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Project Summary 

This DPhil project aims to investigate the social, ethical, and institutional dimensions of emerging technologies central to the Pathogen Program's mission to transform infectious disease diagnosis and response. The Pathogen Program is building a global pathogen monitoring ecosystem using frontier approaches such as metagenomics, federated data infrastructures, and AI. Alongside striving for 91���� excellence, the program is committed to proactively incorporating the ethical, legal, and social implications (ELSI) of these technologies to ensure their responsible, equitable, and effective deployment. 

This project aims to embed a rigorous socio-technical research project within the Pathogen Program’s activities, exploring how new challenges can be anticipated and governed through academically grounded methods and real-world insight. It is anticipated that the candidate will apply mixed methods, such as ethnography, co-design, policy analysis or technical audits, to examine how tools and platforms are developed, implemented, and sustained across diverse health systems. 

The project is intentionally broad, with the expectation that the DPhil candidate will explore up to three focus areas based on their background, areas of interest and most urgent need of the program. Illustrative research questions include: 

• How can diagnostic devices be co-designed to build trust, equity, and usability in diverse care settings? 
• What frameworks enable clinical diagnostics to function as both patient tools and public health sensors? 
• How can federated data platforms balance data sovereignty, public health goals, and equitable participation? 
• What governance mechanisms support responsible cross-border data sharing? 
• How can bias detection, transparency, and explainability be built into AI outbreak detection systems? 
• What makes digital tools adaptable and trustworthy across different health system contexts? 
• How can global surveillance efforts be sustainably coordinated and governed as a public good? 

Potential Supervisors 

• Professor Gil McVean (Principal Scientist, Pathogen Program, EIT & Professor of Statistical Genetics, Department of Statistics and the Nuffield Department of Medicine, University of Oxford)����
• Dr Maxine Mackintosh (Pathogen Program & Associate Researcher, University of Oxford)  
• Ethox representative to be confirmed  

Skills Recommended 

• Qualitative research methods: ethnography, narrative interviews, participatory design 
• Foundational understanding of science and technology studies (STS), bioethics, and health systems 
• Technical literacy in genomics workflows, diagnostic devices, and machine learning pipelines 
• Mixed-methods competencies: network analysis, comparative policy review, regulatory mapping 
• Stakeholder facilitation and engagement across clinical, technical, and community domains 

Skills to be Developed 

• Algorithmic audit methods and fairness assessment frameworks 
• Advanced co-design and translational research facilitation with interdisciplinary teams 
• Comparative legal and policy analysis of data governance and global health law 
• Governance toolkit development and evaluation metrics for real-world implementation 
• Strategic communication of socio-technical risks to non-specialist and policy audiences 

University DPhil Courses

A range of possible DPhil courses may include:

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Relevant Background Reading 

• Panteli, D., et al. (2025). Artificial intelligence in public health: Promises, challenges, and an agenda for policy makers and public health institutions. The Lancet Public Health, 10(5), e428–e432. 
• Black, A., MacCannell, D. R., Sibley, T. R., et al. (2020). Ten recommendations for supporting open pathogen genomic analysis in public health. Nature Medicine, 26, 832–841. 
• Moodley, K., et al. (2022). Ethics and governance challenges related to genomic data sharing in southern Africa: The case of SARS-CoV-2. The Lancet Global Health, 10(12), e1855–e1859. 
• Shaw, J., & Sekalala, S. (2023). Health data justice: Building new norms for health data governance. npj Digital Medicine, 6, 30.  
• Zhai, Y., Hong, G., Jiang, M., & Wei, Q. (2022). Access and benefit-sharing of pathogenic microorganisms such as SARS-CoV-2. Biosafety and Health, 4(6), 414–420. 
• Schwalbe, N., et al. (2020). Artificial intelligence and the future of global health. The Lancet, 395(10236), 1579–1586. 
• Greenbaum, D., Gurwitz, D., & Joly, Y. (2022). Editorial: COVID-19 pandemics: Ethical, legal and social issues. Frontiers in Genetics, 13, Article 1021865. 

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