Using a Mathematical Model to Investigate the Efficacy of Asymptomatic Testing to Detect SARS-CoV-2

A mathematical model was constructed to investigate the efficacy of asymptomatic testing for SARS-CoV-2 detection. Preliminary data suggests that the stage of disease at the time of testing impacts its efficacy. The probability of being detected by the asymptomatic test was compared by the number of days waited until taking the test since arrival given the unknown state of disease at arrival, the variability of the infectious period and whether case detection efforts were undergone prior to arrival. It was found that if assuming an equal probability of being in the incubation stage or an asymptomatic infectious stage, waiting until the fifth day since arrival to be tested is the earliest testing date that results in more detected than undetected cases. Additionally, in the 50% of COVID-19 cases with an infectious period longer than 22 days, there are limited differences in the probability of being detected when tested within the first 2, 5 or 8 days since arrival.

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