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A mathematical programming approach for equitable COVID-19 vaccine distribution in developing countries

Developing countries scramble to contain and mitigate the spread of coronavirus disease 2019 (COVID-19), and world leaders demand equitable distribution of vaccines to trigger economic recovery. Although numerous strategies, including education, quarantine, and immunization, have been used to contro...

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Autores principales: Tavana, Madjid, Govindan, Kannan, Nasr, Arash Khalili, Heidary, Mohammad Saeed, Mina, Hassan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer US 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8172366/
https://www.ncbi.nlm.nih.gov/pubmed/34099948
http://dx.doi.org/10.1007/s10479-021-04130-z
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author Tavana, Madjid
Govindan, Kannan
Nasr, Arash Khalili
Heidary, Mohammad Saeed
Mina, Hassan
author_facet Tavana, Madjid
Govindan, Kannan
Nasr, Arash Khalili
Heidary, Mohammad Saeed
Mina, Hassan
author_sort Tavana, Madjid
collection PubMed
description Developing countries scramble to contain and mitigate the spread of coronavirus disease 2019 (COVID-19), and world leaders demand equitable distribution of vaccines to trigger economic recovery. Although numerous strategies, including education, quarantine, and immunization, have been used to control COVID-19, the best method to curb this disease is vaccination. Due to the high demand for COVID 19 vaccine, developing countries must carefully identify and prioritize vulnerable populations and rationalize the vaccine allocation process. This study presents a mixed-integer linear programming model for equitable COVID-19 vaccine distribution in developing countries. Vaccines are grouped into cold, very cold, and ultra-cold categories where specific refrigeration is required for their storage and distribution. The possibility of storage for future periods, facing a shortage, budgetary considerations, manufacturer selection, order allocation, time-dependent capacities, and grouping of the heterogeneous population are among the practical assumptions in the proposed approach. Real-world data is used to demonstrate the efficiency and effectiveness of the mathematical programming approach proposed in this study.
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spelling pubmed-81723662021-06-03 A mathematical programming approach for equitable COVID-19 vaccine distribution in developing countries Tavana, Madjid Govindan, Kannan Nasr, Arash Khalili Heidary, Mohammad Saeed Mina, Hassan Ann Oper Res Original Research Developing countries scramble to contain and mitigate the spread of coronavirus disease 2019 (COVID-19), and world leaders demand equitable distribution of vaccines to trigger economic recovery. Although numerous strategies, including education, quarantine, and immunization, have been used to control COVID-19, the best method to curb this disease is vaccination. Due to the high demand for COVID 19 vaccine, developing countries must carefully identify and prioritize vulnerable populations and rationalize the vaccine allocation process. This study presents a mixed-integer linear programming model for equitable COVID-19 vaccine distribution in developing countries. Vaccines are grouped into cold, very cold, and ultra-cold categories where specific refrigeration is required for their storage and distribution. The possibility of storage for future periods, facing a shortage, budgetary considerations, manufacturer selection, order allocation, time-dependent capacities, and grouping of the heterogeneous population are among the practical assumptions in the proposed approach. Real-world data is used to demonstrate the efficiency and effectiveness of the mathematical programming approach proposed in this study. Springer US 2021-06-03 /pmc/articles/PMC8172366/ /pubmed/34099948 http://dx.doi.org/10.1007/s10479-021-04130-z Text en © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2021 This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic.
spellingShingle Original Research
Tavana, Madjid
Govindan, Kannan
Nasr, Arash Khalili
Heidary, Mohammad Saeed
Mina, Hassan
A mathematical programming approach for equitable COVID-19 vaccine distribution in developing countries
title A mathematical programming approach for equitable COVID-19 vaccine distribution in developing countries
title_full A mathematical programming approach for equitable COVID-19 vaccine distribution in developing countries
title_fullStr A mathematical programming approach for equitable COVID-19 vaccine distribution in developing countries
title_full_unstemmed A mathematical programming approach for equitable COVID-19 vaccine distribution in developing countries
title_short A mathematical programming approach for equitable COVID-19 vaccine distribution in developing countries
title_sort mathematical programming approach for equitable covid-19 vaccine distribution in developing countries
topic Original Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8172366/
https://www.ncbi.nlm.nih.gov/pubmed/34099948
http://dx.doi.org/10.1007/s10479-021-04130-z
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