword” in that they can either suppress or promote outbreak, depending on their responses to the epidemic, providing additional support for the idea that these nodes are key to controlling epidemic spreading in complex networks. AIP Publishing LLC 2014-12 2014-10-20 /pmc/articles/PMC7112481/ /pubmed/25554026 http://dx.doi.org/10.1063/1.4896333 Text en © 2014 AIP Publishing LLC 1054-1500/2014/24(4)/043106/7/$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 Zhang, Hai-Feng Xie, Jia-Rong Tang, Ming Lai, Ying-Cheng Suppression of epidemic spreading in complex networks by local information based behavioral responses |
title | Suppression of epidemic spreading in complex networks by local information
based behavioral responses |
title_full | Suppression of epidemic spreading in complex networks by local information
based behavioral responses |
title_fullStr | Suppression of epidemic spreading in complex networks by local information
based behavioral responses |
title_full_unstemmed | Suppression of epidemic spreading in complex networks by local information
based behavioral responses |
title_short | Suppression of epidemic spreading in complex networks by local information
based behavioral responses |
title_sort | suppression of epidemic spreading in complex networks by local information
based behavioral responses |
topic | Regular Articles |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7112481/ https://www.ncbi.nlm.nih.gov/pubmed/25554026 http://dx.doi.org/10.1063/1.4896333 |
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