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Effective Social Network-Based Allocation of COVID-19 Vaccines

Authors: Jiangzhuo Chen,

Achla Marathe, Henning Mortveit,

Bryan Lewis, Srinivasan Venkatramanan,

Arash Haddadan, Parantapa Bhattacharya,

Anil Vullikanti, Aravind Srinivasan,

Mandy L. Wilson, Gal Ehrlich, Maier Fenster,

Stephen Eubank, Christopher Barrett,

Madhav MaratheAuthors Info & Claims

KDD '22: Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining

Pages 4675 - 4683

https://doi.org/10.1145/3534678.3542673

Published: 14 August 2022 Publication History

Abstract

We study allocation of COVID-19 vaccines to individuals based on the structural properties of their underlying social contact network. Using a realistic representation of a social contact network for the Commonwealth of Virginia, we study how a limited number of vaccine doses can be strategically distributed to individuals to reduce the overall burden of the pandemic. We show that allocation of vaccines based on individuals' degree (number of social contacts) and total social proximity time is significantly more effective than the usually used age-based allocation strategy in reducing the number of infections, hospitalizations and deaths. The overall strategy is robust even: (i) if the social contacts are not estimated correctly; (ii) if the vaccine efficacy is lower than expected or only a single dose is given; (iii) if there is a delay in vaccine production and deployment; and (iv) whether or not non-pharmaceutical interventions continue as vaccines are deployed. For reasons of implementability, we have used degree, which is a simple structural measure and can be easily estimated using several methods, including the digital technology available today. These results are significant, especially for resource-poor countries, where vaccines are less available, have lower efficacy, and are more slowly distributed.

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Index Terms

Effective Social Network-Based Allocation of COVID-19 Vaccines
1. Applied computing
  1. Life and medical sciences
    1. Health informatics
2. Computing methodologies
  1. Modeling and simulation
    1. Simulation types and techniques
      1. Agent / discrete models

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cover image ACM Conferences

KDD '22: Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining

August 2022

5033 pages

ISBN:9781450393850

DOI:10.1145/3534678

General Chairs:
Aidong Zhang
University of Virginia
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Huzefa Rangwala
Amazon/George Mason University

Copyright © 2022 Owner/Author.

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Published: 14 August 2022

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https://doi.org/10.1109/JBHI.2024.3392436
Yin FCrooks AYin L(2024)How information propagation in hybrid spaces affects decision-making: using ABM to simulate Covid-19 vaccine uptakeInternational Journal of Geographical Information Science10.1080/13658816.2024.233393038:6(1109-1135)Online publication date: 3-Apr-2024
https://doi.org/10.1080/13658816.2024.2333930
Chen DLi ALi GMarathe MSrinivasan ATsepenekas LVullikanti AElkind E(2023)Efficient and equitable deployment of mobile vaccine distribution centersProceedings of the Thirty-Second International Joint Conference on Artificial Intelligence10.24963/ijcai.2023/8(64-72)Online publication date: 19-Aug-2023
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