How maps and machine learning are helping to eliminate malaria

Allie Lieber at The Keyword: “Today is World Malaria Day, a moment dedicated to raising awareness and improving access to tools to prevent malaria. The World Health Organization says nearly half of the world’s population is at risk for malaria, and estimates that in 2015 there were 212 million malaria cases resulting in 429,000 deaths. In places with high transmission rates, children under five account for 70 percent of malaria deaths.

DiSARM (Disease Surveillance and Risk Monitoring), a project led by the Malaria Elimination Initiative and supported by the Bill and Melinda Gates Foundationand Clinton Health Access Initiative, is fighting the spread of malaria by mapping the places where malaria could occur. With the help of Google Earth Engine, DiSARM creates high resolution “risk maps” that help malaria control programs identify the areas where they should direct resources for prevention and treatment.

We sat down with Hugh Sturrock, who leads the DiSARM project and is an Assistant Professor of Epidemiology and Biostatistics in the University of California, San Francisco’s Global Health Group, to learn more about DiSARM’s fight against malaria, and how Google fits in….

How does DiSARM use Google Earth Engine to help fight malaria?

If we map where malaria is most likely to occur, we can target those areas for action. Every time someone is diagnosed with malaria in Swaziland and Zimbabwe, a team goes to the village where the infection occurred and collects a GPS point with the precise infection location. Just looking at these points won’t allow you to accurately determine the risk of malaria, though. You also need satellite imagery of conditions like rainfall, temperature, slope and elevation, which affect mosquito breeding and parasite development.

To determine the risk of malaria, DiSARM combines the precise location of the malaria infection,  with satellite data of conditions like rainfall, temperature, vegetation, elevation, which affect mosquito breeding. DiSARM’s mobile app can be used by the malaria programs and field teams to target interventions.

Google Earth Engine collects and organizes the public satellite imagery data we need. In the past we had to obtain those images from a range of sources: NASA, USGS and different universities around the world. But with Google Earth Engine, it’s all in one place and can be processed using Google computers. We combine satellite imagery data from Google Earth Engine with the locations of malaria cases collected by a country’s national malaria control program, and create models that let us generate maps identifying areas at greatest risk.

The DiSARM interface gives malaria programs a near real-time view of malaria and predicts risk at specific locations, such as health facility service areas, villages and schools. Overlaying data allows malaria control programs to identify high-risk areas that have insufficient levels of protection and better distribute their interventions….(More)”