Published June 27, 2022 | Version 1.0
Project deliverable Open

Cohort monitoring of Adverse Events of Special Interest and COVID-19 diagnoses prior to and after COVID-19 vaccination

  • 1. University Medical Center Utrecht, The Netherlands
  • 2. Regional Health Agency Tuscany, Italy
  • 3. Spanish Medicines Agency, Spain
  • 4. University Utrecht, The Netherlands
  • 5. PHARMO Institute, the Netherlands


This is a final study report with the following objectives

Primary objectives

  • To monitor and estimate the incidence rates of adverse events of special interest (AESI) in vaccinated and non-vaccinated persons by data source over the period January 1st 2020-October 31st  2021 by brand and dose of vaccine and age of the population.
  • To monitor and estimate the incidence rates of diagnosed COVID-19 in vaccinated and non-vaccinated persons by data source over the period January 1st 2020-October 31st 2021 by brand and dose of vaccine as well as age.
  • To monitor exposure and coverage to COVID-19 vaccines by brand and dose of vaccine as well as age.

 Secondary objectives

  • To compare the incidence rates of AESIs in the risk window of 28 days after vaccination with dose 1 and/or dose 2 with the incidence rates of AESIs in 2020. 
  • To monitor and estimate vaccine exposure, incidence rates of adverse events of special interest. (AESI) and of COVID-19 in vaccinated and non-vaccinated persons over the period January 1st  2020-October 31st  2021 in the at-risk population for developing severe COVID-19 by data source, brand and dose of vaccine as well as age.



We used a retrospective cohort design, in 4 electronic health care databases, with periodic updates of the data during the study period (January 2020 -September 2021). Persons entered the cohort on 1/1/2020 and exit upon latest data extraction, death, moving out or the specific events of interest. Person-time after cohort entry was divided in non-exposed person-time, and person-time following vaccination by specific brands, labelled by dose and distance since last vaccination (-1, -2, -3 weeks etc). 

The source population included all individuals observed in one of the participating data sources for at least one day during the study period (01 January 2020 - last data availability) and who have at least 1 year of data availability before cohort entry, except for individuals with data available since birth.

Per event, for calculation of incidence, individuals were followed from cohort entry and contribute to person-time in month (prior to vaccination) and in weeks after vaccination plus specific vaccine exposure (brand & dose) category. Follow-up was censored upon the earliest of date of the event (except for recurrent events), death, exiting the data source, or last data draw-down. For comparison of post-vaccination rates follow-up ended 28 days after each of the vaccine doses, if they had a 2nd dose the intervals post-dose stopped at the date of vaccination with the second. Incidence rates were calculated for 2020 (non-exposed), and after vaccination by vaccine brand, dose and data source. Incidence rates were standardised directly to the Eurostat population and standardised rate differences were calculated using R. Following results of the interim analysis in July 2021, Poisson regression was added to the amended protocol to adjust for measured covariates that were related to the chance of exposure to certain vaccines (age, sex, risk factors for severe covid and prior covid-19). We did not design to adjust for covariates related to the specific outcomes and this study was not designed for causal inference but for monitoring safety. This means that residual confounding may remain, which is why we pre-stated that we classify an association as ‘disproportional’ if the IRR was above 2. 



This study comprised a total of 25,720,158 subjects. We count only the largest population for BIFAP for the total, as the regions with hospital linkage are a subset of the primary care populations. The largest population included was from CPRD with more than 14 million participants. Data locks differed per site: June 30, 2021 in Tuscany, August 31st for BIFAP, August 1st 2021 for PHARMO and May 2021 for CPRD Aurum. At the start of the study 1/1/2020, 34% of the Tuscany population had one or more risk factors for severe COVID-19 disease, and this was around 25% in each of the other data sources (table 2).  Median age was highest in Tuscany region (49) and BIFAP-HOSP regions (49).

Overall, 12,117,458 persons received a first dose of a Covid-19 vaccine (47.1%) (excluding unknown vaccines manufacturers). Percentage was highest in BIFAP (68.7%). In BIFAP the majority of persons also had received a second dose for each of the vaccine brands. Percentage of full primary regimen of 2-dose primary regimens were lower in other data sources, in particular for AstraZeneca in CPRD, as this vaccine also had the highest distance between dose 1 and 2 in each data source. mRNA vaccines had a short distance between dose 1 and 2 in all sites except for CPRD, where Pfizer also had a mean of 76 days between dose 1 and 2, but only 28 days for Moderna vaccine. In this data instance heterologous schedules were very rare. 

Vaccination coverage data reflected well the regional/national data for ARS and BIFAP, but were lower for CPRD and PHARMO, probably due to delays in automated feedback on vaccination from immunization registers.

We studied the 2020 rates of different AESI. Most AESI were very rare, only the coagulation disorders were more common. We monitored the occurrence of AESI using cumulative weekly rates, and by censoring at 28-day intervals after each dose. The latter was used to compare against background, which was done using age standardized incidence rate differences, and subsequent Poisson analysis adjusting (where possible for age, sex, prior covid-19 and any risk factors for COVID). The table below shows the key results. For most AESI no excess risk was observed following vaccination, 30 event/vaccine/dose combinations showed excess age standardized rate differences and associations in the Poisson analyses (see table below), however after adjustment for factors associated with vaccine roll out, only 10 significant associations of pooled incidence rate ratios remained based on dose 1 and 2 combined. These comprised anaphylaxis after AstraZeneca, 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 venous thromboembolism after Moderna and Pfizer vaccines. The risk was more than two-fold increased for TTS, SOCV and thrombocytopenia. 


This study has provided many lessons

  1. It showed that we could monitor a large number of AESI and COVID-19 across 4 data sources in four countries based on the ConcePTION common data model, and common analytics pipeline, and that semantic harmonization was possible across the different disease terminologies
  2. Monitoring could start very early in the vaccination campaign, and repeated updates were possible 
  3. The same population and data sources were used both to compute background rates, and to retrieve observed events after vaccination. This design avoids a limitation of using, on the one hand, real-world data to assess background rates, and, on the other, spontaneous reporting to assess observed cases: underestimation, if any, is more likely to affect the two periods is a uniform way, thus improving the validity of comparison. 
  4. Underestimation of an AESI can be discussed, based on the characteristics of the data source in relation with the AESI. For example, ICPC codes do not allow for studying the majority for rare AESI, which affected the ability of PHARMO of monitoring such AESI; or, events that do not require hospitalisation or access to emergency room cannot be studied in the ARS data source.
  5. COVID-19 vaccines had very different user patterns across the countries in terms of type, distance between dose 1 and 2 and the populations targeted. We observed strong channelling of the different vaccines that differed across countries
  6. AESI incidence rates were mostly very low, especially for neurological, immunological and haematological events.  Coagulations disorders and cardiac disorders were more frequent, at the same time such events were those with stronger confounding 
  7. For several AESI we observed disproportionalities between post-vaccination observed and expected rates.  Most of these events had been the topic of regulatory discussions, based on public records such as the haematological events, neurological events and erythema multiforme. 
  8. In spite of the large numbers of vaccinees, power is limited for the events that are very rare <10/100,000 PY and continuous monitoring and scaling up (across countries and over time) is required.
  9. This study was for monitoring purposes and not for testing signals, if this needs to be done, proper pharmacoepidemiological designs (such as matching/restriction) should be applied to deal with confounding.




The research leading to these results was conducted as part of the activities of the EU PE&PV (Pharmacoepidemiology and Pharmacovigilance) Research Network (led by Utrecht University) with collaboration from the Vaccine Monitoring Collaboration for Europe network (VAC4EU). Scientific work for this project was coordinated by the University Medical Center Utrecht. The project has received support from the European Medicines Agency under the Framework service contract nr EMA/2018/28/PE. This document expresses the opinion of the authors, and may not be understood or quoted as being made on behalf of or reflecting the position of the European Medicines Agency or one of its committees or working parties. The authors from BIFAP would like to acknowledge the excellent collaboration of the primary care practitioners and pediatricians, and also the support of the regional authorities participating in the database.


Final ReportECVMWP2v1.0Final.pdf

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