Analysis of adverse event reporting patterns following COVID-19 vaccination: findings from VigiAccess, FAERS and EudraVigilance databases with comparative assessment of data representation and categorization across three databases - Mahurkar, Ram N.; Bhave, Kiran A.; Pandit, Prasad R.; Patel, Tejal C. (International Journal of Basic & Clinical Pharmacology, 2025)
The clinical presentation of COVID-19 varied from mild to severe or fatal illness, and vaccination played a pivotal role in preventing the spread of severe acute respiratory syndrome coronavirus 2 (SARS‑CoV‑2). Despite cumulative evidence suggesting that the benefits of COVID-19 vaccination outweighed the risks, evaluating its safety profile remained imperative. This study aimed to analyse adverse events following immunization (AEFI) after COVID-19 vaccination using three pharmacovigilance databases and to assess how these data were categorized and represented. A cross-sectional observational study was conducted in January 2024 using VigiAccess (WHO), FAERS (U.S. FDA), and EudraVigilance (EMA). The total number of reported AEFI cases for COVID-19 vaccines were 55,49,876 in VigiAccess, 11,640 in FAERS, and 23,16,918 in EudraVigilance. The most common reaction group in all three databases was general disorders and administration site conditions (VigiAccess 59.07%, FAERS 62.57%, EudraVigilance 62.67%). The most frequently reported reaction in VigiAccess was headache (22.73%), while fatigue (19.79%) was the most common reaction in FAERS. VigiAccess grouped AEFIs for different COVID-19 vaccines under the general term “COVID-19 vaccine,” whereas FAERS and EudraVigilance categorized adverse events by specific vaccine types. All three databases categorized individual case safety reports (ICSRs) data, but only FAERS and EudraVigilance categorized the AEFI data. Overall, the comparative analysis revealed that the most commonly reported adverse reactions were consistent across the three databases, while also highlighting significant differences in how these databases represented and categorized the data.