Prevalence of Mycobacterium avium ssp. paratuberculosis infections in Canadian dairy herds
Bibliographic record
Abstract
Johne's disease is a progressive, chronic disease with inflammation of the small intestine of ruminants caused by Mycobacterium avium ssp. paratuberculosis (MAP). Accurately estimating prevalence of MAP infections is important when controlling spread of infection or monitoring effectiveness of control programs. In the absence of a consistent test method used in prevalence studies across Canada, prevalence estimates among regions and programs cannot be compared. The aim of the current study was to estimate and compare prevalence of MAP infection in Western Canada, Ontario, Québec, and the Atlantic provinces, as well as among varying herd sizes and housing types. On 362 dairy farms located in all 10 provinces of Canada, environmental samples were collected and cultured for detection of MAP. For each herd, 1 sample was collected from the lactating cow area and manure storage. An additional environmental sample was collected from the area where breeding-age heifers were housed. Using prior distributions from previous research, diagnostic sensitivity and specificity were calculated to assess the ability of only 2 environmental samples (manure storage and lactating cow area) to identify MAP-positive farms, resulting in a sensitivity and specificity of 38 and 100%, respectively. We found no difference in sensitivity and specificity when including breeding-age heifers environmental samples. Test characteristics were applied to environmental culture results from the 362 participating farms in all 4 regions, resulting in true prevalence estimates of 66% for farms in Western Canada, 54% in Ontario, 24% in Québec, and 47% in Atlantic Canada. Herds housed in tiestalls had lower prevalence than freestall-housed herds, and herds with 101-150 and >151 cows had higher prevalence than herds with ≤100 cows. This was the first time MAP prevalence was determined using 1 detection method, performed in 1 laboratory, and within a single year across Canada, enabling direct comparisons of prevalence among regions, housing types, and herd sizes.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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".