Seasonal Bird Migration Could Explain Regional Synchronicity and Amplification in Human West Nile Virus Case Numbers
Bibliographic record
Abstract
West Nile virus (WNV) is a zoonotic virus with a mosquito-avian transmission cycle having occasional spillover to mammals. A network analysis of annual log-transformed WNV case numbers (2003-2022) generated four spatially and temporally coherent clusters among 48 U.S. states and six Canadian provinces. Cluster 1 and Cluster 3 were the largest groups corresponding to the Central Flyway and the closely associated Eastern Flyway (with an east-coast subset). Cluster 2 and Cluster 4 corresponded with less-well defined segments of a distinctly different Western Flyway. Thus, clustering can be explained by migratory pathways of terrestrial birds. We investigated avian involvement in the spread of WNV from potential sources in the southern U.S. Analyses revealed consistent patterns in log-transformed case numbers of human WNV. This study highlights the significant role of migratory birds in shaping the spatiotemporal patterns of WNV incidence across North America. However, the observed variability in incidence also likely reflects the interplay of other factors including local environmental conditions, mosquito populations, and regional variations in both migratory and non-migratory bird populations.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.001 | 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 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".