A geographic study of West Nile virus in humans, dead corvids and mosquitoes in Ontario using spatial scan statistics with a survival time application
Bibliographic record
Abstract
Surveillance of West Nile virus (WNv) in Ontario has included passive reporting of human cases and testing of trapped mosquitoes and dead birds found by the public. The dead bird surveillance programme was limited to testing within a public health unit (PHU) until a small number of birds test positive. These dead corvid and mosquito surveillance programmes have not been compared for their ability to provide early warning in geographic areas where human cases occur each year. Spatial scan statistics were applied to time-to-event survival data based on first cases of WNv in found dead corvids, mosquitoes and humans. Clusters identified using raw data were compared to clusters based on model-adjusted survival times to evaluate whether geographic and sociodemographic factors influenced their distribution. Statistically significant (p < .05) space-time clusters of PHUs with faster time to detection were found using each surveillance data stream. During 2002-2004, the corvid surveillance programme outperformed the mosquito programme in terms of time to WNv detection, while the clusters of first-positive mosquito pools were more spatially similar to first human cases. In 2006, a cluster of first-positive dead corvids was located in northern PHUs and preceded a cluster of early human cases that was identified after controlling for the influence of geographic region and sociodemographic profile.
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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) | 0.000 | 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".