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

Madjid Tavana*, Kannan Govindan, Arash Khalili Nasr, Mohammad Saeed Heidary, Hassan Mina

*Corresponding author for this work

Research output: Contribution to journalJournal articleResearchpeer-review


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.

Original languageEnglish
JournalAnnals of Operations Research
Publication statusE-pub ahead of print - 3. Jun 2021

Bibliographical note

Publisher Copyright:
© 2021, The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.


  • Coronavirus vaccine
  • COVID-19
  • Equitable distribution
  • Location-inventory problem
  • Mixed-integer linear programming model
  • Vaccine supply chain


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