Quantifying SARS-CoV-2 infection risk within the Apple/Google exposure notification framework to inform quarantine recommendations

Wilson, A. M.; Aviles, N.; Beamer, P. I.; Szabo, Z.; Ernst, K. C.; Masel, J.

Background: Bluetooth-based exposure notification apps can supplement manual contact tracing to reduce SARS-CoV-2 transmission. Their speed, scalability, and privacy preservation are generally acknowledged, but less exploited are smartphones' accurate measurement of duration, and ability to automatically calculate risk from multiple inputs. Methods: We model uncertainty in the shape of an exhaled virus-containing plume, inhalation parameters, and distance as a function of Bluetooth attenuation. We assume relative rates of viral shedding depend on the timing of exposure relative to symptom onset. We calibrate an exponential dose-response curve on the basis of the infection probabilities of household contacts. The conditional probability of current or future infectiousness, conditioned on how long post-exposure an exposed individual has been free of symptoms, decreases during quarantine, with shape determined by the distribution of incubation periods, proportion of asymptomatic cases, and distribution of asymptomatic shedding durations. It can be adjusted for negative test results using Bayes Theorem. Findings: As an example of our calculations, fifteen minutes of close contact with a high-shedding individual, given a 15% asymptomatic infection rate and no testing, would require 5- and 14-day quarantine for their risk of current or future infectiousness to fall below 0.84% and 0.14% risk, respectively. Interpretation: The Covid-Watch app is currently programmed either to use a threshold on initial infection risk to determine 14-day quarantine onset, or on the conditional probability of current and future infectiousness conditions to determine both quarantine and duration. Either threshold can be set by public health authorities.