Impact of information diffusion on epidemic spreading in partially mapping two-layered time-varying networks

Guo, Haili; Yin, Qian; Xia, Chengyi; Dehmer, Matthias

doi:10.1007/s11071-021-06784-7

Cited by 47 publications

(12 citation statements)

References 48 publications

(52 reference statements)

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“…Later works observed that, apart from information diffusion, epidemic transmission is influenced by other factors, including network topology, heterogeneity in individual activity levels, and the adoption of immune behavior. Among these factors, the heterogeneity of individual activity levels has attracted extensive attention from scholars and yielded some interesting insights [27,28]. For example, Liu et al [29] investigated the dynamic propagation process in complex networks with active nodes.…”

Section: Introductionmentioning

confidence: 99%

The interaction of information diffusion and epidemic transmission in time-varying multiplex networks with simplicial complexes and asymmetric activity levels

Xie,

Huo,

Dong

et al. 2024

Phys. Scr.

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Information diffusion among individuals occurs in various ways, mainly involving pairwise and higher-order interactions, and their coexistence can be characterized by simplicial complexes. This paper introduces a novel two-layer model that investigates coupled information-epidemic propagation. Specifically, the upper layer represents the virtual layer that depicts information diffusion, where the interaction process among individuals is not only limited to pairwise interactions but also influenced by higher-order interactions. The lower layer denotes the physical contact layer to portray epidemic transmission, where the interaction process among individuals is only considered in pairwise interactions. In particular, the emergence of asymmetric activity levels in two-layer networks reshapes the propagation mechanism. We then employ the micro-Marko chain approach (MMCA) to establish the probabilistic transfer equation for each state, deduce the epidemic outbreak threshold, and investigate the equilibrium and stability of the proposed model. Furthermore, we perform extensive Monte Carlo (MC) simulations to validate the theoretical predictions. The results demonstrate that the higher-order interaction generates synergistic reinforcement mechanisms that both facilitate information diffusion and inhibit epidemic transmission. Moreover, this study suggests that the activity level of individuals at the physical contact level has a greater impact on epidemic transmission. In addition, we utilize two different networks to explore the influence of network structural features on the transmission and scale of epidemics.

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Section: Introductionmentioning

confidence: 99%

The interaction of information diffusion and epidemic transmission in time-varying multiplex networks with simplicial complexes and asymmetric activity levels

Xie,

Huo,

Dong

et al. 2024

Phys. Scr.

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“…These models have various useful applications in real-world situations and can suggest effective and suitable strategies to control the spreading of rumors. It is important to note that rumors are often spread in community and social networks; hence, there is a high similarity between the spreading of rumors and the transmission of infectious diseases (see, for instance, [13][14][15]).…”

Section: Introductionmentioning

confidence: 99%

Lyapunov functions for studying global asymptotic stability of two rumor spreading models

Hoang

2023

Commun. Theor. Phys.

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In a previous work (2018, Commun. Theor. Phys. 70, 795–802), a new compartment model for the spreading of rumors was introduced and analyzed. However, only the local asymptotic stability of this model was discussed. In the present work, we first provide a rigorous mathematical analysis for the global asymptotic stability (GAS) of the above-mentioned rumor spreading model. By constructing suitable Lyapunov candidate functions, we obtain the GAS of a rumor-free (boundary) equilibrium point and a unique rumor-spreading (positive) equilibrium point. After that, we utilize the approach based on the Lyapunov candidate functions to study the GAS of another rumor spreading model with control strategies, which was proposed in (2022, Physica A 606, 128157). As an important consequence, the GAS of the rumor spreading model with control strategies is determined fully without resorting to technical hypotheses used in the benchmark work. Lastly, the theoretical findings are supported by a set of illustrative numerical examples. The obtained results not only improve the ones constructed in the two above-mentioned benchmark papers but also can be extended to study the global dynamics of other rumor propagation models in the context of both integer-order and fractional-order derivatives.

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“…Wang et al [5] presented a new epidemic model in multiplex networks to investigate the impact of positive and negative preventive information on epidemic spreading. Considering the partial mapping relationship in a two-layered time-varying network, Guo et al [6] proposed a novel epidemic model to study the impact of information diffusion on epidemic propagation. Zeng et al [7] identified the super communicators by studying the dynamic mechanism of information-disease coupling.…”

Section: Introductionmentioning

confidence: 99%

Dynamics of a stochastic epidemic-like rumor propagation model with generalized nonlinear incidence and time delay

et al. 2023

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Rumors are abnormal children of public opinion, they usually arise with environmental crisisand have serious negative functions. Hence, how to control rumor propagation has become an urgent topicfor the government. Since the communication between people in the real world is inevitably interferedby random factors, and time delay exists in the process of rumor propagation not only influence rumor-forwarding individuals by rumor-hesitant individuals but also in government decision-making. Basedon these premises, we propose a stochastic delayed rumor propagation model with generalized incidencefunction. By setting the suitable Lyapunov functions, we show that the asymptotic behavior of stochasticrumor spreading model is constrained by some conditions. Finally, our analytical results are supportedby numerical simulations. The results show that (1) the increase of noise intensity in social environmentwill reduce rumor propagation; (2) time delay has an impact on rumor propagation to a certain extent.Extending the thinking time may reduce the number of rumor-forwarding individuals and even lead tothe disappearance of rumors; (3) improve scientific literacy and accelerate rumor refutation (i.e. reducethe value of β), strengthen rumor suppression (i.e. increase the value of γ) can effectively control rumortransmission.

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Impact of information diffusion on epidemic spreading in partially mapping two-layered time-varying networks

Cited by 47 publications

References 48 publications

The interaction of information diffusion and epidemic transmission in time-varying multiplex networks with simplicial complexes and asymmetric activity levels

The interaction of information diffusion and epidemic transmission in time-varying multiplex networks with simplicial complexes and asymmetric activity levels

Lyapunov functions for studying global asymptotic stability of two rumor spreading models

Dynamics of a stochastic epidemic-like rumor propagation model with generalized nonlinear incidence and time delay

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