Widespread antimicrobial use in laboratory rodent vivaria in North America revealed by a cross-sectional survey of American College of Laboratory Animal Medicine certified veterinarians
Bibliographic record
Abstract
Antimicrobial resistance (AMR) is a major global threat to human health, animal welfare and sustainable development. Whilst resistance can arise naturally, inappropriate antimicrobial exposure accelerates its emergence. Recognizing this risk, international One Health initiatives emphasize reducing antimicrobial use, especially of drugs considered critical for human medicine. Much of the evidence guiding these efforts comes from food-producing and companion animals, but antimicrobial use in laboratory animals, particularly rodents, remains poorly described. To address this gap, we surveyed all veterinarians certified by the American College of Laboratory Animal Medicine in the United States (921) and Canada (10). A total of 157 veterinarians completed the survey, resulting in a 16.9% overall response rate. The response rate was 16.6% for participants in the United States and 40.0% for those in Canada. Despite a strong response, the small number of eligible veterinarians restricts data extrapolation in the Canadian context. Survey results showed that antimicrobial use is common and routine in rodent vivaria. Overall, 91.7% of respondents reported regular antimicrobial use. Applications included both clinical treatment and research purposes such as induction of microbiome dysbiosis, prophylaxis in immunocompromised rodents and gene induction. Reported drug classes included fluoroquinolones and third-generation cephalosporins, with some use of glycopeptides and carbapenems, all considered critically important to human health. Disposal practices often involved release into sewerage or landfill without inactivation, raising environmental concerns. These findings suggest that antimicrobial use in laboratory rodents may represent an underrecognized contributor to AMR and highlight the importance of targeted stewardship.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.005 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".