Prevalence of Zoonotic Bacteria in Wild and Farmed Aquatic Species and Seafood: A Scoping Study, Systematic Review, and Meta-analysis of Published Research
Bibliographic record
Abstract
Increased reliance on seafood has brought to light concerns regarding food safety, but the information to inform risk assessment or surveillance needs is lacking. A scoping study (ScS) was conducted to characterize published research investigating selected zoonotic bacteria and public health topics in various wild and farmed aquatic species and seafood. This was followed by a systematic review (SR) on selected bacteria (Aeromonas spp., generic Escherichia coli, Salmonella spp., and Vibrio spp.) and aquatic species (clams, mussels, oysters, salmon, and shrimp [including prawn]); a meta-analysis (MA) was conducted only at the retail level due to considerable variability among various pathogen/seafood combinations. The ScS revealed the most frequently investigated themes were farm-level prevalence and intervention research for Vibrio spp. and Aeromonas spp. Antimicrobial use (AMU) and the association between AMU and antimicrobial resistance were rarely investigated. The SR indicated a consistent lack of reporting regarding study methodology and results, precluding the use of many studies in and full benefits of MA. MA of Aeromonas, E. coli, and Salmonella prevalence in retail salmon resulted in pooled estimates of 13% (6-27%), 2% (0.1-11%), and 1% (0-5%), respectively. When MA of pathogen/seafood combination resulted in statistically significant heterogeneity (p<0.1), median/range were reported at the region level. The results from our ScS, SR, and MA could be used for better design of future bacteriological surveys of seafood and as inputs for risk assessments or surveillance initiatives in this field.
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 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 | 0.030 | 0.080 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.015 | 0.027 |
| Bibliometrics | 0.018 | 0.017 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.002 | 0.002 |
| 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".