A NEW SCORE TO IMPROVE RESOURCE ALLOCATION DURING MASS GATHERING EVENTS

Abstract

Mass gathering events (MGEs) place a strain on public health systems and require careful planning of healthcare resource allocation, including ambulances and personnel. The Maurer’s algorithm is commonly used to determine resource allocation, taking into account event type, location, participants, and potential public order issues. A working group from the Italian Regional Emergency and Urgency Agency (AREU) analyzed critical aspects of Maurer’s algorithm and developed the G.A.M.E.S. algorithm (Management Assistance for Sporting Events). The G.A.M.E.S. algorithm optimizes health care resource planning for MGEs and addresses the shortcomings of Maurer’s algorithm. Compared to Maurer, G.A.M.E.S. shows improved accuracy, especially for smaller events. Standardized event categorization and sports event prioritization improve resource allocation. The G.A.M.E.S. algorithm is a useful tool for predicting resource needs, especially for small and medium-sized events. Prospective validation studies are essential to assess its applicability across a wider range of contexts.

Keywords

• Mass gathering events
• preparedness
• emergency medical service
• score