Evolving Epidemiological Characteristics of COVID-19 in Hong Kong From January to August 2020: Retrospective Study

Abstract

Background: COVID-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.

Objective: This 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 (R_t), 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.

Methods: We 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). R_t was estimated with the best fitted distribution for serial intervals.

Results: The two epidemic waves were characterized by imported cases and clusters of local cases, respectively. R_t 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.

Conclusions: First, 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.

Keywords: COVID-19; China; Hong Kong; SARS-CoV-2; case study; containment delay; epidemiology; evolving epidemiology; intervention; public health; serial interval; transmission.

Figure 1

Epidemic curve of COVID-19 and timeline for major interventions in Hong Kong. A1: School closure, January 25-May 26, 2020. A2: School closure, July 13, 2020 to ongoing as of August 2, 2020. B1: The government spearheaded work-from-home arrangements, January 29-March 1, 2020. B2: The government spearheaded work-from-home arrangements, March 23-May 3, 2020. B3: The government spearheaded work-from-home arrangements, July 20, 2020 to ongoing as of August 2, 2020. C1: Regulations imposed on dine-in services, March 28-April 23, 2020: (1) tables ≥1.5 meters apart, (2) ≤4 persons per table, and (3) number of customers ≤50% of capacity. C2: Regulations imposed on dine-in services, April 24-May 7, 2020: (1) tables ≥1.5 meters apart and (2) ≤4 persons per table. C3: Regulations imposed on dine-in services, May 8-June 18, 2020: (1) tables ≥1.5 meters apart and (2) ≤8 persons per table. C4: Regulations imposed on dine-in services, June 19-July 10, 2020: tables ≥1.5 meters apart. C5: Regulations imposed on dine-in services, July 11-July 14, 2020: (1) tables ≥1.5 meters apart, (2) ≤8 persons per table, and (3) number of customers ≤60% of capacity. C6: Regulations imposed on dine-in services, July 15-July 28, 2020: (1) tables ≥1.5 meters apart, (2) ≤4 persons per table, (3) number of customers ≤50% of capacity, and (4) no dine-in service from 6 PM to 4:59 AM every day. C7: No dine-in service at any time, July 29-July 30, 2020. C8: Regulations imposed on dine-in services, July 31, 2020 to ongoing as of August 2, 2020: (1) tables ≥1.5 meters apart, (2) ≤2 persons per table, (3) number of customers ≤50% of capacity, and (4) no dine-in service from 6 PM to 4:59 AM every day.

Figure 2

Age-specific transmission events in (A) all settings, (B) households, (C) social settings, (D) work settings, and (E) institutions.