The changing dynamics of highly pathogenic avian influenza H5N1: Next steps for management & science in North America
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Highly pathogenic avian influenza virus (HPAIV) H5N1 was introduced in North America in late 2021 through trans-Atlantic pathways via migratory birds. These introductions have resulted in an unprecedented epizootic, a widespread disease event in animals, heavily affecting poultry, wild birds, and recently mammals. The North American incursions occurred during the largest epidemic season (2021–2022) in Europe where H5N1 may now be endemic (i.e., continuously present). The continuing outbreak includes expansion into Mexico, Central and South America beginning in late 2022. Here, we provide an overview of the Eurasian origin H5N1 introduction to the Americas, including a significant shift in virus dynamics and severe disease in wild birds. Then, to investigate the global changes in confirmed detections in wild birds and poultry across time and geographic regions, we analyzed FAO's EMPRES-i + database. To examine the 2021 introduction and spread in North American wild birds and poultry, we collated publicly available data across USA and Canadian federal sources. Based on our assessment, the unique magnitude of the North American H5N1 spread indicates the need for effective decision framing to prioritize management needs and scientific inquiry, particularly for species at risk and interface areas for wildlife, poultry, and humans. We illustrate the rapidly occurring and likely increasing detrimental effects that this One Health issue has on wildlife, agriculture, and potentially human health, and we offer a reframing of HPAIV disease response towards a decision analytical context to guide scientific prioritization as a potentially valuable change in focus.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| 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 it