Antimicrobial Use and Awareness of Antimicrobial Resistance in the Livestock Sector in the Western Balkans
Bibliographic record
Abstract
Background/Objectives: Antimicrobial resistance (AMR) is a major threat to human, animal, and environmental health. To tackle AMR in the livestock sector, there is a need to understand the antimicrobial use (AMU) practices of different stakeholders in order to target the common knowledge gaps and inappropriate practices with tailored interventions. In the Western Balkans, published evidence shows the presence of AMR in both humans and animals. Since studies on AMU have mainly been conducted in humans, there is a significant knowledge gap about AMU in the livestock sector. The aim of this study was to assess the knowledge, attitudes, and practices of farmers, veterinarians, veterinary pharmacy personnel, and feed mill personnel related to AMU (focusing on antibiotics) and AMR in Albania, Bosnia and Herzegovina, Kosovo (References to Kosovo shall be understood to be in the context of Security Council resolution 1244 (1999)), Montenegro, North Macedonia, and Serbia. Methods: Field interviews were conducted in 2022 with 2815 participants in selected regions of the countries. Results: The findings showed that farmers engaged in imprudent practices, including purchasing antimicrobials without a prescription, administering antimicrobials for growth promotion, and disposing of expired antimicrobials in the garbage. Farmers’ main knowledge gaps were related to the duration of antimicrobial treatment and the differentiation between AMR and antimicrobial residues. This study also revealed poor record-keeping on animal treatments and a lack of some biosecurity measures. In terms of the attitudes and practices of veterinarians and veterinary pharmacy personnel, the belief that antimicrobial drugs are important for growth promotion, and the common use and sales of highest priority critically important antimicrobials should be targets for future interventions. Conclusions: Despite significant ongoing efforts to tackle AMR, there is still a need for training, awareness-raising, and policy interventions to address the knowledge gaps identified by this study and optimize AMU in the livestock sector in the Western Balkans.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".