Advisory
Bryan Tegomoh, MD, MPH advises the institutions making consequential decisions about AI in public health: health agencies and global health organizations, the funders who back them, and the companies and labs building population-scale tools. Engagements are independent and evidence-centered, held to the same standard as this handbook: what the evidence shows, what it does not, and what is at stake for the population when a tool is wrong.
The chapters linked below are the public evidence base for the areas where independent review is most valuable.
Advisory Scope
For public health agencies, funders, and health technology teams, advisory work is most appropriate when a decision requires epidemiologic judgment, operational realism, and governance-aware AI evaluation:
- Disease surveillance and outbreak detection for digital surveillance, early-warning systems, and multi-source signal review
- Epidemic forecasting for model selection, uncertainty communication, and scenario-planning decisions
- AI system evaluation for validation plans, performance metrics, and post-deployment monitoring
- Privacy, security, and governance for data-sharing, public trust, and deployment safeguards
- AI policy and governance for model policy, institutional review, and public health program design
Advisory work is independent. It does not imply endorsement of a product, organization, or public claim.
Tell me the organization, the decision in front of you, and any materials worth reading first.