Modeling Access Differences to Reduce Disparity in Resource Allocation

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Kenya S. Andrews, Mesrob I Ohannessian, Tanya Berger-Wolf

Published: 17 Oct 2022, Last Modified: 25 Jan 2025EAAMOEveryoneCC BY 4.0
Abstract: eaamo research-article Modeling Access Differences to Reduce Disparity in Resource Allocation Authors: Kenya Andrews, Mesrob Ohannessian, Tanya Berger-WolfAuthors Info & Claims EAAMO '22: Proceedings of the 2nd ACM Conference on Equity and Access in Algorithms, Mechanisms, and Optimization Article No.: 17, Pages 1 - 11 https://doi.org/10.1145/3551624.3555302 Published: 17 October 2022 Publication History 0 citation 76 Downloads Get Access EAAMO '22: Proceedings of the 2nd ACM Conference on Equity and Access in Algorithms, Mechanisms, and Optimization Modeling Access Differences to Reduce Disparity in Resource Allocation Pages 1 - 11 Previous Next Abstract Supplementary Material References Recommendations Comments ACM Digital Library Information & Contributors Bibliometrics & Citations Get Access References35 Share Abstract Motivated by COVID-19 vaccine allocation, where vulnerable subpopulations are simultaneously more impacted in terms of health and more disadvantaged in terms of access to the vaccine, we formalize and study the problem of resource allocation when there are inherent access differences that correlate with advantage and disadvantage. We identify reducing resource disparity as a key goal in this context and show its role as a proxy to more nuanced downstream impacts. We develop a concrete access model that helps quantify how a given allocation translates to resource flow for the advantaged vs. the disadvantaged, based on the access gap between them. We then provide a methodology for access-aware allocation. Intuitively, the resulting allocation leverages more vaccines in locations with higher vulnerable populations to mitigate the access gap and reduce overall disparity. Surprisingly, knowledge of the access gap is often not needed to perform access-aware allocation. To support this formalism, we provide empirical evidence for our access model and show that access-aware allocation can significantly reduce resource disparity and thus improve downstream outcomes. We demonstrate this at various scales, including at county, state, national, and global levels.