Robust Analytics for Adaptive Malaria Control

Robust Analytics for Malaria Policy (RAMP) is a bespoke inferential system that combines conventional and simulation-based analytics to develop malaria policy that has gone to great lengths to characterize, quantify, and propagate uncertainty. RAMP was developed to support Adaptive Malaria Control a methodology for managing malaria with high quality, robust analytics that includes two essential components:

• it should be iterative; and

• it should be designed to identify, prioritize, and fill critical uncertainties.

This methodology draws on principles developed for adaptive management of natural resources, including a reliance on mathematical theory and models. The concept is not entirely new to malaria, but it had not been formally described as a methodology or implemented by a national malaria program

Here, we describe RAMP and adaptive malaria control with a focus on developing the supporting concepts and methods.

• We have presented the material in this website in a series of short focused essays or vignettes. The sidebar presents an outline of the material with links to the vignettes. A good place to start is the Overview

• In the navigation bar (at the top), there are some additional links:

  • Related Content includes links to websites developed to support RAMP and Adaptive Malaria Control.

  • Essays includes links to short vignettes around concepts and essays that don’t fit naturally into the the flow of topics in the sidebar.

• We have implemented the methodology for the national malaria program in Uganda. To learn more, please see the companion website Adaptive Malaria Control, Uganda