MediScout+ improves the ability of health program planners to predict communities most prone to poverty-related diseases and the worst outcomes from outbreaks. These predictions with other predictive maps will help in better targetting intensified disease detection programs and emergency preparedness. It builds on the success of MediScout+ ; an integrated set of tools used to plan, implement and monitor community-based disease control programs. MediScout+ was trained to automatically analyze satellite images and classify each neighborhood with an outbreak vulnerability score. This layer of analysis will increase the impact of MediScout+ predictive tools in urban settings.

The tool has proved valuable in identifying tuberculosis at-risk populations across the Great Lake region in Africa (Rwanda, Burundi, DRC), predicting risk zones using data from various sources such as open sources, socioeconomic data, historical epidemiological data, and satellite imagery data.