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We’re #1! Not a distinction for which the US was looking. And it might not be true anyway if we had a clear picture of what is going on in the world’s most populous country — China. (Or is it India, now?) And we are not #1 on the “misery index” (yet).
I start today with a confession that I am a numidiot. I described numidiocy yesterday as “whenever numbers get so numerous that it ceases to convey clear and useful information.” @markcamp gently reminded me that the problem is not in the numbers it is in ourselves — our ability to order and interpret them. And, of course, he is correct. And herein lies the story of my own numidiocy.
Look at the chart below:
This is from the 91-DIVOC website I mentioned yesterday. I love these charts but it was irritating that when I wanted to see a graphic of the countries high on what I call the “misery index” (Cases/1 Million population) and focus only on the top ten (as the 91-DIVOC site permits) it was highlighting Vatican City (Holy See), San Marino, Andorra, etc. None of the heavy hitters — Italy, Spain, USA — were to be seen. And the reason was that 91-DIVOC draws it data from Worldometer.com which was displaying that data in tabular form at the time like this:
The calculations were accurate but inconvenient. Inconvenient in the sense that I wanted the graphical focus to be on populous locations as a means of comparing what was going on in those countries of more relevance to our experience in the US. And an event about a week ago had primed me to doubt entries in the Cases/1 Million population column: Somebody hacked the Worldometers site and inserted data for Vatican City that were extremely and ludicrously high. The website posted an apology for the hack and the data was corrected. Except that at various times as I would scroll through the tables sorted by total cases I would come upon the Vatican with its 4 cases and see the “misery index” at near 5,000 and dismissed it as some artifact of the hack that somehow hadn’t been cleaned up. Except, of course, it wasn’t an artifact as one can see when you do the sort above that pushes places with small populations to the top of the list.
And you may ask yourself how can the total cases for these places be so small and the “misery index” so high? Well, its based on how we massage the numbers, not the numbers themselves. What I call the “misery index” was a ratio created to try and compare the significance of the outbreak in countries with different populations, i.e., normalizing for population. This is helpful when cases climbed into five digits as a means of comparing how different populations are experiencing the outbreak. Thus even as we speak while the US has more total cases than Italy our “misery index” nationally is 260 compared to Italy’s at 1,333. Spain’s index of 1,370 is higher than Italy even with ~20,000 fewer cases. To the first order this suggests that Spain is in greater national distress with fewer cases than either Italy or the US, while the US is in significantly less national distress than Italy or Spain even with more persons affected by the disease.
But this begs the question of whether Vatican City is about 20 times worse off than the US? Well, of course it isn’t. Which is why I was irritated to have my lovely 91-DIVOC graph messed up with these high index countries whose index was so high simply because the ratio is multiples of the cases you have rather a fraction of them as in other countries. The formula for the “misery index” is Total Cases divided by the product of the division of a given population by 1,000,000. In other words, when the given population is less than a million you end up with an index value of some multiple of the total cases. So, for Vatican City, 4 total cases converted to an index value of 4,944 because Vatican City’s population is less than 1/1000 of 1,000,000. And so on and so forth with San Marino, Andorra, etc.
My numidiocy was driven by my interpretation of the index. The index was simply an index. The math works the way it works. We give meaning to the relationships. The index isn’t even really a “misery index”; that is just a catchy phrase (in my own mind). The numbers do not in and of themselves tell you the severity of illness within the populations, the level of emotions (fear and sorrow) that are being experienced in a particular locale within the indexed countries.
We are going to see a lot of numidiocy in the coming days as we try to sort out the path forward. That is because the meaning of numbers, not the math itself, requires interpretation. And getting agreement on interpretation may be difficult. I stumbled because of something I wanted; something of which the numbers were getting in the way. A lot of people are going to want the numbers to prove all sorts of things. There will be disputes. There will be uncertainty. But there will also be destiny. And, in the end, there will be numbers to describe what happened, if not why.
[Note: Links to all my COVID-19 posts can be found here.]Published in