Epidemiology of <i>Campylobacter jejuni</i> in raccoons (<i>Procyon lotor</i>) on swine farms and in conservation areas in southern Ontario
Bibliographic record
Abstract
Campylobacter is a leading cause of foodborne illness in humans worldwide. Sources of infection are often difficult to identify, and are, generally, poorly understood. Recent work suggests that wildlife may represent a source of Campylobacter for human infections. Using a repeated cross-sectional study design, raccoons were trapped on five swine farms and five conservation areas in southern Ontario from 2011 to 2013. Our objectives were to: (a) assess the impact of seasonal, climatic, location, annual and raccoon demographic factors on the occurrence of Campylobacter jejuni in these animals; and (b) identify clusters of C. jejuni in space, time and space-time using spatial scan statistics. Multi-level multivariable logistic regression was used to examine the odds of isolating C. jejuni, with site and animal modelled as random intercepts. The following independent variables were examined: raccoon age and sex, year, location type, season, temperature and rainfall. A total of 1,096 samples were obtained from 627 raccoons; 46.3% were positive for C. jejuni. The following interactions and their main effects were significant (p < .05) and retained in the final model: season × temperature, year × rainfall, year × temperature. Based on the results from our multivariable model and spatial scan statistics, climatic variables (i.e. rainfall, temperature and season) were associated with the carriage of C. jejuni by raccoons, but the effects were not consistent, and varied by location and year. Although raccoons may pose a zoonotic risk due to their carriage of Campylobacter, further work is required to characterize the transmission and movement of this microorganism within the ecosystem.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".