Artificial Intelligence Applied to Recognize and Monitor Outbreaks


Dr. Kamran Khan, an epidemiologist and entrepreneur, established BlueDot in 2014 after raising close to $10 million in venture capital funding. The company sifts through reports in 65 languages, reviews airline data, and official reports of human and animal disease outbreaks.

 Natural language processing and machine learning are applied to develop predictions relating to disease using proprietory algorithms. The automated data-gathering and predictions developed by BlueDot computers are then evaluated by epidemiologists for credibility and likelihood based on scientific principles before being formally incorporated into reports distributed to clients, including public health agencies and multinational companies.

BlueDot informed its clients that an outbreak of a disease with potential severity had occured in China on December 31st 2019. CDC was aware of a problem and issued a warning on January 6th, but it was only until January 9th that the World Health Organization announced the emergence of an influenza-like outbreak with clusters of pneumonia in China.

BlueDot successfully predicted that the Wuhan Coronavirus would spread to Bangkok, Seoul, Tokyo, and Taipei within a short period by analyzing air traffic data. BlueDot represents the future of detecting epidemics and their possible routes of dissemination, a direct application of “big data”.