Enhancing surveillance of antimicrobial resistant organisms in British Columbia through community-level wastewater testing
Bibliographic record
Abstract
Antimicrobial resistance (AMR) is a global health challenge, with carbapenemase-producing organisms (CPOs) posing a significant concern in British Columbia, Canada. Traditional surveillance focuses on hospital-associated data, overlooking community-level trends. Monitoring carbapenemase genes in communities can provide early insights into resistance trends and support antimicrobial stewardship efforts. This study employs wastewater surveillance to track antimicrobial resistance genes (ARGs) at the community level. Four ARGs, blaNDM, blaKPC, blaOXA−48, and mcr-1, were detected and quantified in wastewater samples from five treatment plants across British Columbia. The results revealed year-round ARG presence in wastewater, with blaOXA−48 being the most prevalent, followed by blaNDM, blaKPC, and mcr-1. Seasonal fluctuations were observed, with most ARGs peaking in the winter and spring, a trend not reflected in clinical data. Notably, mcr-1 was detected in wastewater despite its limited clinical presence. These results highlight the value of integrating wastewater surveillance with traditional methods to enhance AMR monitoring.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".