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Factors associated with serious adverse event following immunization

A real-world analysis of the vaccine adverse event reporting system 2025

Bibliographic Data

ID22073106
AuthorsXuejiao Pan (0000-0003-2418-3174, Zhejiang Center for Disease Control and Prevention), Yaping Chen (0000-0002-7502-1848, Department of Immunization Program, Zhejiang Provincial Center for Disease Control and Prevention), Y P Chen (Zhejiang Center for Disease Control and Prevention), Fuxing Chen (0000-0001-7240-2699, Department of Immunization Program, Zhejiang Provincial Center for Disease Control and Prevention), F X Chen (Zhejiang Center for Disease Control and Prevention), Hanqing He (0000-0003-0863-5177, Zhejiang Center for Disease Control and Prevention), Xiaohua Qi (Department of Immunization Program, Zhejiang Provincial Center for Disease Control and Prevention), X H Qi (Zhejiang Center for Disease Control and Prevention), Hui Liang (0000-0003-1341-6980, Department of Immunization Program, Zhejiang Provincial Center for Disease Control and Prevention)
Year2026
Volume14
Pages1820862-1820862
Publication date2026-04-29
Open AccessYes
TypeARTICLE
VenueFrontiers in Public Health (JOURNAL)
Journal identifiersISSN: 2296-2565 • E-ISSN: 2296-2565
PublisherFrontiers Media SA (PUBLISHER • CH)
DOI10.3389/fpubh.2026.1820862
PMID42136579
OpenAlexW7159650303
LanguageEN
References cited33

Background and aims: While vaccination is a vital and cost-effective public health tool, a small fraction of recipients experience serious adverse events (SAEs) that impose a profound clinical and systemic burden. Identifying the specific factors that predispose an individual to an SAE remains complex due to limitations in existing literature. This study analyzes SAE following immunization in the US population and identifies associated factors. Methods: We analyzed a national cross-section of 50,655 reports submitted to the Vaccine Adverse Event Reporting System (VAERS) throughout 2025. Data were categorized into five domains: demographic characteristics, clinical features, medical history, vaccine variables, and patient outcomes. A multivariable logistic regression model was employed to identify factors associated with reporting SAEs. Results: Of the 50,655 AEFIs reported (median age: 40 years), 9.58% were classified as SAEs. Multivariable analysis identified significant demographic and clinical factors associated with SAE reporting, including advanced age (≥65 years, aOR: 1.73), male sex (aOR for females: 0.72), longer onset times (aOR: 1.06), administration facilities (military, aOR: 1.76; private facilities, aOR: 1.39), and systemic symptoms (aOR: 1.72), while local symptoms were highly protective (aOR: 0.35). Patient history variables, such as current illness (aOR: 1.51) and medical history (aOR: 1.24), were associated with increased odds of SAE reporting, while prior reactions were protective (aOR: 0.77). Regarding vaccine characteristics, mRNA platforms (Pfizer/Wyeth aOR: 1.65), second doses (aOR: 1.33), non-intramuscular administration routes (oral aOR: 2.85; subcutaneous aOR: 1.51), and right-arm injections (aOR: 1.24) were all associated with higher odds of SAEs. Conclusion: SAE reporting is driven by a complex intersection of demographic, clinical, and vaccine-related characteristics. These findings carry significant clinical and public health implications, highlighting the need for enhanced screening and proactive monitoring of high-risk populations to optimize global vaccine safety protocols. Future studies should integrate passive reporting with active surveillance to optimize vaccine safety protocols

Adverse effect · Adverse Event Reporting System · Logistic regression · Medical history · Odds · Odds ratio · Population · Vaccination · Pharmacovigilance and Adverse Drug Reactions · SARS-CoV-2 and COVID-19 Research · Vaccine Coverage and Hesitancy

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    Open Access•Fernando P Polack, Stephen J Thomas et al.•New England Journal of Medicine•2020

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