Although somewhat helpful, such a map may say more about how connected a country is to the rest of the world, rather than showing how the virus has spread. In any case, it does not provide information about the number of cases. From this map on March 10, we cannot deduct that there was only one confirmed case in Burkina Faso, but over 10.000 in Italy, and over 80.000 in China.

A typical approach to avoid this issue are choropleth maps, a complicated name for something very simple. Blame the Greeks, choros means ‘region’ and plethos means ‘multitude’, hence the name. My scientific brain always tricks me into saying ‘chloropleth maps’, probably because it thinks about chloroplasts in plant cells. But don’t get your hopes up, there’s no connection at all — just my stupid brain. The ‘chloro-’ in chloroplasts also comes from Greek, but from chloros, ‘green’. The same origin, it turns out, as chlorine (because of its pale green color) or chloroform (which contains chlorine). But my apologies, I digress… I might have been reading too much Stephen Fry lately, who would probably love this kind of etymological exploratory ramblings.

So, a choropleth map. In such a map, regions are again colored, but the value of the color (lightness or darkness) depends on the underlying parameter, for example the number of infections in a country. In its most basic form it looks like this example by CNBC:

However, choropleth maps have their own unfortunate downsides and pitfalls. I will not go into much detail here, as everything was already written down excellently by ‘cartonerd’ Kenneth Field. Let me just summarize:

• choose your colors or color scheme responsibly,
• choose your categories responsibly, and
• use relative numbers to avoid population density distortion.

Or, just maybe, a bar chart might be a better choice:

Bubble maps, such as the ones by the Washington Post shown above, avoid this trap because each nation gets its own bubble, independent of area, population, or population density. This is what makes this kind of chart so successful to map a wide range of values in a wide range of countries around the globe.

There is only one minor downside: bubbles can start overlapping each other when two neighbouring regions have very large values (or one of them has a large value while the other only a small one). Then your bubble chart might start looking like this:

I already hinted earlier that in some cases, a simple bar chart might be a better option than a complicated map. As Leonardo Da Vinci said: “Simplicity is the ultimate sophistication” (except that he never said that). Another simple but effective alternative might just be… a table.

Many great examples can be found, including the Washington Post ones at the beginning of this chapter, but I was particularly charmed by the Datawrapper ones by Lisa Charlotte Rost, with a clever use of color to bring a touch of optimism to this heavy subject matter:

Also, differences in age distribution among the population have an impact on the death rate, so it’s rarely a good idea to blindly start comparing different columns or rows with each other, without thinking things through. Remember: if creating panic is your goal, you will always find some data somewhere presented in such a way that you can do so.

There are many, mány more amazing things you can do with tables, also in coronavirus times, but that will be something for another chapter!