Suppr超能文献

复杂行为反应对多重网络中不对称相互作用传播动力学的影响。

Impacts of complex behavioral responses on asymmetric interacting spreading dynamics in multiplex networks.

作者信息

Liu Quan-Hui, Wang Wei, Tang Ming, Zhang Hai-Feng

机构信息

Web Sciences Center, University of Electronic Science and Technology of China, Chengdu 611731, China.

Big Data Research Center, University of Electronic Science and Technology of China, Chengdu 611731, China.

出版信息

Sci Rep. 2016 May 9;6:25617. doi: 10.1038/srep25617.

Abstract

Information diffusion and disease spreading in communication-contact layered network are typically asymmetrically coupled with each other, in which disease spreading can be significantly affected by the way an individual being aware of disease responds to the disease. Many recent studies have demonstrated that human behavioral adoption is a complex and non-Markovian process, where the probability of behavior adoption is dependent on the cumulative times of information received and the social reinforcement effect of the cumulative information. In this paper, the impacts of such a non-Markovian vaccination adoption behavior on the epidemic dynamics and the control effects are explored. It is found that this complex adoption behavior in the communication layer can significantly enhance the epidemic threshold and reduce the final infection rate. By defining the social cost as the total cost of vaccination and treatment, it can be seen that there exists an optimal social reinforcement effect and optimal information transmission rate allowing the minimal social cost. Moreover, a mean-field theory is developed to verify the correctness of simulation results.

摘要

通信接触分层网络中的信息传播与疾病传播通常相互不对称耦合,其中疾病传播会受到个体对疾病认知的反应方式的显著影响。最近的许多研究表明,人类行为采纳是一个复杂的非马尔可夫过程,行为采纳的概率取决于接收到的信息的累积次数以及累积信息的社会强化效应。本文探讨了这种非马尔可夫疫苗接种采纳行为对疫情动态和控制效果的影响。研究发现,通信层中的这种复杂采纳行为可以显著提高疫情阈值并降低最终感染率。通过将社会成本定义为疫苗接种和治疗的总成本,可以看出存在一个最优社会强化效应和最优信息传输率以使社会成本最小化。此外,还发展了一种平均场理论来验证模拟结果的正确性。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a5da/4860576/076a5b030906/srep25617-f1.jpg

相似文献

2
Asymmetrically interacting spreading dynamics on complex layered networks.
Sci Rep. 2014 May 29;4:5097. doi: 10.1038/srep05097.
3
6
Cooperative spreading processes in multiplex networks.
Chaos. 2016 Jun;26(6):065311. doi: 10.1063/1.4952964.
7
Coevolving spreading dynamics of negative information and epidemic on multiplex networks.
Nonlinear Dyn. 2022;110(4):3881-3891. doi: 10.1007/s11071-022-07776-x. Epub 2022 Aug 23.
10
Spreading of two interacting diseases in multiplex networks.
Chaos. 2020 Jul;30(7):073115. doi: 10.1063/5.0009588.

引用本文的文献

2
Spatial analysis of COVID-19 hospitalised cases in an entire city: The risk of studying only lattice data.
Sci Total Environ. 2022 Feb 1;806(Pt 1):150521. doi: 10.1016/j.scitotenv.2021.150521. Epub 2021 Sep 24.
3
Accounting for the spread of vaccination behavior to optimize influenza vaccination programs.
PLoS One. 2021 Jun 4;16(6):e0252510. doi: 10.1371/journal.pone.0252510. eCollection 2021.
4
A Systematic Review and Meta-Analysis of Hospitalised Current Smokers and COVID-19.
Int J Environ Res Public Health. 2020 Oct 11;17(20):7394. doi: 10.3390/ijerph17207394.
5
Coevolution spreading in complex networks.
Phys Rep. 2019 Aug 2;820:1-51. doi: 10.1016/j.physrep.2019.07.001. Epub 2019 Jul 29.
6
Correlated network of networks enhances robustness against catastrophic failures.
PLoS One. 2018 Apr 18;13(4):e0195539. doi: 10.1371/journal.pone.0195539. eCollection 2018.

本文引用的文献

1
The structure and dynamics of multilayer networks.
Phys Rep. 2014 Nov 1;544(1):1-122. doi: 10.1016/j.physrep.2014.07.001. Epub 2014 Jul 10.
2
Dynamics of social contagions with memory of nonredundant information.
Phys Rev E Stat Nonlin Soft Matter Phys. 2015 Jul;92(1):012820. doi: 10.1103/PhysRevE.92.012820. Epub 2015 Jul 27.
5
Adoption of a High-Impact Innovation in a Homogeneous Population.
Phys Rev X. 2014 Oct 15;4(4):041008. doi: 10.1103/PhysRevX.4.041008.
6
Interplay of network dynamics and heterogeneity of ties on spreading dynamics.
Phys Rev E Stat Nonlin Soft Matter Phys. 2014 Jul;90(1):012812. doi: 10.1103/PhysRevE.90.012812. Epub 2014 Jul 28.
8
Asymmetrically interacting spreading dynamics on complex layered networks.
Sci Rep. 2014 May 29;4:5097. doi: 10.1038/srep05097.
9
The simple rules of social contagion.
Sci Rep. 2014 Mar 11;4:4343. doi: 10.1038/srep04343.
10
Dynamical interplay between awareness and epidemic spreading in multiplex networks.
Phys Rev Lett. 2013 Sep 20;111(12):128701. doi: 10.1103/PhysRevLett.111.128701. Epub 2013 Sep 17.

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验