Measurement-Based Evaluation Of Google/Apple Exposure Notification API For Proximity Detection in a Commuter Bus

TL;DR

This study evaluates the effectiveness of the Google/Apple Exposure Notification API in a bus environment, revealing complex radio effects and limited detection performance, with only modest improvements using threshold adjustments.

Contribution

It provides the first measurement-based analysis of GAEN API performance in a real-world bus setting, highlighting environmental impacts on proximity detection accuracy.

Findings

Attenuation levels do not reliably correlate with distance inside a bus.

The Swiss contact tracing rule would not trigger notifications in this environment.

Adjusting exposure thresholds can modestly improve detection rates.

Abstract

We report on the results of a measurement study carried out on a commuter bus in Dublin, Ireland using the Google/Apple Exposure Notification (GAEN) API. This API is likely to be widely used by Covid-19 contact tracing apps. Measurements were collected between 60 pairs of handset locations and are publicly available. We find that the attenuation level reported by the GAEN API need not increase with distance between handsets, consistent with there being a complex radio environment inside a bus caused by the metal-rich environment. Changing the people holding a pair of handsets, with the location of the handsets otherwise remaining unchanged, can cause variations of +/-10dB in the attenuation level reported by the GAEN API. Applying the rule used by the Swiss Covid-19 contact tracing app to trigger an exposure notification to our bus measurements we find that no exposure notifications would have been triggered despite the fact that all pairs of handsets were within 2m of one another for at least 15 mins. Applying an alternative threshold-based exposure notification rule can somewhat improve performance to a detection rate of 5% when an exposure duration threshold of 15 minutes is used, increasing to 8% when the exposure duration threshold is reduced to 10 mins. Stratifying the data by distance between pairs of handsets indicates that there is only a weak dependence of detection rate on distance.