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How AI Could Help Us Survive the Next Plague

over 2 years ago by Ben Taylor

People Wearing Surgical Masks in Shanghai

As news of the coronavirus outbreak plagues headlines of newspapers the world over, we still know very little about how it has developed and is being spread. And whilst there is almost a global ‘panic’ surrounding the coronavirus, as it is still relatively mysterious – governments and public health officials are scrambling to coordinate a quick and effective response. So in the midst of a health epidemic, could artificial intelligence be the answer to helping us survive what is being referred to as the ‘next plague’.

On January 9, the WHO (World Health Organisation) announced to the public that there was a flu-like outbreak in Wuhan, China, where there had been several reported cases of pneumonia, possibly linked to exposure to live animals at the Huanan Seafood Market. However, BlueDot (a Canadian health monitory platform) had already raised concerns of an outbreak to their customers over a week before hand.

BlueDot is a Canadian firm which specialises in automated infectious disease surveillance. Using an AI-driven algorithm, BlueDot analyses around 100,000 news reports, animal and plant disease networks and official proclamations in 65 languages in order to give its clients warnings to avoid danger zones like Wuhan ahead of an outbreak. After the automated data-sifting has concluded, epidemiologists will check the conclusions over from a scientific standpoint and the report is then sent to government, business and public health clients.

Kamran Khan, CEO and founder of BlueDot is quick to point out that in the case of an outbreak, speed is essential and while we currently rely on public health officials to monitor and share information about diseases, air pollution and natural disasters, AI might get there faster. 

Khan says, “We know that governments may not be relied upon to provide information in a timely fashion, we can pick up news of possible outbreaks, little murmurs or forums or blogs of indications of some kind of unusual events going on.” Khan also points out that they do not currently use data from social media as it isn’t always reliable.

Until now, there has been around 100 fatalities linked to the coronavirus, and according to some experts it could affect as many as 100,000 people globally. So, while we must rely on public health officials to act honestly and quickly to help stop the spread of disease, it seems clear that we should also utilise AI-driven epidemiologists to assist in catching the early signs of an outbreak before it escalates into a global pandemic.

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