Factors associated with development of adverse events after taking COVID-19 vaccine in a tribal state of India: Regression analysis

J Family Med Prim Care. 2022 Oct;11(10):6260-6267. doi: 10.4103/jfmpc.jfmpc_519_22. Epub 2022 Oct 31.

Abstract

Background: Coronavirus disease (COVID-19) vaccination becomes a crucial weapon in the pandemic's control. Two vaccines, Covishield and Covaxin, are approved in India to vaccinate against the virus. Hence, the present study was done to determine the factors associated with the development of adverse events after taking the COVID-19 vaccine in a tribal state of India.

Materials and methods: This was a cross-sectional analytical study. All persons who were willing to participate in our study and had received the first or second dose of the COVID-19 vaccine from January 1 to March 31, 2021, were included. We got 1497 complete responses via (free, web-based Google Docs Editors suite offered by google, Founders- Larry Page Sergey Brin. Menlo Park, California, United States). So our final sample size came out to be 1497 in which analysis was done. The data was compiled in MS excel sheets (Microsoft version 2013, Microsoft Corporation, Redmond, Washington, United States) and a template was generated which was further analyzed in SPSS version 20 (version 25.0; IBM Corp., Armonk, NY, USA).

Results: The total number of respondents who participated in the surveillance of adverse events following immunization (AEFI) was 1497. Among them, a majority have taken the Covishield vaccine followed by Covaxin. The majority of participants were female of age group less than 30 years and above 18 years with a mean age of 33.63 ± 51.51. The most common AEFI was pain at the site of injection, after the first and second dose followed by fever after the first and second dose within 24 h following immunization.

Conclusion: We conclude that factors like the type of vaccine, gender, and participants who have allergies have a higher risk of presenting the adverse events after the COVID-19 vaccination.

Keywords: Adverse events; COVID-19; factors; regression analysis.