The mysterious coronavirus is spreading at an alarming rate. There have been at least 305 deaths as more than 14,300 persons have been infected.
In the case of the virus outbreak, the AI algorithm reportedly used airline ticketing information to accurately predict the virus' rapid spread from Wuhan to other parts of the world.
Millions of posts about coronavirus on social media and news sites are allowing algorithms to generate near-real-time information for public health officials.
On 30 Jan 2020, the World Health Organization declared the . According to a BBC News report, the death toll from the outbreak in China has reached above 300 and a confirmed case in Tibet means the virus has reached every region in mainland China.
Many countries are working hard to quell the virus. There have been quarantines, lock-downs on major cities, limits on travel and accelerated research on vaccine development. Technologies like AI are helping out to identify outbreaks. Here is how AI is becoming a useful tool to spot an early coronavirus outbreak.
more and more withthe advancement in technology. It is not going to stop the new coronavirus or replace the role of expert epidemiologists. But for the first time in a global outbreak, it is becoming a useful tool in efforts to monitor and respond to the crisis, according to health data specialists.And how it is doing that? Millions of posts about coronavirus on social media and news sites are allowing algorithms to generate near-real-time information for public health officials tracking its spread.
“The field has evolved dramatically,” said John Brownstein who is a computational epidemiologist at Boston Children’s Hospital who operates a public health surveillance site called healthmap.org that uses AI to analyze data from government reports, social media, news sites, and other sources.
“During SARS, there was not a huge amount of information coming out of China,” he said, referring to a that emerged from China, infecting more than 8,000 people and killing nearly 800. ”Now, we’re constantly mining news and social media.”
A key challenge in combating contagious diseases is limiting the spread of the virus within a hospital. Cross infection from patient-to-patient and patient-to-caregiver can be a major problem. While quarantining patients may limit contact between patient-to-patient or caregivers and patients can also be avoided with technology.
Technology is giving ways to minimize the effect of virus spread with every possible method. VivaLNK, a Santa Clara, California-based connected health start-up, recently announced that Shanghai Public Health Clinical Center (SPHCC) is using the start-up’s continuous temperature sensor to combat the spread of coronavirus in China. Instead of physically checking the patient temperature every hour with a thermometer, the temperature can be measured and monitored remotely and automatically, thereby limiting the patient to caregiver contact.
“The world will never be rid of diseases, but more effective methods of prevention and treatment can be achieved through technological advances."
Jiang Li, CEO, VivaLNK.
Kamran Khan, an infectious disease physician and BlueDot’s founder and CEO explained in an interview , including natural-language processing and machine learning, to track over 100 infectious diseases by analyzing about 100,000 articles in 65 languages every day. That data helps the company know when to notify its clients about the potential presence and spread of an infectious disease.
Other data, like traveler itinerary information and flight paths, can help give the company additional hints about how a disease will likely spread. For instance, earlier this month, BlueDot researchers predicted other cities in Asia where the coronavirus would show up after it appeared in mainland China.
The idea behind BlueDot’s model 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 as early as possible.
Khan added that his system can also 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.He points out that, back in 2016, in Florida six months before it showed up there.
Similarly, the epidemic-monitoring company Metabiota determined that Thailand, South Korea, Japan, and Taiwan had the highest risk of seeing the virus show up more than a week before cases in those countries were reported, partially by looking to flight data. Metabiota, like BlueDot, uses natural-language processing to evaluate online reports about a potential disease, and it’s also working on developing the same technology for social media data.
“Machine learning is very good at identifying patterns in the data, such as risk factors that might identify zip codes or cohorts of people that are connected to the virus."
Don Woodlock, vice president of InterSystems
Artificial intelligence can be far more useful than just keeping epidemiologists and officials informed as a disease pops up. Researchers have built AI-based which can inform how doctors respond to potential crises. Artificial intelligence could also be used to guide how public health officials distribute resources during a crisis. In effect, .
More broadly, .Some AI surveillance tools have been available in public health for more than a decade, but the with greater data availability, are making them mu , combinedch more powerful. They are also enabling uses that stretch beyond baseline surveillance, to help officials more accurately predict how far and how fast outbreaks will spread, and which types of people are most likely to be affected.
Advancements in AI represent a more optimistic outlook of what AI can do. The idea of AI battling deadly disease offers a case where we might feel slightly less uneasy, if not altogether hopeful. Perhaps this technology if developed and used properly could help save some lives.