Dancing and Singing Clusters Project

Country/area: Hong Kong

Organisation: South China Morning Post

Organisation size: Big

Publication date: 2/1/2021

Credit: Marcelo Duhalde, Senior Infographic designer;
Dennis Wong, Infographic designer, web developing;
Gigi Choy, Reporter

Biography: Marcelo joined the Post as its infographic designer in 2016, having worked previously as the deputy infographic editor at the Times of Oman. Duhalde has won more than 90 Society for News Design awards, 17 Malofiej medals, one Peter Sullivan’s best of show.

Dennis joined the Post as a graphic designer after working for TIME Magazine for almost two decades. His infographics focus on local and regional developments.

Gigi joined the Post as a reporter in 2019 and covers Hong Kong’s housing, land and development policies. She graduated from the University of California, Berkeley with a degree in political economy.

Project description:

The project was developed following the need to explain to the audience the reasons for the explosive expansion of Covid-19 among dancing clubs, in view of the fourth wave of infections and the subsequent imposition of restrictive measures for all the activities.

The main goal was to show the movement of infected people among the dancing venues and its incidence over the spread of the new wave of cases. A secondary goal was to explain the reasons of this outbreak and the analysis of the data gathered to depict a frame of the population affected.

Impact reached:

In late 2020 and early 2021, the dancing clubs were fully operational and receiving significant numbers of visitors every day.

In Hong Kong it is a tradition among people of all ages, especially among the population above 45 year-old, to attend private dance events, group singing and dancing lessons, where attendees tend to move from one venue to another. During the pandemic, the spread of the virus among these venues was significant and took only a few days to become a critical origin of new infections.

Once the project was released, it was pretty active in social media, due to the relevancy of the subject and the noticeable consequences of the fourth wave in the city. The untraceable cases triggered a series of specific lockdowns and strict social distancing measures. The project had its print version explaining specifically the spread of the virus among the dancing clubs, enabling the infographic to reach a wider audience group.

Techniques/technologies used:

The Hong Kong government has kept strict records on everyone who has been infected. The data includes: Number of infected (since the beginning of the pandemic), Gender, Age, Date of confirmation of contagion, Residential address and Status (resident-not resident).

The below part explains how did we manage to date back the time when those infected cases began to have symptoms before going to dance clubs (in total 28 places):

– It was determined that in 30 days there were 732 infections originating in the dancing clusters. With this database, it was possible to establish the relationship between the places and the infected visitors.
– The paths were determined to reconstruct the contagion pattern according to the recorded dates.
– Relationships were established between these clusters and other existing outbreaks in Hong Kong, relationships between infected people, their mobility in different venues and their places of residence.
– It was determined that 41% of infected women were people between 60 and 69 years old
– It was established that the sources of contagion came mainly from mainland China, despite the efforts of the government to control the borders, there were situations in which the vectors of contagion were dance instructors from China hired from Hong Kong who had crossed the border for illegal entries.

Once all the information was gathered, it was easy to find connections between the venues.

The interactive animation of spreading infected cases, with an inset locator map, is created using javascript libraries such as jQuery, D3, GSAP and Scroll Magic. For the charts and illustrations, we used animated gifs and graphics generated in Adobe Illustrator and Maps generator to work with locations

What was the hardest part of this project?

The information gathered turned out to be multidimensional. Information includes places in Hong Kong to plot in a map or in a spatial reference, days covered, ages of infected people, genders, people’s origins and immigration status, close contacts situation, symptoms and iteration of patterns.
In the beginning it was difficult to establish which factors should be the predominant ones to tell the story. Several flow diagrams were tested to explain the temporality and displacement effects.

We realized that the static solutions were not effective, that is why an interactive exploration formula was chosen so that the user could superficially or deeply analyze all the connections between the clusters.

Once that functionality was defined, the time was invested in the design of the tool. The interactivity worked well but the design of the visual elements represented an important challenge due to the limitations imposed by the desktop and mobile screen in particular. It is a story that must be displayed vertically without losing the whole context, it was chosen to use a small lateral navigator to guide the user within this network of cases. The curved lines, colors and the movement of the elements in the interaction are determined by the concept of dance, which is what was wanted to secure aesthetic to arrange the elements of the visual story.

What can others learn from this project?

The reporters had to collect a massive amount of data that was continually being updated. They also suggested multiple ways to visualize the problem because for them it was necessary to find patterns in the clusters and contagions in order to tell the story.

The coverage of this news was based from the beginning on the need to visualize the data instead of delivering raw data, due to the large number of variables. Both journalists and designers understood that there are various stories behind the data relationship that deserved to be told and related to the interests and daily life of a city, and they will always have a good reception among the audience. The series of graphs are explorative and allow users to draw conclusions that help understand human phenomena in the face of a pandemic.

Project links: