Applying Field and Genomic Epidemiology Methods to Investigate Transmission Networks of Highly Pathogenic Avian Influenza A (H5N1) in Domestic Poultry in British Columbia, Canada (2022–2023)
Bibliographic record
Abstract
Highly pathogenic avian influenza (HPAI) virus A (H5N1) was first detected in North America in 2021. Ongoing spillover events from wild to domestic birds and subsequent transmission between domestic birds resulted in Canada's largest recorded epidemic of HPAI. Between December 2021 and April 2024, 422 A (H5N1) outbreaks in domestic birds were confirmed in Canada. Of these, 158 (37%) occurred in British Columbia (BC). This study integrates field and genomic epidemiology (GE) results to investigate the potential for lateral or local spread between infected poultry farms in BC. Five genetically distinct viral clusters were identified during this period. Among the 31 noncommercial premises, 27 (87.1%) were classified as independent introductions, while four premises (12.9%) were attributed to local spread within 10 km of a phylogenetically connected infected premises (IP). No lateral spread events were identified among noncommercial premises. All infected noncommercial premises housed birds with outdoor access, emphasizing their susceptibility to wild bird exposure. Of the 127 infected commercial poultry premises, 21 (16.5%) were classified as independent introductions, 82 (64.6%) as local spread, 18 (14.2%) with potential for lateral spread, five (3.9%) with potential for both local and/or lateral spread, and one (0.8%) for which sequencing was unavailable. Local spread emerged as a prominent feature, with most IP in proximity to one another having genetically similar viruses. Results suggest that proximity (<200 m) to an IP was a more reliable predictor of future infection status than contact with an IP. These findings underscore the critical value of combining field and GE to understand outbreak dynamics comprehensively. This integrative approach improves resource allocation, informs targeted containment strategies, and supports the need for effective biosecurity measures to mitigate future risks, particularly in densely populated poultry production regions. Robust interventions are needed to address both independent introductions and secondary spread pathways.
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How this classification was reachedexpand
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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".