Digital proximity tracing on empirical contact networks for pandemic control

Digital contact tracing is increasingly considered as one of the tools to control infectious disease outbreaks, in particular the COVID-19 epidemic. Here, the authors present a modeling framework informed by empirical high-resolution contact data to analyze the impact of digital contact tracing apps...

Descripción completa

Guardado en:
Detalles Bibliográficos
Autores principales: G. Cencetti, G. Santin, A. Longa, E. Pigani, A. Barrat, C. Cattuto, S. Lehmann, M. Salathé, B. Lepri
Formato: article
Lenguaje:EN
Publicado: Nature Portfolio 2021
Materias:
Q
Acceso en línea:https://doaj.org/article/ac6b3461ae074685b3b8c94fb8c2002a
Etiquetas: Agregar Etiqueta
Sin Etiquetas, Sea el primero en etiquetar este registro!
id oai:doaj.org-article:ac6b3461ae074685b3b8c94fb8c2002a
record_format dspace
spelling oai:doaj.org-article:ac6b3461ae074685b3b8c94fb8c2002a2021-12-02T13:15:56ZDigital proximity tracing on empirical contact networks for pandemic control10.1038/s41467-021-21809-w2041-1723https://doaj.org/article/ac6b3461ae074685b3b8c94fb8c2002a2021-03-01T00:00:00Zhttps://doi.org/10.1038/s41467-021-21809-whttps://doaj.org/toc/2041-1723Digital contact tracing is increasingly considered as one of the tools to control infectious disease outbreaks, in particular the COVID-19 epidemic. Here, the authors present a modeling framework informed by empirical high-resolution contact data to analyze the impact of digital contact tracing apps.G. CencettiG. SantinA. LongaE. PiganiA. BarratC. CattutoS. LehmannM. SalathéB. LepriNature PortfolioarticleScienceQENNature Communications, Vol 12, Iss 1, Pp 1-12 (2021)
institution DOAJ
collection DOAJ
language EN
topic Science
Q
spellingShingle Science
Q
G. Cencetti
G. Santin
A. Longa
E. Pigani
A. Barrat
C. Cattuto
S. Lehmann
M. Salathé
B. Lepri
Digital proximity tracing on empirical contact networks for pandemic control
description Digital contact tracing is increasingly considered as one of the tools to control infectious disease outbreaks, in particular the COVID-19 epidemic. Here, the authors present a modeling framework informed by empirical high-resolution contact data to analyze the impact of digital contact tracing apps.
format article
author G. Cencetti
G. Santin
A. Longa
E. Pigani
A. Barrat
C. Cattuto
S. Lehmann
M. Salathé
B. Lepri
author_facet G. Cencetti
G. Santin
A. Longa
E. Pigani
A. Barrat
C. Cattuto
S. Lehmann
M. Salathé
B. Lepri
author_sort G. Cencetti
title Digital proximity tracing on empirical contact networks for pandemic control
title_short Digital proximity tracing on empirical contact networks for pandemic control
title_full Digital proximity tracing on empirical contact networks for pandemic control
title_fullStr Digital proximity tracing on empirical contact networks for pandemic control
title_full_unstemmed Digital proximity tracing on empirical contact networks for pandemic control
title_sort digital proximity tracing on empirical contact networks for pandemic control
publisher Nature Portfolio
publishDate 2021
url https://doaj.org/article/ac6b3461ae074685b3b8c94fb8c2002a
work_keys_str_mv AT gcencetti digitalproximitytracingonempiricalcontactnetworksforpandemiccontrol
AT gsantin digitalproximitytracingonempiricalcontactnetworksforpandemiccontrol
AT alonga digitalproximitytracingonempiricalcontactnetworksforpandemiccontrol
AT epigani digitalproximitytracingonempiricalcontactnetworksforpandemiccontrol
AT abarrat digitalproximitytracingonempiricalcontactnetworksforpandemiccontrol
AT ccattuto digitalproximitytracingonempiricalcontactnetworksforpandemiccontrol
AT slehmann digitalproximitytracingonempiricalcontactnetworksforpandemiccontrol
AT msalathe digitalproximitytracingonempiricalcontactnetworksforpandemiccontrol
AT blepri digitalproximitytracingonempiricalcontactnetworksforpandemiccontrol
_version_ 1718393350679166976