Bursty communication patterns facilitate spreading in a threshold-based epidemic dynamics.

Records of social interactions provide us with new sources of data for understanding how interaction patterns affect collective dynamics. Such human activity patterns are often bursty, i.e., they consist of short periods of intense activity followed by long periods of silence. This burstiness has be...

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Autores principales: Taro Takaguchi, Naoki Masuda, Petter Holme
Formato: article
Lenguaje:EN
Publicado: Public Library of Science (PLoS) 2013
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Acceso en línea:https://doaj.org/article/74a06a70d10f46598f4a2100a2d03f2b
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spelling oai:doaj.org-article:74a06a70d10f46598f4a2100a2d03f2b2021-11-18T09:03:50ZBursty communication patterns facilitate spreading in a threshold-based epidemic dynamics.1932-620310.1371/journal.pone.0068629https://doaj.org/article/74a06a70d10f46598f4a2100a2d03f2b2013-01-01T00:00:00Zhttps://www.ncbi.nlm.nih.gov/pmc/articles/pmid/23894326/pdf/?tool=EBIhttps://doaj.org/toc/1932-6203Records of social interactions provide us with new sources of data for understanding how interaction patterns affect collective dynamics. Such human activity patterns are often bursty, i.e., they consist of short periods of intense activity followed by long periods of silence. This burstiness has been shown to affect spreading phenomena; it accelerates epidemic spreading in some cases and slows it down in other cases. We investigate a model of history-dependent contagion. In our model, repeated interactions between susceptible and infected individuals in a short period of time is needed for a susceptible individual to contract infection. We carry out numerical simulations on real temporal network data to find that bursty activity patterns facilitate epidemic spreading in our model.Taro TakaguchiNaoki MasudaPetter HolmePublic Library of Science (PLoS)articleMedicineRScienceQENPLoS ONE, Vol 8, Iss 7, p e68629 (2013)
institution DOAJ
collection DOAJ
language EN
topic Medicine
R
Science
Q
spellingShingle Medicine
R
Science
Q
Taro Takaguchi
Naoki Masuda
Petter Holme
Bursty communication patterns facilitate spreading in a threshold-based epidemic dynamics.
description Records of social interactions provide us with new sources of data for understanding how interaction patterns affect collective dynamics. Such human activity patterns are often bursty, i.e., they consist of short periods of intense activity followed by long periods of silence. This burstiness has been shown to affect spreading phenomena; it accelerates epidemic spreading in some cases and slows it down in other cases. We investigate a model of history-dependent contagion. In our model, repeated interactions between susceptible and infected individuals in a short period of time is needed for a susceptible individual to contract infection. We carry out numerical simulations on real temporal network data to find that bursty activity patterns facilitate epidemic spreading in our model.
format article
author Taro Takaguchi
Naoki Masuda
Petter Holme
author_facet Taro Takaguchi
Naoki Masuda
Petter Holme
author_sort Taro Takaguchi
title Bursty communication patterns facilitate spreading in a threshold-based epidemic dynamics.
title_short Bursty communication patterns facilitate spreading in a threshold-based epidemic dynamics.
title_full Bursty communication patterns facilitate spreading in a threshold-based epidemic dynamics.
title_fullStr Bursty communication patterns facilitate spreading in a threshold-based epidemic dynamics.
title_full_unstemmed Bursty communication patterns facilitate spreading in a threshold-based epidemic dynamics.
title_sort bursty communication patterns facilitate spreading in a threshold-based epidemic dynamics.
publisher Public Library of Science (PLoS)
publishDate 2013
url https://doaj.org/article/74a06a70d10f46598f4a2100a2d03f2b
work_keys_str_mv AT tarotakaguchi burstycommunicationpatternsfacilitatespreadinginathresholdbasedepidemicdynamics
AT naokimasuda burstycommunicationpatternsfacilitatespreadinginathresholdbasedepidemicdynamics
AT petterholme burstycommunicationpatternsfacilitatespreadinginathresholdbasedepidemicdynamics
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