COVID-19 Exposure Notification in Simulated Real-World Environments
Abstract
Privacy-preserving contact tracing mobile applications, such as those that use the Google-Apple Exposure Notification (GAEN) service, have the potential to limit the spread of COVID-19 in communities, but the privacy-preserving aspects of the protocol make it difficult to assess the performance of the apps in real-world populations. To address this gap, we exercised the CovidWatch app on both Android and iOS phones in a variety of scripted real-world scenarios, relevant to the lives of university students and employees. We collected exposure data from the app and from the lower-level Android service, and compared it to the phones' actual distances and durations of exposure, to assess the sensitivity and specificity of the GAEN service configuration as of February 2021. Based on the app's reported ExposureWindows and alerting thresholds for Low and High alerts, our assessment is that the chosen configuration is highly sensitive under a range of realistic scenarios and conditions. With this configuration, the app is likely to capture many long-duration encounters, even at distances greater than six feet, which may be desirable under conditions with increased risk of airborne transmission.
Document Details
- Document Type
- Technical Report
- Publication Date
- Apr 15, 2022
- Accession Number
- AD1167312
Entities
People
- Joseph St. Germain
- M. C. Schiefelbein
- Richard C. Gervin
- Steven L. Mazzola
Organizations
- Massachusetts Institute of Technology