Optimal Models for Distributing Vaccines in a Pandemic

Md Hassan, Md Hassan, Mahzabeen Emu, Zubair Fadlullah, Zubair Fadlullah, Salimur Choudhury

2022

Abstract

Distributing vaccines among a massive population is one of the challenging tasks in a pandemic. Therefore, health care organizations need to optimize the assignment of vaccination appointments for people while considering their priorities and preferences. In this paper, we propose two optimal vaccine distribution models as Integer Linear Programming (ILP) models; namely, Priority-based Model (PM) and Priority & Preference-based Model (PPM), to maximize the distribution of vaccines among a given population. In PM, we divide the people among several priority groups and ensure maximum vaccine distribution among the higher priority groups. However, along with the priority groups, PPM also considers a list of preferred vaccine distribution centers and time slots for each person. Thus, this model maximizes vaccine distribution among the higher priority groups by assigning appointments in their desired location and time. We analyzed the performance of our proposed models on a randomly generated dataset. In addition, we also performed a case study for our proposed models on the COVID-19 vaccination dataset from Thunder Bay, Canada. In both experiments, we show that PPM outperforms PM in full-filling people’s preferences while maximizing the distribution of vaccines among the higher priority groups.

Paper Citation

in Harvard Style

Hassan M., Emu M., Fadlullah Z. and Choudhury S. (2022). Optimal Models for Distributing Vaccines in a Pandemic. In Proceedings of the 11th International Conference on Operations Research and Enterprise Systems - Volume 1: ICORES, ISBN 978-989-758-548-7, pages 337-344. DOI: 10.5220/0010819600003117

in Bibtex Style

@conference{icores22,
author={Md Hassan and Mahzabeen Emu and Zubair Fadlullah and Salimur Choudhury},
title={Optimal Models for Distributing Vaccines in a Pandemic},
booktitle={Proceedings of the 11th International Conference on Operations Research and Enterprise Systems - Volume 1: ICORES,},
year={2022},
pages={337-344},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0010819600003117},
isbn={978-989-758-548-7},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 11th International Conference on Operations Research and Enterprise Systems - Volume 1: ICORES,
TI - Optimal Models for Distributing Vaccines in a Pandemic
SN - 978-989-758-548-7
AU - Hassan M.
AU - Emu M.
AU - Fadlullah Z.
AU - Choudhury S.
PY - 2022
SP - 337
EP - 344
DO - 10.5220/0010819600003117