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Record W325402124

ADVISORY COMMITTEE REPORTS TO HEALTH CANADA ON “ANTIMICROBIALS IN FOOD ANIMALS IN CANADA: IMPACT ON RESISTANCE AND ANIMAL HEALTH”

2002· article· en· W325402124 on OpenAlexaboutno aff
John F. Prescott

Bibliographic record

VenueEurope PMC (PubMed Central) · 2002
Typearticle
Languageen
FieldEnvironmental Science
TopicPharmaceutical and Antibiotic Environmental Impacts
Canadian institutionsnot available
Fundersnot available
KeywordsAnimal healthOne HealthStakeholderMedicinePublic healthAnimal welfareMedical prescriptionPopulationAdvisory committeeFormularyEnvironmental healthVeterinary medicineBusinessPolitical scienceFamily medicinePublic relationsNursingPublic administration
DOInot available

Abstract

fetched live from OpenAlex

The report of the Committee formed to advise the Veterinary Drugs Directorate of Health Canada on animal uses of antimicrobials and their impact on resistance and human health has just been published (http://www.hc-sc.gc.ca/vetdrugs-medsvet/amr/e_policy_dev.html). Chaired by Dr Scott McEwen of the Department of Population Medicine, University of Guelph, the 20-person committee included representatives of farm organizations, the animal pharmaceutical and feed industries, medical and veterinary microbiologists, public health, consumer, and animal welfare organizations. The CVMA was represented by Dr Deb Stark. The report, if acted on, will have a major impact on how antimicrobials are used in food animals in Canada, with a significant increase in veterinary responsibility for their use. The Committee worked for 3 years to produce the 165-page report, focussed on agricultural use of antimicrobial drugs. The report contains a fairly detailed discussion of the evidence of human and animal health impacts of antimicrobial use in food animals, the international response to the problem, stakeholder perspectives on the benefits of antimicrobials in animals, and the options for managing resistance risks. The 38 recommendations are based on its analysis of how to reduce the potential resistance and human health and safety impacts of such use. Six major recommendations are made as follows: Make all antimicrobials used for disease treatment and control available by prescription only. Develop an extra-label use policy, which ensures that this practice does not endanger human health. Such a policy should include the ability to prohibit the extra-label use of specific drugs of critical importance to human health. Evaluate, register, and assign a drug identification number (DIN) to all antimicrobials used for food animals, whether they are manufactured domestically or imported. This includes antimicrobials imported in bulk (active pharmaceutical ingredients [APIs]), which should be allowed into Canada only under permit. The intent of this recommendation is to stop the direct use of APIs in food animals. Stop the importation, sale, and use of antimicrobials not evaluated and registered by Health Canada. The intent of this recommendation is to stop the “own use” loophole. Evaluate antimicrobials for growth promotion or feed efficiency by using sound risk analysis principles and rapidly phase out antimicrobial claims not fulfilling the following criteria: demonstrably effective; rarely, if ever, used in human therapy; and not likely to impair the efficacy of any other prescribed antimicrobial for human infections through development of resistant strains. In consultation with the provinces, other federal agencies, and industry groups, design and implement an ongoing, permanent national surveillance system for antimicrobial resistance arising from food-animal production. Surveillance should include indicator and pathogenic bacteria isolated from animals, food, and imported animal products. Among the more minor recommendations, aimed at veterinarians, the report recommends the following: Recommendation 20: Veterinarians and veterinary medical organizations should effectively implement the prudent-use principles developed by the CVMA and periodically review the principles and their implementation. Recommendation 21: Provincial licensing bodies and veterinary medical associations should endorse and promote the CVMA's prudent-use principles. Recommendation 38: Encourage Canadian veterinary colleges and veterinary associations to ensure that preventative medicine, prudent use of antimicrobials, and antimicrobial resistance are given high priority in veterinary undergraduate, postgraduate, and continuing education programs. The report discusses producer concerns that prescription-only access to antimicrobial drugs would drive up the cost of animal health care through higher drug costs. While not a formal recommendation, the report suggests that veterinarians are in a conflict of interest when they profit from the sale of antimicrobial drugs, and that ways be found to remove this conflict. Dr. Peter Provis, chair of the CVMA Prudent Use of Antimicrobials Working Group, commented, “The CVMA welcomes this well-argued and authoritative report, including its endorsement of the 1999 CVMA prudent-use principles. The key recommendations of the report should result in more prudent use of antimicrobial drugs in food animals in Canada, and an enhanced responsibility for veterinarians in ensuring better use of these precious resources. The CVMA will support the Veterinary Drug Directorate in its implementation of the recommendations of the report, and will continue its own commitment to prudent use through the education of its members, development and endorsement of species specific guidelines, promotion of involvement of veterinarians in on-farm food safety programs, and in other ways. Reducing antimicrobial resistance requires a long-term effort by everyone using antimicrobial drugs, and implementation of this report will be an important boost to this effort.” (by John F. Prescott, DVM, University of Guelph)

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.013
metaresearch head score (Gemma)0.020
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.061
Threshold uncertainty score0.245

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0130.020
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0020.003
Science and technology studies0.0060.002
Scholarly communication0.0050.001
Open science0.0030.001
Research integrity0.0070.007
Insufficient payload (model declined to judge)0.0310.007

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.

Opus teacher head0.025
GPT teacher head0.240
Teacher spread0.215 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreOther

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".

Quick stats

Citations17
Published2002
Admission routes1
Has abstractyes

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