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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 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.

SUBMITTER: Sattler F

PROVIDER: S-EPMC7538938 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature

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

Sattler Felix F Ma Jackie J Wagner Patrick P Neumann David D Wenzel Markus M Schäfer Ralf R Samek Wojciech W Müller Klaus-Robert KR Wiegand Thomas T

NPJ digital medicine 20201006

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 ...[more]

PMID: 33083564

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