Digital Twin of COVID-19 Mass Vaccination Centers

Abstract

The problem is the vaccination of a large number of people in a short time period, using minimum space and resources. The tradeoff is that this minimum number of resources must guarantee a good service for the patients, represented by the time spent in the system and in the queue. The goal is to develop a digital twin which integrates the physical and virtual systems and allows a real-time mapping of the patient flow to create a sustainable and dynamic vaccination center. Firstly, to reach this goal, a discrete-event simulation model is implemented. The simulation model is integrated with a mobile application that automatically collects time measures. By processing these measures, indicators can be computed to find problems, run the virtual model to solve them, and replicate improvements in the real system. The model is tested in a South Tyrol vaccination clinic and the best configuration found includes 31 operators and 306 places dedicated for the queues. This configuration allows the vaccination of 2164 patients in a 10-h shift, with a mean process time of 25 min. Data from the APP are managed to build the dashboard with indicators like number of people in queue for each phase and resource utilization.