This website uses cookies.

We use cookies to personalise content and ads, to provide social media features and to analyse our traffic. We also share information about your use of our site with our social media, advertising and analytics partners who may combine it with other information that you’ve provided to them or that they’ve collected from your use of their services.

Welcome to History of Data Science. Discover the stories of heroes who transformed our daily lives!

BROUGHT TO YOU BY Dataiku Dataiku

xperiences-ico Xperiences
Applications / Applied Data Science Dataiku Favorite

The Role of Data Science During the COVID-19 Pandemic

4 min read
With a transmission rate greater than SARS or the common flu, COVID-19 quickly spread across the globe, requiring unprecedented efforts to limit its impact and propagation. At the heart of this ongoing battle, data science is playing a game-changing role.

In December 2019, the first outbreak of COVID-19 was detected in China, later spreading to every continent except Antarctica. Data science, along with statistical analysis, computer science, and computational biology, is driving applications from epidemiology to drug discovery and molecular design for therapeutic purposes. Data-driven, mathematical, and predictive models are providing insights into the spread of COVID-19, who is most at risk, and how to live with an endemic virus.

“I think the biggest innovations of the 21st century will be at the intersection of biology and technology. A new era is beginning.”
Steve Jobs

Predicting COVID-19 Trends and Hotspots

Determining where the next surge in coronavirus cases could happen is critical for governments and public health practitioners. For example, to get a real-time picture of how the virus is moving around the world, Johnson & Johnson built a global surveillance dashboard. Pulling in data at a country, state, and county level guided where they tested their investigational COVID-19 vaccine candidate.

Reducing Risk

Data also helps identify those most at risk, including what might make someone more prone to severe illness and how different treatment courses may affect patient outcomes. For example, machine learning has enabled us to accurately categorize, or predict, who is likely to be immune from COVID-19 and who is in the 20% at-risk group. Those predictions allowed health authorities to focus their efforts and increase the efficacy of public health interventions and policies.

Life Beyond the Pandemic

As many countries attempt to “learn to live with COVID-19” and get back on track, key decisions need to be made. These include when to return to the workplace. Data science enables companies to decide how many people can be on-site at a time and how facilities should be configured and sanitized.