Michael Höhle: Risk Scoring in Digital Contact Tracing Apps
Tid: On 2020-12-09 kl 15.15
Plats: Zoom, email organisers
Medverkande: Michael Höhle, Stockholm University
Inspired by the influential paper of Ferretti et al. (2020), many countries have decided to use a digital contact tracing app as part of their COVID-19 response. Due to its widespread availability on standard mobile phones and its privacy preserving decentralized approach, Google and Apple’s Exposure Notification (GAEN) framework based on Bluetooth Low Energy proximity tracing, has become the de-facto standard on which such digital contact tracing apps are based.
In this data-free talk, I will give a short introduction to the aims of digital contact tracing and then focus on the mathematical calculations occurring within the GAEN while determining the risk of being infected. In particular I will focus on the possibility to perform a more detailed computation of the so called Transmission Risk Level (TRL), which is an indication of how infectious a given individual is at the time of the potential exposure event. This TRL score computation is used as part of the German Corona-Warn-App (CWA) and consists of deducing infectiousness based on the day of upload via a stochastic model. I will end the talk with some general remarks about the importance of transparency when using mathematical risk scoring in applications that heavily depend on widespread voluntary use in the population.
CWA Team (2020), Epidemiological Motivation of the Transmission Risk Level, https://github.com/corona-warn-app/cwa-documentation/blob/master/transmission_risk.pdf
Ferretti, L., Wymant, C., Kendall, M., Zhao, L., Nurtay, A., Abeler-Dörner, L., Parker, M., Bonsall, D., & Fraser, C. (2020). Quantifying SARS-CoV-2 transmission suggests epidemic control with digital contact tracing. Science (New York, N.Y.), 368(6491), eabb6936. https://doi.org/10.1126/science.abb6936
Höhle, M. (2020), Risk Scoring in Digital Contact Tracing Apps, https://staff.math.su.se/hoehle/blog/2020/09/17/gaen_riskscoring.html
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