Taipei Lockdown: Three Containment Models to Flatten the Curve
Organisation: CommonWealth Magazine
Organisation size: Big
Publication date: 7 Apr 2020
Credit: Chen-Hua Chen, Daniel Kao, Yi-Wen Lin, Yu-Hsin Lee
As of April 2020, nearly half of Taiwan’s confirmed COVID-19 cases were concentrated in Taipei City and New Taipei City. In “Taipei Lockdown”, Commonwealth Magazine collaborated with Professor Wen from National Taiwan University to analyze and model how the virus would spread through communities in Taipei City and New Taipei City. Given the high population density and high human and economic activity of these two northern Taiwanese metropolises, what different containment strategies would most effectively contain the virus to prevent large-scale community spread?
Commonwealth Magazine published “Taipei Lockdown” as cases were still rising in Taiwan and serious containment measures were being planned by the Taiwanese government. Worried about a potential lockdown, residents of Taipei City and New Taipei City began stocking up on toilet paper and rubbing alcohol while looking to the government and the media for information and guidance.
After Commonwealth Magazine published this report, many other news organizations also picked up this story, allowing various epidemiologists to discuss potential lockdown strategies. Our charts appeared on various websites and television news programs, and Professor Wen was also contacted by the Taiwanese government to advise on potential lockdown measures. Although a lockdown never came to fruition, “Taipei Lockdown” served an important role in the discourse and preparation of Taiwan’s pandemic response.
In the reporting of “Taipei Lockdown”, Commonwealth Magazine started with research done by Professor Wen at NTU. Through his research, Professor Wen modeled different containment strategies and identified that dividing Taipei and New Taipei into twenty-six containment zones would be most effective for combating the spread of COVID-19. Commonwealth Magazine combined the data and models from Professor Wen’s research with transit data from Taipei’s MRT (Mass Rapid Transit) to create interactive charts and maps of different lockdown strategies.
Python was used for data cleaning and analysis, and dynamic maps were created with D3 and open source cartography tools such as QGIS. All of this was built on top of our internal Svelte.js interactive graphics library which Commonwealth Magazine has developed for visual storytelling.
What was the hardest part of this project?
The most difficult part of “Taipei Lockdown” was the framing of Professor Wen’s research. Because all three models Professor Wen simulated were hypothetical scenarios based on epidemiological theories, it was important to Commonwealth Magazine that the reporting was relevant to and easily understood by our readers.
In order to increase comprehension of how the containment districts in Professor Wen’s model were established, we visualized the transit patterns of people on the MRT, allowing readers to understand that the most effective containment districts would be based on how people’s daily patterns.
We also spent a significant amount of time discussing how to best disseminate the SIR epidemic model in our report, and ultimately settled on a visual, animated representation of how many cases have occurred at a given time, and made the comparison between different lockdown strategies very apparent.
What can others learn from this project?
Other journalists can take this project as a model for collaboration with academic researchers. Oftentimes, data-related stories may use modeled or hypothetical data for a variety of reasons, requiring the input of a subject matter expert to help guide or supply the data for a visualization. Under such circumstances, academics play a valuable role in making our projects more holistic and rigorous.