DISCRETE EVENT SIMULATION FOR COVID-19 DRIVE-THROUGH MASS VACCINE DISTRIBUTION EVENTS

The key aim of this research is to demonstrate how a discrete-event simulation model and the simulation-based optimization model could help organizers of the mass vaccination distribution site better understand the system dynamics and make effective data-driven decisions. The proposed simulation model was developed based on empirical data collected during the COVID-19 drive-through vaccination events and insights provided by the system experts. Both the simulation and the simulation-based optimization models are found to be effective in helping the COVID-19 drive-through events' decision- makers by providing information on how their system would respond over time under various scenarios leading to more informed and systematic decisions about the process and resource management. The model could easily be extended and reused for any other drive-through mass vaccination facilities in the future.