<i>Salmonella</i> Infections in Ninety Alberta Swine Finishing Farms: Serological Prevalence, Correlation Between Culture and Serology, and Risk Factors for Infection
Bibliographic record
Abstract
The aim of this study was to determine serological prevalence for Salmonella in 90 Alberta finishing swine farms over a 5-month period; to evaluate the correlation between the detection of Salmonella by bacteriological culture and serology; and to identify risk factors for Salmonella seroprevalence. Participating farms were visited 3 times. A total of 30 blood and 15 fecal samples were collected from finishing pigs on each farm. VetScreen Salmonella covalent mix-ELISA (Svanovir) and conventional culture were performed. The apparent Salmonella seroprevalences at the sample and farm level were 13.2% (95% confidence interval [CI], 10.5-15.5%) and 83.3% (95% CI, 74-90.4%), respectively. Most of the farms had within-farm seroprevalence of <or=20%, indicating that pigs on these farms had a low exposure to Salmonella. The Salmonella farm status changed frequently across 3 visits. The correlation between fecal prevalence and seroprevalence at the farm and farm visit level was 0.71 (P < 0.0001) and 0.47 (P < 0.0001), respectively. The use of meal feed and the reported use of antimicrobials through water were associated with a lower farm seroprevalence for Salmonella. Longitudinal sampling and testing are required to properly evaluate Salmonella on-farm status. The interpretation of existing serological and culture tests for Salmonella in swine should take into consideration their imperfect sensitivity, what these tests actually measure (previous exposure vs. current shedding), and the Salmonella serovar distribution within the targeted population. Further work is necessary to demonstrate the effectiveness of on-farm interventions against Salmonella in swine.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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".