Cost–benefit analysis of the COVID-19 vaccination model incorporating different infectivity reductions

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dc.contributor.authorAsamoah, Joshua Kiddy K.
dc.contributor.authorAppiah,, Raymond Fosu
dc.contributor.authorJin, Zhen
dc.contributor.authorYang, Junyuan
dc.contributor.orcid0000-0002-7066-246X
dc.date.accessioned2024-11-21T08:06:53Z
dc.date.available2024-11-21T08:06:53Z
dc.date.issued2024-05
dc.descriptionThis article is published by Frontiers 2024 and is also available at 10.3389/fphy.2024.1383357
dc.description.abstractThe spread and control of coronavirus disease 2019 (COVID-19) present a worldwide economic and medical burden to public health. It is imperative to probe the effect of vaccination and infectivity reductions in minimizing the impact of COVID-19. Therefore, we analyze a mathematical model incorporating different infectivity reductions. This work provides the most economical and effective control methods for reducing the impact of COVID-19. Using data fromGhana as a sample size, we study the sensitivity of the parameters to estimate the contributions of the transmission routes to the effective reproduction number Re. We also devise optimal interventions with cost–benefit analysis that aim to maximize outcomes while minimizing COVID-19 incidences by deploying cost-effectiveness and optimization techniques. The outcomes of this work contribute to a better understanding of COVID-19 epidemiology and provide insights into implementing interventions needed to minimize the COVID-19 burden in similar settings worldwide.
dc.description.sponsorshipKNUST
dc.identifier.citationAppiah RF, Jin Z, Yang J and Asamoah JKK (2024), Cost–benefit analysis of the COVID-19 vaccination model incorporating different infectivity reductions. Front. Phys. 12:1383357.
dc.identifier.uri10.3389/fphy.2024.1383357
dc.identifier.urihttps://ir.knust.edu.gh/handle/123456789/15985
dc.language.isoen
dc.titleCost–benefit analysis of the COVID-19 vaccination model incorporating different infectivity reductions
dc.typeArticle
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