A Retrospective Analysis of Postmortem <i>Salmonella</i> Dublin Cases in Dairy Cattle in British Columbia
Bibliographic record
Abstract
Salmonella Dublin is a bovine‐adapted bacterial pathogen that primarily affects dairy cattle. The incidence of S . Dublin has been increasing across North America, including strains that are multidrug resistant. In British Columbia, the Ministry of Agriculture’s Animal Health Center (AHC) reported an increase in cases since 2015, warranting an investigation into how S . Dublin is spreading within the province. The objectives of this study were to make use of historical data collected from dairy farms across the province to (1) describe S . Dublin cases diagnosed at the AHC between 2007 and 2021, (2) identify risk factors for S . Dublin transmission across British Columbia dairy farms, and (3) identify any potential biases associated with passive laboratory‐based data that may apply to our results. We found that S . Dublin cases diagnosed at the AHC have been increasing over time. Over half of the cases had respiratory symptoms; however, clinical signs tended to be highly variable. The prevalence of respiratory symptoms was mirrored by florfenicol treatment and was suggested to be due to using a first‐line antibiotic for more common causes of pneumonia when presented with an S . Dublin case. Calves were 38 times more likely to have S . Dublin when compared to adults (odds ratio = 38.43, confidence interval = 7.26–203.64), and given the sample population (postmortem cases), it is reasonable to conclude clinical disease is most severe in this age group. Farm premise accounted for a large amount of variability within our model (92% of unexplained variance), suggesting that farm‐level management practices may be the most important risk factor for S . Dublin infection. In total, only 54% of BC dairy farms submitted to the laboratory between 2007 and 2021; however, proximity to the laboratory did not appear to influence submissions as proportionally; farms within the Fraser Valley submitted as frequently as farms from other regions. We strongly suggest that future work explore factors associated with farm management practices, given our findings regarding the clustering by premises.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| 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".