双均匀超网络中的 SIS 流行模型分析

IF 2.2 3区物理与天体物理 Q2 MECHANICS

Journal of Statistical Mechanics: Theory and Experiment Pub Date : 2024-08-22 DOI:10.1088/1742-5468/ad6c30

Wenhui Wang, Juping Zhang, Maoxing Liu, Zhen Jin

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引用次数: 0

摘要

为了描述多个体相互作用的流行病传播动态，我们建立了一个具有高阶相互作用的一般超网络中集体和个体传染的易感-感染-易感（SIS）传播模型。我们将所构建的模型应用于双均匀超网络，从而获得 SIS 模型的均值场模型。得到了流行病在双均匀超网络中传播的阈值，并对其进行了动态分析。通过分析，该模型具有双稳态性，即无疾病平衡和流行平衡共存。最后，对所建立的模型进行了数值模拟，给出了单个传染超导的比例对流行病传播的影响。

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Analysis of SIS epidemic model in bi-uniform hypernetworks

To describe the dynamics of epidemic spread with multiple individuals interacting with each other, we develop a susceptible-infected-susceptible (SIS) spread model with collective and individual contagion in general hypernetworks with higher-order interactions. The constructed model is applied to a bi-uniform hypernetwork to obtain a mean-field model for the SIS model. The threshold value at which an epidemic can spread in the bi-uniform hypernetwork is obtained and analyzed dynamically. By analysis, the model leads to bistability, in which a disease-free equilibrium and an endemic equilibrium coexist. Finally, numerical simulations of the developed model are carried out to give the effect of the proportion of individual contagion hyperedges on the spread of an epidemic.

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来源期刊

Journal of Statistical Mechanics: Theory and Experiment 物理-力学

CiteScore

4.50

自引率

12.50%

发文量

210

审稿时长

1.0 months

期刊介绍： JSTAT is targeted to a broad community interested in different aspects of statistical physics, which are roughly defined by the fields represented in the conferences called ''Statistical Physics''. Submissions from experimentalists working on all the topics which have some ''connection to statistical physics are also strongly encouraged. The journal covers different topics which correspond to the following keyword sections. 1. Quantum statistical physics, condensed matter, integrable systems Scientific Directors: Eduardo Fradkin and Giuseppe Mussardo 2. Classical statistical mechanics, equilibrium and non-equilibrium Scientific Directors: David Mukamel, Matteo Marsili and Giuseppe Mussardo 3. Disordered systems, classical and quantum Scientific Directors: Eduardo Fradkin and Riccardo Zecchina 4. Interdisciplinary statistical mechanics Scientific Directors: Matteo Marsili and Riccardo Zecchina 5. Biological modelling and information Scientific Directors: Matteo Marsili, William Bialek and Riccardo Zecchina