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Modeling the Logistics of Response to Anthrax Bioterrorism

Author

Listed:
  • Gregory S. Zaric

    (Ivey School of Business, University of Western Ontario, Canada, gzaric@ivey.uwo.ca)

  • Dena M. Bravata

    (Center for Primary Care and Outcomes Research, Stanford University School of Medicine, Stanford, California, Stanford-UCSF Evidence-Based Practice Center, Stanford, California)

  • Jon-Erik Cleophas Holty

    (Center for Primary Care and Outcomes Research, Stanford University School of Medicine, Stanford, California, VA Palo Alto Health Care System, Palo Alto, California)

  • Kathryn M. McDonald

    (Center for Primary Care and Outcomes Research, Stanford University School of Medicine, Stanford, California, Stanford-UCSF Evidence-Based Practice Center, Stanford, California)

  • Douglas K. Owens

    (Center for Primary Care and Outcomes Research, Stanford University School of Medicine, Stanford, California, Stanford-UCSF Evidence-Based Practice Center, Stanford, California, VA Palo Alto Health Care System, Palo Alto, California)

  • Margaret L. Brandeau

    (Department of Management Science and Engineering, Stanford University, Stanford, California)

Abstract

Background. A bioterrorism attack with an agent such as anthrax will require rapid deployment of medical and pharmaceutical supplies to exposed individuals. How should such a logistical system be organized? How much capacity should be built into each element of the bioterrorism response supply chain? Methods. The authors developed a compartmental model to evaluate the costs and benefits of various strategies for preattack stockpiling and postattack distribution and dispensing of medical and pharmaceutical supplies, as well as the benefits of rapid attack detection. Results. The authors show how the model can be used to address a broad range of logistical questions as well as related, nonlogistical questions (e.g., the cost-effectiveness of strategies to improve patient adherence to antibiotic regimens). They generate several key insights about appropriate strategies for local communities. First, stockpiling large local inventories of medical and pharmaceutical supplies is unlikely to be the most effective means of reducing mortality from an attack, given the availability of national and regional supplies. Instead, communities should create sufficient capacity for dispensing prophylactic antibiotics in the event of a large-scale bioterror attack. Second, improved surveillance systems can significantly reduce deaths from such an attack but only if the local community has sufficient antibiotic-dispensing capacity. Third, mortality from such an attack is significantly affected by the number of unexposed individuals seeking prophylaxis and treatment. Fourth, full adherence to treatment regimens is critical for reducing expected mortality. Conclusions. Effective preparation for response to potential bioterror attacks can avert deaths in the event of an attack. Models such as this one can help communities more effectively prepare for response to potential bioterror attacks.

Suggested Citation

  • Gregory S. Zaric & Dena M. Bravata & Jon-Erik Cleophas Holty & Kathryn M. McDonald & Douglas K. Owens & Margaret L. Brandeau, 2008. "Modeling the Logistics of Response to Anthrax Bioterrorism," Medical Decision Making, , vol. 28(3), pages 332-350, May.
  • Handle: RePEc:sae:medema:v:28:y:2008:i:3:p:332-350
    DOI: 10.1177/0272989X07312721
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    References listed on IDEAS

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    1. Eva K. Lee & Siddhartha Maheshwary & Jacquelyn Mason & William Glisson, 2006. "Large-Scale Dispensing for Emergency Response to Bioterrorism and Infectious-Disease Outbreak," Interfaces, INFORMS, vol. 36(6), pages 591-607, December.
    2. Nathaniel Hupert & Alvin I. Mushlin & Mark A. Callahan, 2002. "Modeling the Public Health Response to Bioterrorism: Using Discrete Event Simulation to Design Antibiotic Distribution Centers," Medical Decision Making, , vol. 22(1_suppl), pages 17-25, September.
    3. Howard Kunreuther & Erwann Michel-Kerjan & Beverly Porter, 2003. "Assessing, Managing, and Financing Extreme Events: Dealing with Terrorism," NBER Working Papers 10179, National Bureau of Economic Research, Inc.
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    Cited by:

    1. Caunhye, Aakil M. & Li, Mingzhe & Nie, Xiaofeng, 2015. "A location-allocation model for casualty response planning during catastrophic radiological incidents," Socio-Economic Planning Sciences, Elsevier, vol. 50(C), pages 32-44.
    2. Margaret L. Brandeau, 2019. "OR Forum—Public Health Preparedness: Answering (Largely Unanswerable) Questions with Operations Research—The 2016–2017 Philip McCord Morse Lecture," Operations Research, INFORMS, vol. 67(3), pages 700-710, May.
    3. David Simchi-Levi & Nikolaos Trichakis & Peter Yun Zhang, 2019. "Designing Response Supply Chain Against Bioattacks," Operations Research, INFORMS, vol. 67(5), pages 1246-1268, September.
    4. Kılıç, Hakan & Güneş, Evrim Didem, 2024. "Patient adherence in healthcare operations: A narrative review," Socio-Economic Planning Sciences, Elsevier, vol. 91(C).
    5. Alain, Guinet & Angel, Ruiz, 2016. "Modeling the logistics response to a bioterrorist anthrax attackAuthor-Name: Wanying, Chen," European Journal of Operational Research, Elsevier, vol. 254(2), pages 458-471.
    6. Michael A. Hamilton & Tao Hong & Elizabeth Casman & Patrick L. Gurian, 2015. "Risk‐Based Decision Making for Reoccupation of Contaminated Areas Following a Wide‐Area Anthrax Release," Risk Analysis, John Wiley & Sons, vol. 35(7), pages 1348-1363, July.
    7. Ubaid Illahi & Mohammad Shafi Mir, 2021. "Maintaining efficient logistics and supply chain management operations during and after coronavirus (COVID-19) pandemic: learning from the past experiences," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 23(8), pages 11157-11178, August.
    8. Aakil M. Caunhye & Xiaofeng Nie, 2018. "A Stochastic Programming Model for Casualty Response Planning During Catastrophic Health Events," Transportation Science, INFORMS, vol. 52(2), pages 437-453, March.
    9. Galindo, Gina & Batta, Rajan, 2013. "Review of recent developments in OR/MS research in disaster operations management," European Journal of Operational Research, Elsevier, vol. 230(2), pages 201-211.
    10. Pan, Yuqing & Cheng, T.C.E. & He, Yuxuan & Ng, Chi To & Sethi, Suresh P., 2022. "Foresighted medical resources allocation during an epidemic outbreak," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 164(C).
    11. Hanane Allioui & Azzeddine Allioui & Youssef Mourdi, 2024. "Maintaining effective logistics management during and after COVID‑19 pandemic: survey on the importance of artificial intelligence to enhance recovery strategies," OPSEARCH, Springer;Operational Research Society of India, vol. 61(2), pages 918-962, June.

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