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Spectral Analysis of Epidemic Thresholds of Temporal Networks
Adaptive Networks and Control Laboratory, Department of Electronic Engineering, and the Center of Smart Networks and Systems, School of Information Science and Engineering, Fudan University.
Adaptive Networks and Control Laboratory, Department of Electronic Engineering, and the Center of Smart Networks and Systems, School of Information Science and Engineering, Fudan University.
Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.ORCID iD: 0000-0003-1902-9877
2017 (English)In: IEEE Transactions on Cybernetics, ISSN 2168-2267, E-ISSN 2168-2275Article in journal (Refereed) Epub ahead of print
Abstract [en]

Many complex systems can be modeled as temporal networks with time-evolving connections. The influence of their characteristics on epidemic spreading is analyzed in a susceptible-infected-susceptible epidemic model illustrated by the discrete-time Markov chain approach. We develop the analytical epidemic thresholds in terms of the spectral radius of weighted adjacency matrix by averaging temporal networks, e.g., periodic, nonperiodic Markovian networks, and a special nonperiodic non-Markovian network (the link activation network) in time. We discuss the impacts of statistical characteristics, e.g., bursts and duration heterogeneity, as well as time-reversed characteristic on epidemic thresholds. We confirm the tightness of the proposed epidemic thresholds with numerical simulations on seven artificial and empirical temporal networks and show that the epidemic threshold of our theory is more precise than those of previous studies.

Place, publisher, year, edition, pages
Institute of Electrical and Electronics Engineers (IEEE), 2017.
National Category
Media and Communication Technology
Research subject
Mobile and Pervasive Computing
Identifiers
URN: urn:nbn:se:ltu:diva-65713DOI: 10.1109/TCYB.2017.2743003OAI: oai:DiVA.org:ltu-65713DiVA: diva2:1142228
Available from: 2017-09-19 Created: 2017-09-19 Last updated: 2017-11-24

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