ArticleBMC medical informatics and decision making2019
A statistical analysis of vaccine-adverse event data.
Article in BMC medical informatics and decision making, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
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Who cites it
10 citing papers in PubMed.
- Descriptive analysis of adverse events following immunization with oral cholera vaccine in Lebanon.Frontiers in public health · 2024Article
- The association between adverse events of COVID-19 vaccination and anxiety and willingness to receive a booster dose.Human vaccines & immunotherapeutics · 2023Article
- Vaccine adverse event reporting system (VAERS): Evaluation of 31 years of reports and pandemics' impact.Saudi pharmaceutical journal : SPJ : the official publication of the Saudi Pharmaceutical Society · 2022Article
- COVID-19 vaccine design using reverse and structural vaccinology, ontology-based literature mining and machine learning.Briefings in bioinformatics · 2022Article
- Unusual lymphadenopathies secondary to the BNT162b2 mRNA Covid-19 vaccine.Medicina clinica (English ed.) · 2022Article
- Unusual lymphadenopathies secondary to the BNT162b2 mRNA Covid-19 vaccine.Medicina clinica · 2022Article
- Article
- Reactogenicity to COVID-19 vaccination in the United States of America.Clinical and experimental vaccine research · 2022Article
- Safety and Considerations of the COVID-19 Vaccine Massive Deployment.Virologica Sinica · 2021Article
- Differentially private release of medical microdata: an efficient and practical approach for preserving informative attribute values.BMC medical informatics and decision making · 2020Article
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Authors and funding
4 authors.
Funding
Abstract
backgroundVaccination has been one of the most successful public health interventions to date, and the U.S. FDA/CDC Vaccine Adverse Event Reporting System (VAERS) currently contains more than 500,000 reports for post-vaccination adverse events that occur after the administration of vaccines licensed in the United States. The VAERS dataset is huge, contains very large dimension nominal variables, and is complex due to multiple listing of vaccines and adverse symptoms in a single report. So far there has not been any statistical analysis conducted in attempting to identify the cross-board patterns on how all reported adverse symptoms are related to the vaccines.
methodsFor studies of the relationship between vaccines and reported adverse events, we consider a partial VAERS dataset which includes all reports filed over a period of 24 years between 1990-2013. We propose a neighboring method to process this dataset for dealing with the complications caused by multiple listing of vaccines and adverse symptoms in a single report. Then, the combined approaches based on our neighboring method and novel utilization of data visualization techniques are employed to analyze the large dimension dataset for characterization of the cross-board patterns of the relations between all reported vaccines and events.
resultsThe results of our analysis indicate that those events or symptoms with overall high occurrence frequencies are positively correlated, and those most frequently occurred adverse symptoms are mostly uncorrelated or negatively correlated under different bacteria vaccines, but they are in many cases positively correlated under different virus vaccines, especially under flu vaccines. No particular patterns are shown under live vs. inactive vaccines.
conclusionsThis article identifies certain cross-board patterns of the relationship between the vaccines and the reported adverse events or symptoms. This helps for better understanding the VAERS data, and provides a useful starting point for the development of statistical models and procedures to further analyze the VAERS data.
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