• Kin On Kwok, Wan In Wei, Ying Huang, Kai Man Kam, ChanEmily Ying YangEYY0000-0002-8854-5093JC School of Public Health and Primary Care, The Chinese University of Hong Kong, Hong Kong, China (Hong Kong).GX Foundation, Hong Kong, China (Hong Kong)., Steven Riley, Ho Hin Henry Chan, HuiDavid Shu CheongDSC0000-0003-4382-2445Stanley Ho Centre for Emerging Infectious Diseases, The Chinese University of Hong Kong, Hong Kong, China (Hong Kong).Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Hong Kong, China (, Samuel Yeung Shan Wong, and Eng Kiong Yeoh.
• JC School of Public Health and Primary Care, The Chinese University of Hong Kong, Hong Kong, China (Hong Kong).
• J. Med. Internet Res. 2021 Apr 16; 23 (4): e26645.

BackgroundCOVID-19 has plagued the globe, with multiple SARS-CoV-2 clusters hinting at its evolving epidemiology. Since the disease course is governed by important epidemiological parameters, including containment delays (time between symptom onset and mandatory isolation) and serial intervals (time between symptom onsets of infector-infectee pairs), understanding their temporal changes helps to guide interventions.ObjectiveThis study aims to characterize the epidemiology of the first two epidemic waves of COVID-19 in Hong Kong by doing the following: (1) estimating the containment delays, serial intervals, effective reproductive number (Rt), and proportion of asymptomatic cases; (2) identifying factors associated with the temporal changes of the containment delays and serial intervals; and (3) depicting COVID-19 transmission by age assortativity and types of social settings.MethodsWe retrieved the official case series and the Apple mobility data of Hong Kong from January-August 2020. The empirical containment delays and serial intervals were fitted to theoretical distributions, and factors associated with their temporal changes were quantified in terms of percentage contribution (the percentage change in the predicted outcome from multivariable regression models relative to a predefined comparator). Rt was estimated with the best fitted distribution for serial intervals.ResultsThe two epidemic waves were characterized by imported cases and clusters of local cases, respectively. Rt peaked at 2.39 (wave 1) and 3.04 (wave 2). The proportion of asymptomatic cases decreased from 34.9% (0-9 years) to 12.9% (≥80 years). Log-normal distribution best fitted the 1574 containment delays (mean 5.18 [SD 3.04] days) and the 558 serial intervals (17 negative; mean 4.74 [SD 4.24] days). Containment delays decreased with involvement in a cluster (percentage contribution: 10.08%-20.73%) and case detection in the public health care sector (percentage contribution: 27.56%, 95% CI 22.52%-32.33%). Serial intervals decreased over time (6.70 days in wave 1 versus 4.35 days in wave 2) and with tertiary transmission or beyond (percentage contribution: -50.75% to -17.31%), but were lengthened by mobility (percentage contribution: 0.83%). Transmission within the same age band was high (18.1%). Households (69.9%) and social settings (20.3%) were where transmission commonly occurred.ConclusionsFirst, the factors associated with reduced containment delays suggested government-enacted interventions were useful for achieving outbreak control and should be further encouraged. Second, the shorter serial intervals associated with the composite mobility index calls for empirical surveys to disentangle the role of different contact dimensions in disease transmission. Third, the presymptomatic transmission and asymptomatic cases underscore the importance of remaining vigilant about COVID-19. Fourth, the time-varying epidemiological parameters suggest the need to incorporate their temporal variations when depicting the epidemic trajectory. Fifth, the high proportion of transmission events occurring within the same age group supports the ban on gatherings outside of households, and underscores the need for residence-centered preventive measures.©Kin On Kwok, Wan In Wei, Ying Huang, Kai Man Kam, Emily Ying Yang Chan, Steven Riley, Ho Hin Henry Chan, David Shu Cheong Hui, Samuel Yeung Shan Wong, Eng Kiong Yeoh. Originally published in the Journal of Medical Internet Research (http://www.jmir.org), 16.04.2021.

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