Bursts of vertex activation and epidemics in evolving networks.

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 o...

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Autores principales:	Luis E C Rocha, Vincent D Blondel
Formato:	article
Lenguaje:	EN
Publicado:	Public Library of Science (PLoS) 2013
Materias:	Biology (General) QH301-705.5
Acceso en línea:	https://doaj.org/article/b1d4af620d85424ebc8950405473a980
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spelling	oai:doaj.org-article:b1d4af620d85424ebc8950405473a9802021-11-18T05:52:19ZBursts of vertex activation and epidemics in evolving networks.1553-734X1553-735810.1371/journal.pcbi.1002974https://doaj.org/article/b1d4af620d85424ebc8950405473a9802013-01-01T00:00:00Zhttps://www.ncbi.nlm.nih.gov/pmc/articles/pmid/23555211/?tool=EBIhttps://doaj.org/toc/1553-734Xhttps://doaj.org/toc/1553-7358The 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 R(0), 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 [Formula: see text] is generally higher for heterogeneous patterns, except for sufficiently large infection duration and transmission probability.Luis E C RochaVincent D BlondelPublic Library of Science (PLoS)articleBiology (General)QH301-705.5ENPLoS Computational Biology, Vol 9, Iss 3, p e1002974 (2013)
institution	DOAJ
collection	DOAJ
language	EN
topic	Biology (General) QH301-705.5
spellingShingle	Biology (General) QH301-705.5 Luis E C Rocha Vincent D Blondel Bursts of vertex activation and epidemics in evolving networks.
description	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 R(0), 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 [Formula: see text] is generally higher for heterogeneous patterns, except for sufficiently large infection duration and transmission probability.
format	article
author	Luis E C Rocha Vincent D Blondel
author_facet	Luis E C Rocha Vincent D Blondel
author_sort	Luis E C Rocha
title	Bursts of vertex activation and epidemics in evolving networks.
title_short	Bursts of vertex activation and epidemics in evolving networks.
title_full	Bursts of vertex activation and epidemics in evolving networks.
title_fullStr	Bursts of vertex activation and epidemics in evolving networks.
title_full_unstemmed	Bursts of vertex activation and epidemics in evolving networks.
title_sort	bursts of vertex activation and epidemics in evolving networks.
publisher	Public Library of Science (PLoS)
publishDate	2013
url	https://doaj.org/article/b1d4af620d85424ebc8950405473a980
work_keys_str_mv	AT luisecrocha burstsofvertexactivationandepidemicsinevolvingnetworks AT vincentdblondel burstsofvertexactivationandepidemicsinevolvingnetworks
_version_	1718424749497909248

Bursts of vertex activation and epidemics in evolving networks.

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