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Vaccine Benefit-Risk (B-R) assessment consists of evaluating the benefits and risks of a vaccine and making a judgment whether the expected key benefits outweigh the potential key risks associated with its expected use. B-R supports regulatory and public health decision-making throughout the vaccine's lifecycle. In August 2021, the Brighton Collaboration's Benefit-Risk Assessment of VAccines by TechnolOgy (BRAVATO) Benefit-Risk Assessment Module working group was established to develop a standard module to support the planning, conduct and evaluation of structured B-R assessments for vaccines from different platforms, based on data from clinical trials, post-marketing studies and real-world evidence. It enables sharing of relevant information via value trees, effects tables and graphical depictions of B-R trade-offs. It is intended to support vaccine developers, funders, regulators and policy makers in high-, middle- or low-income countries to help inform decision-making and facilitate transparent communication concerning development, licensure, deployment and other lifecycle decisions., Competing Interests: Declaration of Competing Interest The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: B.L. is an employee of Janssen Research and Development, LLC, is a stockholder in Johnson & Johnson, and possesses a portfolio that at times includes other pharmaceutical, vaccine and health care-related companies. V.B. is an employee, and own shares options, of GSK. N.L.B. is an employee of and stockholder of Novavax, Inc., (Copyright © 2023 The Author(s). Published by Elsevier Ltd.. All rights reserved.)

The influenza A/H1N1 pandemic in 2009 taught us that the monitoring of vaccine benefits and risks in Europe had potential for improvement if different public and private stakeholders would collaborate better (public health institutes (PHIs), regulatory authorities, research institutes, vaccine manufacturers). The Innovative Medicines Initiative (IMI) subsequently issued a competitive call to establish a public-private partnership to build and test a novel system for monitoring vaccine benefits and risks in Europe. The ADVANCE project (Accelerated Development of Vaccine benefit-risk Collaboration in Europe) was created as a result. The objective of this paper is to describe the perspectives of key stakeholder groups of the ADVANCE consortium for vaccine benefit-risk monitoring and their views on how to build a European system addressing the needs and challenges of such monitoring. These perspectives and needs were assessed at the start of the ADVANCE project by the European Medicines Agency together with representatives of the main stakeholders in the field of vaccines within and outside the ADVANCE consortium (i.e. research institutes, public health institutes, medicines regulatory authorities, vaccine manufacturers, patient associations). Although all stakeholder representatives stated they conduct vaccine benefit-risk monitoring according to their own remit, needs and obligations, they are faced with similar challenges and needs for improved collaboration. A robust, rapid system yielding high-quality information on the benefits and risks of vaccines would therefore support their decision making. ADVANCE has developed such a system and has tested its performance in a series of proof of concept (POC) studies. The system, how it was used and the results from the POC studies are described in the papers in this supplementary issue., Competing Interests: Declaration of Competing Interest Priya Bahri, Tyra Grove Krause, Susan Hahné, Maarit Kokki, Piotr Kramarz, Xavier Kurz and Patrick Mahy declared no conflict of interests. Miriam Sturkenboom declared that she has received grants from Novartis, CDC and Bill & Melinda Gates Foundation for work unrelated to the work presented here. Antonella Chiucchiuini declared that she received personal fees from Takeda Pharmaceuticals International AG during the study. Alena Khromava and Laurence Torcel-Pagnon declared that they are employed by Sanofi Pasteur and hold company shares/stock options. Heidi J Larson declared that her research group has received funding from Merck to convene a research symposium, and research funding from GSK for a global study on maternal vaccine acceptance. Simon de Lusignan declared he has university-based research (enhanced surveillance of influneza vaccines) funded by GSK, he is also a member of Seqirus and Sanofi Pasteur Advisory Boards for influenza. Lina Titievsky declared that she is employed by Pfizer and holds company stocks/shares. Vincent Bauchau declared that he is employed by GSK Vaccines and holds restricted company shares., (Copyright © 2019. Published by Elsevier Ltd.)

Introduction: Quantitative benefit-risk models (qBRm) applied to vaccines are increasingly used by public health authorities and pharmaceutical companies as an important tool to help decision makers with supporting benefit-risk assessment (BRA). However, many publications on vaccine qBRm provide insufficient details on the methodological approaches used. Incomplete and/or inadequate qBRm reporting may affect result interpretation and confidence in BRA, highlighting a need for the development of standard reporting guidance., Objectives: Our objective was to provide an operational checklist for improved reporting of vaccine qBRm., Methods: The consolidated standards of reporting quantitative Benefit-RIsk models applied to VACcines (BRIVAC) were designed as a checklist of key information to report in qBRm scientific publications regarding the assessed vaccines, the methodological considerations and the results and their interpretation., Results: In total, 22 items and accompanying definitions, recommendations, explanations and examples were provided and divided into six main sections corresponding to the classic subdivisions of a scientific publication: title and abstract (items 1-2), introduction (items 3-4), methods (items 5-15), results (items 16-17), discussion (items 18-20) and other (items 21-22)., Conclusions: The BRIVAC checklist is the first initiative providing an operational checklist for improved reporting of qBRm applied to vaccines in scientific articles. It is intended to assist authors, peer-reviewers, editors and readers in their critical appraisal. Future initiatives are needed to provide methodological guidance to perform qBRm while taking into account the vaccine specificities.

Introduction: Understanding the balance between the benefits and risks of vaccination is essential to ensure informed and adequate public health decision making. Quantitative benefit-risk models (qBRm) represent useful tools to help decision makers with supporting benefit-risk assessment throughout the lifecycle of a medical product. However, few initiatives have been launched to harmonise qBRm approaches, specifically for vaccines., Objectives: The aim of this paper was to identify publications about qBRm applied to vaccines through a systematic literature review, and to describe their characteristics., Methods: Medline, Scopus and Institute for Scientific Information Web of Knowledge databases were searched to identify articles in English, published from database inceptions up to December 2019. The search strategy included the combination of three key concepts: 'benefit-risk', 'modelling' and 'vaccines'. Data extracted included the modelling context and the methodological approaches used., Results: Of 3172 publications screened, 48 original publications were included. Most of the selected studies were published over the past decade and focused on rotavirus (15), dengue (10) and influenza (6) vaccines. The majority (30) of studies reported analyses related to high-income countries. The methodology of the studies differed, particularly in modelling techniques, benefit-risk measures, and sensitivity analyses. The present work also pointed out a high level of variability in the quality of reporting across studies, with particular regard to input parameters and methodological approaches., Conclusions: This review provides an extensive list of qBRm applied to vaccines. Discrepancies across studies were identified during our review. While the number of published qBRm studies is increasing, no reporting guidance for qBRm applied to vaccines is currently available. This may affect decision makers' confidence in the results and their benefit-risk assessment(s); therefore, the development of such reporting guidance is highly needed.

Background and Objectives: Over the last decades, medicinal regulations have been put into place and have considerably improved manufacturing practices. Nevertheless, safety issues may still arise. Using the simulation described in this manuscript, our aim is to develop adequate detection methods for manufacturing-related safety signals, especially in the context of biological products., Methods: Pharmaceutical companies record the entire batch genealogies, from seed batches over intermediates to final product (FP) batches. We constructed a hierarchical tree based on this genealogy information and linked it to the spontaneous safety data available for the FP batch numbers. The tree-based scan statistic (TBSS) was used on simulated data as a proof of concept to locate the source that may have subsequently generated an excess of specific adverse events (AEs) within the manufacturing steps, and to evaluate the method's adjustment for multiple testing. All calculations were performed with a customized program in SAS v9.2., Results: The TBSS generated a close to expected number of false positive signals, demonstrating that it adjusted for multiple testing. Overall, the method detected 71% of the simulated signals at the correct production step when a 6-fold increase in reports with AEs of interest (AEOI) was applied, and 31% when a 2-fold increase was applied. The relatively low detection performance may be attributed to the higher granularity associated with the lower levels of the hierarchy, leading to a lack of power and the stringent definition criteria that were applied for a true positive result., Conclusion: As a data-mining method for manufacturing-related safety signal detection, the TBSS may provide advantages over other disproportionality analyses (using batch information) but may benefit from complementary methods (not relaying on batch information). While the method warrants further refinement, it may improve safety signal detection and contribute to improvements in the quality of manufacturing processes., (Copyright © 2018 GlaxoSmithKline Biologicals SA. Published by Elsevier Ltd.. All rights reserved.)

Introduction: New vaccines are launched based on their benefit-risk (B/R) profile anticipated from clinical development. Proactive post-marketing surveillance is necessary to assess whether the vaccination uptake and the B/R profile are as expected and, ultimately, whether further public health or regulatory actions are needed. There are several, typically not integrated, facets of post-marketing vaccine surveillance: the surveillance of vaccination coverage, vaccine safety, effectiveness and impact., Objective: With this work, we aim to assess the feasibility and added value of using an interactive dashboard as a potential methodology for near real-time monitoring of vaccine coverage and pre-specified health benefits and risks of vaccines., Methods: We developed a web application with an interactive dashboard for B/R monitoring. The dashboard is demonstrated using simulated electronic healthcare record data mimicking the introduction of rotavirus vaccination in the UK. The interactive dashboard allows end users to select certain parameters, including expected vaccine effectiveness, age groups, and time periods and allows calculation of the incremental net health benefit (INHB) as well as the incremental benefit-risk ratio (IBRR) for different sets of preference weights. We assessed the potential added value of the dashboard by user testing amongst a range of stakeholders experienced in the post-marketing monitoring of vaccines., Results: The dashboard was successfully implemented and demonstrated. The feedback from the potential end users was generally positive, although reluctance to using composite B/R measures was expressed., Conclusion: The use of interactive dashboards for B/R monitoring is promising and received support from various stakeholders. In future research, the use of such an interactive dashboard will be further tested with real-life data as opposed to simulated data.

Purpose: Composite disease burden measures such as disability-adjusted life-years (DALY) have been widely used to quantify the population-level health impact of disease or injury, but application has been limited for the estimation of the burden of adverse events following immunization. Our objective was to assess the feasibility of adapting the DALY approach for estimating adverse event burden., Methods: We developed a practical methodological framework, explicitly describing all steps involved: acquisition of relative or absolute risks and background event incidence rates, selection of disability weights and durations, and computation of the years lived with disability (YLD) measure, with appropriate estimation of uncertainty. We present a worked example, in which YLD is computed for 3 recognized adverse reactions following 3 childhood vaccination types, based on background incidence rates and relative/absolute risks retrieved from the literature., Results: YLD provided extra insight into the health impact of an adverse event over presentation of incidence rates only, as severity and duration are additionally incorporated. As well as providing guidance for the deployment of DALY methodology in the context of adverse events associated with vaccination, we also identified where data limitations potentially occur., Conclusions: Burden of disease methodology can be applied to estimate the health burden of adverse events following vaccination in a systematic way. As with all burden of disease studies, interpretation of the estimates must consider the quality and accuracy of the data sources contributing to the DALY computation., (© 2018 The Authors. Pharmacoepidemiology & Drug Safety Published by John Wiley & Sons Ltd.)

Post-authorisation safety studies (PASS) of vaccines assess or quantify the risk of adverse events following immunisation that were not identified or could not be estimated pre-licensure. The aim of this perspective paper is to describe the authors' experience in the design and conduct of twelve PASS that contributed to the evaluation of the benefit-risk of vaccines in real-world settings. We describe challenges and learnings from selected PASS of rotavirus, malaria, influenza, human papillomavirus and measles-mumps-rubella-varicella vaccines that assessed or identified potential or theoretical risks, which may lead to changes to risk management plans and/or to label updates. Study settings include the use of large healthcare databases and de novo data collection. PASS methodology is influenced by the background incidence of the outcome of interest, vaccine uptake, availability and quality of data sources, identification of the at-risk population and of suitable comparators, availability of validated case definitions, and the frequent need for case ascertainment in large databases. Challenges include the requirement for valid exposure and outcome data, identification of, and access to, adequate data sources, and mitigating limitations including bias and confounding. Assessing feasibility is becoming a key step to confirm that study objectives can be met in a timely manner. PASS provide critical information for regulators, public health agencies, vaccine manufacturers and ultimately, individuals. Collaborative approaches and synergistic efforts between vaccine manufacturers and key stakeholders, such as regulatory and public health agencies, are needed to facilitate access to data, and to drive optimal study design and implementation, with the aim of generating robust evidence., (Copyright © 2017 GSK Biologicals SA. Published by Elsevier Ltd.. All rights reserved.)

Purpose: We evaluated the use of logistic regression to model the probabilities of spontaneously reported vaccine-event pairs being adverse reactions following immunization (ARFI), using disproportionality and unexpectedness of time-to-onset (TTO) distributions as predictive variables and the presence of events in the global product information as a dependent variable., Methods: We used spontaneous reports of adverse events from eight vaccines and their labels as proxies for ARFIs. Three logistic regressions were built to predict ARFIs based on different combinations of the proportional reporting ratio (PRR; disproportionality measure) and two Kolmogorov-Smirnov (KS) tests ('between vaccines' and the 'between events') of TTO distribution: model 1, using the PRR estimate and its 95% lower confidence interval (CI) limit; model 2, using the p values of the two KS tests; and model 3, using the PRR (point estimate and lower CI limit) and both KS tests. The performance of the regressions (model fit statistics, calibration, and discrimination) was measured on 100 bootstrap samples., Results: Model 3, using two quantified causality criteria, provided the best performance for all measures. The p value of the 'between vaccines' KS test was the most significant predictive factor. Model 1 had the worst performance., Conclusions: Logistic regression allows estimation of the probability of a vaccine-event pair being an ARFI using two causality criteria at the population level assessed in spontaneous report data: the strength of association (disproportionality measure) and temporality (TTO distribution tests). Logistic regression combines and weights these causality criteria based on their respective ability to predict known safety issues.

Purpose: For disproportionality measures based on the Relative Reporting Ratio (RRR) such as the Information Component (IC) and the Empirical Bayesian Geometrical Mean (EBGM), each product and event is assumed to represent a negligible fraction of the spontaneous report database (SRD). Here, we provide the tools for allowing signal detection experts to assess the consequence of the violation of this assumption on their specific SRD., Methods: For each product-event pair (P-E), a worst-case scenario associated all the reported events-of-interest with the product of interest. The values of the RRR under this scenario were measured for different sets of stratification factors using the GlaxoSmithKline vaccines SRD. These values represent the RRR upper bound that RRR cannot exceed whatever the true strength of association., Results: Depending on the choice of stratification factors, the RRR could not exceed an upper bound of 2 for up to 2.4% of the P-Es. For Engerix™, 23.4% of all reports in the SDR, the RRR could not exceed an upper bound of 2 for up to 13.8% of pairs. For the P-E Rotarix™-Intussusception, the choice of stratification factors impacted the upper bound to RRR: from 52.5 for an unstratified RRR to 2.0 for a fully stratified RRR., Conclusions: The quantification of the upper bound can indicate whether measures such as EBGM, IC, or RRR can be used for SRD for which products or events represent a non-negligible fraction of the entire SRD. In addition, at the level of the product or P-E, it can also highlight detrimental impact of overstratification., (© 2014 The Authors. Pharmacoepidemiology and Drug Safety published by John Wiley & Sons, Ltd.)

Purpose: Disproportionality methods measure how unexpected the observed number of adverse events is. Time-to-onset (TTO) methods measure how unexpected the TTO distribution of a vaccine-event pair is compared with what is expected from other vaccines and events. Our purpose is to compare the performance associated with each method., Methods: For the disproportionality algorithms, we defined 336 combinations of stratification factors (sex, age, region and year) and threshold values of the multi-item gamma Poisson shrinker (MGPS). For the TTO algorithms, we defined 18 combinations of significance level and time windows. We used spontaneous reports of adverse events recorded for eight vaccines. The vaccine product labels were used as proxies for true safety signals. Algorithms were ranked according to their positive predictive value (PPV) for each vaccine separately; amedian rank was attributed to each algorithm across vaccines., Results: The algorithm with the highest median rank was based on TTO with a significance level of 0.01 and a time window of 60 days after immunisation. It had an overall PPV 2.5 times higher than for the highest-ranked MGPS algorithm, 16(th) rank overall, which was fully stratified and had a threshold value of 0.8. A TTO algorithm with roughly the same sensitivity as the highest-ranked MGPS had better specificity but longer time-to-detection., Conclusions: Within the scope of this study, the majority of the TTO algorithms presented a higher PPV than for any MGPS algorithm. Considering the complementarity of TTO and disproportionality methods, a signal detection strategy combining them merits further investigation. © 2013 GlaxoSmithKline. Pharmacoepidemiology and Drug Safety published by John Wiley & Sons, Ltd., (© 2013 GlaxoSmithKline. Pharmacoepidemiology and Drug Safety published by John Wiley & Sons, Ltd.)

Purpose: To optimize the efficiency of signal detection by maximizing the proportion of true positive (TP) signals among signals detected by a disproportionality algorithm., Methods: We compared 176 different combinations of stratification factors, sex (S), age (A), region (R) and year of report (Y), and cut-off values of a Multi-Item Gamma Poisson Schrinker (MGPS) algorithm. Spontaneous adverse event reports of eight vaccines from the GlaxoSmithKline Biologicals safety database were used. Defining events listed in the Product Information as proxy of true safety signals, we compared each algorithm performance in terms of positive predictive value (PPV). For each vaccine, each algorithm was ranked according to PPV. Median rank and overall PPV were computed across vaccines., Results: For a standard cut-off of 2, the optimal stratification factors differed by vaccine and led to a set of algorithms with a median rank of 34.5 (PPV = 0.22; 34 TP). Keeping the original SARY stratification led to optimal cut-offs that differed by vaccine and a set of algorithms with a median rank of 1.75 (PPV = 0.20; 142 TP). The optimal combination of cut-off and stratification led to different algorithms by vaccine with a median rank of 1 (PPV = 0.19; 139 TP). The best unique algorithm parameterization across vaccines was 0.8-SARY (cut-off-stratification), with a median rank of 3 (PPV = 0.20; 195 TP). The original 2-SARY was one of the worst algorithms, with a median rank of 150.75 (PPV = 0.13; 8 TP)., Conclusion: Within the scope of this study, a unique MGPS algorithm across vaccines with the original full stratification but a lowered cut-off provided major performance improvement., (Copyright © 2012 John Wiley & Sons, Ltd.)

Introduction: The Accelerated Development of VAccine beNefit-risk Collaboration in Europe (ADVANCE) is a public private collaboration aiming to develop and test a system for rapid benefit-risk (B/R) monitoring of vaccines, using existing electronic healthcare record (eHR) databases in Europe. Part of the data in such sources is missing due to incomplete follow-up hampering the accurate estimation of vaccination coverage. We compared different methods for coverage estimation from eHR databases; naïve period prevalence, complete case period prevalence, period prevalence adjusted for follow-up time, Kaplan-Meier (KM) analysis and (adjusted) inverse probability weighing (IPW). Methods: We created simulation scenarios with different proportions of completeness of follow-up. Both completeness independent and dependent from vaccination date and status were considered. The root mean squared error (RMSE) and relative difference between the estimated and true coverage were used to assess the performance of the different methods for each of the scenarios. We included data examples on the vaccination coverage of human papilloma virus and pertussis component containing vaccines from the Spanish BIFAP database. Results: Under completeness independent from vaccination date or status, several methods provided estimates with bias close to zero. However, when dependence between completeness of follow-up and vaccination date or status was present, all methods generated biased estimates. The IPW/CDF methods were generally the least biased. Preference for a specific method should be based on the type of censoring and type of dependence between completeness of follow-up and vaccination. Additional insights into these aspects, might be gained by applying several methods. [ABSTRACT FROM AUTHOR]

The 2009 influenza pandemic highlighted challenges for vaccine post-marketing monitoring in Europe, particularly the need to have appropriate infrastructures to strengthen public-private collaborations (PPCs) with suitable processes to improve stakeholder interactions and collection and analysis of safety and effectiveness data. The ADVANCE consortium comprises public and private stakeholders who have worked together to build and test new system components for vaccine post-marketing projects, one component being a governance framework for efficient, transparent and trustworthy PPCs. Based on the results of a landscape analysis and screening of formalised existing governance structures, we identified the elements of a governance framework and developed recommendations to support stakeholders willing and able to implement collaborative projects. These proposals and their implementation were discussed by 70 experts during a workshop to gain from their experience. We identified core governance principles and defined five fundamental functions (decision-making, scientific advice, quality control and audit, implementation and management, and financial administration) that can be attributed to individual partner organisations or to a committee with representatives from more than one partner organisation. We propose a generic governance model with options for its adaptation to specific contexts and projects. The advantages and disadvantages of PPCs were also examined. Stakeholders' concerns (e.g. scientific integrity and public trust) were addressed through recommendations about transparent decision-making rules and conflict of interest management. No one-size-fits-all solution for PPC governance exists but our recommendations could be used to set-up a tailored-made and fully transparent governance structure supporting collaborative projects in the European vaccine post-marketing environment. To allow the rapid establishment of robust projects, the next steps will involve this guidance being used by real-world collaborations to assess what works and what does not work and what added-value can be obtained from these collaborations. [ABSTRACT FROM AUTHOR]

Lessons learnt from the 2009 (H1N1) flu pandemic highlighted factors limiting the capacity to collect European data on vaccine exposure, safety and effectiveness, including lack of rapid access to available data sources or expertise, difficulties to establish efficient interactions between multiple parties, lack of confidence between private and public sectors, concerns about possible or actual conflicts of interest (or perceptions thereof) and inadequate funding mechanisms. The Innovative Medicines Initiative’s Accelerated Development of VAccine benefit-risk Collaboration in Europe (ADVANCE) consortium was established to create an efficient and sustainable infrastructure for rapid and integrated monitoring of post-approval benefit-risk of vaccines, including a code of conduct and governance principles for collaborative studies. The development of the code of conduct was guided by three core and common values (best science, strengthening public health, transparency) and a review of existing guidance and relevant published articles. The ADVANCE Code of Conduct includes 45 recommendations in 10 topics (Scientific integrity, Scientific independence, Transparency, Conflicts of interest, Study protocol, Study report, Publication, Subject privacy, Sharing of study data, Research contract). Each topic includes a definition, a set of recommendations and a list of additional reading. The concept of the study team is introduced as a key component of the ADVANCE Code of Conduct with a core set of roles and responsibilities. It is hoped that adoption of the ADVANCE Code of Conduct by all partners involved in a study will facilitate and speed-up its initiation, design, conduct and reporting. Adoption of the ADVANCE Code of Conduct should be stated in the study protocol, study report and publications and journal editors are encouraged to use it as an indication that good principles of public health, science and transparency were followed throughout the study. [ABSTRACT FROM AUTHOR]

• Non-clinical studies raised no safety concerns regarding the use of AS03. • In clinical trials, AS03-adjuvanted influenza vaccines were generally well tolerated. • Post-licensure data showed a favourable benefit-risk profile in various populations. • The increased risk of narcolepsy with Pandemrix may not be directly linked to AS03. • Available safety data support the development and use of AS03-adjuvanted vaccines. Clinical and post-licensure data have demonstrated that AS03-adjuvanted inactivated split virion vaccines, many with reduced antigen content, are effective against influenza infection. The objective of this review is to provide a comprehensive assessment of the safety of trivalent seasonal, monovalent pre-pandemic and pandemic AS03-adjuvanted influenza vaccines, based on non-clinical, clinical and post-licensure data in various populations. Non-clinical studies on local tolerance, toxicology and safety pharmacology did not raise any safety concerns with AS03 administered alone or combined with various influenza antigens. Data from clinical trials with over 55,000 vaccinated subjects showed that AS03-adjuvanted influenza vaccines were generally well tolerated and displayed an acceptable safety profile, although the power to detect rare events was limited. Approximately 90 million doses of A/H1N1pdm09 pandemic influenza vaccines (Pandemrix and Arepanrix H1N1) were administered worldwide, which contributed post-licensure data to the collective safety data for AS03-adjuvanted influenza vaccines. An association between Pandemrix and narcolepsy was observed during the A/H1N1pdm09 pandemic, for which a role of a CD4 T cell mimicry sequence in the haemagglutinin protein of A/H1N1pdm09 cannot be excluded. Provided that future AS03-adjuvanted influenza vaccines do not contain this putative mimicry sequence, this extensive safety experience supports the further development and use of AS03-adjuvanted inactivated split virion candidate vaccines against seasonal and pandemic influenza infections. [ABSTRACT FROM AUTHOR]

The Accelerated Development of VAccine beNefit-risk Collaboration in Europe (ADVANCE) is a public-private collaboration aiming to develop and test a system for rapid benefit-risk (B/R) monitoring of vaccines using electronic health record (eHR) databases in Europe. Proof-of-concept studies were designed to assess the proposed processes and system for generating the required evidence to perform B/R assessment and near-real time monitoring of vaccines. We aimed to test B/R methodologies for vaccines, using the comparison of the B/R profiles of whole-cell (wP) and acellular pertussis (aP) vaccine formulations in children as an example. We used multi-criteria decision analysis (MCDA) to structure the B/R assessment combined with individual-level state transition modelling to build the B/R effects table. In the state transition model, we simulated the number of events in two hypothetical cohorts of 1 million children followed from first pertussis dose till pre-school-entry booster (or six years of age, whichever occurred first), with one cohort receiving wP, and the other aP. The benefits were reductions in pertussis incidence and complications. The risks were increased incidences of febrile convulsions, fever, hypotonic-hyporesponsive episodes, injection-site reactions and persistent crying. Most model parameters were informed by estimates (coverage, background incidences, relative risks) from eHR databases from Denmark (SSI), Spain (BIFAP and SIDIAP), Italy (Pedianet) and the UK (RCGP-RSC and THIN). Preferences were elicited from clinical and epidemiological experts. Using state transition modelling to build the B/R effects table facilitated the comparison of different vaccine effects (e.g. immediate vaccine risks vs long-term vaccine benefits). Estimates from eHR databases could be used to inform the simulation model. The model results could be easily combined with preference weights to obtain B/R scores. Existing B/R methodology, modelling and estimates from eHR databases can be successfully used for B/R assessment of vaccines. [ABSTRACT FROM AUTHOR]