Do you know that feeling when you are focused on a particular thing and all of sudden you have experiences that are either directly or vaguely related? You hope to get pregnant, (all those decades ago, for some of us,) and start to notice pregnant women everywhere, baby clothes stores popping up in unexpected locations, lullabies being broadcast on your classical radio station? I’m sure you can come up with multiple comparable examples.

Lately, I have been focused on numbers. Numbers people are asking those poor doctors, who struggle to paint a hopeful picture, which might or might not be misleading. Number of stages, of treatments available, number of side effects, number of years that signal a future, or not. Numbers that are given in averages, since that is what basic statistical evaluations will provide. Averages that some happily accept if they speak in their favor, or qualify with “each case is special” if they don’t. Averages that might rely on way too few data points, or be weakened by insufficient randomization. Averages that mean, honestly, nothing if they are not accompanied by information about variability, which patients won’t receive, or might not even know about and consider relevant, if they were not trained as scientists.

Wouldn’t you know it, some complex issues around numbers promptly popped up in my daily readings.

A fascinating discourse on what numbers are used – and which are left out – in the reporting on countries’ death rates from Covid-19, for example. Here I learned about how informations is given in absolute numbers, by news outlets all across the world, telling us how many people died in each country. Huge numbers, to be sure, unfathomably horrifying numbers, if you look, for example, at India. Has anybody noticed that the relative number, when counting numbers of the deceased in proportion to the size of any country’s population, (India has 1.392 billion inhabitants) spells out that pandemic loss of life in the United Kingdom was much higher than what is happening in India? Even if you account for bad data collection and multiply the official numbers given by the Indian government by a factor of four?

Then again, (and I am summarizing what I learned) the numbers that are not captured, either by design or by the difficulty of collecting them, could tell a more complete picture. How many people were sent back to their Indian home villages, dying of poverty-induced hunger or disease, or accidents in dangerous travel condition? What hit did an economy take that had not provided an even barely adequate health care system in a country that has no social safety net?

Closer to home, what numbers were or are suppressed in regard to heightened endangerment of susceptible populations? The elderly are still dying in great numbers in nursing homes, but no-one mentions them anymore after the first wave subsided. The poverty divide, etched along racial lines, is not often captured in the numbers presented in the general news media. (You can get to them by going to governmental/CDC website, which I strongly discourage, given the depressing nature of the data.)

What other numbers never enter the printed press or the evening news? Have you had daily updates on tuberculosis cases, even if every year it causes the death of around 1.7 million people? Or the 1.4 million people who die every year in car accidents?

Was it just that the pandemic was new, affording heightened attention? Or did publication of these numbers have to do with the need to keep populations sufficiently fearful so that they would passively accept heightened lockdown measures and other deprivations, sparing the government the economic and political cost of enacting them by force, police measures included?

Numbers as a form of indoctrination might make you shrug, or confirm your beliefs about statistics as the biggest lies of all. They do have consequences, though. If people who work one hour per week are taken out of the unemployment numbers because, they have, after all, worked!, it points a certain picture that might benefit governmental goals and policies. These, in turn, might hurt some populations and help others, depending what kind of government we elected.

The consequences can be deadly. Here is an example of the typical number problem in service of Nazi Eugenics presented to my parents and their age-mates in the late 1930s in every German middle school book.(Source here.)

“To keep a mentally ill person costs approximately 4 marks a day. There are 300,000 mentally ill people in care. How much do these people cost to keep in total? How many marriage loans of 1000 marks could be granted with this money?”

I do not have to spell out the pathway from these seeds of numerical indoctrination to the T-4 Euthanasia program of 1940, which murdered 200.000 disabled people in the next 5 years.

Given how much of a punch numbers can pull, it is truly important to figure out how they were collected, which were included and which ignored, who collected them, and what purpose they serve. Now I am stuck with the question how all the media seem so seamlessly clued in as to what is desirable to report and what not, even outside of state-sponsored broadcasting. A better preoccupation than worrying about medical numbers, I guess.

Here are fewthrown out by W.A.Mozart, some happy numbers (Figaro) , and some cruel ones…(Don Giovanni.)

Here is a short article on Mozart’s fascination with numbers, as well as that of other composers. In case you need to read something a little more cheerful.

Photographs today are of patterns that invite counting.