Predicting resource use at mass gatherings using a simplified stratification scoring model.

INTRODUCTION: Mass gathering events require varying types and amounts of medical resources to deal with patient presentations. The needs of various events have so far been difficult to predict with precision, yet likely are impacted by several factors which may be used in a predictive fashion.

HYPOTHESIS: Medical needs at mass gathering events can be predicted based on a combination of weather, number in attendance, presence of alcohol, demographic of the participants in attendance, and crowd intentions. Furthermore, each of these factors can be assigned a score and events can be stratified based on that score.

METHODS: Fifty-five mass gathering events of varying type occurring in proximity to a large mid-Atlantic university were analyzed retrospectively. Based on a scoring system using the factors described, the events were categorized as "minor," "intermediate," or "major." The actual medical needs at each event were then analyzed.

RESULTS: Twelve events were classified a priori as "minor," 20 events were classified as "intermediate," and 23 received a classification of "major." These events had averages of 2.3, 6.3, and 71 total contacts, respectively. These trends were consistent for minor encounters, major encounters, and transports. The classification system correctly predicted the resource demand for the 3 classes of events.

CONCLUSION: A classification system that stratifies events based on weather, number in attendance, presence of alcohol, demographic in attendance, and crowd intentions can effectively predict medical needs at mass gatherings. This system is most accurate in the description of minor- and intermediate-type events; major events were less well described by this classification system.