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AI Warned of Wuhan Coronavirus Outbreak Ahead of WHO and CDC
January 28, 2020 News


The World Health Organisation (WHO) first notified the public about the outbreak of the Wuhan coronavirus on the 9th of January after Chinese authorities confirmed that they had identified a new virus in Wuhan City located in the Hubei Province of China.

The disease, temporarily named “2019-nCoV”, has since spread to other parts of mainland China as well as the rest of the world in just a matter of a few weeks, with the death toll now reaching 106 people at the time of writing.

According to reports, what’s truly dangerous about the virus is that officials believe since the incubation period can be up to two weeks without showing any symptoms, a person may be able to spread the virus without even knowing it. In China, around 15 cities, with a combined population of over 57 million people, have been placed under full or partial lockdown in an effort to contain the virus.

In the case of such outbreaks, time is of the essence. The sooner people are informed about the spread of the virus as well as its characteristics, the better chance they have at combating it, or at least keeping casualties to a minimum. It is therefore interesting to note that a Canadian health monitoring platform, powered by artificial intelligence, had warned its customers of the outbreak as early as 31st of December 2019.

The platform, named BlueDot, is a solution that’s designed to “track, contextualise, and anticipate infectious disease risks”. As stated on its website, “Infectious diseases pose a growing global threat in our interconnected world. More frequent and severe in the last 20 years than at any other time in history, infectious diseases are flourishing within a new reality of global travel, urbanisation, and climate change. But while diseases spread fast, knowledge can spread even faster.”

BlueDot is able to give customers advance warning to avoid high-risk zones such as Wuhan using an AI-driven algorithm that scours foreign-language news reports, animal and plant disease networks, as well as official announcements. spoke to BlueDot’s founder and CEO, Kamran Khan, who said that since governments may not always be relied upon to provide information in a timely fashion, we are now in the position to use AI to get accurate information regarding diseases, air pollution, or natural disasters much faster.

While the algorithm does not use social media postings (because that data is too messy), it was able to leverage airline ticketing data to correctly predict that the virus would spread from Wuhan to Bangkok, Seoul, Taipei, and Tokyo in the days following its initial appearance.

Khan was reported to have launched BlueDot in 2014, and the company now has 40 employees consisting of physicians and programmers. The algorithm uses natural language processing (NLP) and machine learning techniques to sift through vast amounts of data. The ensuing report will then be examined and analysed by epidemiologists before it is sent to government, business, and public health clients.

Khan decided to come up with the solution in his search to find “a better way to track diseases” after he himself went through the harrowing experience of working as a hospital infectious disease specialist in Toronto during the SARS epidemic of 2003 which recorded almost 800 casualties worldwide.

Unlike the SARS epidemic, where China was criticised by the UN’s global health body for concealing the scale of the outbreak, critics are saying that they’ve learned a few lessons this time around.

But another powerful weapon that we may have at our disposal now and going forward is how we can now use AI and lots of data from disparate and disconnected sources to produce a wide range of insights – even in the field of epidemiology to prevent, control, monitor and predict the spread of diseases.