基于UANU-SIS模型的信息–疾病耦合传播动力学
Information-Disease Coupled Propagation Dynamics Based on the UANU-SIS Model
摘要: 为了研究当信息遗忘概率随时间变化、正负向信息之间可以直接相互转化的情况下，正负向信息传播对传染病传播的影响，本文提出了UANU-SIS双层耦合网络模型。首先，建立了一个双层耦合网络模型。其次，通过微观马尔可夫链(MMCA)的方法，推导出模型的动态转移方程和双层耦合网络流行病阈值表达式。最后，利用仿真实验分析模型中各个参数对传染病传播的影响。结果表明，加快个体间正面信息传播、抑制负面信息传播以及采取更好的传染病预防措施可以有效抑制传染病传播。
Abstract: To investigate the impact of the spread of positive and negative information on the transmission of infectious diseases when the probability of information forgetting changes over time and positive and negative information can be directly converted into each other, this paper proposes a UANU-SIS dual-coupled network model. First, a dual-coupled network model is established. Second, the dynamic transition equations and the epidemic threshold expressions for the dual-coupled network are derived using the method of microscopic Markov chain analysis (MMCA). Finally, simulation experiments are used to analyze the impact of various parameters in the model on the transmission of infectious diseases. The results indicate that accelerating the spread of positive information among individuals, suppressing the spread of negative information, and adopting better preventive measures for infectious diseases can effectively inhibit the spread of infectious diseases.
文章引用：陈陆平. 基于UANU-SIS模型的信息–疾病耦合传播动力学[J]. 建模与仿真, 2025, 14(1): 721-733. https://doi.org/10.12677/mos.2025.141068

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