Paper on addressing potential bias in R(t) for COVID-19

PhD student Jesse Knight and Dr. Mishra published a paper titled “Estimating effective reproduction number using generation time versus serial interval, with application to covid-19 in the Greater Toronto Area, Canada” in Infectious Disease Modelling.

Brief summary:
The effective reproduction number R(t) is a well-known measure of epidemic potential, reflecting the average number of new infections transmitted by each current infection. R(t) can be calculated based on recent daily case counts and the average time between infections. Since the moment of infection is often hard to determine, the time between infections is often approximated by the time between symptom onset. However, we find that this can result in biased estimates of R(t) for COVID-19 because the time between infections cannot be negative (by definition), whereas the time between symptom onset can be negative due to variability in the incubation period (pre-symptomatic transmission), such as in the case of COVID-19. We also developed a method to estimate the distribution of time between infections based on the time between symptom onset and the incubation period, allowing unbiased estimates of R(t).

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