Evidence map›Paper›PMID 42221622›Full record

ArticleFrontiers in public health2026

A comparison of antibiotic resistance reports in pharmacovigilance databases and conventional surveillance across "One Health".

Joseph Mitchell, Manju Purohit, Pinelopi Lundquist, Camilla Westerberg, Cecilia Stålsby Lundborg

Abstract readComparative Study
In one paragraph

Article in Frontiers in public health, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Joseph MitchellDepartment of Global Public Health, Health Systems and Policy: Improving Use of Medicines, Karolinska Institutet, Stockholm, Sweden.
Manju PurohitDepartment of Global Public Health, Health Systems and Policy: Improving Use of Medicines, Karolinska Institutet, Stockholm, Sweden.
Pinelopi LundquistUppsala Monitoring Centre, Uppsala, Sweden.
Camilla WesterbergUppsala Monitoring Centre, Uppsala, Sweden.
Cecilia Stålsby LundborgDepartment of Global Public Health, Health Systems and Policy: Improving Use of Medicines, Karolinska Institutet, Stockholm, Sweden.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

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.

Indexed as

Anti-Bacterial AgentsDatabases, FactualDrug Resistance, BacterialDrug Resistance, MicrobialOne HealthPharmacovigilanceAnimalsHumansAnti-Bacterial Agentsantibiotic resistanceEudraVigilance VeterinaryGLASSOne HealthpharmacovigilanceVigiBase

Identifiers

PMID42221622
PMCPMC13219042

What Socratic holds

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LicenceCC BY
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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.