Optimization methods for large-scale vaccine supply chains: a rapid review.

Autor: Lopes JM; Gaesi, Departament of Electric Energy and Automation Engineering, Polytechnic School, University of São Paulo, São Paulo, SP Brazil., Morales CC; HEALTH-Engine Laboratory, Department of Industrial and Systems Engineering, University of Florida, Gainesville, FL USA., Alvarado M; HEALTH-Engine Laboratory, Department of Industrial and Systems Engineering, University of Florida, Gainesville, FL USA., Melo VAZC; Gaesi, Departament of Electric Energy and Automation Engineering, Polytechnic School, University of São Paulo, São Paulo, SP Brazil., Paiva LB; Gaesi, Departament of Electric Energy and Automation Engineering, Polytechnic School, University of São Paulo, São Paulo, SP Brazil., Dias EM; Gaesi, Departament of Electric Energy and Automation Engineering, Polytechnic School, University of São Paulo, São Paulo, SP Brazil., Pardalos PM; HEALTH-Engine Laboratory, Department of Industrial and Systems Engineering, University of Florida, Gainesville, FL USA.
Jazyk: angličtina
Zdroj: Annals of operations research [Ann Oper Res] 2022; Vol. 316 (1), pp. 699-721. Date of Electronic Publication: 2022 Apr 30.
DOI: 10.1007/s10479-022-04720-5
Abstrakt: Global vaccine revenues are projected at $59.2 billion, yet large-scale vaccine distribution remains challenging for many diseases in countries around the world. Poor management of the vaccine supply chain can lead to a disease outbreak, or at worst, a pandemic. Fortunately, a large number of those challenges, such as decision-making for optimal allocation of resources, vaccination strategy, inventory management, among others, can be improved through optimization approaches. This work aims to understand how optimization has been applied to vaccine supply chain and logistics. To achieve this, we conducted a rapid review and searched for peer-reviewed journal articles, published between 2009 and March 2020, in four scientific databases. The search resulted in 345 articles, of which 25 unique studies met our inclusion criteria. Our analysis focused on the identification of article characteristics such as research objectives, vaccine supply chain stage addressed, the optimization method used, whether outbreak scenarios were considered, among others. Approximately 64% of the studies dealt with vaccination strategy, and the remainder dealt with logistics and inventory management. Only one addressed market competition (4%). There were 14 different types of optimization methods used, but control theory, linear programming, mathematical model and mixed integer programming were the most common (12% each). Uncertainties were considered in the models of 44% of the studies. One resulting observation was the lack of studies using optimization for vaccine inventory management and logistics. The results provide an understanding of how optimization models have been used to address challenges in large-scale vaccine supply chains.
Competing Interests: Conflict of interestThe authors declare that they have no conflict of interest.
(© The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2022.)
Databáze: MEDLINE
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