Airport emergencies are rare but potentially catastrophic; therefore, system preparedness is crucial. Airport emergency plans include the organization of emergency drills on a regular basis, including full-scale exercises, to train and test the entire rescue organization.

This report describes a full-scale simulation at Bologna International Airport, Italy, in October 2022, involving local EMS resources.

A full-scale aeroplane crash was simulated on the airport ground, activating the Airport emergency plan, and requiring the intervention of supplementary resources (ambulances, medical cars, and other emergency vehicles).

Twenty-seven simulated patients were evaluated by EMS: START triage assessment was correct for 81.48% of patients; 11.11% were over-triaged and 7.41% were under-triaged. All patients were transported to the hospitals of the area. The simulation ended 2 hours and 28 minutes after the initial alarm.

The response time proved a good response. Triage accuracy was correct in more than 80% of simulated patients. The availability of a trauma centre within 6 kilometres allowed the transportation of a quota of patients directly from the event, without affecting transportation times. Areas for improvement were identified in the communication within the different agencies and in moving ambulances within the airport runway without airport personnel guidance.

Mass-casualty incidents (MCIs) and disasters are characterized by a high heterogeneity of effects and may pose important logistic challenges that could hamper the emergency rescue operations.

The main objective of this study was to establish the most frequent logistic challenges (red flags) observed in a series of Italian disasters with a problem-based approach and to verify if the 80-20 rule of the Pareto principle is respected.

A series of 138 major events from 1944 through 2020 with a Disaster Severity Score (DSS) ≥ four and five or more victims were analyzed for the presence of twelve pre-determined red flags.

A Pareto graph was built considering the most frequently observed red flags, and eventual correlations between the number of red flags and the components of the DSS were investigated.

Eight out of twelve red flags covered 80% of the events, therefore not respecting the 80-20 rule; the number of red flags showed a low positive correlation with most of the components of the DSS score. The Pareto analysis showed that potential hazards, casualty nest area > 2.5km2, number of victims over 50, evacuation noria over 20km, number of nests > five, need for extrication, complex access to victims, and complex nest development were the most frequently observed red flags.

Logistic problems observed in MCIs and disaster scenarios do not follow the 80-20 Pareto rule; this demands for careful and early evaluation of different logistic red flags to appropriately tailor the rescue response.