How I Built It: Mapping the Racial Disparities of COVID in Chicago

Robert Martin (guest author)
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Oct 28, 2020

How I Built It: Mapping the Racial Disparities of COVID in Chicago

Robert Martin (guest author)

Guest

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Guest

Oct 28, 2020

What would every COVID-19 case, death, and test in Chicago look like on a map, using color to show race? 

That’s something I wondered in early April as I watched a press briefing from Mayor Lori Lightfoot and the Chicago Department of Public Health. The city had released some early statistics on the toll of the virus broken down by age, race, and ZIP code. The data was striking even when presented on slides and graphs—but I wondered if seeing the same data on a map could be more impactful. So I set to work building a visualization using Mapbox GL JS.


The Color of COVID

My project, the Color of COVID, uses dot-density maps to  underscores the disproportionate impact this pandemic has had on specific communities of color in Chicago. The racial divide in COVID-19 cases is stark: According to the Chicago Department of Public Health (CDPH), 72% of COVID deaths with a known race were Black residents, even though the city as a whole is 30% Black. The national trend is similar: while black Americans make up just 12.3 percent of the general population, they account for 21.1 percent of the people who have died from COVID-19 and 18.7 percent of those who have tested positive (Racial Data Dashboard).

Digging into the data

The open data I used to create these maps were provided by the Illinois Department of Public Health, which is one of the few agencies that publish COVID data aggregated by ZIP codes and demographics (more commonly, these are released as separate datasets that can’t be combined).

To create the map, the raw data on counts of cases, deaths, and tests were converted into discrete dots. This was done using a method similar to that of the Racial Dot Map created by the Cooper Center at the University of Virginia. However, in contrast to the Racial Dot Map, data for this project were derived from ZIP codes instead of Census Blocks to reduce the amount of noise when visualizing random points at a city scale.

The Racial Dot Map centered over Chicago

In addition, to make the locations more reflective of where people live in Chicago, 2018 American Community Survey data were used to assign each point to a census block group, based on the probability that a person of that race and ZIP code would live there. 

Once the data was converted into a Vector Tile format and uploaded into Mapbox Studio, I used data-driven styling rules to color each point according to the race.  

Three Datasets, Three Stories

Viewing the data on a map, the patterns of inequality were, unfortunately, easy to spot.

Cases. Looking at the distribution of COVID cases in Chicago, it’s clear that Black and Brown communities have borne the brunt of the pandemic. The city’s South Side, predominantly Black, is the large swath of green towards the bottom of the map. The orange clusters, representing Latinx cases, are most pronounced in the western parts of the city. Less noticeable are White cases (blue), Asian cases (red), and other races (brown).

COVID cases. Green = Black, Orange = Latinx, Blue = White, Red = Asian, Brown = other.

Deaths. COVID deaths show a similar predominance of Black (green) and Latinx (orange) clusters on the South and West Sides. However, there is a difference of magnitudes—the Latinx community has recorded the most infections in the city, but Black Chicagoans are comparatively more likely to die from the virus. This is evident by the higher quantity of green dots on this map, especially on the South Side.

COVID cases. Green = Black, Orange = Latinx, Blue = White, Red = Asian, Brown = other.

Tests. COVID testing paints a more equitable picture than cases or deaths—in fact, this more closely resembles what a dot map of the general population of Chicago would look like. The whiter, more affluent North Side makes its first strong appearance here. Although they have seen fewer infections and lower mortality from COVID, these neighborhoods tend to have better access to health care, resulting in more routine and preventative testing.

COVID cases. Green = Black, Orange = Latinx, Blue = White, Red = Asian, Brown = other.

It’s important to note that these trends are not unique to Chicago — similar patterns are playing out across the country, echoing disparate and deadly health outcomes from San Francisco to Omaha to New Orleans to Boston. No matter where you are, the odds are that the three maps above are not all that different from what’s happening in your own community.

The Road Ahead

The Color of COVID maps don’t just illustrate the story of the pandemic in Chicago—they visualize the jagged and unjust landscape of public health in America.

The same conditions that allowed this pandemic to exact a higher toll on people of color will continue to take lives long after this virus ceases to be a crisis. The news cycles will have moved on, but the chronic health conditions, lower life expectancies, and life-altering trauma will remain.

Technologists, data mavens, mapmakers, designers, and concerned citizens are in a unique position to help effect change by:

  • Demanding thoughtful, actionable open data about COVID near you (this should include demographics and local geographies, such as ZIP codes).
  • Creating expressive visualizations and interactive tools to help that data be understood by a larger audience.

No matter what story you choose to tell, remember: social injustice thrives in a void of information. Let engaging, immersive data products be one light that we shine on institutional oppression in the digital age.

The Mapbox Community Team provides tools and resources to individuals and organizations using maps for positive impact. Learn more about Mapbox Community and get in touch with our team.


Maps feature data from Mapbox and OpenStreetMap and their data partners.
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