Modeling Monthly Variation of Culex tarsalis (Diptera: Culicidae) Abundance and West Nile Virus Infection Rate in the Canadian Prairies
Bibliographic record
Abstract
The Canadian prairie provinces of Alberta, Saskatchewan, and Manitoba have generally reported the highest human incidence of West Nile virus (WNV) in Canada. In this study, environmental and biotic factors were used to predict numbers of Culex tarsalis Coquillett, which is the primary mosquito vector of WNV in this region, and prevalence of WNV infection in Cx. tarsalis in the Canadian prairies. The results showed that higher mean temperature and elevated time lagged mean temperature were associated with increased numbers of Cx. tarsalis and higher WNV infection rates. However, increasing precipitation was associated with higher abundance of Cx. tarsalis and lower WNV infection rate. In addition, this study found that increased temperature fluctuation and wetland land cover were associated with decreased infection rate in the Cx. tarsalis population. The resulting monthly models can be used to inform public health interventions by improving the predictions of population abundance of Cx. tarsalis and the transmission intensity of WNV in the Canadian prairies. Furthermore, these models can also be used to examine the potential effects of climate change on the vector population abundance and the distribution of WNV.
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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 | 0.002 | 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".