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Co-evolution spreading of multiple information and epidemics on two-layered networks under the influence of mass media

During epidemic outbreaks, there are various types of information about epidemic prevention disseminated simultaneously among the population. Meanwhile, the mass media also scrambles to report the information related to the epidemic. Inspired by these phenomena, we devise a model to discuss the dyna...

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Autores principales: Wang, Zhishuang, Xia, Chengyi
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer Netherlands 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7604231/
https://www.ncbi.nlm.nih.gov/pubmed/33162672
http://dx.doi.org/10.1007/s11071-020-06021-7
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author Wang, Zhishuang
Xia, Chengyi
author_facet Wang, Zhishuang
Xia, Chengyi
author_sort Wang, Zhishuang
collection PubMed
description During epidemic outbreaks, there are various types of information about epidemic prevention disseminated simultaneously among the population. Meanwhile, the mass media also scrambles to report the information related to the epidemic. Inspired by these phenomena, we devise a model to discuss the dynamical characteristics of the co-evolution spreading of multiple information and epidemic under the influence of mass media. We construct the co-evolution model under the framework of two-layered networks and gain the dynamical equations and epidemic critical point with the help of the micro-Markov chain approach. The expression of epidemic critical point show that the positive and negative information have a direct impact on the epidemic critical point. Moreover, the mass media can indirectly affect the epidemic size and epidemic critical point through their interference with the dissemination of epidemic-relevant information. Though extensive numerical experiments, we examine the accuracy of the dynamical equations and expression of the epidemic critical point, showing that the dynamical characteristics of co-evolution spreading can be well described by the dynamic equations and the epidemic critical point is able to be accurately calculated by the derived expression. The experimental results demonstrate that accelerating positive information dissemination and enhancing the propaganda intensity of mass media can efficaciously restrain the epidemic spreading. Interestingly, the way to accelerate the dissemination of negative information can also alleviate the epidemic to a certain extent when the positive information hardly spreads. Current results can provide some useful clues for epidemic prevention and control on the basis of epidemic-relevant information dissemination.
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spelling pubmed-76042312020-11-02 Co-evolution spreading of multiple information and epidemics on two-layered networks under the influence of mass media Wang, Zhishuang Xia, Chengyi Nonlinear Dyn Original Paper During epidemic outbreaks, there are various types of information about epidemic prevention disseminated simultaneously among the population. Meanwhile, the mass media also scrambles to report the information related to the epidemic. Inspired by these phenomena, we devise a model to discuss the dynamical characteristics of the co-evolution spreading of multiple information and epidemic under the influence of mass media. We construct the co-evolution model under the framework of two-layered networks and gain the dynamical equations and epidemic critical point with the help of the micro-Markov chain approach. The expression of epidemic critical point show that the positive and negative information have a direct impact on the epidemic critical point. Moreover, the mass media can indirectly affect the epidemic size and epidemic critical point through their interference with the dissemination of epidemic-relevant information. Though extensive numerical experiments, we examine the accuracy of the dynamical equations and expression of the epidemic critical point, showing that the dynamical characteristics of co-evolution spreading can be well described by the dynamic equations and the epidemic critical point is able to be accurately calculated by the derived expression. The experimental results demonstrate that accelerating positive information dissemination and enhancing the propaganda intensity of mass media can efficaciously restrain the epidemic spreading. Interestingly, the way to accelerate the dissemination of negative information can also alleviate the epidemic to a certain extent when the positive information hardly spreads. Current results can provide some useful clues for epidemic prevention and control on the basis of epidemic-relevant information dissemination. Springer Netherlands 2020-11-02 2020 /pmc/articles/PMC7604231/ /pubmed/33162672 http://dx.doi.org/10.1007/s11071-020-06021-7 Text en © Springer Nature B.V. 2020 This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic.
spellingShingle Original Paper
Wang, Zhishuang
Xia, Chengyi
Co-evolution spreading of multiple information and epidemics on two-layered networks under the influence of mass media
title Co-evolution spreading of multiple information and epidemics on two-layered networks under the influence of mass media
title_full Co-evolution spreading of multiple information and epidemics on two-layered networks under the influence of mass media
title_fullStr Co-evolution spreading of multiple information and epidemics on two-layered networks under the influence of mass media
title_full_unstemmed Co-evolution spreading of multiple information and epidemics on two-layered networks under the influence of mass media
title_short Co-evolution spreading of multiple information and epidemics on two-layered networks under the influence of mass media
title_sort co-evolution spreading of multiple information and epidemics on two-layered networks under the influence of mass media
topic Original Paper
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7604231/
https://www.ncbi.nlm.nih.gov/pubmed/33162672
http://dx.doi.org/10.1007/s11071-020-06021-7
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