The Impact of Heterogeneity and Awareness in Modeling Epidemic Spreading on Multiplex Networks

Marialisa Scatà, Alessandro Di Stefano, Pietro Liò, Aurelio La Corte

Research output: Contribution to journalArticlepeer-review

19 Citations (Scopus)

Abstract

In the real world, dynamic processes involving human beings are not disjoint. To capture the real complexity of such dynamics, we propose a novel model of the coevolution of epidemic and awareness spreading processes on a multiplex network, also introducing a preventive isolation strategy. Our aim is to evaluate and quantify the joint impact of heterogeneity and awareness, under different socioeconomic conditions. Considering, as case study, an emerging public health threat, Zika virus, we introduce a data-driven analysis by exploiting multiple sources and different types of data, ranging from Big Five personality traits to Google Trends, related to different world countries where there is an ongoing epidemic outbreak. Our findings demonstrate how the proposed model allows delaying the epidemic outbreak and increasing the resilience of nodes, especially under critical economic conditions. Simulation results, using data-driven approach on Zika virus, which has a growing scientific research interest, are coherent with the proposed analytic model.

Original languageEnglish
Article number37105
JournalScientific Reports
Volume6
DOIs
Publication statusPublished - 16 Nov 2016

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