English

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

Artificial Intelligence 2022-02-11 v1 Data Structures and Algorithms Multiagent Systems Social and Information Networks

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.

Keywords

Cite

@article{arxiv.2202.04705,
  title  = {Deploying Vaccine Distribution Sites for Improved Accessibility and Equity to Support Pandemic Response},
  author = {George Li and Ann Li and Madhav Marathe and Aravind Srinivasan and Leonidas Tsepenekas and Anil Vullikanti},
  journal= {arXiv preprint arXiv:2202.04705},
  year   = {2022}
}

Comments

14 pages, 4 figures, to appear at AAMAS 2022