Artificial Intelligence to end infectious diseases
Innovator Rainier Mallol has developed a platform that uses Artificial Intelligence to predict future epidemics three months in advance.
Two years ago, zika virus raised serious concerns in Latin America. The disease, caused by a mosquito bite, spread across 20 countries in the region. The whole world became worried when the Rio Olympics in Brazil became compromised after some sportsmen were recommended not to attend that edition of the games.
One of the greatest risks involved by infectious diseases is the fact that it is very hard to accurately predict the next outbreak. Innovator Rainier Mallol has developed AIME with a view to fighting these epidemics. His tool has been designed to stop diseases such as denghe fever, zika and chikunguña.
Mallol, who is an IT engineer by training, explains how institutions for the prevention and control of epidemics are currently working to mitigate and end infectious diseases. However, they can only study these diseases’ behavioural patterns after their outbreak. This innovator from Dominican Republic has created a platform that uses an Artificial Intelligence algorithm to analyse huge amounts of data related to such diseases, in order to predict when and where the next outbreaks will take place.
Mallol has made an intranet available to hospitals and institutions so that they can access huge amounts of pandemics’ data, such as medical records. In this way, they can share their different health-related documents. For any other users, he has designed a mobile app that assesses data from sources as diverse as social media.
Through an analysis of all that information, AIME predicts future outbreaks three months in advance. This gives governments time to take all necessary measures to stop the spread of these diseases in time, which is key to stopping any pandemic at an early stage. In addition, AIME produces different resources that can help the design of public health strategies. For instance, it provides prediction maps and control panels where users can visualise the records and patients’ profiles from previous outbreaks.
This former participant at the Singularity University (US) claims that they have achieved 88% accuracy for denghe epidemics. In order to conduct these calculations, Mallol incorporated historical records about the disease and then generated predictions. Afterwards, he compared the results against outbreaks that occurred three months later.
Mallol, who was chosen by MIT Technology Review in Spanish as one of its Innovators under 35 in Latin America in 2017, and who has also participated in other great events such as Solution Summit 2016 in New York (US), believes that AIME would not only considerably improve public health in Latin America, but would have a huge financial impact too. “When you ignore when and where the next outbreak will take place, resources are invested blindly. There are countries, such as Brazil, that invest $1.3 billion every year for the sole purpose of fighting denghe”, says Mallol.
AIME has already been implemented in three cities: Rio de Janeiro (Brazil), Kuala Lumpur (Malaysia) and Manila (Philippines). In two of them they are working in close collaboration with the respective governments. Now, one of Mallol’s main goals is to bring the tool to more countries in Southeast Asia, since the countries in that region are amongst the world’s most affected by these diseases. However, as he acknowledges himself, his most pressing challenge is to build a healthier society: a future world that is better than today’s.