How to flatten the curve? What other countries experiences reveal

Country/area: Portugal

Organisation: Público

Organisation size: Big

Publication date: 5 Apr 2020

Credit: Rui Barros, Dinis Correia

Project description:

Flattening the curve became probably the most influential and most important chart of 2020. At the beginning of the pandemic, everyone was using that term, but we at Público felt that people didn’t understand why it was so important. That’s why we developed this scrollytelling article where people could understand a little better what that meant and what the data across the world showed us about it.

Impact reached:

This story went viral on social media. Portugal had registered the first cases at the beginning of March and numbers were increasing in April. So the timing of this story – that using scrollytelling techniques explained the little we knew about Covid-19 and added contextual data about how the situation was going on in other countries. That helped people understand better what ‘flattening the curve” meant and what was going on in other places – like Italy and South Korea.

Techniques/technologies used:

To gather the data, I’ve used R and the Our World In Data dataset that provided the numbers for all countries. For the Portuguese data, and since the Portuguese authorities kept publishing the numbers in pdf files, I used the tabulizer package to convert the data into csv files. A few days after publishing this work, which we wanted to update daily, the Portuguese authorities changed the pdf where the data was being published and started using the data from a group that was transcribing the data by hand and putting it in a github repository.
The scroller relied on scrollama.js and all the charts use chart.js library.

Since I was the one doing the data transformation and the data visualizations, I used R to generate the json file that feeds the data to the charts.

What was the hardest part of this project?

Getting the Portuguese data was hard because of the technical problems I’ve talked about before. Keeping it updated was hard because the data transformation needed from pdf to csv daily.
Since this was a scroller, it was also hard to keep information concise.

What can others learn from this project?

This was one of my first interactive features at Público. Since I was new in the news organization and I had the challenge to bootstrap a data unit there, it was the kind of article that let everyone know what I did – that I did more than just ‘infographics’ – and that data doesn’t need to be boring.

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