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

IEEE Trans Eng Manag. 2022 Aug 18;70(8):2931-2943. doi: 10.1109/TEM.2022.3195813. eCollection 2023 Aug.

Abstract

Hospitals and other healthcare settings use various simulation methods to improve their operations, management, and training. The COVID-19 pandemic, with the resulting necessity for rapid and remote assessment, has highlighted the critical role of modeling and simulation in healthcare, particularly distributed simulation (DS). DS enables integration of heterogeneous simulations to further increase the usability and effectiveness of individual simulations. This article presents a DS system that integrates two different simulations developed for a hospital intensive care unit (ICU) ward dedicated to COVID-19 patients. AnyLogic has been used to develop a simulation model of the ICU ward using agent-based and discrete event modeling methods. This simulation depicts and measures physical contacts between healthcare providers and patients. The Unity platform has been utilized to develop a virtual reality simulation of the ICU environment and operations. The high-level architecture, an IEEE standard for DS, has been used to build a cloud-based DS system by integrating and synchronizing the two simulation platforms. While enhancing the capabilities of both simulations, the DS system can be used for training purposes and assessment of different managerial and operational decisions to minimize contacts and disease transmission in the ICU ward by enabling data exchange between the two simulations.

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).

Grants and funding

This work was supported in part by the Canadian Institutes of Health Research under Grant OV4-170646 and in part by the University Health Network under Grant GCS: 111163.1.