How Can AI and Data Analytics Help Predict the Outbreak of nCoV?

by | Published on Feb 20, 2020 | Business Process Outsourcing

AI and Data Analytics Help Predict the Outbreak of nCoV

The outbreak of a novel Coronavirus (nCoV) in the city of Wuhan in China’s Hubei Province has been all over the global news for the last couple of weeks. A dedicated hospital sprang up in just eight days, the stock market took a hit, and travel restrictions were imposed. As the outbreak continued to spread and represented a risk outside China, on January 31, 2020, the World Health Organization (WHO) declared the new coronavirus as a global emergency. However, two weeks before the WHO alerted the public about the nCoV outbreak, a Canadian Artificial Intelligence (AI) company – BlueDot was already sounding the alarm. The company used AI-powered algorithms to analyze information from a multitude of sources to identify disease outbreaks and forecast how they may spread. On December 31st 2019, the company sent out a warning to its customers to avoid Wuhan, where the virus originated. While the possibility of a global pandemic is real, people can take some solace in the fact that public health officials have at their disposal an array of powerful data collection and analytics techniques that previous generations lacked. AI and Big Data are driving various new technological innovations and will impact the future of digital transformation. Digitization and automation of services offer multiple opportunities to increase efficiency and stay competitive. To undergo digitization, the support of data entry companies is indispensable to convert data into digital format and ensure accuracy.

The current death toll of nCoV stands at over 1500 people with those infected estimated at about 60,000 people. More than 25 countries have reported the coronavirus with evacuations taking place to protect foreign nationals from infections. Outside China, only Japan, HongKong and Philippines have reported deaths. With the WHO declaring the nCoV as a global pandemic and quarantine efforts and shutdowns happening everywhere from airports to businesses and transport, the Chinese people are suffering, and they need global support.

AI and Data Analytics – A Powerful Tool to Prevent Global Disease Outbreak

Artificial intelligence and predictive data analytics have become powerful tools for combating deadly disease outbreaks like nCoV. However, 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, AI is becoming a useful tool in efforts to monitor and respond to the crisis, according to health data specialists.

In prior outbreaks, the Artificial Intelligence (AI) technology offered limited value due to the shortage of data required to provide updates quickly. But in recent times, the field has evolved dramatically with AI being used to analyze data from government reports, social media, news sites, and other sources thereby allowing algorithms to generate near-real-time information for public health officials tracking the spread of the disease.

The spread of a given virus is partly linked to how long it remains undetected. Identifying a new virus is the first step towards mobilizing a response. Warning at-risk populations as quickly as possible also helps with limiting the spread. This is the point where BlueDot’s achievement is crucial as it illustrates how AI tools can sift through vast troves of data to identify ongoing virus outbreaks.

Natural Language Processing (NLP) and machine learning are important tools that were used by BlueDot to scour a variety of information sources (including chomping through 100,000 news reports in 65 languages a day). Machine learning algorithms offer updated information about possible disease occurrences. Data is compared with flight records to help predict virus outbreak patterns. Once the automated data sifting is completed, epidemiologists check whether the findings make sense from a scientific standpoint. However, AI technology saves valuable time and resources by empowering health professionals with information on prevention measures. Often, disease prevention poses threats compared to predicting and thanks to the machine learning tools, health specialists can focus on patient safety.

Apart from BlueDot, other companies are also using data-driven approaches to track the spread of the likes of the coronavirus. “Insilico Medicine” is another start-up based in Maryland, USA, focused on using analytics in disease prevention. They are currently developing technology that will inform physicians about molecules capable of fighting against the coronavirus. On the other hand, “Harvard Medical School” is leading efforts to find solutions for the nCoV by using machine learning technology to review data and information from various sources, including patient records, social media and public health data. With the NLP technology, researchers can search online information about the coronavirus and understand the current location of the outbreak. “The University of Southampton” is also undertaking research efforts in the current coronavirus outbreak with the institution using AI technology to model data from search engines to map the outbreak. All these machine learning and AI technologies have assisted researchers to predict the virus, its structure and its spreading methods in real time. Others are using AI algorithms to identify how preventive measures can have the greatest effect. AI is also being used to create new drugs, which we may well see repeated for the coronavirus.

Role of Geographic Information Systems (GIS) Technology

The GIS (Geographic Information System) technology has become another important tool to stop the spread of the coronavirus, with the John Hopkins University leading the way in this area. For instance, the institution has a dashboard that shows all cases of coronavirus around the world. Data mining services are crucial for GIS technology to work. Social media sites are good information sources for GIS as the technology can easily map the area of interest where people are talking about the coronavirus. Accordingly, prevention measures can be implemented as the technology can track both the location and the spread of a disease. With AI, machine learning and GIS, data mining and processing is both easier and powerful at locating viruses. The bottom line is – prevention response time is quicker today.

Artificial intelligence tops the chart of technologies used by China to handle the coronavirus outbreak. In fact, technology companies in China are constantly developing applications to help people confirm their movements during the period of the outbreak as a safety measure and to avoid further spread. For instance, data from trains is a typical example of passenger screening where applications check the movement and contact of people. Secondly, tech companies in China are analyzing passenger flight information (like cases such as in Guangzhou where AI robots are reminding people to wear masks for disease prevention). These initiatives reveal the various, novel technological solutions incorporated by China in the midst of this crisis.

Today, more and more companies are investing in Big Data and AI initiatives to increase productivity, efficiency, and performance. Artificial Intelligence (AI), data analytics and machine learning technologies play a prominent role in addressing the new Coronavirus (nCoV) outbreak. Reports from the WHO suggest that the situation is stabilizing despite new infections being reported and death tolls still increasing. To reap the full range of benefits of these technologies, companies need carefully devise an enterprise-level strategy to implement AI in such a way that it offers more than just customer experience. The Chinese government in collaboration with the WHO and other governments across the globe are working round the clock by incorporating advanced technology to combat the outbreak. Not only will it improve the overall customer experience, but can also provide valuable savings by reducing labor costs, identifying fraud, and managing risk. Error-free data entry services along with AI, data analytics and other machine learning technologies can help consolidate data, reduce the total expenses, and substantially reduce fraud.

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