Covid-19’s rapid global spread has brought forward advanced Big Data Analytics tools at the front and center, with entities from all healthcare industry sectors seeking to monitor and reduce the impact of this virus. Researchers and developers increasingly use artificial intelligence, machine learning, and natural language processing to track and contain coronavirus and gain a more comprehensive understanding of the disease. Researchers have been hard at work in the months since Covid-19 hit the world trying to unseal the nature of the virus – why it affects some people more, what measures can help reduce the spread, and where the disease is likely to go next. At the heart of these efforts is very familiar to the healthcare industry: Big data. Want to make a Big Data career and do not know where to begin? Join a big data certification course or big data training today.
Table of Contents
- How does Big Data help in the Covid-19 fight?
- Big data role in COVID-19 aid
- Conclusion
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In this article, we know more about the collaboration seek of Big Data to fight Covid-19.
How does Big Data help in the Covid-19 fight?
The swift spread and impact of Covid-19 have made people around the world feel helpless, frightened, and frustrated. However, the news and discoveries over the cure and use of modern data-backed technology now and then make them feel safe and hopeful in the tragic ‘pandemic’ time. Here is how Big Data helps fight Covid-19:
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Detection
The role of big data in Covid-19 help starts from the first step – detection. In December 2019, Toronto-based big data startup BluDot found some unusual pneumonia cases in Wuhan, China. They did it by using their algorithm of big data that pulled data from a variety of sources. To predict the rise of an illness, the algorithm analyzed data from health records, airline ticketing data, news reports, government notices, and disease networks.
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Analyzing COVID-19 Spread
BluDot has been able to predict the spread of Covid-19 from Wuhan to other Asian cities using the airline ticketing data. In addition to this, mobile phone data is also used to track where the virus could spread. Big data tools can analyze data on illnesses and information about senior citizens at risk of contracting coronavirus. The algorithms and tools can track such people down to the postcode level, considering factors such as obesity or diabetes. These reports of analysis will suggest health centers and hospitals where additional medical facilities such as beds are needed. Big data experts are working on mobile applications that will be used to trace contacts. People can be signaled if they have been bared to the virus by using the location data on their smartphones. A team at the University of Southern Illinois (SIU) has developed a data visualization tool that uses GPS data to alert users about Covid-19 cases.
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Virus tracking dashboards
Big data role is becoming more evident in Covid-19 aid as organizations like WHO, CDC, and Microsoft are creating dashboards based on it. Such dashboards draw data from various countries, showing confirmed cases, deaths, and locations. The dashboards can be used to prepare Big Data Model datasets. The models can predict potential hotspots and warn healthcare authorities. The outbreak analytics is another critical big data process used against Covid-19. This deals with gathering and analyzing data on the outbreak response. Data including deaths, confirmed cases, tracing patients contacted by infected patients, population densities, and much more are used to develop disease data models. These models can predict high rates of infection and their impact.
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Handling risks
Big data can play a fundamental role in analyzing patient screening data and connecting it to the hospital’s unnamed health problems. The results of this analysis will support the identification of key risk factors. So, as more and more data is being fed into big data programs and tools, risk prediction accuracy will increase. Google’s artificial intelligence system, DeepMind, uses big data to understand the virus by analyzing its features. This will help the doctors develop plans for drugs and treatment.
Big data role in COVID-19 aid
The more we understand this virus and discover it, the higher the chances of its defeat. Big Data plays a role in:
- Helping governments prevent and fight future outbreaks once this global pandemic is resolved.
- The data from this outbreak may be used to test scenarios and analyze their outcomes to make future vital decisions.
- Enabling early detection of future diseases by identifying potential patients and performing productive and active clinical trials is due to the faster and near-real-time evaluation of data-based decision-making.
- During the COVID-19 crisis, because of its ability to process video, audio, and other types of non-standard information in ways that structured data processing can not, we have seen big data play an essential role as an enabler.
- The best Big Data apps are those that unlock both structured and unstructured data values. In combating COVID-19, devices such as thermometers and contact tracers can be coupled with statistical data to track virus outbreaks to mitigate the outbreaks. To produce these comprehensive COVID-19 tracking and detection engines, big data experts must select the best data sources to integrate and aggregate so that they can create a composite picture of what is happening. Big data toolsets allow it to do so.
- There are at least 78 vaccine projects underway around the world with COVID-19. Without the assistance of the big data processing, none of these vaccine formulations and trials could occur. This squarely positions the processing of big data as a mission-critical application, which is indispensable to developing a vaccine that can finish the pandemic.
Conclusion
Big Data is an asset that helps to forecast and understand coronavirus reach and impact. Healthcare workers, scientists, epidemiologists, and policy-makers are employed to regularly and globally aggregate and synthesize incident data. Big data will play an essential role in analyzing global data on detected viruses, patterning disease, tracking human activity, and visualizing it in the coming years. Data scientists will have a better shot to prevent such outbreaks as more and more data piles up into massive datasets.
