The community nurse's role on the promotion of papillomavirus vaccination among young students: A study protocol

Vaccination is the principal strategy for primary prevention of infection by Human Papilloma Virus (HPV), which causes different pathological conditions, up to cancer, in both males and females. However, to date, knowledge among adolescents and their parents about the HPV vaccine is still low. The aim of this quasi-experimental, multicenter study is to assess the effectiveness of a digital educational intervention, conducted by a multidisciplinary health-care team including a Community Nurse, to increase adolescents' HPV vaccination uptake, their knowledge, self-efficacy, feelings and involvement in HPV vaccine decision-making, and parents' vaccination hesitancy. The study will be carried out among a population of students (and their parents), aged between 11 and 13, at secondary schools in Italy. Validated questionnaires will be administered to both students and parents at baseline (T0) and 3 months after a digital educational intervention (T1). The findings may be useful in evaluating and deepening a methodology for designing and implementing educational interventions, embedded in the school setting, that could promote the achievement of outcomes within the broader process of youth's health promotion.

The impact of COVID-19 vaccine spring boosters on COVID-19 hospital admissions in England 2022/23

BACKGROUND

In the spring of 2022 and 2023 COVID-19 vaccine boosters were recommended for those aged ≥75 years in England as well as those in an immunosuppression risk group. The aim was to reduce severe COVID-19 disease in these groups.

METHODS

The large difference in coverage between those above and below age 75 years was the basis for applying an age-discontinuity approach for measuring the impact of vaccination on COVID-19 hospitalisations in both spring 2022 and 2023. Hospitalisations in individuals positive by PCR for COVID-19 were obtained from the national secondary user service hospital dataset. The ratio of hospital counts by each year of age in 8-week periods after compared to before the roll out was modelled using negative binomial regression to estimate the discontinuity at age 75 years.

RESULTS

A clear discontinuity was seen at age 75 years of 17.0% (95% CI: 6.1%-26.6%) in 2022 and 18.0% (3.3%-30.4%) in 2023. If applied to those aged ≥75 years this translates to 1302 and 418 averted hospitalisations in the 8-week period in 2022 and 2023, respectively.

CONCLUSIONS

This study shows a clear impact of vaccination on preventing COVID-19 hospitalisations and compliments other epidemiological methods assessing the impact of COVID-19 vaccines.

PLAIN LANGUAGE SUMMARY

One way to see if the booster vaccines doses given to protect against COVID-19 disease are working is to compare hospital admissions in groups of people who were and were not eligible for the dose. In England the spring booster doses were recommended for those aged 75 years and above. We could therefore compare hospitalisations in those above this age to those just below (aged 65-74) and see if there is a step change in rates from age 74 to 75 in the time after the vaccine was given. The results showed hospitalisations were about 18% lower in the group that were eligible, which is evidence that the vaccine is protecting against severe COVID-19.

Quasi-experimental methods for pharmacoepidemiology: difference-in-differences and synthetic control methods with case studies for vaccine evaluation

Difference-in-differences and synthetic control methods have become common study designs for evaluating the effects of changes in policies, including health policies. They also have potential for providing real-world effectiveness and safety evidence in pharmacoepidemiology. To effectively add to the toolkit of the field, however, designs-including both their benefits and drawbacks-must be well understood. Quasi-experimental designs provide an opportunity to estimate the average treatment effect on the treated without requiring the measurement of all possible confounding factors, and to assess population-level effects. This requires, however, other key assumptions, including the parallel trends or stable weighting assumptions, a lack of other concurrent events that could alter time trends, and an absence of contamination between exposed and unexposed units. The targeted estimands are also highly specific to the settings of the study, and combining across units or time periods can be challenging. Case studies are presented for 3 vaccine evaluation studies, showcasing some of these challenges and opportunities in a specific field of pharmacoepidemiology. These methods provide feasible and valuable sources of evidence in various pharmacoepidemiologic settings and can be improved through research to identify and weigh the advantages and disadvantages in those settings. This article is part of a Special Collection on Pharmacoepidemiology.

The full value of immunisation against respiratory syncytial virus for infants younger than 1 year: effects beyond prevention of acute respiratory illness

Respiratory syncytial virus (RSV) is a leading cause of severe respiratory illness and death among children worldwide, particularly in children younger than 6 months and in low-income and middle-income countries. Feasible and cost-effective interventions to prevent RSV disease are not yet widely available, although two new products aimed at preventing RSV disease-long-acting monoclonal antibodies and maternal vaccines-have been licensed within the past 2 years. The primary target of these products is reduction of the substantial burden of RSV-associated acute lower respiratory tract infections (LRTI) in infants younger than 1 year. However, other important public health benefits might also accrue with the prevention of RSV-associated LRTI during the first year of life. Mounting evidence shows that preventing RSV-associated LRTI in infants younger than 1 year could prevent secondary pneumonia caused by other pathogens, reduce recurrent hospitalisations due to other respiratory diseases in later childhood, decrease all-cause infant mortality, ameliorate the burden of respiratory diseases on health-care systems, reduce inappropriate antibiotic use, and possibly improve lung health beyond infancy. We herein review current evidence and suggest approaches to better assess the magnitude of these potential secondary effects of RSV prevention, which, if proven substantial, are likely to be relevant to policy makers in many countries as they consider the use of these new products.

The augmented synthetic control method in public health and biomedical research

Estimating treatment (or policy or intervention) effects on a single individual or unit has become increasingly important in health and biomedical sciences. One method to estimate these effects is the synthetic control method, which constructs a synthetic control, a weighted average of control units that best matches the treated unit's pre-treatment outcomes and other relevant covariates. The intervention's impact is then estimated by comparing the post-intervention outcomes of the treated unit and its synthetic control, which serves as a proxy for the counterfactual outcome had the treated unit not experienced the intervention. The augmented synthetic control method, a recent adaptation of the synthetic control method, relaxes some of the synthetic control method's assumptions for broader applicability. While synthetic controls have been used in a variety of fields, their use in public health and biomedical research is more recent, and newer methods such as the augmented synthetic control method are underutilized. This paper briefly describes the synthetic control method and its application, explains the augmented synthetic control method and its differences from the synthetic control method, and estimates the effects of an antimalarial initiative in Mozambique using both the synthetic control method and the augmented synthetic control method to highlight the advantages of using the augmented synthetic control method to analyze the impact of interventions implemented in a single region.

Estimating the Effectiveness of First Dose of COVID-19 Vaccine Against Mortality in England: A Quasi-Experimental Study

Estimating real-world vaccine effectiveness is vital to assessing the coronavirus disease 2019 (COVID-19) vaccination program and informing the ongoing policy response. However, estimating vaccine effectiveness using observational data is inherently challenging because of the nonrandomized design and potential for unmeasured confounding. We used a regression discontinuity design to estimate vaccine effectiveness against COVID-19 mortality in England using the fact that people aged 80 years or older were prioritized for the vaccine rollout. The prioritization led to a large discrepancy in vaccination rates among people aged 80-84 years compared with those aged 75-79 at the beginning of the vaccination campaign. We found a corresponding difference in COVID-19 mortality but not in non-COVID-19 mortality, suggesting that our approach appropriately addressed the issue of unmeasured confounding factors. Our results suggest that the first vaccine dose reduced the risk of COVID-19 death by 52.6% (95% confidence limits: 15.7, 73.4) in those aged 80 years, supporting existing evidence that a first dose of a COVID-19 vaccine had a strong protective effect against COVID-19 mortality in older adults. The regression discontinuity model's estimate of vaccine effectiveness is only slightly lower than those of previously published studies using different methods, suggesting that these estimates are unlikely to be substantially affected by unmeasured confounding factors.

The effectiveness of influenza vaccine among elderly Chinese: A regression discontinuity design based on Yinzhou regional health information platform

In China, a free influenza vaccination policy is being implemented among individuals aged 70 years and over in Zhejiang province during the COVID-19 pandemic. The objective was to assess the effectiveness of influenza vaccine in reducing hospitalization and mortality in the elderly. We used data from the Regional Health Information Platform in Yinzhou located in Zhejiang province and applied a regression discontinuity design to estimate the intention-to-treat effect on admission and mortality rates by month of age in the population who was near the age of 70 years threshold. At age 70 years, the influenza vaccination rate increased by 29.1% (95% CI, 28.2% to 29.9%) compared to those under 70 in the study population. When turning age 70 years, the potential effectiveness of receiving influenza vaccine was 8.2% (95% CI, -36.8% to 51.3%) for total hospitalization and the evaluation of vaccine effectiveness was 13.1% (95% CI, -34.2 to 61.8) for the all-cause mortality. An increase in the influenza vaccination rate was associated with a weak decline in most outcomes, but no significance was found for all outcomes. Influenza vaccination had a limited effect on hospital admission and mortality for the free influenza vaccination program that can be related to the low vaccination rate among the Chinese elderly. Supplementation strategies and future studies may be needed to expand immunization coverage and validate this finding, and further provide a reference for other cities to promote the free influenza vaccination policy in China, especially under circumstances of the COVID-19 pandemic.

Reduced COVID-19 hospitalizations among New York City residents following age-based SARS-CoV-2 vaccine eligibility: Evidence from a regression discontinuity design

BACKGROUND

In clinical trials, several SARS-CoV-2 vaccines were shown to reduce risk of severe COVID-19 illness. Local, population-level, real-world evidence of vaccine effectiveness is accumulating. We assessed vaccine effectiveness for community-dwelling New York City (NYC) residents using a quasi-experimental, regression discontinuity design, leveraging a period (January 12-March 9, 2021) when ≥ 65-year-olds were vaccine-eligible but younger persons, excluding essential workers, were not.

METHODS

We constructed segmented, negative binomial regression models of age-specific COVID-19 hospitalization rates among 45-84-year-old NYC residents during a post-vaccination program implementation period (February 21-April 17, 2021), with a discontinuity at age 65 years. The relationship between age and hospitalization rates in an unvaccinated population was incorporated using a pre-implementation period (December 20, 2020-February 13, 2021). We calculated the rate ratio (RR) and 95% confidence interval (CI) for the interaction between implementation period (pre or post) and age-based eligibility (45-64 or 65-84 years). Analyses were stratified by race/ethnicity and borough of residence. Similar analyses were conducted for COVID-19 deaths.

RESULTS

Hospitalization rates among 65-84-year-olds decreased from pre- to post-implementation periods (RR 0.85, 95% CI: 0.74-0.97), controlling for trends among 45-64-year-olds. Accordingly, an estimated 721 (95% CI: 126-1,241) hospitalizations were averted. Residents just above the eligibility threshold (65-66-year-olds) had lower hospitalization rates than those below (63-64-year-olds). Racial/ethnic groups and boroughs with higher vaccine coverage generally experienced greater reductions in RR point estimates. Uncertainty was greater for the decrease in COVID-19 death rates (RR 0.85, 95% CI: 0.66-1.10).

CONCLUSION

The vaccination program in NYC reduced COVID-19 hospitalizations among the initially age-eligible ≥ 65-year-old population by approximately 15% in the first eight weeks. The real-world evidence of vaccine effectiveness makes it more imperative to improve vaccine access and uptake to reduce inequities in COVID-19 outcomes.

Coverage for pertussis vaccination during pregnancy with 4 models of vaccine delivery: a quasiexperimental, multicentre observational study

BACKGROUND

Vaccination of pregnant people with a vaccine containing acellular pertussis (tetanus-diphtheria-acellular pertussis [Tdap]) has been recommended in Canada since 2018, and the evaluation of delivery models for efficient maternal Tdap administration is a priority for the Quebec Ministry of Health. We implemented 3 vaccine delivery models, in addition to the existing standard of practice model, and compared the vaccine coverage achieved by the 4 models in Quebec.

METHODS

In this quasiexperimental, multicentre observational study, we recruited pregnant people at less than 21 weeks' gestation in 4 Quebec regions from April to October 2019. We compared 4 vaccine delivery models: local community service centres (centre local de services communautaires [CLSCs], baseline), family medicine groups (FMGs), obstetrics clinic and the oral glucose challenge test (OGCT). In addition to the CLSCs, 3 FMGs, 1 obstetric clinic and a hospital-based OGCT screening program participated. We determined vaccination status from a self-reported questionnaire, the Quebec Immunization Registry or medical charts. We compared model-specific (for participants recruited to a model and subsequently vaccinated within that model) and overall vaccine coverage (considering all vaccine delivery pathways) and used logistic regression to adjust for sociodemographic variables.

RESULTS

Overall, 946 of 1000 recruited pregnant people were eligible for analyses. Vaccination via the FMGs achieved the highest model-specific vaccine coverage (67.8%, 95% confidence interval [CI] 60.5%-74.4%), but coverage was not significantly different from the CLSCs (63.8%, 95% CI 57.6%-69.6%). For overall vaccine coverage, the FMG (86.5%, 95% CI 80.6%-90.9%) and obstetrics models (85.9%, 95% CI 80.9%-89.7%) achieved significantly higher vaccine coverage than the CLSCs (66.3%, 95% CI 60.1%-71.9%). The OGCT model did not improve overall vaccine coverage (61.8%, 95% CI 56.1%-67.2%).

INTERPRETATION

Compared with CLSCs, overall vaccine coverage was higher when Tdap was offered in FMGs or an obstetrics clinic providing prenatal care. Health professionals involved in pregnancy follow-up recommending and offering the vaccine may be a key factor in optimizing vaccine coverage.

Methods to evaluate COVID-19 vaccine effectiveness, with an emphasis on quasi-experimental approaches

The evaluation of vaccine effectiveness is conducted with real-world data. They are essential to monitor the performance of vaccination programmes over time, and in the context of the emergence of new variants. Until now, the effectiveness of COVID-19 vaccines has been assessed based on classic methods, such as cohort and test-negative case-control studies, which may often not allow for adequate control of inherent biases in the assignment of vaccination campaigns. The aim of this review was to discuss the study designs available to evaluate vaccine effectiveness, highlighting quasi-experimental studies, which seek to mimic randomized trials, by introducing an exogenous component to allocate to treatment, in addition to the advantages, limitations, and applicability in the context of Brazilian data. The use of quasi-experimental approaches, such as interrupted time series, difference-in-differences, propensity scores, instrumental variables, and regression discontinuity design, are relevant due to the possibility of providing more accurate estimates of COVID-19 vaccine effectiveness. This is especially important in scenarios such as the Brazilian, which characterized by the use of various vaccines, with the respective numbers and intervals between doses, applied to different age groups, and introduced at different times during the pandemic.

Managing confounding and effect modification in pediatric/congenital interventional cardiology research

Measuring the effect of a treatment on outcomes is an important goal for research in pediatric/congenital interventional cardiology. The breadth of anatomic and physiologic variations, patient ages, and genetic syndromes and noncardiac comorbid conditions all represent sources of potential confounding and effect modification that are major obstacles to this goal. If not accounted for, these factors can obscure the "true" treatment effect and lead to spurious conclusions about the relative efficacy and/or safety of therapies. In this review, we discuss the importance of confounding and effect modification in pediatric/congenital interventional cardiology research. We define these terms and discuss strategies (both in study design and data analysis) to mitigate error introduced by confounding and effect modification. The importance of confounding by indication in pediatric/congenital cardiology is discussed along with specific methods to address it.

Evaluation of post-introduction COVID-19 vaccine effectiveness: Summary of interim guidance of the World Health Organization

Phase 3 randomized-controlled trials have provided promising results of COVID-19 vaccine efficacy, ranging from 50 to 95% against symptomatic disease as the primary endpoints, resulting in emergency use authorization/listing for several vaccines. However, given the short duration of follow-up during the clinical trials, strict eligibility criteria, emerging variants of concern, and the changing epidemiology of the pandemic, many questions still remain unanswered regarding vaccine performance. Post-introduction vaccine effectiveness evaluations can help us to understand the vaccine's effect on reducing infection and disease when used in real-world conditions. They can also address important questions that were either not studied or were incompletely studied in the trials and that will inform evolving vaccine policy, including assessment of the duration of effectiveness; effectiveness in key subpopulations, such as the very old or immunocompromised; against severe disease and death due to COVID-19; against emerging SARS-CoV-2 variants of concern; and with different vaccination schedules, such as number of doses and varying dosing intervals. WHO convened an expert panel to develop interim best practice guidance for COVID-19 vaccine effectiveness evaluations. We present a summary of the interim guidance, including discussion of different study designs, priority outcomes to evaluate, potential biases, existing surveillance platforms that can be used, and recommendations for reporting results.

Real-World Effectiveness of Adjuvant Oxaliplatin Chemotherapy in Stage III Colon Cancer: A Controlled Interrupted Time Series Analysis

Background: The real-world effectiveness of oxaliplatin in stage III colon cancer has not been determined in a large-scale population. We aimed to assess the real-world impact of adjuvant oxaliplatin treatment on the survival of these patients.

Methods: Based on Taiwan cancer registry, we evaluated 17,801 patients with resected stage III colon cancer, including 14,168 patients receiving adjuvant chemotherapy and 3,633 not receiving adjuvant chemotherapy as the control group between 2004 and 2014. We used the controlled interrupted time-series analysis to assess the three-year disease-free survival and five-year overall survival rates before (2004–2008) and after (2009–2014) the addition of oxaliplatin.

Results: The introduction of oxaliplatin was associated with no significant improvement in the slopes (per half-year) of the three-year disease-free survival rate (0.2%, 95% CI: −1.7∼2.2%) and five-year overall survival rate (0.6%, 95% CI: −1.8∼3%). The patients receiving oxaliplatin-based chemotherapy also showed no significant increase in the slopes (per half-year) of the three-year disease-free survival rate (0.6%, 95% CI: −1.4∼2.6%) and five-year overall survival rate (1%, 95% CI: −1.5∼3.5%). The nonsignificant results were consistent across subgroup analyses of age (<70 vs. ≥70 years), recurrence risk (T1-3 or N1 vs. T4 or N2), and cycle of oxaliplatin use (≤6 vs. >6). However, oxaliplatin-based chemotherapy significantly increased the slope (per half-year) of the five-year OS (2%, 95% CI: 0.2∼3.8%) for patients in the high-risk group (T4 or N2). The present results were robust in several sensitivity analyses.

Conclusion: Among real-world patients with stage III colon cancer, the introduction of oxaliplatin does not yield a significant improvement in survival. Future work should identify the subpopulation(s) of patients who benefit significantly from the addition of oxaliplatin.

The Dutch influenza vaccination policy and medication use, outpatient visits, hospitalization and mortality at age 65

BACKGROUND

Our objective was to obtain estimates of the impact of the Dutch vaccination programme on medication use, outpatient visits, hospitalization and mortality at age 65.

METHODS

We linked population-wide mortality, hospitalization and municipality registries to identify influenza-related deaths and hospitalizations, and used health interview surveys to identify medication use and outpatient visits during 1996-2008. We applied a regression discontinuity design to estimate the intention-to-treat effect of the personal invitation for a free influenza vaccination sent to every Dutch inhabitant at age 65 years on each of the outcomes, separately in influenza-epidemic and non-epidemic months.

RESULTS

Invitation receipt for free influenza vaccination at age 65 led to a 9.8 percentage points [95% confidence interval (CI) = 3.5 to16.1; P < 0.01] rise in influenza vaccination. During influenza-epidemic months, it was associated with 1.5 fewer influenza/pneumonia deaths per 100 000 individuals (95% CI = -3.1 to -0.0; P = 0.05), a 15 percentage point lower probability to use prescribed medicines (95% CI = -28 to -3; P = 0.02) and 0.13 fewer General Practitioner (GP) visits per month (95% CI = -0.28 to 0.02; P = 0.09), while the association with hospitalizations due to influenza/pneumonia was small and imprecisely estimated (seven more hospitalizations per 100 000 individuals, 95% CI = -20 to 33; P = 0.63). No associations were found with any outcomes during non-epidemic months.

CONCLUSIONS

Personal invitations for a free influenza vaccination sent to every Dutch inhabitant at age 65 took pressure off primary health care but had small effects on hospitalizations and mortality.

Pneumococcal conjugate vaccine use during humanitarian crises

Streptococcus pneumoniae is a common human commensal that causes a sizeable part of the overall childhood mortality in low income settings. Populations affected by humanitarian crises are at especially high risk, because a multitude of risk factors that are enhanced during crises increase pneumococcal transmission and disease severity. Pneumococcal conjugate vaccines (PCVs) provide effective protection and have been introduced into the majority of routine childhood immunisation programmes globally, though several barriers have hitherto limited their uptake during humanitarian crises. When PCV coverage cannot be sustained during crises or when PCV has not been part of routine programmes, mass vaccination campaigns offer a quick acting and programmatically feasible bridging solution until services can be restored. However, we currently face a paucity of evidence on which to base the structure of such campaigns. We believe that, now that PCV can be procured at a substantially reduced price through the Humanitarian Mechanism, this lack of information is a remaining hurdle to PCV use in humanitarian crises. Considering the difficulties in conducting research in crises, we propose an evidence generation pathway consisting of primary data collection in combination with mathematical modelling followed by quasi-experimental evaluation of a PCV intervention, which can inform on optimal vaccination strategies that consider age targeting, dosing regimens and impact duration.

Evaluating the Effectiveness of Vaccines Using a Regression Discontinuity Design

The regression discontinuity design (RDD), first proposed in the educational psychology literature and popularized in econometrics in the 1960s, has only recently been applied to epidemiologic research. A critical aim of infectious disease epidemiologists and global health researchers is to evaluate disease prevention and control strategies, including the impact of vaccines and vaccination programs. RDDs have very rarely been used in this context. This quasi-experimental approach using observational data is designed to quantify the effect of an intervention when eligibility for the intervention is based on a defined cutoff such as age or grade in school, making it ideally suited to estimating vaccine effects given that many vaccination programs and mass-vaccination campaigns define eligibility in this way. Here, we describe key features of RDDs in general, then specific scenarios, with examples, to illustrate that RDDs are an important tool for advancing our understanding of vaccine effects. We argue that epidemiologic researchers should consider RDDs when evaluating interventions designed to prevent and control diseases. This approach can address a wide range of research questions, especially those for which randomized clinical trials would present major challenges or be infeasible. Finally, we propose specific ways in which RDDs could advance future vaccine research.