Estimation of Serial Interval and Reproduction Number to Quantify the Transmissibility of SARS-CoV-2 Omicron Variant in South Korea

Jointly estimating epidemiological dynamics of Covid-19 from case and wastewater data in Aotearoa New Zealand

BACKGROUND

Timely and informed public health responses to infectious diseases such as COVID-19 necessitate reliable information about infection dynamics. The case ascertainment rate (CAR), the proportion of infections that are reported as cases, is typically much less than one and varies with testing practices and behaviours, making reported cases unreliable as the sole source of data. The concentration of viral RNA in wastewater samples provides an alternate measure of infection prevalence that is not affected by clinical testing, healthcare-seeking behaviour or access to care.

METHODS

We construct a state-space model with observed data of levels of SARS-CoV-2 in wastewater and reported case incidence and estimate the hidden states of the effective reproduction number, R, and CAR using sequential Monte Carlo methods.

RESULTS

We analyse data from 1 January 2022 to 31 March 2023 from Aotearoa New Zealand. Our model estimates that R peaks at 2.76 (95% CrI 2.20, 3.83) around 18 February 2022 and the CAR peaks around 12 March 2022. We calculate that New Zealand's second Omicron wave in July 2022 is similar in size to the first, despite fewer reported cases. We estimate that the CAR in the BA.5 Omicron wave in July 2022 is approximately 50% lower than in the BA.1/BA.2 Omicron wave in March 2022.

CONCLUSIONS

Estimating R, CAR, and cumulative number of infections provides useful information for planning public health responses and understanding the state of immunity in the population. This model is a useful disease surveillance tool, improving situational awareness of infectious disease dynamics in real-time.

Analysis of the impact of COVID-19 variants and vaccination on the time-varying reproduction number: statistical methods

Introduction

The COVID-19 pandemic has profoundly impacted global health systems, requiring the monitoring of infection waves and strategies to control transmission. Estimating the time-varying reproduction number is crucial for understanding the epidemic and guiding interventions.

Methods

Probability distributions of serial interval are estimated for Pre-Delta and Delta periods. We conducted a comparative analysis of time-varying reproduction numbers, taking into account population immunity and variant differences. We incorporated the regional heterogeneity and age distribution of the population, as well as the evolving variants and vaccination rates over time. COVID-19 transmission dynamics were analyzed with variants and vaccination.

Results

The reproduction number is computed with and without considering variant-based immunity. In addition, values of reproduction number significantly differed by variants, emphasizing immunity's importance. Enhanced vaccination efforts and stringent control measures were effective in reducing the transmission of the Delta variant. Conversely, Pre-Delta variant appeared less influenced by immunity levels, due to lower vaccination rates. Furthermore, during the Pre-Delta period, there was a significant difference between the region-specific and the non-region-specific reproduction numbers, with particularly distinct pattern differences observed in Gangwon, Gyeongbuk, and Jeju in Korea.

Discussion

This research elucidates the dynamics of COVID-19 transmission concerning the dominance of the Delta variant, the efficacy of vaccinations, and the influence of immunity levels. It highlights the necessity for targeted interventions and extensive vaccination coverage. This study makes a significant contribution to the understanding of disease transmission mechanisms and informs public health strategies.

Longitudinal evolution of the HIV effective reproduction number following sequential expansion of treatment as prevention and pre-exposure prophylaxis in British Columbia, Canada: a population-level programme evaluation

BACKGROUND

Treatment as prevention and pre-exposure prophylaxis (PrEP) are key strategies in the control of HIV/AIDS. We aimed to characterise the longitudinal effects of antiretroviral therapy (ART), followed by treatment as prevention and the addition of PrEP, on the HIV effective reproduction number (Re) in British Columbia, Canada.

METHODS

This population-level programme evaluation used data from the Drug Treatment Program of the British Columbia Centre for Excellence in HIV/AIDS (Vancouver, British Columbia, Canada). We also used estimates of HIV incidence and prevalence from the Public Health Agency of Canada, data on the number of new HIV diagnoses per year from the British Columbia Centre for Disease Control, and mortality data from the British Columbia Vital Statistics Agency. Data were obtained from 1985 until 2022, depending on the database source. Outcomes were the annual HIV prevalence, HIV incidence, number of new HIV diagnoses, number of people living with HIV on ART, HIV/AIDS-related and all-cause mortality rates, the HIV incidence-to-all-cause-mortality ratio, and Re. We calculated the modified effective reproduction number (Rme) using two thresholds of viral suppression and compared these values with Re.

FINDINGS

We found a 95% decline in HIV/AIDS-related mortality and a 91% decrease in HIV incidence over the study period. The Re progressively declined from 1996 to 2022; however, from 1996 to 2017, Rme remained stable (>1) when calculated for people living with HIV with unsuppressed viraemia, suggesting that treatment as prevention reduces HIV incidence by decreasing the pool of individuals who are potentially able to transmit the virus. From 2018 to 2022, a decline in the estimated Re and Rme (<1) was observed regardless of whether we considered all people living with HIV or only those who were virologically unsuppressed. This finding suggests that PrEP decreases HIV incidence by reducing the number of susceptible individuals in the community, independently of viral suppression.

INTERPRETATION

Our results show the synergy between generalised treatment as prevention and targeted PrEP in terms of decreasing HIV incidence. These findings support the incorporation of longitudinal monitoring of Re at a programmatic level to identify opportunities for the optimisation of treatment-as-prevention and PrEP programmes.

FUNDING

British Columbia Ministry of Health, Health Canada, Public Health Agency of Canada, Vancouver Coastal Health, Vancouver General Hospital Foundation, Genome British Columbia, and the Canadian Institutes of Health Research.

The impact of quality-adjusted life years on evaluating COVID-19 mitigation strategies: lessons from age-specific vaccination roll-out and variants of concern in Belgium (2020-2022)

BACKGROUND

When formulating and evaluating COVID-19 vaccination strategies, an emphasis has been placed on preventing severe disease that overburdens healthcare systems and leads to mortality. However, more conventional outcomes such as quality-adjusted life years (QALYs) and inequality indicators are warranted as additional information for policymakers.

METHODS

We adopted a mathematical transmission model to describe the infectious disease dynamics of SARS-COV-2, including disease mortality and morbidity, and to evaluate (non)pharmaceutical interventions. Therefore, we considered temporal immunity levels, together with the distinct transmissibility of variants of concern (VOCs) and their corresponding vaccine effectiveness. We included both general and age-specific characteristics related to SARS-CoV-2 vaccination. Our scenario study is informed by data from Belgium, focusing on the period from August 2021 until February 2022, when vaccination for children aged 5-11 years was initially not yet licensed and first booster doses were administered to adults. More specifically, we investigated the potential impact of an earlier vaccination programme for children and increased or reduced historical adult booster dose uptake.

RESULTS

Through simulations, we demonstrate that increasing vaccine uptake in children aged 5-11 years in August-September 2021 could have led to reduced disease incidence and ICU occupancy, which was an essential indicator for implementing non-pharmaceutical interventions and maintaining healthcare system functionality. However, an enhanced booster dose regimen for adults from November 2021 onward could have resulted in more substantial cumulative QALY gains, particularly through the prevention of elevated levels of infection and disease incidence associated with the emergence of Omicron VOC. In both scenarios, the need for non-pharmaceutical interventions could have decreased, potentially boosting economic activity and mental well-being.

CONCLUSIONS

When calculating the impact of measures to mitigate disease spread in terms of life years lost due to COVID-19 mortality, we highlight the impact of COVID-19 on the health-related quality of life of survivors. Our study underscores that disease-related morbidity could constitute a significant part of the overall health burden. Our quantitative findings depend on the specific setup of the interventions under review, which is open to debate or should be contextualised within future situations.

How the Timing of Annual COVID-19 Vaccination of Nursing Home Residents and Staff Affects Its Value

OBJECTIVES

To evaluate the epidemiologic, clinical, and economic value of an annual nursing home (NH) COVID-19 vaccine campaign and the impact of when vaccination starts.

DESIGN

Agent-based model representing a typical NH.

SETTING AND PARTICIPANTS

NH residents and staff.

METHODS

We used the model representing an NH with 100 residents, its staff, their interactions, COVID-19 spread, and its health and economic outcomes to evaluate the epidemiologic, clinical, and economic value of varying schedules of annual COVID-19 vaccine campaigns.

RESULTS

Across a range of scenarios with a 60% vaccine efficacy that wanes starting 4 months after protection onset, vaccination was cost saving or cost-effective when initiated in the late summer or early fall. Annual vaccination averted 102 to 105 COVID-19 cases when 30-day vaccination campaigns began between July and October (varying with vaccination start), decreasing to 97 and 85 cases when starting in November and December, respectively. Starting vaccination between July and December saved $3340 to $4363 and $64,375 to $77,548 from the Centers for Medicare & Medicaid Services and societal perspectives, respectively (varying with vaccination start). Vaccination's value did not change when varying the COVID-19 peak between December and February. The ideal vaccine campaign timing was not affected by reducing COVID-19 levels in the community, or varying transmission probability, preexisting immunity, or COVID-19 severity. However, if vaccine efficacy wanes more quickly (over 1 month), earlier vaccination in July resulted in more cases compared with vaccinating later in October.

CONCLUSIONS AND IMPLICATIONS

Annual vaccination of NH staff and residents averted the most cases when initiated in the late summer through early fall, at least 2 months before the COVID-19 winter peak but remained cost saving or cost-effective when it starts in the same month as the peak. This supports tethering COVID vaccination to seasonal influenza campaigns (typically in September-October) for providing protection against SARS-CoV-2 winter surges in NHs.

Variability in the serial interval of COVID-19 in South Korea: a comprehensive analysis of age and regional influences

Introduction

Quantifying the transmissibility over time, particularly by region and age, using parameters such as serial interval and time-varying reproduction number, helps in formulating targeted interventions. Moreover, considering the impact of geographical factors on transmission provides valuable insights into the effectiveness of control measures.

Methods

Drawing on a comprehensive dataset of COVID-19 cases in South Korea, we analyzed transmission dynamics with a focus on age and regional variations. The dataset, compiled through the efforts of dedicated epidemiologists, includes information on symptom onset dates, enabling detailed investigations. The pandemic was divided into distinct phases, aligning with changes in policies, emergence of variants, and vaccination efforts. We analyzed various interventions such as social distancing, vaccination rates, school closures, and population density. Key parameters like serial interval, heatmaps, and time-varying reproduction numbers were used to quantify age and region-specific transmission trends.

Results

Analysis of transmission pairs within age groups highlighted the significant impact of school closure policies on the spread among individuals aged 0-19. This analysis also shed light on transmission dynamics within familial and educational settings. Changes in confirmed cases over time revealed a decrease in spread among individuals aged 65 and older, attributed to higher vaccination rates. Conversely, densely populated metropolitan areas experienced an increase in confirmed cases. Examination of time-varying reproduction numbers by region uncovered heterogeneity in transmission patterns, with regions implementing strict social distancing measures showing both increased confirmed cases and delayed spread, indicating the effectiveness of these policies.

Discussion

Our findings underscore the importance of evaluating and tailoring epidemic control policies based on key COVID-19 parameters. The analysis of social distancing measures, school closures, and vaccine impact provides valuable insights into controlling transmission. By quantifying the impact of these interventions on different age groups and regions, we contribute to the ongoing efforts to combat the COVID-19 pandemic effectively.

Near-term forecasting of Covid-19 cases and hospitalisations in Aotearoa New Zealand

Near-term forecasting of infectious disease incidence and consequent demand for acute healthcare services can support capacity planning and public health responses. Despite well-developed scenario modelling to support the Covid-19 response, Aotearoa New Zealand lacks advanced infectious disease forecasting capacity. We develop a model using Aotearoa New Zealand's unique Covid-19 data streams to predict reported Covid-19 cases, hospital admissions and hospital occupancy. The method combines a semi-mechanistic model for disease transmission to predict cases with Gaussian process regression models to predict the fraction of reported cases that will require hospital treatment. We evaluate forecast performance against out-of-sample data over the period from 2 October 2022 to 23 July 2023. Our results show that forecast performance is reasonably good over a 1-3 week time horizon, although generally deteriorates as the time horizon is lengthened. The model has been operationalised to provide weekly national and regional forecasts in real-time. This study is an important step towards development of more sophisticated situational awareness and infectious disease forecasting tools in Aotearoa New Zealand.

Pediatric humoral immune responses and infection risk after severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection and two-dose vaccination during SARS-CoV-2 omicron BA.5 and BN.1 variants predominance in South Korea

Background

Humoral immune responses and infection risk after severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection and coronavirus disease 2019 (COVID-19) vaccination during the Omicron BA.5 and BN.1 variants predominant period remains unexplored in pediatric population.

Methods

We examined anti-spike (anti-S) immunoglobulin G (IgG) responses in a total of 986 children aged 4-18 years who visited outpatient clinics between June 2022 and January 2023, with a history of SARS-CoV-2 infection alone, completed two doses of COVID-19 vaccination alone, vaccine-breakthrough infection (i.e., infection after the single dose of vaccination), and no antigenic exposure. Furthermore, to determine SARS-CoV-2 infection risk, the incidence of newly developed SARS-CoV-2 infection was investigated up to March 2023.

Results

The anti-S IgG levels in the 'vaccine-breakthrough infection' group exceeded those in the 'infection alone' and 'vaccination alone' groups (both P <0.01). Furthermore, the 'vaccination alone' group experienced more rapid anti-S IgG waning than the 'infection alone' and 'vaccine-breakthrough infection' groups (both P <0.01). We could not identify newly developed SARS-CoV-2 infection in the 'vaccine-breakthrough infection' group.

Conclusion

Our findings suggest that hybrid immunity, acquired from SARS-CoV-2 infection and COVID-19 vaccination, was a potentially higher and longer-lasting humoral immune response and protected against SARS-CoV-2 infection in pediatric population during Omicron BA.5 and BN.1 variants predominant.

Depressive symptoms among people under COVID-19 quarantine or self-isolation in Korea: a propensity score matching analysis

Introduction

This study aims to determine the effect of COVID-19-related hospital isolation or self-isolation on depression using the propensity score matching method.

Methods

Data on 217,734 participants were divided into groups based on whether or not they underwent quarantine for their COVID-19 diagnosis. COVID-19-related anxiety, depressive symptoms, subjective health status, and perceived stress were evaluated.

Results

Based on the calculated propensity score, we matched the quarantined group and non-quarantined group using 1:2 matching with nearest neighbor matching and a caliper width of 0.1. Within the quarantined group, 16.4% of participants experienced significant depressive symptoms, which was significantly higher than that of the non-quarantined group. However, there was no significant difference between the two groups in COVID-19-related anxiety, self-rated health status, and perceived stress. In our multiple logistic regression analysis with related variables corrected, the quarantined group was 1.298 times more likely to have depressive symptoms than the non-quarantined group (95% CI = 1.030-1.634).

Conclusion

Our study confirmed that COVID-19 quarantine is associated with depressive symptoms. These results indicate that healthcare policymakers and healthcare professionals must consider the negative mental and physical effects of quarantine when determining quarantine measures during an infectious disease disaster such as the COVID-19 pandemic.

COVID-19 vaccination strategies in settings with limited rollout capacity: a mathematical modelling case study in Sierra Leone

BACKGROUND

COVID-19 vaccine coverage in low- and middle-income countries continues to be challenging. As supplies increase, coverage is increasingly becoming determined by rollout capacity.

METHODS

We developed a deterministic compartmental model of COVID-19 transmission to explore how age-, risk-, and dose-specific vaccine prioritisation strategies can minimise severe outcomes of COVID-19 in Sierra Leone.

RESULTS

Prioritising booster doses to older adults and adults with comorbidities could reduce the incidence of severe disease by 23% and deaths by 34% compared to the use of these doses as primary doses for all adults. Providing a booster dose to pregnant women who present to antenatal care could prevent 38% of neonatal deaths associated with COVID-19 infection during pregnancy. The vaccination of children is not justified unless there is sufficient supply to not affect doses delivered to adults.

CONCLUSIONS

Our paper supports current WHO SAGE vaccine prioritisation guidelines (released January 2022). Individuals who are at the highest risk of developing severe outcomes should be prioritised, and opportunistic vaccination strategies considered in settings with limited rollout capacity.

Epidemiological features of SARS-CoV-2 Omicron infection under new control strategy: a cross-sectional study of the outbreak since December 2022 in Sichuan, China

BACKGROUND

A major shift in the "dynamic zero-COVID" policy was announced by China's National Health Commission on December 7, 2022, and the subsequent immediate large-scale outbreak of SARS-CoV-2 infections in the entire country has caused worldwide concern. This observational cross-sectional study aimed to describe the epidemiological characteristics of this outbreak in Sichuan, China.

METHODS

All data were self-reported online by volunteers. We described the epidemic by characterizing the infection, symptoms, clinical duration, severity, spatiotemporal clustering, and dynamic features of the disease. Prevalence ratio (PR), Odds ratios (ORs) and adjusted ORs were calculated to analyze the associations between risk factors and infection and the associations of risk factors with clinical severity using log-binomial and multivariable logistic regression models; 95% confidence intervals (CIs) and Wald test results were reported. The prevalence rates and clinical severity among different subgroups were compared using the Chi-square and trend Chi-square tests.

RESULTS

Between January 6 and 12, 2023, 138,073 volunteers were enrolled in this survey, and 102,645 were infected with COVID-19, holding a prevalence rate of 74.34%; the proportion of asymptomatic infections was 1.58%. Log-binomial regression revealed that the risk of infection increased among those living in urban areas. Multivariable logistic regression analysis showed that female sex, chronic diseases, older age and the fewer doses of vaccine received were associated with an increased risk of severe clinical outcomes after infection. We estimated the mean reproduction number during this pandemic was 1.83. The highest time-dependent reproduction number was 4.15; this number decreased below 1 after 11 days from December 7, 2022. Temporal trends revealed a single peak curve with a plateau pattern of incidence during the outbreak, whereas spatiotemporal clustering analysis showed that the onset in 21 cities in the Sichuan province had four-wave peaks.

CONCLUSIONS

The peak of the first wave of Omicron infection in Sichuan Province had passed and could be considered a snapshot of China under the new control strategy. There were significant increases in the risk of severe clinical outcomes after infection among females, with chronic diseases, and the elderly. The vaccines have been effective in reducing poor clinical outcomes.

Monitoring the reproductive number of COVID-19 in France: Comparative estimates from three datasets

BACKGROUND

The effective reproduction number (Rt) quantifies the average number of secondary cases caused by one person with an infectious disease. Near-real-time monitoring of Rt during an outbreak is a major indicator used to monitor changes in disease transmission and assess the effectiveness of interventions. The estimation of Rt usually requires the identification of infected cases in the population, which can prove challenging with the available data, especially when asymptomatic people or with mild symptoms are not usually screened. The purpose of this study was to perform sensitivity analysis of Rt estimates for COVID-19 surveillance in France based on three data sources with different sensitivities and specificities for identifying infected cases.

METHODS

We applied a statistical method developed by Cori et al. to estimate Rt using (1) confirmed cases identified from positive virological tests in the population, (2) suspected cases recorded by a national network of emergency departments, and (3) COVID-19 hospital admissions recorded by a national administrative system to manage hospital organization.

RESULTS

Rt estimates in France from May 27, 2020, to August 12, 2022, showed similar temporal trends regardless of the dataset. Estimates based on the daily number of confirmed cases provided an earlier signal than the two other sources, with an average lag of 3 and 6 days for estimates based on emergency department visits and hospital admissions, respectively.

CONCLUSION

The COVID-19 experience confirmed that monitoring temporal changes in Rt was a key indicator to help the public health authorities control the outbreak in real time. However, gaining access to data on all infected people in the population in order to estimate Rt is not straightforward in practice. As this analysis has shown, the opportunity to use more readily available data to estimate Rt trends, provided that it is highly correlated with the spread of infection, provides a practical solution for monitoring the COVID-19 pandemic and indeed any other epidemic.

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 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 (I2 > 80%; I2 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.

Marginal effects of public health measures and COVID-19 disease burden in China: A large-scale modelling study

China had conducted some of the most stringent public health measures to control the spread of successive SARS-CoV-2 variants. However, the effectiveness of these measures and their impacts on the associated disease burden have rarely been quantitatively assessed at the national level. To address this gap, we developed a stochastic age-stratified metapopulation model that incorporates testing, contact tracing and isolation, based on 419 million travel movements among 366 Chinese cities. The study period for this model began from September 2022. The COVID-19 disease burden was evaluated, considering 8 types of underlying health conditions in the Chinese population. We identified the marginal effects between the testing speed and reduction in the epidemic duration. The findings suggest that assuming a vaccine coverage of 89%, the Omicron-like wave could be suppressed by 3-day interval population-level testing (PLT), while it would become endemic with 4-day interval PLT, and without testing, it would result in an epidemic. PLT conducted every 3 days would not only eliminate infections but also keep hospital bed occupancy at less than 29.46% (95% CI, 22.73-38.68%) of capacity for respiratory illness and ICU bed occupancy at less than 58.94% (95% CI, 45.70-76.90%) during an outbreak. Furthermore, the underlying health conditions would lead to an extra 2.35 (95% CI, 1.89-2.92) million hospital admissions and 0.16 (95% CI, 0.13-0.2) million ICU admissions. Our study provides insights into health preparedness to balance the disease burden and sustainability for a country with a population of billions.

Rapid review and meta-analysis of serial intervals for SARS-CoV-2 Delta and Omicron variants

BACKGROUND

The serial interval is the period of time between symptom onset in the primary case and symptom onset in the secondary case. Understanding the serial interval is important for determining transmission dynamics of infectious diseases like COVID-19, including the reproduction number and secondary attack rates, which could influence control measures. Early meta-analyses of COVID-19 reported serial intervals of 5.2 days (95% CI: 4.9-5.5) for the original wild-type variant and 5.2 days (95% CI: 4.87-5.47) for Alpha variant. The serial interval has been shown to decrease over the course of an epidemic for other respiratory diseases, which may be due to accumulating viral mutations and implementation of more effective nonpharmaceutical interventions. We therefore aggregated the literature to estimate serial intervals for Delta and Omicron variants.

METHODS

This study followed Preferred Reporting Items for Systematic Reviews and Meta-analyses guidelines. A systematic literature search was conducted of PubMed, Scopus, Cochrane Library, ScienceDirect, and preprint server medRxiv for articles published from April 4, 2021, through May 23, 2023. Search terms were: ("serial interval" or "generation time"), ("Omicron" or "Delta"), and ("SARS-CoV-2" or "COVID-19"). Meta-analyses were done for Delta and Omicron variants using a restricted maximum-likelihood estimator model with a random effect for each study. Pooled average estimates and 95% confidence intervals (95% CI) are reported.

RESULTS

There were 46,648 primary/secondary case pairs included for the meta-analysis of Delta and 18,324 for Omicron. Mean serial interval for included studies ranged from 2.3-5.8 days for Delta and 2.1-4.8 days for Omicron. The pooled mean serial interval for Delta was 3.9 days (95% CI: 3.4-4.3) (20 studies) and Omicron was 3.2 days (95% CI: 2.9-3.5) (20 studies). Mean estimated serial interval for BA.1 was 3.3 days (95% CI: 2.8-3.7) (11 studies), BA.2 was 2.9 days (95% CI: 2.7-3.1) (six studies), and BA.5 was 2.3 days (95% CI: 1.6-3.1) (three studies).

CONCLUSIONS

Serial interval estimates for Delta and Omicron were shorter than ancestral SARS-CoV-2 variants. More recent Omicron subvariants had even shorter serial intervals suggesting serial intervals may be shortening over time. This suggests more rapid transmission from one generation of cases to the next, consistent with the observed faster growth dynamic of these variants compared to their ancestors. Additional changes to the serial interval may occur as SARS-CoV-2 continues to circulate and evolve. Changes to population immunity (due to infection and/or vaccination) may further modify it.

Optimal strategies for coordinating infection control and socio-economic activities

It becomes challenging to identify feasible control strategies for simultaneously relaxing the countermeasures and containing the Covid-19 pandemic, given China's huge population size, high susceptibility, persist vaccination waning, and relatively weak strength of health systems. We propose a novel mathematical model with waning of immunity and solve the optimal control problem, in order to provide an insight on how much detecting and social distancing are required to coordinate socio-economic activities and epidemic control. We obtain the optimal intensity of countermeasures, i.e., the dynamic nucleic acid screening and social distancing, under which the health system is functioning normally and people can engage in a certain level of socio-economic activities. We find that it is the isolation capacity or the restriction of the case fatality rate (CFR) rather than the hospital capacity that mainly determines the optimal strategies. And the solved optimal controls under quarterly CFR restrictions exhibit oscillations. It is worth noticing that, if without considering booster or very low booster rate, the optimal strategy is a "on-off" mode, alternating between lock down and opening with certain social distancing, which reflects the importance and necessity of China's static management on a certain area during Covid-19 outbreak. The findings suggest some feasible paths to smoothly transit from the Covid-19 pandemic to an endemic phase.

MAM: Flexible Monte-Carlo Agent based Model for Modelling COVID-19 Spread

In the three years since SARS-CoV-2 was first detected in China, hundreds of millions of people have been infected and millions have died. Along with the immediate need for treatment solutions, the COVID-19 epidemic has reinforced the need for mathematical models that can predict the spread of the pandemic in an ever-changing environment. The susceptible-infectious-removed (SIR) model has been widely used to model COVID-19 transmission, however, with limited success. Here, we present a novel, dynamic Monte-Carlo Agent-based Model (MAM), which is based on the basic principles of statistical physics. Using public aggregative data from Israel on three major outbreaks, we compare predictions made by SIR and MAM, and show that MAM outperforms SIR in all aspects. Furthermore, MAM is a flexible model and allows to accurately examine the effects of vaccinations in different subgroups, and the effects of the introduction of new variants.

Serial Intervals and Incubation Periods of SARS-CoV-2 Omicron and Delta Variants, Singapore

We compared serial intervals and incubation periods for SARS-CoV-2 Omicron BA.1 and BA.2 subvariants and Delta variants in Singapore. Median incubation period was 3 days for BA.1 versus 4 days for Delta. Serial interval was 2 days for BA.1 and 3 days for BA.2 but 4 days for Delta.

Estimation of the Effectiveness of a Tighter, Reinforced Quarantine for the Coronavirus Disease 2019 (COVID-19) Outbreak: Analysis of the Third Wave in South Korea

It has been claimed that a tighter, reinforced quarantine strategy was advocated to reduce the transmission of coronavirus disease 2019 (COVID-19) during major outbreaks; however, there have been no prior quantitative studies examining the effectiveness and duration of such a reinforced quarantine. Consequently, the purpose of this research was to determine the impact of a “tighter, reinforced” quarantine during the third COVID-19 breakout wave in South Korea, which occurred between late 2020 and early 2021. The efficacy of the quarantine was determined by comparing the number of newly diagnosed COVID-19 patients between the “prediction model” and “actual observed data.” Two prediction models were developed using the autoregressive integrated moving average (ARIMA; 1, 0, 0) model. The effect of a “tighter, reinforced” quarantine, which would show as an immediate drop in the number of new cases, predicted its efficacy by lowering the number of new cases by 20,400. In addition, the efficacy of the quarantine lasted up to more than three months. The findings of our investigation confirmed the beneficial influence of “tighter, controlled” quarantine laws during a widespread COVID-19 epidemic. During an epidemic, when the population has not yet developed immunity to respiratory viral diseases, our study may be evidence for implementing stricter quarantine restrictions in order to reduce the number of new cases.

Performance Evaluation of RapiSure (EDGC) COVID-19 S1 RBD IgG/Neutralizing Ab Test for the Rapid Detection of SARS-CoV-2 Antibodies

The accurate detection of anti-neutralizing SARS-CoV-2 antibodies can aid in the understanding of the development of protective immunity against COVID-19. This study evaluated the diagnostic performance of the RapiSure (EDGC) COVID-19 S1 RBD IgG/Neutralizing Ab Test. Using the 90% plaque reduction neutralization test (PRNT₉₀) as a reference, 200 serum samples collected from 78 COVID-19-positive and 122 COVID-19-negative patients were divided into 76 PRNT₉₀-positive and 124 PRNT₉₀-negative groups. The ability of the RapiSure test to detect antibodies was compared to that of the STANDARD Q COVID-19 IgM/IgG Plus test and that of PRNT₉₀. The positive, negative, and overall percent agreement between the RapiSure and STANDARD Q test was 95.7%, 89.3%, and 91.5%, respectively, with a Cohen's kappa of 0.82. The RapiSure neutralizing antibody test results revealed a sensitivity of 93.4% and a specificity of 100% compared to the PRNT results, with an overall percent agreement of 97.5% and Cohen's kappa of 0.95. The diagnostic performance of the RapiSure test was in good agreement with the STANDARD Q COVID-19 IgM/IgG Plus test and comparable to that of the PRNT. The RapiSure S1 RBD IgG/Neutralizing Ab Test was found to be convenient and reliable and, thus, can provide valuable information for rapid clinical decisions during the COVID-19 pandemic.

A Small Surge in Incidence of SARS-CoV-2 Omicron Variant in the "Dynamic Zero" Period

To describe the epidemiological characteristics and transmission dynamics of SARS-CoV-2 Omicron variant during "Dynamic Zero" period, we analyzed data on the 108 laboratory-confirmed SARS-CoV-2 cases during 14 to 30 May 2022 in Beichen district, Tianjin, China. We collected information on demographic characteristics, exposure history, and illness timelines of the 108 cases. We described characteristics of the patients and estimated the key epidemiological parameters, including serial interval and the time-dependent reproduction number of the Omicron variant, Rt. Among the 108 laboratory-confirmed patients, the median age was 38 years old, and 50.9% were females. Obvious symptoms were observed among 67.6% (73/108) of all cases, and major clinical manifestations included fever, sore throat, and cough, which occurred in 31.5%, 26.9%, and 19.4% of the 108 cases, respectively. The mean and standard deviation of the SI were estimated as 2.89 and 0.95 days, the Rt varied from 1.24 to 0.27 for a 7-day timelapse. The low reproduction number and the Omicron outbreak being suppressed within a short time marked the effectiveness of the implemented public health measures, such as nucleic acid screening, social distancing, masking, vaccination, medical treatment of patients, and isolation of close contacts. These measures play an important role in fulfilling the goal of controlling the spread of the disease.

The Role of Surveillance Inspections in Reducing False-Positives of SARS-CoV-2 Omicron Variants during the COVID-19 Epidemic

Objective

This study aims to assess the effectiveness of surveillance inspections conducted by the provincial health committee in Quanzhou city during a COVID-19 outbreak in reducing false-positive results in SARS-CoV-2 RT-PCR assays.

Method

The team conducted on-site inspections of laboratories that participated in mass screening, recording any violations of rules.

Results

The positive cases in five rounds of mass screening were 23, 173, and 4 in Licheng District, Fengze District, and Luojang District, respectively. The false-positive rates in the five rounds of mass screening were 0.0099%, 0.0063%, 0.0018%, 0.0006%, and 0%, respectively. The study also recorded that the number of violations in the seven selected laboratories was 36, 68, 69, 42, 60, 54 and 47. The corresponding false-positive rates were 0.0012%, 0.0060%, 0.0082%, 0.0032%, 0.0060%, 0.0027%, and 0.0021%, respectively. The study found a positive correlation between false-positive rates and the number of violations (r = 0.905, P=0.005), and an inverse correlation between false-positive rates and the frequency of surveillance inspections (r = -0.950, P < 0.001).

Conclusion

Daily surveillance inspection in laboratories can remind laboratories to strictly comply with standard procedures, focus on laboratory quality control, and reduce the occurrence of false-positive cases in SARS-CoV-2 nucleic acid tests to some extent. This study recommends that government decision-making departments establish policies and arrange experts to conduct daily surveillance inspections to improve laboratory quality control.

Mathematical assessment of the role of waning and boosting immunity against the BA.1 Omicron variant in the United States

Three safe and effective vaccines against SARS-CoV-2 have played a major role in combating COVID-19 in the United States. However, the effectiveness of these vaccines and vaccination programs has been challenged by the emergence of new SARS-CoV-2 variants of concern. A new mathematical model is formulated to assess the impact of waning and boosting of immunity against the Omicron variant in the United States. To account for gradual waning of vaccine-derived immunity, we considered three vaccination classes that represent high, moderate and low levels of immunity. We showed that the disease-free equilibrium of the model is globally-asymptotically, for two special cases, if the associated reproduction number is less than unity. Simulations of the model showed that vaccine-derived herd immunity can be achieved in the United States via a vaccination-boosting strategy which entails fully vaccinating at least 59% of the susceptible populace followed by the boosting of about 72% of the fully-vaccinated individuals whose vaccine-derived immunity has waned to moderate or low level. In the absence of boosting, waning of immunity only causes a marginal increase in the average number of new cases at the peak of the pandemic, while boosting at baseline could result in a dramatic reduction in the average number of new daily cases at the peak. Specifically, for the fast immunity waning scenario (where both vaccine-derived and natural immunity are assumed to wane within three months), boosting vaccine-derived immunity at baseline reduces the average number of daily cases at the peak by about 90% (in comparison to the corresponding scenario without boosting of the vaccine-derived immunity), whereas boosting of natural immunity (at baseline) only reduced the corresponding peak daily cases (in comparison to the corresponding scenario without boosting of natural immunity) by approximately 62%. Furthermore, boosting of vaccine-derived immunity is more beneficial (in reducing the burden of the pandemic) than boosting of natural immunity. Finally, boosting vaccine-derived immunity increased the prospects of altering the trajectory of COVID-19 from persistence to possible elimination.

Differences in the superspreading potentials of COVID-19 across contact settings

BACKGROUND

Superspreading events (SSEs) played a critical role in fueling the COVID-19 outbreaks. Although it is well-known that COVID-19 epidemics exhibited substantial superspreading potential, little is known about the risk of observing SSEs in different contact settings. In this study, we aimed to assess the potential of superspreading in different contact settings in Japan.

METHOD

Transmission cluster data from Japan was collected between January and July 2020. Infector-infectee transmission pairs were constructed based on the contact tracing history. We fitted the data to negative binomial models to estimate the effective reproduction number (R) and dispersion parameter (k). Other epidemiological issues relating to the superspreading potential were also calculated.

RESULTS

The overall estimated R and k are 0.561 (95% CrI: 0.496, 0.640) and 0.221 (95% CrI: 0.186, 0.262), respectively. The transmission in community, healthcare facilities and school manifest relatively higher superspreading potentials, compared to other contact settings. We inferred that 13.14% (95% CrI: 11.55%, 14.87%) of the most infectious cases generated 80% of the total transmission events. The probabilities of observing superspreading events for entire population and community, household, health care facilities, school, workplace contact settings are 1.75% (95% CrI: 1.57%, 1.99%), 0.49% (95% CrI: 0.22%, 1.18%), 0.07% (95% CrI: 0.06%, 0.08%), 0.67% (95% CrI: 0.31%, 1.21%), 0.33% (95% CrI: 0.13%, 0.94%), 0.32% (95% CrI: 0.21%, 0.60%), respectively.

CONCLUSION

The different potentials of superspreading in contact settings highlighted the need to continuously monitoring the transmissibility accompanied with the dispersion parameter, to timely identify high risk settings favoring the occurrence of SSEs.

Modelling the dynamics of infection, waning of immunity and re-infection with the Omicron variant of SARS-CoV-2 in Aotearoa New Zealand

Aotearoa New Zealand experienced a wave of the Omicron variant of SARS-CoV-2 in 2022 with around 200 confirmed cases per 1000 people between January and May. Waning of infection-derived immunity means people become increasingly susceptible to re-infection with SARS-CoV-2 over time. We investigated a model that included waning of vaccine-derived and infection-derived immunity under scenarios representing different levels of behavioural change relative to the first Omicron wave. Because the durability of infection-derived immunity is a key uncertainty in epidemiological models, we investigated outcomes under different assumptions about the speed of waning. The model was used to provide scenarios to the New Zealand Government, helping to inform policy response and healthcare system preparedness ahead of the winter respiratory illness season. In all scenarios investigated, a second Omicron wave was projected to occur in the second half of 2022. The timing of the peak depended primarily on the speed of waning and was typically between August and November. The peak number of daily infections in the second Omicron wave was smaller than in the first Omicron wave. Peak hospital occupancy was also generally lower than in the first wave but was sensitive to the age distribution of infections. A scenario with increased contact rates in older groups had higher peak hospital occupancy than the first wave. Scenarios with relatively high transmission, whether a result of relaxation of control measures or voluntary behaviour change, did not necessarily lead to higher peaks. However, they generally resulted in more sustained healthcare demand (>250 hospital beds throughout the winter period). The estimated health burden of Covid-19 in the medium term is sensitive to the strength and durability of infection-derived and hybrid immunity against reinfection and severe illness, which are uncertain.

Seroprevalence of SARS-CoV-2 antibodies among children and adolescents recruited in a malariometric survey in north-eastern Tanzania July 2021

Background

African countries stand out globally as the region seemingly least affected by the COVID-19 pandemic, caused by the virus SARS-CoV-2. Besides a younger population and potential pre-existing immunity to a SARS-CoV-2-like virus, it has been hypothesized that co-infection or recent history of Plasmodium falciparum malaria may be protective of COVID-19 severity and mortality. The number of COVID-19 cases and deaths, however, may be vastly undercounted. Very little is known about the extent to which the Tanzanian population has been exposed to SARS-CoV-2. Here, we investigated the seroprevalence of IgG to SARS-CoV-2 spike protein in two Tanzanian rural communities 1½ years into the pandemic and the association of coinciding malaria infection and exposure.

Methods

During a malariometric survey in July 2021 in two villages in north-eastern Tanzania, blood samples were taken from 501 participants (0–19 years old). Malaria was detected by mRDT and microscopy. Levels of IgG against the spike protein of SARS-CoV-2 were measured by ELISA as well as IgG against five different antigens of P. falciparum; CIDRα1.1, CIDRα1.4 and CIDRα1.5 of PfEMP1 and GLURP and MSP3.

Results

The seroprevalence of SARS-CoV-2 IgG was 39.7% (106/267) in Kwamasimba and 32.5% (76/234) in Mkokola. In both villages the odds of being seropositive increased significantly with age (AOR = 1.12, 95% CI 1.07–1.17, p < 0.001). P. falciparum malaria prevalence by blood smear microscopy was 7.9% in Kwamasimba and 2.1% in Mkokola. 81.3% and 70.5% in Kwamasimba and Mkokola, respectively, showed recognition of minimum one malaria antigen. Residing in Kwamasimba was associated with a broader recognition (AOR = 1.91, 95% CI 1.34–2.71, p < 0.001). The recognition of malaria antigens increased significantly with age in both villages (AOR = 1.12; 95% CI 1.08–1.16, p < 0.001). Being SARS-CoV-2 seropositive did not associate with the breadth of malaria antigen recognition when adjusting for age (AOR = 0.99; 95% CI 0.83–1.18; p = 0.91).

Conclusion

More than a third of the children and adolescents in two rural communities in Tanzania had antibodies to SARS-CoV-2. In particular, the adolescents were seropositive but being seropositive did not associate with the status of coinciding malaria infections or previous exposure. In Tanzania, natural immunity may have developed fast, potentially protecting a substantial part of the population from later variants.

Delineating the spread and prevalence of SARS-CoV-2 Omicron sub-lineages (BA.1- BA.5) and Deltacron using wastewater in the Western Cape, South Africa

This study was one of the first to detect Omicron sublineages BA.4 and BA.5 in wastewater from South Africa. Spearman rank correlation analysis confirmed a strong positive correlation between severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) viral RNA in wastewater samples and clinical cases (r = 0.7749, P < .0001). SARS-CoV-2 viral load detected in wastewater, resulting from the Delta-driven third wave, was significantly higher than during the Omicron-driven fourth wave. Whole-genome sequencing confirmed presence of Omicron lineage defining mutations in wastewater with the first occurrence reported 23 November 2021 (BA.1 predominant). The variant spread rapidly, with prevalence of Omicron-positive wastewater samples rising to >80% by 10 January 2022 with BA.2 as the predominant sublineage by 10 March 2022, whilst on 18 April 2022 BA.4 and BA.5 were detected in selected wastewater sites. These findings demonstrate the value of wastewater-based epidemiology to monitor the spatiotemporal spread and potential origin of new Omicron sublineages.

Increasing contributions of airborne route in SARS-CoV-2 omicron variant transmission compared with the ancestral strain

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) Omicron variant has become the dominant lineage worldwide. Experimental studies have shown that SARS-CoV-2 Omicron variant is more stable on various environmental surfaces than the ancestral strains of SARS-CoV-2. However, the influences on the role of the contact route in SARS-CoV-2 transmission are still unknown. In this study, we built a Markov chain model to simulate the transmission of the Omicron and ancestral strains of SARS-CoV-2 within a household over a 1-day period from multiple pathways; that is, airborne, droplet, and contact routes. We assumed that there were two adults and one child in the household, and that one of the adults was infected with SARS-CoV-2. We assumed two scenarios. (1) Asymptomatic/presymptomatic infection, and (2) symptomatic infection. During asymptomatic/presymptomatic infection, the contact route contributing the most (37%-45%), followed by the airborne (34%-38%) and droplet routes (21%-28%). During symptomatic infection, the droplet route was the dominant pathway (48%-71%), followed by the contact route (25%-42%), with the airborne route playing a negligible role (<10%). Compared to the ancestral strain, although the contribution of the contact route increased in Omicron variant transmission, the increase was slight, from 25%-41% to 30%-45%. With the growing concern about the increase in the proportion of asymptomatic/presymptomatic infection in Omicron strain transmissions, the airborne route, rather than the fomite route, should be of focus. Our findings suggest the importance of ventilation in the SARS-CoV-2 Omicron variant prevention in building environment.

Association Between the Relaxation of Public Health and Social Measures and Transmission of the SARS-CoV-2 Omicron Variant in South Korea

This cohort study investigates the association between relaxation of public health and social measures and daily cases of SARS-CoV-2 Omicron variant infection in South Korea.

Estimating the incubation period of SARS-CoV-2 Omicron BA.1 variant in comparison with that during the Delta variant dominance in South Korea

Based on exposure history and symptom onset of 22 Omicron BA.1 cases in South Korea from November to December 2021, we estimated mean incubation period of 3.5 days (95% CI: 2.5, 3.8), and then compared to that of 6.5 days (95% CI: 5.3, 7.7) for 64 cases during Delta variants' dominance in June 2021. For Omicron BA.1 variants, we found that 95% of symptomatic cases developed clinical conditions within 6.0 days (95% CI: 4.3, 6.6) after exposure. Thus, a shorter quarantine period may be considered based on symptoms, or similarly laboratory testing, when Omicron BA.1 variants are circulating.

Incubation period of wild type of SARS-CoV-2 infections by age, gender, and epidemic periods

Background

The incubation period of the coronavirus disease 2019 (COVID-19) is estimated to vary by demographic factors and the COVID-19 epidemic periods.

Objective

This study examined the incubation period of the wild type of SARS-CoV-2 infections by the different age groups, gender, and epidemic periods in South Korea.

Methods

We collected COVID-19 patient data from the Korean public health authorities and estimated the incubation period by fitting three different distributions, including log-normal, gamma, and Weibull distributions, after stratification by gender and age groups. To identify any temporal impact on the incubation period, we divided the study period into two different epidemic periods (Period-1: 19 January−19 April 2020 and Period-2: 20 April−16 October 2020), and assessed for any differences.

Results

We identified the log-normal as the best-fit model. The estimated median incubation period was 4.6 (95% CI: 3.9–4.9) days, and the 95th percentile was 11.7 (95% CI: 10.2–12.2) days. We found that the incubation period did not differ significantly between males and females (p = 0.42), age groups (p = 0.60), and the two different epidemic periods (p = 0.77).

Conclusions

The incubation period of wild type of SARS-CoV-2 infection during the COVID-19 pandemic 2020, in South Korea, does not likely differ by age group, gender and epidemic period.

Omicron - The new SARS-CoV-2 challenge?

SARS-CoV-2 virus has infected nearly 300 M people worldwide and has been associated with over 6 M deaths by March 2022. Since the virus emergence in December 2019 in Wuhan, several new mutations have been described. The World Health Organization has developed a working name for these emerging variants according to their impact on the worldwide population. In this context a high alert has been paid to variants of concern (VOC) due to their high infectiousness and transmissibility patterns. The most recent VOC, Omicron (B.1.1.529), has become dominant in the shortest time ever and has placed Europe under an overwhelming and unprecedented number of new cases. This variant has numerous mutations in regions that are associated with higher transmissibility, stronger viral binding, affinity and antibody escape. Moreover, the mutations and deletions present in the spike protein suggest that the SARS-CoV-2 specific attachment inhibitors may not be the best option for Omicron therapy. Omicron is the dominant variant circulating worldwide and, at the end of February 2022, it was responsible for nearly all sequences reported to GISAID. Omicron is made up of several sublineages, where the most common are BA.1 and BA.2 (or Nextstrain clade 21K and 21L, respectively). At a global level, it is possible to say that the proportion of BA.2 has been increasing relative to BA.1 and in some countries it has been replacing it at high rates. In order to better assess the Omicron effectiveness on antibody escape, spread and infectious ability it is of the highest relevance to maintain a worldwide tight surveillance. Even though this variant has been associated with a lower death rate, it is important to highlight that the number of people becoming infected is concerning and that further unpredictable mutations may emerge as the number of infected people rises.

Serial Intervals for SARS-CoV-2 Omicron and Delta Variants, Belgium, November 19-December 31, 2021

We investigated the serial interval for SARS-CoV-2 Omicron BA.1 and Delta variants and observed a shorter serial interval for Omicron, suggesting faster transmission. Results indicate a relationship between empirical serial interval and vaccination status for both variants. Further assessment of the causes and extent of Omicron dominance over Delta is warranted.

Cost-effectiveness of Coronavirus Disease 2019 Vaccination in Low- and Middle-Income Countries

BACKGROUND

Despite the advent of safe and effective coronavirus disease 2019 vaccines, pervasive inequities in global vaccination persist.

METHODS

We projected health benefits and donor costs of delivering vaccines for up to 60% of the population in 91 low- and middle-income countries (LMICs). We modeled a highly contagious (Re at model start, 1.7), low-virulence (infection fatality ratio [IFR], 0.32%) "Omicron-like" variant and a similarly contagious "severe" variant (IFR, 0.59%) over 360 days, accounting for country-specific age structure and healthcare capacity. Costs included vaccination startup (US$630 million) and per-person procurement and delivery (US$12.46/person vaccinated).

RESULTS

In the Omicron-like scenario, increasing current vaccination coverage to achieve at least 15% in each of the 91 LMICs would prevent 11 million new infections and 120 000 deaths, at a cost of US$0.95 billion, for an incremental cost-effectiveness ratio (ICER) of US$670/year of life saved (YLS). Increases in vaccination coverage to 60% would additionally prevent up to 68 million infections and 160 000 deaths, with ICERs <US$8000/YLS. ICERs were <US$4000/YLS under the more severe variant scenario and generally robust to assumptions about vaccine effectiveness, uptake, and costs.

CONCLUSIONS

Funding expanded COVID-19 vaccine delivery in LMICs would save hundreds of thousands of lives, be similarly or more cost-effective than other donor-funded global aid programs, and improve health equity.

A Testing and Quarantine Algorithm for Individual International Travelers Using Published Data on WHO-Approved Vaccines and Bayes’ Theorem

Policies such as border closures and quarantines have been widely used during the COVID-19 pandemic. Policy modifications and updates, however, must be adjusted as global vaccination rates increase. We calculated the risks of individual travelers based on their expected transmission and benchmarked them against that of an unvaccinated traveler quarantined for 14 days without testing. All individuals with a negative preboarding test can be released with a negative arrival test, when both tests have a sensitivity ≥ 90% and a specificity ≥ 97%, performance characteristics that could be accomplished by rapid antigen tests. This assumption is valid for an incidence rate up to 0.1 (prior to testing) and effective reproduction number (Rt) up to 4 in the arrival country. In a sensitivity analysis scenario where the incidence rate is 0.4 and Rt is 16, a negative preboarding test and a negative arrival test, both with a sensitivity ≥ 98% and a specificity ≥ 97%, can ensure that a traveler has a lower expected transmission than an unvaccinated person who is quarantined for 14 days. In most cases, fully vaccinated travelers (with or without booster) and a negative preboarding test can be released with a negative rapid antigen test upon arrival, allowing travelers to depart the airport within 30 min.

Collateral Impact of Public Health and Social Measures on Respiratory Virus Activity during the COVID-19 Pandemic 2020–2021

Many countries have implemented public health and social measures (PHSMs) to control the spread of severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2). Although the PHSMs are targeted at SARS-CoV-2 transmission control, they directly or indirectly impact the epidemiology of different respiratory viral diseases. The purpose of this study was to investigate the collateral impact of PHSMs used during the coronavirus disease 2019 (COVID-19) pandemic on the epidemiology of other respiratory viruses, including influenza, parainfluenza, respiratory syncytial virus, rhinovirus, and adenovirus infections. We conducted a systematic review of the published literature on changes in the incidence of respiratory viral diseases and detection rates of the respiratory viruses during COVID-19 pandemic, lasting from 2020–2021, published between December 2019 and March 2022 in PubMed, Embase, and Cochrane Library databases. We identified an overall decrease of 23–94% in the incidence of respiratory viral diseases and a decrease of 0–98% in the detection of the viruses. Our study suggests that the PHSMs implemented during COVID-19 pandemic reduced the incidence of respiratory viral diseases and transmission of respiratory viruses. At the time of this study, and as governments relax PHSMs, public health authorities should prepare for a probable increase in the burden of respiratory viral diseases.

Transmission potential of the Omicron variant of SARS-CoV-2 in South Korea: From November 25, 2020 to January 8, 2022

Our study indicates sustained transmission (effective reproduction number, 1.3; serial interval, 4.2 days; regional doubling times, 3.3–11.4 days) of the severe acute respiratory syndrome coronavirus 2 Omicron (B.1.1.529) variant (N = 2351) in South Korea (25 November 2021–8 January 2022), implicating insufficient protection through vaccination and supporting nonpharmaceutical control measures.

An assessment of the potential impact of the Omicron variant of SARS-CoV-2 in Aotearoa New Zealand

New Zealand delayed the introduction of the Omicron variant of SARS-CoV-2 into the community by the continued use of strict border controls through to January 2022. This allowed time for vaccination rates to increase and the roll out of third doses of the vaccine (boosters) to begin. It also meant more data on the characteristics of Omicron became available prior to the first cases of community transmission. Here we present a mathematical model of an Omicron epidemic, incorporating the effects of the booster roll out and waning of vaccine-induced immunity, and based on estimates of vaccine effectiveness and disease severity from international data. The model considers differing levels of immunity against infection, severe illness and death, and ignores waning of infection-induced immunity. This model was used to provide an assessment of the potential impact of an Omicron wave in the New Zealand population, which helped inform government preparedness and response. At the time the modelling was carried out, the date of introduction of Omicron into the New Zealand community was unknown. We therefore simulated outbreaks with different start dates, as well as investigating different levels of booster uptake. We found that an outbreak starting on 1 February or 1 March led to a lower health burden than an outbreak starting on 1 January because of increased booster coverage, particularly in older age groups. We also found that outbreaks starting later in the year led to worse health outcomes than an outbreak starting on 1 March. This is because waning immunity in older groups started to outweigh the increased protection from higher booster coverage in younger groups. For an outbreak starting on 1 February and with high booster uptake, the number of occupied hospital beds in the model peaked between 800 and 3,300 depending on assumed transmission rates. We conclude that combining an accelerated booster programme with public health measures to flatten the curve are key to avoid overwhelming the healthcare system.

Evolution of Responses to COVID-19 and Epidemiological Characteristics in South Korea

The characteristics of COVID-19 have evolved at an accelerated rate over the last two years since the first SARS-CoV-2 case was discovered in December 2019. This evolution is due to the complex interplay among virus, humans, vaccines, and environments, which makes the elucidation of the clinical and epidemiological characteristics of COVID-19 essential to assess ongoing policy responses. In this study, we carry out an extensive retrospective analysis on infection clusters of COVID-19 in South Korea from January 2020 to September 2021 and uncover important clinical and social factors associated with age and regional patterns through the sophisticated large-scale epidemiological investigation using the data provided by the Korea Disease Control and Prevention Agency (KDCA). Epidemiological data of COVID-19 include daily confirmed cases, gender, age, city of residence, date of symptom onset, date of diagnosis, and route of infection. We divide the time span into six major periods based on the characteristics of COVID-19 according to various events such as the rise of new variants, vaccine rollout, change of social distancing levels, and other intervention measures. We explore key features of COVID-19 such as the relationship among unlinked, asymptomatic, and confirmed cases, serial intervals, infector–infectee interactions, and age/region-specific variations. Our results highlight the significant impact of temporal evolution of interventions implemented in South Korea on the characteristics of COVID-19 transmission, in particular, that of a high level of vaccination coverage in the senior-aged group on the dramatic reduction of confirmed cases.