IDEAS home Printed from https://ideas.repec.org/a/eee/transe/v156y2021ics136655452100301x.html
   My bibliography  Save this article

A multi-echelon dynamic cold chain for managing vaccine distribution

Author

Listed:
  • Manupati, Vijaya Kumar
  • Schoenherr, Tobias
  • Subramanian, Nachiappan
  • Ramkumar, M.
  • Soni, Bhanushree
  • Panigrahi, Suraj

Abstract

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.

Suggested Citation

  • Manupati, Vijaya Kumar & Schoenherr, Tobias & Subramanian, Nachiappan & Ramkumar, M. & Soni, Bhanushree & Panigrahi, Suraj, 2021. "A multi-echelon dynamic cold chain for managing vaccine distribution," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 156(C).
  • Handle: RePEc:eee:transe:v:156:y:2021:i:c:s136655452100301x
    DOI: 10.1016/j.tre.2021.102542
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S136655452100301X
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.tre.2021.102542?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Xie, Lei & Hou, Pengwen & Han, Hongshuai, 2021. "Implications of government subsidy on the vaccine product R&D when the buyer is risk averse," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 146(C).
    2. Bozorgi, Ali & Pazour, Jennifer & Nazzal, Dima, 2014. "A new inventory model for cold items that considers costs and emissions," International Journal of Production Economics, Elsevier, vol. 155(C), pages 114-125.
    3. Savachkin, Alex & Uribe, Andrés, 2012. "Dynamic redistribution of mitigation resources during influenza pandemics," Socio-Economic Planning Sciences, Elsevier, vol. 46(1), pages 33-45.
    4. Ozgur Araz & Alison Galvani & Lauren Meyers, 2012. "Geographic prioritization of distributing pandemic influenza vaccines," Health Care Management Science, Springer, vol. 15(3), pages 175-187, September.
    5. Hamed Mamani & Stephen E. Chick & David Simchi-Levi, 2013. "A Game-Theoretic Model of International Influenza Vaccination Coordination," Management Science, INFORMS, vol. 59(7), pages 1650-1670, July.
    6. Malcolm Torry, 2019. "Feasibility and Implementation," Exploring the Basic Income Guarantee, in: Malcolm Torry (ed.), The Palgrave International Handbook of Basic Income, chapter 0, pages 157-173, Palgrave Macmillan.
    7. Rachaniotis, Nikolaos P. & Dasaklis, Tom K. & Pappis, Costas P., 2012. "A deterministic resource scheduling model in epidemic control: A case study," European Journal of Operational Research, Elsevier, vol. 216(1), pages 225-231.
    8. Venkatanarayana Motkuri & Udaya S. Mishra, 2020. "Human Resources in Healthcare and Health Outcomes in India," Millennial Asia, , vol. 11(2), pages 133-159, August.
    9. Ming Liu & Ding Zhang, 2016. "A dynamic logistics model for medical resources allocation in an epidemic control with demand forecast updating," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 67(6), pages 841-852, June.
    10. Ivanov, Dmitry, 2020. "Predicting the impacts of epidemic outbreaks on global supply chains: A simulation-based analysis on the coronavirus outbreak (COVID-19/SARS-CoV-2) case," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 136(C).
    11. Enayati, Shakiba & Özaltın, Osman Y., 2020. "Optimal influenza vaccine distribution with equity," European Journal of Operational Research, Elsevier, vol. 283(2), pages 714-725.
    12. Govindan, Kannan & Mina, Hassan & Alavi, Behrouz, 2020. "A decision support system for demand management in healthcare supply chains considering the epidemic outbreaks: A case study of coronavirus disease 2019 (COVID-19)," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 138(C).
    13. Dmitry Ivanov & Ajay Das, 2020. "Coronavirus (COVID-19/SARS-CoV-2) and supply chain resilience: a research note," International Journal of Integrated Supply Management, Inderscience Enterprises Ltd, vol. 13(1), pages 90-102.
    14. Duijzer, Lotty Evertje & van Jaarsveld, Willem & Dekker, Rommert, 2018. "Literature review: The vaccine supply chain," European Journal of Operational Research, Elsevier, vol. 268(1), pages 174-192.
    15. Lin, Qi & Zhao, Qiuhong & Lev, Benjamin, 2020. "Cold chain transportation decision in the vaccine supply chain," European Journal of Operational Research, Elsevier, vol. 283(1), pages 182-195.
    16. Zhang, Xiunian & Lam, Jasmine Siu Lee, 2018. "Shipping mode choice in cold chain from a value-based management perspective," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 110(C), pages 147-167.
    17. Esmizadeh, Yalda & Bashiri, Mahdi & Jahani, Hamed & Almada-Lobo, Bernardo, 2021. "Cold chain management in hierarchical operational hub networks," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 147(C).
    18. Dutta, Pankaj & Choi, Tsan-Ming & Somani, Surabhi & Butala, Richa, 2020. "Blockchain technology in supply chain operations: Applications, challenges and research opportunities," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 142(C).
    19. Saif, Ahmed & Elhedhli, Samir, 2016. "Cold supply chain design with environmental considerations: A simulation-optimization approach," European Journal of Operational Research, Elsevier, vol. 251(1), pages 274-287.
    20. Chowdhury, Priyabrata & Paul, Sanjoy Kumar & Kaisar, Shahriar & Moktadir, Md. Abdul, 2021. "COVID-19 pandemic related supply chain studies: A systematic review," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 148(C).
    21. Peng Sun & Liu Yang & Francis de Véricourt, 2009. "Selfish Drug Allocation for Containing an International Influenza Pandemic at the Onset," Operations Research, INFORMS, vol. 57(6), pages 1320-1332, December.
    22. Yu, Yunlong & Xiao, Tiaojun, 2021. "Analysis of cold-chain service outsourcing modes in a fresh agri-product supply chain," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 148(C).
    23. Azrah A. Anparasan & Miguel A. Lejeune, 2018. "Data laboratory for supply chain response models during epidemic outbreaks," Annals of Operations Research, Springer, vol. 270(1), pages 53-64, November.
    24. Abadie, Alberto & Diamond, Alexis & Hainmueller, Jens, 2010. "Synthetic Control Methods for Comparative Case Studies: Estimating the Effect of California’s Tobacco Control Program," Journal of the American Statistical Association, American Statistical Association, vol. 105(490), pages 493-505.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Yılmaz, Ömer Faruk & Yeni, Fatma Betül & Gürsoy Yılmaz, Beren & Özçelik, Gökhan, 2023. "An optimization-based methodology equipped with lean tools to strengthen medical supply chain resilience during a pandemic: A case study from Turkey," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 173(C).
    2. Maleki, Abolfazl & Hemmati, Vahid & Reza Abazari, Seyed & Aghsami, Amir & Rabbani, Masoud, 2024. "Optimal distribution and waste management of Covid-19 vaccines from vaccination centers’ satisfaction perspective – A fuzzy time window-based VRP," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 183(C).
    3. Karakaya, Sırma & Balcik, Burcu, 2024. "Developing a national pandemic vaccination calendar under supply uncertainty," Omega, Elsevier, vol. 124(C).
    4. Wang, Fan & Xu, Danni & Zhuo, Xiaopo & Zhang, Chao & Liu, Yaoqi, 2022. "Improving consumer welfare in vaccine market: Pricing, government subsidies and consumer awareness," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 167(C).
    5. Vahdani, Behnam & Mohammadi, Mehrdad & Thevenin, Simon & Gendreau, Michel & Dolgui, Alexandre & Meyer, Patrick, 2023. "Fair-split distribution of multi-dose vaccines with prioritized age groups and dynamic demand: The case study of COVID-19," European Journal of Operational Research, Elsevier, vol. 310(3), pages 1249-1272.
    6. Kundu, Tanmoy & Sheu, Jiuh-Biing & Kuo, Hsin-Tsz, 2022. "Emergency logistics management—Review and propositions for future research," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 164(C).
    7. Choudhury, Nishat Alam & Ramkumar, M. & Schoenherr, Tobias & Singh, Shalabh, 2023. "The role of operations and supply chain management during epidemics and pandemics: Potential and future research opportunities," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 175(C).
    8. Kargar, Bahareh & MohajerAnsari, Pedram & Esra Büyüktahtakın, İ. & Jahani, Hamed & Talluri, Sri, 2024. "Data-driven modeling for designing a sustainable and efficient vaccine supply chain: A COVID-19 case study," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 184(C).

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Muhammad Umar Farooq & Amjad Hussain & Tariq Masood & Muhammad Salman Habib, 2021. "Supply Chain Operations Management in Pandemics: A State-of-the-Art Review Inspired by COVID-19," Sustainability, MDPI, vol. 13(5), pages 1-33, February.
    2. Chowdhury, Priyabrata & Paul, Sanjoy Kumar & Kaisar, Shahriar & Moktadir, Md. Abdul, 2021. "COVID-19 pandemic related supply chain studies: A systematic review," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 148(C).
    3. Xiaoyan Xu & Suresh P. Sethi & Sai‐Ho Chung & Tsan‐Ming Choi, 2023. "Reforming global supply chain management under pandemics: The GREAT‐3Rs framework," Production and Operations Management, Production and Operations Management Society, vol. 32(2), pages 524-546, February.
    4. Fadaki, Masih & Abareshi, Ahmad & Far, Shaghayegh Maleki & Lee, Paul Tae-Woo, 2022. "Multi-period vaccine allocation model in a pandemic: A case study of COVID-19 in Australia," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 161(C).
    5. Choudhury, Nishat Alam & Ramkumar, M. & Schoenherr, Tobias & Singh, Shalabh, 2023. "The role of operations and supply chain management during epidemics and pandemics: Potential and future research opportunities," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 175(C).
    6. Maciel M. Queiroz & Dmitry Ivanov & Alexandre Dolgui & Samuel Fosso Wamba, 2022. "Impacts of epidemic outbreaks on supply chains: mapping a research agenda amid the COVID-19 pandemic through a structured literature review," Annals of Operations Research, Springer, vol. 319(1), pages 1159-1196, December.
    7. Hosseini-Motlagh, Seyyed-Mahdi & Samani, Mohammad Reza Ghatreh & Homaei, Shamim, 2023. "Design of control strategies to help prevent the spread of COVID-19 pandemic," European Journal of Operational Research, Elsevier, vol. 304(1), pages 219-238.
    8. Salarpour, Mojtaba & Nagurney, Anna, 2021. "A multicountry, multicommodity stochastic game theory network model of competition for medical supplies inspired by the Covid-19 pandemic," International Journal of Production Economics, Elsevier, vol. 236(C).
    9. Jahani, Hamed & Chaleshtori, Amir Eshaghi & Khaksar, Seyed Mohammad Sadegh & Aghaie, Abdollah & Sheu, Jiuh-Biing, 2022. "COVID-19 vaccine distribution planning using a congested queuing system—A real case from Australia," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 163(C).
    10. Duijzer, Lotty Evertje & van Jaarsveld, Willem & Dekker, Rommert, 2018. "Literature review: The vaccine supply chain," European Journal of Operational Research, Elsevier, vol. 268(1), pages 174-192.
    11. Paul, Ananna & Shukla, Nagesh & Trianni, Andrea, 2023. "Modelling supply chain sustainability challenges in the food processing sector amid the COVID-19 outbreak," Socio-Economic Planning Sciences, Elsevier, vol. 87(PA).
    12. Rozhkov, Maxim & Ivanov, Dmitry & Blackhurst, Jennifer & Nair, Anand, 2022. "Adapting supply chain operations in anticipation of and during the COVID-19 pandemic," Omega, Elsevier, vol. 110(C).
    13. Burgos, Diana & Ivanov, Dmitry, 2021. "Food retail supply chain resilience and the COVID-19 pandemic: A digital twin-based impact analysis and improvement directions," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 152(C).
    14. Lin, Qi & Zhao, Qiuhong & Lev, Benjamin, 2022. "Influenza vaccine supply chain coordination under uncertain supply and demand," European Journal of Operational Research, Elsevier, vol. 297(3), pages 930-948.
    15. Xie, Lei & Hou, Pengwen & Han, Hongshuai, 2021. "Implications of government subsidy on the vaccine product R&D when the buyer is risk averse," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 146(C).
    16. Queiroz, Maciel M. & Fosso Wamba, Samuel & Chiappetta Jabbour, Charbel Jose & Machado, Marcio C., 2022. "Supply chain resilience in the UK during the coronavirus pandemic: A resource orchestration perspective," International Journal of Production Economics, Elsevier, vol. 245(C).
    17. Brusset, Xavier & Ivanov, Dmitry & Jebali, Aida & La Torre, Davide & Repetto, Marco, 2023. "A dynamic approach to supply chain reconfiguration and ripple effect analysis in an epidemic," International Journal of Production Economics, Elsevier, vol. 263(C).
    18. Juliano Marçal Lopes & Coralys Colon Morales & Michelle Alvarado & Vidal Augusto Z. C. Melo & Leonardo Batista Paiva & Eduardo Mario Dias & Panos M. Pardalos, 2022. "Optimization methods for large-scale vaccine supply chains: a rapid review," Annals of Operations Research, Springer, vol. 316(1), pages 699-721, September.
    19. Muckstadt, John A. & Klein, Michael G. & Jackson, Peter L. & Gougelet, Robert M. & Hupert, Nathaniel, 2023. "Efficient and effective large-scale vaccine distribution," International Journal of Production Economics, Elsevier, vol. 262(C).
    20. Hu, Hui & Xu, Jiajun & Liu, Mengqi & Lim, Ming K., 2023. "Vaccine supply chain management: An intelligent system utilizing blockchain, IoT and machine learning," Journal of Business Research, Elsevier, vol. 156(C).

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:transe:v:156:y:2021:i:c:s136655452100301x. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/wps/find/journaldescription.cws_home/600244/description#description .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.