Coupled dynamics of SIRS-UAU disease-awareness spreading on multiplex networks

IF 2.8 3区 物理与天体物理 Q2 PHYSICS, MULTIDISCIPLINARY Physica A: Statistical Mechanics and its Applications Pub Date : 2024-08-27 DOI:10.1016/j.physa.2024.130064
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Abstract

In this paper we investigate an SIRS-UAU disease-awareness spreading model on multiplex networks that incorporates the influence of mass media. Through the microscopic Markov chain approach, we derive the evolution equations for the probability of an individual being in each possible state and obtain the epidemic threshold, which is shown to be a continuous phase transition point between the disease-free state and the endemic state in the phase diagram. Our results show that increasing the immunity wanning rate will enlarge the epidemic prevalence and reduce the fraction of recovered individuals; however, the temporal immunity has no impact on the epidemic threshold. Moreover, implementing mass media broadcast helps raise the awareness incidence and decrease the fraction of recovered individuals. In addition, for the special case when awareness confers complete self-protection against infection, the mass media broadcast significantly diminishes the epidemic prevalence and increases the epidemic threshold. Nevertheless, when awareness provides only partial self-protective effectiveness, the mass media broadcast plays a limited role in changing the epidemic prevalence and the epidemic threshold. Furthermore, in the special case where the mass media broadcast is not included, we discover the metacritical point, a point above which the epidemic threshold starts to grow nonlinearly with the awareness spreading rate and below which the epidemic threshold is independent of the awareness spreading rate. Conversely, the metacritical point disappears as long as the mass media broadcast is incorporated into the model. Our analytical results are confirmed by extensive Monte Carlo simulations.

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多路网络上 SIRS-UAU 疾病感知传播的耦合动力学
本文研究了多路网络上的 SIRS-UAU 疾病认知传播模型,该模型结合了大众传媒的影响。通过微观马尔可夫链方法,我们推导出了个体处于每种可能状态的概率演化方程,并得到了流行阈值,该阈值是相图中无疾病状态和流行状态之间的连续相变点。我们的结果表明,提高免疫婉宁率会扩大流行率,降低康复个体的比例;但时间免疫对流行阈值没有影响。此外,实施大众媒体广播有助于提高知晓率,降低康复率。此外,在意识能完全自我保护免受感染的特殊情况下,大众媒体广播能显著降低流行率并提高流行阈值。然而,当认知只提供部分自我保护效力时,大众媒体广播在改变流行率和流行阈值方面的作用有限。此外,在不包括大众媒体广播的特殊情况下,我们发现了元临界点,即在此临界点之上,流行病阈值开始与意识传播速度呈非线性增长,而在此临界点之下,流行病阈值与意识传播速度无关。相反,只要将大众媒体广播纳入模型,元临界点就会消失。我们的分析结果得到了大量蒙特卡罗模拟的证实。
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来源期刊
CiteScore
7.20
自引率
9.10%
发文量
852
审稿时长
6.6 months
期刊介绍: Physica A: Statistical Mechanics and its Applications Recognized by the European Physical Society Physica A publishes research in the field of statistical mechanics and its applications. Statistical mechanics sets out to explain the behaviour of macroscopic systems by studying the statistical properties of their microscopic constituents. Applications of the techniques of statistical mechanics are widespread, and include: applications to physical systems such as solids, liquids and gases; applications to chemical and biological systems (colloids, interfaces, complex fluids, polymers and biopolymers, cell physics); and other interdisciplinary applications to for instance biological, economical and sociological systems.
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