Operationalizing AI-assisted decision support for high-consequence biological threats in Kenya

What does it take to put AI-assisted decision support to work in a real public health system?

This virtual workshop answers that question through a case study from Kenya, offering a look at what becomes possible when researchers and practitioners build and apply these tools in practice.

OASIS-Kenya focuses on high-consequence biological threats, where timely, well-informed decisions can shape the course of a response. Presented by people doing the work, the session moves beyond the theory of AI and big data for health to show how decision support can be operationalized: what it looks like on the ground, what it can enable, and what it asks of the teams and systems that use it.

The workshop is designed for professionals in global health, pandemic preparedness and response, infectious disease research, and health data science. Whether you are building data infrastructure, advising on response strategy, or exploring how AI can strengthen public health decision-making in your own setting, you will come away with a concrete example of what is possible and ideas to carry into your own work.