Mass gathering manifestations attended by large crowds are an increasingly common feature of society. Each year, the Belgian Red Cross (BRC) provides first aid services at >8000 public events, including mass gatherings (music, sport, festival, etc.). Mass gatherings are associated with increased health risks and hazards such as the transmission of communicable diseases, exacerbation of non-communicable diseases and comorbidities, an increased number of patients presented at first aid posts and an increased number of patients that need to be transported to the hospital.
In order to formulate evidence-based, robust and effective interventions in the planning and management of first aid services at mass gatherings, CEBaP supports BRC Relief Service to scientifically underpin their preventive relief actions. In a first project, we conducted a systematic review to identify existing multivariable prediction models for medical usage rates at mass gatherings, to summarize the evidence for individual biomedical, psychosocial and environmental predictors at mass gatherings, and to summarize the predictive performance of these models.
We included 16 studies that developed or validated prediction models in the USA (n = 8), Australia (n = 4), Japan (n = 1), Singapore (n = 1), South Africa (n = 1) and The Netherlands (n = 1), with a combined audience of >48 million people in >1700 mass gatherings. Variables to predict medical usage rates were biomedical (i.e. age, gender, level of competition, training characteristics and type of injury) and environmental predictors (i.e. crowd size, accommodation, weather, free water availability, time of the manifestation and type of the manifestation) (low-certainty evidence). Evidence from 3 studies indicated that using existing models in other contexts significantly over- or underestimated medical usage rates (from 22% overestimation to 81% underestimation).
Since the overall certainty of the evidence is low and the predictive performance is generally poor, proper development and validation of a context-specific model is recommended. Therefore, in a second ongoing project, CEBaP will use data collected by BRC Relief Service at mass gatherings to develop and validate our own matrix to predict patient presentation rate and transfer to hospital rate at different Flemish mass gathering manifestations. Further details will follow later.