A multi-index investigation of the spatiotemporal relationships between heat and EMS calls during the 2015 pan american games in Toronto, Canada
Why this work is in the frame
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Bibliographic record
Abstract
Weather has a profound effect on human health and well-being, with extreme heat being one of the greatest causes of human morbidity, specifically at large gatherings such as sporting events. Various univariate, bivariate, and multivariate heat stress metrics are used to identify episodes of oppressive weather that are detrimental to human health. In an attempt to better understand weather variations in the Greater Toronto Area (GTA), Environment Canada deployed a mesonet system of 53 weather stations during the summer of 2015 during which the Pan American Games were held and where thousands of tourists and athletes visited Toronto. This research combines the mesonet data with pin-pointed EMS ambulance response data, which allows for a unique and detailed exploration of the effects of heat on human health than is traditionally possible with city-wide weather and health estimates. \n \n The goal of the current study is therefore to investigate the relationship between various heat stress metrics and heat illness in Toronto, Canada during the summer of 2015. Spatiotemporal analyses are completed through statistical comparisons between five heat stress metrics: daily temperature: maximum (Tmax) and minimum (Tmin), humidex, wet-bulb globe thermometer index, and the COMFA human energy budget (EB) model. All metrics were also compared to heat-related (HR) EMS calls for three human spatial exposure proxies (airport, averaged-city, and station-specific). With these heat metrics and the health data, the following tasks/objectives were pursued: create heat metric-based spatial maps of the GTA, determine which heat metric and spatial exposure proxy has the strongest relationship with HR EMS calls, and perform human EB case studies during the Pan American Games' sporting events at venues of escalated risk of exposure. \n \n Geospatial maps across the GTA demonstrate variations by heat metric, identifying Hamilton, Ontario as an area of escalated risk for HR illness. Additionally, statistical regression modeling of the human spatial exposure proxies and the heat stress metrics demonstrated that the more localized proxy (station-specific) and the COMFA heat metric had the strongest relationships with HR EMS calls within the city limits. A case study focused on thermal comfort at the Pan American Games' soccer venue (located in Hamilton) found that athlete and spectator EBs routinely reached the `dangerous' level of experiencing heat stress, which aligned primarily with absorbed radiation and metabolic activity values. \n \n These results provide new information on the potential benefits and uses of mesonet systems during large-scale events specific to extreme heat assessments. Findings improve our understanding of the variability among common heat metrics in relation to intra-urban heat-health burden to enhance Toronto's resilience to extreme heat. This information can be used to inform public health officials and/or urban planners alike of areas of increased heat exposure at a finer intra-urban scale, thereby creating awareness of the most crucial areas and times in which to implement corrective bioclimatic design and/or plan EMS dispatches/resources to on days of excessive heat.
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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 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 it