April 25 is the World Malaria Day. World Health Organization data show that nearly half of the world's people have the risk of malaria, and estimated 2015, 212 million cases of malaria, resulting in 42.9 million deaths. In areas with high transmission rates, the number of malaria deaths in children under 5 years of age accounts for 70% of malaria deaths.
Although the number of malaria deaths has fallen sharply in the last decade, it is still a huge public health problem. For this reason, some technology companies are doing what they can to help eliminate the disease, such as through the Google Earth engine to use machine learning to achieve.
One of the key strategies for eradicating malaria is to identify the sites that are spreading and to block their footprints from the source as soon as possible. With the help of the Google Earth engine, DiSARM developed a high-resolution "risk map" to help organizations that develop malaria control programs to determine how resources are allocated across regions to prevent and treat.
DiSARM (disease surveillance and risk monitoring) is led by the Malaria Elimination Initiative and supported by the Bill and Melinda & Middot; Gates Foundation, as well as the Clinton Health Initiative. It curls the spread of malaria by drawing a map of the place where malaria occurs.
The head of the DiSARM project, Hugh Sturrock, said that at the very beginning they were piloting in Swaziland and Zimbabwe, where malaria was dying. Between 2000 and 2014, Swaziland reported a 99 per cent decline in malaria cases, compared with less than 400 cases reported by 2015. At the same time, Zimbabwe reported a decrease of 74 per cent in 2005 to 2015.
And when there are a few cases in a region, you need to accurately intervene to fully eliminate it. And DiSARM is to do so, by more strategic concentration of resources, can reduce the malaria map, and in some countries completely eliminate the disease.
How do I use Google Maps Engine to curb malaria?
If you can map the most likely place of malaria, you can act in these areas. Specifically, whenever someone is diagnosed with malaria in Swaziland and Zimbabwe, there will be a team of people coming to the infected village to collect accurate GPS information for the site of infection.
Of course, just looking at these locations is not possible to accurately determine the risk of malaria. There are also satellite images of various conditions, such as rainfall, temperature, slope and altitude, which will affect mosquito breeding and parasite development.
Lei Feng network (public: Lei Feng network) learned that the role of Google Maps Engine is to collect and organize the required public satellite image data. In the past, access to these image information is to find a variety of sources, such as NASA, USGS (US Geological Survey) and universities around the world. However, using Google Maps will be able to do this at a site and process it.
Combining satellite imagery data from the Google Maps Engine with malaria cases collected by the National Malaria Control Program, you can use models to generate and determine maps of the largest risk areas.
DiSARM has also developed a mobile application that can provide near real-time malaria and predict the risks of specific locations such as sanitation service areas, rural areas and schools. The overlay data also identifies areas where the level of protection is insufficient, so that resources can be allocated better for intervention.
The positioning module uses risk maps to prioritize interventions such as indoor residual spray, pesticide treatment networks and a large number of drug management.
In the future, Google Maps Engine will not only show malaria risk, but may also make predictions of future trends.