PROJECT OVERVIEW

Roughly 76% of Ethiopia’s population currently lives in rural areas with limited access to basic healthcare. To address this, government planners are working to build or upgrade health facilities in ways that maximize access to comprehensive care. However, these choices are incredibly complex as budgets may change unexpectedly across years and regional priorities often differ.

RESEARCH OVERVIEW

In collaboration with the Ethiopian Ministry of Health and public health researchers, our team developed a decision-support tool that helps planners make more data-informed, equitable choices about where and when to invest in health infrastructure.

Behind the scenes, this tool is powered by AI algorithms that reason about yearly budget uncertainty and regional prioritization tradeoffs. Our goal is not to replace planners, but to empower them — providing a transparent and flexible interface for making better decisions. This project demonstrates how AI can be co-developed with local stakeholders to support long-term health equity on a national scale.

To enhance the applicability and the acceptance of our tool, we are extending our method to incorporate input from local experts and stakeholders, in addition to the other considerations.

PROJECT PARTICIPANTS

(Sorted in alphabetical last name ordering)

PARTNER ORGANIZATIONS AND AFFILIATIONS OF PROJECT PARTICIPANTS

MEDIA

To be updated.

RELATED PUBLICATIONS

(* Indicates equal contribution)

Davin Choo*, Yohai Trabelsi*, Fentabil Getnet, Samson Warkaye Lamma, Wondesen Nigatu, Kasahun Sime, Lisa Matay, Milind Tambe, Stéphane Verguet. Optimizing Health Coverage in Ethiopia: A Learning-augmented Approach and Persistent Proportionality Under an Online Budget. In AISI track, AAAI Conference on Artificial Intelligence (2026).