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A comparison of antibiotic resistance reports in pharmacovigilance databases and conventional surveillance across “One Health”

Bibliographic Data

ID22074271
AuthorsJoseph Mitchell (0000-0003-0806-8248, Uppsala Monitoring Centre, corresponding author), Manju Purohit (0000-0001-5385-7305, Ruxmaniben Deepchand Gardi Medical College), Pinelopi Lundquist (Uppsala Monitoring Centre), Camilla Westerberg (Uppsala Monitoring Centre), Cecilia Stålsby Lundborg (0000-0001-6525-1861, Global Policy Institute)
Year2026
Volume14
Pages1758180-1758180
Publication date2026-05-15
Peer ReviewedYes
Open AccessYes
TypeARTICLE
VenueFrontiers in Public Health (JOURNAL)
Journal identifiersISSN: 2296-2565 • E-ISSN: 2296-2565
PublisherFrontiers Media SA (PUBLISHER • CH)
DOI10.3389/fpubh.2026.1758180
PMID42221622
OpenAlexW7161299942
LanguageEN
References cited37

Introduction: Pharmacovigilance has been highlighted as a potential additional source of information to supplement conventional antibiotic resistance surveillance. However, it is not known how well the potential cases of antibiotic resistance identified in pharmacovigilance databases replicate those captured in traditional surveillance, either in human medicine or across "One Health." Methods: Cases of antibiotic resistance captured by traditional surveillance were taken from publicly available data for both humans and animals. The data sources used were the WHO Global Antibiotic Resistance and Use Surveillance System (GLASS), and the joint European Food Safety Authority (EFSA) and European Centre for Disease Prevention and Control (ECDC) report, respectively, for humans and animals. Pharmacovigilance data were taken from VigiBase, the WHO global database of adverse event reports, for humans, and from EudraVigilance Veterinary for animals. Potential antibiotic resistance cases were identified using previously reviewed search criteria. No suitable data sources were identified for environmental health. Data were grouped by Anatomical Therapeutic Chemical (ATC) class to the third level and by continent (only Europe was used for animals). Likelihood ratio tests of logistic regression models with and without an interaction between the ATC class and database were then used to compare the reported antibiotic distribution. Results: For VigiBase, there were 26,086 reports from 91 countries identified. There was a consistent statistically significant difference between the distribution of cases for at least one ATC third-level grouping. The search of EudraVigilance Veterinary identified 1,010 cases from 18 countries. Again, there was a consistent, statistically significant difference between the distribution of the cases for at least one ATC third-level grouping compared with EFSA/ECDC data. Discussion: There was more complete surveillance for humans compared to animals, with the study restricted to Europe only for animals but conducted globally for humans based on the availability of data. The absence of an appropriate data source for environmental health further highlights the need to improve surveillance in environmental health. The statistically significant differences between the antibiotic distribution should be investigated further, as this could improve the understanding of the relative strengths and weaknesses of pharmacovigilance databases as a potential supplementary tool

Adverse effect · Antibiotic resistance · Antibiotics · Drug resistance · Global health · Logistic regression · Pharmacovigilance · Antibiotic Use and Resistance · Pharmaceutical and Antibiotic Environmental Impacts · Pharmacovigilance and Adverse Drug Reactions

  • A ‘One Health’ cross-sectional analysis of reports of potential antibiotic resistance cases in international pharmacovigilance databases

    Open Access•Joseph Mitchell, Pinelopi Lundquist et al.•Frontiers in Public Health•2026

Citation velocityhistorical
Highly citedNo

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