Impact of temporal correlations on high risk outbreaks of independent and cooperative SIR dynamics.

We first propose a quantitative approach to detect high risk outbreaks of independent and coinfective SIR dynamics on three empirical networks: a school, a conference and a hospital contact network. This measurement is based on the k-means clustering method and identifies proper samples for calculat...

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Autores principales:	Sina Sajjadi, Mohammad Reza Ejtehadi, Fakhteh Ghanbarnejad
Formato:	article
Lenguaje:	EN
Publicado:	Public Library of Science (PLoS) 2021
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/552f5932a0c7435fa102bab7bdd006a6
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spelling	oai:doaj.org-article:552f5932a0c7435fa102bab7bdd006a62021-12-02T20:09:07ZImpact of temporal correlations on high risk outbreaks of independent and cooperative SIR dynamics.1932-620310.1371/journal.pone.0253563https://doaj.org/article/552f5932a0c7435fa102bab7bdd006a62021-01-01T00:00:00Zhttps://doi.org/10.1371/journal.pone.0253563https://doaj.org/toc/1932-6203We first propose a quantitative approach to detect high risk outbreaks of independent and coinfective SIR dynamics on three empirical networks: a school, a conference and a hospital contact network. This measurement is based on the k-means clustering method and identifies proper samples for calculating the mean outbreak size and the outbreak probability. Then we systematically study the impact of different temporal correlations on high risk outbreaks over the original and differently shuffled counterparts of each network. We observe that, on the one hand, in the coinfection process, randomization of the sequence of the events increases the mean outbreak size of high-risk cases. On the other hand, these correlations do not have a consistent effect on the independent infection dynamics, and can either decrease or increase this mean. Randomization of the daily pattern correlations has no strong impact on the size of the outbreak in either the coinfection or the independent spreading cases. We also observe that an increase in the mean outbreak size does not always coincide with an increase in the outbreak probability; therefore, we argue that merely considering the mean outbreak size of all realizations may lead us into falsely estimating the outbreak risks. Our results suggest that some sort of contact randomization in the organizational level in schools, events or hospitals might help to suppress the spreading dynamics while the risk of an outbreak is high.Sina SajjadiMohammad Reza EjtehadiFakhteh GhanbarnejadPublic Library of Science (PLoS)articleMedicineRScienceQENPLoS ONE, Vol 16, Iss 7, p e0253563 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Sina Sajjadi Mohammad Reza Ejtehadi Fakhteh Ghanbarnejad Impact of temporal correlations on high risk outbreaks of independent and cooperative SIR dynamics.
description	We first propose a quantitative approach to detect high risk outbreaks of independent and coinfective SIR dynamics on three empirical networks: a school, a conference and a hospital contact network. This measurement is based on the k-means clustering method and identifies proper samples for calculating the mean outbreak size and the outbreak probability. Then we systematically study the impact of different temporal correlations on high risk outbreaks over the original and differently shuffled counterparts of each network. We observe that, on the one hand, in the coinfection process, randomization of the sequence of the events increases the mean outbreak size of high-risk cases. On the other hand, these correlations do not have a consistent effect on the independent infection dynamics, and can either decrease or increase this mean. Randomization of the daily pattern correlations has no strong impact on the size of the outbreak in either the coinfection or the independent spreading cases. We also observe that an increase in the mean outbreak size does not always coincide with an increase in the outbreak probability; therefore, we argue that merely considering the mean outbreak size of all realizations may lead us into falsely estimating the outbreak risks. Our results suggest that some sort of contact randomization in the organizational level in schools, events or hospitals might help to suppress the spreading dynamics while the risk of an outbreak is high.
format	article
author	Sina Sajjadi Mohammad Reza Ejtehadi Fakhteh Ghanbarnejad
author_facet	Sina Sajjadi Mohammad Reza Ejtehadi Fakhteh Ghanbarnejad
author_sort	Sina Sajjadi
title	Impact of temporal correlations on high risk outbreaks of independent and cooperative SIR dynamics.
title_short	Impact of temporal correlations on high risk outbreaks of independent and cooperative SIR dynamics.
title_full	Impact of temporal correlations on high risk outbreaks of independent and cooperative SIR dynamics.
title_fullStr	Impact of temporal correlations on high risk outbreaks of independent and cooperative SIR dynamics.
title_full_unstemmed	Impact of temporal correlations on high risk outbreaks of independent and cooperative SIR dynamics.
title_sort	impact of temporal correlations on high risk outbreaks of independent and cooperative sir dynamics.
publisher	Public Library of Science (PLoS)
publishDate	2021
url	https://doaj.org/article/552f5932a0c7435fa102bab7bdd006a6
work_keys_str_mv	AT sinasajjadi impactoftemporalcorrelationsonhighriskoutbreaksofindependentandcooperativesirdynamics AT mohammadrezaejtehadi impactoftemporalcorrelationsonhighriskoutbreaksofindependentandcooperativesirdynamics AT fakhtehghanbarnejad impactoftemporalcorrelationsonhighriskoutbreaksofindependentandcooperativesirdynamics
_version_	1718375124154974208

Impact of temporal correlations on high risk outbreaks of independent and cooperative SIR dynamics.

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