Abstract Background After the first COVID-19 wave caused by the ancestral lineage, the pandemic has been fueled from the continuous emergence of new SARS-CoV-2 variants. Understanding key time-to-event periods for each emerging variant of concern is critical as it can provide insights into the future trajectory of the virus and help inform outbreak preparedness and response planning. Here, we aim to examine how the incubation period, serial interval, and generation time have changed from the ancestral SARS-CoV-2 lineage to different variants of concern. Methods We conducted a systematic review and meta-analysis that synthesized the estimates of incubation period, serial interval, and generation time (both realized and intrinsic) for the ancestral lineage, Alpha, Beta, and Omicron variants of SARS-CoV-2. Results Our study included 280 records obtained from 147 household studies, contact tracing studies, or studies where epidemiological links were known. With each emerging variant, we found a progressive shortening of each of the analyzed key time-to-event periods, although we did not find statistically significant differences between the Omicron subvariants. We found that Omicron BA.1 had the shortest pooled estimates for the incubation period (3.49 days, 95% CI: 3.13–4.86 days), Omicron BA.5 for the serial interval (2.37 days, 95% CI: 1.71–3.04 days), and Omicron BA.1 for the realized generation time (2.99 days, 95% CI: 2.48–3.49 days). Only one estimate for the intrinsic generation time was available for Omicron subvariants: 6.84 days (95% CrI: 5.72–8.60 days) for Omicron BA.1. The ancestral lineage had the highest pooled estimates for each investigated key time-to-event period. We also observed shorter pooled estimates for the serial interval compared to the incubation period across the virus lineages. When pooling the estimates across different virus lineages, we found considerable heterogeneities ( I 2 &gt; 80%; I 2 refers to the percentage of total variation across studies that is due to heterogeneity rather than chance), possibly resulting from heterogeneities between the different study populations (e.g., deployed interventions, social behavior, demographic characteristics). Conclusions Our study supports the importance of conducting contact tracing and epidemiological investigations to monitor changes in SARS-CoV-2 transmission patterns. Our findings highlight a progressive shortening of the incubation period, serial interval, and generation time, which can lead to epidemics that spread faster, with larger peak incidence, and harder to control. We also consistently found a shorter serial interval than incubation period, suggesting that a key feature of SARS-CoV-2 is the potential for pre-symptomatic transmission. These observations are instrumental to plan for future COVID-19 waves. 

pdf/assessing-changes-in-incubation-period-serial-interval-and-4ikij46v4b.pdf

Assessing changes in incubation period, serial interval, and generation time of SARS-CoV-2 variants of concern: a systematic review and meta-analysis

Background: After the first COVID-19 wave caused by the ancestral lineage, the pandemic has been fueled from the continuous emergence of new SARS-CoV-2 variants. Understanding key time-to-event periods for each emerging variant of concern is critical as it can provide insights into the future trajectory of the virus and help inform outbreak preparedness and response planning. Here, we aim to examine how the incubation period, serial interval, and generation time have changed from the ancestral SARS-CoV-2 lineage to different variants of concern. Methods: We conducted a systematic review and meta-analysis that synthesized the estimates of incubation period, serial interval, and generation time (both realized and intrinsic) for the ancestral lineage, Alpha, Beta, and Omicron variants of SARS-CoV-2. Results: Our study included 274 records obtained from 147 household studies, contact tracing studies or studies where epidemiological links were known. With each emerging variant, we found a progressive shortening of each of the analyzed key time-to-event periods. Specifically, we found that Omicron had the shortest pooled estimates for the incubation period (3.63 days, 95%CI: 3.25-4.02 days), serial interval (3.19 days, 95%CI: 2.95-3.43 days), and realized generation time (2.96 days, 95%CI: 2.54-3.38 days) whereas the ancestral lineage had the highest pooled estimates for each of them. We also observed shorter pooled estimates for the serial interval compared to the incubation period across the virus lineages. We found considerable heterogeneities (I2 > 80%) when pooling the estimates across different virus lineages, indicating potential unmeasured confounding from population factors (e.g., social behavior, deployed interventions). Conclusion: Our study supports the importance of conducting contact tracing and epidemiological investigations to monitor changes in SARS-CoV-2 transmission patterns. Our findings highlight a progressive shortening of the incubation period, serial interval, and generation time, which can lead to epidemics that spread faster, with larger peak incidence, and harder to control. We also consistently found a shorter serial interval than incubation period, suggesting that a key feature of SARS-CoV-2 is the potential for pre-symptomatic transmission. These observations are instrumental to plan for future COVID-19 waves. Keywords: COVID-19, variants of concern, incubation period, serial interval, realized generation time, intrinsic generation time, systematic review, meta-analysis

/pdf/assessing-changes-in-incubation-period-serial-interval-and-1tokysx0.pdf

https://doi.org/10.1016/j.lanwpc.2022.100678

Risk of within-hotel transmission of SARS-CoV-2 during on-arrival quarantine in Hong Kong: an epidemiological and phylogenomic investigation

Initial response strategies to the COVID-19 pandemic were heavily reliant on nonpharmaceutical interventions (NPIs), a set of measures implemented to slow or even stop the spread of infection. Here, we reviewed key measures used during the COVID-19 pandemic.Some NPIs were successful in reducing the transmission of SARS-CoV-2. Personal protective measures such as face masks were widely used, and likely had some effect on transmission. The development and production of rapid antigen tests allowed self-diagnosis in the community, informing isolation and quarantine measures. Community-wide measures such as school closures, workplace closures and complete stay-at-home orders were able to reduce contacts and prevent transmission. They were widely used in the pandemic and contributed to reduce transmission in the community; however, there were also negative unintended consequences in the society and economy.NPIs slowed the spread of SARS-CoV-2 and are essential for pandemic preparedness and response. Understanding which measures are more effective at reducing transmission with lower costs is imperative. 

Nonpharmaceutical interventions for managing SARS-CoV-2

Purpose of review Initial response strategies to the COVID-19 pandemic were heavily reliant on nonpharmaceutical interventions (NPIs), a set of measures implemented to slow or even stop the spread of infection. Here, we reviewed key measures used during the COVID-19 pandemic. Recent findings Some NPIs were successful in reducing the transmission of SARS-CoV-2. Personal protective measures such as face masks were widely used, and likely had some effect on transmission. The development and production of rapid antigen tests allowed self-diagnosis in the community, informing isolation and quarantine measures. Community-wide measures such as school closures, workplace closures and complete stay-at-home orders were able to reduce contacts and prevent transmission. They were widely used in the pandemic and contributed to reduce transmission in the community; however, there were also negative unintended consequences in the society and economy. Summary NPIs slowed the spread of SARS-CoV-2 and are essential for pandemic preparedness and response. Understanding which measures are more effective at reducing transmission with lower costs is imperative.

https://journals.lww.com/co-pulmonarymedicine/Fulltext/9900/Nonpharmaceutical_interventions_for_managing.54.aspx

Background: Hong Kong has enforced stringent travel restrictions particularly for inbound travellers since the emergence of SARS-CoV-2. Understanding the characteristics of imported COVID-19 cases is important for establishing evidence-based control measures. Methods: We conducted a retrospective cohort study to summarise the characteristics of cases classified as imported cases that were detected on or soon after arrival into Hong Kong from 13 November 2020 through to 31 January 2022, when all arriving persons were required to quarantine in a hotel or a designated quarantine facility. We analysed individual demographics, and clinical information including symptoms and disease severity, virus variants, and Ct values. Results: There were 2269 imported COVID-19 cases aged 0-85 years identified in Hong Kong. Almost half (48.6%) of the imported cases were detected on arrival. A shorter median delay from arrival to isolation was observed in Delta and Omicron cases (3 days) than cases infected with the ancestral strain and other variants (12 days; p<0.001) while lower Ct values at isolation were observed in cases infected with Omicron than the ancestral strain or other variants. No Omicron cases were detected beyond 14 days after arrival, and the cases (n=58, 2.6%) detected after 14 days of quarantine more frequently presented without symptoms at isolation and had a higher RT-PCR Ct-value during isolation. At least some of these cases were post-arrival infections. Conclusions: Testing inbound travellers at arrival and during on-arrival quarantine can detect imported cases early although it may not be sufficient to prevent all introductions of COVID-19 into the community. Public health measures should be adjusted in responses to the emergence of new variants of SARS-CoV-2 based on the epidemiologic evidence from continuous surveillance.

An observational study on imported COVID-19 cases in Hong Kong during mandatory on-arrival hotel quarantine

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.

/pdf/insights-into-covid-19-epidemiology-and-control-from-27uu3n0l.pdf

Insights into COVID-19 epidemiology and control from temporal changes in serial interval distributions in Hong Kong

With the emergence of SARS-CoV-2 variants that eluded immunity from vaccines and prior infections, vaccine shortages and their effectiveness pose unprecedented challenges for governments to expand booster vaccination programs. Fractionation of vaccine doses might be an effective strategy to help society to face these challenges, which may have comparable efficacies in contrast with the standard doses. In this study, we analyzed the relationship between in-vitro neutralization levels and the observed efficacies against asymptomatic and symptomatic infection of ten types of COVID-19 vaccines using data from 13 studies from vaccination and convalescent cohorts. We further projected efficacies for fractional doses based on 51 studies included in our systematic review. By comparing with the convalescent level, vaccine efficacy increases from 8.8% (95% CI: 1.4%, 16.1%) to 71.8% (95% CI: 63.0%, 80.7%) against asymptomatic infection, and from 33.6% (95% CI: 23.6%, 43.6%) to 98.6% (95% CI: 97.6%, 99.7%) against symptomatic infection, respectively, along with the mean neutralization level from 0.1 to 10 folds of convalescent level. And mRNA vaccines provide the strongest protection, and decrease slowly for fractional dosing between 50% and 100% dosage. Our results are consistent with studies for immune protection from COVID-19 infection. Based on our study, we expect that fractional dose vaccination could provide a partial immunity for SARS-CoV-2 virus. Fractional doses of vaccines could be a viable vaccination strategy compared to full-dose vaccination and deserves further exploration.

/pdf/predictive-efficacies-of-vaccine-dose-fractionation-using-3snhax6o.pdf

Predictive efficacies of vaccine dose fractionation using neutralizing antibody levels

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An observational study on imported COVID-19 cases in Hong Kong during mandatory on-arrival hotel quarantine

Insights into COVID-19 epidemiology and control from temporal changes in serial interval distributions in Hong Kong

Predictive efficacies of vaccine dose fractionation using neutralizing antibody levels