Global stability of a susceptible-infected-susceptible epidemic model on networks with individual awareness

Li, Ke-Zan; Xu, Zhongpu; Zhu, Guanghu; Ding, Yong

doi:10.1088/1674-1056/23/11/118904

Cited by 8 publications

(5 citation statements)

References 28 publications

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“…This advancement further enhances the alignment of infectious disease dynamics research with real-world scenarios. In recent years, an increasing amount of research has been directed towards understanding the impact of population contact networks and their heterogeneity on the transmission of infectious diseases [ 12 , 13 , 14 , 15 , 16 , 17 , 18 , 19 , 20 , 21 ]. In particular, Huo et al [ 22 ] introduced a fractional SIR model with birth and death rates on heterogeneous complex networks and analyzed both its local and global stability of disease-free and endemic equilibrium.…”

Section: Introductionmentioning

confidence: 99%

Dynamical Analysis of an Improved Bidirectional Immunization SIR Model in Complex Network

Han,

Yan,

Pei

et al. 2024

Entropy

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In order to investigate the impact of two immunization strategies—vaccination targeting susceptible individuals to reduce their infection rate and clinical medical interventions targeting infected individuals to enhance their recovery rate—on the spread of infectious diseases in complex networks, this study proposes a bilinear SIR infectious disease model that considers bidirectional immunization. By analyzing the conditions for the existence of endemic equilibrium points, we derive the basic reproduction numbers and outbreak thresholds for both homogeneous and heterogeneous networks. The epidemic model is then reconstructed and extensively analyzed using continuous-time Markov chain (CTMC) methods. This analysis includes the investigation of transition probabilities, transition rate matrices, steady-state distributions, and the transition probability matrix based on the embedded chain. In numerical simulations, a notable concordance exists between the outcomes of CTMC and mean-field (MF) simulations, thereby substantiating the efficacy of the CTMC model. Moreover, the CTMC-based model adeptly captures the inherent stochastic fluctuation in the disease transmission, which is consistent with the mathematical properties of Markov chains. We further analyze the relationship between the system’s steady-state infection density and the immunization rate through MCS. The results suggest that the infection density decreases with an increase in the immunization rate among susceptible individuals. The current research results will enhance our understanding of infectious disease transmission patterns in real-world scenarios, providing valuable theoretical insights for the development of epidemic prevention and control strategies.

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Section: Introductionmentioning

confidence: 99%

Dynamical Analysis of an Improved Bidirectional Immunization SIR Model in Complex Network

Han,

Yan,

Pei

et al. 2024

Entropy

View full text Add to dashboard Cite

show abstract

“…Received information will make individuals take self-protective actions to protect themselves. [17][18][19][20][21] Epidemic spreading on one layer will asymmetrically interact with the communication on another layer. [22,23] Objective traveling of choosing the shortest path will accelerate the epidemic spreading, [24][25][26][27][28] in contrast to the random diffusion model where individuals randomly choose one of its neighboring nodes for diffusion.…”

Section: Introductionmentioning

confidence: 99%

Reverse-feeding effect of epidemic by propagators in two-layered networks

Zhao

Zheng

et al. 2016

Chinese Phys. B

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Epidemic spreading has been studied for a long time and is currently focused on the spreading of multiple pathogens, especially in multiplex networks. However, little attention has been paid to the case where the mutual influence between different pathogens comes from a fraction of epidemic propagators, such as bisexual people in two separated groups of heterosexual and homosexual people. We here study this topic by presenting a network model of two layers connected by impulsive links, in contrast to the persistent links in each layer. We let each layer have a distinct pathogen and their interactive infection is implemented by a fraction of propagators jumping between the corresponding pairs of nodes in the two layers. By this model we show that (i) the propagators take the key role to transmit pathogens from one layer to the other, which significantly influences the stabilized epidemics; (ii) the epidemic thresholds will be changed by the propagators; and (iii) a reverse-feeding effect can be expected when the infective rate is smaller than its threshold of isolated spreading. A theoretical analysis is presented to explain the numerical results.

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“…In most of the literature dealing with the epidemic spreading behavior, the topology structure of the underlying network is assumed to be static. [1][2][3][4][5][6][7][8][9][10] However, in practice, the relations between individuals are unlikely to keep unchanged all the time, the movements of individuals cause a dynamic topology structure. In fact, some recent study results indicate that the mobility of individuals can play a significant role in the epidemic spreading process.…”

Section: Introductionmentioning

confidence: 99%

Epidemic spreading on random surfer networks with infected avoidance strategy

et al. 2016

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In this paper, we study epidemic spreading on random surfer networks with infected avoidance (IA) strategy. In particular, we consider that susceptible individuals' moving direction angles are affected by the current location information received from infected individuals through a directed information network. The model is mainly analyzed by discrete-time numerical simulations. The results indicate that the IA strategy can restrain epidemic spreading effectively. However, when long-distance jumps of individuals exist, the IA strategy's effectiveness on restraining epidemic spreading is heavily reduced. Finally, it is found that the influence of the noises from information transferring process on epidemic spreading is indistinctive.

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Global stability of a susceptible-infected-susceptible epidemic model on networks with individual awareness

Abstract: Global stability of a susceptible-infected-susceptible epidemic model on networks with individual awareness *Li Ke-Zan(李科赞) a) , Xu Zhong-Pu(徐忠朴) a) , Zhu Guang-Hu(祝光湖) a) , and Ding Yong(丁勇) a)b) †

Cited by 8 publications

References 28 publications

Dynamical Analysis of an Improved Bidirectional Immunization SIR Model in Complex Network

Dynamical Analysis of an Improved Bidirectional Immunization SIR Model in Complex Network

Reverse-feeding effect of epidemic by propagators in two-layered networks

Epidemic spreading on random surfer networks with infected avoidance strategy

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Global stability of a susceptible-infected-susceptible epidemic model on networks with individual awareness

Abstract: Global stability of a susceptible-infected-susceptible epidemic model on networks with individual awareness *Li Ke-Zan(李科赞) a) , Xu Zhong-Pu(徐忠朴) a) , Zhu Guang-Hu(祝光湖) a) , and Ding Yong(丁 勇) a)b) †

Cited by 8 publications

References 28 publications

Dynamical Analysis of an Improved Bidirectional Immunization SIR Model in Complex Network

Dynamical Analysis of an Improved Bidirectional Immunization SIR Model in Complex Network

Reverse-feeding effect of epidemic by propagators in two-layered networks

Epidemic spreading on random surfer networks with infected avoidance strategy

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Product

Resources

About

Abstract: Global stability of a susceptible-infected-susceptible epidemic model on networks with individual awareness *Li Ke-Zan(李科赞) a) , Xu Zhong-Pu(徐忠朴) a) , Zhu Guang-Hu(祝光湖) a) , and Ding Yong(丁勇) a)b) †