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How Artificial Intelligence predicted the coronavirus outbreak

How Artificial Intelligence predicted the coronavirus outbreak

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Since the outbreak of a novel strain of coronavirus, the world has been on edge. Given that this particular strain is new, scientists have yet to discover how it will react, how it mutates and just how serious this has the potential of becoming.

What is the coronavirus?

Recently, it was reported that the death toll from the coronavirus in China has reached 170. The disease, which originated in Wuhan, China, has been able to spread with ease due to the fact that it’s symptoms resemble those of any common less serious respiratory illness. These symptoms can include a fever, sore throat, headache and difficulty in breathing. Interestingly enough, although diseases such as coronavirus are difficult to diagnose by doctors, computer programmes have the ability to detect warning signs of an epidemic before it begins.

How did AI predict coronavirus?

BlueDot, a Canadian firm that specialises in infectious disease surveillance, was the first to report of an impending biohazard. BlueDot is one of the many companies that is able to use data to evaluate public health risks. On December 31st, BlueDot was able to predict the outbreak of coronavirus. It notified it’s customers about the potential outbreak of this disease days before the US Centre for Disease Control and Protection and World Health Organisation were able to issue notices about it.

They were successful in doing this by using an artificial-intelligence powered system that combs through animal and plant disease networks, news reports in vernacular websites, government documents, and other online sources. They are then able to warn their clients against travelling to danger zones such as Wuhan and they were successful in doing this much before foreign governments issued travel bans.

AI was also successful in predicting where it would spread

BlueDot was not just successful in predicting that coronavirus was going to spread in Wuhan, but it managed to predict the other areas that the virus would spread to. It did this by using global airline ticketing data and was able to anticipate that the virus would spread to Seoul, Bangkok, Taipei and Tokyo.

How is the system able to do this?

The company is able to do this by using machine learning and natural language processing techniques. Through these ways, they were able to create models that processed large amounts of data in real time. The different types of data include airline ticketing data, news reports in up to 65 different languages, animal and plant disease networks.

After the system churns out automated results, the findings are analysed by trained epidemiologists who draw inferences and attach a risk factor to each case. Then, a report is drafted sent to BlueDot’s clients.

The system is also able to use an array of other data, such as information about an area’s climate, temperature, or even local livestock, to predict whether someone infected with a disease is likely to cause an outbreak in that area. BlueDot’s technology has had success in the past by predicting the appearance of the Zika virus in Florida six months before it actually showed up there.

What is the goal behind this technology?

The idea behind BlueDot’s model, whose final results are always analyzed by human researchers, is to get information to health care workers as quickly as possible, with the hope that they can diagnose and, if needed, isolate infected and potentially contagious people early on.

Kamran Khan, an infectious disease physician and BlueDot’s founder and CEO, explained in an interview that “The official information isn’t always timely,” he continued “The difference between one case in a traveler and an outbreak depends upon your frontline health care worker recognizing that there is a particular disease. It could be the difference in preventing an outbreak from actually occurring.”

What’s are the next steps?

With the coronavirus death toll increasing, the Chinese government has put the city of Wuhan on lockdown and restricted air travel in an effort to contain the spread. The problem is that this is that the lockdown of a public area has the potential to become detrimental to public health. It furthers the risk to the domestic population, as well as causing the decline of medical supplies into the quarantined area. This is not to mention the public resentment and anger that is likely to foster within residents of this region.

Can AI help us predict future epidemics?

One of the most difficult things for researchers and government officials is quickly gathering data once a mysterious new disease emerges. In this regard, AI can be incredibly useful. If used correctly and given enough attention to, AI can help prevent future epidemics and potentially even future pandemics.

Keep up to date with more news at ProperGaanda: What I learned about society when I lost weight

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