Antimicrobial resistance in <i>Escherichia coli</i> isolated from pigs and associations with aggregated antimicrobial usage in Ireland: A herd‐level exploration
Bibliographic record
Abstract
AIMS: Antimicrobial resistance (AMR) is of significant global concern and is a major One Health issue. There is evidence to suggest that increased antimicrobial usage (AMU) can be associated with AMR patterns, and therefore, there have been efforts to reduce AMU in anticipation of reducing AMR emergence risk. The aim of this study was to investigate whether there were any associations between AMU and AMR patterns of commensal Escherichia coli isolated from pig herds in Ireland. METHODS AND RESULTS: Data on AMR from a panel of antimicrobials (AMDs) were gathered as part of national surveillance activities. These data were associated with reported usage of AMDs, on a year-quarter basis, measured in mg/kg at a herd-level using generalized estimating equation regression analysis. Associations were tested with AMR presence or multi-drug resistance (MDR; ≥3 classes) profiles and total AMU during the contemporaneous quarter and previous quarter, respectively. Furthermore, individual and AMD class-based associations were tested. The final dataset contained 218 observations (herd-quarter usage and AMR resistance profile) from 122 herds during 2019-2021. Apparent resistance prevalence varied according to AMD type, with the highest mean prevalence found with tetracycline at 51.57% (95% CI: 45.06%-58.09%). There were significant associations between a herd obtaining a positive AMR result for any AMDs and the overall levels of AMU during the year-quarter. Furthermore, there were significant positive associations between MDR and total AMU. At the compound level, chloramphenicol resistance was significantly associated with increased usage of trimethoprim/sulfadiazine and chlortetracycline, respectively (p < 0.010). Tetracycline resistance was associated with increased use of chlortetracycline (p = 0.008). At the antimicrobial class level, there was a significant positive relationship between the usage of phenicol and the probability of a resistance for chloramphenicol (p = 0.026) and between the usage of tetracycline and tetracycline resistance probability (p = 0.018). CONCLUSIONS: Our data provide evidence of associations between overall AMU and AMR or MDR risk at the herd-quarter level. There was also evidence of associations between specific AMDs and patterns of resistance. Associations varied depending on whether time lags in usage were modelled or how usage was modelled (e.g. dichotomized or continuous). Associations with rarely used AMDs (e.g. critically important AMDs) were precluded due to a lack of statistical power. Continued monitoring of both AMU and AMR is crucial to assess the impacts of policy changes aimed at reducing AMU.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".