Calculating the Probability that a Previously Susceptible Individual is Infected as a Function of Time Following...

Reliable assessment of disease state probabilities for an individual following a specific exposure event, such as an occupational exposure, is critical for managing isolation and quarantine and reducing onward transmission to susceptible individuals. Such assessments are particularly important for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), where infection, testing, and infectiousness vary substantially across individuals and time since exposure.

We present a method, accompanying software programs, and a publicly available website for calculating the probability that an individual is in each disease state immediately following an exposure event that may or may not have resulted in transmission of SARS-CoV-2. The framework integrates timing of exposure, test type and timing, and symptom status to estimate probabilities of latent infection, infectiousness, recovery, or no infection.

We illustrate the utility of this approach by calculating: (i) the time at which an exposed individual's risk of being infectious falls below an acceptable threshold; (ii) the benefit of a second test for asymptomatic individuals with an initial negative test; (iii) the value of polymerase chain reaction (PCR) and antigen testing for case counting; and (iv) the time at which the risk that an infected individual remains infectious becomes comparable to background population risk. The results demonstrate that test interpretation should not be done naively: a negative test may reflect absence of transmission, a false-negative result, rapid resolution of infection, or an unusually prolonged latent period, each with distinct implications for risk management.

Accurate differentiation among possible disease states following exposure is essential for informed public health decision-making. Our software provides a rigorous, transparent means to assess and clearly communicate state probabilities, enabling more nuanced interpretation of test results and better-supported decisions regarding isolation, quarantine, and testing strategies.