On January 9, the World Health Organization notified the public of an influenza-like outbreak in China: Wuhan City reported a series of pneumonia cases, which may have been caused by street vendors’ contact with live animals in the South China seafood market. The US Centers for Disease Control and Prevention announced the news a few days ago on January 6, but Canada’s health monitoring platform defeated both of them on December 31. The epidemic was sent to its customers.
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It is understood that BlueDot uses AI-driven algorithms to search foreign language news reports, animal and plant disease networks and official announcements to issue early warnings to its customers to avoid dangerous areas like Wuhan.
Speed during an outbreak is critical, and public health officials at WHO and the CDC must rely on these identical health officials for disease surveillance. So maybe AI can get there faster. BlueDot’s founder and CEO, Kamran Khan, said: “We know that it may not be possible to rely entirely on timely government information.” “We can gather news, rumors, forums or blogs about possible outbreaks to show that something unusual has happened event.”
Khan said the algorithm doesn’t use social media to post content because the data is too messy. But he does have a trick: access to global air ticket data can help predict the next whereabouts and time of infected residents-it correctly predicts that the virus will jump from Wuhan to Bangkok, Seoul, Taipei and Tokyo.
Khan worked as a hospital infectious disease specialist in Toronto during the SARS epidemic in 2003. He dreamed of finding a better way to track the disease. The virus started in China, then spread to Hong Kong and then to Toronto, killing 44 people.
When talking about today ’s coronavirus outbreak, he said, “It looks a bit familiar now.” “In 2003, I saw the virus sweeping across the city and paralyzing hospitals. Both mentally and physically tired, I thought,“ Let ’s Don’t do it again. “
After testing several predictive plans, Khan launched BlueDot in 2014 and raised $ 9.4 million in venture capital funding. The company now has 40 employees who are doctors and programmers who design disease surveillance analysis programs that use natural language processing and machine learning to screen news reports in 65 languages, as well as airline data and reports of animal disease outbreaks .
“What we do is train the engine using natural language processing and machine learning to identify whether this is an anthrax outbreak in Mongolia or a reunion of the heavy metal band anthrax,” Khan said.
Khan said that once automated data screening is complete, manual analysis will take over. Epidemiologists check the conclusions from a scientific perspective and send the reports to governments, businesses and public health customers. BlueDot then sent the reports to public health officials in dozens of countries (including the United States and Canada), airlines, and first-line hospitals that could eventually infect patients. Khan said BlueDot is not currently selling its data to the general public, but they are working on it.
The company is not the first to look for opportunities around public health officials, but they hope to do better than Google Flu Trends, which was “euthanized” after underestimating the severity of the 2013 flu season by 140%. BlueDot successfully predicted the location of the Zika outbreak in South Florida in the British medical journal The Lancet.
Whether BlueDot proves successful this time remains to be seen. But at the same time, some public health experts say that Chinese officials have responded more quickly this time than SARS in 2002.
James Lawler, an infectious disease specialist at the University of Nebraska Medical Center, said: “The outbreak may be much larger than the one confirmed by public health officials. He has treated isolated Ebola patients in 2017 and 2018. “From a rough calculation of the number of visitors from China in the past week, and the percentage that may be affected, there are many more. “
Lawler and others say the coronavirus outbreak will continue to spread as travellers from China to other countries become infected. “We still don’t know how many people will get sick and how many people will die before the epidemic subsides.”
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To stop the spread of disease, public health officials need to respond quickly, and at the same time, it may be worth entrusting some tasks to AI-driven epidemiologists.