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Spectral Analysis of Epidemic Thresholds of Temporal Networks
Department of Electronic Engineering, and the Center of Smart Networks and Systems, School of Information Science and Engineering, Adaptive Networks and Control Laboratory, Fudan University, Shanghai, China.
Department of Electronic Engineering, and the Center of Smart Networks and Systems, School of Information Science and Engineering, Adaptive Networks and Control Laboratory, Fudan University, Shanghai, China.
Luleå tekniska universitet, Institutionen för system- och rymdteknik, Datavetenskap.ORCID-id: 0000-0003-1902-9877
2020 (engelsk)Inngår i: IEEE Transactions on Cybernetics, ISSN 2168-2267, E-ISSN 2168-2275, Vol. 50, nr 5, s. 1965-1977Artikkel i tidsskrift (Fagfellevurdert) Published
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.

sted, utgiver, år, opplag, sider
Institute of Electrical and Electronics Engineers (IEEE), 2020. Vol. 50, nr 5, s. 1965-1977
Emneord [en]
Bursts, discrete-time Markov chain approach, epidemic threshold, spectral radius, temporal networks, time-reversed characteristic
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URN: urn:nbn:se:ltu:diva-65713DOI: 10.1109/TCYB.2017.2743003ISI: 000528622000017PubMedID: 28910782Scopus ID: 2-s2.0-85030316174OAI: oai:DiVA.org:ltu-65713DiVA, id: diva2:1142228
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Validerad;2020;Nivå 2;2020-04-23 (alebob)

Tilgjengelig fra: 2017-09-19 Laget: 2017-09-19 Sist oppdatert: 2020-05-14bibliografisk kontrollert

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