The Disease Surveillance And Risk Monitoring project: supporting data-driven disease elimination
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Project overview

Using data can lead to more impactful decision making over intuition alone. But collecting, analyzing, and visualizing data is difficult, especially in resource constrained settings. The Disease Surveillance and Risk Monitoring (DiSARM) project, which ran from 2015-2020, built tools to help disease control programs use data to target interventions spatially, guide field teams more precisely, and evaluate coverage more robustly. A key aspect of the DiSARM project was the development of algorithms that can help distill data into actionable intelligence. These algorithms can be integrated into applications such as the DiSARM application or can be accessed through an application programming interface (API).

While the project has now closed, information about the project, including algorithm and software code, remains open-source. Links to the relevant GitHub repositories are contained on the documentation site.

The DiSARM project was led by the Malaria Elimination Initiative at the University of California San Francisco in collaboration with Peoplesized and the Clinton Health Access Initiative. The project was supported by the Bill & Melinda Gates Foundation, Task Force for Global Health, and Google.


The DiSARM project is developing a variety of algorithms that turn raw data into actionable outputs. You can access our algorithms through the DiSARM API.

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DiSARM Application

The DiSARM app is a spatial intelligence tool that supports disease control programs in carrying out intervention field campaigns in a more effective way. In its current form, the DiSARM app is being used to implement insecticide residual spray campaigns in southern Africa.

A series of screencasts are available here

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