Optimized Vaccine Allocation Based on Preferences and Access: Case of COVID-19

Document Type : Research/ Original/ Regular Article

Authors

1 Assistant professor of industrial engineering, Gorgan faculty of engineering, Golestan University, Gorgan, Iran

2 Graduated in Industrial Engineering, Gorgan Faculty of Engineering, Golestan University, Gorgan, Iran

Abstract

The development of new technologies for producing COVID-19 vaccines, due to time constraints in the   production process and the influence of diverse media reports, has led to varying perceptions among individuals regarding the efficacy and side effects of different vaccine brands. This highlights that individuals' understanding of the quality and desirability of a vaccine brand can play a significant role in their willingness to receive it. This study focuses on examining the impact of logistical measures on the   equitable distribution of various vaccine brands, aiming to increase vaccination rates and ultimately achieve better pandemic management. In this research, three mathematical models were designed to      simulate consumer behavior: the first model does not consider individuals' preferences for a specific  vaccine brand; the second model takes these preferences into account; and the third model, in addition to preferences, examines individuals' reactions when their preferred vaccine brand is unavailable. In all   models, the primary priorities are reducing the spread of the disease, focusing on densely populated areas, and mitigating the social consequences of the pandemic. Results reveal that these models can facilitate   equitable distribution of vaccines across the country, contributing to improved disease control and a  reduction in the social impacts of the pandemic.
 

Keywords

Main Subjects

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Supply Chain Management
Volume 26, Issue 85 - Serial Number 85
Serial number 85. Winter 2025
March 2025
Pages 47-68

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History

  • Receive Date: 28 November 2024
  • Revise Date: 06 January 2025
  • Accept Date: 11 February 2025
  • Publish Date: 10 March 2025

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