Simulation modeling assessment and improvement of a COVID-19 mass vaccination center operations. (June 2023)

• Record Type: Journal Article
• Authors: Jerbi, Abdessalem; Masmoudi, Faouzi
• Is Part Of: Simulation. Volume 99:Number 6(2023)
• Page Start: 553
• Page End: 572
• Publication Date: 2023-06
• Subjects: Discrete event simulation -- COVID-19 -- mass vaccination center -- public health simulation; Computer simulation -- Periodicals; 003.3
• DOI: 10.1177/00375497221135214
• Languages: English
• ISSNs: 0037-5497

Abstract

The development of safe and effective vaccines against COVID-19 has been a turning point in the international effort to control this disease. However, vaccine development is only the first phase of the COVID-19 vaccination process. Correct planning of mass vaccination is important for any policy to immunize the population. For this purpose, it is necessary to set up and properly manage mass vaccination centers. This paper presents a discrete event simulation model of a real COVID-19 mass vaccination center located in Sfax, Tunisia. This model was used to evaluate the management of this center through different performance measures. Three person's arrival scenarios were considered and simulated to verify the response of this real vaccination center to arrival variability. A second model was proposed and simulated to improve the performances of the vaccination center. Like the first model, this one underwent the same evaluation process through the three arrivals scenarios. The simulation results show that both models respond well to the arrival's variability. Indeed, most of the arriving persons are vaccinated on time for all the studied scenarios. In addition, both models present moderate average vaccination and waiting times. However, the average utilization rates of operators are modest and need to be improved. Furthermore, both simulation models show a high average number of persons present in the vaccination center, which goes against the respect of the social distancing condition. Comparison between the two simulation models shows that the proposed model is more efficient than the actual one.