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Improving the distribution of covid-19 vaccines using the blockchain technology: the Italian case study.
Rinaldi, Marta; Turino, Maria Antonietta; Fera, Marcello; Macchiaroli, Roberto.
  • Rinaldi M; University of Campania "Luigi Vanvitelli", Department of Engineering, via Roma 29, Aversa 81031, Italy.
  • Turino MA; University of Campania "Luigi Vanvitelli", Department of Engineering, via Roma 29, Aversa 81031, Italy.
  • Fera M; University of Campania "Luigi Vanvitelli", Department of Engineering, via Roma 29, Aversa 81031, Italy.
  • Macchiaroli R; University of Campania "Luigi Vanvitelli", Department of Engineering, via Roma 29, Aversa 81031, Italy.
Procedia Comput Sci ; 217: 366-375, 2023.
Article in English | MEDLINE | ID: covidwho-2182444
ABSTRACT
Vaccination is one of the most effective ways to prevent and control the outbreak of infectious diseases. The vaccine supply chain differs from the traditional supply chains because of the perishability of the products, which need strict transport and warehousing conditions to guarantee the health and safety of people. In addition, in case of pandemics, the big amount of doses requested for the implementation of a mass vaccination campaign forces governments to design a proper logistic network and plan a rapid and efficient distribution of vaccines. This paper studies the organization of allocation and distribution of the covid-19 vaccines in Italy. The main criticalities in managing the vaccine supply chain have been identified and, because of its peculiarities, the blockchain has been considered a suitable technology to solve them. A simulation model has been developed to reproduce the current distribution of vaccines in Italy, and a future scenario with blockchain has been studied. The findings show that it is possible to improve the performance of the vaccine supply chain and make it more resilient by implementing the blockchain technology.
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Full text: Available Collection: International databases Database: MEDLINE Type of study: Case report / Observational study Topics: Vaccines Language: English Journal: Procedia Comput Sci Year: 2023 Document Type: Article Affiliation country: J.procs.2022.12.232

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Full text: Available Collection: International databases Database: MEDLINE Type of study: Case report / Observational study Topics: Vaccines Language: English Journal: Procedia Comput Sci Year: 2023 Document Type: Article Affiliation country: J.procs.2022.12.232