Feasibility analysis of a European infrastructure for COVID-19 vaccine monitoring: Background rates of Adverse Events of Special Interest

Date of ISAC Approval: 
Lay Summary: 
The Covid-19 pandemic has triggered the need to develop vaccines to protect the society. Side effects of vacines that are currently being developed are concern, especially with the large number of people that will be use such a vaccine after it becomes avaialble. When new vaccines are launched on a market and used at a large scale, monitoring of adverse events post-immunisation are necessary to ensure a proper evaluation of the benefit-risk profile of vaccines. Methods for monitoring such side effects rely on accurate background rates of the event under evaluation. In the absence of these background rates, occurrence of rare events or an apparent increase in more common events can be interpreted as a signal of an unsafe vaccine. In this multi-country study that includes data from UK CPRD, background rates of a 38 different side effects will be calculated within the general population in the period 2017-2020, also looking within relevant population subgroups (e.g. age, sex, certain medical conditions) . Results can be used to give context to future data from prospective covid-19 vaccine monitoring studies and spontaneous reporting databases, and thereby, to help identify potential safety signals.
Technical Summary: 
The global rapid spread of COVID-19 caused by the SARS-CoV2 triggered the need for developing vaccines to control for this pandemic. This study will generate background incidence rates of adverse events of special interest (AESI) that may be used to monitor benefit-risk profile of upcoming COVID-19 vaccines. A retrospective multi-database dynamic cohort study will be conducted over the period 2017 to 2020 using 10 healthcare databases in 7 European countries, including UK CPRD. The study population will include all individuals observed in for at least one day during the study period (01 January 2017 - last data availability) and who have at least 1 year of data availability before cohort entry, except for individuals with data available since birth. Outcomes of interest include 38 different AESI, as defined by relevant Read/Snomed/ICD-10 codes, using both GP and HES data. Person-time of interest in CPRD will be based on the standard relevant patient and practice dates. Several at-risk medical conditions will be used as stratification factors. Incidence rates by calendar year will be calculated by dividing the number of incident cases (not in run-in year) (numerator) by the total person-time at risk (denominator). Prevalence rates by calendar year will be calculated by dividing the number of existing cases in a year (numerator) by the average of the total number of persons recorded monthly (denominator). Incidence rates will also be reported stratified by time prior to SARS-CoV2 circulation and during SARS-CoV2 circulation period to investigate potential changes in health care behaviours during the pandemic and associated lockdown periods on the incidence rates. Incidence rates will also be provided among persons at higher risk for developing severe COVID-19.
Health Outcomes to be Measured: 
Guillain-Barré Syndrome;Acute disseminated encephalomyelitis;Narcolepsy;Acute aseptic arthritis;Diabetes (type 1 and broader);(Idiopathic) Thrombocytopenia; Acute cardiovascular injury(Microangiopathy, Heart failure, Stress cardiomyopathy, Coronary artery disease, Arrhythmia, Myocarditis); Coagulation disorders (Thromboembolism, Hemorrhage); Single Organ Cutaneous Vasculitis; Acute liver injury; Acute kidney injury;Generalized convulsion;Meningoencephalitis;Transverse myelitis; Acute respiratory distress syndrome; Erythema multiforme; Chilblain – like lesions;Anosmia, ageusia;Anaphylaxis;Multisystem inflammatory syndrome in children;Death (any causes);COVID-19 disease (by levels of severity): Level 1: any recorded diagnosis, level 2: hospitalization for COVID-19 (confirmed or suspected), level 3: ICU admission in those with COVID-19 related admission; level 4: Acute respiratory distress requiring ventilation (ARDS) during a hospitalization for COVID-19; level 5 death during a hospitalization for COVID-19 (any cause);Sudden death;Gestational Diabetes; Pre-eclampsia; Maternal death; Fetal growth restriction; Spontaneous abortions;Stillbirth;Preterm birth;Major congenital anomalies;Microcephaly;Neonatal death;Termination Of Pregnancy for Fetal Anomaly; colonic diverticulitis; hypertension

Patrick Souverein - Chief Investigator - Utrecht University
Helga Gardarsdottir - Collaborator - Utrecht University
Olaf Klungel - Collaborator - Utrecht University
Patrick Souverein - Corresponding Applicant - Utrecht University
Romin Pajouheshnia - Collaborator - Utrecht University

HES Admitted