Epidemic outbreak for an SIS model in multiplex networks with immunization

Wu, Qingchu; Lou, Yijun; Zhu, Wenfang

doi:10.1016/j.mbs.2016.04.004

Cited by 28 publications

(26 citation statements)

References 38 publications

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“…Meanwhile, we also can see that the interlayer degree correlation has no direct impact on the epidemic threshold since k r a does not present in this expression except for the awareness term. This is different from the SIS dynamics on multiplex networks [21], where the inter-layer correlation has a strong impact on the outbreak threshold.…”

Section: Epidemic Thresholdsmentioning

confidence: 63%

“…By using the generalized HMF approach, Sanz et al [30] studied the dynamics of two interacting pathogens in multiplex networks. In [21], we studied the epidemic spreading of SIS model in multiplex networks and the immunization.…”

Section: Multiplex Network Modelling For Studying Effects Of Situmentioning

confidence: 99%

“…(1) in ref. [21]. Using almost the same technique, the explicit expression of epidemic threshold τ 3 c can be derived as…”

Section: Epidemic Thresholdsmentioning

confidence: 99%

“…First, how could a continuous-time dynamical evolution model be built to predict the epidemic spreading dynamics and further to derive the explicit expression of epidemic threshold? Secondly, how does the epidemic threshold depend on the inter-layer degree correlation (i.e., the correlation between the node degrees in different layers [19][20][21]) and the portion of overlapping links in the whole network [22][23][24][25]? Thirdly, what kinds of epidemic information may affect the epidemic threshold as that in the single network?…”

Section: Introductionmentioning

confidence: 99%

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A colored mean-field model for analyzing the effects of awareness on epidemic spreading in multiplex networks

Xiao

2018

Chaos: An Interdisciplinary Journal of Nonlinear Science

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We study the impact of susceptible nodes' awareness on epidemic spreading in social systems, where the systems are modelled as multiplex networks coupled with an information layer and a contact layer. We develop a colored heterogeneous mean-field model taking into account the portion of the overlapping neighbors in the two layers. With theoretical analysis and numerical simulations, we derive the epidemic threshold which determines whether the epidemic can prevail in the population, and find that the impacts of awareness on threshold value only depends on epidemic information being available in network nodes' overlapping neighborhood. When there is not any link overlap between the two network layers, the awareness cannot help to raise the epidemic threshold. Such an observation is different from that in a single-layer network, where the existence of awareness almost always helps.

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Section: Epidemic Thresholdsmentioning

confidence: 63%

Section: Multiplex Network Modelling For Studying Effects Of Situmentioning

confidence: 99%

“…(1) in ref. [21]. Using almost the same technique, the explicit expression of epidemic threshold τ 3 c can be derived as…”

Section: Epidemic Thresholdsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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A colored mean-field model for analyzing the effects of awareness on epidemic spreading in multiplex networks

Xiao

2018

Chaos: An Interdisciplinary Journal of Nonlinear Science

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“…The choice of such a vaccination strategy is motivated by the following consideration. We observe that a lot of studies on vaccination strategies take the node degree as the characteristic index of individual heterogeneity [22,23,60,62,65,66,67,68,69]. As an alternative measurement to quantify the diversity among individuals, interaction radius can characterize the range and ability of individuals' activity [50].…”

Section: Sis Epidemic Model With Vaccinationmentioning

confidence: 99%

An SIS epidemic model with vaccination in a dynamical contact network of mobile individuals with heterogeneous spatial constraints

Peng

Zhang

Yang

et al. 2019

Communications in Nonlinear Science and Numerical Simulation

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Pre-emptive spectral graph protection strategies on multiplex social networks

Wijayanto

Murata

2018

Appl Netw Sci

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Constructing effective and scalable protection strategies over epidemic propagation is a challenging issue. It has been attracting interests in both theoretical and empirical studies. However, most of the recent developments are limited to the simplified single-layered networks. Multiplex social networks are social networks with multiplelayers where the same set of nodes appear in different layers. Consequently, a single attack can trigger simultaneous propagation in all corresponding layers. Therefore, suppressing propagation in multiplex topologies is more challenging given the fact that each layer also has a different structure. In this paper, we address the problem of suppressing the epidemic propagation in multiplex social networks by allocating protection resources throughout different layers. Given a multiplex graph, such as a social network, and k budget of protection resources, we aim to protect a set of nodes such that the percentage of survived nodes at the end of epidemics is maximized. We propose MultiplexShield, which employs the role of graph spectral properties, degree centrality and layer-wise stochastic propagation rate to pre-emptively select k nodes for protection. We also comprehensively evaluate our proposal in two different approaches: multiplex-based and layer-based node protection schemes. Furthermore, two kinds of common attacks are also evaluated: random and targeted attack. Experimental results show the effectiveness of our proposal on real-world datasets.

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Epidemic outbreak for an SIS model in multiplex networks with immunization

Cited by 28 publications

References 38 publications

A colored mean-field model for analyzing the effects of awareness on epidemic spreading in multiplex networks

A colored mean-field model for analyzing the effects of awareness on epidemic spreading in multiplex networks

An SIS epidemic model with vaccination in a dynamical contact network of mobile individuals with heterogeneous spatial constraints

Pre-emptive spectral graph protection strategies on multiplex social networks

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