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A model of supply‐chain decisions for resource sharing with an application to ventilator allocation to combat COVID‐19

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  • Sanjay Mehrotra
  • Hamed Rahimian
  • Masoud Barah
  • Fengqiao Luo
  • Karolina Schantz

Abstract

We present a stochastic optimization model for allocating and sharing a critical resource in the case of a pandemic. The demand for different entities peaks at different times, and an initial inventory for a central agency are to be allocated. The entities (states) may share the critical resource with a different state under a risk‐averse condition. The model is applied to study the allocation of ventilator inventory in the COVID‐19 pandemic by FEMA to different U.S. states. Findings suggest that if less than 60% of the ventilator inventory is available for non‐COVID‐19 patients, FEMA's stockpile of 20 000 ventilators (as of March 23, 2020) would be nearly adequate to meet the projected needs in slightly above average demand scenarios. However, when more than 75% of the available ventilator inventory must be reserved for non‐COVID‐19 patients, various degrees of shortfall are expected. In a severe case, where the demand is concentrated in the top‐most quartile of the forecast confidence interval and states are not willing to share their stockpile of ventilators, the total shortfall over the planning horizon (until May 31, 2020) is about 232 000 ventilator days, with a peak shortfall of 17 200 ventilators on April 19, 2020. Results are also reported for a worst‐case where the demand is at the upper limit of the 95% confidence interval. An important finding of this study is that a central agency (FEMA) can act as a coordinator for sharing critical resources that are in short supply over time to add efficiency in the system. Moreover, through properly managing risk‐aversion of different entities (states) additional efficiency can be gained. An additional implication is that ramping up production early in the planning cycle allows to reduce shortfall significantly. An optimal timing of this production ramp‐up consideration can be based on a cost‐benefit analysis.

Suggested Citation

  • Sanjay Mehrotra & Hamed Rahimian & Masoud Barah & Fengqiao Luo & Karolina Schantz, 2020. "A model of supply‐chain decisions for resource sharing with an application to ventilator allocation to combat COVID‐19," Naval Research Logistics (NRL), John Wiley & Sons, vol. 67(5), pages 303-320, August.
    • Handle: RePEc:wly:navres:v:67:y:2020:i:5:p:303-320
    DOI: 10.1002/nav.21905
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    References listed on IDEAS

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    1. Yisha Xiang & Jun Zhuang, 2016. "A medical resource allocation model for serving emergency victims with deteriorating health conditions," Annals of Operations Research, Springer, vol. 236(1), pages 177-196, January.
    2. Stephanie Earnshaw & Katherine Hicks & Anke Richter & Amanda Honeycutt, 2007. "A linear programming model for allocating HIV prevention funds with state agencies: a pilot study," Health Care Management Science, Springer, vol. 10(3), pages 239-252, September.
    3. Steffen Flessa, 2000. "Where efficiency saves lives: A linear programme for the optimal allocation of health care resources in developing countries," Health Care Management Science, Springer, vol. 3(3), pages 249-267, June.
    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. Hui Cao & Simin Huang, 2012. "Principles of Scarce Medical Resource Allocation in Natural Disaster Relief," Medical Decision Making, , vol. 32(3), pages 470-476, May.
    6. Yen-Yi Feng & I-Chin Wu & Tzu-Li Chen, 2017. "Stochastic resource allocation in emergency departments with a multi-objective simulation optimization algorithm," Health Care Management Science, Springer, vol. 20(1), pages 55-75, March.
    7. Benjamin Armbruster & Margaret Brandeau, 2007. "Contact tracing to control infectious disease: when enough is enough," Health Care Management Science, Springer, vol. 10(4), pages 341-355, December.
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