Longitudinal study of influenza A virus circulation in a nursery swine barn
Bibliographic record
Abstract
Commercial production of swine often involves raising animals in large groups through the use of multi-stage production systems. In such systems, pigs can experience different degrees of contact with animals of the same or different ages. Population size and degree of contact can greatly influence transmission of endemic pathogens, including influenza A virus (IAV). IAV can display high genetic variability, which can further complicate population-level patterns. Yet, the IAV transmission in large multi-site swine production systems has not been well studied. The objectives of this study were to describe the IAV circulation in a multi-source nursery facility and identify factors associated with infection in nursery pigs. Pigs from five sow herds were mixed in one all-in/all-out nursery barn, with 81 and 75 pigs included in two longitudinal studies. Virus isolation was performed in Madin-Darby canine kidney cells and serology was performed using hemagglutination inhibition assays. Risk factor analysis for virological positivity was conducted using logistic regression and stratified Cox's regression for recurrent events. In Study 1, at ≈30 days post-weaning, 100% of pigs were positive, with 43.2% of pigs being positive recurrently over the entire study period. In study 2, 48% of pigs were positive at the peak of the outbreak, and 10.7% were positive recurrently over the entire study period. The results suggest that IAV can circulate during the nursery phase in an endemic pattern and that the likelihood of recurrent infections was associated in a non-linear way with the level of heterologous (within-subtype) maternal immunity (p < 0.05). High within-pen intracluster correlation coefficients (> 0.75) were also observed for the majority of sampling times suggesting that pen-level factors played a role in infection dynamics in this study.
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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 | 0.001 |
| 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 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".