Deploying Vaccine Distribution Sites for Improved Accessibility and Equity to Support Pandemic Response

TL;DR

This paper formulates and analyzes an optimization problem for deploying vaccine sites to enhance accessibility and equity, providing algorithms with theoretical guarantees and demonstrating their effectiveness through real-world data experiments.

Contribution

It introduces a novel combinatorial model for vaccine site placement focusing on accessibility and equity, along with efficient algorithms and hardness results.

Findings

Algorithms achieve near-optimal solutions in practice.

Strong theoretical guarantees on accessibility and equity.

Demonstrated effectiveness on real-world vaccination data.

Abstract

In response to COVID-19, many countries have mandated social distancing and banned large group gatherings in order to slow down the spread of SARS-CoV-2. These social interventions along with vaccines remain the best way forward to reduce the spread of SARS CoV-2. In order to increase vaccine accessibility, states such as Virginia have deployed mobile vaccination centers to distribute vaccines across the state. When choosing where to place these sites, there are two important factors to take into account: accessibility and equity. We formulate a combinatorial problem that captures these factors and then develop efficient algorithms with theoretical guarantees on both of these aspects. Furthermore, we study the inherent hardness of the problem, and demonstrate strong impossibility results. Finally, we run computational experiments on real-world data to show the efficacy of our methods.