IDEAS home Printed from https://ideas.repec.org/a/inm/oropre/v56y2008i6p1348-1365.html
   My bibliography  Save this article

An Analysis of Pediatric Vaccine Formulary Selection Problems

Author

Listed:
  • Shane N. Hall

    (Department of Operational Sciences, Air Force Institute of Technology, Wright-Patterson AFB, Ohio 45433)

  • Sheldon H. Jacobson

    (Simulation and Optimization Laboratory, Department of Computer Science, University of Illinois at Urbana-Champaign, Urbana, Illinois 61801)

  • Edward C. Sewell

    (Department of Mathematics and Statistics, Southern Illinois University, Edwardsville, Illinois 62026)

Abstract

Vaccination against infectious disease is hailed as one of the great achievements in public health. However, the United States Recommended Childhood Immunization Schedule is becoming increasingly complex as it is expanded to cover additional diseases. Moreover, biotechnology advances have allowed vaccine manufacturers to create combination vaccines that immunize against several diseases in a single injection. All these factors are creating a combinatorial explosion of alternatives and choices (each with a different cost) for public health policy makers, pediatricians, and parents/guardians (each with a different perspective). The General Vaccine Formulary Selection Problem (GVFSP) is introduced to model general childhood immunization schedules that can be used to illuminate these alternatives and choices by selecting a vaccine formulary that minimizes the cost of fully immunizing a child and the amount of extraimmunization. Both exact algorithms and heuristics for GVFSP are presented. A computational comparison of these algorithms and heuristics is presented for the 2006 Recommended Childhood Immunization Schedule, as well as several randomly generated childhood immunization schedules that are likely to be representative of future childhood immunization schedules. The results reported here provide both fundamental insights into the structure of the GVFSP models and algorithms and practical value for the public health community.

Suggested Citation

  • Shane N. Hall & Sheldon H. Jacobson & Edward C. Sewell, 2008. "An Analysis of Pediatric Vaccine Formulary Selection Problems," Operations Research, INFORMS, vol. 56(6), pages 1348-1365, December.
  • Handle: RePEc:inm:oropre:v:56:y:2008:i:6:p:1348-1365
    DOI: 10.1287/opre.1080.0612
    as

    Download full text from publisher

    File URL: http://dx.doi.org/10.1287/opre.1080.0612
    Download Restriction: no

    File URL: https://libkey.io/10.1287/opre.1080.0612?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
    ---><---

    References listed on IDEAS

    as
    1. 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.
    2. Mitchell L. Cohen, 2000. "Changing patterns of infectious disease," Nature, Nature, vol. 406(6797), pages 762-767, August.
    3. John J. Bartholdi, 1981. "A Guaranteed-Accuracy Round-off Algorithm for Cyclic Scheduling and Set Covering," Operations Research, INFORMS, vol. 29(3), pages 501-510, June.
    4. Edward Sewell & Sheldon Jacobson, 2003. "Using an Integer Programming Model to Determine the Price of Combination Vaccines for Childhood Immunization," Annals of Operations Research, Springer, vol. 119(1), pages 261-284, March.
    5. Alberto Caprara & Matteo Fischetti & Paolo Toth, 1999. "A Heuristic Method for the Set Covering Problem," Operations Research, INFORMS, vol. 47(5), pages 730-743, October.
    6. V. Chvatal, 1979. "A Greedy Heuristic for the Set-Covering Problem," Mathematics of Operations Research, INFORMS, vol. 4(3), pages 233-235, August.
    7. Haddadi, Salim, 1997. "Simple Lagrangian heuristic for the set covering problem," European Journal of Operational Research, Elsevier, vol. 97(1), pages 200-204, February.
    8. Alberto Caprara & Paolo Toth & Matteo Fischetti, 2000. "Algorithms for the Set Covering Problem," Annals of Operations Research, Springer, vol. 98(1), pages 353-371, December.
    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. Bruno Alves-Maciel & Ruben A. Proano, 2024. "Enhancing affordability and profit in a non-cooperative, coordinated, hypothetical pediatric vaccine market via sequential optimization," Health Care Management Science, Springer, vol. 27(3), pages 436-457, September.
    2. Lunday, Brian J. & Robbins, Matthew J., 2019. "Collaboratively-developed vaccine pricing and stable profit sharing mechanisms," Omega, Elsevier, vol. 84(C), pages 102-113.
    3. 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).
    4. Matthew J. Robbins & Sheldon H. Jacobson & Uday V. Shanbhag & Banafsheh Behzad, 2014. "The Weighted Set Covering Game: A Vaccine Pricing Model for Pediatric Immunization," INFORMS Journal on Computing, INFORMS, vol. 26(1), pages 183-198, February.
    5. Ho‐Yin Mak & Tinglong Dai & Christopher S. Tang, 2022. "Managing two‐dose COVID‐19 vaccine rollouts with limited supply: Operations strategies for distributing time‐sensitive resources," Production and Operations Management, Production and Operations Management Society, vol. 31(12), pages 4424-4442, December.
    6. 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.
    7. Robbins, Matthew J. & Jacobson, Sheldon H., 2011. "Pediatric vaccine procurement policy: The monopsonist's problem," Omega, Elsevier, vol. 39(6), pages 589-597, December.
    8. Robbins, Matthew J. & Lunday, Brian J., 2016. "A bilevel formulation of the pediatric vaccine pricing problem," European Journal of Operational Research, Elsevier, vol. 248(2), pages 634-645.
    9. E. C. Sewell & S. H. Jacobson, 2012. "A Branch, Bound, and Remember Algorithm for the Simple Assembly Line Balancing Problem," INFORMS Journal on Computing, INFORMS, vol. 24(3), pages 433-442, August.

    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. Li, Shengyin & Huang, Yongxi, 2014. "Heuristic approaches for the flow-based set covering problem with deviation paths," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 72(C), pages 144-158.
    2. Patrizia Beraldi & Andrzej Ruszczyński, 2002. "The Probabilistic Set-Covering Problem," Operations Research, INFORMS, vol. 50(6), pages 956-967, December.
    3. Lan, Guanghui & DePuy, Gail W. & Whitehouse, Gary E., 2007. "An effective and simple heuristic for the set covering problem," European Journal of Operational Research, Elsevier, vol. 176(3), pages 1387-1403, February.
    4. Gao, Chao & Yao, Xin & Weise, Thomas & Li, Jinlong, 2015. "An efficient local search heuristic with row weighting for the unicost set covering problem," European Journal of Operational Research, Elsevier, vol. 246(3), pages 750-761.
    5. Masoud Yaghini & Mohammad Karimi & Mohadeseh Rahbar, 2015. "A set covering approach for multi-depot train driver scheduling," Journal of Combinatorial Optimization, Springer, vol. 29(3), pages 636-654, April.
    6. Wang, Yiyuan & Pan, Shiwei & Al-Shihabi, Sameh & Zhou, Junping & Yang, Nan & Yin, Minghao, 2021. "An improved configuration checking-based algorithm for the unicost set covering problem," European Journal of Operational Research, Elsevier, vol. 294(2), pages 476-491.
    7. Otto, Alena & Tilk, Christian, 2024. "Intelligent design of sensor networks for data-driven sensor maintenance at railways," Omega, Elsevier, vol. 127(C).
    8. Victor Reyes & Ignacio Araya, 2021. "A GRASP-based scheme for the set covering problem," Operational Research, Springer, vol. 21(4), pages 2391-2408, December.
    9. Owais, Mahmoud & Moussa, Ghada S. & Hussain, Khaled F., 2019. "Sensor location model for O/D estimation: Multi-criteria meta-heuristics approach," Operations Research Perspectives, Elsevier, vol. 6(C).
    10. Dimitris Bertsimas & Dan A. Iancu & Dmitriy Katz, 2013. "A New Local Search Algorithm for Binary Optimization," INFORMS Journal on Computing, INFORMS, vol. 25(2), pages 208-221, May.
    11. Naji-Azimi, Zahra & Toth, Paolo & Galli, Laura, 2010. "An electromagnetism metaheuristic for the unicost set covering problem," European Journal of Operational Research, Elsevier, vol. 205(2), pages 290-300, September.
    12. Kedong Yan & Dongjing Miao & Cui Guo & Chanying Huang, 2021. "Efficient feature selection for logical analysis of large-scale multi-class datasets," Journal of Combinatorial Optimization, Springer, vol. 42(1), pages 1-23, July.
    13. Yagiura, Mutsunori & Kishida, Masahiro & Ibaraki, Toshihide, 2006. "A 3-flip neighborhood local search for the set covering problem," European Journal of Operational Research, Elsevier, vol. 172(2), pages 472-499, July.
    14. İbrahim Muter & Ş. İlker Birbil & Güvenç Şahin, 2010. "Combination of Metaheuristic and Exact Algorithms for Solving Set Covering-Type Optimization Problems," INFORMS Journal on Computing, INFORMS, vol. 22(4), pages 603-619, November.
    15. Murray, Alan T., 2001. "Strategic analysis of public transport coverage," Socio-Economic Planning Sciences, Elsevier, vol. 35(3), pages 175-188, September.
    16. Marco E. Lübbecke & Jacques Desrosiers, 2005. "Selected Topics in Column Generation," Operations Research, INFORMS, vol. 53(6), pages 1007-1023, December.
    17. Ablanedo-Rosas, José H. & Rego, César, 2010. "Surrogate constraint normalization for the set covering problem," European Journal of Operational Research, Elsevier, vol. 205(3), pages 540-551, September.
    18. Giovanni Felici & Sokol Ndreca & Aldo Procacci & Benedetto Scoppola, 2016. "A-priori upper bounds for the set covering problem," Annals of Operations Research, Springer, vol. 238(1), pages 229-241, March.
    19. Amadeu A. Coco & Andréa Cynthia Santos & Thiago F. Noronha, 2022. "Robust min-max regret covering problems," Computational Optimization and Applications, Springer, vol. 83(1), pages 111-141, September.
    20. Sergio Valdivia & Ricardo Soto & Broderick Crawford & Nicolás Caselli & Fernando Paredes & Carlos Castro & Rodrigo Olivares, 2020. "Clustering-Based Binarization Methods Applied to the Crow Search Algorithm for 0/1 Combinatorial Problems," Mathematics, MDPI, vol. 8(7), pages 1-42, July.

    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:inm:oropre:v:56:y:2008:i:6:p:1348-1365. 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: Chris Asher (email available below). General contact details of provider: https://edirc.repec.org/data/inforea.html .

    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.