Evaluation of Agricultural Interventions on Human and Poultry-Related <i>Salmonella</i> Enteritidis in British Columbia
Bibliographic record
Abstract
A collaborative investigation between public health and animal health led to numerous interventions along the food chain in response to an outbreak of human salmonellosis and increased incidence of Salmonella Enteritidis (SE) among poultry. Incidence of both human and chicken SE decreased substantially in 2012 and 2013 following these interventions. We used time series analysis to assess the impact of three interventions: vaccination of broiler breeder flocks, separation in the hatchery of breeder eggs, and an industry order to stop farm-gate sales of ungraded broiler hatching eggs. Results show a Granger causal association between human SE incidence and SE incidence in chickens 8 months earlier. Among the interventions, separation of breeder flocks showed a consistent and statistically significant association with declining SE incidence in chickens. Our results did not show consistent declines in chicken SE following breeder flock vaccination (live or inactivated vaccine). None of the interventions had statistically significant impacts on human SE incidence. Our results are consistent with a positive effect of certain interventions and also reveal where additional data are needed for a more comprehensive evaluation. Multiple interventions throughout the food chain are best practices when dealing with enteric pathogens; collecting data on the timing and intensity of these interventions allow proper evaluation of their independent and combined effects. Finally, we identify considerations for others interested in undertaking similar evaluations. Ongoing collaborative work between public health and animal health is required to refine strategies for SE control in British Columbia.
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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 | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".