The impact of multiple information on coupled awareness-epidemic dynamics in multiplex networks

Pan, Yaohui; Yan, Zhijun

doi:10.1016/j.physa.2017.08.082

Cited by 45 publications

(27 citation statements)

References 39 publications

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“…Consequently, simulations exploiting coupled multiplex networks have provided important insights into the impact of social construction of risk perception on the spread of infectious diseases [e.g. refs (46, 47)].…”

Section: Introductionmentioning

confidence: 99%

Improving pandemic mitigation policies across communities through coupled dynamics of risk perception and infection

Silk

Carrignon

Bentley

et al. 2020

Preprint

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Decisions to adhere to health-protective behaviors (e.g. mask-wearing, social distancing, etc.) that impact the spread of COVID-19 are not made in isolation by each individual. They are instead the result of the social construction of perceived risks and resulting community norms. In populations in which disease is unlikely to spread throughout all communities simultaneously, community-driven perception of risk can drastically alter collective outcomes. A community could respond to a few infections by becoming fearful and adopting anticipatory behaviors that protect them from disease spread. Similarly, there could be false reassurance, in which low disease incidence over time leads to community consensus that protective actions are unnecessary (even if they are the reason cases remains rare). We therefore model COVID-19 spread with three synergistic dynamics governing individual behavioral choices: (1) Social construction of concern, (2) Awareness of disease incidence, and (3) Reassurance by lack of disease. We use a multiplex network approach that captures social communication and epidemiological spread. We find that effective protective policies enacted too early may backfire by allowing a community to become reassured and therefore unwilling to adopt or maintain further protective behaviors. Based on these insights, we propose that public health policies for which success relies on collective action should be designed to exploit the behaviourally receptive phase; the period between the generation of sufficient concern as to foster adoption of novel protective behaviors and the relaxation of adherence driven by reassurance fostered by avoidance of negative outcomes over time.

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Section: Introductionmentioning

confidence: 99%

Improving pandemic mitigation policies across communities through coupled dynamics of risk perception and infection

Silk

Carrignon

Bentley

et al. 2020

Preprint

View full text Add to dashboard Cite

show abstract

“…The same happens to firms: When enterprise are aware of risks, they will take certain measures and countermeasures to avoid being triggered by these firms that have already occurred risk. In recent years, there is a growing interest in studying the dynamical interplay between epidemic spreading and awareness diffusion [19][20][21][22][23][24][25][26], which is typically modeled as two competing spreading in multiplex networks. Two diffusive processes are interacting with each other in a two-layer network, where the epidemic spreads on one layer and the awareness propagates on another one.…”

Section: Introductionmentioning

confidence: 99%

“…Following this thought, Granell et al proposed a UAU-SIS model to study the interplay of epidemic spreading and diffusion of awareness, and found that the spreading of awareness is able to control the onset of epidemic [19]. Different models have been proposed in order to extend the coupled awareness-epidemic dynamics corresponding to diverse realistic scenarios by considering other various factors, such as local awareness [20], individual heterogeneity [21,25,27], self-initiated awareness [22], global awareness [25,28], etc.…”

Section: Introductionmentioning

confidence: 99%

The impact of firm heterogeneity and awareness in modeling risk propagation on multiplex networks

Liu

Yang

Zhao

et al. 2020

Physica A: Statistical Mechanics and its Applications

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Growing interest has emerged to understand the coupled awareness-epidemic dynamics in multiplex network. However, most previous studies usually assume that all the infected nodes have the same influence on the susceptible neighbors, without considering node's heterogeneity. In this paper, with the similarity between epidemic spreading and risk propagation, we apply the UAU-SIS model to investigate the interplay between awareness and risk propagation in RD networks considering firms' heterogeneity. Here, the risk triggering probabilities are heterogenous and depend on two factors: cooperation intensity and local risk prevalence. The results reveal that the cooperation intensity can increase the risk propagation prevalence and decrease the risk propagation threshold, while the local risk prevalence can only increase the risk propagation prevalence. Moreover, we find that the risk propagation threshold undergoes an abrupt transition with a certain point of the local awareness ratio (the global awareness ratio) ignoring the global awareness (the local awareness ratio), which includes two-stage effects on risk propagation threshold. Furthermore, threshold lies in three different areas when considering both the global and local awareness. These results could provide a basis for managerial professionals to improve the robustness of interdependent RD networks under risk propagation by taking effective measures.

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“…Information epidemics, which is analogous to epidemics spreading in populations, describes the information dissemination in social networks [1,2]. Thus the epidemics models are introduced to the field of information diffusion [3,4,5].…”

Section: Introductionmentioning

confidence: 99%

Robust optimal control of deterministic information epidemics with noisy transition rates

Liu

Zhang

Buss

2019

Physica A: Statistical Mechanics and its Applications

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In this paper the robust optimal control of deterministic information epidemics is inspected taking into consideration the noisy transition rates. Distinct from conventional works, the heterogeneous susceptible-infected-susceptible (SIS) model is adopted where both the heterogeneities in the network topology and the individual diversity are considered. In light of the commonly existing noise in the transition processes, we address the robust optimal control problem aiming at maximizing the spreading performance at the finite time instant given a fixed budget. By using the distribution analysis techniques, the inspected problem is transformed to a constrained optimal control problem and solved by the Pontryagin Maximum Principle (PMP). A novel approach combining the forward backward sweep method and the secant method is proposed to efficiently reduce the computation burden. The performance of the robust optimal control as well as the influence of the parameters is examined by numerical experiments in real social networks.

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The impact of multiple information on coupled awareness-epidemic dynamics in multiplex networks

Cited by 45 publications

References 39 publications

Improving pandemic mitigation policies across communities through coupled dynamics of risk perception and infection

Improving pandemic mitigation policies across communities through coupled dynamics of risk perception and infection

The impact of firm heterogeneity and awareness in modeling risk propagation on multiplex networks

Robust optimal control of deterministic information epidemics with noisy transition rates

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