How Would the Covid Pandemic Look in the Absence of Data Science?

Data Science

Data science along with the whole family of related technology including machine learning and artificial intelligence has been readily associated with a dreadful adjective – disruptive. While some people might accept ‘disruptive’ as a powerful reference to the paradigm-shifting powers of modern data-driven technology, most of us interpret it as a signifier of the threat that automation poses to the old world industrial order. 

Now, if that is quite enough of philosophic deliberation, let us get to the point – the Covid Pandemic could have grown to an apocalyptic measure with not much of the world even realizing what hit them (not saying it cannot assume an apocalyptic proportion from this point, but at least we will have a countdown).

Now that we have made a statement, it is time to defend it. Let us start with an old story and then we shall quickly jump right into the present. 

The Crimean War connection

I find it hard to talk about big data and healthcare without referring to this war that took place in the early 1850s solely because of a lady called Florence Nightingale. This nursing supervisor saved hundreds of lives and also changed the popular view about hygiene around the wounded patients for the better with her unique brand of data visualization. She created bar charts, honeycomb density plots, and coxcomb plots that made a terrific impact. This story is important to illustrate the inseparability of the two things – data analysis and healthcare. 

Understanding the pandemic

The most intriguing as well as the most dreadful thing about the Covid 19 virus is that it is stealthy. The number of asymptomatic careers is astoundingly high. This made it difficult for nations to comprehend the initial threat and some of them were not prepared for the real impact.

The socio-economic scene

An organization created an analytics system that could analyze social media posts from China in mid-January and compare them with the same from America in April. This paved the way for predicting the intensity of the spread and the concurrent social impact. 

The sudden hike in demand for essentials put the retail system off balance. All the predictive models created upon earlier data faltered due to the major paradigm shift in the market. Nevertheless, advanced analytics was used to augment warehouse management systems and most companies managed to deal with the situation. 

The struggle for containment

We have been getting daily updates about the numbers of victims in various affected areas. This would have been unthinkable in an era before big data analytics. More importantly, without these updates, it would have been impossible to take appropriate steps to contain the infection. 

Although there were little or no definitive symptoms that could indicate that a person might be infected with Covid – 19 in the beginning, we got hints and indications. There was also a constant effort from the WHO to contain all the misleading information about the pandemic. 

In the course of the last few months we have got applications powered by computer vision that can help control the crowd or detect people without masks. 

We have also had important breakthroughs in digital banking and remote learning. One could hardly think of these things in the absence of big data analytics. 

The biomedical frontier

It has not yet been a year since the pandemic hit and the words about vaccines are loud and abundant. This is quite astonishing if you consider the fact that vaccine development is usually a decade long procedure. Scientists have been tirelessly testing the possibility of curing or containing the virus with the drugs that we already have. This task has been tremendously accelerated by the use of machine learning. 

AI and machine learning have reduced the time consumed in protein structure testing manifolds. Moreover, these technologies have freed the scientists for more meaningful work through the automation of various repetitive tasks. 

From predicting the availability of beds in hospitals to narrowing down on possible modes of caregiving, data analytics has backed the professionals who have led from the front. 

The spirit of education

The academic cycle did not stop, it shook itself out of the short hiatus and started rolling on the wheels of technology. Video lessons, online assignments, remote assessments, it could have been a terrible mess. Nevertheless, the needs of the students, as well as teachers, were well judged by various service providers and many reliable systems were up and ready to take up the challenge. 

The spirit of acceptance shown by the teachers across the globe is inspiring and the digital footprint created by the whole effort is unprecedented. Concurrently the demand for data science education has grown by leaps and bounds. A big data course had never been so relevant. The data revolution coincided with the pandemic and we cannot complain about that.


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