Serial Intervals and Case Isolation Delays for Coronavirus Disease 2019: A Systematic Review and Meta-Analysis.

BACKGROUND: Estimates of the serial interval distribution contribute to our understanding of the transmission dynamics of coronavirus disease 2019 (COVID-19). Here, we aimed to summarize the existing evidence on serial interval distributions and delays in case isolation for COVID-19. METHODS: We conducted a systematic review of the published literature and preprints in PubMed on 2 epidemiological parameters, namely, serial intervals and delay intervals relating to isolation of cases for COVID-19 from 1 January 2020 to 22 October 2020 following predefined eligibility criteria. We assessed the variation in these parameter estimates using correlation and regression analysis. RESULTS: Of 103 unique studies on serial intervals of COVID-19, 56 were included, providing 129 estimates. Of 451 unique studies on isolation delays, 18 were included, providing 74 estimates. Serial interval estimates from 56 included studies varied from 1.0 to 9.9 days, while case isolation delays from 18 included studies varied from 1.0 to 12.5 days, which were associated with spatial, methodological, and temporal factors. In mainland China, the pooled mean serial interval was 6.2 days (range, 5.1-7.8) before the epidemic peak and reduced to 4.9 days (range, 1.9-6.5) after the epidemic peak. Similarly, the pooled mean isolation delay related intervals were 6.0 days (range, 2.9-12.5) and 2.4 days (range, 2.0-2.7) before and after the epidemic peak, respectively. There was a positive association between serial interval and case isolation delay. CONCLUSIONS: Temporal factors, such as different control measures and case isolation in particular, led to shorter serial interval estimates over time. Correcting transmissibility estimates for these time-varying distributions could aid mitigation efforts.

The Incubation Period Distribution of Coronavirus Disease 2019: A Systematic Review and Meta-analysis.

Incubation period is an important parameter to inform quarantine period and to study transmission dynamics of infectious diseases. We conducted a systematic review and meta-analysis on published estimates of the incubation period distribution of coronavirus disease 2019, and showed that the pooled median of the point estimates of the mean, median and 95th percentile for incubation period are 6.3 days (range, 1.8-11.9 days), 5.4 days (range, 2.0-17.9 days), and 13.1 days (range, 3.2-17.8 days), respectively. Estimates of the mean and 95th percentile of the incubation period distribution were considerably shorter before the epidemic peak in China compared to after the peak, and variation was also noticed for different choices of methodological approach in estimation. Our findings implied that corrections may be needed before directly applying estimates of incubation period into control of or further studies on emerging infectious diseases.

COVID-19 transmission in Hong Kong despite universal masking.

OBJECTIVES: mask-wearing outside the home has been almost universal in Hong Kong since late January 2020 with very high compliance. Nevertheless, community spread of COVID-19 has still occurred. We aimed to assess the settings where COVID-19 transmission occurred and determine the fraction of transmission events that occurred in settings where masks are not usually worn. METHODS: we reviewed detailed information provided by the Hong Kong Department of Health on local COVID-19 cases diagnosed up to 30 September 2020 to determine the most likely settings in which transmission occurred. We classified them in probably mask-on or mask-of and compared the prevalence of asymptomatic infections in these settings. RESULTS: among the 2425 cases (65.3%, 2425/3711) with information on transmission setting, 77.6% of the transmission occurred in household and social settings where face masks are not usually worn. Infections that occurred in mask-on settings were more likely to be asymptomatic (adjusted odds ratio 1.33; 95% confidence interval: 1.04, 1.68). CONCLUSIONS: we conclude that universal mask-wearing can reduce transmission, but transmission can continue to occur in settings where face masks are not usually worn. The higher proportion of asymptomatic cases in mask-on settings could be related to a milder disease presentation or earlier case detection.