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Meta-analysis

Evaluating the reactogenicity of COVID-19 vaccines from network-meta analyses

ORCID Icon, ORCID Icon, ORCID Icon, ORCID Icon, , ORCID Icon & ORCID Icon show all
Pages 410-418 | Received 05 Apr 2023, Accepted 25 Apr 2023, Published online: 08 May 2023
 

ABSTRACT

Background

Evidence-based reassurances addressing vaccine-related concerns are crucial to promoting primary vaccination, completion of the primary series, and booster vaccination. By summarizing and comparing the reactogenicity of COVID-19 vaccines authorized by the European Medicines Agency, this analysis aims to support in-formed decision-making by the lay public and help overcome vaccine hesitancy.

Research design and methods

A systematic literature review identified 24 records reporting solicited adverse events for AZD1222, BNT162b2, mRNA-1273, NVX-Cov2373, and VLA2001 in individuals aged 16 or older. Network meta-analyses were conducted for each solicited adverse events reported for at least two vaccines that were not compared head-to-head but could be connected through a common comparator.

Results

A total of 56 adverse events were investigated through network meta-analyses within a Bayesian framework with random-effects models. Overall, the two mRNA vaccines were found to be the most reactogenic vaccines. VLA2001 had the highest likelihood of being the least reactogenic vaccine after the first and second vaccine dose, especially for systemic adverse events after the first dose.

Conclusions

The reduced chance of experiencing an adverse event with some COVID-19 vaccines may help to overcome vaccine hesitancy in population groups with concerns about the side effects of vaccines.

Declaration of Interest

G Tiozzo, T Louwsma, S Konings are employees of Asc Academics. Asc Academics has received consultancy fees for this project from Valneva SE. G Vondeling and JP Gomez are paid employees at Valneva SE. M Postma had received funding from Janssen-Cilag B.V for projects unrelated to the current study. The authors have no other relevant affiliations or financial involvement with any organization or entity with a financial interest in or financial conflict with the subject matter or material discussed in the manuscript apart from those disclosed.

Reviewer disclosures

Peer reviewers on this manuscript have received an honorarium for their review work. Peer reviewers on this manuscript have no other relevant financial or other relationships to disclose.

Author Contributions

Conceptualization, G.T., T.L., S.K., G.V. and J.P.G.; methodology, G.T., T.L. and S.K.; software, S.K.; formal analysis, G.T. and S.K.; data curation, G.T. and S.K.; writing – original draft preparation, G.T. and T.L.; writing – review and editing, S.K., G.V., J.P.G., M.P and R.F.; visualization, S.K.; supervision, G.V., J.P.G., M.P. and R.F.; project administration, G.T. and T.L. All authors have read and agreed to the published version of the manuscript.

Supplementary material

Supplemental data for this article can be accessed online at https://doi.org/10.1080/14760584.2023.2208216.

Additional information

Funding

This paper was funded by Valneva SE. Valneva SE had no role in the set-up of the study or interpretation of the results.