Epidemic Dynamics in Temporal Clustered Networks with Local-World Structure

Population demography can change the network structure, which further plays an important role in the spreading of infectious disease. In this paper, we study the epidemic dynamics in temporal clustered networks where the local-world structure and clustering are incorporated into the attachment mecha...

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Main Authors: Wenjun Jing, Juping Zhang, Xiaoqin Zhang
Format: Article
Language:English
Published: Hindawi-Wiley 2023-01-01
Series:Complexity
Online Access:http://dx.doi.org/10.1155/2023/4591403
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author Wenjun Jing
Juping Zhang
Xiaoqin Zhang
author_facet Wenjun Jing
Juping Zhang
Xiaoqin Zhang
author_sort Wenjun Jing
collection DOAJ
description Population demography can change the network structure, which further plays an important role in the spreading of infectious disease. In this paper, we study the epidemic dynamics in temporal clustered networks where the local-world structure and clustering are incorporated into the attachment mechanism of new nodes. It is found that increasing the local-world size of new nodes has little influence on the clustering coefficient but increases the degree heterogeneity of networks. Besides, when the network evolves faster, increasing the local-world size of new nodes leads to a faster initial growth rate and a larger steady density of infectious nodes, while it has small impacts on the steady density of infectious disease when the network evolves slowly. Furthermore, if the average degree is fixed, increasing the probability of triad formation p enlarges the clustering coefficient of a network, which reduces the initial growth rate and steady density of infectious nodes in the network. This work could provide a theoretical foundation for the control of infectious disease.
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spelling doaj.art-d5dab6cd7cca4339b2737987d55c2d9e2023-02-13T01:08:24ZengHindawi-WileyComplexity1099-05262023-01-01202310.1155/2023/4591403Epidemic Dynamics in Temporal Clustered Networks with Local-World StructureWenjun Jing0Juping Zhang1Xiaoqin Zhang2School of StatisticsComplex Systems Research CenterSchool of StatisticsPopulation demography can change the network structure, which further plays an important role in the spreading of infectious disease. In this paper, we study the epidemic dynamics in temporal clustered networks where the local-world structure and clustering are incorporated into the attachment mechanism of new nodes. It is found that increasing the local-world size of new nodes has little influence on the clustering coefficient but increases the degree heterogeneity of networks. Besides, when the network evolves faster, increasing the local-world size of new nodes leads to a faster initial growth rate and a larger steady density of infectious nodes, while it has small impacts on the steady density of infectious disease when the network evolves slowly. Furthermore, if the average degree is fixed, increasing the probability of triad formation p enlarges the clustering coefficient of a network, which reduces the initial growth rate and steady density of infectious nodes in the network. This work could provide a theoretical foundation for the control of infectious disease.http://dx.doi.org/10.1155/2023/4591403
spellingShingle Wenjun Jing
Juping Zhang
Xiaoqin Zhang
Epidemic Dynamics in Temporal Clustered Networks with Local-World Structure
Complexity
title Epidemic Dynamics in Temporal Clustered Networks with Local-World Structure
title_full Epidemic Dynamics in Temporal Clustered Networks with Local-World Structure
title_fullStr Epidemic Dynamics in Temporal Clustered Networks with Local-World Structure
title_full_unstemmed Epidemic Dynamics in Temporal Clustered Networks with Local-World Structure
title_short Epidemic Dynamics in Temporal Clustered Networks with Local-World Structure
title_sort epidemic dynamics in temporal clustered networks with local world structure
url http://dx.doi.org/10.1155/2023/4591403
work_keys_str_mv AT wenjunjing epidemicdynamicsintemporalclusterednetworkswithlocalworldstructure
AT jupingzhang epidemicdynamicsintemporalclusterednetworkswithlocalworldstructure
AT xiaoqinzhang epidemicdynamicsintemporalclusterednetworkswithlocalworldstructure