A Two-layer Coupled Network Disease Transmission Model Considering Multiple Messages
DOI:
https://doi.org/10.62051/ijcsit.v2n2.42Keywords:
Two-layer network; Propagation model; Hesitant individual; Threshold model; Microscopic Markov chainAbstract
In order to discuss the coupling dynamics relationship between disease propagation and information diffusion more accurately, we propose a SIR−UAOE1E2 information-disease two-layer coupling network propagation model, which takes into account individual heterogeneity and the mutual influence of nodes, introducing hesitant individuals. The impact of various behavioral factors of observing individuals on disease transmission under the influence of various information was explored through simulation experiments. The results show that enhancing the correctness of observing individual behavior decisions, improving their sensitivity to disease information, and enhancing their response intensity to infected neighbors, would play a positive role in suppressing disease outbreaks.
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References
ANDERSON R M, MAY R M, ANDERSON B. 1992 Infectious diseases of humans: dynamics and control [M]. USA: Oxford University Press, 1992:127.
HETHCOTE H W. The mathematics of infectious diseases [J]. Siam Review, 2000, 42(4): 599-653.
GRABOWSKI A, KOSINSKI R A. Epidemic spreading in a hierarchical social network [J]. Physical Review E, 2004, 70(3) : 031908.
YANG H, GU C G, TANG M, et al. Suppression of epidemic spreading in time-varying multiplex networks [J]. Applied Mathematical Modelling, 2019, 75 : 806-818.
DAVIS J T, PERRA N, ZHANG Q, et al. Phase transitions in information spreading on structured populations [J]. Nature physics, 2020, 16(5): 590-596.
WANG B, GOU M, HAN Y X. Impacts of information propagation on epidemic spread over different migration routes [J]. Nonlinear Dynamics, 2021, 105(4): 3835-3847.
WEN T. Evaluating the Vulnerability of Communities in Social Networks by Gravity Model [J]. arXiv, 2019, arXiv:1912.07293.
FERGUSON N. Capturing human behaviour [J]. Nature, 2007, 446 (7137): 733.
WANG Z, ANDREWS M A, WU Z X, et al. Coupled disease-behaviour dynamics on complex networks: a review [J]. Physics of Life Reviews, 2015, 15: 1-29.
WANG Z, BAUCH C T, BHATTACHARYYA S, et al. Statistical physics of vaccination [J]. Physics Reports, 2016, 664:1-113.
FUNK S, GILAD E, WATKINS C, et al. The spread of awareness and its impact on epidemic outbreaks [J]. Proceedings of the National Academy of Sciences of the United States of America, 2009, 106 (16):6872-6877.
GRANELL C, GOMEZ S, ARENAS A. Dynamical interplay between awareness and epidemic spreading in multiplex networks [J]. Physical Review Letters, 2013, 111 (12):128701.
XIA C Y, WANG Z S, ZHENG C Y, et al. A new coupled disease-awareness spreading model with mass media on multiplex networks [J], Information Sciences: an International Journal, 2019, 471:185-200.
WANG Z S, XIA C Y. Co-evolution spreading of multiple information and epidemics on two-layered networks under the influence of mass media [J], Nonlinear Dynamics, 2020,102(4): 3039-3052.
WANG H, ZHANG H F, ZHU P C, et al. Interplay of simplicial awareness contagion and epidemic spreading on time-varying multiplex networks [J]. Chaos: An Interdisciplinary Journal of Nonlinear Science, 2022, 32(8):083110.
YANG B, LIU C, CHENG X, et al. Understanding users' group behavioral decisions about sharing articles in social media: an elaboration likelihood model perspective [J]. Group Decision and Negotiation,2022, 31(4): 819-842.
HUANG H, CHEN Y, MA Y, Modelling the competitive diffusions of rumor and knowledge and the impacts on epidemic spreading[J]. Applied Mathematics and Computation, 2021, 388:125536.
WANG Z, XIA C, CHEN Z, et al. Epidemic propagation with positive and negative preventive information in multiplex networks [J]. IEEE Transactions on Cybernetics,2020, 51 (3): 1454-1462.
GUO H, XU L. Research on the application of big data visualisation technology in urban road congestion [J]. European Journal of Remote Sensing, 2022,11: 1-12.
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Copyright (c) 2024 Yang Li, Gengxin Sun, Sheng Bin

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