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Autocorrelation of the susceptible-infected-susceptible process on networks

In this paper, we focus on the autocorrelation of the susceptible-infected-susceptible (SIS) process on networks. The [Formula: see text]-intertwined mean-field approximation (NIMFA) is applied to calculate the autocorrelation properties of the exact SIS process. We derive the autocorrelation of the...

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Detalles Bibliográficos
Autores principales: Liu, Qiang, Van Mieghem, Piet
Formato: Online Artículo Texto
Lenguaje:English
Publicado: American Physical Society 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7217534/
https://www.ncbi.nlm.nih.gov/pubmed/30011514
http://dx.doi.org/10.1103/PhysRevE.97.062309
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author Liu, Qiang
Van Mieghem, Piet
author_facet Liu, Qiang
Van Mieghem, Piet
author_sort Liu, Qiang
collection PubMed
description In this paper, we focus on the autocorrelation of the susceptible-infected-susceptible (SIS) process on networks. The [Formula: see text]-intertwined mean-field approximation (NIMFA) is applied to calculate the autocorrelation properties of the exact SIS process. We derive the autocorrelation of the infection state of each node and the fraction of infected nodes both in the steady and transient states as functions of the infection probabilities of nodes. Moreover, we show that the autocorrelation can be used to estimate the infection and curing rates of the SIS process. The theoretical results are compared with the simulation of the exact SIS process. Our work fully utilizes the potential of the mean-field method and shows that NIMFA can indeed capture the autocorrelation properties of the exact SIS process.
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spelling pubmed-72175342020-05-13 Autocorrelation of the susceptible-infected-susceptible process on networks Liu, Qiang Van Mieghem, Piet Phys Rev E Articles In this paper, we focus on the autocorrelation of the susceptible-infected-susceptible (SIS) process on networks. The [Formula: see text]-intertwined mean-field approximation (NIMFA) is applied to calculate the autocorrelation properties of the exact SIS process. We derive the autocorrelation of the infection state of each node and the fraction of infected nodes both in the steady and transient states as functions of the infection probabilities of nodes. Moreover, we show that the autocorrelation can be used to estimate the infection and curing rates of the SIS process. The theoretical results are compared with the simulation of the exact SIS process. Our work fully utilizes the potential of the mean-field method and shows that NIMFA can indeed capture the autocorrelation properties of the exact SIS process. American Physical Society 2018-06-11 2018-06 /pmc/articles/PMC7217534/ /pubmed/30011514 http://dx.doi.org/10.1103/PhysRevE.97.062309 Text en ©2018 American Physical Society This article is made available via the PMC Open Access Subset for unrestricted re-use and analyses in any form or by any means with acknowledgement of the original source.
spellingShingle Articles
Liu, Qiang
Van Mieghem, Piet
Autocorrelation of the susceptible-infected-susceptible process on networks
title Autocorrelation of the susceptible-infected-susceptible process on networks
title_full Autocorrelation of the susceptible-infected-susceptible process on networks
title_fullStr Autocorrelation of the susceptible-infected-susceptible process on networks
title_full_unstemmed Autocorrelation of the susceptible-infected-susceptible process on networks
title_short Autocorrelation of the susceptible-infected-susceptible process on networks
title_sort autocorrelation of the susceptible-infected-susceptible process on networks
topic Articles
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7217534/
https://www.ncbi.nlm.nih.gov/pubmed/30011514
http://dx.doi.org/10.1103/PhysRevE.97.062309
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