Exploring the Role of Wild Bird Species in the Transmission of Avian Influenza to Poultry
Bibliographic record
Abstract
Wild aquatic birds are crucial in maintaining the high pathogenicity avian influenza (HPAI) viruses. However, the HPAI dynamic at the wild‐domestic interface is still poorly known, and a comprehensive understanding of species that could potentially act as a bridge between wetlands and poultry farms is still lacking. In this study, an eco‐epidemiological framework was used to build species distribution models for 40 wild bird species camera‐trapped at 10 poultry farms in northeastern Italy. The predicted wild bird favorability distributions were used to estimate HPAI outbreak occurrences in the area of interest, using an ensemble approach that included five methodologies: generalized linear model (GLM), generalized additive model (GAM), boosted regression trees (BRTs), random forest (RF), and maximum entropy (MaxEnt). The group of species that included most of the Ardeidae (i.e., great egret, purple heron, little egret, and cattle egret), one Galliformes (i.e., common pheasant), and one Gruiformes (i.e., common moorhen) showed the highest importance (IMP = 28%) in explaining the HPAI outbreak probability of occurrence in poultry, highlighting their potential bridging role between the reservoir species and the domestic populations. The second most important group of species (IMP = 17%) included one Anseriformes (i.e., mallard), two Charadriiformes (i.e., black‐headed gull and yellow‐legged gull), and one Ardeidae (i.e., gray heron), remarking their role in the disease ecology. These results underline the complex role of the wild‐domestic interface in the epidemiology of HPAI, suggesting that a broader range of species than what is typically considered might be involved in HPAI virus ecology. Including these groups of species in targeted surveillance programs would help in fine‐tuning sampling efforts and identifying early warning signals of possible transmission to poultry holdings.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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".