Mechanism design for a fair and equitable approach to global vaccine distribution: The case of COVID-19

Khaled Abedrabboh, Lolwa Al-Majid, Zaid Al-Fagih and Luluwah Al-Fagih

PLOS Global Public Health, 2023, vol. 3, issue 12, 1-21

Abstract: Vaccines are one of the most effective tools humanity has in the fight against pandemics. One of the major challenges of vaccine distribution is achieving fair and equitable allocation across the countries of the world, regardless of their economic wealth. The self-interested behaviour of high-income countries and the underutilisation of vaccines allocated to underprepared countries are some of the failures reported during COVID-19 vaccine roll-out. These shortcomings have motivated the need for a central market mechanism that takes into account the countries’ vulnerability to COVID-19 and their readiness to distribute and administer their allocated vaccines. In this paper, we leverage game theory to study the problem of equitable global vaccine distribution and propose a fair market mechanism that aligns self-interested behaviour with optimal global objectives. First, we model the interaction between a central vaccine provider (e.g. COVAX) and a country reporting its demand as a two-player game, and discuss the Nash and mixed Nash equilibria of that game. Then, we propose a repeated auction mechanism with an artificial payment system for allocating vaccines among participating countries, where each auction round is based on a Vickrey-Clarke-Groves (VCG) mechanism. The proposed allocation mechanism aims at minimising deaths and incentivises the self-interested countries to report their demand truthfully. Compared with real-world COVAX allocation decisions, our results show that the proposed auction mechanism achieves more efficient outcomes that maximise the number of averted deaths. Pragmatic considerations are investigated and policy recommendations are discussed.

Date: 2023
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Persistent link: https://EconPapers.repec.org/RePEc:plo:pgph00:0001711

DOI: 10.1371/journal.pgph.0001711

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