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A multi-echelon dynamic cold chain for managing vaccine distribution

While cold chain management has been part of healthcare systems, enabling the efficient administration of vaccines in both urban and rural areas, the COVID-19 virus has created entirely new challenges for vaccine distributions. With virtually every individual worldwide being impacted, strategies are...

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Autores principales: Manupati, Vijaya Kumar, Schoenherr, Tobias, Subramanian, Nachiappan, Ramkumar, M., Soni, Bhanushree, Panigrahi, Suraj
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier Ltd. 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8602632/
https://www.ncbi.nlm.nih.gov/pubmed/34815731
http://dx.doi.org/10.1016/j.tre.2021.102542
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author Manupati, Vijaya Kumar
Schoenherr, Tobias
Subramanian, Nachiappan
Ramkumar, M.
Soni, Bhanushree
Panigrahi, Suraj
author_facet Manupati, Vijaya Kumar
Schoenherr, Tobias
Subramanian, Nachiappan
Ramkumar, M.
Soni, Bhanushree
Panigrahi, Suraj
author_sort Manupati, Vijaya Kumar
collection PubMed
description While cold chain management has been part of healthcare systems, enabling the efficient administration of vaccines in both urban and rural areas, the COVID-19 virus has created entirely new challenges for vaccine distributions. With virtually every individual worldwide being impacted, strategies are needed to devise best vaccine distribution scenarios, ensuring proper storage, transportation and cost considerations. Current models do not consider the magnitude of distribution efforts needed in our current pandemic, in particular the objective that entire populations need to be vaccinated. We expand on existing models and devise an approach that considers the needed extensive distribution capabilities and special storage requirements of vaccines, while at the same time being cognizant of costs. As such, we provide decision support on how to distribute the vaccine to an entire population based on priority. We do so by conducting predictive analysis for three different scenarios and dividing the distribution chain into three phases. As the available vaccine doses are limited in quantity at first, we apply decision tree analysis to find the best vaccination scenario, followed by a synthetic control analysis to predict the impact of the vaccination programme to forecast future vaccine production. We then formulate a mixed-integer linear programming (MILP) model for locating and allocating cold storage facilities for bulk vaccine production, followed by the proposition of a heuristic algorithm to solve the associated objective functions. The application of the proposed model is evaluated by implementing it in a real-world case study. The optimized numerical results provide valuable decision support for healthcare authorities.
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spelling pubmed-86026322021-11-19 A multi-echelon dynamic cold chain for managing vaccine distribution Manupati, Vijaya Kumar Schoenherr, Tobias Subramanian, Nachiappan Ramkumar, M. Soni, Bhanushree Panigrahi, Suraj Transp Res E Logist Transp Rev Article While cold chain management has been part of healthcare systems, enabling the efficient administration of vaccines in both urban and rural areas, the COVID-19 virus has created entirely new challenges for vaccine distributions. With virtually every individual worldwide being impacted, strategies are needed to devise best vaccine distribution scenarios, ensuring proper storage, transportation and cost considerations. Current models do not consider the magnitude of distribution efforts needed in our current pandemic, in particular the objective that entire populations need to be vaccinated. We expand on existing models and devise an approach that considers the needed extensive distribution capabilities and special storage requirements of vaccines, while at the same time being cognizant of costs. As such, we provide decision support on how to distribute the vaccine to an entire population based on priority. We do so by conducting predictive analysis for three different scenarios and dividing the distribution chain into three phases. As the available vaccine doses are limited in quantity at first, we apply decision tree analysis to find the best vaccination scenario, followed by a synthetic control analysis to predict the impact of the vaccination programme to forecast future vaccine production. We then formulate a mixed-integer linear programming (MILP) model for locating and allocating cold storage facilities for bulk vaccine production, followed by the proposition of a heuristic algorithm to solve the associated objective functions. The application of the proposed model is evaluated by implementing it in a real-world case study. The optimized numerical results provide valuable decision support for healthcare authorities. Elsevier Ltd. 2021-12 2021-11-19 /pmc/articles/PMC8602632/ /pubmed/34815731 http://dx.doi.org/10.1016/j.tre.2021.102542 Text en © 2021 Elsevier Ltd. All rights reserved. Since January 2020 Elsevier has created a COVID-19 resource centre with free information in English and Mandarin on the novel coronavirus COVID-19. The COVID-19 resource centre is hosted on Elsevier Connect, the company's public news and information website. Elsevier hereby grants permission to make all its COVID-19-related research that is available on the COVID-19 resource centre - including this research content - immediately available in PubMed Central and other publicly funded repositories, such as the WHO COVID database with rights for unrestricted research re-use and analyses in any form or by any means with acknowledgement of the original source. These permissions are granted for free by Elsevier for as long as the COVID-19 resource centre remains active.
spellingShingle Article
Manupati, Vijaya Kumar
Schoenherr, Tobias
Subramanian, Nachiappan
Ramkumar, M.
Soni, Bhanushree
Panigrahi, Suraj
A multi-echelon dynamic cold chain for managing vaccine distribution
title A multi-echelon dynamic cold chain for managing vaccine distribution
title_full A multi-echelon dynamic cold chain for managing vaccine distribution
title_fullStr A multi-echelon dynamic cold chain for managing vaccine distribution
title_full_unstemmed A multi-echelon dynamic cold chain for managing vaccine distribution
title_short A multi-echelon dynamic cold chain for managing vaccine distribution
title_sort multi-echelon dynamic cold chain for managing vaccine distribution
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8602632/
https://www.ncbi.nlm.nih.gov/pubmed/34815731
http://dx.doi.org/10.1016/j.tre.2021.102542
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