Workforce planning for first aid and medical coverage of mass gatherings is hampered by limited research. In particular, the characteristics and likely presentation patterns of low-volume mass gatherings of between several hundred to several thousand people are poorly described in the existing literature.

This study was conducted to:

1. Describe key patient and event characteristics of medical presentations at a series of mass gatherings, including events smaller than those previously described in the literature;

2. Determine whether event type and event size affect the mean number of patients presenting for treatment per event, and specifically, whether the 1:2,000 deployment rule used by St John Ambulance Australia is appropriate; and

3. Identify factors that are predictive of injury at mass gatherings.

A retrospective, observational, case-series design was used to examine all cases treated by two Divisions of St John Ambulance (Queensland) in the greater metropolitan Brisbane region over a three-year period (01 January 2002–31 December 2004). Data were obtained from routinely collected patient treatment forms completed by St John officers at the time of treatment. Event-related data (e.g., weather, event size) were obtained from event forms designed for this study. Outcome measures include: total and average number of patient presentations for each event; event type; and event size category. Descriptive analyses were conducted using chi-square tests, and mean presentations per event and event type were investigated using Kruskal-Wallis tests. Logistic regression analyses were used to identify variables independently associated with injury presentation (compared with non-injury presentations).

Over the three-year study period, St John Ambulance officers treated 705 patients over 156 separate events. The mean number of patients who presented with any medical condition at small events (≤2,000 attendees) did not differ significantly from that of large (>2,000 attendees) events (4.44 vs. 4.67, F = 0.72, df = 1, 154, p = 0.79). Logistic regression analyses indicated that presentation with an injury compared with non-injury was independently associated with male gender, winter season, and sporting events, even after adjusting for relevant variables.

In this study of low-volume mass gatherings, a similar number of patients sought medical treatment at small (<2,000 patrons) and large (>2,000 patrons) events. This demonstrates that for low-volume mass gatherings, planning based solely on anticipated event size may be flawed, and could lead to inappropriate levels of first-aid coverage. This study also highlights the importance of considering other factors, such as event type and patient characteristics, when determining appropriate first-aid resourcing for low-volume events. Additionally, identification of factors predictive of injury presentations at mass gatherings has the potential to significantly enhance the ability of event coordinators to plan effective prevention strategies and response capability for these events.

St John Ambulance Operations Branch Volunteers have been providing first-aid services at the Royal Adelaide Show for 90 years. The project arose from a need to more accurately predict the workload for first-aid providers at mass gathering events. A formal analysis of workload patterns and the determinants of workload had not been performed.

Casualty presentation workload would be predicted by factors including day of the week, weather, and crowd size.

Collated and analyzed casualty reports over a seven-year period representing >7,000 patients who presented for first-aid assistance for that period (63 show days) were reviewed retrospectively.

Casualty presentations correlated significantly with crowd size, maximum daily temperature, humidity, and day of the week. Patient presentation rate had heterogeneous determinants. The most frequent presentation was minor medical problems with Wednesdays attracting higher casualty presentations and more major medical categories.

Individual event analysis is a useful mechanism to assist in determining resource allocation at mass gathering events providing an evidence base upon which to make decisions about future needs. Subsequent analysis of other events will assist in supporting accurate predictor models.