Polynomials may help scientists combat one of the world’s deadliest diseases. Every year, malaria kills 660,000 people. Most of the victims are children under the age of five. People who contract malaria are stuck with the disease for the rest of their lives. Relapses can keep a person from earning a living or feeding her family. As the climate warms, more and more areas will become susceptible to this mosquito-borne disease.
Planning for Outbreaks
To prevent malaria deaths, aid workers need to know how to best use their limited resources. Mosquito nets treated with insecticides can protect children while they sleep. If a child begins showing symptoms of the disease, he needs to receive medical treatment within 24 hours in order to prevent death. Since malaria is transmitted by mosquitoes, malaria spreads more quickly when the local population of mosquitoes increases. If health workers knew where to expect mosquitoes, they could move their resources to the area at risk and prepare for an outbreak.
Recall that artificial neural networks are computational models that can be “trained” to detect patterns in data and make predictions. These networks consist of a group of nodes, each of which performs a mathematical operation to simulate the way the brain processes information and makes decisions. Using polynomials, scientists have built a neural network that analyzes the effects of weather on malaria outbreaks. Based on weather data, the program can predict new outbreaks with 88% accuracy. This information allows aid organizations to relocate supplies to where people will need them most.
The power to predict outbreaks is an important step in the fight against malaria. However, medical researchers are also trying to develop new treatments and search for a vaccine, with the ultimate hope of eradicating the disease.
Take a closer look at the transmission of malaria: http://www.youtube.com/watch?v=IVbq2yQH52g
Check out the articles below to find out about recent developments in malaria research. Watch the video to learn about the epidemic in Central Africa.