Method of predicting the number of casualties in the Sydney City‐to‐Surf fun runs[1]
Summary
Describes a simple method for predicting the number of casualties requiring urgent medical attention at the Sydney City-to-Surf fun runs, built from prior years' experience and driven by weather forecasts and entry numbers. Applied prospectively in 1983 and 1984, the predicted casualty counts were consistent with actual counts, and the predictions were used to deploy human and material resources effectively, with all casualties treated efficiently.
So what
The origin point of casualty prediction in event medicine: the first published demonstration that a weather-plus-attendance model could prospectively forecast urgent casualties well enough to size the medical deployment — pre-dating Arbon's regression models by nearly two decades and establishing the City-to-Surf as the field's longest-running prediction laboratory. Every PPR model on this site descends from this method; its two variables (entries, forecast weather) remain the dominant terms in every successor model, which is itself a finding worth stating.
Key findings
- First published prospective casualty-prediction method for a mass-participation event
- Inputs: prior-year experience, weather forecast, number of entries
- 1983 and 1984 predictions consistent with actual casualty counts
- Predictions used to size and deploy resources effectively
- Ancestor of the Arbon/Zeitz/nonlinear prediction lineage
Read the paper
- Publisher (DOI) ↗may be paywalled
- PubMed ↗abstract · free