research-article

An epidemiology-based model for the operational allocation of COVID-19 vaccines: : A case study of Thailand

Authors:

Pisit Jarumaneeroj,

Puwadol Oak Dusadeerungsikul,

Tharin Chotivanich,

Tanawin Nopsopon,

Krit PongpirulAuthors Info & Claims

Volume 167, Issue C

https://doi.org/10.1016/j.cie.2022.108031

Published: 01 May 2022 Publication History

Highlights

•

An SIQRV model is integrated with the COVID-19 Vaccine Allocation Problem (CVAP).

•

With limited vaccine supply, epicenter-based strategies tend to underperform.

•

Demographics and vaccine efficacy greatly affect the potency of vaccine allocation.

•

Early vaccination could significantly reduce the number of infected individuals.

•

Societal cooperation plays a crucial role in controlling the spread of COVID-19.

Abstract

This paper addresses a framework for the operational allocation and administration of COVID-19 vaccines in Thailand, based on both COVID-19 transmission dynamics and other vital operational restrictions that might affect the effectiveness of vaccination strategies in the early stage of vaccine rollout. In this framework, the SIQRV model is first developed and later combined with the COVID-19 Vaccine Allocation Problem (CVAP) to determine the optimal allocation/administration strategies that minimize total weighted strain on the whole healthcare system. According to Thailand’s second pandemic wave data (17^th January 2021, to 15^th February 2021), we find that the epicenter-based strategy is surprisingly the worst allocation strategy, due largely to the negligence of provincial demographics, vaccine efficacy, and overall transmission dynamics that lead to higher number of infectious individuals. We also find that early vaccination seems to significantly contribute to the reduction in the number of infectious individuals, whose effects tend to increase with more vaccine supply. With these insights, healthcare policy-makers should therefore focus not only on the procurement of COVID-19 vaccines at strategic levels but also on the allocation and administration of such vaccines at operational levels for the best of their limited vaccine supply.

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Cited By

Nikoubin AMahnam MMoslehi G(2023)A relax-and-fix Pareto-based algorithm for a bi-objective vaccine distribution network considering a mix-and-match strategy in pandemicsApplied Soft Computing10.1016/j.asoc.2022.109862132:COnline publication date: 1-Jan-2023
https://dl.acm.org/doi/10.1016/j.asoc.2022.109862

Index Terms

An epidemiology-based model for the operational allocation of COVID-19 vaccines: A case study of Thailand
1. Applied computing
  1. Life and medical sciences
2. Computing methodologies
  1. Modeling and simulation

Index terms have been assigned to the content through auto-classification.

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cover image Computers and Industrial Engineering

Computers and Industrial Engineering Volume 167, Issue C

May 2022

696 pages

ISSN:0360-8352

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Elsevier Ltd.

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Pergamon Press, Inc.

United States

Publication History

Published: 01 May 2022

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Cited By

Nikoubin AMahnam MMoslehi G(2023)A relax-and-fix Pareto-based algorithm for a bi-objective vaccine distribution network considering a mix-and-match strategy in pandemicsApplied Soft Computing10.1016/j.asoc.2022.109862132:COnline publication date: 1-Jan-2023
https://dl.acm.org/doi/10.1016/j.asoc.2022.109862

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