Improving Healthcare Systems' Performance during Mass Casualty Incidents using a Simulation, Optimization, and Machine Learning approach

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Disaster events such as floods, earthquakes, chemical spills, or epidemics usually take place all aroundthe world. Such events lead to the injury of a large number of people in a short amount of time. As aresult, there will be a high level of demand for health services. The heavy workload created in thehealthcare system during these incidents disrupts the function of the healthcare systems so that thehealth centers such as hospitals cannot provide medical treatment and care services to thepatients/injured people properly. This endangers human health and may even lead to the loss of humanlives. In this research project, we address this problem in a scientific way of knowing, using quantitativemethods to improve the performance of health centers. We expect the results of the study to improvethe delivery of health services and prevent loss of life during disaster incidents.