Ethical Implications of Artificial Intelligence in Vaccine Equity: Protocol for Exploring Vaccine Distribution Planning and Scheduling in Pandemics in Low- and Middle-Income Countries
BackgroundThe COVID-19 pandemic highlighted significant disparities in vaccine distribution, particularly in low- and middle-income countries (LMICs). Artificial intelligence (AI) has emerged as a potential tool to optimize vaccine distribution planning and scheduling. Howeve...
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JMIR Publications
2025-07-01
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| Series: | JMIR Research Protocols |
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| author | Ifeanyichukwu Akuma Vina Vaswani Elif Perihan Ekmekci |
| author_facet | Ifeanyichukwu Akuma Vina Vaswani Elif Perihan Ekmekci |
| author_sort | Ifeanyichukwu Akuma |
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BackgroundThe COVID-19 pandemic highlighted significant disparities in vaccine distribution, particularly in low- and middle-income countries (LMICs). Artificial intelligence (AI) has emerged as a potential tool to optimize vaccine distribution planning and scheduling. However, its ethical implications, including equity, transparency, bias, and accessibility, remain underexplored. Ensuring ethical AI implementation in vaccine distribution is crucial to addressing health equity challenges worldwide.
ObjectiveThis study aims to assess the ethical implications of AI-assisted vaccine distribution planning and scheduling in LMICs during pandemics. It seeks to evaluate AI’s role in ensuring equitable vaccine access, analyze ethical concerns associated with its deployment, and propose an ethical framework to guide AI-based vaccine distribution strategies.
MethodsOur multiphase qualitative research approach will combine a systematic scoping review, a witness seminar with key stakeholders (health care professionals, AI developers, policymakers, and bioethicists), and a meta-synthesis of findings. The scoping review will follow PRISMA-ScR (Preferred Reporting Items for Systematic reviews and Meta-Analyses Extension for Scoping Reviews) guidelines, focusing on studies from 2019 to 2023. The witness seminar will provide firsthand insights into AI’s ethical impact on vaccine equity. Thematic content analysis and qualitative coding will be used for data interpretation, with findings integrated into a policy-driven ethical framework.
ResultsThis study received institutional ethical approval in October 2023. Recruitment commenced in mid-August 2024 through email requests to prospective participants, and recruitment for the witness seminar (focus group discussion) is still ongoing, with 7 expert participants confirmed. Data collection is projected to conclude by August 2025. Preliminary literature analysis from the scoping review is ongoing, and qualitative data analysis from the witness seminar is scheduled for September 2025. The final results and proposed ethical framework are expected to be published in early 2026.
ConclusionsBy examining the ethical implications of AI in vaccine distribution, this research will provide actionable recommendations for policymakers, health care organizations, and AI developers. The findings will contribute to the discourse on responsible AI deployment in health care worldwide, ensuring transparency, fairness, and inclusivity in pandemic response strategies.
International Registered Report Identifier (IRRID)DERR1-10.2196/76634 |
| format | Article |
| id | doaj-art-8633ca48554b45a89fe2f4348d0944ce |
| institution | Kabale University |
| issn | 1929-0748 |
| language | English |
| publishDate | 2025-07-01 |
| publisher | JMIR Publications |
| record_format | Article |
| series | JMIR Research Protocols |
| spelling | doaj-art-8633ca48554b45a89fe2f4348d0944ce2025-08-20T03:33:35ZengJMIR PublicationsJMIR Research Protocols1929-07482025-07-0114e7663410.2196/76634Ethical Implications of Artificial Intelligence in Vaccine Equity: Protocol for Exploring Vaccine Distribution Planning and Scheduling in Pandemics in Low- and Middle-Income CountriesIfeanyichukwu Akumahttps://orcid.org/0000-0002-7010-9322Vina Vaswanihttps://orcid.org/0000-0001-8914-0795Elif Perihan Ekmekcihttps://orcid.org/0000-0002-0777-3861 BackgroundThe COVID-19 pandemic highlighted significant disparities in vaccine distribution, particularly in low- and middle-income countries (LMICs). Artificial intelligence (AI) has emerged as a potential tool to optimize vaccine distribution planning and scheduling. However, its ethical implications, including equity, transparency, bias, and accessibility, remain underexplored. Ensuring ethical AI implementation in vaccine distribution is crucial to addressing health equity challenges worldwide. ObjectiveThis study aims to assess the ethical implications of AI-assisted vaccine distribution planning and scheduling in LMICs during pandemics. It seeks to evaluate AI’s role in ensuring equitable vaccine access, analyze ethical concerns associated with its deployment, and propose an ethical framework to guide AI-based vaccine distribution strategies. MethodsOur multiphase qualitative research approach will combine a systematic scoping review, a witness seminar with key stakeholders (health care professionals, AI developers, policymakers, and bioethicists), and a meta-synthesis of findings. The scoping review will follow PRISMA-ScR (Preferred Reporting Items for Systematic reviews and Meta-Analyses Extension for Scoping Reviews) guidelines, focusing on studies from 2019 to 2023. The witness seminar will provide firsthand insights into AI’s ethical impact on vaccine equity. Thematic content analysis and qualitative coding will be used for data interpretation, with findings integrated into a policy-driven ethical framework. ResultsThis study received institutional ethical approval in October 2023. Recruitment commenced in mid-August 2024 through email requests to prospective participants, and recruitment for the witness seminar (focus group discussion) is still ongoing, with 7 expert participants confirmed. Data collection is projected to conclude by August 2025. Preliminary literature analysis from the scoping review is ongoing, and qualitative data analysis from the witness seminar is scheduled for September 2025. The final results and proposed ethical framework are expected to be published in early 2026. ConclusionsBy examining the ethical implications of AI in vaccine distribution, this research will provide actionable recommendations for policymakers, health care organizations, and AI developers. The findings will contribute to the discourse on responsible AI deployment in health care worldwide, ensuring transparency, fairness, and inclusivity in pandemic response strategies. International Registered Report Identifier (IRRID)DERR1-10.2196/76634https://www.researchprotocols.org/2025/1/e76634 |
| spellingShingle | Ifeanyichukwu Akuma Vina Vaswani Elif Perihan Ekmekci Ethical Implications of Artificial Intelligence in Vaccine Equity: Protocol for Exploring Vaccine Distribution Planning and Scheduling in Pandemics in Low- and Middle-Income Countries JMIR Research Protocols |
| title | Ethical Implications of Artificial Intelligence in Vaccine Equity: Protocol for Exploring Vaccine Distribution Planning and Scheduling in Pandemics in Low- and Middle-Income Countries |
| title_full | Ethical Implications of Artificial Intelligence in Vaccine Equity: Protocol for Exploring Vaccine Distribution Planning and Scheduling in Pandemics in Low- and Middle-Income Countries |
| title_fullStr | Ethical Implications of Artificial Intelligence in Vaccine Equity: Protocol for Exploring Vaccine Distribution Planning and Scheduling in Pandemics in Low- and Middle-Income Countries |
| title_full_unstemmed | Ethical Implications of Artificial Intelligence in Vaccine Equity: Protocol for Exploring Vaccine Distribution Planning and Scheduling in Pandemics in Low- and Middle-Income Countries |
| title_short | Ethical Implications of Artificial Intelligence in Vaccine Equity: Protocol for Exploring Vaccine Distribution Planning and Scheduling in Pandemics in Low- and Middle-Income Countries |
| title_sort | ethical implications of artificial intelligence in vaccine equity protocol for exploring vaccine distribution planning and scheduling in pandemics in low and middle income countries |
| url | https://www.researchprotocols.org/2025/1/e76634 |
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