The Danger of Green
By: Ron Giordano
Tags: Public Health, Design, Covid 19, Pandemic, Data Visualization

The Danger of Green

Are COVID-19 visualizations unintentionally putting readers at risk?

Should we stop using green for all COVID related visualizations?

As we collectively experience the COVID-19 pandemic, we are continuously inundated with more and more information. In response, millions of people have used visualizations and dashboards to identify patterns and differences. One of the first and most widely used COVID-19 dashboards was developed by John Hopkins (which I wrote about previously), but hundreds of dashboards are now available. There are country-specific dashboards, comparative dashboards, state and even county dashboards that are delivering greater insight and valuable information to the public. This accessibility to complicated scientific data is great.

As one navigates these dashboards, they tend to have a similar look and feel. The ubiquity of the US map combined with the color schemes that are often standard palettes from within the developer’s tool of choice, be it Tableau, Qlik, or PowerBI, deliver familiarity. For many visualizations, the choice of colors is a preference with limited impact on the ultimate utility of the information. That isn’t the case for COVID-19 visualizations. For these dashboards, I wonder if the prevalence of the color green is delivering a false sense of safety and security?

The Stoplight — A brief history

In 1920, the first red, amber and green traffic light was installed on the corner of Woodward and Michigan avenues in Detroit. A police officer, William Potts, designed the signals as a way to address the traffic problems that accompanied the proliferation of the automobile. Earlier versions of traffic signals were binary (stop/go), but his design included a “warning” light. Mr. Potts borrowed the colors from train engineering, and the scientific wave-length-based reasons for red as the color for stop. For the issues addressed here, traffic signals provide a cognitive gateway to establishing a false sense of security.

At a very young age, we become aware of traffic signals and their meaning. By our mid-to-late teenage years, most of us are tested on our understanding of these signals in order to earn a driver’s license.

Photo by Harshal Desai on Unsplash

The rules are simple, as laid out in the California Driver’s Handbook:

A red traffic signal light means “STOP.”

A yellow traffic signal light means “CAUTION.”

A green traffic signal light means “GO.”

It is that conditioned, automated response to green that concerns me. During a pandemic, with limited abilities to control the spread of the virus, do we really want to send readers a “GO” signal? Shouldn’t we always pause at “caution” levels until we know more?

Visualizing Momentum

The maturation of COVID visualizations have migrated from simple data elements (positive tests, deaths) to focus on a more complicated series of measurements that indicate momentum. The idea of momentum for COVID grew out of policy guidelines designed to determine if states are trending better or worse with regard to their ability to slow the spread, treat the sick, and limit the number of deaths. ICU bed utilization is an example of a metric that not many outside of the medical profession cared about six months ago. Now, it may literally mean life or death for a relative or loved one. That makes it awfully damn important.

The visualizations are a user-defined combination of trend data. Fourteen-day positive count, rolling averages, testing availability, positivity rate trend, and R (the rate of virus reproduction). All of these are indicators used in the determination of momentum. Where are we getting better, where are we getting worse?

“For many visualizations of COVID-19, measures of momentum are encoded in color. As you can see in the pictures of websites in this article, the details of momentum are consolidated by state or county and encoded with a color. For a great many sites, those colors are red, yellow, and green.