Epidemiology of <i>Salmonella</i> on the Paws and in the Faeces of Free‐Ranging Raccoons (<i>Procyon Lotor</i>) in Southern Ontario, Canada
Bibliographic record
Abstract
Raccoons are common in urban and rural environments and can carry a wide range of bacteria, including Salmonella, that can negatively affect human and livestock health. Although previous studies have reported that raccoons shed a variety of Salmonella serovars in their faeces, it is unknown whether Salmonella is carried on raccoon paws. Our objective was to compare the prevalence of Salmonella on the paws and in the faeces of raccoons in south-western Ontario. Raccoons were sampled in a repeat cross-sectional study on five swine farms and five conservation areas from May to October 2012. A total of 416 paired faecal and paw samples were collected from 285 individual raccoons. Salmonella was detected in 18% (75/416; 95% CI, 14-22%) and 27% (111/416; 95% CI, 22-31%) of paw and faecal samples, respectively. Salmonella was detected only on paws in 8% (35/416; 95% CI, 5.9-11.5%), only in faeces in 17% (71/416; 95% CI, 13.6-21.0%) and on both paws and in faeces in 10% (40/416; 95% CI, 7.0-12.9%) of raccoon captures. Multilevel logistic regression models were used to examine associations between the presence of Salmonella and age (adult, juvenile), sex (male, female), location type (swine farm, conservation area), sample type (faeces, paw) and season (May-July and August-October). Random intercepts were included to account for clustering by individual animal and location. Significant differences, that varied by sample type and season, were noted in the prevalence of Salmonella carriage between sexes. Raccoons can carry Salmonella serovars known to infect humans and livestock on their paws and/or in their faeces and therefore have the potential to mechanically and biologically disseminate Salmonella among livestock facilities and human recreational areas.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".