Abstract
BackgroundVaccines are one of the most important public health successes in last century. Besides effectiveness in reducing the morbidity and mortality from many infectious diseases, a successful vaccine program also requires a rigorous assessment on their safety. Due to the limitations of adverse event (AE) data from clinical trials and post-approval surveillance systems, novel computational approaches are needed to organize, visualize, and analyze such high-dimensional complex data.ResultsIn this paper, we proposed a network-based approach to investigate the vaccine-AE association network from the Vaccine AE Reporting System (VAERS) data. Statistical summary was calculated using the VAERS raw data and represented in the Resource Description Framework (RDF). The RDF graph was leveraged for network analysis. Specifically, we compared network properties of (1) vaccine - adverse event association network based on reports collected over a 23 year period as well as each year; and (2) sex-specific vaccine-adverse event association network. We observed that (1) network diameter and average path length don’t change dramatically over a 23-year period, while the average node degree of these networks changes due to the different number of reports during different periods of time; (2) vaccine - adverse event associations derived from different sexes show sex-associated patterns in sex-specific vaccine-AE association networks.ConclusionsWe have developed a network-based approach to investigate the vaccine-AE association network from the VAERS data. To our knowledge, this is the first time that a network-based approach was used to identify sex-specific association patterns in a spontaneous reporting system database. Due to unique limitations of such passive surveillance systems, our proposed network-based approaches have the potential to summarize and analyze the associations in passive surveillance systems by (1) identifying nodes of importance, irrespective of whether they are disproportionally reported; (2) providing guidance on sex-specific recommendations in personalized vaccinology.Electronic supplementary materialThe online version of this article (doi:10.1186/s13326-015-0032-2) contains supplementary material, which is available to authorized users.
Highlights
Vaccines are one of the most important public health successes in last century
We defined that a vaccine-adverse event (AE) association is significant if proportional reporting ratio (PRR) for this association is greater than 1
Among all vaccine-AE associations reported in the Vaccine AE Reporting System (VAERS), we identified 277,698 vaccine-AE associations, 53,795 of which have overall PRR greater than 1 between 1990 and 2013
Summary
Vaccines are one of the most important public health successes in last century. Besides effectiveness in reducing the morbidity and mortality from many infectious diseases, a successful vaccine program requires a rigorous assessment on their safety. Vaccines are one of the most cost-effective public health interventions to date, leading to at least 95–99 % decrease of most vaccine-preventable diseases in the United States [1] While their benefits far overweigh their risks and costs, vaccines are accompanied with specific adverse events (AEs). Harpez et al proposed a clustering approach to identify drug groups that were reported to have same AEs [6] This approach didn’t account for all coadministered drugs and co-occurring AEs. Since VAERS receives more than 14,000 reports every year, there is a pressing need to develop novel approaches to organize these high-dimensional VAERS data and identify potential vaccine-AE associations
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
