Author: Hatke, Gary F.; Montanari, Monica; Appadwedula, Swaroop; Wentz, Michael; Meklenburg, John; Ivers, Louise; Watson, Jennifer; Fiore, Paul
Title: Using Bluetooth Low Energy (BLE) Signal Strength Estimation to Facilitate Contact Tracing for COVID-19 Cord-id: xh4volns Document date: 2020_6_28
ID: xh4volns
Snippet: The process of contact tracing to reduce the spread of highly infectious and life-threatening diseases has traditionally been a primarily manual process managed by public health entities. This process becomes challenged when faced with a pandemic of the proportions of SARS-CoV2. Digital contact tracing has been proposed as way to augment manual contact tracing and lends itself to widely proliferated devices such as cell phones and wearables. This paper describes a method and analysis of determin
Document: The process of contact tracing to reduce the spread of highly infectious and life-threatening diseases has traditionally been a primarily manual process managed by public health entities. This process becomes challenged when faced with a pandemic of the proportions of SARS-CoV2. Digital contact tracing has been proposed as way to augment manual contact tracing and lends itself to widely proliferated devices such as cell phones and wearables. This paper describes a method and analysis of determining whether two cell phones, carried by humans, were in persistent contact of no more than 6 feet over 15 minutes using Bluetooth Low Energy signals. The paper describes the approach to detecting these signals, as well as a data-driven performance analysis showing that larger numbers of samples coupled with privacy preserving auxiliary information improves detection performance.
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