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A multi-agent simulation approach to evaluating spatial interventions in emergency departments for infection control and behavioral performance
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DOI：10.1080/17452007.2026.2694392.png)
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Abstract
En 中文
Emergency departments (EDs) are characterized by both high operational intensity and elevated infection risk, where spatial and system-level interventions strongly shape behavioral dynamics and infection control performance. This study examines how an intervention bundle, consisting of coordinated spatial and operational measures, affects movement patterns and potential transmission pathways in an ED environment. A multi-agent simulation model of the emergency department (MAS-ED) was developed and applied to a real-world case in a tertiary hospital in eastern China. The model includes nine agent types, such as doctors, nurses, patients, janitorial staff, and visitors, and integrates actual spatial layouts, staffing schedules, and operational workflows to reproduce movement trajectories, space utilization, and contact-based transmission processes before and after the intervention. The results indicate that the intervention bundle significantly reduces crowding in high-risk patient room-related areas, with encounters in these zones nearly eliminated in some scenarios. However, activity patterns shift toward diagnosis areas, where interaction frequencies increase across multiple scenarios. This suggests that intervention effects are not simply a linear reduction of risk, but a spatial redistribution of interaction patterns. In terms of transmission structure, direct contact risk decreases in some scenarios, while secondary transmission chains, particularly those mediated by healthcare staff, become more prominent. Methodologically, this study extends post-occupancy evaluation from static spatial assessment to behavior-driven dynamic simulation. Practically, MAS-EDprovides a quantitative decision-support tool for optimizing safety, efficiency, and resilience in healthcare environments.
Keywords:
Emergency department
spatial intervention
agent-based modeling
infection risk transmission
post-occupancy evaluation
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