IDEAS home Printed from https://ideas.repec.org/a/kap/hcarem/v9y2006i4p371-389.html
   My bibliography  Save this article

An analysis of the pediatric vaccine supply shortage problem

Author

Listed:
  • Sheldon Jacobson
  • Edward Sewell
  • Ruben Proano

Abstract

In 2002, several factors resulted in pediatric vaccine manufacturers not being able to produce a sufficient number of vaccines to vaccinate all the children in the United States according to the Recommended Childhood Immunization Schedule. The resulting vaccine supply shortage resulted in thousands of children not being fully immunized according to this schedule, and hence, created an unnecessary risk for epidemic outbreaks of several childhood diseases. The Centers for Disease Control and Prevention responded to this crisis by using pediatric vaccine stockpiles to mitigate the impact of future shortages. This paper presents a stochastic model that captures the vaccine supply during production interruptions. This model is used to assess the impact of pediatric vaccine stockpile levels on vaccination coverage rates, by considering the probability that all children can be immunized according to the Recommended Childhood Immunization Schedule over a given time period and the expected minimum vaccine supply. The model is also used to assess the proposed pediatric vaccine stockpile levels recommended by the United States Department of Health and Human Services. The results of this analysis suggest that the proposed vaccine stockpile levels are adequate to meet future vaccine production interruptions, provided that such production interruptions do not last more than six months (which is not surprising, given that is the time period for which they were designed). However, given that recent vaccine production interruptions have lasted (on average) for over one year, the proposed vaccine stockpile levels are insufficient to meet the nation’s pediatric immunization needs during such time periods, which in turn could lead to localized and/or widespread disease outbreaks. Moreover, a moderate investment in higher vaccine stockpile levels would lead to a significantly reduced risk of such events. Copyright Springer Science + Business Media, LLC 2006

Suggested Citation

  • Sheldon Jacobson & Edward Sewell & Ruben Proano, 2006. "An analysis of the pediatric vaccine supply shortage problem," Health Care Management Science, Springer, vol. 9(4), pages 371-389, November.
    • Handle: RePEc:kap:hcarem:v:9:y:2006:i:4:p:371-389
    DOI: 10.1007/s10729-006-0001-5
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1007/s10729-006-0001-5
    Download Restriction: Access to full text is restricted to subscribers.
    File URL: https://libkey.io/10.1007/s10729-006-0001-5?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. Harry Groenevelt & Liliane Pintelon & Abraham Seidmann, 1992. "Production Lot Sizing with Machine Breakdowns," Management Science, INFORMS, vol. 38(1), pages 104-123, January.
    2. Gary D. Eppen & R. Kipp Martin, 1988. "Determining Safety Stock in the Presence of Stochastic Lead Time and Demand," Management Science, INFORMS, vol. 34(11), pages 1380-1390, November.
    3. Shmuel S. Oren & Shao Hong Wan, 1986. "Optimal Strategic Petroleum Reserve Policies: A Steady State Analysis," Management Science, INFORMS, vol. 32(1), pages 14-29, January.
    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. Raman Pall & Yvan Gauthier & Sofia Auer & Walid Mowaswes, 2023. "Predicting drug shortages using pharmacy data and machine learning," Health Care Management Science, Springer, vol. 26(3), pages 395-411, September.
    2. Tang, Lianhua & Li, Yantong & Bai, Danyu & Liu, Tao & Coelho, Leandro C., 2022. "Bi-objective optimization for a multi-period COVID-19 vaccination planning problem," Omega, Elsevier, vol. 110(C).
    3. Shane Hall & Edward Sewell & Sheldon Jacobson, 2008. "Maximizing the effectiveness of a pediatric vaccine formulary while prohibiting extraimmunization," Health Care Management Science, Springer, vol. 11(4), pages 339-352, December.
    4. Kimberly M. Thompson & Radboud J. Duintjer Tebbens, 2016. "Framework for Optimal Global Vaccine Stockpile Design for Vaccine‐Preventable Diseases: Application to Measles and Cholera Vaccines as Contrasting Examples," Risk Analysis, John Wiley & Sons, vol. 36(7), pages 1487-1509, July.
    5. 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).
    6. van Ackere, Ann & Schulz, Peter J., 2020. "Explaining vaccination decisions: A system dynamics model of the interaction between epidemiological and behavioural factors," Socio-Economic Planning Sciences, Elsevier, vol. 71(C).
    7. 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.
    8. Abdul Salam Khan, 2024. "One size does not fit all- Strategizing the vaccine supply chain in developing countries," Operations Management Research, Springer, vol. 17(3), pages 941-962, September.
    9. Ece Zeliha Demirci & Nesim Kohen Erkip, 2020. "Designing intervention scheme for vaccine market: a bilevel programming approach," Flexible Services and Manufacturing Journal, Springer, vol. 32(2), pages 453-485, June.

    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. Gonçalves, João N.C. & Sameiro Carvalho, M. & Cortez, Paulo, 2020. "Operations research models and methods for safety stock determination: A review," Operations Research Perspectives, Elsevier, vol. 7(C).
    2. A. Dolgui & M. Kovalyov & K. Shchamialiova, 2011. "Multi-product lot-sizing and sequencing on a single imperfect machine," Computational Optimization and Applications, Springer, vol. 50(3), pages 465-482, December.
    3. Mohebbi, E., 2008. "A note on a production control model for a facility with limited storage capacity in a random environment," European Journal of Operational Research, Elsevier, vol. 190(2), pages 562-570, October.
    4. Scott Webster & Z. Kevin Weng, 2001. "Improving Repetitive Manufacturing Systems: Model and Insights," Operations Research, INFORMS, vol. 49(1), pages 99-106, February.
    5. Kumar, Anupam & Evers, Philip T., 2015. "Setting safety stock based on imprecise records," International Journal of Production Economics, Elsevier, vol. 169(C), pages 68-75.
    6. Bai, Y. & Dahl, C.A. & Zhou, D.Q. & Zhou, P., 2014. "Stockpile strategy for China׳s emergency oil reserve: A dynamic programming approach," Energy Policy, Elsevier, vol. 73(C), pages 12-20.
    7. Jiao, Jian-Ling & Han, Kuang-Yi & Wu, Gang & Li, Lan-Lan & Wei, Yi-Ming, 2014. "The effect of an SPR on the oil price in China: A system dynamics approach," Applied Energy, Elsevier, vol. 133(C), pages 363-373.
    8. Chen, Youhua Frank, 2005. "Fractional programming approach to two stochastic inventory problems," European Journal of Operational Research, Elsevier, vol. 160(1), pages 63-71, January.
    9. Chakraborty, Tulika & Giri, B.C. & Chaudhuri, K.S., 2008. "Production lot sizing with process deterioration and machine breakdown," European Journal of Operational Research, Elsevier, vol. 185(2), pages 606-618, March.
    10. Zhang, Xiao-Bing & Fan, Ying & Wei, Yi-Ming, 2009. "A model based on stochastic dynamic programming for determining China's optimal strategic petroleum reserve policy," Energy Policy, Elsevier, vol. 37(11), pages 4397-4406, November.
    11. Daniela Favaretto & Alessandro Marin & Marco Tolotti, 2023. "A theoretical validation of the DDMRP reorder policy," Computational Management Science, Springer, vol. 20(1), pages 1-28, December.
    12. Chiu, Singa Wang & Chou, Chung-Li & Wu, Wen-Kuei, 2013. "Optimizing replenishment policy in an EPQ-based inventory model with nonconforming items and breakdown," Economic Modelling, Elsevier, vol. 35(C), pages 330-337.
    13. Dev, Navin K. & Shankar, Ravi & Swami, Sanjeev, 2020. "Diffusion of green products in industry 4.0: Reverse logistics issues during design of inventory and production planning system," International Journal of Production Economics, Elsevier, vol. 223(C).
    14. Chiu, Singa Wang & Liang, Gang-Ming & Chiu, Yuan-Shyi Peter & Chiu, Tiffany, 2019. "Production planning incorporating issues of reliability and backlogging with service level constraint," Operations Research Perspectives, Elsevier, vol. 6(C).
    15. Fan, Ying & Zhang, Xiao-Bing, 2010. "Modelling the strategic petroleum reserves of China and India by a stochastic dynamic game," Journal of Policy Modeling, Elsevier, vol. 32(4), pages 505-519, July.
    16. Om Prakash & A.R. Roy & A. Goswami, 2014. "Stochastic manufacturing system with process deterioration and machine breakdown," International Journal of Systems Science, Taylor & Francis Journals, vol. 45(12), pages 2539-2551, December.
    17. Riezebos, Jan, 2006. "Inventory order crossovers," International Journal of Production Economics, Elsevier, vol. 104(2), pages 666-675, December.
    18. Chakravarty, Amiya K. & Balakrishnan, Nagraj, 1997. "Job sequencing rules for minimizing the expected makespan in flexible machines," European Journal of Operational Research, Elsevier, vol. 96(2), pages 274-288, January.
    19. Peymankar, Mahboobe & Dehghanian, Farzad & Ghiami, Yousef & Abolbashari, Mohammad Hassan, 2018. "The effects of contractual agreements on the economic production quantity model with machine breakdown," International Journal of Production Economics, Elsevier, vol. 201(C), pages 203-215.
    20. Sandun C. Perera & Suresh P. Sethi, 2023. "A survey of stochastic inventory models with fixed costs: Optimality of (s, S) and (s, S)‐type policies—Discrete‐time case," Production and Operations Management, Production and Operations Management Society, vol. 32(1), pages 131-153, January.

    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:kap:hcarem:v:9:y:2006:i:4:p:371-389. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    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.