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.
Highlights
Since the beginning of 2020, the world has been facing a devastating pandemic calledCOVID-19, which has caused more than 150 million infected people and 3 million deaths as of the end of April 2021 [1]
This paper describes the development of a digital twin for the mass vaccination process against the COVID-19 pandemic
The most relevant KPI considered was the number of patients vaccinated every hour by a single nurse (Npat/nurse ) because it gave a measure of the system efficiency
Summary
Since the beginning of 2020, the world has been facing a devastating pandemic calledCOVID-19, which has caused more than 150 million infected people and 3 million deaths as of the end of April 2021 [1]. Kim et al [3] presented a model that, according to the characteristics of the dataset, finds the classification algorithm which better predicts future trends They demonstrated that this model provides a solution quickly and, allows digital technologies to save time and electrical power and be more sustainable from different perspectives. As a new promising way to defeat the coronavirus, in December 2020 the first vaccine against COVID-19, developed by Pfizer-BioNTech, was approved by European Medicines Agency (EMA), which recommended the administration to people above 16 years of age [4]. This vaccine is stored in trays which contain 195 multidose vials, each of which contains five doses. Besides Pfizer-BioNTech, several vaccines have been approved and provided to all the countries, many of which require higher temperatures [7]
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