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Bursts of vertex activation and epidemics in evolving networks

Bursts of vertex activation and epidemics in evolving networks

Rocha, Luis E. C. ORCID: 0000-0001-9046-8739 and Blondel, Vincent (2013) Bursts of vertex activation and epidemics in evolving networks. PLoS Computational Biology, 9 (3):e1002974. ISSN 1553-734X (Print), 1553-7358 (Online) (doi:https://doi.org/10.1371/journal.pcbi.1002974)

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Abstract

The dynamic nature of contact patterns creates diverse temporal structures. In particular, empirical studies have shown that contact patterns follow heterogeneous inter-event time intervals, meaning that periods of high activity are followed by long periods of inactivity. To investigate the impact of these heterogeneities in the spread of infection from a theoretical perspective, we propose a stochastic model to generate temporal networks where vertices make instantaneous contacts following heterogeneous inter-event intervals, and may leave and enter the system. We study how these properties affect the prevalence of an infection and estimate , the number of secondary infections of an infectious individual in a completely susceptible population, by modeling simulated infections (SI and SIR) that co-evolve with the network structure. We find that heterogeneous contact patterns cause earlier and larger epidemics in the SIR model in comparison to homogeneous scenarios for a vast range of parameter values, while smaller epidemics may happen in some combinations of parameters. In the case of SI and heterogeneous patterns, the epidemics develop faster in the earlier stages followed by a slowdown in the asymptotic limit. For increasing vertex turnover rates, heterogeneous patterns generally cause higher prevalence in comparison to homogeneous scenarios with the same average inter-event interval. We find that is generally higher for heterogeneous patterns, except for sufficiently large infection duration and transmission probability.

Item Type: Article
Additional Information: © 2013 Rocha, Blondel. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Uncontrolled Keywords: epidemic modelling, temporal network, simulations
Faculty / Department / Research Group: Faculty of Business
Faculty of Business > Centre for Business Network Analysis (CBNA)
Faculty of Business > Networks and Urban Systems Centre (NUSC) > Centre for Business Network Analysis (CBNA)
Faculty of Business > Department of International Business & Economics
Last Modified: 10 Nov 2018 00:57
Selected for GREAT 2016: None
Selected for GREAT 2017: None
Selected for GREAT 2018: None
Selected for GREAT 2019: None
URI: http://gala.gre.ac.uk/id/eprint/20550

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