Publication
Title
Vaccine distribution modelling in pandemics through multi-agent systems : COVID-19 case
Author
Abstract
Multi-agent systems (MAS) have become increasingly used in addressing complex problems that require collaboration and coordination between multiple entities. In the context of infectious disease management, MAS can enable a more nuanced understanding of the complex social dynamics at play, including the behavior and interactions of individuals that determine the rate of infection and mortality.This paper proposes two vaccine distribution methods based on MAS and the concepts of bankruptcy and the Susceptible-Exposed-Infectious-Recovered (SEIR) model, which take into account the prioritization of individuals based on their behavior and their impact on the infection rate of the disease. To propose these methods first, we propose a base algorithm named Vaccine Allocation Problem (VAP) that prioritizes individuals based on their impact on community health.The proposed methods were evaluated in comparison with classic bankruptcy methods such as Proportional (P), Talmud, and Pinile methods. In addition, we use the Covid-19 data set provided by "Belgian Institute for Health" as a case study. Simulation results indicated the better performance of the proposed method in terms of infection, hospitalization, Intensive Care Unit (ICU), new-In, and mortality rates.
Language
English
Source (book)
2023 13th International Conference on Computer and Knowledge Engineering (ICCKE), 01-02 November, 2023, Mashhad, Iran
Publication
IEEE , 2023
ISBN
979-83-503-3015-1
DOI
10.1109/ICCKE60553.2023.10326240
Volume/pages
(2023) , p. 277-285
Full text (Publisher's DOI)
Full text (publisher's version - intranet only)
UAntwerpen
Faculty/Department
Research group
Publication type
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Affiliation
Publications with a UAntwerp address
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Creation 05.01.2024
Last edited 09.01.2024
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