An information-theoretic approach to study activity driven networks

Christian Bongiorno, Alessandro Rizzo, Maurizio Porfiri

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

In this work, we leverage the information-theoretic notion of transfer entropy theory to study causal information flow in epidemic spreading over temporal networks. An improved understanding of causal information flow may lead to the early detection of population segments that should be monitored or immunized to enhance epidemic containment. We focus on activity driven networks, which constitute a powerful and elegant paradigm to capture the inherent time-varying nature of contacts and population heterogeneity. Our preliminary results confirm the intuition that individuals who have a higher propensity in contacting others are responsible for the largest information transfer. Moreover, we find that epidemic parameters such as the probability of infection and recovery may dominate the spreading phenomenon over heterogeneities in the contact formation.

Original languageEnglish (US)
Title of host publication2018 IEEE International Symposium on Circuits and Systems, ISCAS 2018 - Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
Volume2018-May
ISBN (Electronic)9781538648810
DOIs
StatePublished - Apr 26 2018
Event2018 IEEE International Symposium on Circuits and Systems, ISCAS 2018 - Florence, Italy
Duration: May 27 2018May 30 2018

Other

Other2018 IEEE International Symposium on Circuits and Systems, ISCAS 2018
CountryItaly
CityFlorence
Period5/27/185/30/18

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ASJC Scopus subject areas

  • Electrical and Electronic Engineering

Cite this

Bongiorno, C., Rizzo, A., & Porfiri, M. (2018). An information-theoretic approach to study activity driven networks. In 2018 IEEE International Symposium on Circuits and Systems, ISCAS 2018 - Proceedings (Vol. 2018-May). [8351825] Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ISCAS.2018.8351825