Drive-Through COVID-19 Mass Vaccination AI APP

Advanced Disaster, Emergency and Rapid-response Simulation
Laboratory for Industrial and Applied Mathematics

York University


Use of drive-through has been suggested as one of the possible mass vaccination methods. We developed a simulation tool that can estimate the number of persons that can be vaccinated and the average processing time under different drive through configurations and parameters setting. This application helps you estimate the number of people that can be vaccinated and the average waiting times in a drive through facilities according to the users initial settings of the drive through layout, staff availability, incoming cars arrival rates, pre-registration, and vaccination times.


The Drive Through Mass Vaccination AI Application has been developed based on a big dataset extracted from more than 125K runs of a drive through simulation (583c2075-6a8b-41be-8a03-d692eba71683). The simulation uses a mix of discrete event and agent-bases models. For more details please refer to the journal article published on this simulation (2227-9032/8/4/469). The machine learning model developed for the AI application is a fully connected feed-forward network.



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The team acknowledge the support received from a number of funding agencies including: Public Health Agency of Canada (PHAC), Canadian Institute for health research (CIHR), and Ontario Research Fund.