Evidence of a decrease in sales of antimicrobials of very high importance for humans in dairy herds after a new regulation restricting their use in Quebec, Canada
Bibliographic record
Abstract
In the province of Quebec, Canada, a new regulation restricting usage of antimicrobials of very high importance for human health (Health Canada: category 1 antimicrobials) in production animals is effective since February 2019. The objective of this study was to estimate changes in AM sales in dairy herds after the implementation of the regulation. Therefore, invoice data were extracted from veterinary software, Vet-Expert, used by most dairy veterinarians in the province of Quebec, and antimicrobial quantities were transformed in Canadian defined course doses for cattle (DCDbovCA). The sum of antimicrobials sales monthly in each herd was estimated in DCDbovCA from June 2016 to May 2020. To evaluate the herd-level change in AM sales and the impact of different factors, the number of DCDbovCA by herd from June 2017 to May 2018 (pre-regulation period) were compared with those of June 2019 to May 2020 (post-regulation period). Total category 1 AM sales of 3,569 Quebec's herds went from a range of 14,258 to 21,528 DCDbovCA/month to a range of 1,494 to 4,707 DCDbovCA/month after the implementation of the new regulation. Moreover, using data from 3,337 herds, we estimated a mean (95% confidence interval) reduction in 19 DCDbovCA/herd-year (14.8, 24.2), while the pre-regulation herd-level category 1 AM sales was 26 DCDbovCA/herd-year. This reduction was achieved without evidence of an increase in other antimicrobials. Finally, the veterinary facility associated with the herd was an important determinant of the herd-level reduction in category 1 antimicrobials. This study was the first to quantify a significant reduction in category 1 AM sales following the implementation of a restrictive regulation in dairy production in Canada. These results demonstrate that such an approach is effective to reduce the sales of a specific category of antimicrobial in animal production.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 source (direct Gemma or distilled Codex), 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".