A decision support system for scheduling a vaccination campaign during a pandemic emergency: The COVID-19 case. (March 2023)

• Record Type: Journal Article
• Authors: Fabbri, Cristiano; Ghedini, Pierfrancesco; Leonessi, Marco; Malaguti, Enrico; Tubertini, Paolo
• Is Part Of: Computers & industrial engineering. Volume 177(2023)
• Publication Date: 2023-03
• Subjects: COVID-19 -- Vaccination campaign -- Mathematical model -- Healthcare -- Scheduling; Engineering -- Data processing -- Periodicals; Industrial engineering -- Periodicals; 620.00285
• DOI: 10.1016/j.cie.2023.109068
• Languages: English
• ISSNs: 0360-8352

Abstract

Abstract: This paper considers the organization and scheduling of a vaccination campaign during a pandemic emergency. We describe the decision process and introduce an optimization model, which showed a powerful multi-scenario tool for scheduling a campaign in detail within a dynamic and uncertain context. The solution of the model gave the decision maker the possibility to test different settings and have a configurable solution within few seconds, compared with the man-days of effort that would have required a manual schedule. Analysis of a real case study on COVID-19 vaccination campaign in northern Italy showed that the use of such optimized solution allowed to cover the target population within a much shorter time interval, compared to a manual approach. Highlights: We consider the organization and scheduling of a vaccination campaign during a pandemic emergency. We describe the decision process and introduce an optimization model to support it. Analysis of a real case study is discussed.