research-article

Initial COVID-19 Vaccine Distribution Policy Optimisation

Authors:

Susan Grant-Muller,

Lili YangAuthors Info & Claims

EBEE '21: Proceedings of the 2021 3rd International Conference on E-Business and E-commerce Engineering

Pages 108 - 118

https://doi.org/10.1145/3510249.3510270

Published: 23 March 2022 Publication History

Abstract

As COVID-19 becoming a global epidemic, owing to the interventions’ operation limited efficacy and virus’ super transmission ability, the vaccine is considered the most potent method left to cease the COVID-19 effectively. At the beginning of the vaccine distribution policy design, there were many real concerns: vaccine priority, budget control, vaccine inventory limitation, and expected objectives making the problem complex. The research optimised the vaccine distribution policy (VDP) in an explicit form incorporated in an age-stratified SEIR model based on the proposed policy optimisation methodology. The VDP could explain when and how many vaccines to take for each age group. The designed evaluation system consisted of direct policy cost, indirect healthcare cost, and extra financial budget during the pandemic, combined as a weighted sum equalling one to suit flexible scenarios and decision-makers’ requirements. A case study with ground truth data in the U.K was implemented, where the optimised VDP could decrease the comprehensive cost and suppress the virus transmission. Furthermore, the sensitivity analysis demonstrated the effect of some critical parameters for optimised VDP. The vaccination priority and policy objectives’ weight combination play a significant role in impacting the VDP optimisation. The research could be a framework for flexible vaccination policy design in different scenarios by changing weights, vaccine limitations, and other initial parameter configurations.

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A APPENDICES

Cited By

Wu SWu ZMo LHuang ZYang L(2023)Time-delayed Geodemographic Scaling Algorithm for Fast COVID-19 Simulation2023 4th International Conference on Computer, Big Data and Artificial Intelligence (ICCBD+AI)10.1109/ICCBD-AI62252.2023.00128(700-705)Online publication date: 15-Dec-2023
https://doi.org/10.1109/ICCBD-AI62252.2023.00128
Wu SHuang ZGrant-Muller SGu DYang L(2023)Modelling the reopen strategy from dynamic zero-COVID in China considering the sequela and reinfectionScientific Reports10.1038/s41598-023-34207-713:1Online publication date: 5-May-2023
https://doi.org/10.1038/s41598-023-34207-7

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EBEE '21: Proceedings of the 2021 3rd International Conference on E-Business and E-commerce Engineering

December 2021

331 pages

ISBN:9781450387392

DOI:10.1145/3510249

Copyright © 2021 ACM.

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Publication History

Published: 23 March 2022

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EBEE 2021: 2021 3rd International Conference on E-Business and E-commerce Engineering

December 17 - 19, 2021

Sanya, China

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Cited By

Wu SWu ZMo LHuang ZYang L(2023)Time-delayed Geodemographic Scaling Algorithm for Fast COVID-19 Simulation2023 4th International Conference on Computer, Big Data and Artificial Intelligence (ICCBD+AI)10.1109/ICCBD-AI62252.2023.00128(700-705)Online publication date: 15-Dec-2023
https://doi.org/10.1109/ICCBD-AI62252.2023.00128
Wu SHuang ZGrant-Muller SGu DYang L(2023)Modelling the reopen strategy from dynamic zero-COVID in China considering the sequela and reinfectionScientific Reports10.1038/s41598-023-34207-713:1Online publication date: 5-May-2023
https://doi.org/10.1038/s41598-023-34207-7

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