Adverse events following COVID-19 vaccination: first 90 days of experience from a tertiary care teaching hospital in South India.

Abstract

Background: The COVID-19 vaccination program was introduced in India on 16 January 2021. The Government-issued fact sheet was the only source of information regarding Adverse Events Following Immunizations (AEFIs) for these vaccines. The objective of this study was to assess the AEFIs reported following COVID-19 vaccination in a tertiary care teaching hospital.

Materials and methods: The spontaneous reporting method was used for data collection for a period of 3 months. A data collection form was designed to collect the data from the study population who reported adverse events. Collected data were analyzed and categorized by severity and seriousness. The causality assessment team performed causality assessment of the AEFIs using the World Health Organization's causality assessment algorithm.

Results: A total of 11,656 doses of COVID-19 vaccine were administered at the study site during the study period, of which 9292 doses were COVISHIELD™ and 2364 doses were COVAXIN™. In all, 445 AEFIs were reported from 269 subjects with an incidence rate of 3.48%. The majority of the subjects with AEFIs belonged to the age group of 18-45 years. Out of the total 445 AEFIs, 418 AEFIs were expected as per the fact sheets, 409 with COVISHIELD™ and 9 with COVAXIN™. Most of the AEFIs [62.02% (n = 276)] were observed at the system organ class of 'General disorders and administration site conditions'. After the causality assessment, out of 433 AEFIs to COVISHIELD^TM vaccine, 94.22% (n = 408) of events were categorized to have 'consistent causal association with immunization'. Out of 12 adverse events following COVAXIN™, 8 (66.66%) events were categorized as 'consistent causal association with immunization'. All of them recovered from their adverse events without any sequelae.

Conclusion: Spontaneous reporting is one of the cheapest methods that can be used for the reporting of AEFI. This method helps health care professionals to identify rare events and potential signals.