Highlights Developing a novel agent-based simulation-optimization model for a vaccine supply chain (VSC). Proposing an extented epidemiological simulation model of COVID-19 to incorporate vaccine compartment and forecast disease transmission. Considering sustainability concerns and optimizing the VSC given the evolving disease dynamics. Validating the model by a case study in the US and testing the generalizability of the model to other infectious diseases.

    Abstract We present an agent-based simulation-optimization modeling framework to determine the optimal location of warehouses for the distribution of vaccines. We first extend an agent-based epidemiological simulation model of COVID-19 to capture disease transmission and forecast the number of susceptible individuals and infections. We then develop a sustainable VSC considering the impact of greenhouse gases and integrate the simulation model into the VSC model to minimize total costs and environmental impacts. We validate our proposed model using a real-world COVID-19 VSC in the US. Our findings underscore the importance of strategically managing vaccine supplies to control COVID-19 and other infectious outbreaks.


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    Titel :

    Data-driven modeling for designing a sustainable and efficient vaccine supply chain: A COVID-19 case study


    Beteiligte:


    Erscheinungsdatum :

    2024-03-14




    Medientyp :

    Aufsatz (Zeitschrift)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch




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