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Linked vaccine adverse event data from VAERS for biomedical data analysis and longitudinal studies

BACKGROUND: Vaccines have been one of the most successful public health interventions to date. The use of vaccination, however, sometimes comes with possible adverse events. The U.S. FDA/CDC Vaccine Adverse Event Reporting System (VAERS) currently contains more than 200,000 reports for post-vaccinat...

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Autores principales: Tao, Cui, Wu, Puqiang, Luo, Yi, Zhang, Yuji
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2014
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4333877/
https://www.ncbi.nlm.nih.gov/pubmed/25699091
http://dx.doi.org/10.1186/s13040-014-0036-y
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author Tao, Cui
Wu, Puqiang
Luo, Yi
Zhang, Yuji
author_facet Tao, Cui
Wu, Puqiang
Luo, Yi
Zhang, Yuji
author_sort Tao, Cui
collection PubMed
description BACKGROUND: Vaccines have been one of the most successful public health interventions to date. The use of vaccination, however, sometimes comes with possible adverse events. The U.S. FDA/CDC Vaccine Adverse Event Reporting System (VAERS) currently contains more than 200,000 reports for post-vaccination events that occur after the administration of vaccines licensed in the United States. Although the data from the VAERS has been applied to many public health and vaccine safety studies, each individual report does not necessarily indicate a casuality relationship between the vaccine and the reported symptoms. Further statistical analysis and summarization needs to be done before this data can be leveraged. METHODS: This paper introduces our efforts on representing the vaccine-symptom correlations and their corresponding meta-information extracted from the VAERS database using Resource Description Framework (RDF). Numbers of occurrences of vaccine-symptom pairs reported to the VAERS were summarized with corresponding proportional reporting ratios (PRR) calculated. All the data was stored in an RDF file. We then applied network analysis approaches to the RDF data to illustrate a use case of the data for longititual studies. We further dicussed our vision on integrating the data with vaccine information from other sources using RDF linked approach to facilitate more comprehensive analyses. RESULTS: The 1990–2013 data from VAERS has been extracted from the VAERS database. There are 83,148 unique vaccine-symptom pairs with 75 vaccine types and 5,865 different reported symptoms. The yearly and over PRR values for each reported vaccine-symptom pair were calculated. The network properties of networks consisting of significant vaccine-symptom associations (i.e., PRR larger than 1) were then investigated. The results indicated that vaccine-symptom association network is a dense network, with any given node connected to all other nodes through an average of approximately two other nodes and a maximum of five nodes. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s13040-014-0036-y) contains supplementary material, which is available to authorized users.
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spelling pubmed-43338772015-02-20 Linked vaccine adverse event data from VAERS for biomedical data analysis and longitudinal studies Tao, Cui Wu, Puqiang Luo, Yi Zhang, Yuji BioData Min Research BACKGROUND: Vaccines have been one of the most successful public health interventions to date. The use of vaccination, however, sometimes comes with possible adverse events. The U.S. FDA/CDC Vaccine Adverse Event Reporting System (VAERS) currently contains more than 200,000 reports for post-vaccination events that occur after the administration of vaccines licensed in the United States. Although the data from the VAERS has been applied to many public health and vaccine safety studies, each individual report does not necessarily indicate a casuality relationship between the vaccine and the reported symptoms. Further statistical analysis and summarization needs to be done before this data can be leveraged. METHODS: This paper introduces our efforts on representing the vaccine-symptom correlations and their corresponding meta-information extracted from the VAERS database using Resource Description Framework (RDF). Numbers of occurrences of vaccine-symptom pairs reported to the VAERS were summarized with corresponding proportional reporting ratios (PRR) calculated. All the data was stored in an RDF file. We then applied network analysis approaches to the RDF data to illustrate a use case of the data for longititual studies. We further dicussed our vision on integrating the data with vaccine information from other sources using RDF linked approach to facilitate more comprehensive analyses. RESULTS: The 1990–2013 data from VAERS has been extracted from the VAERS database. There are 83,148 unique vaccine-symptom pairs with 75 vaccine types and 5,865 different reported symptoms. The yearly and over PRR values for each reported vaccine-symptom pair were calculated. The network properties of networks consisting of significant vaccine-symptom associations (i.e., PRR larger than 1) were then investigated. The results indicated that vaccine-symptom association network is a dense network, with any given node connected to all other nodes through an average of approximately two other nodes and a maximum of five nodes. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s13040-014-0036-y) contains supplementary material, which is available to authorized users. BioMed Central 2014-12-31 /pmc/articles/PMC4333877/ /pubmed/25699091 http://dx.doi.org/10.1186/s13040-014-0036-y Text en © Tao et al.; licensee BioMed Central. 2014 This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
spellingShingle Research
Tao, Cui
Wu, Puqiang
Luo, Yi
Zhang, Yuji
Linked vaccine adverse event data from VAERS for biomedical data analysis and longitudinal studies
title Linked vaccine adverse event data from VAERS for biomedical data analysis and longitudinal studies
title_full Linked vaccine adverse event data from VAERS for biomedical data analysis and longitudinal studies
title_fullStr Linked vaccine adverse event data from VAERS for biomedical data analysis and longitudinal studies
title_full_unstemmed Linked vaccine adverse event data from VAERS for biomedical data analysis and longitudinal studies
title_short Linked vaccine adverse event data from VAERS for biomedical data analysis and longitudinal studies
title_sort linked vaccine adverse event data from vaers for biomedical data analysis and longitudinal studies
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4333877/
https://www.ncbi.nlm.nih.gov/pubmed/25699091
http://dx.doi.org/10.1186/s13040-014-0036-y
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