After nearly losing his mother to a mosquito-borne disease called dengue, a young scientist by the name of Rainier Mallol developed an AI algorithm that uses big data to predict outbreaks of the pandemic-prone illness. His mother was one of an estimated 390 million Dengue infections every year. And although there is a vaccine, there is no specific treatment once contracted. Mallol, who grew up in the Dominican Republic, wanted to do something about the life-threatening disease, which is why he set up Aime, an epidemiology company which has one clear aim: to predict disease outbreaks before they happen. Aime uses a predictive system that considers data outside the common domains of public health, such as weather and geographical data in order to find patterns and monitor the spread of the disease. So far, the company has tested the predictive model in two countries and claims an average accuracy of 86.4 percent. The breakthrough could potentially help authorities in disease-stricken countries to easily break down an outgoing outbreak by prevalent symptoms, population demographics and other relevant factors and act accordingly.
How using AI could help predict pandemics of life-threatening diseases
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