Inventory policy for the vaccine of a new pandemic


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PINARBAŞI A., Vizvári B.

Computers and Industrial Engineering, vol.208, 2025 (SCI-Expanded, Scopus) identifier identifier

  • Publication Type: Article / Article
  • Volume: 208
  • Publication Date: 2025
  • Doi Number: 10.1016/j.cie.2025.111383
  • Journal Name: Computers and Industrial Engineering
  • Journal Indexes: Science Citation Index Expanded (SCI-EXPANDED), Scopus, ABI/INFORM, Aerospace Database, Applied Science & Technology Source, Business Source Elite, Business Source Premier, Communication Abstracts, Compendex, Computer & Applied Sciences, INSPEC, Metadex, DIALNET, Civil Engineering Abstracts
  • Keywords: Hungarian inventory model, Pandemic, Sigmoid function, Upper confidence contour, Vaccine
  • Middle East Technical University Affiliated: Yes

Abstract

The COVID-19 pandemic underscored that vaccine inventory management differs fundamentally from conventional production-related inventory problems. In this context, ensuring supply reliability takes precedence over cost minimization. This paper applies the Hungarian inventory model to determine the optimal initial vaccine stock based on a predefined probability of avoiding shortages. Unlike traditional models, this approach incorporates the non-linear dynamics of vaccine uptake, where the population's willingness to be vaccinated follows a sigmoid time function. The vaccine stocking scenario is treated as a single-period inventory problem. Simulations are conducted for three countries—Denmark, Hungary, and Mexico—each representing different levels of public willingness to receive vaccines. The numerical results demonstrate that the target probability of non-shortage can be achieved under the proposed model. These findings offer valuable insights for public health authorities and policymakers in planning efficient and reliable vaccine procurement strategies under uncertainty.