Case Study: Spatial analysis

We analyzed tens of thousands of machine learning models to identify the most influential factors contributing to child mortality across seven countries. This extensive process allowed us to map regional variations in key drivers of child mortality, offering detailed insights into local challenges. These findings are now being leveraged by an international development agency to create and implement targeted interventions that address the specific needs of vulnerable populations. By integrating data science with on-the-ground health strategies, our work is directly contributing to the development of more effective, region-specific solutions to improve child survival outcomes.