It’s no secret that we are currently dealing with a global crisis. COVID-19, which emerged in January 2020, has now caused over 70,000 deaths and over 1.2 million infections worldwide. At the heart of the COVID-19 crisis is big data, as everyone looks to the daily tallies across different countries to look for signs of recovery.
Gary Maziarz of Denver, Colorado, is an IT business manager with several years of experience. He believes that big data has the power to combat coronavirus by providing us all with valuable insights.
What is Big Data?
As the name suggests, big data is the collection of a large set of data that grows exponentially with time.
This data is so complex that it is not possible to perform proper analysis through traditional data management tools. Big data has emerged along with advancements in technology, allowing data to be stored in large quantities and available to the wider public, says Gary Maziarz. Examples of big data include the stock market and social media.
Big data is vital to today’s society, as we can use it to determine many upcoming issues or failures. Many companies use big data to improve operations and efficiencies, but it can be applied beyond traditional purposes.
Big Data and Coronavirus
With many past pandemics, big data was not available to aid medical researchers and the public with information. The “Black Death” of the mid 1300s killed around half of the U.K.’s population. The Spanish Flu infected about one-third of the world’s population and killed between 20 to 50 million. Aside from not having the proper medicine to treat or prevent these illnesses, there was no data to analyze in order to determine potential causes or risk factors for individuals. Today, says Gary Maziarz, Coronavirus is putting big data to the test.
Health and technology experts alike are hard at work, analyzing data as it relates to the coronavirus to identify epicenters, track the spread of the disease, and accelerate the human response. In fact, big data is what first led to the discovery of the illness. On January 30, 2020, BlueDot, an artificial intelligence software company in Canada, uncovered a cluster of “unusual pneumonia cases,” in Wuhan, China. This was nine days before the World Health Organization alerted the world to the emergence of COVID-19.
Since then, big data has been used to track the spread, and it is currently being used to predict the curve.
How is Big Data Aiding in the Fight Against Coronavirus?
Data analysis and AI are helping governments and medical professionals alike to understand more about COVID-19. For example, according to reports, Taiwan used data analytics to perform a detailed mapping to determine the exact points of transmission of the virus and was able to stop further transmission early on. Taiwan’s immigration and customs database enabled the government to track the 14-day travel histories and symptoms of citizens. Officials used IT to estimate the region’s supply of masks, negative pressure isolation rooms, and other health supplies. This is just one example of using big data to control the spread of Coronavirus.
Around the world, big data is being used to create projections of the disease to estimate the amounts of total infections, deaths, and the approximate length of the threat, notes Gary Maziarz. The data is also being used to identify the most vulnerable communities. More analysis is being conducted every day, and as a result, we understand a lot more about the illness than we did when it first emerged.
Gary Maziarz Looks to the Numbers
When it comes to COVID-19 and many other health crises and situations, the proof is in the numbers. We will know when the risk of the disease has passed when the numbers show us, says Gary Maziarz. The truth is, we all look at big data without even realizing it. These numbers of new infections and deaths we look at every day reveal estimations of when we may have hit our peak.
Furthermore, when the crisis is over, we will have a final set of data that will be used in history books. We will be able to see if estimates that were made throughout the crisis were accurate or if they were way off base. And hopefully, we will be able to use the data to prevent future outbreaks of this scale by applying newer and more sophisticated data models.
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