Modeling the Lagged and Nonlinear Effects of Weather Conditions on Abundance of Culex Tarsalis Mosquitoes in Saskatchewan, Western Canada Using a Bi-Dimensional Distributed Lag Nonlinear Model
Bibliographic record
Abstract
The establishment of West Nile Virus (WNV) competent vectors continues to pose a major public health challenge in Canada, especially in the south. While studies have examined the association between weather conditions and the abundance of mosquitoes over trap weeks, there is limited research on the effects of weather conditions on the abundance of Culex tarsalis (Cx. tarsalis) mosquitoes for a lapse of time beyond the trap week in Saskatchewan, Western Canada. To address this gap, we analyzed provincially available weekly mosquito trap and co-incident meteorological station data in Saskatchewan from 2010 to 2021 using a bi-dimensional distributed lag and nonlinear model. Data indicate that 171,141 Cx. tarsalis mosquitoes were trapped across much of Saskatchewan, from 2010 to 2021. Cx. tarsalis were found to be most abundant between weeks 26 and 35 (July and August) and peaked in weeks 30 and 31. Based on the WNV-positive pools, mosquito infection rates increased from week 23 to 36. While weekly average maximum air temperatures between 20 °Cand 30 °C were associated with more Cx. tarsalis across all lags (0 - 8 weeks), higher weekly average minimum air temperatures had a strong and immediate effect that diminished over longer lags. Higher weekly average rainfall amounts (> 20 mm) were associated with fewer Cx. tarsalis mosquitoes across all lags, while average weekly rainfall between 8 and 20 mm was strongly associated with a high abundance of Cx. tarsalis mosquitoes over longer lags (5 -7 weeks). Additionally, increasing wind speed was associated with lower abundance of Cx. tarsalis across all lags. Findings identified nonlinear lag associations for weekly average maximum air temperature and rainfall, but linear associations for weekly average minimum air temperature and wind speed. Identified lags and thresholds for temperature, rainfall, and wind speed at which mosquito abundance peaked could help to inform public health authorities in timing of vector control measures to prevent WNV transmission.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".