The role of ‘filth flies’ in the spread of antimicrobial resistance
Bibliographic record
Abstract
BACKGROUND: 'Filth flies' feed and develop in excrement and decaying matter and can transmit enteric pathogens to humans and animals, leading to colonization and infection. Considering these characteristics, 'filth flies' are potential vectors for the spread of antimicrobial resistance (AMR). This review defines the role of flies in the spread of AMR and identifies knowledge gaps. METHODS: The literature search (original articles, reviews indexed for PubMed) was restricted to the English language. References of identified studies were screened for additional sources. RESULTS: 'Filth flies' are colonized with antimicrobial-resistant bacteria of clinical relevance. This includes extended spectrum beta-lactamase-, carbapenemase-producing and colistin-resistant (mcr-1 positive) bacteria. Resistant bacteria in flies often share the same genotypes with bacteria from humans and animals when their habitat overlap. The risk of transmission is most likely highest for enteric bacteria as they are shed in high concentration in excrements and are easily picked up by flies. 'Filth flies' can 'bio-enhance' the transmission of AMR as bacteria multiply in the digestive tract, mouthparts and regurgitation spots. CONCLUSION: To better understand the medical importance of AMR in flies, quantitative risk assessment models should be refined and fed with additional data (e.g. vectorial capacity, colonization dose). This requires targeted ecological, epidemiological and in vivo experimental studies.
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 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".