Pair quenched mean-field approach to epidemic spreading in multiplex networks

Wu, Qingchu; Hadzibeganovic, Tarik

doi:10.1016/j.apm.2018.03.011

Cited by 28 publications

(7 citation statements)

References 62 publications

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“…From the perspective of network science, there is a significant difference between spontaneous social distancing and public social distancing. Specifically, an individual’s communication network is different from his contact network [27] , [28] . For example, the individual may communicate with an online friend that he never contact with, and the individual may randomly contact with a stranger that he never communicate with [29] .…”

Section: Introductionmentioning

confidence: 99%

Impacts of social distancing on the spread of infectious diseases with asymptomatic infection: A mathematical model

Huang

Chen

Yan

2021

Applied Mathematics and Computation

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Section: Introductionmentioning

confidence: 99%

Impacts of social distancing on the spread of infectious diseases with asymptomatic infection: A mathematical model

Huang

Chen

Yan

2021

Applied Mathematics and Computation

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“…By means of the quasi-static approximation, Wu et al. derive the condition for the epidemic threshold in a static multiplex network overlapped by the randomly connected subnetwork without clustering [25] . Wang et al.…”

Section: Introductionmentioning

confidence: 99%

Analysis of epidemic vaccination strategies on heterogeneous networks: Based on SEIRV model and evolutionary game

Meng

Cai

et al. 2021

Applied Mathematics and Computation

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Nowadays, vaccination is the most effective way to control the epidemic spreading. In this paper, an epidemic SEIRV (susceptible-exposed-infected-removed -vaccinated) model and an evolutionary game model are established to analyze the difference between mandatory vaccination method and voluntary vaccination method on heterogeneous networks. Firstly, we divide the population into four categories, including susceptible individuals, exposed individuals, infected individuals and removed individuals. Based on the mean field approximation theory, differential equations are developed to characterize the changes of the proportions of the four groups over time under mandatory vaccination. Then through the analysis of the differential equations, the disease-free equilibrium point (DFE) and the endemic disease equilibrium point (EDE) are obtained. Also, the basic reproduction number is obtained by the next-generation matrix method and the stability analysis of the equilibrium points is performed. Next, by considering factors such as vaccination cost, treatment cost and government subsidy rate, differential equations are established to represent the change of vaccination rate over time. By analyzing the final vaccination coverage rate, we can get the minimum vaccination cost to make infectious disease disappear. Finally, the Monte Carlo method is used for numerical simulation to verify the results obtained from the theoretical analysis. Using the SARS-Cov-2 pandemic data from Wuhan, China, the experimental results show that when the effectiveness rate of vaccination is 0.75, the vaccination cost is not higher than 0.886 so that the vaccination strategy can be spread among the population. If mandatory vaccination is adopted, the minimum vaccination rate is 0.146.

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“…Epidemic spreading has been modelled extensively through SIRD dynamics on networks 6 – 9 . It has also been studied independently through game-theoretic approaches, many of which involve networks 10 , 11 .…”

Section: Introductionmentioning

confidence: 99%

Mass Testing and Proactiveness Affect Epidemic Spreading

2021

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The detection and management of diseases become quite complicated when pathogens contain asymptomatic phenotypes amongst their ranks, as evident during the recent COVID-19 pandemic. Spreading of diseases has been studied extensively under the paradigm of susceptible–infected–recovered–deceased (SIRD) dynamics. Various game-theoretic approaches have also addressed disease spread, many of which consider , , , and as strategies rather than as states. Remarkably, most studies from the above approaches do not account for the distinction between the symptomatic or asymptomatic aspect of the disease. It is well-known that precautionary measures like washing hands, wearing masks and social distancing significantly mitigate the spread of many contagious diseases. Herein, we consider the adoption of such precautions as strategies and treat , , , and as states. We also attempt to capture the differences in epidemic spreading arising from symptomatic and asymptomatic diseases on various network topologies. Through extensive computer simulations, we examine that the cost of maintaining precautionary measures as well as the extent of mass testing in a population affects the final fraction of socially responsible individuals. We observe that the lack of mass testing could potentially lead to a pandemic in case of asymptomatic diseases. Network topology also seems to play an important role. We further observe that the final fraction of proactive individuals depends on the initial fraction of both infected as well as proactive individuals. Additionally, edge density can significantly influence the overall outcome. Our findings are in broad agreement with the lessons learnt from the ongoing COVID-19 pandemic.

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Pair quenched mean-field approach to epidemic spreading in multiplex networks

Cited by 28 publications

References 62 publications

Impacts of social distancing on the spread of infectious diseases with asymptomatic infection: A mathematical model

Impacts of social distancing on the spread of infectious diseases with asymptomatic infection: A mathematical model

Analysis of epidemic vaccination strategies on heterogeneous networks: Based on SEIRV model and evolutionary game

Mass Testing and Proactiveness Affect Epidemic Spreading

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