AGENT-BASED MODELING FOR CASUALTY RATE ASSESSMENT OF LARGE EVENT ACTIVE SHOOTER INCIDENTS

Abstract

The 1999 Columbine attack changed police response to the active shooter incidents (ASI) by the public and first responder's tactics and training. With FBI data suggesting ASI events increasing, this study offers an AnyLogic models to understand mitigation actions such as Run.Hide.Fight. Our model represents a general densely populated area, such as public transportation terminal or indoor arena. Model agents include civilians, police, and shooter agents interact with the following parameters: civilian evacuation time, the response of police, firearm discharge by the shooter and police. The casualty rates vary from 85 to 1 causalities when the shooter's rate of discharge was 1 to 60 seconds, respectively. The model as developed was shown to provide a method to evaluate and compare actions such as adequacy of training, introduction of technology into public buildings and the general design of public spaces to reduce the impact of ASI events.

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