Ever heard the word "Choropleth?"
It is not a common word, yet it is commonly encountered in our daily lives, whether on television, or in newspapers or magazines. It's a fancy word that describes encoding data into geospatial maps or into colorful graphs to help the viewer gain easier understanding of complex data.
For example, Figure 1 is a temperature-graded weather map for an early summer day across America:
Figure 1 -- June 2, 2013 temperature ranges across America
And Figure 2 is a population density map of the American states:
Figure 2 Population densities for states in America, circa 2007
There is a lot of sophistication that goes into creating effective choropleths, and some subtleties that might not be apparent at first blush. One of the key capabilities is comparison of 'similar' data, for example, one time-frame vs. another while holding the variables constant.
Figure 3, for example, shows successive three-month 'windows' for COVID case-rates for the upper Midwest states (seven states--North and South Dakota, Montana, Wyoming, Nebraska, Iowa, and Minnesota). For these choropleths, counties shown in white are the 'best,' grading into blue and then brown and finally into orange (the worst level).
Note that the first three months of the COVID pandemic had little penetration into these states (left graph), while the middle three months showed increasing discovery. The right graph, though, shows an enormous growth in case-rates, which in fact had a very explainable cause--the Sturgis motorcycle rally in mid-August in South Dakota even though most public health officials state-wide and nationally urged that the event be cancelled. The SD governor, Kristi Noam, refused to do so (you've heard of her since).
Figure 3 COVID case-rates (X per 100,000) for Upper Midwest in 2020
Figure 4 illustrates the same criteria (cases per 100,000 population) for seven states New England states (e.g. Maine, Vermont, New Hampshire, Massachusetts, Rhode Island, Connecticut and New York). Note here that the first period (the left graph) was the worst for this region, especially in areas around New York City and up the Atlantic Coast to Boston. Later periods lessened the case-rate impact for NYC, and it remained virtually constant along the seacoasts, even as more of the upstate counties showed increased case-rates. None of these seven states had regions that ever 'went nuts' by comparison with virtually all of the seven upper Midwest states in the same third period.
Figure 4 COVID case-rates (X per 100,000) forNew England and NY in 2020
Over the 2020-2022 three-year period, InnovaScapes Institute (with help from AstroVirtual Inc.) compiled, collated, and analyzed daily COVID data for all 3,141 US counties, along with 196 total countries. Choropleths became our most important tool for displaying and describing our findings.
I eventually talked with many epidemiologists around America and Europe, and occasionally I would ask "are you familiar with choropleths?". One fellow, a key individual at Johns Hopkins hospital (which created, and shared publicly, the most complete data collection), said {somewhat haughtily, to my mind} that "every epidemiologist KNOWS about and uses choropleths." He went on, though, to say that "practically no one in the Public Health sector knows how to use them."
For our purposes, they proved invaluable. For example, using them nationally in March 2020 enabled us to 'discover' that ski resorts were a tremendous source of contamination, something that eluded the entire world community except for what they thought were isolated instances. Our findings easily revealed that eight US ski resorts were among the highest fifteen counties in America the third week in March, 2020--but 'who knew?" If public health officials were serious about stopping or slowing the pandemic spread, they'd have to say, "Half of the worst one-half of one percent of American counties, were international ski resort counties? Wow, we need to focus on that!" The sad fact is that they didn't know to do so.
Powerful tools--now you know to call them "Choropleths."