Environmental sample characteristics and herd size associated with decreased herd-level prevalence of Mycobacterium avium ssp. paratuberculosis
Bibliographic record
Abstract
Environmental sampling is an effective method for estimating regional dairy herd-level prevalence of infection with Mycobacterium avium ssp. paratuberculosis (MAP). However, factors affecting prevalence estimates based on environmental samples are not known. The objective was to determine whether odds of environmental samples collected on farm changed culture status over 2 sampling times and if changes were specific for location and type of housing (freestall, tiestall, or loose housing), the sample collected (i.e., manure of lactating, dry, or sick cows; namely, cow group), and effects of herd size. In 2012-2013 [sampling 1 (S1)] and 2015-2017 [sampling 2 (S2)], 6 environmental samples were collected and cultured for MAP from all 167 (99%) and 160 (95%) farms, respectively, in the province of Saskatchewan, Canada. Only the 148 dairy farms sampled at both sampling periods were included in the analysis. A mixed effects logistic regression was used to determine whether differences between sampling periods were associated with herd size and sample characteristics (cow group contributing to environmental sample, type of housing, and location). In S1 and S2, 55 and 34%, respectively, of farms had at least 1 MAP-positive environmental sample. Correcting for sensitivity of environmental sampling, estimated true prevalence in S1 and S2 was 79 and 48%, respectively. Herds with >200 cows were more often MAP-positive than herds with <51 cows in both S1 and S2. The percentage of positive samples was lower in S2 compared with S1 for all sampled areas, cow groups contributing to samples, types of housing where samples were collected, and herd size categories. However, samples collected from dry cow areas had the largest decrease in MAP-positive samples in S2 compared with all other cow group samples. Herds that were MAP-negative in S1 with a herd size 51 to 100 or 101 to 150 were more likely to stay MAP-negative, whereas MAP-positive herds with >200 cows more frequently stayed MAP-positive. No difference was observed in the odds of a sample being MAP-positive among housing types or location of sample collection in both sample periods. Of all farms sampled, 104 (70%) did not change status from S1 to S2. In conclusion, when herd-level MAP prevalence decreased over the 3-yr interval, the change in prevalence differed among herd size categories and was larger in samples from dry cow areas. It was, however, not specific to other characteristics of environmental samples collected.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.002 | 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".