{"title":"Influences of individual interaction validity on coupling propagation of information and disease in a two-layer higher-order network.","authors":"Ming Li, Liang'an Huo","doi":"10.1063/5.0253301","DOIUrl":null,"url":null,"abstract":"<p><p>All complex phenomena in complex systems arise from individual interactions, which include pairs and higher-order forms. Research indicates that various physical and mental factors can impact the validity of these interactions, potentially preventing diffusion phenomena. This paper explores the influences of the interaction validity on coupling propagation of information and disease in a two-layer higher-order network. Interaction validity is defined using a threshold function based on the individual activity level. The dynamic evolution equations of the nodes are derived by using the microscopic Markov chain approach, and the transmission threshold of the disease is determined. Extensive numerical simulations on both artificial and real-world networks reveal that higher-order interactions significantly enhance the diffusion of disease and related information. Reducing individual activity levels diminishes interaction validity, thereby restricting disease transmission. Moreover, optimizing disease control can be achieved by increasing public activity in virtual social networks while reducing it in physical contact networks. Strengthening interlayer coupling enhances self-protective measures, thus amplifying the suppression of disease by information.</p>","PeriodicalId":9974,"journal":{"name":"Chaos","volume":"35 2","pages":""},"PeriodicalIF":2.7000,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Chaos","FirstCategoryId":"100","ListUrlMain":"https://doi.org/10.1063/5.0253301","RegionNum":2,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"MATHEMATICS, APPLIED","Score":null,"Total":0}
引用次数: 0
Abstract
All complex phenomena in complex systems arise from individual interactions, which include pairs and higher-order forms. Research indicates that various physical and mental factors can impact the validity of these interactions, potentially preventing diffusion phenomena. This paper explores the influences of the interaction validity on coupling propagation of information and disease in a two-layer higher-order network. Interaction validity is defined using a threshold function based on the individual activity level. The dynamic evolution equations of the nodes are derived by using the microscopic Markov chain approach, and the transmission threshold of the disease is determined. Extensive numerical simulations on both artificial and real-world networks reveal that higher-order interactions significantly enhance the diffusion of disease and related information. Reducing individual activity levels diminishes interaction validity, thereby restricting disease transmission. Moreover, optimizing disease control can be achieved by increasing public activity in virtual social networks while reducing it in physical contact networks. Strengthening interlayer coupling enhances self-protective measures, thus amplifying the suppression of disease by information.
期刊介绍:
Chaos: An Interdisciplinary Journal of Nonlinear Science is a peer-reviewed journal devoted to increasing the understanding of nonlinear phenomena and describing the manifestations in a manner comprehensible to researchers from a broad spectrum of disciplines.