An assessment of the vaccination of school-aged children in England against SARS-CoV-2

COVID-19 vaccine uptake and associated factors among adolescents and youths: Findings and implications for future vaccination programmes

Adolescents and youths are a key part of the population that needs to be protected against the coronavirus disease 2019 (COVID-19). This is because they are more likely to spread the virus to vulnerable individuals. In view of these concerns, this study investigated the uptake of COVID-19 vaccines and associated factors among adolescents and youths attending secondary schools in Zambia. This cross-sectional study was conducted among 1500 school-going adolescents in Lusaka from September 2022 to November 2022. Overall, 1409 participants took part giving a response rate of 94%. Only 29.2% (n = 411) of the participants were vaccinated against COVID-19 at the time of the study. Compared to their unvaccinated counterparts, vaccinated adolescents and youths scored higher for knowledge (66.2% vs 57.8%) and attitudes (76.7% vs 39.4%) regarding COVID-19 vaccines. Healthcare workers, family/friends and social media were key sources of information regarding the vaccine. Factors associated with increased vaccine uptake were positive attitudes (AOR = 33.62, 95% CI: 19.92-56.73), indicating it was stressful to follow COVID-19 preventive measures (AOR = 1.47, 95% CI: 1.09-1.99), participants in Grade 12 (AOR = 3.39, 95% CI: 1.94-5.91), Grade 11 (AOR = 2.59, 95% CI: 1.94-5.91), Grade 10 (AOR = 3.48, 95% CI: 1.98-6.11) and Grade 9 (AOR = 3.04, 95% CI: 1.74-5.32) compared to Grade 8. This study found a relatively low uptake of COVID-19 vaccines among adolescents and youths in Zambia. There is a need to provide adequate strategies to address knowledge and attitude gaps regarding COVID-19 vaccines to improve uptake and reduce future morbidity and mortality.

Factors associated with the formation of SARS-CoV-2 case-clusters in Danish schools: a nationwide register-based observational study

A register-based retrospective observational study was conducted to describe SARS-CoV-2 cases and case-clusters in schoolchildren of Danish primary and lower secondary schools and identify which factors were associated with the occurrence of case-clusters in schools. The study period was the autumn school semester 2021. Clusters were defined as three or more cases in a school-class level within 14 days. Descriptive analysis was carried out and multivariable logistic regression analysis was performed to determine which factors were associated with case introductions (i.e., primary case) being linked to a cluster. More cases and clusters were identified in lower than in higher class levels. Out of 21,497 cases introduced into a school, 41.6% started a cluster. A higher assumed immunity level in a class level was significantly reducing the odds of a case introduction being linked to a cluster (e.g., assumed immunity of ≥80% vs <20%: OR: 0.28; 95%CI: 0.17-0.44). A previous infection (in the primary case) had a protective effect (OR: 0.58; 95%CI: 0.33-0.99). This study suggests that most cases appearing in schools did not induce clusters, but that once cluster occur sizes can be large. It further indicates that vaccination of children markedly reduces the risk of secondary infections.

A Methodological Framework for Assessing the Benefit of SARS-CoV-2 Vaccination following Previous Infection: Case Study of Five- to Eleven-Year-Olds

Vaccination rates against SARS-CoV-2 in children aged five to eleven years remain low in many countries. The current benefit of vaccination in this age group has been questioned given that the large majority of children have now experienced at least one SARS-CoV-2 infection. However, protection from infection, vaccination or both wanes over time. National decisions on offering vaccines to this age group have tended to be made without considering time since infection. There is an urgent need to evaluate the additional benefits of vaccination in previously infected children and under what circumstances those benefits accrue. We present a novel methodological framework for estimating the potential benefits of COVID-19 vaccination in previously infected children aged five to eleven, accounting for waning. We apply this framework to the UK context and for two adverse outcomes: hospitalisation related to SARS-CoV-2 infection and Long Covid. We show that the most important drivers of benefit are: the degree of protection provided by previous infection; the protection provided by vaccination; the time since previous infection; and future attack rates. Vaccination can be very beneficial for previously infected children if future attack rates are high and several months have elapsed since the previous major wave in this group. Benefits are generally larger for Long Covid than hospitalisation, because Long Covid is both more common than hospitalisation and previous infection offers less protection against it. Our framework provides a structure for policy makers to explore the additional benefit of vaccination across a range of adverse outcomes and different parameter assumptions. It can be easily updated as new evidence emerges.

Public health impact of UK COVID-19 booster vaccination programs during Omicron predominance

BACKGROUND

We aimed to estimate the public health impact of booster vaccination against COVID-19 in the UK during an Omicron-predominant period.

RESEARCH DESIGN AND METHODS

A dynamic transmission model was developed to compare public health outcomes for actual and alternative UK booster vaccination programs. Input sources were publicly available data and targeted literature reviews. Base case analyses estimated outcomes from the UK's Autumn-Winter 2021-2022 booster program during January-March 2022, an Omicron-predominant period. Scenario analyses projected outcomes from Spring and in Autumn 2022 booster programs over an extended time horizon from April 2022-April 2023, assuming continued Omicron predominance, and explored hypothetical program alternatives with modified eligibility criteria and/or increased uptake.

RESULTS

Estimates predicted that the Autumn-Winter 2021-2022 booster program averted approximately 12.8 million cases, 1.1 million hospitalizations, and 290,000 deaths. Scenario analyses suggested that Spring and Autumn 2022 programs would avert approximately 6.2 million cases, 716,000 hospitalizations, and 125,000 deaths; alternatives extending eligibility or targeting risk groups would improve these benefits, and increasing uptake would further strengthen impact.

CONCLUSIONS

Boosters were estimated to provide substantial benefit to UK public health during Omicron predominance. Benefits of booster vaccination could be maximized by extending eligibility and increasing uptake.

Impact of SARS-CoV-2 vaccination of children ages 5-11 years on COVID-19 disease burden and resilience to new variants in the United States, November 2021-March 2022: A multi-model study

Background

The COVID-19 Scenario Modeling Hub convened nine modeling teams to project the impact of expanding SARS-CoV-2 vaccination to children aged 5-11 years on COVID-19 burden and resilience against variant strains.

Methods

Teams contributed state- and national-level weekly projections of cases, hospitalizations, and deaths in the United States from September 12, 2021 to March 12, 2022. Four scenarios covered all combinations of 1) vaccination (or not) of children aged 5-11 years (starting November 1, 2021), and 2) emergence (or not) of a variant more transmissible than the Delta variant (emerging November 15, 2021). Individual team projections were linearly pooled. The effect of childhood vaccination on overall and age-specific outcomes was estimated using meta-analyses.

Findings

Assuming that a new variant would not emerge, all-age COVID-19 outcomes were projected to decrease nationally through mid-March 2022. In this setting, vaccination of children 5-11 years old was associated with reductions in projections for all-age cumulative cases (7.2%, mean incidence ratio [IR] 0.928, 95% confidence interval [CI] 0.880-0.977), hospitalizations (8.7%, mean IR 0.913, 95% CI 0.834-0.992), and deaths (9.2%, mean IR 0.908, 95% CI 0.797-1.020) compared with scenarios without childhood vaccination. Vaccine benefits increased for scenarios including a hypothesized more transmissible variant, assuming similar vaccine effectiveness. Projected relative reductions in cumulative outcomes were larger for children than for the entire population. State-level variation was observed.

Interpretation

Given the scenario assumptions (defined before the emergence of Omicron), expanding vaccination to children 5-11 years old would provide measurable direct benefits, as well as indirect benefits to the all-age U.S. population, including resilience to more transmissible variants.

Funding

Various (see acknowledgments).

Comparison of the 2021 COVID-19 roadmap projections against public health data in England

Control and mitigation of the COVID-19 pandemic in England has relied on a combination of vaccination and non-pharmaceutical interventions (NPIs). Some of these NPIs are extremely costly (economically and socially), so it was important to relax these promptly without overwhelming already burdened health services. The eventual policy was a Roadmap of four relaxation steps throughout 2021, taking England from lock-down to the cessation of all restrictions on social interaction. In a series of six Roadmap documents generated throughout 2021, models assessed the potential risk of each relaxation step. Here we show that the model projections generated a reliable estimation of medium-term hospital admission trends, with the data points up to September 2021 generally lying within our 95% prediction intervals. The greatest uncertainties in the modelled scenarios came from vaccine efficacy estimates against novel variants, and from assumptions about human behaviour in the face of changing restrictions and risk.

The ’Roadmap’ for relaxation of COVID-19 restrictions in England in 2021 was informed by mathematical modelling. Here, the authors perform a retrospective assessment of the accuracy of modelling predictions and identify the main sources of uncertainty that led to observed values deviating from projections.