INFLUENZA A VIRUSES OF SWINE IN WESTERN CANADIAN PIGS AND PEOPLE
Bibliographic record
Abstract
Influenza A viruses (IAV) are well-known for their zoonotic potential, and the health and economic threats they pose to humans and pigs. The complexity of influenza virus ecology involving genetically variant viral strains and several natural hosts means that the virus continuously challenges the host-species barrier. Surveillance of IAV is essential as it provides helpful information that can lead to a better understanding of the behavior of the virus at the animal-human interface, the risk factors and the key genetic changes that allow the virus to cross the species barrier. The research aimed to compare the suitability of samples collected for the detection of IAV in swine and to identify the epidemiological and viral factors that might play a fundamental role in the human-swine interface of transmission. The suitability of three types of samples for the detection of IAV in pigs, nasal swabs (NS), oral fluids (OF) and oral swabs (OS), was compared. IAV Matrix gene PCR results showed NS were the most effective method of IAV detection in swine. Compared to NS, OS had a relative sensitivity of 43.6% to 43.8% and relative specificity of 99.3% to 100%. The relative sensitivity and specificity of OF was 57.1% and 95.5%, respectively. Furthermore, the degree of agreement between NS and the other two samples was moderate (k = 0.531-0.583, p < 0.001). Human-swine transmission was evaluated through a pilot project consisting of active surveillance in both swine workers and pigs from 11 farms in Western Canada. Nasal swabs, OS, and surveys assessing flu-like symptoms were collected from 26 swine workers and results were compared with Matrix real-time reverse transcriptase PCR (RT-qPCR) results from swine nasal swabs. There was no statistically significant correlation between the clinical symptoms in humans and the RT-qPCR results from swine samples. However, the IAV Matrix gene PCR results from the NS and OS of the swine workers had a very weak correlation with the results found in swine (r = 0.182-0.200, p = 0.024- 0.040). Transmission among species was not confirmed, but samples with suspect results from human samples coincided with positive swine pool results and the presence of an Alpha H1N2 virus in 4 farms, which is suggestive of a common link between humans and pigs for IAV.
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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 | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".