Ordering COVID-19 vaccines for social welfare with information updating: Optimal dynamic order policies and vaccine selection in the digital age

Xiaoyan Xu, Suresh P. Sethi, Sai-Ho Chung and Tsan-Ming Choi

IISE Transactions, 2024, vol. 56, issue 7, 729-745

Abstract: In the digital age, operations can be improved by a wise use of information and technological tools. During the COVID-19 pandemic, governments faced various choices of vaccines possessing different efficacy and availability levels at different time points. In this article, we consider a two-stage vaccine ordering problem of a government from a first and only supplier in the first stage, and either the same supplier or a new second supplier in the second stage. Between the two stages, potential demand information for the vaccine is collected to update the forecast. Using dynamic programming, we derive the government’s optimal vaccine ordering policy. We find that the government should select its vaccine supplier based on the disease’s infection rate in the society. When the infection rate is low, the government should order nothing at the first stage and order from the supplier with a higher efficacy level at the second stage. When the disease’s infection rate is high, the government should order vaccines at the first stage and switch to the other supplier with a lower efficacy level at the second stage. We extend our model to examine (i) the value of blockchain adoption and (ii) the impact of vaccines’ side effects.

Date: 2024
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DOI: 10.1080/24725854.2023.2204329

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