My daughter, Annie, was a “camp kid”– she LOVED summer camp. We even had a happy song and dance that we all did as summer approached: “Camp, camp, camp, camp, camp, camp, camp…” (Use your imagination here, folks.) She always came home having met lots of new friends, and with great stories and memories. But in 2004 she came back to us with something more, something that no one ever wants: pertussis, or whooping cough — this in spite of the fact that she had been vaccinated against it. It seems the whooping cough vaccine introduced in the late 1990’s provides less protection each year after it is administered, often leaving children vulnerable before they can get their booster shots. The new vaccine uses only pieces of the bacteria that cause whooping cough, as opposed to whole, dead bacteria. In short, the new vaccine loses its effectiveness a year after it is first administered, according to experts and several recent studies in the Journal of the American Medical Association (JAMA).
And as bad as it was for Annie (and it was bad: just ask her!) it was also devastating for her parents. Bret and I could do nothing except offer love, comfort and reassurance as the virus ran its long (six-month) course. It was exhausting and nerve-wracking for everyone.
I am firmly in support of vaccinations, full stop. They work, and are vital to combating (and, in the best of worlds, eradicating) diseases that cause suffering and death. But in addition to being in support of vaccinations and alarmed at the number of people who have not been immunized for certain diseases (yes, like measles), I am now fully aware of the new and growing problem of ineffective vaccines. The interactive map below, was created by The Global Health Program at the Council on Foreign Relations, shows the situation in an easy-to-understand way and leaves no doubt that this too is a problem that urgently needs a solution.
In the column at left are the diseases of interest (measles, mumps, pertussis, etc.). When the viewer chooses one and the map is re-drawn, a bar graph (or bar graphs, if more than one malady is selected) appear[s] showing the colors used to display the number of cases for a disease on the map, along with the total number of cases (approximately 1.5 million) for the time-frame displayed (2008-January 2015).
Next to this bar, at the top right of the display, is another bar graph that I found particularly helpful: it lists in rank order the number of cases by region. You can hover over each region on the map to see exact values, but the addition of this bar chart is a nice quick way to quickly grasp the volume of cases. (I would like to see a total bar included, and a different choice of colors, but in general, I like these features a lot.) The following bar graph displays all of the data in the graph above by region.
Another design choice I like is the way the “Year” filter runs across the top of the full length of the map (and isn’t placed in the left-hand column with the other filters). It makes clear that a viewer can change time-frames on the fly; and because it is just above the map, it’s easy to tell what data year[s] are displayed on it; the bar serves as a sort of title to the map.
Sliding the cursor across the horizontal list of years reveals where the disease has traveled in the world. It is also worth noting that the size of the bubble on the map encodes the number of cases, so the prevalence of the disease in one region can be compared to that in another. Here is how pertussis spread from 2008 to 2014.
Whooping Cough 2008
Whooping Cough 2010
Whooping Cough 2012
Whooping Cough 2014
The power of this method of display is in its ability to throw into high relief (in ways that tables and line graphs cannot) where diseases have occurred, and — in this example — how specific ones have traveled and spread throughout the world. A word of caution, all the same: it may be tempting to create a cool map simply because you have location information in your data. But displaying information in this way is of use to viewers only when location (of a disease outbreak or anything else) is a meaningful part of the data’s story.
Perhaps no one expressed better the power of such information well-displayed than “the Lady with the Lamp”-nurse, reformer, and statistician Florence Nightingale. Properly presented, it could, she said, “affect thro’ the eyes what we may fail to convey to the brains of the public through their word-proof ears.”