Diagnostic serial interval as an alternative measure of clinical serial interval using ancestral COVID-19 waves in Hong Kong and mainland China

To estimate the reproductive numbers (Rt), it is essential to infer generation time, which is often approximated by serial interval (SI). The SI based on clinical outcomes is not free from recall biases and even such clinical information is not always available. We defined diagnostic serial interval (SId), as a potential alternative metric and compared with traditional SI. We analyzed confirmed COVID-19 cases from three ancestral waves in Hong Kong and the first wave in mainland China. Using Bayesian methods, we inferred the distributions of effective SI and SId, along with onset-to-reporting delays, and compared the resulting estimates. The distributions of SI and SId were comparable across waves, with shorter means observed in SId. Reporting delays for infectors (d1) were longer than these for infectees (d2), which was identified as a key factor influencing the temporal variation in SId. The PHSMs, case profile and demography were also found to be significant factors of SId. Time-varying Rt estimates derived from both SI and SId were comparable, with median absolute differences ranging from 0.12 to 0.19. Therefore, SId shows potentials as an alternative metric to SI for estimating Rt in assessing COVID-19 transmission dynamics can be extended for other respiratory viruses.