In the wake of the COVID-19 pandemic, the coronavirus impacted heavily on all aspects of human life, and technology is coming to the rescue to mitigate the impact and underpin public health policies.
Big data alerted about the outbreak: in December 2019, the startup BlueDot, a native of Canada, warned his customers (companies, hospitals, governments) that in the city of Wuhan, China, was developing a rare infectious epidemic. This happened even before China informed the World Health Organization (WHO), and before the organization alerted the planet, which finally happened in January.
How did BlueDot do it? Their artificial intelligence (AI) -based algorithms tracked and processed a massive body of data received from social media posts, and noted that many Wuhan residents said they had a fever, coughed, and felt bad. They also released official reports, news in different languages, blogs, etc. And then, based on information about the flow of airfare, the Canadian firm also anticipated where the outbreak would be going, and when it would impact each location.
Track and prevent
Today, during the pandemic, artificial intelligence (AI), machine learning, big data, and data analytics are used to track and isolate cases. How? Using data from different sources, big data, analytical technology solutions, and services can track population movement and contact, quickly detect sources, and help prevent contagion.
For example, mobile phone data is crossed with information on the evolution of infected people.
In this way, it is possible to establish who was closed and warn them that they probably are infected. Also, to identify the geographical areas with the highest degree of exposure. The information is consolidated and analyzed in real-time: this allows us to immediately determine the infected people and the potential reasons for infection.
The analyzes of measures of epidemiological and scientific data that are carried out today would not have been possible 10 years ago. Today it operates in real-time for the combination of data science tools, analytical databases, and the Cloud, which allows developing exhaustive forecasts.
The case of China became controversial for its well-known surveillance system, which has few considerations regarding data privacy. Facial recognition technologies, smart helmets, and thermal scanners are using at train stations to identify high body temperatures. Besides, mobile phone data is used to follow user movements for 14 days.
The government created an app in which citizens had to fill out a report daily with data such as the places they had visited, who they had been with, and their body temperature.
After processing that information, they have assigned a QR code. Those who received green could move freely, those who received yellow reached the risk areas and implied being 7 days isolated, and red required quarantine.
Beyond discussions around information privacy in other Western countries, such as Argentina, the USA, and Italy, big data and analytics and mobile data are also being used to support the tracking of contacts and generate early alerts.
Control panels from entities such as the WHO are also being used, which provide real-time statistics and data that can be used to create models and predict critical points.
In summary, big data and analytics are being used to:
√ Predict the impact of the coronavirus in granular regions.
√ Predict the demand that hospitals will have.
√ Predict probable mortality rates and timing.
√ Forecast the financial impacts of the crisis.
√ Track the population view as the virus spreads.
At Accion Point, through our R + D + I area, we are actively working with big data, machine learning, and AI developments. Our developments capture, manage, and analyze data sets whose volume and complexity prevents processing using conventional tools and technologies.
The power of big data is turning out to be the key to anticipate the flow and the future of the current coronavirus pandemic.
These technologies implemented together, provide helpful information for a determination at these uncertain times when it is important to take care of public health.
Big data, machine learning algorithms (which help automate analysis tasks), and analytics techniques are proving to be key to predicting the flow and future of the current pandemic.
They provide valuable information for decision-making at these unstable times when it is necessary to take care of public health.
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