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Epidemic Threshold in Continuous-Time Evolving Networks
Current understanding of the critical outbreak condition on temporal networks relies on approximations (time scale separation, discretization) that may bias the results. We propose a theoretical framework to compute the epidemic threshold in continuous time through the infection propagator approach....
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
American Physical Society
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7219439/ https://www.ncbi.nlm.nih.gov/pubmed/29481258 http://dx.doi.org/10.1103/PhysRevLett.120.068302 |
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author | Valdano, Eugenio Fiorentin, Michele Re Poletto, Chiara Colizza, Vittoria |
author_facet | Valdano, Eugenio Fiorentin, Michele Re Poletto, Chiara Colizza, Vittoria |
author_sort | Valdano, Eugenio |
collection | PubMed |
description | Current understanding of the critical outbreak condition on temporal networks relies on approximations (time scale separation, discretization) that may bias the results. We propose a theoretical framework to compute the epidemic threshold in continuous time through the infection propagator approach. We introduce the weak commutation condition allowing the interpretation of annealed networks, activity-driven networks, and time scale separation into one formalism. Our work provides a coherent connection between discrete and continuous time representations applicable to realistic scenarios. |
format | Online Article Text |
id | pubmed-7219439 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | American Physical Society |
record_format | MEDLINE/PubMed |
spelling | pubmed-72194392020-05-13 Epidemic Threshold in Continuous-Time Evolving Networks Valdano, Eugenio Fiorentin, Michele Re Poletto, Chiara Colizza, Vittoria Phys Rev Lett Letters Current understanding of the critical outbreak condition on temporal networks relies on approximations (time scale separation, discretization) that may bias the results. We propose a theoretical framework to compute the epidemic threshold in continuous time through the infection propagator approach. We introduce the weak commutation condition allowing the interpretation of annealed networks, activity-driven networks, and time scale separation into one formalism. Our work provides a coherent connection between discrete and continuous time representations applicable to realistic scenarios. American Physical Society 2018-02-06 2018-02-09 /pmc/articles/PMC7219439/ /pubmed/29481258 http://dx.doi.org/10.1103/PhysRevLett.120.068302 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 | Letters Valdano, Eugenio Fiorentin, Michele Re Poletto, Chiara Colizza, Vittoria Epidemic Threshold in Continuous-Time Evolving Networks |
title | Epidemic Threshold in Continuous-Time Evolving Networks |
title_full | Epidemic Threshold in Continuous-Time Evolving Networks |
title_fullStr | Epidemic Threshold in Continuous-Time Evolving Networks |
title_full_unstemmed | Epidemic Threshold in Continuous-Time Evolving Networks |
title_short | Epidemic Threshold in Continuous-Time Evolving Networks |
title_sort | epidemic threshold in continuous-time evolving networks |
topic | Letters |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7219439/ https://www.ncbi.nlm.nih.gov/pubmed/29481258 http://dx.doi.org/10.1103/PhysRevLett.120.068302 |
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