Ethical Barriers to Artificial Intelligence Adoption in Vaccine Distribution: A Systematic Scoping Review

Abstract

The rapid advancement of AI has opened new avenues for improving healthcare systems, particularly in a pandemic response. AI technologies can potentially affect the equitable distribution of vaccines. However, there are ethical concerns such as privacy, governance, data security, acceptance, access, affordability, prioritization among others that arise from such implementation. This article synthesizes literature to identify the ethical implications of utilizing AI in vaccine distribution, planning and scheduling during a pandemic, with a focus on ensuring equitable access to vaccines in LMICs using a combination of 20 search string-words. The Preferred Reporting Items for Systematic Review and Meta-Analysis (PRISMA) guideline for scoping review was used. A full-text open access peer review journals in English addressing the research interest from PubMed, ScienceDirect, and the Directory of Open Access Journals (DOAJ) was included in the study. These search engines were chosen based on their comprehensive coverage, advanced search capabilities, reputation for academic quality, and efficient retrieval of relevant and diverse literature. Data from each search engine was screened for inclusion criteria and charted from 2019 to 2023 to cover the COVID-19 pandemic period. Bibliometric analysis was done on the Web of Science search engine using R-studio and Biblioshiny to identify trends. Out of 1,555 records, 358 articles relevant to the search query were found; after careful consideration, 28 articles met the inclusion criteria for analysis. Thematic analysis was done to identify the ethical considerations associated with using AI in planning and scheduling vaccine distribution, particularly in the context of a pandemic. The article emphasized the importance of integrating lessons learned from the COVID-19 pandemic into future actions to strengthen a fair and equitable pandemic preparedness plan ensuring the ethical compliance of AI-support system responses in LMICs during pandemics. © 2025 Elsevier B.V., All rights reserved