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

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