Age and season predict influenza A virus dynamics in urban gulls: consequences for natural hosts in unnatural landscapes
Bibliographic record
Abstract
Gulls are ubiquitous in urban areas due to a growing reliance on anthropogenic feeding sites, which has led to changes in their abundance, distribution, and migration ecology, with implications for disease transmission. Gulls offer a valuable model for testing hypotheses regarding the dynamics of influenza A virus (IAV) - for which gulls are a natural reservoir in urban areas. We sampled sympatric populations of Ring-billed (Larus delawarensis), Herring (L. argentatus), and Great Black-backed Gulls (L. marinus) along the densely populated Atlantic rim of North America to understand how IAV transmission is influenced by drivers such as annual cycle, host species, age, habitat type, and their interplay. We found that horizontal transmission, rather than vertical transmission, played an outsized role in the amplification of IAV due to the convergence of gulls from different breeding grounds and age classes. We detected overlapping effects of age and season in our prevalence model, identifying juveniles during autumn as the primary drivers of the seasonal epidemic in gulls. Gulls accumulated immunity over their lifespan, however short-term fluctuations in seroprevalence were observed, suggesting that migration may impose limits on the immune system to maintain circulating antibodies. We found that gulls in coastal urban habitats had higher viral prevalence than gulls captured inland, correlating with higher richness of waterbird species along the coast, a mechanism supported by our movement data. The peak in viral prevalence in newly fledged gulls that are capable of long-distance movement has important implications for the spread of pathogens to novel hosts during the migratory season as well as for human health as gulls increasingly utilize urban habitats.
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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 | 0.001 |
| 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".