Fighting the Spread of Coronavirus with Artificial Intelligence

fighing-the-spread-of-coronavirus-with-artificial-intelligence

While the spread of the coronavirus may have been inevitable, modern technology has certainly added to the challenge. For example, inexpensive air, vehicle, and rail travel has allowed infected people to spread the virus far beyond its genesis in Wuhan, China. The use of social media is allowing unfounded rumors around the cause, prevention techniques, and likely impact of the virus to flourish. And even the traditional news media’s 24/7 coverage of the virus is, in some cases, adding to the hysteria surrounding the outbreak.

However, artificial intelligence (AI) technology, in particular, is being used to aid governments, researchers, and health organizations that wish to contain the spread of the virus. From early warning and detection algorithms to big data-based analyses of patient travel histories and the eventual creation and development of a coronavirus vaccine, AI likely will be a key enabling technology.

Detecting and Tracking the Virus

For example, reports surfaced that BlueDot, a Canada-based health monitoring platform, had actually identified and pinpointed the outbreak of coronavirus on December 31, 5 days prior to the official warning from the U.S. Centers for Disease Control and Prevention. BlueDot’s algorithm uses natural language processing (NLP) and machine learning (ML) techniques to analyze news reports in 65 languages, along with airline flight data and reports of animal disease outbreaks. By sifting through these reports, the system was able to identify where and when infected residents were likely to travel, and it correctly predicted that the virus would jump from Wuhan to Bangkok, Seoul, Taipei, and Tokyo.

AI is also being deployed to help screen travelers for potential coronavirus exposure. The Malaysian e-government services firm MY EG Services Berhad, along with Chinese travel firm Phoenix Travel Worldwide, is deploying an AI-based coronavirus risk profiling solution that will be used on Chinese visitors to Malaysia and the Philippines. This solution is capable of incorporating historical geolocation and anomaly tracking. The ML algorithm is powered by a number of data points (previous known locations, heart rate, blood pressure, etc.) that can be cross-referenced with public transport ridership, as well as exposure to locations where there have been instances of infections, to determine whether they may have been exposed to or are at risk of having the coronavirus.

Developing a Treatment Plan

Beyond tracking the virus, AI is being used to help develop a vaccine or cure. Insilico Medicine is a Rockville, Maryland-based company that is developing technology designed to inform doctors about molecules capable of fighting against the coronavirus. The technology uses ML to analyze the properties of specific molecules and how they may interact with the virus, and it is designed to provide feedback on those suited to counter the coronavirus.

Enabling Communications and Coordinated Responses: Smart Cities

Smart cities are also expected to be active in using AI to address not only the coronavirus outbreak, but also future pandemics or emergencies. The development of faster and more robust communications networks, such as 5G, is integral to the deployment and use of technology that can be used to monitor and treat virus outbreaks. Examples include active monitoring of and communications among patients that are being held under quarantine, as well as tracking the movement of people within the city or around the globe. AI can also be used to predict where demand for emergency teams are needed, and then automatically coordinate a response, taking into account labor schedules, material stockpiles, and expertise.

These types of coordinated responses are being enabled by the increasing use of AI within smart cities. While many of the technologies are in testing or limited deployment now, the successes of AI technology being used to track the coronavirus may help city governments underscore the demand for AI-driven systems. Such systems can often respond to situations more quickly and efficiently than solutions that solely rely on humans.

Omdia|Tractica discusses these issues in our Artificial Intelligence Applications for Smart Cities report, which provides a quantitative assessment of the market opportunity for smart city AI applications. The study includes analyses of 23 AI use cases distributed across six industry sectors: governance, safety & security, mobility & transportation, energy & resource management, infrastructure management, and healthcare.

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