In February 2020, South Korea announced thousands of coronavirus cases in the space of only a few days, an outbreak that initially pushed South Korea’s tally of confirmed cases much higher than anywhere else outside of China.
Reuters manually combed through daily government press releases to build a data-driven account of the spread and the emergence of patient 31, a single super spreader believed to be the source of thousands of infections.
Our forensic reporting showed how one person could have a ripple effect in spreading the novel coronavirus. The story was lauded because of how we were able to explain the chain of transmission early in the pandemic.
The piece went viral far outside of Asia, with many on social media in the U.S. sharing it as an example of what can happen if social distancing isn’t adhered to.
The Korea Centers for Disease Control & Prevention put out a detailed health bulletin every day. We had to sift through and look for specific details piecing together how “patient 31” became the inflection point for the virus in South Korea.
We were then able to build custom visualisations in the browser locally which could be exported and styled in Adobe Illustrator and placed within the story page using ai2html.
What was the hardest part of this project?
This story was built on manual data collection and old school reporting. Although not alien to our team who often rely on computer assisted reporting, it was an equally rewarding experience to handle a project in this way. Technology helped us piece some of the parts together and visualise what we were seeing in the data but whiteboards and markers were definitely involved too.
What can others learn from this project?
Press releases and health bulletins may look mundane at surface level, but are often packed with valuable information which can be reworked to show patterns or reveal stories.