Optimizing Health Coverage in Ethiopia: A Learning-augmented Approach and Persistent Proportionality Under an Online Budget
Researchers have developed a new optimization framework called the Health Access Resource Planner (HARP) to help Ethiopia's Ministry of Health prioritize healthcare investments. This tool aims to maximize population coverage within budget constraints and meet regional proportionality targets. Two algorithms, a learning-augmented approach and a greedy multi-step planning algorithm, were proposed and demonstrated effective in simulations with Ethiopian public health data. AI
IMPACT This AI-driven planning tool could improve resource allocation for public health initiatives in developing nations.