Date: March 18, 3 — 4 pm UTC (convert to your local time)
This webinar will show how a mass COVID-19 drive-through vaccination simulation was developed and applied in the real world. The webinar will also include insight into the development of the simulation's machine learning model and online application.
Different methods are needed to vaccinate millions of people quickly and safely during the COVID-19 pandemic. However, drive-through vaccination facilities are widely applicable, and a simulation model is helping public health agencies plan, design, and implement drive-through vaccination facilities.
The simulation shows waiting times and the number of vaccinations possible for different simulation input settings, including the number of vaccination lanes, the number of staff, and the time needed for screening, registration, immunization, and observation.
Using AnyLogic Cloud to expedite run times, the developers ran the simulation 125 thousand times to create a large dataset from a wide range of input parameters. The machine learning model subsequently developed using this dataset can accurately predict output values and was deployed as an online AI application.
Results from comparisons with real-world implementations of drive-through mass vaccination show that the simulation model can accurately assist public health agencies with the planning, design, and implementation of a drive-through approach for COVID-19 mass vaccination.
- Introduction to COVID-19 vaccination challenges
- Options for mass vaccination and the role of simulation in planning, design and implementation
- Drive-through simulation components
- AnyLogic Cloud and AI Model of the drive-through simulation
- Drive-through online application
- Drive-through implementation case studies
Dr. Arash Mahdavi is a simulation modeling expert and AI Program Lead at The AnyLogic Company in North America. He holds a PhD degree in civil engineering from Purdue University where he applied a system-of-systems approach and agent-based modeling to profitability analysis of construction companies. Dr. Mahdavi has recently authored a simulation textbook titled “The Art of Process-Centric Modeling”. He has trained hundreds of professionals and faculty members from Fortune 100 companies and elite research universities.
Dr. Ali Asgary is an associate professor and founding member of York University's Disaster and Emergency Management Program. He served as the global board member of the International Association of Emergency Management (IAEM) and president of the IAEM-Canada from 2007-2009. Since 2015 he has been the executive director of the Advanced Disaster, Emergency and Rapid-response Simulation (ADESIM) at York University. Dr. Asgary was among the recipients of the York Research Leaders Award in 2015 and 2019. His teaching and research interests are in diverse areas of disaster and emergency management with special focus on "disaster and emergency simulation and modelling" and "community, organizational, and businesses resilience and post disaster recovery". He is currently involved as the principal investigator and co-investigator of a number of major research projects related to COVID-19 funded by Canadian funding agencies including SSHRC, CIHR, NSERC, and DRDC, IDRC among others.