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• W4380990809 abstract "Mass vaccination programs should employ effective strategies to design a resilient vaccine supply chain for immunizing populations quickly and efficiently. The need for more flexible and responsive vaccine supply chain design is highlighted during the pandemic, where authorities are required to effectively execute vaccine distribution. Our study proposes a scientifically driven approach to identify suitable supply chain strategies for vaccine distribution, enhancing the effectiveness of mass vaccination. We propose a two-stage approach for identifying the best supply chain strategy that supports faster vaccine rollouts, reducing infections and deaths during the pandemic. We optimize the vaccine distribution network under both supply chain strategies using Mixed Integer Programming (MIP) for four disruption scenarios in the first stage. Second, we have used systems dynamics simulation and the Susceptible-Exposed-Infectious-Recovered (SEIR) model for pandemics to identify the impact of vaccination. In all disruption scenarios, vaccine distribution using the Lean strategy is less costly, and the Agile strategy reduces lead time and supports faster vaccine rollout. We show achieving a cost-saving or lead-time saving using either supply chain strategy becomes increasingly difficult when the severity of disruptions at storage increases. Our study suggests a novel methodology that determines the most suitable strategy for vaccine distribution which minimizes infections and deaths under several disruption scenarios. The decision-makers can identify appropriate supply chain strategies for vaccine delivery to densely populated developing regions, using the proposed framework which compares supply chain strategies’ impact on vaccine distribution network design." @default.
• W4380990809 created "2023-06-17" @default.
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• W4380990809 date "2023-09-01" @default.
• W4380990809 modified "2023-10-05" @default.
• W4380990809 title "Comparative analysis of lean and agile supply chain strategies for effective vaccine distribution in pandemics: A case study of COVID-19 in a densely populated developing region" @default.
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• W4380990809 doi "https://doi.org/10.1016/j.sca.2023.100022" @default.
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