A Scoping Review of the Role of Wildlife in the Transmission of Bacterial Pathogens and Antimicrobial Resistance to the Food Chain
Bibliographic record
Abstract
Wildlife can contribute to environmental contamination with bacterial pathogens and their transfer to the human food chain. Global usage and frequent misuse of antimicrobials contribute to emergence of new antimicrobial resistant (AMR) strains of foodborne pathogens. We conducted a scoping review of published research to identify and characterize the evidence on wildlife's role in transmission of AMR and/or bacterial pathogens to the food chain. An advisory group (AG) of 13 North American experts from diverse disciplines was surveyed to solicit insight in the review scope, priority topics and research characteristics. A pre-tested search strategy was implemented in seven bibliographic databases (1990 to January 2013). Citations were relevance screened, and key characteristics on priority topics extracted independently by two reviewers. Analysis identified topic areas with solid evidence and main knowledge gaps. North America reported 30% of 866 relevant articles. The prevalence of five targeted bacterial pathogens and/or AMR in any pathogen in wildlife was reported in 582 articles. Transmission risk factors for selected bacteria or AMR in any bacteria were reported in 300. Interventions to control transmission were discussed in 124 articles and formally evaluated in 50. The majority of primary research investigated birds, cervids, rodents, feral pigs, opossums, E. coli (n = 329), Salmonella (n = 293) and Campylobacter (n = 124). An association between wildlife and transmission of bacterial pathogens and/or AMR to the food chain was supported in 122 studies. The scoping review identified a significant body of research on the role of wild birds in the prevalence and transmission of E. coli, Salmonella and Campylobacter. There was little research employing molecular methods contributing to the evidence concerning the importance and direction of transmission of wildlife/pathogen combinations. Given the advancements of these methods, future research should focus in this area to help prioritize future intervention studies and risk mitigation strategies.
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 | 0.016 | 0.070 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.006 | 0.006 |
| Bibliometrics | 0.028 | 0.030 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.006 | 0.005 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.004 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".