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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...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer US
2021
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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. |
format | Online Article Text |
id | pubmed-8172366 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Springer US |
record_format | MEDLINE/PubMed |
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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