Results

Background: Adverse events following COVID-19 vaccination, included Thrombosis with Thrombocytopenia Syndrome (TTS). The Brighton Collaboration (BC) case definition for TTS was based on clinical presentation, imaging, investigatory findings, and laboratory results. This definition was intended for use in clinical trials and post-licensing settings to allow Level Of Certainty (LOC) of cases to be determined. The Positive Predicted Value (PPV) of LOCs can estimate the validity of cases identified in Real-World Data (RWD) sources.

Objectives: To determine the PPV of TTS cases using the BC case definition across various RWD sources, while also assessing the impact of data source type on PPV. Secondary objectives were to establish whether risk windows, or publication of the signal of TTS, affected the PPV of cases.

Methods: As part of a global project, co-ordinated by the Global Vaccine Data Network (GVDN) in collaboration with Vaccine Monitoring Collaboration for Europe (VAC4EU), the association of TTS with COVID-19 vaccination was assessed. Sites (across Spain and the United Kingdom) contributed to this study and validated potential TTS cases.

Cases were assessed based on diagnostic codes from electronic healthcare records between 1 December 2020 to 31 October 2022. Data extraction to support validation was collated via Research Electronic Data CAPture (REDCap), a web-based platform for data capture hosted by GVDN. LOC of diagnosis (based on the BC case definition) was determined by an algorithm created by GVDN, where LOC1 or 2 are definite cases and 5 is a non-case. To determine the accuracy of LOCs, PPVs were calculated, with Yates’ continuity correction. Sensitivity analyses were also performed. Sub-group analyses were conducted to fulfil the secondary objectives. Analysis was conducted in RStudio using R 4.4.1.

Results: 187 TTS cases were identified, of which LOC was assessed in 136 cases, CPRD cases were not validated due to lack of information in CPRD Aurum to fulfil the BC definition. The PPV ranged from 0-65% for LOC1-2 cases. Sites with access to hospital records achieved higher PPVs for LOC1-2 cases compared to sites with primary care data, where a maximum of LOC4 was achieved. PPVs from hospital records were highest outside of vaccination risk windows (70% [95%CI: 47.0-85.9]) and prior to publication of the TTS signal (100% [95% CI: 19.8-100.0]).

Conclusions: The PPV of TTS case validation was highly variable. Validation of cases using the BC case definition required the availability of highly granular data; from clinical observations, scans, laboratory findings as well as prior medical history and medications, the availability of which was highly variable between different healthcare settings and countries.

Background: Coronavirus disease 2019 (COVID-19) in pregnancy is associated with increased risks of adverse maternal and neonatal outcomes. Moderna mRNA-1273 vaccine was authorised in the European Union and in the United Kingdom (UK) in early 2021 and subsequently recommended for use in pregnancy.

Objectives: To assess whether mRNA-1273 during pregnancy is associated with an elevated risk of adverse pregnancy outcomes; major congenital malformations (MCMs); or adverse birth and neonatal outcomes.

Methods: This multi-database study used secondary healthcare data from national registries (Denmark and Norway), SIDIAP database (Catalonia, Spain), and CPRD Aurum (UK). Study population included pregnancies ending in 2021-2023 and their linkable offspring. Depending on population and outcome types, cohort, prevalence, or cross-sectional designs were used. Exposure was 1+ dose of mRNA-1273 vs. no COVID-19 vaccines during pregnancy, time-varying where appropriate. For the MCM outcomes, only first-trimester exposure was assessed. Local data were harmonised into the ConcePTION common data model and analysed in a federated manner. Country-specific results were pooled using random-effects meta-analysis.

Results: For pregnancy hypertensive disorders, bleeding, and gestational diabetes, adjusted hazard ratios (aHR) (95% confidence interval [CI]) were 0.54 (0.47-0.61), 0.90 (0.76-1.08) and 0.50 (0.46-0.54). For foetal death and elective termination, aHRs (95% CI) were 1.17 (0.91-1.49) and 1.18 (0.91-1.54). For pregnancy-related death and postpartum haemorrhage, aHR (95% CI) were 0.76 (0.23-2.59) and 1.14 (0.96-1.35). For any MCM, adjusted prevalence ratio (aPR) (95% CI) was 1.00 (0.91-1.10). For specific MCMs, most aPR (95% CI) were consistent with a null association, ranging from 0.63 (0.12-3.31) for respiratory MCM to 1.41 (0.88-2.25) for "other" MCMs.

Adjusted PRs (95% CI) were 0.89 (0.84-0.94) for preterm birth, 0.81 (0.76-0.87) for low birth weight, 0.95 (0.80-1.13) for small for gestational age (SGA) defined by birth weight >2 standard deviations below the mean, 0.92 (0.79-1.08) for SGA defined by < 10th centile of birth weight, and 0.88 (0.72-1.09) for low 5-minute Apgar score. For neonatal death, adjusted risk ratio (95% CI) was 0.70 (0.41-1.20).

Conclusions: This study does not indicate an association between receipt of mRNA-1273 vaccine (regardless of other COVID-19 vaccination during pregnancy) and an elevated risk of adverse pregnancy, birth, or neonatal outcomes compared with no COVID-19 vaccination. Limitations include potential selection bias due to prevalent design, incomplete mother-offspring linkage, confounding by indication, healthy vaccinee bias, and imprecise estimates for certain outcomes.

Background:

Adverse events of special interest (AESI) are assessed in post-authorization safety studies (PASS) using real-world data (RWD), but the accuracy of codes and algorithms to identify them require validation according to the regulatory guidance for RWD studies.

Objectives:

To estimate the positive predictive value (PPV) of diagnostic algorithms for 11 prespecified AESIs across neurological, hematological/thrombotic, and cardiovascular disorders in a retrospective PASS of JCOVDEN in the European Union.

Methods:

Case validation was conducted using the VAC4EU framework for defining, ascertaining, and validating AESIs. This was carried out across two data sources (VID, SIDIAP) by trained abstractors using electronic medical records and REDCap questionnaires. We validated up to 50 cases for JCOVDEN and 30 for comparators for each AESI. Cases were assigned a level of diagnostic certainty (LOC) ranging from 1 (definite case) to 5 (definite alternative diagnosis) using adapted Brighton Collaboration case definitions. For each AESI, the PPVs with 95% confidence intervals (CIs) were calculated by dividing the number of confirmed cases (those with a LOC 1-3) by the total number of validated cases (LOC 1, 2, 3, 4a, or 5).

Results:

Among JCOVDEN vaccinees, 324 events were validated. The PPV (95%CI) for thrombosis with thrombocytopenia syndrome was 55.2% (35.7–73.6%) in SIDIAP and 100% (2.5–100%) in VID . The PPV of cerebral venous sinus thrombosis was 100% in both data sources. The other AESIs were validated only in VID. High PPVs (above 80%) were observed for cardiac inflammatory disorder (PPV = 83.3% (62.6–95.3%); pulmonary embolism (PPV = 83.3% (67.2–93.6%); hemorrhagic stroke, (PPV = 85.7% (67.3–96.0%). Moderate PPVs (60-75%) were observed for immune thrombocytopenia, PPV = 75.0% (34.9-96.8%); non-hemorrhagic stroke, PPV = 72.4% (52.8–87.3%); transverse myelitis, PPV = 66.7% (9.4-99.1%); Guillain-Barré syndrome, PPV = 62.5% (24.5–91.5%); and deep vein thrombosis, PPV = 60.0% (42.1-76.1%). The PPV for encephalitis was low, PPV = 26.7% (7.8-55.1%).

Conclusion:

Levels of diagnostic certainty and PPVs varied across AESIs. The validation approach was effective but limited by available clinical data, highlighting the need for robust data in vaccine safety monitoring.

Background: Comirnaty® received conditional marketing authorisation in the European Union (EU), United Kingdom (UK) and United States (US) in December 2020. We describe interim results from a post-authorisation safety study (PASS); a commitment to EU and US regulatory authorities.

Objectives: Determine the risk of 37 adverse events of special interest (AESIs) following ≥1 dose of Comirnaty in the general European population.

Methods: This is an ongoing retrospective cohort study, with Comirnaty vaccinated and unvaccinated matched 1:1 on age, sex and other demographic and clinical factors, from 6 electronic health record data sources in 5 countries: Italy (Pedianet, general practitioner, GP); Netherlands (PHARMO Data Network, GP); Norway (NHR, inpatient and outpatient); Spain (EpiChron, GP and inpatient and SIDIAP, GP and inpatient/outpatient specialist); and UK (CPRD Aurum, GP). Analyses were conducted using a common protocol, the ConcePTION common data model and common analytical programs. Propensity score-adjusted hazard ratios (HRs) were estimated for event-specific risk windows.

Results: From December 2020 to March 2022 (CPRD Aurum), December 2022 (Pedianet, NHR), June 2023 (PHARMO, SIDIAP) and July 2023 (EpiChron), 12,400,847 recipients of ≥1 dose of Comirnaty were matched (Pedianet: 10,500, NHR: 3,584,238, PHARMO: 992,144, EpiChron: 627,972, SIDIAP: 3,087,124, CPRD: 4,098,869).

There was no increased risk of most of the 37 AESIs associated with the vaccine, including myocarditis (21-day risk window) with HRs of 0.94 (95% CI: 0.46, 1.94) in NHR, 1.23 (95% CI: 0.13, 11.84) in PHARMO, 3.64 (95% CI: 0.41, 32.53) in EpiChron, 1.05 (95% CI: 0.35, 3.16) in SIDIAP, and 2.30 (95% CI: 0.94, 5.66) in CPRD. Results of note were arrhythmia with HRs of 1.36 (95% confidence interval [CI]: 1.29, 1.44) in PHARMO, 1.03 (95% CI: 1.00, 1.05) in NHR, 1.12 (95% CI: 1.04, 1.21) in EpiChron, and 1.27 (95% CI: 1.21, 1.33) in CPRD; heart failure 1.29 (95% CI: 1.13, 1.47) in PHARMO; coronary artery disease 1.49 (95% CI: 1.31, 1.69) in PHARMO, and 1.40 (95% CI: 1.30, 1.50) in CPRD. For secondary amenorrhoea, HRs were 1.71 (95% CI: 1.34, 2.18) in EpiChron and 1.24 (95% CI: 1.17, 1.30) in CPRD and for hypermenorrhoea 1.40 (95% CI: 1.23, 1.60) in EpiChron.

Conclusions: In this PASS which evaluated the safety of Comirnaty for 37 AESIs in >12 million vaccinated individuals, there was no increased risk for most AESIs. However, adjusted HRs for a few cardiac events and menstrual disorders were slightly elevated among vaccinated in some data sources. Potential explanations for these results include the divergence of cumulative incidence of cardiac events with long risk windows and differences in the composition of unvaccinated individuals over time.

Background: Real-world data (RWD) is essential for post-licensure monitoring of vaccine safety, as pre-licensure trials are often limited in size, population diversity, and follow-up duration. Regulatory agencies rely on real-world evidence to identify potential safety signals but emphasize the need for validation of adverse events of special interest (AESI). Validation primarily involved reviewing electronic medical records to verify disease codes and classifying the events based on LOC as cases or non-cases. The Vaccine Monitoring Collaboration for Europe (VAC4EU) developed a validation pipeline designed to apply Brighton Collaboration (BC) case definitions adapted for RWD in a harmonized, reusable manner.

Objectives: To develop and implement a comprehensive framework for validating AESIs in RWD studies, ensuring standardization and adaptability based on BC case definitions.

Methods: VAC4EU collaborators developed a structured approach to validating safety outcomes. These definitions provide a standardized method for assessing LOC, but implementation in RWD required adaptations. Validation preparation followed a stepwise approach: reviewing and adapting BC definitions with expert input, designing and testing REDCap data collection forms, training abstractors with real-time feedback, and validating dummy cases to refine validation logic. Inter-rater reliability was assessed using Cohen’s kappa (κ) to measure agreement between abstractors and expected results.

Results: For COVID-19 safety studies, VAC4EU validated 16 AESIs, with BC preexisting case definitions available for 13. A total of 78 dummy cases and 15 REDCap forms were created, and 33 abstractors were trained across various event categories. During training, 605 dummy cases were abstracted, with discrepancies between the abstractors' results and the expected results observed in 84 cases (κ = 0.72), particularly for thrombosis with thrombocytopenia syndrome (TTS). Errors were most frequent in laboratory data for TTS and alternative diagnoses for myocarditis/pericarditis. Concordance improved with training, and performance was higher among medical doctors compared to non-medical doctors.

By the end of 2024, validated AESIs included 170 Guillain-Barré Syndrome, 113 narcolepsy, 352 immune thrombocytopenia, 263 TTS, 2,133 myocarditis, 2,593 pericarditis, and smaller counts for other events.

Conclusions: The VAC4EU validation pipeline provides a standardized framework for validating safety outcomes, emphasizing the need to adapt BC definitions to RWD and train abstractors effectively. However, the lack of direct chart abstraction in most data sources limits validation, as reliance on electronic medical records may result in incomplete clinical details.

Background: Myocarditis and pericarditis are recognized as possible adverse events following COVID-19 mRNA vaccines, including mRNA-1273. Previous studies indicate these events predominantly occur in young males and after the second dose of the vaccine. However, other risk factors remain to be elucidated.

Objectives: The study aim was to identify associated risk factors in individuals experiencing myocarditis and/or pericarditis after vaccination with mRNA-1273.

Methods: This case-cohort study utilized secondary healthcare data from 5 VAC4EU network data experts and access partners (DEAPs) across 4 European countries (national registries in Denmark and Norway, VID (Valencia region), and SIDIAP (Catalonia region) in Spain and CPRD Aurum in the United Kingdom (UK)). Inclusion criteria for the base cohort were receipt of at least one dose of mRNA-1273 between 1/6/2021 and 8/31/2024, a minimum one-year enrolment in the participating database before vaccination, and no diagnosis of myo- or pericarditis in the six months preceding vaccination. Cases were individuals diagnosed with myo- and/or pericarditis within 30 days following mRNA-1273 vaccination, and 1:4 calendar-time matched controls were selected from the base cohort. We conducted multivariable logistic regression to estimate odds ratios (ORs) and corresponding 95% confidence intervals (CIs), aiming to identify associated risk factors for myo- and/or pericarditis. Analyses were performed per database and considered age, sex and previous SARS-CoV-2 infection, which are known risk factors, as well as potential confounders selected in a variable selection procedure.

Results: All databases included 5 to 7 million individuals, of which 0.7 to 3.9 million were mRNA-1273-exposed. Males were overrepresented in both myo- and pericarditis cases, but not in controls. Pericarditis cases had more baseline comorbidities, prior ER visits and hospital admissions than matched controls. Myocarditis cases showed no such differences. No differences in vaccination history (against either COVID-19 or other diseases (e.g., influenza)) were observed between myo- and pericarditis cases and their controls. In multivariable logistic regression analyses, a history of cardiac comorbidities was associated with a higher risk of developing myo- and/or pericarditis in 3 databases [UK: OR 2.2 (95% CI 1.1-4.2); VID: OR 5.0 (95% CI 2.5-9.9); Norway: OR 8.5 (95%CI 3.8-19.3)]. Hospital visits in the previous year were associated with a higher risk of myo- and pericarditis in two databases [Denmark: OR 1.9 (95% CI 1.0-3.5); VID: OR 2.6 (95% CI 1.2-5.7)].

Conclusions: History of cardiac comorbidities and prior healthcare utilization were identified as risk factors for developing myo- or pericarditis after mRNA-1273 vaccination.

Background: Paxlovid is an oral combination of protease inhibitors nirmatrelvir and ritonavir licensed in January 2022 in Europe to treat COVID 19 in patients who do not require supplemental oxygen and are at increased risk for progression to severe COVID 19. Here, we describe preliminary results from a post-authorization safety study to assess the safety of Paxlovid in pregnancy because clinical trials excluded such patients, and EU and UK summary of product characteristics (SmPCs) do not recommend its use in pregnancy.

Objectives: To assess the risk of adverse pregnancy, offspring, and maternal outcomes in women exposed to Paxlovid or to other COVID-19 treatments during pregnancy.

Methods: This ongoing cohort study used data from SIDIAP (Spain), CPRD Aurum (UK), and SNDS (France) from January 2022 until December 2023/January 2024.The ConcePTION common data model and common analytics were used in SIDIAP and CPRD. Aggregated user counts from the general population were obtained via Open Medic in France.

The study included pregnant patients who had been enrolled in the data source for ≥12 months, had COVID-19, and started treatment up to 6 days after COVID-19 diagnosis, and their offspring. Follow-up started at the first treatment during pregnancy and ended at the earliest of the following: 6 months after the end of pregnancy (age 1 year for offspring), outcome, death, disenrollment, or end of study period.

Primary outcomes were spontaneous abortion, elective termination, stillbirth, preterm delivery, major congenital malformations, intrauterine growth retardation/small for gestational age, gestational diabetes, gestational hypertension, postpartum hemorrhage, and maternal death. Exploratory outcomes were empirically assessed from diagnoses in eligible Paxlovid-exposed individuals in the 30 days after exposure.

Results: In SIDIAP and in CPRD, no eligible pregnancy was exposed to Paxlovid; 1≤n≤4 were exposed to molnupiravir in CPRD; they had unknown outcomes. No other primary or exploratory study outcomes were observed. In France, 206,069 patients had ≥1 Paxlovid dispensing (≈70% aged ≥60 years; >55% female); fewer patients used anakinra (5,895; ≈40% aged ≥60 years, ≈50% female) or tocilizumab (22,306; ≈60% aged ≥60 years, ≈70% female); use in pregnancy will be assessed in future analyses.

Conclusions: Although the study period was relatively short, the lack of Paxlovid-exposed pregnancies is consistent with the literature and in alignment with recommendations in the EU and UK SmPCs. Future reports will include a longer study period and individual-level data from SNDS in France.

Background: Myocarditis and pericarditis are recognized as possible rare adverse events that may occur following COVID-19 mRNA vaccines, including mRNA-1273.

Objectives: The aim was to characterize the clinical course of myo- and pericarditis of varying origin, including cases associated with mRNA-1273 vaccination and cases not associated with COVID-19 vaccination and to identify risk factors for severe outcomes (cardiac or thromboembolic complications, severe hospital outcomes, all-cause hospital readmission, and death).

Methods: This cohort study utilized secondary health data from the VAC4EU network through five data experts and access partners across four European countries (national registries in Denmark and Norway, VID (Valencia region) and SIDIAP (Catalonia region) in Spain and CPRD Aurum in the UK). It included individuals diagnosed with myo- or pericarditis within 30 days after mRNA-1273 vaccination (exposed) and those that did not receive any COVID-19 vaccine in the 30 days before myo- or pericarditis onset (unexposed), and were enrolled in the database for at least a year. Different follow-up windows at 1, 3, 6 and 12 months after myo- or pericarditis onset were considered in the analysis. Cox regression analyses were used to estimate hazards ratios (HRs) for sequelae.

Results: The number of myo- and/or pericarditis cases in each database varied from 2,700 to 6,908, of which 90 to 158 were associated with mRNA-1273. Exposed cases had lower prevalence of pre-existing comorbidities and shorter hospital stays than unexposed cases. Two percent (2%) of the exposed myocarditis cases compared to 5% of unexposed cases were severe. None of the post-mRNA-1273 pericarditis cases were severe. Cox regression models of the combined exposed and unexposed cases showed that age (HR range: 1.00-1.03), Charlson Comorbidity Index (CCI) score (HR range: 1.18-2.41), and history of cardiac drug use (HR range 1.24-4.00) were risk factors for cardiac complications in both myo- and pericarditis cases across follow-up windows. CCI score (HR range: 1.09-2.11) and previous healthcare use (HR range: 1.13-6.89) were risk factors for severe hospital outcomes and hospital readmission in both myo- and pericarditis cases. Age (HR range: 1.04-1.11) and CCI score (HR range: 1.30-2.32) were the most apparent risk factors for death in both myo- and pericarditis cases.

Conclusions: Post-mRNA-1273 myocarditis cases were less severe and had fewer pre-existing comorbidities compared to unexposed cases. Risk factors for cardiac complications, severe hospital outcomes, and mortality after myo- or pericarditis diagnosis include older age, higher CCI score, and previous healthcare use.

Involving patient communities in vaccine development can enhance the relevance, trust, and effectiveness of vaccines. These communities offer unique perspectives on patient needs, experiences, and preferences, helping to ensure that vaccines address real-world health concerns. Involving patients can also reduce vaccine hesitancy through increased awareness and vaccine literacy. This session explores these themes, aims to map existing initiatives in this area and needs for further education and training.

Background: SIDIAP, one of Europe’s largest primary care databases, contains comprehensive real‑world clinical data for more than six million people in Catalonia. Integrating SIDIAP into the ConCEPTION Common Data Model (CDM) enables harmonised, privacy‑preserving analytics across the VAC4EU network, supporting high‑quality vaccine safety and effectiveness studies. This transformation aims to enhance data interoperability, accelerate evidence generation, and strengthen European public health capabilities.

Methods: The transformation followed a structured process comprising semantic mapping of local coding systems (e.g., ICD‑10, ATC), structural harmonisation to the ConCEPTION CDM, and detailed ETL design using Python‑based scripts within containerised environments. Specification tables were completed for each origin table to document mappings, transformations, and metadata. Multi‑level quality control (QC) checks—including structural, logical, and clinical plausibility assessments—were conducted using dummy data and the current SIDIAP instance. Additional linkages, including mother–child connections, were established through deterministic matching. Data access procedures ensured GDPR‑compliant, pseudo‑anonymised, ethics‑approved workflows.

Results: SIDIAP was successfully mapped into a CDM framework comprising 6 routine healthcare tables, 3 surveillance tables, 3 linkage tables, and 4 metadata tables. The resulting harmonised dataset supports population‑representative research with rich demographic, clinical, medication, laboratory, lifestyle, and reproductive health information. External linkages (e.g., hospital data, PADRIS) deepen clinical context. Integration enabled participation in multi‑country studies across VAC4EU, including Pfizer, Moderna, Janssen, AZ, Hipra and EMA‑funded PASS projects, as well as GVDN initiatives. This CDM‑based transformation facilitates rapid, comparable, real‑time pharmacoepidemiological analyses, improving vaccine safety monitoring and regulatory readiness.

Conclusions: Integrating SIDIAP into the ConCEPTION CDM marks a major step forward for European real‑world evidence generation. The CDM enhances data quality, structure, and interoperability, enabling faster, robust, and internationally aligned research—particularly for vaccine safety. Through VAC4EU, SIDIAP now contributes to a federated research ecosystem capable of advanced analytics, rapid signal detection, and cross‑country comparability. Future directions include expanding linkages, developing real‑time analytical pipelines, and applying AI‑driven methods to support proactive public health decision‑making.

The use of large language models in healthcare is rapidly growing. In this work, we are interested in analyzing the capabilities of large language models in filling questionnaires related to clinical practices, where the information needed to answer each specific question is contained in the clinical records of a given patient. We present preliminary experiments on a publicly available dataset in the English language, with very promising results that show the great potential of the approach and motivate further research in this challenging direction.

As part of the lifecycle benefit-risk assessment of vaccines, we are conducting a post-authorisation safety study (PASS) utilizing real-world data to characterize and assess the safety profile of JCOVDEN.

Objectives: As part of the JCOVDEN PASS, this second feasibility study aimed to i) describe JCOVDEN patterns of use compared to other COVID-19 vaccine brands, ii) characterise vaccinated individuals, iii) describe follow–up time and reasons for censoring, and iv) conduct time-to-onset analyses for 36 pre-specified adverse events of special interest (AESIs).

Methods: This retrospective observational study used electronic healthcare data from two European countries (the Netherlands [PHARMO Data Network] and Spain [VID, SIDIAP]) collaborating in the VAC4EU consortium. Data were harmonised across data sources using the ConcePTION common data model. Analytical steps included syntactic and semantic harmonisation of data, implementation of the epidemiological study design, and statistical analysis.

Descriptive statistics were used. Unadjusted incident rates (IRs) of AESIs (per 10.000 person-years) were compared to 1st feasibility assessment and to the 2018 background rates published in the ACCESS study.

Results: A total of 510,145 individuals received the first dose of the JCOVDEN vaccine in line with ECDC Vaccine Tracker data for the Netherlands and Spain. The first dose was predominantly administered to those aged 40-49 in SIDIAP and VID and 20-29 in PHARMO; female vaccinated individuals were 36.9% in PHARMO, 44.1% in SIDIAP, and 46.2% in VID. Between 0.4 and 1.2% of vaccinated individuals were pregnant across data sources. Most individuals (>65%) received a COVID-19 mRNA vaccine as a second dose approximately six months after initial vaccination with JCOVDEN.

The AESIs were identified using disease codes (ICD10CM, ICD9CM, ICPC) and free texts and our feasibility analyses identified clinically relevant AESIs. Compared to the 1st feasibility assessment, this assessment exhibits improved specificity in centralised code lists, programming enhancements, and refined study population selection. IRs of AESIs were also consistent with 2018 ACCESS background rates.

Conclusions: This feasibility study identified over half a million individuals vaccinated with JCOVDEN. While the data from the three data sources are suitable for the planned final analysis, statistical power may be limited for very rare AESIs for the final comparative analysis.

Myocarditis and pericarditis are recognized as possible adverse events of special interest (AESIs) following mRNA-1273 vaccination. Prior research indicates these events predominantly occur in young males and after the second dose of the vaccine. However, comprehensive studies on other potential risk factors are lacking.

Objectives:

These interim analyses sought to identify possible risk factors for myocarditis and pericarditis among individuals vaccinated with mRNA-1273.

Methods:

This case-cohort study utilized secondary health data from five VAC4EU network data access partners across four European countries (national registries in Denmark and Norway, VID and SIDIAP in Spain and CPRD Aurum in the UK). Inclusion criteria for the base cohort were receival of at least one dose of mRNA-1273 between 6 January 2021 and 31 August 2024, a minimum one year enrolment in the participating databases before vaccination, and no diagnosis of myocarditis/pericarditis in the six months preceding vaccination. Cases were identified within 30 days following vaccination using diagnostic codes, and a 1:4 calendar-time matched control sample was selected from the base cohort. Preliminary analysis included demographic assessments, medical history (comorbidities, medication use, healthcare utilization), and vaccination history for both cases and controls. Federated analyses were performed using the ConcePTION common data model.

Results:

The analysis included the following number of mRNA-1273 recipients (and respective myocarditis and pericarditis cases): 679,702 in Danish national registries (45 and 52 cases); 2,120,376 in VID (20 and 70 cases); 266,558 in SIDIAP (<5 cases each); and 1,544,983 in Norwegian registries (80 and 138 cases). Data from CPRD Aurum (UK) were pending at the time of this report. The proportion of male cases was 70-89% for myocarditis and 65-79% for pericarditis, compared to a more balanced sex distribution in controls (up to 54% males). Myocarditis cases were younger than controls, with no apparent differences in medical history. Pericarditis cases had more pronounced healthcare utilization and comorbidities compared to controls.

Conclusions:

Preliminary findings suggest age and sex to be potential risk factors for the occurrence of myocarditis/pericarditis after mRNA-1273 vaccination. In addition, comorbidities and prior healthcare utilization may be potential risk factors for the occurrence of pericarditis.

Myocarditis and pericarditis are among the identified risks following COVID-19 mRNA vaccination, including the mRNA-1273 vaccine. Most cases occur within 14 days following the second dose of this vaccine, and incidence is highest among young males aged 18 to 39. Additional data are needed to characterize risk factors, natural history and long-term outcomes of these events.

Objectives:

(1) To identify possible risk factors for myocarditis and pericarditis following mRNA-1273 vaccination, and (2) To examine the clinical course of myocarditis and pericarditis of varying origin and to identify prognostic factors in the course of myocarditis and pericarditis.

Methods:

Performed within the VAC4EU association, the study will draw on electronic healthcare records from five data access partners (DAPs) located in Denmark (Aarhus University), Norway (University of Oslo), Spain (IDIAP and FISABIO) and the United Kingdom (DSRU) to create a source population representative of the European population overall. The study is performed using the published ConcePTION common data model (CDM) for all DAPs and analyses will be run locally before performing a pooled meta-analysis of outcomes. All cases will be validated based on criteria from the Brighton Collaboration Case Definition. A case-cohort design will address Objective (1), and will include all cases of myocarditis and pericarditis following mRNA-1273 vaccination, as well as a random sub-cohort of individuals who have received this vaccine as controls. A Cox model with non-proportional hazards, including variables for demographic characteristics, medical history and vaccination history, will be used to investigate risk factors in the case-cohort design. Objective (2) will be addressed through a cohort study including all cases of myocarditis and pericarditis in the data. A Cox model will be used to compare cases following mRNA-1273 vaccination to cases not following COVID-19 vaccination for outcome measures such as cardiac and clinical outcomes, hospital readmission, and death, in this cohort.

Results:

As of April 2022, the source population includes over 6 million vaccinated individuals, and in each study design we expect to include 150 to 1500 cases. Over the course of 2023 and 2024, this study will continue to include individuals in the analyses sets, as to most accurately describe risk factor profiles of interest.

Conclusions:

By drawing from electronic healthcare records from several DAPs and using the ConcePTION CDM, the design of this study allows for identification of risk factors for the development of myocarditis and pericarditis and for comparing the clinical course of cases following mRNA-1273 vaccination to cases not following vaccination.

The COVID-19 pandemic underscored the need for rapid evidence generation to inform public health decisions beyond the limitations of conventional clinical trials. This report summarises presentations and discussions from a conference on the role of Real-World Evidence (RWE) in expediting vaccine deployment. Attended by regulatory bodies, public health entities, and industry experts, the gathering was a collaborative exchange of experiences and recommendations for leveraging RWE for vaccine deployment. RWE proved instrumental in refining decision-making processes to optimise dosing regimens, enhance guidance on target populations, and steer vaccination strategies against emerging variants. Participants felt that RWE was successfully integrated into lifecycle management, encompassing boosters and safety considerations. However, challenges emerged, prompting a call for improvements in data quality, standardisation, and availability, acknowledging the variability and potential inaccuracies in data across diverse healthcare systems. Regulatory transparency should also be prioritised to foster public trust, and improved collaborations with governments are needed to streamline data collection and navigate data privacy regulations. Moreover, building and sustaining resources, expertise, and infrastructure in LMICs emerged as imperative for RWE-generating capabilities. Continued stakeholder collaboration and securing adequate funding emerged as vital pillars for advancing the use of RWE in shaping responsive and effective public health strategies.

COVID-19 pandemic crowned the crucial role of real-world-evidence to promptly fuel researchers’, national authorities’, and regulators’ preparedness for important and urgent healthcare decision-making processes, enriching society’s awareness over the fundaments of decisions through solid communication based on big data.

The European Medicines Agency funded the Covid Vaccines Effectiveness study, where effectiveness and waning of immunity of different homologous and heterologous COVID-19 vaccines combinations in response to mild and severe SARS-CoV-2 infection outcomes were retrospectively analysed for primary and booster vaccinations in more than 20 million adults and 300,000 children from 6 pan-European electronic healthcare data sources (United Kingdom, Spain, Italy, Netherlands) since the beginning of the vaccination campaign to December 2021/February 2022.

Based on the primary or booster vaccinations, vaccinees were matched 1:1 to their respective control. Heterologous and homologous primary vaccinations in adults were directly compared. Children's homologous primary vaccinations were matched to unvaccinated. Homologous and heterologous booster regimens were compared to non-boosted, for adults and pre-adolescents with the same first dose and meeting strict matching criteria (primary/booster vaccination schedules/dates, age, sex, region, and comorbidities among those without prior SARS-CoV-2 infection). Effectiveness was calculated as 1 minus the Hazard ratio after inverse probability weighting by multiple potential confounders (Cox models) of severe COVID-19-related outcomes and multiplied by 100 (1-95% confidence intervals).

Our analyses support health institutions' recommendation of mixing different brands for primary vaccinations since no threatening differences in effectiveness were found across different homologous and heterologous combinations. Independently of the type of primary vaccination, mRNA booster doses offered clear protection against severe post-infection events during the Delta and the early Omicron variants, both in the general population and in people with immunodeficiency and cancer, subjects at high risk of severe COVID-19, adding also important clinical evidence for the benefit-risk assessment of vaccinations in these generally less represented populations.

Background: Children were less affected by COVID-19 at the start of the pandemic. Little is known about the severity of COVID-19 infection in children on a population level.

Objective: To estimate the incidence rate (IR) of SARS-CoV-2 infections stratified by severity and vaccine intake in the general paediatric population. 

Methods: Multi-database cohort study using data from 6 Italian and Spanish population-based electronic healthcare records databases. The study period started the 1st of January 2020 until the latest data available for each data source. SARS-CoV-2 infections were obtained from PCR or antigen tests, or diagnosis codes. Four COVID-19 severity levels were distinguished: 1) without hospitalization (non-severe), 2) hospitalization, 3) intensive care unit admission, and 4) death. Incidence rates (IRs per 100,000 person-years (PY)) and exact 95% confidence intervals for COVID-19 disease severity levels were estimated prior to vaccination and after the first dose (excluding days 0-7 after vaccination).

Results: The total study population comprised 4,447,460 children 0-18 years of age (54% women), median age 6-9 years across the 6 databases. In Italian databases, the peak of COVID-19 infections was in December 2021 and January 2022. In children 5-11 years, the incidence rate of non-severe COVID-19 disease was highest in December 2021-January 2022: 85,214-248,087/100,000 PY. In 12 to 18-year-olds, the incidence rate of non-severe COVID-19 ranged between 41,495-162,869/100,000 PY (December 2021 and January 2022, respectively). In Spanish databases, the peak of non-severe COVID-19 infection in children from 5-<12 years-old was 84,334-154,083/100,000 PY in December 2021-January 2022. In adolescents, the highest rates of non-complicated COVID-19 were from 74,506-154,000/100,000 PY. Severe cases of COVID-19 infection in the Spanish general population 0-18 years accounted for less than 0.9% of the cases whereas, in Italy, from 0.2 to 2.6% across data sources.  Comirnaty (Pfizer-BioNTech) was the most administered 1st dose vaccine brand followed by Spikevax (9-20%). Non-adjusted rates of COVID-19 dropped substantially one week after vaccination in all the data sources.

Conclusions: Incidence rates of non-severe paediatric COVID-19 infection reached the highest level in December 2021 and January 2022, aligned with the Omicron peak. Severe cases of COVID-19 were low in children. Post-vaccination crude infection rates were very low.

Literature suggests mRNA-based COVID-19 vaccines elevate the risk of myocarditis in young individuals, with a higher risk after the second dose. There is less clarity for third doses and adenovirus-platform vaccines.

Objectives: Report the risk of myocarditis associated with dose 1,2, and 3 of 4 EMA-approved COVID-19 vaccines. 

Methods: We conducted a self-controlled risk interval (SCRI) study using primary and secondary healthcare data from Italian (ARS), Spanish (BIFAP, FISABIO, SIDIAP) and British (CPRD) datasources (DS). Exposed cases with ≥1 year of follow-up before 1 September 2020 (study start) were eligible. Data were extracted from study start to the end of data availability (December 2021 (ARS) - April 2022 (BIFAP)). Exposures were doses 1, 2, and 3 of the Pfizer (PF), Moderna (MO), AstraZeneca (AZ), and Janssen (JJ) COVID-19 vaccines. Outcome was myocarditis (MC) based on diagnosis codes. The SCRI used a 60-day control window starting 90 days before dose 1 and dose-specific 28-day (main analysis) and 7-day (sensitivity analysis) risk windows. Analyses were stratified by vaccine brand and dose, adjusted for calendar time in 30-day periods, and pooled across DS with random effects meta-analysis.

Results: The study population comprised 578 MC cases among 29,563,667 vaccinated individuals. The median distance between doses was 21-42 days for dose 1&2 and 189-197 days for dose 2&3. The MC risk was significantly increased in the 28 days after dose 2 of mRNA vaccines (PF IRR=1.85, 95%CI: 1.32-2.60; MO IRR=2.39, 95%CI 1.40-4.10) but not dose 1 or 3. The 7-day sensitivity analysis suggested higher risks for MC during weeks 1 and 2 after PF dose 1, and during week 1 after dose 2. For MO vaccine, during weeks 1 and 4 after dose 2. For AZ vaccine, during week 2 after dose 1 and during week 2 after dose 2. For JJ, during week 4 after dose 1. Risks were higher in men below 30 years for mRNA vaccines, but not for AZ. PF vaccine, dose 3 was not associated with an increased risk of myocarditis in either below or above 30 years., For MO vaccine, the risk is elevated (not significantly) after dose 3 in those under 30 years, but not in those above 30.

Conclusions: We observed an increased risk of myocarditis following mRNA-based vaccines as well as adenovirus platform vaccines in weekly intervals. The weekly pattern of myocarditis risk following adenovirus platform vaccines differs from the pattern in mRNA platform vaccines. Pfizer vaccine is not associated with an increased risk of myocarditis after dose 3. For Moderna, the risk might be increased.

Tools to improve transparency in reporting study design and variable definitions have been shared in the scientific community (e.g., STaRT-RWE). Tools to improve transparency on implementation in the study script are less common. Complex study protocols for multidatabase distributed studies require study-tailored scripts, but timeliness is needed to support regulatory decisions, so efficiency is required. VAC4EU is an international association of institutions in Europe that supports robust and timely evidence generation on the effects of vaccines.

Objectives: To illustrate a methodology supporting transparent documentation of programming implementation in study scripts

Methods: We report on the application of the methodology in a study on safety of COVID-19 vaccines funded by the European Medicines Agency (ROC 20-readiness).

A sequence of intermediate datasets (IDs) were designed to go from the common data model (CDM) to the final tables with aggregated results to be shared centrally. Each ID was documented with a) unit of observation (UoO) b) number of observations for each UoO (NxUoO), classified as 1, >=1, or >=0 c) codebook, including variable names, format, vocabulary and rules for calculation.

A direct acyclic graph (DAG) was drawn representing the program tree: steps were represented as circles, datasets as boxes. Circles had incoming arrows from input datasets, and outcoming arrows to output dataset(s). Based on specifications, synthetic versions of some IDs were generated before development started.

Scientific programmers (SP) and statisticians (STAT) started programming in parallel from multiple points of the DAG using synthetic IDs. When all the steps were ready, the program was released to data partners (DPs) for local execution.

Results: 231 IDs were designed. Most of them (225, 97%) were selections from the instance of the CDM, based on lists of codes or strings: UoO was the original record. Out of the other 25 IDs, UoO was a person for 13 (52%), an event for 5 (20%), and a stratum of categorical variables for 7 (28%). In IDs where UoO was an event or a stratum, NxUoO was 1. Among the13 IDs having a person as UoO, NxUoO was 1 for 7 (54%), >= 0 for 4 (31%), >= 1 for 2 (15%).

During the specification phase, investigators and SP/STAT could identify cases when the protocol was underspecified and add clarifications, possibly with support of DP. During execution, bugs were tracked back to steps, and DP could access locally generated ID and support SP/STAT in debugging.

Conclusion: We introduced and tested a tool to improve transparency, and allow a higher efficiency, in development and test of study scripts.

The roll-out of the novel COVID-19 vaccines in a large population across multiple countries called for comprehensive monitoring of the safety of these vaccines. The multi-country implementation of a cohort event monitoring study with a common protocol and pooled data shared in real-time provides additional monitoring.

Objective: To report real-time incidence rates of adverse events following immunization (AEFI), serious adverse reactions, and adverse events of special interest (AESI) after receiving one or more EMA-approved COVID-19 vaccines doses.

Methods: A prospective cohort event monitoring study was conducted in 13 European countries to monitor the safety of first, second, and booster doses of the EMA-approved COVID-19 vaccines in both the general population and clinical subgroups of special interest (children/adolescents, pregnant, lactating, immunocompromised, prior SARS-CoV2 infection and allergy). Participants can be included in more than one subset. Participants registered online within two days of receiving the vaccine and reported demographic data, medical history, and AEFI up to six months after vaccination. Incidence rates were calculated for all AEFI after the first and second dose for the general population and for the first booster in the population of special interest.

Results: 642292 participants were included between 20 December 2020 and 30 September 2022 in the general population subset receiving dose 1; 466010 (72.6%) provided follow-up data after dose 2. Of the 642292 general population participants, 495383 (77.1%) and 381876 (81.9%) reported experiencing at least one AEFI after dose 1 and 2, respectively. Only 2001 (0.3%) participants reported experiencing at least one AESI after dose 1 and 1522 (0.3%) after dose 2. A total of 3142 (0.5%) participants reported at least one serious adverse event after dose 1 and 1697 (0.4%) after dose 2. The special interest subgroups included 2513 participants; 127 children ( 5.1%), 351 pregnant (14.0%), 123 lactating (4.9%), 889 prior SARS-CoV2 infection (35.4%), 205 immunocompromised ( 8.2%) and 818 allergy (32.6%). Of these subgroups, participants reported experiencing at least one adverse event (respectively 50, 39.4%; 200, 57.0%; 97,78.9%; 605,68.1%; 128,62.4%; 622,76.0%) after the booster dose.

Conclusion: While a majority of the participants reported experiencing at least one AEFI after vaccination, only a small proportion was considered an AESI or serious event. This is in line with the data reported from clinical trials and other cohort event monitoring studies. A common data model has been developed for further analysis of reported events, comparisons between groups, and confounding.

Safety of COVID-19 vaccines in people with prior SARS-CoV-2 infection has not been investigated in pivotal RCTs. Herein, we monitored COVID-19 vaccines' safety in those people through active surveillance and compare descriptive results with the general population.

Methods: In a prospective cohort of vaccinees with prior SARS-CoV-2 infection, we measured the frequency of local/systemic and serious adverse drug events (ADRs) following doses 1, 2 and booster of EMA-approved COVID-19 vaccines using data from the ""Covid Vaccine Monitor” (CVM) study until December 2022. The results (without adjustments) were descriptively compared with those from the general population.

Results: 2,594 and 889 vaccinees with prior SARS-CoV-2 infection following the 1st and the booster dose, respectively, were enrolled. Most included vaccinees received Vaxzevria (37.1%) as a 1st dose and Comirnaty (57.5%) as a booster dose. Among 1st and 2nd dose recipients, 87.9% and 45.7%, respectively, experienced at least one ADR during a 6-month follow-up period. Injection site pain was the most frequently reported local ADR following both doses 1 (56.7%) and 2 (21.6%) of any vaccine. Systemically, fatigue (56.8% vs. 21.7%), headache (54.8% vs. 18.3%), myalgia (53.8% vs. 17.6%), and malaise (53.5% vs. 23.0%) were the most frequently reported. Similar findings were found after booster doses administration (injection site pain: 43.3%; fatigue: 39.3%; headache: 29.8%; myalgia: 28.3%; malaise: 28.0). Serious ADRs occurred in 0.2% and 0.1% of vaccinees following doses 1 and 2, respectively, and 0.1% following the booster dose. As for the general population (dose 1= 30,175; dose 2= 20,560), 67.7% and 49.1% reported at least one ADR following doses 1 and 2, respectively. The most commonly reported local/systemic ADRs following doses 1 and 2, across all vaccine brands, were injection site pain (36.2% vs. 21.9%), fatigue (35.7% vs. 23.2%), headache (33.1% vs. 17.9%), myalgia (32.9% vs. 18.5%) and malaise (30.9% vs. 19.0%). Serious ADRs were reported following doses 1 and 2, respectively, in 0.2% and 0.1% of vaccinees.

Conclusions: Descriptive analyses from this study showed high frequencies of local/systemic ADRs following dose 1 in vaccinees with prior COVID-19. Injection site pain, fatigue, headache, malaise and myalgia were the most frequently reported local/systemic ADRs, as for general population but with a lower frequency. Lower rates of local/systemic ADRs were reported following dose 2 of any vaccine. The reporting of ADRs for the booster dose was similar to that for dose 1. Higher percentages of local/systemic ADRs were observed following the booster as compared to dose 2 of any vaccine. Serious ADRs were very rare.

As part of the lifecycle benefit-risk assessment of vaccines, a post-authorisation safety study (PASS) using real-world data was required by EMA-PRAC to characterise and evaluate the safety of the JCOVDEN.

Objectives: The first phase of the study was a feasibility assessment i) to describe JCOVDEN patterns of use compared to other COVID-19 vaccine brands, ii) to characterise vaccinated individuals, iii) to describe follow–up time and reasons for censoring, and iv) to conduct time-to-onset analyses for 17 selected adverse events of special interest (AESIs).

Methods: This retrospective observational study used electronic healthcare data from two European countries (the Netherlands [PHARMO Data Network] and Spain [VID, SIDIAP]).

A common protocol and the ConcePTION common data model pipeline were used to perform the data management and analyses. The pipeline encompassed the syntactic and semantic harmonisation of data, the implementation of the epidemiological study design, and the statistical analysis.

We report frequencies and percentages, means and standard deviations (SD), medians and interquartile ranges (IQR). The unadjusted incident rates (IRs) per 10,000 person-years of the selected AESIs were calculated and benchmarked to the 2018 background rates published in the ACCESS study.

Results: A total of 527,513 individuals received the first dose of the JCOVDEN. Almost all administration of JCOVDEN occurred in Q2-Q3 2021 (98%). More than 80% of the COVID-19 vaccines administered in 2021 were mRNA vaccines. The relative use of the different COVID-19 vaccine brands was consistent with that reported by the European Centre for Disease Prevention and Control (ECDC). In VID and SIDIAP, JCOVDEN was administered more frequently in individuals aged 40-49 years. Around 55% of JCOVDEN vaccinees were females. Most individuals with a first dose of JCOVDEN received a booster dose with one of the mRNA vaccines about 6 months later. For PHARMO, only vaccine uptake and follow-up data were available for this first feasibility assessment.

In SIDIAP and VID, the unadjusted IRs for most assessed AESIs were consistent with those expected from the background IRs reported in the ACCESS study.

Conclusions: This feasibility analysis showed that the planned PASS is feasible but faces limitations (e.g., the number of persons who received JCOVDEN, channelling of COVID-vaccines over time to different age groups and heterologous schemes) that will be considered by design during the full implementation of the safety study.

The COVID-19 emergency has accentuated the importance of conducting post-authorisation safety studies (PASS) in the context of monitoring vaccines’ effectiveness and safety.  The PASS studies are conducted in a collaborative manner within the Vaccine monitoring Collaboration for Europe (VAC4EU) consortium. PASS study teams are led by scientific coordinators and monitored by study managers to implement and execute the research protocols. We aim to describe and discuss the challenges and lessons learnt from the perspective of the study managers of PASS studies implemented during the COVID-19 pandemic.

Objectives:
We describe challenges and learnings from the management of selected VAC4EU PASS studies for COVID-19 vaccine monitoring studies, with the goal of improving the quality of COVID-19 vaccine post-marketing monitoring research.

Methods:
We conducted interviews with consortium members involved in #8 studies upon the completion of each of the regulatory reporting cycles to assess the challenges in the management and coordination of the research activities.

Results:
The dynamic regulatory environment due to shifting vaccine registration strategies and administration prioritization, emerging COVID-19 vaccine safety signals, a lack of unified global regulatory pathways as well as the evolution of SARS-CoV-2 added complexity to the execution of the studies.

The main challenge in managing and coordinating multi-centre PASS studies for COVID-19 vaccines was meeting the study reporting timelines, as mandated by the regulators. The demanding schedule, urgent onboarding of participating data access providers (DAPs), data availability, and data refresh frequencies were the main factors for the constant need for flexibility to meet these deadlines. Due to the large number and heterogeneity of study team members and the continuously evolving regulatory context, communication challenges among different study working groups were also identified.

Moreover, resource planning for the study execution phase and staff capacity building in the context of the pandemic situation had an impact on the timely and smooth execution of the studies.

Conclusions:
A variety of challenges and learnings were identified while coordinating and managing the multi-centre COVID-19 vaccine monitoring studies. The successful conduct of such studies requires careful planning and a dedicated collaborating multi-skilled team to execute and monitor study activities, as well as flexibility and fluent communication among the study members.

The self-controlled risk interval (SCRI) design lent itself well to the rapid safety evaluation of COVID-19 vaccines, but limited post-vaccination follow-up necessitated a pre-vaccination control window. This increases the risk of time-varying confounding, especially for later doses. Negative control outcomes (NCOs) are often used to assess unmeasured confounding, but they are rarely applied to SCRIs.

Objectives: Analyse two NCOs to assess unmeasured confounding in a COVID-19 vaccine safety SCRI on myocarditis.

Methods

We used primary and secondary healthcare datasources (DS) from Italian (ARS), Spanish (BIFAP, FISABIO, SIDIAP), and British (CPRD) databases. Exposed cases with ≥1 year of observation before 1 September 2020 (study start) were eligible. Data were extracted from study start to the end of data availability (December 2021 (ARS) - April 2022 (BIFAP)). Exposures were doses 1/2 of the Pfizer (PF), Moderna (MO), AstraZeneca (AZ), and Janssen (JJ) COVID-19 vaccines. Outcomes were myocarditis (MC), otitis externa (OE; NCO), and non-congenital valvular heart disease (VHD; NCO). These NCOs were chosen because their risk factors were similar to MC except for the association with COVID-19 vaccines.

The SCRI used a 60-day control window starting 90 days before dose 1 and dose-specific 28-day risk windows. Analyses were stratified by vaccine brand, adjusted for calendar time in 30-day periods, and pooled across DS with random effects meta-analysis. We expect a null association between exposure and NCOs and interpret deviations from this as potential unmeasured confounding.

Results: We included 461 MC cases (29% women), 40,732 OE cases (58% women), and 17,187 VHD cases (51% women). MC risk increased significantly after dose 2 of PF (IRR = 1.85, 95%CI 1.32-2.60, I2 = 0%) and MO (IRR = 2.39, 95%CI 1.40-4.10, I2 = 0%). Vaccination did not affect OE risk with little heterogeneity between databasesDS, except for JJ (IRR = 1.26, 95%CI 0.99-1.60, I2 = 42%). We also observed heterogeneity for AZ dose 1 (I2 = 69%) because of an isolated finding in ARS (IRR = 4.80, 95%CI 1.62-14.2). VHD risk decreased after vaccination but there was considerable heterogeneity between databases DS (I2 = 0% for JJ to I2 =93% for PF dose 2). The strongest effects were seen in the databases DS relying entirely (ARS) or partially (FISABIO) on hospital records (discharge and emergency admission) for diagnoses.

Conclusions: The VHD results suggest confounding towards the null, underestimating MC risk, but the null finding for OE does not support the same conclusion. We interpret this as VHD being a poor NCO; it could be a cardiac complication of COVID-19 and thus vaccines protect against it. The degree of unmeasured confounding also varies geographically and across DS. NCOs are a useful tool to detect assess weaknesses this in COVID-19 vaccine safety SCRIs.

The novel coronavirus SARS-CoV-2 caused a pandemic and subsequently brought about a mass vaccination
campaign involving several vaccines. The scale and speed of this campaign necessitated unprecedented
collaboration to overcome challenges for large scale European multinational post-authorization studies of
vaccines.

Objectives:
To explore optimal approaches to harmonize multinational observational studies of adverse events of
special interest (AESIs) in vaccinees of mRNA-1273 in Europe.

Methods:
This study, conducted by the Vaccine monitoring Collaboration for Europe (VAC4EU) association, relies on
secondary routinely collected data from 5 countries selected based on availability of specific data elements.
The databases included national registers (Denmark and Norway), regional administrative databases (Italy’s
Agenzia Regionale di Sanita’ della Toscana [ARS]; Spain’s Sistema d’Informació per al Desenvolupament de la
Investigació en Atenció Primaria [IDIAP]), and the Clinical Practice Research Datalink (CPRD), in the UK.
Source data was extracted and transformed into the standardized format of the ConcepTION common data
model, consisting of semantically harmonized tables of persons, observation periods, vaccines, drugs, and
diagnoses. AESI-defining algorithms, based on diagnoses and/or drug proxies, were developed using cross-
mapping with the automated tool Codemapper, published algorithms, and clinical expertise.
We created scripts to define study variables and populations and perform prespecified analyses. Results
from the analyses were output aggregated data, enabling their transfer to a cloud-based centralized Digital
Research Environment where the report tables are generated, while preserving data privacy.

Results:
We programmed 127 scripts which aimed at ultimately generating 23 report tables covering population
selection, population description, and results from seven different epidemiological designs spanning 5
countries and 38 AESIs. Our federated approach identified 4.7M people who received at least one dose of
mRNA-1273. Over 2.1M individuals met the eligibility criteria for the statistical analyses.

Conclusions:
Combining heterogeneous data sources from 5 European countries, this project used and further developed
a successful analysis pipeline, serving as a model for conducting multinational post-authorization
observational studies of vaccine safety. Comparing and harmonizing outcomes of interest without violating
privacy regulations, our solution automates documentation to ensure reproducibility.

Myocarditis and pericarditis are among the identified risks following COVID-19 mRNA vaccination, including the mRNA-1273 vaccine. Most cases occur within 14 days following the second dose of this vaccine, and incidence is highest among young males aged 18 to 39. Additional data are needed to characterize risk factors, natural history and long-term outcomes of these events.

Objectives:

(1) To identify possible risk factors for myocarditis and pericarditis following mRNA-1273 vaccination, and (2) To examine the clinical course of myocarditis and pericarditis of varying origin and to identify prognostic factors in the course of myocarditis and pericarditis.

Methods:

Performed within the VAC4EU association, the study will draw on electronic healthcare records from five data access partners (DAPs) located in Denmark (Aarhus University), Norway (University of Oslo), Spain (IDIAP and FISABIO) and the United Kingdom (DSRU) to create a source population representative of the European population overall. The study is performed using the published ConcePTION common data model (CDM) for all DAPs and analyses will be run locally before performing a pooled meta-analysis of outcomes. All cases will be validated based on criteria from the Brighton Collaboration Case Definition. A case-cohort design will address Objective (1), and will include all cases of myocarditis and pericarditis following mRNA-1273 vaccination, as well as a random sub-cohort of individuals who have received this vaccine as controls. A Cox model with non-proportional hazards, including variables for demographic characteristics, medical history and vaccination history, will be used to investigate risk factors in the case-cohort design. Objective (2) will be addressed through a cohort study including all cases of myocarditis and pericarditis in the data. A Cox model will be used to compare cases following mRNA-1273 vaccination to cases not following COVID-19 vaccination for outcome measures such as cardiac and clinical outcomes, hospital readmission, and death, in this cohort.

Results:

As of April 2022, the source population includes over 6 million vaccinated individuals, and in each study design we expect to include 150 to 1500 cases. Over the course of 2023 and 2024, this study will continue to include individuals in the analyses sets, as to most accurately describe risk factor profiles of interest.

Conclusions:

By drawing from electronic healthcare records from several DAPs and using the ConcePTION CDM, the design of this study allows for identification of risk factors for the development of myocarditis and pericarditis and for comparing the clinical course of cases following mRNA-1273 vaccination to cases not following vaccination.

The self-controlled risk interval (SCRI) design lent itself well to the rapid safety evaluation of COVID-19 vaccines, but limited post-vaccination follow-up necessitated a pre-vaccination control window. This increases the risk of time-varying confounding, especially for later doses. Negative control outcomes (NCOs) are often used to assess unmeasured confounding, but they are rarely applied to SCRIs.

Objectives: Analyse two NCOs to assess unmeasured confounding in a COVID-19 vaccine safety SCRI on myocarditis.

Methods

We used primary and secondary healthcare datasources (DS) from Italian (ARS), Spanish (BIFAP, FISABIO, SIDIAP), and British (CPRD) databases. Exposed cases with ≥1 year of observation before 1 September 2020 (study start) were eligible. Data were extracted from study start to the end of data availability (December 2021 (ARS) - April 2022 (BIFAP)). Exposures were doses 1/2 of the Pfizer (PF), Moderna (MO), AstraZeneca (AZ), and Janssen (JJ) COVID-19 vaccines. Outcomes were myocarditis (MC), otitis externa (OE; NCO), and non-congenital valvular heart disease (VHD; NCO). These NCOs were chosen because their risk factors were similar to MC except for the association with COVID-19 vaccines.

The SCRI used a 60-day control window starting 90 days before dose 1 and dose-specific 28-day risk windows. Analyses were stratified by vaccine brand, adjusted for calendar time in 30-day periods, and pooled across DS with random effects meta-analysis. We expect a null association between exposure and NCOs and interpret deviations from this as potential unmeasured confounding.

Results: We included 461 MC cases (29% women), 40,732 OE cases (58% women), and 17,187 VHD cases (51% women). MC risk increased significantly after dose 2 of PF (IRR = 1.85, 95%CI 1.32-2.60, I2 = 0%) and MO (IRR = 2.39, 95%CI 1.40-4.10, I2 = 0%). Vaccination did not affect OE risk with little heterogeneity between databasesDS, except for JJ (IRR = 1.26, 95%CI 0.99-1.60, I2 = 42%). We also observed heterogeneity for AZ dose 1 (I2 = 69%) because of an isolated finding in ARS (IRR = 4.80, 95%CI 1.62-14.2). VHD risk decreased after vaccination but there was considerable heterogeneity between databases DS (I2 = 0% for JJ to I2 =93% for PF dose 2). The strongest effects were seen in the databases DS relying entirely (ARS) or partially (FISABIO) on hospital records (discharge and emergency admission) for diagnoses.

Conclusions: The VHD results suggest confounding towards the null, underestimating MC risk, but the null finding for OE does not support the same conclusion. We interpret this as VHD being a poor NCO; it could be a cardiac complication of COVID-19 and thus vaccines protect against it. The degree of unmeasured confounding also varies geographically and across DS. NCOs are a useful tool to detect assess weaknesses this in COVID-19 vaccine safety SCRIs.

Myocarditis and pericarditis are among the identified risks following COVID-19 mRNA vaccination, including the mRNA-1273 vaccine. Most cases occur within 14 days following the second dose of this vaccine, and incidence is highest among young males aged 18 to 39. Additional data are needed to characterize risk factors, natural history and long-term outcomes of these events.

Objectives: (1) To identify possible risk factors for myocarditis and pericarditis following mRNA-1273 vaccination, and (2) To examine the clinical course of myocarditis and pericarditis of varying origin and to identify prognostic factors in the course of myocarditis and pericarditis.

Methods: Performed within the VAC4EU association, the study will draw on electronic healthcare records from five data access partners (DAPs) located in Denmark (Aarhus University), Norway (University of Oslo), Spain (IDIAP and FISABIO) and the United Kingdom (DSRU) to create a source population representative of the European population overall. The study is performed using the published ConcePTION common data model (CDM) for all DAPs and analyses will be run locally before performing a pooled meta-analysis of outcomes. All cases will be validated based on criteria from the Brighton Collaboration Case Definition. A case-cohort design will address Objective (1), and will include all cases of myocarditis and pericarditis following mRNA-1273 vaccination, as well as a random sub-cohort of individuals who have received this vaccine as controls. A Cox model with non-proportional hazards, including variables for demographic characteristics, medical history and vaccination history, will be used to investigate risk factors in the case-cohort design. Objective (2) will be addressed through a cohort study including all cases of myocarditis and pericarditis in the data. A Cox model will be used to compare cases following mRNA-1273 vaccination to cases not following COVID-19 vaccination for outcome measures such as cardiac and clinical outcomes, hospital readmission, and death, in this cohort.

Results: As of April 2022, the source population includes over 6 million vaccinated individuals, and in each study design we expect to include 150 to 1500 cases. Over the course of 2023 and 2024, this study will continue to include individuals in the analyses sets, as to most accurately describe risk factor profiles of interest.

Conclusions: By drawing from electronic healthcare records from several DAPs and using the ConcePTION CDM, the design of this study allows for identification of risk factors for the development of myocarditis and pericarditis and for comparing the clinical course of cases following mRNA-1273 vaccination to cases not following vaccination.

Introduction: Since the WHO declared the COVID-19 global pandemic in March 2020, vaccines to prevent severe SARS-CoV-2 infection have been developed at unprecedented speed. Several vaccines have been conditionally authorized by regulators in December 2020 already. The large-scale vaccination campaigns have undeniably raised the importance of post-authorization evaluations not only through spontaneous reporting but also by cohort event monitoring to obtain more in-depth vaccine safety information, rapidly after launch.

Objective: To monitor COVID-19 vaccine safety and estimate the frequency of solicited and non-solicited, non-serious and serious reactions.

Methods: We designed a prospective cohort event monitoring (CEM) study as part of the Covid-Vaccine-Monitor (CVM) project. The CEM collects baseline data, adverse reactions (ADRs) of authorized COVID-19 vaccines in the general and special populations (pregnant and lactating women, children, and adolescents, immunocompromised, allergic, and prior COVID-19 infection people) in twelve countries (Germany, Croatia, Netherlands, Belgium, Italy, France, Spain, Portugal, Slovakia, Romania, Switzerland, and UK). The current results comprise data from February 2021–February 2022.

Depending on the dose and cohort, two data collection platforms are used: the Lareb-managed Intensive Monitoring (LIM) and the UMC Utrecht Research Online (RO). Germany and Croatia used their national tools. Participants meet local age criteria, have a first vaccination cycle or a booster dose within 48 hours, and are followed up for 6 months. Data are pooled, stratified by special cohorts, and analyzed.

Results: We included more than 30,000 general population participants data from Belgium, Croatia, France, Italy, Netherlands, and UK, and more than 520,000 from Germany with the first vaccinations. Across different vaccines, 0.2–0.3% reported at least one serious ADR after receiving the first doses. More than 7,400 special cohorts vaccinees participated. 0.2% and 0.4% reported at least one serious ADR and adverse event of special interest (AESI), respectively, after the first vaccinations. The most-reported ADRs among vaccines were injection site pain, locally, and fatigue, headache, malaise, and myalgia, systemically. Serious ADRs and AESIs were uncommon. More than 11,100 vaccinees from general and special cohorts receiving a booster dose were also included. Among different cohorts, children/adolescents reported the lowest number of ADRs, while lactating women reported the highest.

Conclusion: We collected and analyzed COVID-19 vaccines safety evidence in more than 550,000 general and special population persons after the first cycle and booster doses, combining data from twelve countries. Data confirm common ADR rates that are already listed in the summary of product characteristics, and that serious reactions are uncommon. Additional follow-up is ongoing.

BNT162b2, a mRNA-based vaccine for the prevention of COVID-19, has been authorised in the European Union (EU), United States and United Kingdom. Efficient and timely monitoring of adverse events of special interest (AESIs), is needed, particularly myocarditis and pericarditis which have been identified as potentially associated with the vaccine.

Objectives: To determine whether an increased risk of selected AESIs exists following vaccination with BNT162b2 in the general population and specific populations (immunocompromised, comorbidities, prior COVID-19 infection, pregnant individuals ) compared to unvaccinated, and to characterise utilisation patterns of BNT162b2 in Europe. In addition, a sub-study will describe the natural history of cases of myocarditis and pericarditis among vaccinated and unvaccinated individuals and will analyze risk factors.

Methods: A retrospective cohort design will be used to compare the incidence of AESIs in vaccinated versus unvaccinated individuals matched on relevant individual characteristics. A self-controlled risk interval study design will also be used for selected acute AESIs to control for time-invariant confounders. The natural history of myocarditis and pericarditis cases occurring in the cohort will be described. The study will be performed using electronic healthcare record (EHR) data in eight data sources in the Netherlands (PHARMO), Italy (ARS Toscana; Pedianet; Health Search Database), Spain (EpiChron; SIDIAP), United Kingdom (CPRD Aurum), and Norway (Norwegian health registers). The study consortium is coordinated by VAC4EU, and data analyses are planned biannually for three years. Recorded prescription, dispensing, or administration data will be used to assess vaccination with BNT162b2. AESIs will be identified using algorithms based on codes for diagnoses, procedures, and treatments. Outcome validation will be based on patient profile review of electronic records by healthcare professionals and a subset will undergo clinical validation through chart review.

Results: The study is conducted in a distributed manner using a common protocol, common data model (CDM), and common analytics programmes. The study will provide analyses of the occurrence of AESIs in 15,937,656 doses of the BNT162b2 that were included in the first data cut; 879,971 in PHARMO; 3,885,270 in ARS Toscana; 1,128 in PEDIANET; 621,795 in EpiChron; 3,164,906 in SIDIAP and 7,384,586 in CPRD Aurum.

Conclusions: Safety monitoring with biannual data cuts and clinical validation of AESIs is feasible in the participating data sources. The study will continue to monitor AESIs in the data sources through 2023.

Incomplete capture of COVID-19 vaccination in claims data can lead to misclassification of vaccination status in studies using real world data. As COVID-19 vaccine administration may occur without reimbursement from payers, the capture in claims data of vaccine exposure information needed for vaccine safety studies is not currently well understood.

Objective: To assess capacity for identifying health insurance plan enrollees with Janssen Ad26.COV2.S COVID-19 vaccination within 4 US health insurance databases in preparation for an observational post-authorization safety study (PASS).

Methods: Research partners provided A26.COV2.S counts of vaccinees in May 2021, which included demographic characteristics of vaccinees and source of exposure information as recorded in claims. Partners also provided monthly counts from October 2021 through January 2022 and responded to surveys in May 2021 and November 2021. The surveys included information regarding COVID-19 vaccine capture and timeliness in claims data, and potential linkages to states’ Immunization Information Systems (IISs).

Results: In May 2021, we identified 350,532 enrollees with Ad26.COV2.S vaccination in claims data; of these 51% were female, 47% were 18-49 years, 36% were 50-64 years, and 17% were ≥65 years. Vaccine administrations were most commonly recorded in claims with national drug codes (58%) followed by vaccine administration codes (30%); 11% of enrollees had multiple sources of information. The majority of vaccination claims (approximately 77%) were recorded in outpatient settings; 17% had no setting identified, 5% occurred in other settings, and only 1% were captured in mass vaccination settings. Pharmacy claims had the shortest lag time (~1 month) and inpatient claims the longest (~6 months). As of the November 2021 survey, 2 of 4 partners were conducting linkage with IISs in 9 states and negotiating with 14 others. Timing and frequency of IIS linkage varied by partner and IIS, but typically occurred either monthly or weekly. The ability to incorporate IIS records into databases is still being determined. By January 2022, we identified 566,891 enrollees with Ad26.COV2.S vaccination.

Conclusions: As the extent of missing COVID-19 vaccine information in claims is still unknown, the potential for exposure misclassification should be considered in the design of vaccine safety studies. An active comparator design and a self-controlled risk interval design are planned to be used in this US PASS to overcome potential misclassification of unexposed vaccination status. Ongoing work includes assessment of Ad26.COV2.S vaccine uptake in the insurers’ databases and the ability to incorporate IIS records.

Setting: Primary and/or secondary health care data from four European countries: Italy, the Netherlands, the United Kingdom, Spain

Participants"" Individuals with complete data for the year preceding enrollment or those born at the start of observation time. The cohort comprised 25,720,158 subjects.

Interventions: First and second dose of Pfizer, AstraZeneca, Moderna, or Janssen COVID-19 vaccine.

Main outcome measures: 29 adverse events of special interest (AESI): acute aseptic arthritis, acute coronary artery disease, acute disseminated encephalomyelitis (ADEM), acute kidney injury, acute liver injury, acute respiratory distress syndrome, anaphylaxis, anosmia or ageusia, arrhythmia, Bells’ palsy, chilblain-like lesions death, erythema multiforme, Guillain Barré Syndrome (GBS), generalized convulsion, haemorrhagic stroke, heart failure, ischemic stroke, meningoencephalitis, microangiopathy, multisystem inflammatory syndrome, myo/pericarditis, myocarditis, narcolepsy, single organ cutaneous vasculitis (SOCV), stress cardiomyopathy, thrombocytopenia, thrombotic thrombocytopenia syndrome (TTS) venous thromboembolism (VTE)

Results: 12,117,458 individuals received at least a first dose of COVID-19 vaccine: 54% with Comirnaty (Pfizer), 6% Spikevax (Moderna), 38% Vaxzevria (AstraZeneca) and 2% Janssen Covid-19 vaccine. AESI were very rare <10/100,000 PY in 2020, only thrombotic and cardiac events were uncommon. After adjustment for factors associated with severe COVID, 10 statistically significant associations of pooled incidence rate ratios remained based on dose 1 and 2 combined. These comprised anaphylaxis after AstraZeneca vaccine, TTS after both AstraZeneca and Janssen vaccine, erythema multiforme after Moderna, GBS after Janssen vaccine, SOCV after Janssen vaccine, thrombocytopenia after Janssen and Moderna vaccine and VTE after Moderna and Pfizer vaccines. The pooled rate ratio was more than two-fold increased only for TTS, SOCV and thrombocytopenia.

Conclusion: We showed associations with several AESI, which remained after adjustment for factors that determined vaccine roll out. Hypotheses testing studies are required to establish causality.

Estimates of the association between COVID-19 vaccines and myo-/pericarditis risk vary widely across studies due to scarcity of events, especially in age- and sex-stratified analyses.

Methods: Population-based cohort study with nested self-controlled risk interval (SCRI) using healthcare data from five European databases. Individuals were followed from 01/01/2020 until end of data availability (31/12/2021 latest). Outcome was first myo-/pericarditis diagnosis. Exposures were first and second dose of Pfizer, AstraZeneca, Moderna, and Janssen COVID-19 vaccines. Baseline incidence rates (IRs), and vaccine- and dose-specific IRs and rate differences were calculated from the cohort The SCRI calculated calendar time-adjusted IR ratios (IRR), using a 60-day pre-vaccination control period and dose-specific 28-day risk windows. IRRs were pooled using random effects meta-analysis.

Results: Over 35 million individuals (49·2% women, median age 39-49 years) were included, of which 57·4% received at least one COVID-19 vaccine dose. Baseline incidence of myocarditis was low. Myocarditis IRRs were elevated after vaccination in those aged < 30 years, after both Pfizer vaccine doses (IRR = 3·3, 95%CI 1·2-9.4; 7·8, 95%CI 2·6-23·5, respectively) and Moderna vaccine dose 2 (IRR = 6·1, 95%CI 1·1-33·5). An effect of AstraZeneca vaccine dose 2 could not be excluded (IRR = 2·42, 95%CI 0·96-6·07). Pericarditis was not associated with vaccination.

Conclusion: mRNA-based COVID-19 vaccines and potentially AstraZeneca are associated with increased myocarditis risk in younger individuals, although absolute incidence remains low. More data on children (≤ 11 years) are needed.

In this session, the speakers looked back over the many contributions from the pharmacoepidemiological society to the handling of the COVID-19 pandemic, as well as outlined both learnings and likely challenges that lies ahead. Specifically, they discussed the value of coordinated global collaborations in addressing urgent safety issues, what methodological insights we should take from these recent years, what regulators have learned and will expect from the pharmacoepidemiological society in the future, and what areas of the pandemic that will likely provide the study questions of the future.

Background: COVID-19 global health emergency revealed the need for pharmacovigilance projects to proceed rapidly while guaranteeing high-quality standards. Post-authorization safety studies (PASS) are complex and mandatory pharmacovigilance activities that require the participation of specialized scientific project managers at every stage, from scientific and regulatory affairs consultancy to change management readiness. During the COVID-19 pandemic, the undeniable contribution of scientific project managers in pharmacovigilance activities enhanced the ability of study consortia to adapt to rapidly evolving regulatory requirements on top of the existing challenges.

Objectives: To identify and describe coordination and management challenges in the design and execution of PASS studies that emerged during the COVID-19 pandemics and develop methodological procedures for agile management whilst addressing regulatory requirements.

Methods: We retrospectively reviewed PASS workflows and tasks from the initial request stage to the final reporting and archiving; we analyzed the impact of COVID-19 pandemics in the different aspects of studies management including study governance, protocol development, data management and protection, reporting, quality, and risk management.

Results: We established, adopted, and validated high-reliability organizational principles and methodologies, such as good management practices, effective communication systems, actions as a learning partnership to optimize scientific project management processes of PASS studies and address the following needs:•Availability of updated data•Data harmonization and integration•IRB approvals during pandemics•Rapidly changing regulatory requirements•Fast-trackreporting methodology•Accurate validation process of AESIs

CONCLUSIONS: The role of scientific project management is crucial for successfully conducting PASS projects. The management ofuncertainty, rapidly changing regulatory environment, stakeholders' collaboration, change management, continuous improvement through the creation of effective tools, flexibility, and prioritization were identified as key factors for the successful coordination of PASS studies during the pandemic. Beyond this, scientific project managers also contribute to shaping and improving studies technical aspects, such as study implementation, data collection and reporting throughout the continuous support and monitoring alongside the study scientific coordinator.

Knowledge about the safety of COVID-19 vaccines was limited to pre-licensure clinical trials at the time national vaccination programmes were initiated. Therefore, comprehensive surveillance of the real-world safety of these vaccines was essential to detect and rapidly evaluate any signals that warranted regulatory action. Due to the nature of post-marketing surveillance, vaccination roll-out and safety evaluation occur simultaneously. Consequently, any potential safety signal needs to be evaluated rapidly to inform regulatory agencies on post-approval benefit/risk assessment of vaccines. In short, time is of the essence. However, reliability is also key because findings will directly inform regulatory action. How to balance this need for speed with making sure findings are robust to bias, especially in a vaccination setting where such issues are likely to occur? And what about collecting sufficient events for meaningful analyses given the short timeframe? This fringe session will discuss these issues using work from the European Medicines Agency (EMA)-funded Covid Vaccine Monitoring project on myo- and pericarditis as a case study. In July 2021, myocarditis was raised as a potential adverse effect of mRNA-based COVID-19 vaccines, especially in younger men after the second dose. Combining real-world data from four European countries, we applied both a cohort and a nested self-controlled risk interval design to evaluate the effect of four EMA-approved COVID-19 vaccines on myo-/pericarditis risk. Only four months after the signal was first raised, we confirmed an increased incidence of myo-/pericarditis after the second dose of both mRNA vaccines, especially in individuals aged 12-29 years. This fringe session will present the project in real time, encouraging the audience to think along, come up with solutions, and discuss the findings and decisions made. The aim is to interactively introduce the audience to safety evaluation study designs and methods and challenges surrounding observational COVID-19 vaccine safety research.

The global rapid spread of SARS-CoV-2 urges the development of vaccines as preventive measures to control for this pandemic. As part of the preparedness for COVID-19 vaccine monitoring, ACCESS, an EMA-funded project, has identified 37 Adverse Events of Special Interest (AESIs), including pregnancy outcomes, that may be used to monitor benefit-risk profile of COVID-19 vaccines.

Objectives: The overarching goal was to estimate age-and sex-stratified background incidence rates (IRs) of 37 AESIs per calendar year.

Methods: A retrospective multi-database dynamic cohort study was conducted from 2017 to 2020 (2010-2013 for Denmark and 2013-2017 for Germany), until the date of last data availability for each data source. The study population included all individuals observed in one of the participating data sources for at least one day during the study period and who has at least 1 year of data availability before cohort entry, except for individuals with data available since birth. Data from insurance claims (GePaRD, Germany; SNDS, France), hospitalization record linkage (PHARMO, The Netherlands; Aarhus, Denmark; FISABIO and SIDIAP, Spain; ARS, Italy) and general practitioners (Pedianet (only children), Italy; BIFAP, Spain; CPRD, UK) were included. Clinical definition forms were developed for each AESI including concept sets built from diagnosis codes and/or drug codes using 5 coding systems. The study was conducted in a distributed manner using a common protocol (EUPAS37273), common data model, and common analytics programs. R programs for transformation of data were distributed to data access providers for local deployment. Demographic characteristics and baseline characteristics such as at-risk medical conditions for developing severe COVID-19 disease were computed for each database. Age-, sex and calendar year stratified incidence rates (95%CI) of AESIs were computed among the general population and in at-risk population.

Results: Evidence available on 15 February 2021 provides IRs on 26 AESI from 5 countries and 7 data sources. A total number of 20,649,121 subjects contributing to 48 million person-years were included so far, data from 3 other data sources will arrive in the coming month. IRs were stable, although some rates dropped in 2020 (e.g. cardiovascular diseases) potentially due to lock down. A clear age pattern was observed for most AESIs.

Conclusions: The study yielded background IRs with high precision which will be used for further assessment of the safety of COVID-19 vaccines.

Background: Autoimmune disease flare‑ups—defined as transient worsening of underlying symptoms—are critical outcomes for post‑authorisation vaccine safety monitoring. Vaccination may influence immune balance, yet the absence of harmonised flare definitions hampers consistent detection across electronic health records (EHRs). The SAFETY‑VAC initiative, part of the EMA/ECDC Vaccine Monitoring Platform and conducted within the EU PE&PV Research Network in collaboration with VAC4EU, aims to standardise flare detection methodology across Europe.

Methods: A multi‑database cohort study (2017–2024) was conducted using seven EHR databases from five European countries. Flare case definitions and detection algorithms were developed through literature review, Brighton Collaboration guidance, and expert consensus within a multidisciplinary working group. Algorithms incorporated medication changes, symptom worsening, laboratory and imaging findings, and healthcare utilisation (hospitalisations and emergency visits). Iterative refinement ensured applicability across diverse coding systems and data structures.

Results: Algorithms were developed for ten autoimmune diseases: autoimmune hepatitis, erythema nodosum, Graves’ disease, Hashimoto’s thyroiditis, multiple sclerosis, systemic lupus erythematosus, rheumatoid arthritis, psoriatic arthritis, polyarteritis nodosa, and ulcerative colitis. Harmonised definitions improved comparability across seven heterogeneous datasets. Combining clinical and pharmacological indicators enhanced detection accuracy, with medication records emerging as the most sensitive markers of flare activity. The resulting algorithms form the first federated Europe‑wide library for flare‑up identification, enabling real‑time detection and regulatory‑ready safety evaluation.

Conclusions: Standardised flare‑up definitions and algorithms improve the capacity to detect autoimmune disease flares in large‑scale EHR data and strengthen vaccine safety surveillance. Next steps include validation in real‑world data, integration into ongoing monitoring systems, protocol expansion for broader research use, and application to wider safety signal detection frameworks.