According to Forbes, along with being one of the most deadly viruses on the planet, COVID-19, also referred to as the novel coronavirus, is also one of the most contagious diseases currently on Earth. The virus, which has spread to more than 198 countries, infected over two million people and taken over 150,000 lives according to John Hopkins University.
The discussion of how companies can best help reduce the spread of the coronavirus has become a worldwide question. For many companies, especially those involved in the Tech Sector, are working to help stop the spread. Some of the companies, who are centered around Artificial Intelligence, are working with technology to produce products that help disinfect hospitals and help disinfect areas in cities.
In a discussion about an upcoming virtual conference at Stanford regarding AI and its function to combat the coronavirus, Russ Altman, a Stanford associate director of Human-Centered Artificial Intelligence and professor of bioengineering, genetics, medicine, and biomedical data science, addressed the effects of the virus.
“AI is extremely good at finding patterns across multiple data types,” Altman said. “For example, we’re now able to analyze patterns of human response to the pressures of the pandemic as measured through sentiments on social media, and even patterns in geospatial data to see where social distancing may and may not be working.”
Altman also said AI can prevent further spread of the virus.
“The availability of molecular, cellular and genomic data, patient and hospital data, population data — all of that can be harnessed for insight,” Altman said. “We’ve always examined these data sources through more traditional methods. But now for the first time, and at a critical time of global crisis, we have the ability to use AI to look deeper into data and see patterns that were otherwise not visible previously, including the social and cultural impact of this pandemic.”
Rep. Ami Bera, who represents much of Sacramento County, addresses the different efforts that are being taken to reduce the spread of the virus which includes looking into Big Data and other technological applications.
In response to the COVID-19 outbreak, Bera said further testing implementation such as serological testing, which analyzes whether an individual is immune to the disease, will help reduce the risk of spread.
“The first thing and first tool that we really need is serologic testing,” Bera said. “From that perspective, I think Stanford has the serological (tests to see whether one has had a virus) and others so we have to test available (diagnostic). We are now working with the commercial sector and making sure the funding is there to massively ramp up serologic testing and why that’s important.”
With regard to serological testing, Bera said AI and Big Data will help to sort out these numbers.
“Massive serological (testing), I think this is where having the ability to use big data to sort through a lot of that and get a sense of, what is the level of immunity not just in one particular part of the country, but all across this country a second,” Bera said. “So that’s going to be very important in helping guidance (stop spread of virus).”
In addition to testing, Bera said Big Data will be used to sort out large data taken from individual thermometers, testing whether an individual has a fever, and later the data will be used to better understand the distribution of the virus.
“The last thing we’ve talked about is distributing thermometers to every American as we start to reopen (the country), training them to check their own temperatures,” Bera said. “That’s going to be a big data set as well … new clusters pop up, it could give us some information on how to move forward.”
One company working to help stop the spread of the novel virus has launched a platform to track the virus, called BlueDot. BlueDot uses an AI platform that tracks infectious diseases around the world. By using natural language processing and machine learning algorithms, it analyzes information from hundreds of sources of early signs of an infectious disease or virus. With different data points, the company is able to forecast how the virus will spread across the world.
“AI detected the coronavirus long before the world’s population really knew what it was,” Chandler said. “On Dec. 31, a Toronto-based startup called BlueDot identified the outbreak in Wuhan, several hours after the first cases were diagnosed by local authorities.”
The faster that companies are able to understand the spread of the virus, the more like the virus will stop spreading. For the BlueDot team, tracking the virus was a quick process according to Forbes.
“The BlueDot team confirmed the info its system had relayed and informed their clients that very day, nearly a week before Chinese and international health organizations made official announcements,” Chandler said.
According to healthcare professionals, one of the best ways to stop the initial spread of the virus is to reduce contact between patients and individuals who have not been exposed. To further increase social distancing, many companies and organizations used robots to check people for symptoms of the virus and dispense hand sanitizer to people.
UVD Robots, a company based in Denmark, uses this model. Especially in areas such as hospitals, UVD robots help to prevent the spread of the virus. According to Hjortshøj, the goal of the robots is to make healthcare environments safer and improve the quality of care for healthcare facilities around the world.
Cornelia Hjortshøj, a marketing and sales support assistant at UVD Robots ApS, said UVD Robots are working to deliver as many robots as possible.
“Right now, the robot is working in more than 40 countries spread across Europe, Asia, and the U.S.,” Hjortshøj said. “Our autonomous robot can disinfect and kill viruses and bacteria with ultraviolet light, thus, the robot can help to limit the spread of coronavirus without exposing the hospital staff to the risk of infection. The UVD robot strikes 99.99%of the bacteria in a treated area to death, and that includes the air in the room.”
Hjortshøj also said the spread of infections and COVID-19 is affecting many hospitals around the world, including healthcare workers, which is a growing problem that needs to be addressed.
“The risk of infection in hospitals with patients who have COVID-19 is very high,” Hjortshøj said. “In addition, the HAIs result in significant extra costs for hospitals due to extra days in bed, readmissions, and reduced operational efficiency. With the huge pressure on the hospitals at this moment, the UVD Robot helps to streamline workflow in hospitals, while at the most important of all, creating a safer environment.”
Additionally, Hjortshøj said the UVD robots are used for multiple purposes including the regular cleaning cycle (day-to-day basis cleaning in hospitals).
“The UVD Robot is used as part of reducing harmful organic microorganisms in the environment by breaking down their DNA structure,” Hjortshøj said. “We are now helping solve one of the biggest problems of our time, preventing the spread of bacteria and viruses with a robot that saves lives in hospitals every day.”
Associate professor of medicine and biomedical data science at Stanford University, Nigam Shah is working along with many other professors to help find patterns in data and help reduce the spread of the virus.
Shah said that the is current basis of his projects includes looking at patterns in hospitalization data. This kind of data includes, how many patients at each hospital, how many on respirators, etc.
“Our suggestion is to use hospitalization data from your local region for the health system, you’ll be much better off in your capacity planning,” Shah said. “But California has been amongst the most forward-looking and amazingly efficient in responding to the situation. New hospital bed and resource use projection and this allows you to do your county-level or regional hospitalization predictions”
Shah also said a variety of data, such as case rates and hospitalizations, needs to be analyzed in order to make the best decisions about how to best stop the spread of the virus.
“For the kinds of things we’re monitoring, as an institution, this is sort of our situational awareness,” Shah said. “We’re looking at the neighboring counties, we’re looking at case rates, hospitalization. How is the number of new cases changing over time? And all of this feeds into our modeling efforts that then inform our hospital and our neighboring counties. How should we think about this situation and be prepared?”
In the Palo Alto community, Computer science teacher Christopher Kuszmaul addresses his opinion on the technological applications being used to stop coronavirus.
Kuzmaul also said that he is unsure of how specifically Artificial intelligence is going to help, but certain data will be helpful in certain situations.
“I doubt that machine learning specifically will make much of an impact on COVID-19 because the processes that it would assist are not a part of anything I am aware of that would make a difference,” Kuszmaul said. “I suppose that there may be a social manipulation component that machine learning could do, such as having the capacity through machine learning to survey the population to detect people likely to have the virus.”