COVID-19 & Statistics

Data science is everywhere in our lives; however, it is particularly apparent during quarantine. It seems like everywhere we go, we see "x% of Americans have COVID or are asymptomatic." The pandemic, although it has caused many problems, has created an opportunity for data science to prove its worth. Ever since a nationwide quarantine was implemented, data sets on COVID statistics were displayed everywhere. Websites and companies have hosted competitions to see if meaningful information can be extracted from data sets. Anyone can access the data sets, in fact all it takes is a Google search. Personally, I have never seen such transparency with data. I have always seen companies hiding their data, as it is often considered confidential. Thankfully, it seems like everyone is collaborating in trying to find meaningful COVID trends.

None of the COVID-19 statistics displayed today would be here without data science. As a result of data science innovations such as cloud computing, big data, machine learning, predictive modeling, etc. we can predict many facets of COVID-19 and people at risk. Models can factor in the slightest changes, such as whether or not you go for a walk, and then output meaningful information. In fact, MIT made a artificial intelligence model that was trained to predict whether or not someone has COVID-19 based on the way they cough, and it accurately predicted 98.5% of the confirmed cases. We can use these models and others to predict the curve, and consequently determine the resources needed to flatten it. Without statistics, hospitals would have been more overwhelmed than they are currently, data science has provided us a front against COVID.

The use of data science during the COVID-19 pandemic will definitely inspire many to pursue a career in data science. In addition, it will help the government see the usefulness of data science, and likely further the field as a whole. The data science innovations created during the pandemic, such as machine learning models and neural networks can be applied if anything like this ever happens again. In addition, they can be adapted to different diseases around the world. Furthermore, some of the predictive modeling used to predict COVID cases can be adapted to other world problems, such as ocean acidification. All in all, the use of data science during the pandemic will help to educate the public on COVID-19 and also expand the field for further applications.

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