Modeling hemorrhage control in the context of agent-based active shooter simulations

Area of Science:

• Computational modeling and simulation
• Public health and emergency preparedness
• Trauma and injury research

Background:

• Active shooter events present complex challenges for emergency preparedness due to their unpredictable nature and diverse venues.
• Current simulations often use a binary "killed" or "unaffected" model, which is inadequate for assessing the impact of timely interventions.
• Previous work established a model for simulating physiological decline, highlighting the need for more nuanced injury modeling.

Purpose of the Study:

• To develop a computer simulation model for mitigating gunshot wound injuries in active shooter scenarios.
• To improve the realism of emergency preparedness simulations by incorporating injury type, blood loss, and time-to-intervention.
• To provide a foundation for further research into optimizing emergency response protocols.

Main Methods:

• Consulted multiple data sources to quantify blood outflow from gunshot wounds and the effectiveness of various mitigation techniques.
• Developed a simulation model that includes injury type, blood loss dynamics, and time lapse from injury.
• Integrated this model with previous work on physiological decline and exsanguination models.

Main Results:

• The enhanced simulation model provides a more realistic representation of active shooter events compared to traditional binary models.
• The model quantifies blood loss and the impact of different mitigation strategies, offering insights into intervention effectiveness.
• It establishes a unified deterministic model for researchers to test hypotheses regarding emergency response.

Conclusions:

• The proposed simulation model significantly enhances the fidelity of active shooter event preparedness.
• It allows for a more accurate assessment of bystander aid, first responder actions, and critical care transport times.
• This work provides a practical framework for improving emergency response protocols through advanced simulation.