A Preliminary Spatial Analysis of the Association of Asthma and Traffic-Related Air Pollution in the Metropolitan Area of Calgary, Canada
Bibliographic record
Abstract
We performed a preliminary spatial analysis to assess the association of asthma emergency visits (AEV) with ambient air pollutants (NO2, PM2.5, PM10, Black Carbon, and VOCs) over Calgary, Canada. Descriptive analyses identify spatial patterns across the city. The spatial patterns of AEV and air pollutants were analyzed by descriptive and spatial statistics (Moran’s I and Getis G). The association between AEV, air pollutants, and socioeconomic status was assessed by correlation and regression. A spatial gradient was identified, characterized by increasing AEV incidence from west to east; this pattern has become increasingly pronounced over time. The association of asthma and air pollution is consistent with the location of industrial areas and major traffic corridors. AEV exhibited more significant associations with BTEX and PM10, particularly during the summer. Over time, AEV decreased overall, though with varying temporal patterns throughout Calgary. AEV exhibited significant and seasonal associations with ambient air pollutants. Socioeconomic status is a confounding factor in AEV in Calgary, and the AEV disparities across the city are becoming more pronounced over time. Within the current pandemic, this spatial analysis is relevant and timely, bearing potential to identify hotspots linked to ambient air pollution and populations at greater risk.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.000 | 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".