Wuhan Coronavirus, also known as 2019-nCoV

490 deaths, 24 324 confirmed cases worldwide

AI issued first outbreak alert on 31 December 2019

99% of the cases are in China, 97% of deaths are in Hubei province

The death toll from the deadly coronavirus outbreak that began in Wuhan, China has reached 490 as of 5 February. The Philippines recently became the first country outside of mainland China to confirm a death from the infection, with Hong Kong being the second. The total infections world wide rose from 20 438 to 24 324 in just one day. With health officials still struggling to get the virus under control, new technology may be able to help. Here’s how AI could help stop the spread of the coronavirus.



What is the coronavirus?

According to the World Health Organization (WHO), coronaviruses form part of a family of viruses that cause various illnesses, from the common cold to more serious illnesses like SARS and Middle East respiratory syndrome (MERS).



They’re originally transmitted between animals and humans. For example, SARS is believed to have been transmitted from bats to people, and MERS from camels to people.



A number of known coronaviruses are found in animals that haven’t infected humans.



The source of the 2019 Novel Coronavirus is still widely speculated, although it does share some similarities to the 2003 SARS virus which originated from bats. However, the seafood market in Wuhan, Hubei, is believed to be the original source. Scientists are analyzing various wildlife samples, so far it appears that the first transmission was made from animal to human, and the virus then spread through human-to-human contact.



(Map illustrating the world wide confirmed cases, all from individuals who traveled from China. Source: https://www.nytimes.com/interactive/2020/world/asia/china-wuhan-coronavirus-maps.html?auth=login-google. )

How could AI help?

Here’s how AI could help stop the spread of the coronavirus:



Technologies like AI (Artificial Intelligence) could assist in identifying and halting the spread of the 2019 Novel Coronavirus – and, in fact, they already have.



BlueDot, a venture-backed startup, has built an advanced AI platform that can process billions of pieces of data, like the world’s air travel network, that would assist in identifying outbreaks.



In the case of the coronavirus, BlueDot issued its first alert of 31 December 2019. This was even before the United States Centers for Disease Control and Prevention (CDC), made its own statement on 6 January 2020.



Kamran Khan is an infectious disease physician and professor of Medicine and Public Health at the University of Toronto. He was on the frontline as a healthcare worker during the SARS outbreak at the start of the century. As the mastermind behind BlueDot he said,



“We are currently using natural language processing (NLP) and machine learning (ML) to process vast amounts of unstructured text data, currently in 65 languages, to track outbreaks of over 100 different diseases, every 15 minutes around the clock.” He continued, “If we did this work manually, we would probably need over a hundred people to do it well. These data analytics enable health experts to focus their time and energy on how to respond to infectious disease risks, rather than spending their time and energy gathering and organizing information.”



Still, BlueDot won’t be the only company leveraging AI to stop the coronavirus. Here’s a taste of what else we might see from this incredible technology:



According to Colleen Greene, the GM of Healthcare at DataRobot:



“AI could predict the number of potential new cases by area and which types of populations will be at risk the most. This type of technology could be used to warn travelers so that vulnerable populations can wear proper medical masks while traveling.”



Assistant Professor of Computer Science at the University of New Haven, Vahid Behzadan:



“AI can help with the enhancement of optimization strategies. For instance, Dr. Marzieh Soltanolkottabi’s research is on the use of machine learning to evaluate and optimize strategies for social distancing (quarantine) between communities, cities, and countries to control the spread of epidemics. Also, my research group is collaborating with Dr. Soltanolkottabi in developing methods for enhancement of vaccination strategies leveraging recent advances in AI, particularly in reinforcement learning techniques.”



These are just three examples of many organizations leveraging AI at this critical point in modern medical history.

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Stopping the spread

Now that we’ve taken a look at how AI could help stop the spread of the coronavirus, it’s clear that international organizations need to start taking it seriously. BlueDot issued their first warning about the outbreak a full week before the US CDC – something which should come as now surprise, considering that they’re leveraging AI. Governments and health organizations need to take AI into consideration when it comes to tackling this disease, or risk facing even more casualties as a result of not using any resources that they can.