Leveraging digital twin for healthcare emergency management system: Recent advances, critical challenges, and future directions

In the post COVID-19 era, there is an escalating demand to fundamentally rethink and digitalize healthcare emergency management (HEM) to ensure greater resilience and responsiveness. Among emerging technologies, the digital twin (DT) holds unique promise by enabling real-time monitoring, dynamic decision support, and predictive maintenance, all of which are critical in high-stakes emergency scenarios. Despite its potential, DT deployment in HEM remains an intricate, long-term endeavor, hampered by significant conceptual and technical barriers. Many stakeholders lack a clear understanding of DT's functional scope, the requisite technologies for robust implementation, and pathways for integrating DT into established healthcare workflows. In response, this paper offers a comprehensive examination of DT in HEM, categorizing current applications across four levels: individual, hospital, public, and cloud supporting. This paper also highlights how contemporary technical solutions, ranging from advanced networking and distributed computing to AI-driven analytics, can be orchestrated to support novel DT functionalities in real-world healthcare operations. Additionally, challenges, open problems and future directions for DT in HEM are discussed. By synthesizing both functional and research-oriented insights, this review aims to clarify future directions for leveraging DT as a transformative vehicle for healthcare emergency preparedness, response, and long-term resilience.