Speaker: Joanna Masel (University of Arizona).
Title: Quantifying risk of SARS-CoV-2 transmission for use in the Covid Watch app
Abstract: Privacy-preserving exposure notification apps recommend quarantine based on Bluetooth signal. Apps deployed so far recommend quarantine using three binary decision points; when timing falls within a fixed window of infectiousness, duration is above a threshold, and attenuation is below a threshold. However, Bluetooth attenuation is not a reliable measure of distance, and infection risk is not a binary function of distance, nor duration, nor timing. Here we describe a method to integrate all sources of information (including new data on the relationship between distance and Bluetooth attenuation) to more accurately estimate relative infection risk. We also provide a method to calculate the probability of current or future infectiousness, which is a function of initial infection risk and the number of symptom-free days since exposure, and any negative test results. Public health authorities can use either probability, implemented in the Covid Watch app, to apply a threshold for quarantine.