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An Agent-Based Modeling and Virtual Reality Application Using Distributed Simulation: Case of a COVID-19 Intensive

Jalal Possik^1,2, Ali Asgary¹, Adriano O Solis¹

¹School of Administrative Studies and Advanced Disaster, Emergency and Rapid Response SimulationYork University Toronto ON M3J 1P3 Canada.

IEEE Transactions on Engineering Management

|November 13, 2023

Summary

This study introduces a distributed simulation (DS) system integrating AnyLogic and Unity for a COVID-19 intensive care unit (ICU). This novel approach enhances training and operational assessments to minimize disease transmission.

Keywords:

Agent-based modeling (ABM)COVID-19 cloud computing discrete event simulation (DES)distributed simulation (DS)healthcare systems high-level architecture (HLA)hybrid simulation intensive care unit (ICU)interoperability virtual reality (VR)

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Area of Science:

Healthcare Operations Research
Medical Simulation Technology
Infectious Disease Modeling

Background:

Simulation methods are crucial for hospital operations, management, and training.
The COVID-19 pandemic underscored the need for advanced modeling and simulation, especially distributed simulation (DS), for rapid remote assessment.
DS integrates diverse simulations to boost overall effectiveness and usability.

Purpose of the Study:

To present a distributed simulation (DS) system integrating two distinct simulations for a COVID-19 intensive care unit (ICU).
To demonstrate the system's utility for training and assessing managerial/operational decisions aimed at reducing contact and disease spread.
To leverage DS for enhanced data exchange and synchronized operation between simulation platforms.

Main Methods:

Developed an AnyLogic simulation model of an ICU ward using agent-based and discrete event methods to depict healthcare provider-patient contacts.
Created a virtual reality simulation of the ICU environment and operations using the Unity platform.
Integrated and synchronized both simulations using a cloud-based DS system adhering to the IEEE high-level architecture standard.

Main Results:

The integrated DS system enhanced the capabilities of both individual simulations.
The system facilitates data exchange between the AnyLogic and Unity platforms.
The DS system provides a platform for effective training and assessment of operational strategies.

Conclusions:

The developed cloud-based DS system effectively integrates heterogeneous simulations for a COVID-19 ICU.
This approach supports improved training and decision-making for minimizing disease transmission in critical care settings.
Distributed simulation offers a powerful tool for enhancing healthcare operational efficiency and patient safety.