Risk estimation of SARS-CoV-2 transmission from bluetooth low energy measurements

Abstract Digital contact tracing approaches based on Bluetooth low energy (BLE) have the potential to efficiently contain and delay outbreaks of infectious diseases such as the ongoing SARS-CoV-2 pandemic. In this work we propose a machine learning based approach to reliably detect subjects that hav...

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Autores principales:	Felix Sattler, Jackie Ma, Patrick Wagner, David Neumann, Markus Wenzel, Ralf Schäfer, Wojciech Samek, Klaus-Robert Müller, Thomas Wiegand
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2020
Materias:	Computer applications to medicine. Medical informatics R858-859.7
Acceso en línea:	https://doaj.org/article/b9e0aea758e242848b57b9e08fe2a1eb
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spelling	oai:doaj.org-article:b9e0aea758e242848b57b9e08fe2a1eb2021-12-02T18:01:46ZRisk estimation of SARS-CoV-2 transmission from bluetooth low energy measurements10.1038/s41746-020-00340-02398-6352https://doaj.org/article/b9e0aea758e242848b57b9e08fe2a1eb2020-10-01T00:00:00Zhttps://doi.org/10.1038/s41746-020-00340-0https://doaj.org/toc/2398-6352Abstract Digital contact tracing approaches based on Bluetooth low energy (BLE) have the potential to efficiently contain and delay outbreaks of infectious diseases such as the ongoing SARS-CoV-2 pandemic. In this work we propose a machine learning based approach to reliably detect subjects that have spent enough time in close proximity to be at risk of being infected. Our study is an important proof of concept that will aid the battery of epidemiological policies aiming to slow down the rapid spread of COVID-19.Felix SattlerJackie MaPatrick WagnerDavid NeumannMarkus WenzelRalf SchäferWojciech SamekKlaus-Robert MüllerThomas WiegandNature PortfolioarticleComputer applications to medicine. Medical informaticsR858-859.7ENnpj Digital Medicine, Vol 3, Iss 1, Pp 1-4 (2020)
institution	DOAJ
collection	DOAJ
language	EN
topic	Computer applications to medicine. Medical informatics R858-859.7
spellingShingle	Computer applications to medicine. Medical informatics R858-859.7 Felix Sattler Jackie Ma Patrick Wagner David Neumann Markus Wenzel Ralf Schäfer Wojciech Samek Klaus-Robert Müller Thomas Wiegand Risk estimation of SARS-CoV-2 transmission from bluetooth low energy measurements
description	Abstract Digital contact tracing approaches based on Bluetooth low energy (BLE) have the potential to efficiently contain and delay outbreaks of infectious diseases such as the ongoing SARS-CoV-2 pandemic. In this work we propose a machine learning based approach to reliably detect subjects that have spent enough time in close proximity to be at risk of being infected. Our study is an important proof of concept that will aid the battery of epidemiological policies aiming to slow down the rapid spread of COVID-19.
format	article
author	Felix Sattler Jackie Ma Patrick Wagner David Neumann Markus Wenzel Ralf Schäfer Wojciech Samek Klaus-Robert Müller Thomas Wiegand
author_facet	Felix Sattler Jackie Ma Patrick Wagner David Neumann Markus Wenzel Ralf Schäfer Wojciech Samek Klaus-Robert Müller Thomas Wiegand
author_sort	Felix Sattler
title	Risk estimation of SARS-CoV-2 transmission from bluetooth low energy measurements
title_short	Risk estimation of SARS-CoV-2 transmission from bluetooth low energy measurements
title_full	Risk estimation of SARS-CoV-2 transmission from bluetooth low energy measurements
title_fullStr	Risk estimation of SARS-CoV-2 transmission from bluetooth low energy measurements
title_full_unstemmed	Risk estimation of SARS-CoV-2 transmission from bluetooth low energy measurements
title_sort	risk estimation of sars-cov-2 transmission from bluetooth low energy measurements
publisher	Nature Portfolio
publishDate	2020
url	https://doaj.org/article/b9e0aea758e242848b57b9e08fe2a1eb
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Risk estimation of SARS-CoV-2 transmission from bluetooth low energy measurements

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