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• W4313549582 abstract "Social interactions have become more complicated and changeable under the influence of information technology revolution. We, thereby, propose a multi-layer activity-driven network with attractiveness considering the heterogeneity of activated individual edge numbers, which aims to explore the role of heterogeneous behaviors in the time-varying network. Specifically, three types of individual behaviors are introduced: (i) self-quarantine of infected individuals, (ii) safe social distancing between infected and susceptible individuals, and (iii) information spreading of aware individuals. Epidemic threshold is theoretically derived in terms of the microscopic Markov chain approach and the mean-field approach. The results demonstrate that performing self-quarantine and maintaining safe social distance can effectively raise the epidemic threshold and suppress the spread of diseases. Interestingly, individuals' activity and individuals' attractiveness have an equivalent effect on epidemic threshold under the same condition. In addition, a similar result can be obtained regardless of the activated individual edge numbers. The epidemic outbreak earlier in a situation of the stronger heterogeneity of activated individual edge numbers." @default.
• W4313549582 created "2023-01-06" @default.
• W4313549582 creator A5016699509 @default.
• W4313549582 creator A5027622369 @default.
• W4313549582 creator A5065259721 @default.
• W4313549582 date "2023-01-01" @default.
• W4313549582 modified "2023-10-16" @default.
• W4313549582 title "A coupled awareness—epidemic model on a multi-layer time-varying network" @default.
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• W4313549582 doi "https://doi.org/10.1063/5.0125969" @default.
• W4313549582 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/36725628" @default.
• W4313549582 hasPublicationYear "2023" @default.
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