The COVID-19 Open Visualization (COViz) project was created during the pandemic to experiment with innovative cartographic techniques for visualizing COVID-19 risk burden, resource and testing sufficiency. Using a combination of population cartograms, graduated symbols and choropleth colors, real-time animations were designed to communicate trends in case counts and rates relative to the population using natural intuitive cartographic variables. The original website included data on new cases, deaths and tests administered in US states & counties, Canadian provinces and European countries obtained in real time from the CDC, John Hopkins University and the COVID-19 Canadian Open Data Working Group. As real-time data API's are no longer available, COViz currently displays case data by US state using a snapshot of data downloaded from the CDC.

Cartographic Principles

• All maps and cartograms communicate both raw case counts (total burden) and rates per population (individual risk).
• Cartograms also communicate the population of each state, so that map area is proportional to population. For example, Washington D.C. is hardly visible on the map animations but on the cartograms it is the same size as Wyoming.
• Raw counts are expressed using proportional symbols. The bigger the circle, the more cases.
• Rates per population are expressed using sequential light-dark color schemes. The darker the color, the more intense the situation.
• State polygons are highly generalized so that the focus is on the thematic information, not the intricacies of borders and coastlines.

Cartograms

Population cartograms offer two main advantages in the context of epidemiological maps:

• Visual emphasis is proportional to population, so that densely populated areas become visible and large but sparsely populated regions do not receive undue emphasis.
• Rates per population can be inferred by the density of proportional symbols, because the cartogram creates a space of uniform population density.
• Symbols on a cartogram will have less overlap than on a regular map.

The cartograms used in these animations were constructed by hand. Information on how they were constructed can be found here.

Publication

A key motivation of the project was to experiment with the effectiveness of alternative visualizations to simultaneously communicate case counts, rates and underlying population during a pandemic. The techniques illustrated here were tested in a study that is reported on in the following publication:

Kronenfeld, BJ and Kwang il (Jason) Yoo. 2024. Effectiveness of animated choropleth and proportional symbol cartograms for epidemiological dashboards. Cartography and Geographic Information Science, 51(2):330-346 https://doi.org/10.1080/15230406.2023.2264755

COViz was designed and implemented by:

	Barry Kronenfeld Director, GIScience Center, Eastern Illinois University
	Kwang-il Yoo (Jason) PSM in GIScience, Eastern Illinois University
	Sushma Saragadam PSM in GIScience, Eastern Illinois University
	Sarah Kronenfeld University of Toronto