Category: Covid-19 Vaccine

It has been more than three years since the first COVID-19 vaccine received emergency use authorization by the US Food and Drug Administration in December 2020. Since that time, the US has seen the emergence and approval of several other COVID-19 vaccines and distributed hundreds of millions of doses to populations across the nation.

But what about other countries? What is the status of COVID-19 vaccine access around the world? To gain greater clarity on the status of global vaccine access, we asked SIS professor Nina Yamanis a few questions.

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Q&A: Current Global Access to the COVID-19 Vaccine - American University

The purpose of the analyses presented here was to evaluate distinct vaccine uptake strategies in the context of COVID-19. We aim to achieve qualitative results by exploring counterfactual scenarios driven by vaccine uptake. Therefore, we exploited the unfolding of the Belgian COVID-19 crisis with the induction of SARS-COV-2 in February 2020 and the emerging Alpha, Delta, and Omicron (BA.1 and BA.2) VOCs. Each simulation spans the first two years of the COVID-19 pandemic, running from March 2020 to February 2022. It includes age-specific uptake of first, second, and booster doses of adenovirus and mRNA-based vaccines. The uptake scenarios being examined vary between August 2021 and February 2022, which is the period our results primarily focus on.

We extended a previously published stochastic transmission model for SARS-CoV-2 in Belgium by Abrams et al.[27], by including COVID-19 vaccination, emergence of different VOCs and waning immunity. Our transmission model is a discrete-time age-structured compartmental model with a chain-binomial transition process between various disease compartments that can be categorised into susceptible, exposed, infected, recovered, and death states. Overall, after exposure to the pathogen and acquiring infection, an individual becomes infectious after a latent period and moves to a pre-symptomatic state. Subsequently, individuals develop symptoms or remain asymptomatic, before recovering. Symptomatic infections start mild and have an age-specific probability of progressing to serious illness, implying hospitalisation with or without admission to the ICU. We also account for disease-related mortality of hospitalised cases. The original model formulation is duplicated into a two-strain compartmental structure (see Fig.1), and transitions between multiple copies of the two-strain model (see Fig.2) allowed for waning immunity against infection and severe disease. Further elaboration on the construction of the model, specifically based on multiple substructures, is presented in the subsequent paragraphs.

The model structure proposed by Abrams et al.[27] including ten 10-year age groups has been adapted to a two-strain version with a common susceptible class and a duplication of all infection-related health states. Our model structure (see Fig.1) enabled co-circulation of two variants at the same time with distinct properties with respect to susceptibility, latent period, disease severity, hospital length of stay, mortality, and vaccine-related protection. To cover the newly emerging Delta VOC, we re-used the health states of the dominated original strain in the simulation after book keeping all states. A similar transition was made with the Omicron VOC when the Alpha VOC was fully dominated by the Delta VOC. More information about model dynamics and parameters is provided in the Supplementary Information. Our model operates starting from March 1st, 2020, and accounts for the emergence of new pathogen strains and the administration of various vaccine doses. In the early stages, these factors are represented in small amounts, with heterogeneity and randomness playing critical roles. Even slight variations can become amplified over time. Later on, after COVID-19 vaccination is introduced and attains high coverage, the size of the remaining susceptible population becomes small. This makes the stochastic nature of infection and subsequent processes like hospitalisation and death increasingly significant, especially since the model is calibrated using age-specific incidence data for each of these stages. These elements highlight the importance of the stochastic nature of our compartmental model in accurately reflecting and predicting evolving dynamics.

Health states and transitions in the two-strain transmission model. The model structure is described in the main text and model parameters are listed in the Supplementary Information

We used the reported social contact rates of 42 Belgian CoMix survey waves between April2020 and March2022[28, 29] as proxy for effective contacts that allow disease transmission according to the social contact hypothesis[30]. CoMix has been designed as a collection of surveys in which a panel of participants retrospectively reports all social contacts made from 5:00 AM on the day preceding the survey up to 5:00 AM on the day of the survey. A contact was defined as an in-person conversation of at least a few words or a skin-to-skin contact[28]. Changes in transmission that are not directly attributable to changes in contact behaviour are captured in age-specific proportionality factors. They represent, for example, changes in compliance to (social distancing) measures, seasonality effects, and shifts in the location-specific contact intensity (e.g., contacts inside are more risky than contacts outside). For each wave, we estimated age-specific proportionality factors to translate social contact rates into transmission rates that capture age-specific susceptibility and infection-related risk behaviour associated with social contacts[31].

The introduction and presence of VOCs in the model population are taken into account in the parameter estimation process based on the baseline genomic surveillance of SARS-CoV-2 in Belgium by the National Reference Laboratory[32]. To simulate the replacement of the original strain in 2021, we aggregated all Alpha, Beta, and Gamma VOC samples that were identified, which we refer to hereafter as Alpha VOC infections, when estimating the penetration of the VOCs into the Belgian population. We attributed the growth advantage of the Alpha VOC completely to transmissibility and ignored the potential effect of immune escape. We assumed that there was no change in the probability of hospital admission for the (aggregated) Alpha VOC. Conflicting post hoc observations have been reported on the severity of this VOC[33]. Therefore, we have chosen to highlight the significant role that increased transmissibility potential plays in hospitalisations and mortality, regardless of any direct effect of the variant on severity.

For the Delta VOC, we account for increased transmissibility and adopted an adjusted hazard ratio for hospitalisation of 2.26 relative to the Alpha VOC based on a cohort study conducted in the UK[34]. Due to the lack of age-specific information to align the reported 95% confidence interval of [1.32;3.89] with our age-specific model design, we opted to use the estimated mean value without considering parameter uncertainty. This adjusted hazard ratio was essential to match the reported incidence of hospitalisations with genomic surveillance data on the Delta VOC[32].

With the emergence of the Omicron VOC, studies[35, 36] indicated a change in the incubation period and the serial interval, which contributes to its transmission advantage. This had a large impact on the estimated reproduction number and the effect of restrictive measures. As such, we included a VOC-specific latent period in our transmission model, which was inferred specifically for the Omicron VOC during the calibration process. Furthermore, Omicron-specific hazard ratios for hospitalisation were pivotal to capture the trends observed in 2022. We adopted age-specific hazard ratios for hospital attendance with the Omicron VOC compared to the Delta VOC, from a cohort study in the UK[37]. More specifically, we used for our 10-year age bands: 1, 0.89, 0.67, 0.57, 0.54, 0.42, 0.32, 0.42, 0.49 and 0.49. The simulation period covers both Omicron sub-lineages BA.1 and BA.2, the latter became dominant in Belgium on February 28th, 2022. The differences in transmission for BA.2 are absorbed in the wave-specific proportionality parameters for February/March 2022.

All the levels of protection adopted are summarised in Table1. We used a leaky vaccine implementation approach in which vaccination with 74% effectiveness implies that for a vaccinated individual the probability of acquiring infection is 74% lower compared to a non-vaccinated individual of the same age. Vaccine-induced immunity against infection is implemented as a step function in terms of protection against infection 21days after the first dose of vaccine. Protection induced by second and booster vaccine doses is assumed to be fully achieved 7days after vaccine administration (i.e., depending on the maximal effectiveness of the vaccine as reported in Table1). We consider the differences between mRNA- and adenovirus-based vaccines in how they induce immunity and in terms of protection. We assumed that vaccinated individuals who acquire infection are at a lower risk of hospital admission with COVID-19 and all booster doses in Belgium are mRNA-based vaccines. Given our model structure, reported protection levels against hospital admission were applied as protection against severe disease, which ultimately leads to hospital admission. Vaccinated individuals (with or without a booster) who acquire infection do not have a lower risk of transmitting the disease. This assumption is challenged in the sensitivity analysis.

Vaccine-induced protection and waning immunity have been included through duplication of the two-strain compartmental structure with uptake-based and time-specific transitions (see Fig.2). This model structure allowed us to explicitly keep track of vaccine type and dose-specific vaccine uptake and to differentiate protection against infection and severe disease between vaccine type and number of doses. The duplicated two-strain compartmental structure also allowed differential waning immunity against infection and severe disease.

We integrated waning immunity into our model by establishing a series of steps transitioning from complete protection to a state of diminishing immunity over an average period of 90 days. In the framework of the compartmental model, the waning rate is defined as the fraction of individuals transitioning from full protection per time unit, which inversely correlates with the average protection duration. Consequently, we incorporated submodels for diminishing vaccine-induced immunity, featuring levels of reduced protection as detailed in Table1. Initially, infection-induced immunity offers 100% protection, assuming individuals in the Recovered state are not susceptible to reinfection. Therefore, our model accounts for the decrease in infection-induced immunity by moving individuals from the Recovered to the Susceptible compartment within a submodel, which still affords a degree of protection against future infections. We assumed the effect of a booster dose independent of the immunity state upon vaccination, i.e., with or without prior infection or a specific vaccine scheme. We accounted for waning immunity after the booster dose with a dedicated submodel and an average transition time of 90 days. Note that even with waning immunity, vaccinated individuals maintain partial protection against subsequent infection and severe disease upon infection. VOC-specific protection levels for the booster dose have been derived from the literature (see Table1).

Vaccine uptake in the model is based on age-specific data at the national level reported by the Belgian Scientific Institute for Public Health, Sciensano[38]. By August 2021, on average 90% of the population aged over 20 years had completed their two-dose regimen with mRNA or adenovirus-based vaccines. On the contrary, about 10% of the 0-19-year-olds received two doses of an mRNA vaccine at that time. It is important to note that in August 2021, mRNA vaccines were only authorized for use in children aged 12 years and older by the European Medicine Agencys Committee for Medicinal Products for Human Use. Subsequently, in 2022, the authorisation was extended to younger children, initially to those aged 6 years and older, and later to infants as young as 6 months of age. The decision to administer booster doses at the end of 2021 was based on the evaluation by the European Medicines Agency that indicated an increase in antibody levels following a booster dose administered about 6 months after the second dose in individuals aged 18 to 55 years. Based on this evidence, first booster doses were recommended in Belgium for people 18 years and older at least 6 months after the second dose.

Full details on the type- and dose-specific vaccine uptake by age we included in the model is presented in Fig.S2. We did not explicitly account for risk-group vaccination, since our model structure did not facilitate more subpopulations with differential risk and potentially a more severe episode of COVID-19 disease once infected (i.e., a higher probability of hospitalisation and/or a higher probability of death, if hospitalised). In our analysis, we primarily considered age as the main determinant of risk and severity. The reported uptake of Pfizer-BioNtech (Comirnaty) and Moderna (Spikevax) vaccines are aggregated into one mRNA vaccine type. The relatively low number of reported Johnson & Johnson (Ad26.COV2.S) and Curevac (CV07050101) vaccines were aggregated in the model with the adeno-based AstraZeneca vaccine (ChAdOx1 or Vaxzevria) based on similarities in protection and waning immunity. Third doses (i.e. first booster dose) are included in the transmission model as a separate submodel with all health-related compartments. A comprehensive summary of vaccine uptake we included in our model is depicted in Fig.3, which presents also the scenarios discussed in the subsequent sections of the Methods.

Overview of the duplicated two-strain model structure to account for vaccine type- and dose-specific immunity against infection and severe disease in combination with differential waning immunity over time. The grey boxes embody the transmission structure included in Fig.1 while only the Susceptible and Recovered are shown here (with (R_i) representing (R_a) and (R_b)). More information on the waning states is included in Table1

We used Bayesian methods to fit our transmission model to multiple data sources, including daily hospital admissions and bed occupancy, early seroprevalence, genomic surveillance, and mortality data. In order to capture the full extent of the intrinsic variability of the model, we relied on Markov Chain Monte Carlo (MCMC) sampling with 60 chains in the calibration procedure. An adaptive Metropolis-within-Gibbs algorithm was used as MCMC sampler, and parameter priors were based on permutations of previously converged calibration results. The model parameters related to hospital incidence and VOC prevalence were estimated by gradually extending the time horizon over consecutive calibration runs for the stochastic model. The absence of age-specific data on daily hospital discharges and transitions between general wards and ICU hampered a likelihood approach to accommodate hospital occupancy in general and in the ICU. Therefore, the fitting of the model was performed using a multi-step procedure. First, all transmission-related model parameters were estimated while calibrating the model to the observed incidence data on hospitalisation, early seroprevalence and genomic surveillance as described above. Next, all parameters related to hospital and ICU occupancy (including discharge rates) were estimated based on minimising a least squares criterion for the distance between the observed and generated loads. Finally, the estimated mortality-related parameters are inferred again using a likelihood-based approach, distinguishing whether a hospital discharge was due to mortality or recovery. This multi-step procedure has been performed multiple times, of which the final iteration is described in TableS2. Finally, we selected the 40 best performing MCMC chains of the last step to derive parameter estimates for our simulation study.

We used hospital admissions with COVID-19 as a primary source of information to capture the burden of disease. During the development of the model, we observed that around 10%-20% of the admissions with the Alpha and Delta VOCs were primarily due to other pathologies, but patients who tested positive when admitted were transferred to the COVID-19 wards and counted in the COVID-19 hospital load. With the Omicron VOC, the difference between admissions with COVID-19 and for COVID-19 increased even more. Given our focus on hospital capacity, hence occupancy, hospital admissions with COVID-19 were most informative in combination with reported estimates for hospital stay.

We estimated a transmission advantage of the Alpha VOC compared to the original strain of 32% (95% CrI: 24-39%). For the Delta VOC, the transmission advantage compared to the Alpha strain was estimated to be 87% (95% CrI: 71-106%). For Omicron, we estimated an almost instant transition from the exposed to the pre-symptomatic infectious health state (which is in line with the shorter serial interval we referred to previously) and a transmission advantage compared to the Delta VOC of 35% (95% CrI: 9-70%). A comprehensive overview of the model parameters is presented in TableS3 of the Supplementary Information.

The baseline scenario consisted of all estimated parameters during the calibration of the compartmental model and fitted the national trends of SARS-CoV-2 pandemic in Belgium. This includes, for example, the emergence and dominance of the Omicron variant from December 2021 and the observed decrease in hospital admissions and deaths at that time. The full model output from March 2020 is presented in Fig.S4. The transmission model was based on bi-weekly social contact survey data, which allows for including adjusted behaviour over time in the model. The survey data represented changing contact rates, while the estimated proportionality factors captured differences in, for example, contact intensity, susceptibility and infectivity. These factors were age-specific and part of the parameter estimation process (see Fig.S5).

To estimate the burden of disease, we included the loss of QALYs from a published study on the model-based cost-effectiveness of SARS-CoV-2 vaccination along with physical distancing in the United Kingdom[22]. Disease morbidity estimates were obtained by multiplying the model-based incidence of mild infections, and hospitalised and ICU admitted patients with the QALY loss values in Table2. Disease-related mortality based on the quality-adjusted life expectancy[39] is obtained by combining the age-specific model estimations on mortality with the Belgian life expectancy for 2019 reported by Statbel[40] and the latest age-specific Belgian population norms based on EQ-5D-5L[25].

We explored retrospective counterfactual scenarios based on vaccine uptake in the presence or absence of the Omicron VOC. None of these scenarios explicitly included the importation of infected cases as a result of international travel except for the introduction of VOCs. We started from the final calibration of the model and the reported vaccine uptake scheme and explored proportionally increased uptake of two doses in 511-year-old children and first booster doses in adults over 18-years. Vaccine uptake levels and timing could be explored more in detail with additional objectives and trade-offs, although this analysis aims to provide a basis for predominantly qualitative interpretations. We allow for stochastic variation in the transmission process by running each of the 40 estimated model parameter sets 10 times, hence incorporating 400 model realisations in the final comparison. The number of realisations was determined through a process of model exploration and consideration of the trade-off between model realisations and computational feasibility due to model complexity.

To explore the impact of the uptake of the COVID-19 vaccine, we evaluated an adjustment of the uptake of the first booster dose in adults and an increase in the level of childhood vaccination. First, we changed the uptake of the first booster dose so that it matches the age-specific two-dose uptake levels by 1 March 2022 (see Fig.3). That is, we assumed that all those eligible for a first booster dose effectively received an mRNA booster dose. The reported first booster dose uptake in the Belgian adult population was 76%, so the additional uptake in the scenario analysis was rather limited. Secondly, we defined a scenario in which we arbitrarily included only 60% of the reported uptake of the first booster dose. The 40% reduction is applied uniformly across all age groups. A third adoption scenario focused on children aged 5-11 years in July-August of 2021. Vaccination in this age class was was not licensed at the time in Belgium, although we explore possible outcomes if 5- to 17-year-old children had been vaccinated simultaneously. More specifically, we aligned the uptake of the mRNA vaccine for children aged 5-9 and 10-11 years with the reported uptake of children aged 12-15 and 16-17 years, respectively. This approach required scaling the reported uptake to match the number of age bins in each group. For example, for each reported first dose in 12-15-year-old children (i.e. 4 age bins), we included (frac{5}{4}) dose within the 5-9-year-olds (i.e. 5 age bins) at the given point in time. The time between two consecutive doses is assumed to be three weeks, and the resulting vaccine uptake is presented in Fig.3. The final uptake of two doses of vaccine is approximately 80% in the group of 10-19 years and 40% in the group of 0-9 years (which corresponds to 80% in the group of 5-9 years).

Reported and scenario-based uptake of COVID-19 vaccines over time in adults above the age of 20y (top) and 0-19-year-old children (bottom). The uptake is presented in terms of the absolute number of doses (left axis) and as a percentage of the target group (right axis)

To assess the impact of the Omicron VOC on the epidemic trajectory, we performed simulations of our three adjusted vaccine uptake scenarios without the presence of the Omicron VOC, while keeping all other model parameters constant.

In our main analysis, we adopted a conservative approach that assumed no infectiousness-related protection from the COVID-19 vaccine, which potentially underestimates the effect of the intervention. As such, we opt to minimise the risk of overestimating the intervention-related benefits for this exploratory analysis. However, household studies conducted in Denmark[41] and the UK[42] have reported a 31%-45% decrease in the risk of SARS-CoV-2 transmission among vaccinated individuals. Therefore, as a sensitivity analysis taking into account these findings, we performed a comprehensive model calibration assuming a 30% reduction in infectiousness for vaccinated individuals and exploring the effect on the vaccine scenarios.

As robustness analyses, we performed the full model calibration with invariant proportionality factors across different consecutive CoMix waves. A single set of age-specific parameters was not possible as the link between observed contact rates and disease transmission was not constant throughout 20202022 due to differences in contact intensity, duration, and location, among other things. Therefore, we aggregated the CoMix waves into five groups based on the distancing measures that were in place, the (school) holiday periods, and the model fit. For the time period without CoMix data (i.e. for March and SeptemberNovember 2020), we still required time-specific q-factors. Details are provided in Supplementary TableS1.

Part of this epidemiological mathematical modelling study was carried out to inform the Belgian government and the general public about COVID-19 trends and possible interventions. This study is based on data sources from the Belgian Institute of Public Health (Sciensano) in combination with published estimates and data sets (e.g., CoMix). Funding agencies did not have a role in study design, data collection, data analysis, data interpretation, reporting, or in the writing of this manuscript. Data preparation and statistical analyses were performed using R (version 4.2.2; R Foundation for Statistical Computing, Vienna, Austria) on MacOS 12.5 and using R (version 4.0.2) on Rocky Linux 8.8 on the VSC cluster.

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The impact of quality-adjusted life years on evaluating COVID-19 mitigation strategies: lessons from age-specific ... - BMC Public Health

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Morgan Ritz's two year battle with symptoms after COVID 19 vaccinations - Wooster Daily Record

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The study showed that the bivalent vaccine was better at neutralizing more recent viral variants, such as omicron and its subvariants

Credit: Fbio Rodrigues-Pozzebom/Agncia Brasil

A major bivalent COVID-19 vaccine induces production of neutralizing antibodies against the coronavirus that circulated at the start of the pandemic as well as subvariants of omicron, albeit less abundantly, according to a Brazilian studyreportedin theJournal of Medical Virology.

The study confirmed the vaccines effectiveness and its importance to control of the disease, while also showing that, more than three years after the first application of a COVID-19 vaccine in Brazil, the vaccination model should be similar to that adopted for influenza, with frequent adjustments to the formulation to prioritize more recent variants.

This was the first research project conducted to evaluate the immunity induced by the Pfizer-BioNTech bivalent vaccine (COMIRNATY Original/Omicron BA.4-5) in a group of Brazilian subjects. The scientists investigated the antibody neutralization response against different variants of SARS-CoV-2 using serum samples from 93 healthy volunteers (31 males and 62 females) aged between 16 and 84 years and living in Barreiras, Bahia state. Some of the volunteers had previously been given three or four doses of monovalent vaccines based only on the original strain of the virus first identified in Wuhan, China, such as Coronavac (Butantan Institute/Sinovac), Covishield (Oxford/AstraZeneca), or those of Janssen and Pfizer.

Others were also given as an extra booster the bivalent vaccine containing components of the original strain as well as omicron subvariants BA.4 and BA.5.

Serum samples collected from the volunteers were submitted to antibody neutralization assays using different strains of SARS-CoV-2: the original strain from the start of the pandemic; omicron (BA.1), predominant in 2021; and omicron subvariants FE.1.2 and BQ.1.1, predominant in Brazil more recently.

The study was funded by FAPESP (projects20/052047,20/064091,20/089435,21/056611,22/119811 and23/019250), and by the Brazilian Ministry of Science, Technology and Innovation (MCTI).

The study showed that the bivalent vaccine administered as a booster reinforced the immune response and was more effective in neutralizing omicron and its subvariants than in volunteers given only four shots of a monovalent vaccine. However, its main focus was still the original strain that predominated at the start of the pandemic, and the resulting competition limited medium- to long-term immunity against more recent variants, which are now more important epidemiologically.

This was expected because immune memory is based on cells capable of recognizing fractions of the virus and is reinforced by the number of contacts with the contaminant. The immune system will naturally react more against what it already knows, and the participants given the bivalent vaccine had already taken three or four doses of a monovalent vaccine, saidJaime Henrique Amorim, last author of the article. Amorim is a professor at the Federal University of Western Bahia (UFOB) and a visiting researcher at the University of So Paulos Biomedical Sciences Institute (ICB-USP).

Model for the future

Controlling a virus with the high transmission capacity of SARS-CoV-2 requires equally high vaccine coverage, saidLus Carlos de Souza Ferreira,head of ICB-USPs Vaccine Development Laboratory and a co-author of the article. The results of the study show that bivalent vaccines are effective to achieve immunity against subvariants of omicron and that their administration has been fundamental to control novel variants.

According to the researchers, another conclusion to be drawn from the findings is that future planning of vaccination policy should take into account the fact that the immune response induced by existing vaccines is mainly to the original strain, which has ceased circulating since 2020, and vaccines should have their formulation adjusted so that they no longer include these components.

Forthcoming doses should be designed to combat the variants that are circulating now, instead of those that have disappeared, so that immunity is updated and reinforced in accordance with the current epidemiological situation, as it already is in the case of influenza vaccines, Amorim said.

The joint first authors of the article are Milena Silva Souza and Jssica Pires Farias, researchers at UFOB. The other co-authors are affiliated with institutions in Brazil and the United States.

About So Paulo Research Foundation (FAPESP)

The So Paulo Research Foundation (FAPESP) is a public institution with the mission of supporting scientific research in all fields of knowledge by awarding scholarships, fellowships and grants to investigators linked with higher education and research institutions in the State of So Paulo, Brazil. FAPESP is aware that the very best research can only be done by working with the best researchers internationally. Therefore, it has established partnerships with funding agencies, higher education, private companies, and research organizations in other countries known for the quality of their research and has been encouraging scientists funded by its grants to further develop their international collaboration. You can learn more about FAPESP atwww.fapesp.br/enand visit FAPESP news agency atwww.agencia.fapesp.br/ento keep updated with the latest scientific breakthroughs FAPESP helps achieve through its many programs, awards and research centers. You may also subscribe to FAPESP news agency athttp://agencia.fapesp.br/subscribe.

Journal of Medical Virology

Neutralizing antibody response after immunization with a COVID-19 bivalent vaccine: Insights to the future

29-Jan-2024

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Study confirms effectiveness of bivalent COVID-19 vaccine - EurekAlert

Key Points

Question Was implementation of the pediatric COVID-19 immunization program of California associated with reductions in the reported pediatric COVID-19 incidence and hospitalizations?

Finding In this case series including 3.9 million children, pediatric vaccination was estimated to avert 146210 cases of COVID-19 among adolescents aged 12 to 15 years during a 141-day postvaccine evaluation period and 230134 cases among children aged 5 to 11 years during a 199-day postvaccine evaluation period. In addition, an estimated 168 hospitalizations were averted among children aged 6 to 59 months during a 225-day evaluation period.

Meaning The findings of this study suggest that vaccination against SARS-CoV-2 was associated with significant reductions in COVID-19 incidence and hospitalizations among children in California.

Importance A SARS-CoV-2 vaccine was approved for adolescents aged 12 to 15 years on May 10, 2021, with approval for younger age groups following thereafter. The population level impact of the pediatric COVID-19 vaccination program has not yet been established.

Objective To identify whether California's pediatric COVID-19 immunization program was associated with changes in pediatric COVID-19 incidence and hospitalizations.

Design, Setting, and Participants A case series on COVID-19 vaccination including children aged 6 months to 15 years was conducted in California. Data were obtained on COVID-19 cases in California between April 1, 2020, and February 27, 2023.

Exposure Postvaccination evaluation periods spanned 141 days (June 10 to October 29, 2021) for adolescents aged 12 to 15 years, 199 days (November 29, 2021, to June 17, 2022) for children aged 5 to 11 years, and 225 days (July 17, 2022, to February 27, 2023) for those aged 6 to 59 months. During these periods, statewide vaccine coverage reached 53.5% among adolescents aged 12 to 15 years, 34.8% among children aged 5 to 11 years, and 7.9% among those aged 6 to 59 months.

Main Outcomes and Measures Age-stepped implementation of COVID-19 vaccination was used to compare observed county-level incidence and hospitalization rates during periods when each age group became vaccine eligible to counterfactual rates predicted from observations among other age groups. COVID-19 case and hospitalization data were obtained from the California reportable disease surveillance system.

Results Between April 1, 2020, and February 27, 2023, a total of 3913063 pediatric COVID-19 cases and 12740 hospitalizations were reported in California. Reductions of 146210 cases (95% prediction interval [PI], 136056-158948) were estimated among adolescents aged 12 to 15 years, corresponding to a 37.1% (35.5%-39.1%) reduction from counterfactual predictions. Reductions of 230134 (200170-265149) cases were estimated among children aged 5 to 11 years, corresponding to a 23.7% (20.6%-27.3%) reduction from counterfactual predictions. No evidence of reductions in COVID-19 cases statewide were found among children aged 6 to 59 months (estimated averted cases, 259; 95% PI, 1938 to 1019), although low transmission during the evaluation period may have limited the ability to do so. An estimated 168 hospitalizations (95% PI, 42-324) were averted among children aged 6 to 59 months, corresponding to a 24.4% (95% PI, 6.1%-47.1%) reduction. In meta-analyses, county-level vaccination coverage was associated with averted cases for all age groups. Despite low vaccination coverage, pediatric COVID-19 immunization in California averted 376 085 (95% PI, 348355-417328) reported cases and 273 (95% PI, 77-605) hospitalizations among children aged 6 months to 15 years over approximately 4 to 7 months following vaccination availability.

Conclusions and Relevance The findings of this case series analysis of 3913063 cases suggest reduced pediatric SARS-CoV-2 transmission following immunization. These results support the use of COVID-19 vaccines to reduce COVID-19 incidence and hospitalization in pediatric populations.

Vaccination is among the most important interventions to reduce the public health impact of infectious diseases.1 SARS-CoV-2 mRNA vaccines, including mRNA1273 (Moderna) and BNT162b2 (Pfizer BioNTech), were approved for adult use in December 2020.2 On May 10, 2021, the first mRNA COVID-19 vaccine was approved for use in adolescents aged 12 to 15 years. Vaccines were subsequently approved for children aged 5 to 11 years on October 29, 2021, and for children aged 6 to 59 months on June 17, 2022 (Figure 1).2

COVID-19 vaccines are safe for children.3 However, concerns over vaccine-related adverse events, lower vaccine effectiveness against illness in children, and perceptions of a milder disease course in children have resulted in high rates of parental vaccine hesitancy4-6 and resistance to pediatric vaccine mandates.7 While California has among the highest rates of vaccination in the US,8 pediatric vaccination coverage lags that of adults substantially, with only 8.2% of children younger than 5 years and 37.8% of children aged 5 to 11 years fully vaccinated as of May 2023.8 Severe manifestations of COVID-19 are rare among children, but can occur.9 Understanding the population-level impact of COVID-19 vaccinations in SARS-CoV-2 infections and hospitalizations in pediatric populations would aid in public health decision-making on pediatric vaccine and booster policy and provide pediatric-specific information on vaccine outcomes that could be applied to future SARS-CoV-2 variants.

Herein, we analyze data on 3913063 pediatric cases of COVID-19 and 12740 hospitalizations from California. Using the phased introduction of the vaccine to individuals aged 12 to 15 years, 5 to 11 years, and 6 to 59 months, we estimated statewide and county-specific outcomes associated with vaccination on pediatric incidence and hospitalizations in California.

We obtained deidentified information on all pediatric COVID-19 cases reported in California between April 1, 2020, and February 27, 2023, from the California COVID-19 Reporting System, along with the patients county of residence, age, and hospitalization status. Each case was confirmed using a nucleic acid amplification test. Because the research constitutes a public health surveillance activity, the study did not constitute human research and does not require institutional review board review or exemption according to the Common Rule (45 CFR 46). We followed the reporting guideline for case series studies.

Daily cases were aggregated by county and age groups based on dates of vaccination eligibility: 0 to 5 months (vaccine ineligible), 6 to 59 months, 5 to 11 years, 12 to 15 years, and older than 16 years (nonpediatric). To remove variation due to differential health care seeking by day of week, we calculated 7-day moving averages of case counts per county and age group. Due to small counts for pediatric hospitalizations, we aggregated hospitalizations by week and age group within 5 California-designated regions (eFigure 1 in Supplement 1). Descriptions of other covariate data are covered in the eMethods in Supplement 1).

Training and Prediction Periods

For each age group of interest (6-59 months, 5-11 years, and 12-15 years), we split data into age-eligible and age-ineligible periods. The prevaccine eligibility period encompassed data up to the date of vaccine eligibility. The evaluation period for the outcome associated with the vaccine lasted from 1 month following the date of vaccine eligibility (to allow time to complete 2 doses) until the date that the next age group became eligible or until the time of analysis (February 27, 2023) (Figure 1). Ending the evaluation period at the vaccine eligibility date of the next eligible age group permitted that age group to be selected as a control time series in our predictive models.

Candidate Model Generation and Selection

We developed a set of candidate predictive generalized linear models, which are described in greater detail in the eMethods in Supplement 1. Predictors eligible for selection within candidate models included (1) log-incidence series for other age groups (ie, <6 months, 6-59 months, 5-11 years, 12-15 years, and 16 years, omitting the group being modeled) included as either covariates or as an offset term for any 1 age group; (2) an indicator of vaccine age eligibility for other age groups; (3) an indicator for in-person school being in session; (4) interactions between school and vaccine introduction indicators and time series for other age groups, aiming to account for differences in constant proportionality during school periods or when 1 age group became vaccinated; and (5) seasonal controls. Eligible predictors are summarized in eTable 1 in Supplement 1. Quasi-Poisson distributions were fit for the outcome to account for overdispersion. Models were developed separately for each California county.

Candidate models for hospitalizations included similar eligible predictors, with 2 main differences: log weekly case incidence series for other age groups was lagged by 2 weeks in accordance with the expected lag between infection and hospitalization10 and unlagged weekly hospitalizations across other age groups were included as possible predictors. Models were developed separately for each of the 5 regions.

We used a time series with a 1-year gap cross-validation approach (eMethods and eFigure 2 in Supplement 1) to select the best predictive model for each age group and geographic area (county or region) within the prevaccine period.11-13 For each area-age group combination, we selected the model with the lowest out-of-sample mean square error across holdout folds. For this model, we also calculated the coefficient of determination, r2, a goodness-of-fit metric. The selected predictors varied by area and age group. Selected models for each area-age group combination are included in eTable 2 (for cases) and eTable 3 (for hospitalizations) in Supplement 1.

Calculation of Vaccine Outcomes and Association Between Averted Cases and Vaccination Coverage

Selected models were fit to prevaccine eligibility data for their age group and geographic area and then used to predict counterfactual incidence or hospitalization in the postvaccine period or the expected case or hospitalization counts had vaccination not occurred. For inference, we computed 95% prediction intervals (PIs) around the counterfactual predictions, using a sandwich estimator to account for overdispersion when computing SEs (eMethods in Supplement 1).14 Prediction intervals, which are wider than CIs, capture the uncertainty around each future predicted value. Statewide estimates were obtained by summing predictions across geographies (eMethods in Supplement 1).

We estimated the absolute and relative differences between predicted counterfactual values and observed values for each county or region during the postvaccine evaluation period. To understand the association between vaccination coverage and averted cases, we fit regression models relating the reduction in cases within each age and county to county-level vaccination coverage within the same age group, using a fixed-effects meta-analysis with weights equal to the inverse estimated SE of the estimates per county. We used segmented regression models (eMethods in Supplement 1) to examine whether there were coverages below which reductions in cases could not be identified or above which diminishing returns on vaccination were observed.15

To examine whether postvaccine predictions from a different, but well predictive model, yielded similar estimates of vaccination outcomes, we repeated model selection using the mean absolute error instead of the mean square error in our cross-validation algorithm. We conducted jackknife analyses to examine whether postvaccine predictions from any one county were driving observed effects, dropping each county in turn from the overall pool of counties and recalculating the primary analytic end point of cases averted.

All analyses were conducted in R, version 3.6.0 (R Foundation for Statistical Computing).16

Between April 1, 2020, and February 27, 2023, a total of 3913063 COVID-19 cases were reported in California among individuals aged 18 years or younger. Of these, 47174 cases (1.2%) were among children younger than 6 months, 517447 (13.2%) in children aged 6 to 59 months, 1590806 (40.7%) in children aged 5 to 11 years, and 1511690 (38.6%) in adolescents aged 12 to 15 years. A total of 12740 hospitalizations were reported: 1443 (11.3%) were among children younger than 6 months, 3428 (26.9%) in children aged 6 to 59 months, 2536 (19.9%) in children aged 5 to 11 years, and 3921 (30.8%) in adolescents aged 12 to 15 years.

Vaccine-Attributable Averted Cases and Hospitalizations by Pediatric Age Group

As shown in eFigure 3 in Supplement 1, r2 values for models fit to daily case data were 0.92 (IQR, 0.79-0.96) for children aged 6 to 59 months, 0.89 (IQR, 0.78-0.95) for children aged 5 to 11 years, and 0.79 (IQR, 0.62-0.90) for adolescents aged 12 to 15 years. eFigure 4 in Supplement 1 shows the model fit for hospitalizations. More details on model fit are included in the eResults in Supplement 1.

Adolescents Aged 12 to 15 Years

Individuals aged 12 to 15 years were eligible to be vaccinated against SARS-CoV-2 as of May 10, 2021. By October 29, 2021, when the next age group became eligible, 53.5% of this population had completed the 2-dose primary series of the vaccine, corresponding to 1712686 individuals. County-level vaccination rates ranged from 11.5% to 85.7%.8 During the 141 days spanning June 10 to October 29, 2021, 247700 COVID-19 cases were observed among individuals aged 12 to 15 years. We estimated that 394506 (95% PI, 392545-396467) cases of COVID-19 would have occurred absent vaccination, corresponding to 146210 (95% PI, 136056-158948) cases averted statewide or 37.1% (95% PI, 34.5%-40.3%) of expected cases (Table, Figure 2C). Incidence plots from all counties are included as eFigures 9-14 in Supplement 1.

During this same 141-day period, 688 hospitalizations were observed among adolescents. We estimated that 59 (95% PI, 65 to 244) hospitalizations were averted or a reduction of 7.9% (95% PI, 8.7% to 32.7%) from expectation (Table, Figure 3C). Hospitalization plots from all regions are included as eFigures 12-14 in Supplement 1.

Children Aged 5 to 11 Years

Children aged 5 to 11 years were eligible for vaccination on October 29, 2021. By June 17, 2022, 1219432 individuals (34.8% of this population) had completed a primary series of the vaccine, with a range of 10.0% to 74.7% by county.8 During the 199-day period following November 29, 2021, we estimated that 230134 (95% PI, 200170-265149) cases were averted due to the vaccine corresponding to a reduction of 23.7% (95% PI, 20.6%-27.3%) from counterfactual expectations (Table, Figure 2B). During this same period, we estimated that 46 (95% PI, 79 to 221) hospitalizations were averted, corresponding to 5.8% (95% PI, 10.2% to 28.6%) of expected hospitalizations (Table, Figure 3B).

Children Aged 6 to 59 Months

Children aged 6 to 59 months were eligible for vaccination on June 17, 2022. By February 27, 2023, 177087 (7.9%) individuals had received both doses of the primary series, with a range of 0.7% to 38.5% across counties.8 In the 225 days following July 17, 2022, we did not detect any significant changes in cases from counterfactual expectations in the postvaccine period (estimated averted cases: 259; 95% PI, 1938 1019) (Table). The postvaccine evaluation period for this age group did not include a surge in COVID-19 cases as it did for the other age groups (Figure 2A). However, we estimated that 168 (95% PI, 42-324) hospitalizations were averted following vaccination, or a reduction of 24.4% (95% PI, 6.1%-47.1%) from counterfactual expectations (Table and Figure 3A). Summing across all age groups, we estimated that pediatric vaccination was associated with reductions of 376 085 (95% PI, 348 355-417 328) reported cases and 273 (95% PI, 77-605) hospitalizations among children aged 6 months to 15 years during the 4 to 7 months following vaccine availability. This represents a reduction of 26.3% of the number of cases and 12.4% of the hospitalizations that would have been seen in this population absent the vaccine.

As indicated in the eResults and eFigures 5 and 6 in Supplement 1, results for individuals aged 5 to 15 years were not sensitive to the inclusion of any single county, although results for children aged 6 to 59 months were sensitive to the inclusion of Los Angeles (eFigure 7 in Supplement 1). Estimated cases (eTable 4 in Supplement 1) and hospitalizations (eTable 5 in Supplement 1) were consistent when model selection was done using mean absolute error as the loss function for children aged 5 to 15 years. Estimated averted cases in children aged 6 to 59 months were slightly lower using mean absolute error, but hospitalization results were consistent (eResults in Supplement 1). Estimates of cases averted (eTable 6 in Supplement 1) and hospitalizations averted (eTable 7 in Supplement 1) made using the mean absolute error as the loss function for each county or region are available, along with plots of observed and counterfactual case and hospitalization series for all geographic areas (eFigures 9-14 in Supplement 1).

Association Between Averted Cases and Vaccination

County-level vaccination coverage explained 26% of variation of cases averted for children aged 6 to 59 months, 28% for children aged 5 and 11 years, and 12% for adolescents aged 12 to 15 years (Figure 4). On average, every increase of 10 vaccinations per 1000 children corresponded to a reduction of 0.9 (95% CI, 0.3-1.4) cases per 1000 children for individuals aged 6 to 59 months, 3.5 (95% CI, 1.9-5.1) cases per 1000 children for those aged 5 and 11 years, and 2.0 (95% CI, 0.6-3.4) cases per 1000 children for adolescents aged 12 to 15 years. Linear model fits had lower Akaike information criterion and bayesian information criterion values than segmented regression model fits for all age groups. Across all age groups, pediatric vaccination rates in California were generally highest among Bay Area counties (eFigure 8 in Supplement 1), which also ranked highest for averted cases due to vaccination (eResults in Supplement 1).

We provide evidence that Californias pediatric COVID-19 immunization program averted 376 085 (95% PI, 348355-417328) reported cases and 273 (95% PI, 77-605) hospitalizations among children aged 6 months to 15 years during the 4 to 7 months following vaccine availability. This represents a reduction of 26.3% of the number of cases that would have been seen in this population absent the vaccine. Prior work has similarly reported a high impact of widespread administration of mRNA vaccines in adult populations. In California, COVID-19 vaccines were estimated to avert more than 1.5 million cases, 72 000 hospitalizations, and 19 000 deaths statewide during the first 10 months of vaccination (through October 16, 2021).17 In the US, each 10% increase in vaccination coverage among individuals aged 18 years or older at the county level was associated with an 8% reduction in mortality and a 7% reduction in incidence.18 Similarly, a study in Israel estimated that nearly 650 000 cases of COVID-19 were averted in the first 2 months following vaccination introduction,19

Earlier studies have estimated vaccine effectiveness in pediatric populations by comparing incidence rates among vaccinated children with those in unvaccinated children using test-negative designs,20-22 or retrospective23,24 or prospective cohort studies.25 Our counterfactual case series approach, which has been used in other studies to estimate the population-level impact of interventions with a clearly specified rollout time,26,27 enables calculation of vaccine program impact at the population level, without information on individual vaccine status.

The cumulative effect of vaccination at the population level may be meaningful even if individual vaccine effectiveness is low. While influenza vaccine effectiveness was estimated at 29% in 2017-2018,28 it was estimated that widespread vaccination averted more than 3.1 million cases of influenza in the US.29 Nevertheless, overall impact depends on vaccine coverage. We identified positive associations between county-level vaccination coverage and averted cases in each age group, whereby each 10 additional vaccinations per 1000 children corresponded to an average reduction of 0.9 to 3.5 cases per 1000 children. Segmented regression models associating vaccine coverage with averted cases did not identify break points, suggesting that over the range of vaccination coverages examined (0%-85%), we saw neither diminishing returns on increased coverage owing to the acquisition of sufficient population-level immunity nor a threshold below which vaccination has limited public health impact. This is consistent with the persistence of SARS-CoV-2 circulation in populations with high vaccination coverage and resulting value of direct protection.

Results for individuals aged 6 to 59 months differed from those of older age groups in that we found a significant reduction in hospitalizations, but not cases, following vaccination. One explanation for this discrepancy could be that postvaccine evaluation period for children aged 6 to 59 months did not include a surge in COVID-19 cases as it did for the other age groups (Figure 2), potentially making it difficult to detect statistically significant reductions from the counterfactual. However, vaccine effectiveness of early mRNA vaccines was lower against Omicron variants compared with Alpha and Delta variants,30,31 and the Omicron variant dominated during the postvaccine period for children aged 6 months to 11 years (Figure 1). The detection of significant reductions in hospitalization in this age group, but not others, may be due, in part, to the fact that COVID-19 mortality disproportionately affects very young children compared with older children.32 For older age groups, we also estimated reductions in hospitalizations, although the 95% PI spans 0. However, we note that 95% CIs are narrower than PIs and may not have encompassed the null.

This study has limitations. Case data represented individuals who sought testing, which may be differential across unvaccinated and vaccinated groups, geographies, and time. Access to at-home testing likely resulted in further case underascertainment. If individuals were, on average, less likely to seek care for mild illness following vaccination, our analysis could have overestimated the absolute effect of the vaccine on cases averted. Overestimation of the relative effect of the vaccine may have resulted if vaccine recipients were disproportionately represented in the surveillance record both before and after vaccine eligibility compared with never-vaccinated individuals being more connected to care. Data on hospitalizations are less likely to be subjected to biases from differential case ascertainment. We estimated significant reductions in hospitalizations following vaccine introduction compared with counterfactual predictions.

Several considerations could lead to underestimates of the association between vaccination and child long-term health. First, asymptomatic cases are less likely to be reported, yet remain an important outcome, as postCOVID-19 condition symptoms may present after asymptomatic infections.33-35 Second, we were unable to estimate indirect outcomes associated with the vaccine in other age groups or control for social contacts. If children increased social contacts following receipt of the vaccine, as has been shown elsewhere,36 they may be challenged more frequently with SARS-CoV-2. Third, we assessed the outcomes of the vaccine over a short postvaccination period, limiting our ability to examine vaccine responses under waning immunity.

Two important limitations relate to model functional form. First, attributing differences between the observed and the predicted counterfactual cases to the vaccine assumes that the associations between incidence in the age group being modeled and incidence in the age groups selected as model predictors would, absent the vaccine, remain constant over the pre-to-post vaccine periods. This would not occur if one age group developed increased immunity or if different variants had differential age-disease associations. This is especially salient for the 5- to 11-year age group, as the models were primarily trained on data from the period when the Delta variant predominated, yet the Omicron variant, which is less reliant on angiotensin-converting enzyme 2 binding for entry37 and disproportionately influenced children younger than 5 years, prevailed in the evaluation period. Accordingly, the effect of vaccination may have been overestimated for this age group in counties where the incidence in children younger than 5 years was selected as a predictor (eTable 2 in the Supplement).

Second, there is potential for unstable predictions in the evaluation period if the predictive model was faced with values of selected predictors that fell outside the range of data used to fit the model. Our time series with a gap cross-validation approach guards against both of these limitations by prioritizing selection of generalized linear models that do well predicting values in periods that follow the training period, and in periods where the predictors may fall outside the range of what they were during the training period.11-13,38 Moreover, generalized linear models selected using different loss functions resulted in similar model predictions during the postevaluation period, suggesting that results are robust to differences in the nature of the association between incidence in the modeled age group and incidence in the predictor age groups.

In this case series analysis of 3913063 pediatric cases, we provide evidence suggesting that programmatic vaccination against SARS-CoV-2 was associated with significant reductions in COVID-19 incidence among children in California in the 4 to 7 months following vaccine eligibility. At the county level, we found associations of higher vaccine coverage with greater reductions in pediatric cases. Our results support the use of COVID-19 vaccines to reduce COVID-19 incidence and hospitalization in pediatric populations.

Accepted for Publication: February 23, 2024.

Published: April 23, 2024. doi:10.1001/jamanetworkopen.2024.7822

Open Access: This is an open access article distributed under the terms of the CC-BY License. 2024 Head JR et al. JAMA Network Open.

Corresponding Author: Justin V. Remais, PhD, 2121 Berkeley Way, #5302, Berkeley, CA 94720 (jvr@berkeley.edu).

Author Contributions: Dr Head had full access to all of the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis.

Concept and design: Head, Len, Lewnard, Remais.

Acquisition, analysis, or interpretation of data: Head, Collender, Len, White, Sud, Camponuri, Lee, Remais.

Drafting of the manuscript: Head, Remais.

Critical review of the manuscript for important intellectual content: All authors.

Statistical analysis: Head, Collender, Len, Camponuri, Lee.

Obtained funding: Head, Remais.

Administrative, technical, or material support: Collender, Len, White, Sud, Camponuri, Remais.

Supervision: Remais.

Conflict of Interest Disclosures: Dr Len reported having been an employee of the California Department of Public Health (CDPH). No other disclosures were reported.

Funding/Support: This project was supported by a grant from the CDPH through the University of California Health & CDPH COVID Modeling Consortium. Dr Head was supported by the National Institute of Allergy and Infectious Diseases (NIAID) National Institutes of Health (NIH) award K01AI173529. Dr Remais was supported by NIAID NIH award R01AI148336.

Role of the Funder/Sponsor: The funding organizations did not play a role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; and decision to submit the manuscript for publication.

Data Sharing Statement: See Supplement 2.

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COVID-19 Vaccination and Incidence of Pediatric SARS-CoV-2 Infection and Hospitalization - JAMA Network

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JAMA Network Openhas published a new study showing that, from April 1, 2020, to February 27, 2023, in California, an estimated 146,210 COVID-19 cases were averted by vaccination in teens aged 12 to 15 years, representing a 37% reduction.

Researchers also estimated that 230,134 cases were averted in kids aged 5 to 11 years, a 24% reduction.

The study looked at COVID-19 infections in post-vaccination evaluation periods consisting of 141 days (June 10 to October 29, 2021) for adolescents aged 12 to 15 years, 199 days (November 29, 2021 to June 17, 2022) for children aged 5 to 11 years, and 225 days (July 17, 2022, to February 27, 2023) for those aged 6 to 59 months, according to study authors.

From April 2020 to February 2023, California recorded 3,913,063 pediatric COVID-19 cases and 12,740 hospitalizations. During those times, statewide vaccine coverage reached 53.5% among adolescents aged 12 to 15 years, 34.8% among children aged 5 to 11 years, and 7.9% among those aged 6 to 59 months.

The biggest reduction attributed to vaccination occurred with older kids, and there was no evidence of reductions in COVID-19 cases statewide among children aged 6 to 59 months (estimated averted cases, 259; 95% prediction interval, 1,938 to 1,019).

Though there was no evidence in case reduction in the youngest kids, vaccination prevented an estimated 168 hospitalizations among children aged 6 to 59 months during the 225-day evaluation period.

These results support the use of COVID-19 vaccines to reduce COVID-19 incidence and hospitalization in pediatric populations.

"These results support the use of COVID-19 vaccines to reduce COVID-19 incidence and hospitalization in pediatric populations," the authors concluded.

Continued here:

Teen vaccination cut COVID-19 cases by 37% in California, new data show - University of Minnesota Twin Cities

Summary

What is already known about this topic?

In September 2023, the Advisory Committee on Immunization Practices (ACIP) recommended updated (20232024 Formula) COVID-19 vaccination for all persons aged 6 months.

What is added by this report?

On February 28, 2024, ACIP recommended that all persons aged 65 years receive 1 additional dose of any updated (20232024 Formula) COVID-19 vaccine (i.e., Moderna, Novavax, or Pfizer-BioNTech).

What are the implications for public health practice?

Adults aged 65 years should receive an additional dose of the updated (20232024 Formula) COVID-19 vaccine to enhance their immunity and decrease the risk for severe COVID-19associated illness.

COVID-19 remains an important public health threat, despite overall decreases in COVID-19related severe disease since the start of the COVID-19 pandemic. COVID-19associated hospitalization rates remain higher among adults aged 65 years relative to rates in younger adults, adolescents, and children; during October 2023January 2024, 67% of all COVID-19associated hospitalizations were among persons aged 65 years. On September 12, 2023, CDCs Advisory Committee on Immunization Practices (ACIP) recommended updated (20232024 Formula) COVID-19 vaccination with a monovalent XBB.1.5-derived vaccine for all persons aged 6 months to protect against severe COVID-19associated illness and death. Because SARS-CoV-2 continues to circulate throughout the year, and because of the increased risk for COVID-19related severe illness in persons aged 65 years, the protection afforded by updated vaccines against JN.1 and other currently circulating variants, and the expected waning of vaccine-conferred protection against disease, on February 28, 2024, ACIP recommended all persons aged 65 years receive 1 additional dose of the updated (20232024 Formula) COVID-19 vaccine. Implementation of these recommendations is expected to enhance immunity that might have waned and decrease the risk for severe COVID-19associated outcomes, including death, among persons aged 65 years.

Since June 2020, CDCs Advisory Committee on Immunization Practices (ACIP) has convened 39 public meetings to review data and consider recommendations related to the use of COVID-19 vaccines (1). On September 12, 2023, ACIP recommended that all persons aged 6 months receive updated (20232024 Formula) monovalent, XBB.1.5 component (updated) COVID-19 vaccination to protect against severe COVID-19associated illness and death (2).

As of February 3, 2024, approximately 6.7 million COVID-19associated hospitalizations and 1.1 million COVID-19associated deaths had occurred in the United States (3). Although the overall risk for COVID-19associated hospitalization and death has decreased, severe illness related to COVID-19 continues to be a public health problem, especially among older adults. COVID-19associated hospitalization rates remain higher among adults aged 65 years relative to rates among younger adults, adolescents, and children. During October 2023January 2024, 67% of all COVID-19associated hospitalizations were among persons aged 65 years (4). Further, COVID-19 death rates during January 1, 2023January 31, 2024, were highest among adults aged 75 years, followed by adults aged 6574 years (5,6). Whereas approximately 98%99% of the U.S. population has measurable antibody titers against SARS-CoV-2 from infection, vaccination, or both (hybrid immunity), adults aged 65 years are less likely to have immunity resulting from infection (including immunity from infection only or hybrid immunity), compared with adults aged 3049 years and 5064 years (7). In addition, immunosenescence, the age-related decline in the functioning of the immune system, results in a less complete immune response to novel antigens and a reduced ability to develop robust immunity after infections or vaccination (8). The pool of naive T-cells diminishes with age, and this insufficient naive T-cell pool affects the ability to generate neutralizing antibody responses and cytotoxic T-cells in response to SARS-CoV-2 (9).

Thus, adults aged 65 years are more likely than are younger adults, adolescents, and children to rely upon vaccination to increase immunity that might have waned and might need more frequent vaccine doses to maintain protection. Coverage with the updated COVID-19 vaccine among adults aged 65 years was 42% as of February 3, 2024 (10,11). Adults in this age group are more concerned about COVID-19 disease and had higher confidence in COVID-19 vaccine safety and vaccine importance than did younger adults (5). A nationally representative survey conducted during November 2023January 2024 indicated that 68.4% of adults aged 65 years who had received an updated COVID-19 vaccine dose definitely would get another updated vaccine if it were recommended, 27.2% probably would or are unsure if they would get another updated vaccine, and 4.4% said they probably or definitely would not. COVID-19 vaccines are currently on the commercial market, but access-related barriers and disparities in vaccine coverage remain (5); in the absence of any recommendations for an additional dose, access to vaccine would be limited among persons unable to pay out of pocket for the vaccine.*

On February 28, 2024, ACIP voted to recommend that all persons aged 65 years receive 1 additional dose of any updated COVID-19 vaccine (i.e., Moderna, Novavax, or Pfizer-BioNTech). This recommendation was based on continuing SARS-CoV-2 circulation throughout the year, increased risk for severe illness attributable to COVID-19 in adults aged 65 years, protection provided by the updated vaccines against JN.1 and other currently circulating variants, the expected waning of SARS-CoV-2 immunity, and additional implementation considerations, including facilitating clear communication and equitable access to vaccine (5).

In 2018, ACIP adopted the Evidence to Recommendations framework to guide the development of vaccine recommendations. Since November 2023, the ACIP COVID-19 work group met seven times to discuss the current policy question, i.e., whether adults aged 65 years should receive an additional dose of updated COVID-19 vaccine. Work group membership included ACIP voting members, representatives of ACIP ex officio and liaison organizations, and scientific consultants with expertise in public health, immunology, medical specialties, and immunization safety and effectiveness. Work group discussion topics included COVID-19 disease surveillance and epidemiology; COVID-19 vaccination coverage; and the safety, effectiveness, feasibility of implementation, and cost effectiveness of COVID-19 vaccines. This report summarizes the ACIP recommendation for an additional dose of the updated COVID-19 vaccine for persons aged 65 years and the rationale, including evidence reviewed by the work group and presented to ACIP (https://www.cdc.gov/vaccines/acip/recs/grade/covid-19-additional-dose-adults-etr.html).

No clinical trial immunogenicity data on an additional dose of the updated COVID-19 vaccines exist; however, the initial dose elicits a robust neutralizing antibody response and provides protection against JN.1 and other circulating variants (12,13). Early vaccine effectiveness (VE) estimates demonstrate that updated COVID-19 vaccination provided increased protection against symptomatic SARS-CoV-2 infection and COVID-19associated emergency department and urgent care visits and hospitalization, compared with receipt of no updated vaccine dose (12,14). Although these early VE estimates show no substantial waning, based on data on effectiveness of original and bivalent COVID-19 vaccines, waning of vaccine-conferred immunity is expected. Effectiveness of an additional dose in older adults has been demonstrated for previously recommended additional original COVID-19 vaccine doses (15). Among adults aged 50 years who were eligible to receive a second original monovalent mRNA COVID-19 vaccine booster dose, VE against COVID-19associated emergency department and urgent care encounters during the SARS-CoV-2 Omicron BA.2/BA.2.12.1 period 120 days after the third dose was 32% but increased to 66% 7 days after the fourth dose. VE against COVID-19associated hospitalization 120 days after the third dose was 55% but increased to 80% 7 days after the fourth dose (15). In addition, in a large cohort of nursing home residents during circulation of SARS-CoV-2 Omicron subvariants, receipt of a second original monovalent mRNA COVID-19 booster dose 60 days earlier was 74% effective against severe COVID-19related outcomes (including hospitalization or death) and 90% effective against death, compared with receipt of a single booster dose (16).

COVID-19 vaccines have a favorable safety profile as demonstrated by robust safety surveillance during 3 years of COVID-19 vaccine use (17). Anaphylactic reactions have rarely been reported after receipt of COVID-19 vaccines (18). A rare risk for myocarditis and pericarditis exists, predominately in males aged 1239 years (19). No new safety concerns have been identified for the updated COVID-19 vaccine (5). Among adults aged 65 years, overall reactogenicity after COVID-19 vaccination is less frequent and less severe than among adolescents and younger adults (20). A statistical signal for ischemic stroke after Pfizer-BioNTech bivalent mRNA COVID-19 vaccine was detected in the CDC Vaccine Safety Datalink among persons aged 65 years, and information about this detection has been presented at previous ACIP meetings. Ongoing efforts to evaluate the signal have not identified any clear and consistent evidence of a safety concern for ischemic stroke with bivalent mRNA COVID-19 vaccines either when given alone or when given simultaneously with influenza vaccines (21). A recent VE study indicated that the bivalent COVID-19 vaccine was 47% effective in preventing COVID-19 related thromboembolic events (ischemic stroke, myocardial infarction, and deep vein thrombosis) among persons aged 65 years (22).

ACIP considered whether an additional dose of updated COVID-19 vaccine in persons aged 65 years is a reasonable and efficient allocation of resources. The societal incremental cost-effectiveness ratio (ICER) for an additional dose of COVID-19 vaccine in persons aged 65 years was $255,122 per quality-adjusted life year saved for the base case estimate. ICER values were sensitive to probability of hospitalizations, costs, and seasonality assumptions. Estimates of ICER values that approximate cost effectiveness for those with higher risk for COVID-19associated hospitalization, such as persons with underlying conditions or those aged 75 years, were more favorable (23).

On February 28, 2024, ACIP recommended that all persons aged 65 years receive 1 additional dose of any updated COVID-19 vaccine (i.e., Moderna, Novavax, or Pfizer-BioNTech). This additional dose should be administered 4 months after the previous dose of updated COVID-19 vaccine. For initial vaccination with Novavax COVID-19 vaccine, the 2-dose series should be completed before administration of the additional dose. Because Novavax COVID-19 vaccine is currently authorized under Emergency Use Authorization, the recommendation for the updated Novavax COVID-19 vaccine is an interim recommendation.

Persons aged 65 years who are moderately or severely immunocompromised, have completed an initial series, and have received 1 updated COVID-19 vaccine dose should receive 1 additional updated COVID-19 vaccine dose 2 months after the last dose of updated vaccine. Further additional doses may be administered, guided by the clinical judgment of a health care provider and personal preference and circumstances. Any further additional doses should be administered 2 months after the last COVID-19 vaccine dose. Additional clinical considerations, including detailed schedules and tables by age for all age groups and vaccination history for those who are or are not moderately or severely immunocompromised, are available at https://www.cdc.gov/vaccines/covid-19/clinical-considerations/covid-19-vaccines-us.html.

Adverse events after vaccination should be reported to the Vaccine Adverse Event Reporting System (VAERS). For licensed COVID-19 vaccines administered to persons aged 12 years, reporting is encouraged for any clinically significant adverse event even when whether the vaccine caused the event is uncertain, as well as for vaccination errors. For COVID-19 vaccines given under Emergency Use Authorization, vaccination providers are required to report certain adverse events to VAERS. Additional information is available at https://vaers.hhs.gov or by telephone at 1-800-822-7967.

Karen Broder, Mary Chamberland, Demetre Daskalakis, Susan Goldstein, Aron Hall, Elisha Hall, Fiona Havers, Andrew Leidner, Pedro Moro, Sara Oliver, Ismael Ortega-Sanchez, Kadam Patel, Manisha Patel, Amanda Payne, Huong Pham, Jamison Pike, Lauren Roper, Sierra Scarbrough, Tom Shimabukuro, Benjamin Silk, John Su, Evelyn Twentyman, Eric Weintraub, David Wentworth, Melinda Wharton, Michael Whitaker, JoEllen Wolicki, Fangjun Zhou, CDC. Voting members of the Advisory Committee on Immunization Practices (in addition to listed authors): Wilbur Chen, University of Maryland School of Medicine; Sybil Cineas, Warren Alpert Medical School of Brown University; Camille Kotton, Harvard Medical School; James Loehr, Cayuga Family Medicine; Sarah Long, Drexel University College of Medicine. Members of the Advisory Committee on Immunization Practices COVID-19 Vaccines Work Group: Beth P. Bell, University of Washington; Edward Belongia, Center for Clinical Epidemiology & Population Health, Marshfield Clinic Research Institute; Henry Bernstein, Zucker School of Medicine at Hofstra/Northwell Cohen Childrens Medical Center; Uzo Chukwuma, Indian Health Service; Paul Cieslak, Christine Hahn, Council of State and Territorial Epidemiologists; Richard Dang, American Pharmacists Association; Jeffrey Duchin, Infectious Diseases Society of America; Kathy Edwards, Vanderbilt University Medical Center; Sandra Fryhofer, American Medical Association; Jason M. Goldman, American College of Physicians; Robert Hopkins, University of Arkansas for Medical Sciences; Michael Ison, Chris Roberts, National Institutes of Health; Lisa A. Jackson, Jennifer C. Nelson, Kaiser Permanente Washington Health Research Institute; Denise Jamieson, American College of Obstetricians and Gynecologists; Jeffery Kelman, Centers for Medicare & Medicaid Services; Kathy Kinlaw, Center for Ethics, Emory University; Alan Lam, U.S. Department of Defense; Grace M. Lee, Stanford University School of Medicine; Lucia Lee, Anuga Rastogi, Adam Spanier, Rachel Zhang, Food and Drug Administration; Valerie Marshall, Office of the Assistant Secretary for Health, U.S. Department of Health and Human Services; Dayna Bowen Matthew, George Washington University Law School; Preeti Mehrotra, Society for Healthcare Epidemiology of America; Kathleen Neuzil, Center for Vaccine Development and Global Health, University of Maryland School of Medicine; Sean OLeary, American Academy of Pediatrics; Christine Oshansky, Biomedical Advanced Research and Development Authority; Stanley Perlman, Department of Microbiology and Immunology, University of Iowa; Marcus Plescia, Association of State and Territorial Health Officials; Rob Schechter, National Foundation for Infectious Diseases; Kenneth Schmader, American Geriatrics Society; Peter Szilagyi, University of California, Los Angeles; H. Keipp Talbot, Vanderbilt University School of Medicine; Jonathan Temte, American Academy of Family Physicians; Matthew Tunis, National Advisory Committee on Immunization Secretariat, Public Health Agency of Canada; Matt Zahn, National Association of County and City Health Officials; Nicola P. Klein, Kaiser Permanente Northern California; Cara B. Janusz, Lisa Prosser, Angela Rose, University of Michigan.

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Use of an Additional Updated 20232024 COVID-19 Vaccine Dose for Adults Aged 65 Years: Recommendations of ... - CDC

The Metropolitan Transportation Authority has fired one Metro-North Railroad employee and suspended 11 Long Island Rail Road workers for submittingfake COVID-19 vaccination cards, which were provided by an Amityville nurse practitioner convicted ofa $1.5 million scheme to sell fraudulent cards, MTA officials said Wednesday.

The dozen employees, whom the agency did not identify, were disciplined afteran investigation by the MTA inspector general, who reviewed statements by the employees as well as financial information, MTA time and payroll records, and COVID-19 testing records, according to an agency news release.

"The COVID-19 vaccination requirement was implemented to protect MTA workers and the riding public at a time of great uncertainty, but these employees decided the rules don't apply to them," said MTA Inspector General Daniel Cort in the release. "MTA employees who submit fraudulent documents will be caught and face consequences."

The MTA implemented the COVID-19 Vaccine and Test program on Oct. 4, 2021, requiring the vaccination and weekly testing of workers. The investigation began in 2022 after the arrest of Julie DeVuono, a nurse practitioner and owner of Wild Child Pediatric Healthcare in Amityville. She pleaded guilty in September to charges of forging vaccine cards, money laundering and offering a false instrument for filing.

Her sentencing is set for June 11, according to the Suffolk County district attorney's office.

Investigators had obtained a list from the state Health Department of MTA employees who submitted COVID-19 cards claiming they were vaccinated by DeVuono, officials said. The 11 LIRR employees signed agreements admitting to various administrative charges, including submitting false documents and not complying with MTA COVID-19 policies, according to the release.

The MTA ended the vaccine and testing program June 7, 2022.

The Metro-North employee was terminated and the 11 LIRR workers were removed from service in January, with those employees agreeingto serve unpaid suspensions that ranged from 60 to 120 days.

Four of the LIRR workers had admitted not getting vaccinated and paying DeVuono for fake vaccination cards, MTA officials said. Six of the LIRR employees and the terminated Metro-North employee claimed they got vaccinated and paid DeVuono for a homeopathic "detox treatment." The inspector general's office found their accounts "illogical and not credible." The other LIRR worker claimed he got vaccinated at DeVuono's office and did not pay anything. That account, which was contradicted by financial records, was found not to be credible, officials said.

DeVuono admitted that between June 15, 2021, and Jan. 27, 2022, she chargedadult customers $220 for a false vaccination entry on their COVID-19 cards and another $220 to enter the false information into the New York State Immunization Information System, a statewide vaccination database.

DeVuono agreed to forfeit criminal proceeds totaling $1.2 million, officials said. She surrendered her professional license as a nurse practitionerand registered professional nurse, and agreed to shut down her pediatric office, officials said.

Craig Schneider is a Long Island native and Stony Brook University alumnus. He joined Newsday as a general assignment reporter in January 2018 after 20 years at the Atlanta Journal-Constitution.

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MTA suspends 11 Long Island Rail Road workers for submitting fake COVID-19 vaccination cards issued by Julie DeVuono - Newsday

People with a history of uveitis were more likely to experience recurrences of the potentially dangerous eye inflammation after vaccination against COVID-19, a retrospective population-based cohort study from South Korea found.

Of 473,934 vaccinated individuals with a prior case of uveitis, 16.8% developed it again within a year of vaccination, with an overall 21% elevated risk compared with the pre-vaccination period, Seong Joon Ahn, MD, PhD, of Hanyang University Seoul Hospital in South Korea, and colleagues reported in JAMA Ophthalmology.

The risk was especially high in the initial 30 days after the first shot as compared with the pre-vaccination period (HR 1.64, 95% CI 1.55-1.73) and in patients who received the Johnson & Johnson Ad.26.COV2.S vaccine, which is no longer available in the U.S. (HR 2.07, 95% CI 1.40-3.07).

"These findings suggest that there was an elevated risk of uveitis following COVID-19 vaccination, with the vaccine type and period mediating this risk," the authors wrote. "For individuals with a history of uveitis, clinicians should consider the potential risk of uveitis recurrence in vaccination strategies and clinical monitoring."

Although rare, uveitis remains a leading cause of legal blindness in the U.S.

Prior findings on a link between uveitis and COVID-19 vaccines have been mixed. A 2023 analysis of the CDC's Vaccine Adverse Event Reporting System concluded it's a "low safety concern," with estimated incident rates per million persons of 0.57 with Pfizer's BNT162b2 mRNA vaccine (Comirnaty) vaccine, 0.44 with Moderna's mRNA-1273 (Spikevax), and 0.35 with the Johnson & Johnson vaccine. However, a similar 2024 study from British regulators found no links between the vaccines and uveitis in the general population.

The new study aimed to determine if uveitis risk is higher in those with a history of the condition and whether the risk levels differ by type of vaccine or timing of doses.

Within the 3 months after vaccination, 8.6% of patients had anterior uveitis, and 1.6% nonanterior uveitis. The total rates grew to 12.5% at 6 months and 16.8% at 12 months. The ratio of anterior to nonanterior forms remained about the same at 4.4 and 4.8, respectively.

Overall, the post-vaccination rate was higher than pre-vaccination (HR 1.21, 95% CI 1.19-1.24), although it decreased after the initial 30 days after the first vaccine dose. The researchers speculated that an "increased immune response following the initial dose might activate inflammatory pathways, resulting in conditions like uveitis, particularly in individuals prone to autoimmune reactions or with a uveitis history." Later, they wrote, the declining risk "may stem from the immune system adapting to the vaccine antigen, resulting in a more controlled immune response that mitigates inflammatory side effects."

In a commentary accompanying the paper, Anika Kumar, BA, and Nisha Acharya, MD, MS, of the University of California San Francisco, noted that it's important to consider the study findings in light of the risk of not getting vaccinated against COVID-19. On the ocular front alone, conjunctivitis is a well-known symptom in COVID-19, which is also linked to a long list of other ocular conditions.

For their study, the researchers tracked all 473,934 patients in South Korea who were vaccinated, had a history of uveitis, and did not develop COVID-19 during the study period using national healthcare databases. Among these patients, 51.3% were female, the mean age was 59 years, 74.3% had rheumatic diseases, and 45.7% had hypertension. Nearly 40% had four vaccine doses.

By type of vaccine, 36.3% of the individuals received the AstraZeneca ChAdOx1 shot, and 9.3% of those developed uveitis in the 30 days after the first dose. Those numbers were 51.2% and 9.9%, respectively, for Pfizer's vaccine; 10.3% and 10.4% for Moderna's shot; and 2% and 11.7% for the single-dose Johnson & Johnson vaccine.

The uveitis hazard ratios for the 30 days after the first dose versus the pre-vaccination period were:

The authors noted limitations such as a reliance on diagnostic codes and lack of information about uveitis severity or use of anti-inflammatory drugs that could decrease the risk of uveitis. The commentary authors also noted that the approach used "did not account for the healthy vaccinee bias, which refers to how individuals in better health are more likely to receive vaccinations."

Randy Dotinga is a freelance medical and science journalist based in San Diego.

Disclosures

The National Research Foundation of Korea, Ministry of Science and Information and Communication Technology, and Hanyang University funded the study.

The study authors reported no disclosures.

Acharya disclosed receiving advisory fees from Roche and nonfinancial support from AbbVie.

Primary Source

JAMA Ophthalmology

Source Reference: Kim J, et al "COVID-19 vaccineassociated uveitis in patients with a history of uveitis" JAMA Ophthalmol 2024; DOI: 10.1001/jamaophthalmol.2024.0973.

Secondary Source

JAMA Ophthalmology

Source Reference: Kumar A, Acharya NR "Real-world vaccine research and clinical practice" JAMA Ophthalmol 2024; DOI: 10.1001/jamaophthalmol.2024.1049.

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Uveitis History Linked to Recurrence After COVID Vaccination - Medpage Today

A 7 year-old child holds a sticker she received after getting the Pfizer-BioNTech Covid-19 vaccine ... [+] at the Child Health Associates office in Novi, Michigan on November 3, 2021. - An expert panel unanimously recommended Pfizer-BioNTech's Covid vaccine for five- to 11-year-olds on November 2, the penultimate step in the process that will allow injections in young children to begin this week in the United States. The Centers for Disease Control and Prevention (CDC), the top US public health agency, was expected to endorse that recommendation later in the day. (Photo by JEFF KOWALSKY / AFP) (Photo by JEFF KOWALSKY/AFP via Getty Images)

A new California-based study including the data of 3.9 million pediatric Covid-19 cases found that thanks to the states Covid-19 immunization program, there was a reduction of 26.3% in the number of cases among children aged 6 months to 15 years.

More specifically, the researchers estimated that there was a 37.1% reduction in Covid-19 cases among adolescents aged 12 to 15 years and a 23.7% reduction among children aged 5 to 11 years. Whereas Covid-19 vaccinations were associated with 24.4% fewer hospitalizations among children aged 6 months to 4.9 years.

Despite low vaccination coverage, pediatric COVID-19 immunization in California averted 376,085 reported cases and 273 hospitalizations among children aged 6 months to 15 years over approximately 4 to 7 months following vaccination availability, the researchers wrote in their study that was published in JAMA Network Open on April 23, 2024.

COVID-19 vaccines are safe for children. However, concerns over vaccine-related adverse events, lower vaccine effectiveness against illness in children, and perceptions of a milder disease course in children have resulted in high rates of parental vaccine hesitancy and resistance to pediatric vaccine mandates, the authors added. While California has among the highest rates of vaccination in the US, pediatric vaccination coverage lags that of adults substantially, with only 8.2% of children younger than 5 years and 37.8% of children aged 5 to 11 years fully vaccinated as of May 2023. Severe manifestations of COVID-19 are rare among children, but can occur.

Lead author Justin V. Remais of the University of California, Berkeley, and colleagues, analyzed data on 3,913,063 pediatric Covid-19 cases and 12,740 hospitalizations in California. They then studied how pediatric Covid-19 vaccinations were introduced to children belonging to different age groups and calculated statewide outcomes that could be associated with vaccinations preventing or reducing new pediatric cases and Covid-19-related hospitalizations between April 2020 and February 2023. The team obtained data from the California COVID-19 Reporting System.

Of the 3.9 million pediatric Covid-19 cases reported in California among children younger than 18 years, 1.2% cases were among infants younger than 6 months, 13.2% in children aged 6 to 4.9 years, and 38.6% in children aged 12 to 15 years. The highest percentage of cases (40.7%) was in children aged 5 to 11 years. Among pediatric Covid-19 hospitalized cases, adolescents aged 12 to 15 were the most hospitalized group (30.8%).

"On average, every increase of 10 vaccinations per 1000 children corresponded to a reduction of 0.9 cases per 1000 children for individuals aged 6 to 59 months, 3.5 cases per 1000 children for those aged 5 and 11 years, and 2 cases per 1000 children for adolescents aged 12 to 15 years," the researchers explained.

"Prior work has similarly reported a high impact of widespread administration of mRNA vaccines in adult populations. In California, COVID-19 vaccines were estimated to avert more than 1.5 million cases, 72,000 hospitalizations, and 19,000 deaths statewide during the first 10 months of vaccination (through October 16, 2021). In the US, each 10% increase in vaccination coverage among individuals aged 18 years or older at the county level was associated with an 8% reduction in mortality and a 7% reduction in incidence," the researchers added.

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Covid-19 Vaccination Associated With Reductions In Pediatric Cases And Hospitalizations - Forbes