Genomics and Health Data Governance in Africa: Democratize the Use of Big Data and Popularize Public Engagement.

Effectively addressing ethical issues in precision medicine research in Africa requires a holistic social contract that integrates biomedical knowledge with local cultural values and Indigenous knowledge systems. We make several recommendations for a social contract for genomics and data science in health, including the coproduction of genomics knowledge with study communities, power sharing between stakeholders, public education on the ethical and social implications of genetics and data scienc...

⚡ This is an original paraphrased summary — not copied from the abstract. Full paper available at the source link below.

• 1 Drawing on African epistemologies such as ubuntu and ujamaa and on our collective experiences in genomics and big data research for sickle cell disease, hearing impairment, and fragile X syndrome and the project Public Understanding of Big Data in Genomics Medicine in Africa, we envision a transformative shift in health research data governance in Africa that could help create a sense of shared responsibility between all stakeholders in genomics and data-driven health research in Africa.
• 2 This shift includes proposing a social contract for genomics and data science in health research that is grounded in African communitarianism such as solidarity, shared decision-making, and reciprocity.
• 3 We make several recommendations for a social contract for genomics and data science in health, including the coproduction of genomics knowledge with study communities, power sharing between stakeholders, public education on the ethical and social implications of genetics and data science, benefit sharing, giving voice to data subjects through dynamic consent, and democratizing data access to allow wide access by all research stakeholders.

Understanding this could lead to better treatments, improved diagnostics, or a deeper grasp of how the human body works — benefiting patient care globally.

This summary is based on publicly available metadata and abstract. For the full research paper, visit the original source: