Dynamics of a Panzootic: Genomic Insights, Host Range, and Epidemiology of the Highly Pathogenic Avian Influenza A(H5N1) Clade 2.3.4.4b in the United States
Bibliographic record
Abstract
In late 2021, Eurasian-lineage highly pathogenic avian influenza (HPAI) A(H5N1) viruses from HA clade 2.3.4.4b were first detected in the United States. These viruses have caused severe morbidity and mortality in poultry and have been detected in numerous wild and domestic animals, including cows and humans. Notably, infected cows transmitted the virus to cats, causing extreme pathogenicity and death. While human-to-human spread of the virus has not been recorded, efficient transmission of the bovine-origin virus has also led to extreme pathogenicity and death in ferret models. Recently, markers in PB2 (E627K) and HA (E186D, Q222H), indicating mammalian adaptation mutations, were detected in an H5N1-infected patient manifesting critical illness in Canada. These, combined with instances of interspecies spread of the virus, have raised global public health concerns. This could highlight the potential for the virus to successfully adapt to mammals, posing a serious risk of a global outbreak. A One Health approach is, thereby, necessary to monitor and control the outbreak. This review aims to analyze the epidemiology, transmission, and ecological impacts of HPAI A(H5N1) clade 2.3.4.4b in the U.S., identify knowledge gaps, and inform strategies for effective outbreak management and mitigation.
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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 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| 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".