SCALE Nutrition

 What DOES SCALE DO?

SCALE helps Ministries of Health and their partners assess different program design options, estimating the impact on coverage, costs, and efficiency. It supports evidence-based decisions on how to expand treatment for child malnutrition. Learn more.

HOW DOES SCALE WORK?

SCALE is a modeling tool that allows users to compare scenarios by adjusting admission criteria, discharge criteria, product choices, dosages, and delivery strategies. It generates outputs that highlight trade-offs across cost, coverage, and effectiveness. Learn more.

WHO IS SCALE FOR?

SCALE is built for governments, donors, and implementing partners looking to understand the implications of program design decisions. It provides a user-friendly interface with both detailed and default input options for flexible analysis. Learn more.

What does SCALE do?

SCALE is a scenario analysis tool that helps decision-makers compare treatment options and costs for child malnutrition. Developed by the IRC’s Best Use of Resources and Nutrition Research teams, and piloted with UNICEF Kenya and the Kenyan Ministry of Health, the tool allows users to customize scenarios with their own data and instantly see the impact on resources, cost, and efficiency.

By integrating both cost and treatment protocols, SCALE helps practitioners design programs that maximize reach and helps policy-makers choose approaches best suited to their context. Instead of requiring lengthy and technical modeling, SCALE quickly estimates resource needs such as RUTF, staffing, and cost-efficiency, giving governments and partners an accessible way to test and compare program designs.

The MVP of SCALE is now live and open-access, and we are actively piloting and refining it with partners. As further testing continues, the tool will evolve into a fully guided, user-friendly application designed for non-technical users while leveraging the latest global evidence.

HOW DOES SCALE WORK?

SCALE uses a scenario-based approach to compare different malnutrition treatment designs. Users select the program “ingredients” they want to test, such as admission and discharge criteria, RUTF dosages, delivery models, and staffing, and input either detailed local data or use default values built into the tool.

The tool then automatically generates estimates of coverage, resource requirements, and cost-efficiency for each scenario, allowing side-by-side comparison. This makes it easy for decision-makers to understand trade-offs across different program designs without needing complex modeling expertise.

The current MVP provides a functional online platform, and we are piloting it with governments and partners to refine the user experience. The next phase of development will focus on support materials, updated features, and improved outputs tailored to non-technical users, ensuring results are both robust and accessible.