Can existing data on West Nile virus infection in birds and mosquitos explain strain replacement?
Bibliographic record
Abstract
Abstract Understanding pathogen strain displacement is important for predicting and managing the spread of infectious disease. However, a mechanistic understanding for the outcome of pathogen competition often remains unresolved, as in the case of the displacement of the West Nile virus (WNV) NY99 genotype by the newer WN02 genotype. In this study, we seek to explain the observed displacement of the NY99 genotype by examining evidence for differences between NY99 and WN02 over WNV's entire transmission cycle. We synthesized the available empirical data on key aspects of WNV's transmission cycle including viral titer profiles in birds, survival of birds, bird‐to‐mosquito transmission probability, and mosquito‐to‐bird transmission probability for infections with both the NY99 and WN02 genotypes of WNV. Using a Bayesian statistical framework, we combine our literature synthesis on infection dynamics in birds and mosquitos with bird community and mosquito life history parameters to examine fitness differences between NY99 and WN02. We calculate the intrinsic reproduction numbers ( ) for NY99 and WN02 and assume a larger value of for WN02 will explain its competitive dominance over NY99. Our analysis of the collective body of experimental infections of birds and mosquitos produced similar estimates for NY99 and WN02 with wide overlapping credible intervals, which we take as insufficient evidence for greater fitness of WN02. The currently cited explanation for the displacement of WN02 by NY99—the attribution of the displacement of NY99 by WN02 to the latter's more efficient replication in mosquitos—is, at best, weakly supported by the evidence. Further infection studies of American Robins (Turdus migratorius) and broader coverage of possibly competent hosts for WN02, as well as more ecological data such as the spatial and temporal differences in vector and bird communities, will be needed to fully understand the community dynamics of WNV and the determinants of higher fitness in the WN02 genotype.
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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 | 0.008 | 0.033 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".