With the aid of artificial intelligence, a Canadian startup BlueDot had spotted the coronavirus which was first referred to as a case of abnormal pneumonia around the city of Wuhan, China and immediately reports the case.
The startup was quick to report the case nine (9) days earlier which prompted more research before the World Health Organisation (WHO) official release their report about the virus which has now been referred to as COVID-19
BlueDot is a startup that basically use human and artificial intelligence to spot infectious diseases and quickly report it thereby protecting the populace.
It is a proprietary software-as-a-service programmed to track, locate and conceptualize infectious disease spread.
In 2019, the startup received funding of $9.4 million and $7 million series A funding from Horizons Ventures and The Co-operators and BDC Capital’s Women in Technology Venture Fund respectively.
Around December 2019, Kamran Khan, founder and CEO of BlueDot and professor of medicine and public health at the University of Toronto, told CNBC Make It, how they never knew that the Covid-19 will become a major problem when it was first spotted.
“We didn’t know at that moment that this was going to become something of this magnitude”
What if this outbreak gets bigger than what we are already seeing? And what if it’s bigger than we think and project as it is right now? Khan pondered.
Questions like this prompted Kamran Khan to build up the startup BlueDot – “Spread knowledge faster than the diseases spread themselves,” he says.
Khan is an epidemiologist and a physician who never went to any business school or had experience in coding but through the experience, he gathered while treating patients in Toronto during the outbreak of the severe acute respiratory syndrome (SARS), he was able to start BlueDot.
“Certainly, no one knew what SARS was until it literally showed up across major cities and hospitals,” Khan recalls.
He further states that “the mental and emotional fatigue of the SARs outbreak, which went on for six months, and killed a total of 774 people in 29 countries, including many of my fellow healthcare workers.”
According to the Centers for Disease Control, the disease cost an estimated $40 billion globally.
The startup process a lot of information all day long and relies on big data through machine learning and natural language processing to generate data from every source available e.g. official public health organizations, digital media, global airline ticketing data, livestock health reports and population demographics, etc.
The next goal of the startup is the plan to understand and have a clear data of how diseases spread to different parts of the world, and then determine the consequence.