The emergence and evolution of influenza A (H1α) viruses in swine in Canada and the United States
Bibliographic record
Abstract
Swine are a key reservoir host for influenza A viruses (IAVs), with the potential to cause global pandemics in humans. Gaps in surveillance in many of the world's largest swine populations impede our understanding of how novel viruses emerge and expand their spatial range in pigs. Although US swine are intensively sampled, little is known about IAV diversity in Canada's population of ~12 million pigs. By sequencing 168 viruses from multiple regions of Canada, our study reveals that IAV diversity has been underestimated in Canadian pigs for many years. Critically, a new H1 clade has emerged in Canada (H1α-3), with a two-amino acid deletion at H1 positions 146-147, that experienced rapid growth in Manitoba's swine herds during 2014-2015. H1α-3 viruses also exhibit a higher capacity to invade US swine herds, resulting in multiple recent introductions of the virus into the US Heartland following large-scale movements of pigs in this direction. From the Heartland, H1α-3 viruses have disseminated onward to both the east and west coasts of the United States, and may become established in Appalachia. These findings demonstrate how long-distance trading of live pigs facilitates the spread of IAVs, increasing viral genetic diversity and complicating pathogen control. The proliferation of novel H1α-3 viruses also highlights the need for expanded surveillance in a Canadian swine population that has long been overlooked, and may have implications for vaccine design.
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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 | 0.001 | 0.003 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".