The coupled dynamics of information dissemination and SEIR-based epidemic spreading in multiplex networks

Ma, Weicai; Zhang, Peng; Zhao, Xin; Xue, Liutang

doi:10.1016/j.physa.2021.126558

Cited by 24 publications

(7 citation statements)

References 42 publications

(45 reference statements)

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In some research, awareness inhibits the spread of diseases. On the other hand, we can have a situation in which the infected node becomes aware and can spread infection and information about the disease at the same time [12,15,16]. A similar scenario in which disease supports the spread of information, and awareness reduces disease, was also examined for disease and immunization.…”

Section: Interaction Between Processesmentioning

confidence: 99%

“…According to the University of Toronto Citizen Lab report [2], information about it was not released to the general public for more than three weeks, and multiple other sources report that there was an active campaign to limit the spread of information about the virus [3][4][5][6][7][8][9][10]. Since spreading the information (awareness that there is a virus circulating in society) is an important tool in limiting the spread of the virus [11][12][13][14][15][16][17] (aware people might take preventive actions such as staying at home, wearing face masks, washing hands more often, etc. ), we asked questions regarding how delaying information spread influenced the spread of the virus, and how it affected the number of infected individuals and disease dynamic.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Influence of Information Blocking on the Spread of Virus in Multilayer Networks

Wątroba¹,

Bródka

2023

Entropy

View full text Add to dashboard Cite

In this paper, we present the model of the interaction between the spread of disease and the spread of information about the disease in multilayer networks. Next, based on the characteristics of the SARS-CoV-2 virus pandemic, we evaluated the influence of information blocking on the virus spread. Our results show that blocking the spread of information affects the speed at which the epidemic peak appears in our society, and affects the number of infected individuals.

show abstract

Section: Interaction Between Processesmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Influence of Information Blocking on the Spread of Virus in Multilayer Networks

Wątroba¹,

Bródka

2023

Entropy

View full text Add to dashboard Cite

show abstract

“…). MMCA has been used for dynamic research many times, including disease spreading and information dissemination [28][29][30]. It can track the node state in the supply chain risk diffusion process [19].…”

Section: Numerical Simulationmentioning

confidence: 99%

Supply Chain Risk Diffusion in Partially Mapping Double-Layer Hypernetworks

Wang

Sun

et al. 2023

Entropy

View full text Add to dashboard Cite

The impact of COVID-19 is global, and uncertain information will affect product quality and worker efficiency in the complex supply chain network, thus bringing risks. Aiming at individual heterogeneity, a partial mapping double-layer hypernetwork model is constructed to study the supply chain risk diffusion under uncertain information. Here, we explore the risk diffusion dynamics, drawing on epidemiology, and establish an SPIR (Susceptible–Potential–Infected–Recovered) model to simulate the risk diffusion process. The node represents the enterprise, and hyperedge represents the cooperation among enterprises. The microscopic Markov chain approach (MMCA) is used to prove the theory. Network dynamic evolution includes two removal strategies: (i) removing aging nodes; (ii) removing key nodes. Using Matlab to simulate the model, we found that it is more conducive to market stability to eliminate outdated enterprises than to control key enterprises during risk diffusion. The risk diffusion scale is related to interlayer mapping. Increasing the upper layer mapping rate to strengthen the efforts of official media to issue authoritative information will reduce the infected enterprise number. Reducing the lower layer mapping rate will reduce the misled enterprise number, thereby weakening the efficiency of risk infection. The model is helpful for understanding the risk diffusion characteristics and the importance of online information, and it has guiding significance for supply chain management.

show abstract

“…[34] For instance, Ma et al built a novel unaware-aware-unaware-exposed-infected-recovered (UAU-SEIR) model to investigate the effects of information diffusion caused by individuals and mass media on disease transmission. [35] Zhang et al explored the influences of local and global information on disease transmission by analyzing a novel coupled disease-awareness propagation model called local and global information-controlled spreading. [36] These studies highlight the importance of information diffusion and its influence on disease dynamics, providing insights into effective strategies for controlling and preventing diseases.…”

Section: Introductionmentioning

confidence: 99%

Dynamics of information diffusion and disease transmission in time-varying multiplex networks with asymmetric activity levels

Xie 谢,

Huo 霍,

Dong 董

et al. 2024

Chinese Phys. B

View full text Add to dashboard Cite

While the interaction between information and diseases in static networks has been extensively investigated, many studies have ignored the characteristics of network evolution. In this study, we construct a new two-layer coupling model to explore the interactions between information and disease. The upper layer describes the diffusion of disease-related information, and the lower layer represents the disease transmission. We then apply power-law distributions to examine the influence of asymmetric activity levels on dynamic propagation, revealing a mapping relationship characterizing the interconnected propagation of information and diseases among partial nodes within the network. Subsequently, we derive the disease outbreak threshold using the microscopic Markov-chain approach (MMCA). Finally, we perform extensive Monte Carlo (MC) numerical simulations to verify the accuracy of our theoretical results. Our findings indicate that the activity levels of individuals in the disease transmission layer have a more significant influence on disease transmission compared with the individual activity levels in the information diffusion layer. Moreover, reducing the damping factor can delay disease outbreaks and suppress disease transmission, while enhancing individual quarantine measures can contribute positively to disease control. This study provides valuable insights for policymakers in developing outbreak prevention and control strategies.

show abstract

The coupled dynamics of information dissemination and SEIR-based epidemic spreading in multiplex networks

Cited by 24 publications

References 42 publications

Influence of Information Blocking on the Spread of Virus in Multilayer Networks

Influence of Information Blocking on the Spread of Virus in Multilayer Networks

Supply Chain Risk Diffusion in Partially Mapping Double-Layer Hypernetworks

Dynamics of information diffusion and disease transmission in time-varying multiplex networks with asymmetric activity levels

Contact Info

Product

Resources

About