Development of a Simulation Model for Disaster Medical Support

Introduction: Japan frequently experiences natural disasters such as earthquakes and typhoons, and medical support during disasters has become a critical challenge, particularly in a super-aged society. Previous research has utilized simulations to analyze medical resource allocation and Disaster Medical Assistance Teams (DMAT) activities during the acute phase. However, there has been insufficient focus on medium-term measures, including primary care for chronic illnesses in aging populations. This study aims to develop a simulation model that replicates processes from the occurrence of a disaster to evacuation behavior, the emergence of medical needs, especially for chronic diseases, and activities of medical support team patrols at relief stations and shelters, to efficiently allocate medical resources and develop support plans. Methods: An agent-based simulation model was developed to analyze evacuee behavior, changes in medical needs over time, and the impacts of medical team rotations and supply timing on shelters. The model incorporates various scenarios, such as the timing of aid station establishment and medical supply distribution, while considering geographical and timing of actions. This approach enabled a comprehensive analysis of medical support and resource allocation options during disasters. Results: The simulation results validated the effectiveness of multiple policy scenarios and identified optimal resource allocation based on medical demand patterns. Geographical conditions and timing were found to significantly influence the placement of aid stations and the assignment of human resources. Statistical analysis and optimization techniques were applied to determine ideal strategies for specific conditions, enabling the sophistication of simulation model parameters. Conclusion: The disaster medical simulation model developed in this study provides realistic evacuation behaviors and medical demands. It serves as a valuable tool for optimizing resource allocation and intervention timing in disaster scenarios. Additionally, the model demonstrates potential for improving disaster response capabilities through scenario-based training and could contribute to the standardization of disaster medical support plans.