Prediction model for preventive aid actions by Belgian Red Cross at mass gatherings


Every year, volunteers of the Belgian Red Cross (BRC) provide preventive medical aid at more than 8,000 mass gatherings and other events. For optimal use of resources (personnel, materials, and money), it is important to be able to predict patient load and health care needs at these events. 

We developed and validated a prediction model of patient presentation rate (PPR) and transfer to hospital rate (TTHR) at mass gatherings in Belgium, making use of data on more than 200,000 interventions at mass gatherings during the last 10 years, stored in BRC’s Medical Triage and Registration Informatics System (MedTRIS).

The results of our analysis have now been published in BMC Public Health. Our nonlinear model performed well in predicting PPR at the events used to build the model on, but had poor predictive value for other mass gatherings. Therefore, we will keep collecting data on PPR and TTHR at mass gatherings in the future, in order to finetune the model and make better predictions of resources needed at such events.