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

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 e...

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Detalles Bibliográficos
Autores principales: Sattler, Felix, Ma, Jackie, Wagner, Patrick, Neumann, David, Wenzel, Markus, Schäfer, Ralf, Samek, Wojciech, Müller, Klaus-Robert, Wiegand, Thomas
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2020
Materias:
Brief Communication
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7538938/
https://www.ncbi.nlm.nih.gov/pubmed/33083564
http://dx.doi.org/10.1038/s41746-020-00340-0
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author Sattler, Felix
Ma, Jackie
Wagner, Patrick
Neumann, David
Wenzel, Markus
Schäfer, Ralf
Samek, Wojciech
Müller, Klaus-Robert
Wiegand, Thomas
author_facet Sattler, Felix
Ma, Jackie
Wagner, Patrick
Neumann, David
Wenzel, Markus
Schäfer, Ralf
Samek, Wojciech
Müller, Klaus-Robert
Wiegand, Thomas
author_sort Sattler, Felix
collection PubMed
description 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.
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spelling pubmed-75389382020-10-19 Risk estimation of SARS-CoV-2 transmission from bluetooth low energy measurements Sattler, Felix Ma, Jackie Wagner, Patrick Neumann, David Wenzel, Markus Schäfer, Ralf Samek, Wojciech Müller, Klaus-Robert Wiegand, Thomas NPJ Digit Med Brief Communication 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. Nature Publishing Group UK 2020-10-06 /pmc/articles/PMC7538938/ /pubmed/33083564 http://dx.doi.org/10.1038/s41746-020-00340-0 Text en © The Author(s) 2020 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.
spellingShingle Brief Communication
Sattler, Felix
Ma, Jackie
Wagner, Patrick
Neumann, David
Wenzel, Markus
Schäfer, Ralf
Samek, Wojciech
Müller, Klaus-Robert
Wiegand, Thomas
Risk estimation of SARS-CoV-2 transmission from bluetooth low energy measurements
title 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_short 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
topic Brief Communication
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7538938/
https://www.ncbi.nlm.nih.gov/pubmed/33083564
http://dx.doi.org/10.1038/s41746-020-00340-0
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