Medical Support for the 2009 World Police and Fire Games: A Descriptive Analysis of a Large-Scale Participation Event and its Impact
Bibliographic record
Abstract
INTRODUCTION: In the summer of 2009, British Columbia hosted the World Police and Fire Games (WPFG). The event brought together 10,599 athletes from 55 countries. In this descriptive, Canadian study, the composition of the medical team is analyzed, the unique challenges faced are discussed, and an analysis of the illness and injury rates is presented. This event occurred during a labor dispute affecting the sole provider of emergency ambulance service in the jurisdiction, which necessitated additional planning and resource allocation. As such, the context of this event as it relates to the literature on mass gathering medicine is discussed with a focus on how large-scale public events can impact emergency services for the community. METHODS: This is a case report study. RESULTS: There were 1,462 patient encounters. The majority involved musculo-skeletal injuries (53.8%). The patient presentation rate (PPR) was 109.40/1,000. The medical transfer rate (MTR) was 2.32/1,000. The ambulance transfer rate (ATR) for the 2009 WPFG was 0.52/1,000. In total, 31 patients were transported to the hospital, the majority for diagnostic evaluation. Only seven calls were placed to 9-1-1 for emergency ambulance service. CONCLUSIONS: The 2009 WPFG was a mass-gathering sporting event that presented specific challenges in relation to medical support. Despite relatively high patient presentation rates, the widely spread geography of the event, and a reduced ability to depend on 9-1-1 emergency medical services, there was minimal impact on local emergency services. Adequate planning and preparation is crucial for events that have the potential to degrade existing public resources and access to emergency health services for participants and the public at large.
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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) | 0.001 | 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".