Overview of high pathogenicity avian influenza H5N1 clade 2.3.4.4b in wildlife from Central and South America, October 2022–September 2025
Bibliographic record
Abstract
Between 2022 and 2025, high pathogenicity avian influenza (HPAI) H5N1 clade 2.3.4.4b was detected in poultry and wildlife across most countries in Central and South America. The epizootic peaked in 2023, subsided in 2024, and resurged in 2025. In Central America, outbreaks in wildlife were few and small, and mostly affected pelicans. In contrast, South America experienced unprecedented mass mortality in colonial seabirds and pinnipeds, including endangered and endemic species. Notably, viral adaptation enabled mammal-to-mammal transmission in pinnipeds and rapid viral spread across multiple countries along the Pacific and Atlantic coasts. Subsequent introductions to subantarctic islands and Antarctica stemmed from South American viruses. In February 2025, a novel reassortant virus emerged, recombining HPAI H5N1 B3.2 genotype with South American low pathogenicity avian influenza viruses. In May 2025, HPAI H5N1 viruses re-emerged in Brazil, causing a series of outbreaks in poultry and wild birds. The ongoing circulation and evolution of HPAI H5N1 in this region underscores the need for strengthened surveillance, expanded genomic monitoring, and enhanced integration of wildlife conservation and environmental sectors in regional response frameworks.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.006 | 0.005 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".