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The serial interval distribution is used to approximate the generation time distribution, an essential parameter to predict the effective reproductive number “ R t ”, a measure of transmissibility. However, serial interval distributions may change as an epidemic progresses rather than remaining constant. Here we show that serial intervals in Hong Kong varied over time, closely associated with the temporal variation in COVID-19 case profiles and public health and social measures that were implemented in response to surges in community transmission. Quantification of the variation over time in serial intervals led to improved estimation of R t , and provided additional insights into the impact of public health measures on transmission of infections. One-Sentence Summary Real-time estimates of serial interval distributions can improve assessment of COVID-19 transmission dynamics and control.
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Ali et al. (2022) studied this question.
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