In the northern Peruvian department of Loreto, malaria, spread by the Anopheles mosquito, has profound economic and health impacts. Malaria can cause extreme fever, vomiting, seizures and even death. Recovery can take 2-4 weeks, preventing individuals from partaking in economic or educational activities. Medication can also be expensive for low income families, potentially causing substantial economic hardship. 92% of all malaria cases in Peru were located Loreto. Yearly cases of malaria fluctuate greatly from 4,000 cases to over 12,000 cases depending on a wide variety of factors such as rainfall, local interventions as well as personal protection. Better understanding the main drivers of malaria is crucial in preventing future malaria outbreaks.

The project’s goal is to create an early detection and warning system for malaria risk to prevent malaria outbreaks. This is being accomplished by developing a series of interlocking models of rainfall, land cover, hydrology, mosquito counts and case counts of malaria to predict malaria cases, allowing Peruvian health officials to efficiently distribute limited health resources and limit the probability of outbreaks from occurring.