Abstract
Various epidemic spreading processes are considered to take place on time-varying networks. One key factor that alters epidemic spreading on time-varying networks is concurrency, the number of neighbours that a node has at a given time point. In this chapter, we present a theoretical study of the effects of concurrency on the susceptible-infected-susceptible epidemic processes on a class of temporal network models. By theoretical analysis that explicitly takes into account stochastic dying-out effects, we show that network dynamics increase the epidemic threshold (i.e., suppress epidemics), compared to that for the time-averaged network when the nodes’ concurrency is low, but also decrease the epidemic threshold (i.e., enhance epidemics) when the concurrency is high.
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Acknowledgements
T.O. acknowledges the support provided through JSPS KAKENHI Grant Number JP19K14618 and JP19H01506. J.G. acknowledges the support provided through Science Foundation Ireland (Grants No. 16/IA/4470 and No. 16/RC/3918). N.M. acknowledges the support provided through JST, CREST, and JST, ERATO, Kawarabayashi Large Graph Project.
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Onaga, T., Gleeson, J.P., Masuda, N. (2019). The Effect of Concurrency on Epidemic Threshold in Time-Varying Networks. In: Holme, P., Saramäki, J. (eds) Temporal Network Theory. Computational Social Sciences. Springer, Cham. https://doi.org/10.1007/978-3-030-23495-9_14
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DOI: https://doi.org/10.1007/978-3-030-23495-9_14
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