The Madness of King Us – Covid-19

I am trying to  imagine what Cast of Mind we should cultivate to get us through the Covid-19 outburst. Although by no means sure, I am not convinced that the cast of mind being thrust upon us by those in authority, their advocates, and the news media is the best one for the job.

I have been suggesting, in other places, that a Fourfold (or Morefold) Cast of Mind might constitute a better way. By that I mean, most simply, that we should cultivate the capacity to look rigorously at any situation, in this case the new corona virus, in more than one way with equal degrees of rigour. The idea is a little more complicated, in that a truly Morefold Cast of Mind would think in all relevant ways simultaneously. A simple sequential algorithm will work well enough for today.

You will perhaps have noticed that I did not call Covid-19 a crisis, or even a pandemic, but an outburst. I am searching for a neutral term, but not too neutral. I am trying to keep my mind clear of all preconceptions, especially those cultivated by people who might be cultivating some other cast of mind. Is Covid-19, or the virus that causes it, the “crisis”, or is the “crisis” our reaction? In other words, is our reaction proportionate to the phenomenon itself, or are we marching to the beat of some other drummer?

In order to clarify further before I get into specifics, I draw your attention to three examples of Fourfolding that I have encountered so far. Obviously I will be more content when I have a fourth, which ought to come from William Blake, who called our attention to the “supreme delight” of “Fourfold Visions”. His concept however is so complex that I do not yet have the pleasure of understanding it. I have found three more mundane others. I call them Tetrads:

Stephen Butler Leacock, 1860-1944, in his copious and varied writings on education: Knowledge + Imagination + Compassion + Humour;

John Maynard Keynes, 1883-1946, in his tribute to Alfred Marshall, written in 1924: Mathematics + History + Statecraft + Philosophy;

Isaiah Berlin, 1909-1997, who, according to his biographer Michael Ignatieff, sought a cast of mind that is: sceptical, ironical, dispassionate, and free.

A fourth might well be Northrop Frye, 1912-1991, who certainly liked to organize his thoughts in fours, although I am not sure what the full list would be. I am nearly certain that “Literary”, or “Poetic”, would appear on it.

What happens if we approach Covid-19 with a cast of mind somehow consistent with these casts of mind? How would we react?

First of all, I think we would require that whatever we are reacting to ought to be a fact and not merely a belief. Is our reaction itself a fact? No doubt it is, but too far downstream for this analysis. I submit that the “facts” at the root of most of the excitement are (a) statistical, and (b) historical. Other “facts” or perceptions, are augmenting the excitement, I submit, but those are the roots. I will start with the statistics. I am looking at two statistical web sites with coronavirus pages: https://ourworldindata.org, and http://www.worldometers.info.

The result is a blizzard of statistics, far too many for the mind to grasp, no matter what cast of mind one brings to the task. These sites, but particularly the former, are very, very, very, very informative, if you have the time and numerical literacy to make use of them. The natural human need, however, is somehow to distill the essence of what they are saying. This is where we get into trouble, because it is almost impossible to distill the essence without imposing prior judgements or biases. To distill without bias takes one into a realm of sophisticated analysis inaccessible to the citizen-reader who is simply trying to become well informed.

To illustrate how biassed distilling might work, what would I do if I wanted to convince you that some phenomenon, measured in numbers, is larger rather than smaller? First of all, I would look for the largest numbers available and draw your attention to them. For example, given a list of countries and their Covid-19 data, I would first make sure that whatever statistic I was reporting would be as wide as possible. “Cases” does that admirably, and I would make sure that I made any discovery of what I meant by a “case” as difficult as possible. It appears to me, in this instance, that a “case” includes everything from a positive test with no symptoms right through to mortal illness.

What about death? Is that not a more precise phenomenon? For a younger population I believe it is, because death is not generally expected there. But for the very old? People over eighty are at high risk of dying, and usually have more than one condition which, if put under sufficient pressure, can kill them. Is an octogenarian with a weak heart who contracts Covid-19 killed by the weak heart or the virus? Common sense would conclude: by both. In the midst of a panic, what happens to the idea that octogenarians are at high risk of dying, no matter what is flying around, and that they die primarily from being old?

Then, I would make sure that if I did present any ratios, for purposes of comparison and context, I would choose the largest denominator possible. Cases, or death, per million produces numbers ten times larger than per hundred thousand, for example, ten thousand times larger than percentages, and a million times larger than the raw rate which is a measure of the probability of occurrence. Thus, for Canada (today’s figures) 110,000 cases in a population of 38,000,000 sounds a lot more impressive than a probability of occurrence equalling .0029.

Third, I would avoid any comparisons with other comparable statistics, which might make mine look small. For example, according to Our World in Data (these people seem to be very thorough), 56 million people died in 2017, world-wide. Covid-19 has been active for about five months, with 607,000 ascribed deaths (see above caveat about multiple causes of death). The total number of deaths in five months of 2017, well before Covid-19, was somewhere around 23 or 24  million; call it 25 million by 2020. This gives Covid-19 only 2.5% of the world’s deadly effect, considerably smaller than other causes such as heart failure and cancer, and that is before adjusting for the complications of age and the possibility that people are dying from neglect, postponed medical care, over-doses, suicide, etc., causes which come not from the disease itself but as side-effects of our response to it.

If I went on with this purposeful exercise any further, I would bring in the practice of focussing on the larger countries, because they have larger numbers, and neglecting the small ones. I would talk about the U.S.A., Brazil, India, and Russia, with their dramatically large numbers of cases, not about San Marino and Belgium, where the death rates per capita far exceed any other place. San Marino is small, of course, and needs a different kind of analysis, but what on earth was going on in Belgium? When journalists were going on endlessly about Italy, Spain, the U.K., the U.S.A., I do not remember anyone talking about Belgium.

Then there is the whole testing phenomenon. How does that work, and what effect does it have on careful interpretation of the numbers?

Most of all, however, I would make sure that statistics were presented to the public in the grossest possible way, without sensitive geographic or demographic partitioning, so that no one would possibly be confident about what they meant without delving into the detailed tables themselves which, as I have already pointed out, the citizen-reader, trying to become informed, would have neither the time nor possibly the know-how to do.

I am not suggesting for a minute that Covid-19 is not a serious matter, or that some kind of unusual reaction would be inappropriate. Clearly this time is not “life as usual”. Nor am I questioning the reactions taken in the early stages, when no one knew what this virus was or what it might become. For us to be concerned that it might be as terrible as the so-called “Spanish” flu was entirely understandable. What do worry me, however, are the continuing efforts to keep us in a high state of apprehension, even fear, even as the virus becomes much better understood, and as the side effects of our response become increasingly apparent. We are being constantly urged to be afraid of Covid-19. I think we need to be a little more fearful of our reactions.

For me personally, two aspects of our reactions loom very large. The first is the encouragement of isolation from each other. This concern is very real to me, who in my situation could easily, and comfortably, turn into a rural solitaire. What do we become if we act habitually as if we were afraid of each other, are able to interact only under severe constraint, and are not allowed to see each other’s faces? How do you smile at someone through a mask?

The second is the encouragement given to “experts” to beak off in the public media without once telling us what their evidence is. Maybe they have some, but they aren’t saying. I get particularly concerned when these beakings come in the form of predictions, which must be based either on hunch or on statistical models extrapolated from other diseases. We simply cannot have the data yet for valid extrapolation from the history of Covid-19 itself. The broadcasting of “worst-case scenarios” based on untested statistical “models”,—the usual term for sets of equations based on theory or historical data,—was a terrible phenomenon in the early stages of the outburst and a contributor to panic.

Thirdly, I worry about the stimulation being given to the authoritarian tendencies of governments and their officials. In Canada we are, and strive mightily to be, a liberal democracy. We are entirely within our rights as citizens to question every rule imposed on us by our governments, without exception. I do not mean that we have the right to disobey it, but we may and should question it, and press for it to be changed if we think it harmful or unnecessary.

I have seen some talk recently about “metrics”. The only metric that makes any sense to me is the probability that I will catch Covid-19 if I go about my life and business in the normal way, and the probability that I have it already and will give it to someone else. I would like to see that probability adjusted sensitively for different parts of the country, and for different settings.

If I had the data for that calculation I would be able to perform a proper “risk assessment” and make reasonable decisions about what I should do and what I should protest. For example, it seems clear that the risk, the probability of harm and its consequences, would be higher if I were going into a care home or other residential institution, although I would like to see that calculation adjusted for management practices. Anyone who has been in care homes knows that they vary in their facilities, ventilation, and practices, perhaps crucially. What I have been able to learn with a reasonable amount of digging, puts the level of risk in the normal activities of life far lower than is being generally assumed, except perhaps in congested settings.

It appears we may be inching towards a regime where that kind of conclusion prevails, although I believe we are not yet well protected against a return of panic, if the numbers increase abruptly and they continue to be interpreted as grossly as they have been so far. We are certainly not well protected against authoritarian measures thrust upon us without proper explanation. By proper I mean explanations accompanied by statement of the evidence, not the unsupported assertions of people identified as experts, nor anecdotes taken out of context. Explanations of this kind would make the evening news more useful, albeit perhaps more confusing, and less exciting.

I write this article as part of the Fourfold Visions Projectile (see http://www.voyageurstorytelling.ca), out of my beliefs in complex thinking about complex matters, and in the positive usefulness of diverse points of view, openly expressed.

For the next several days I will be reviewing this text each morning, and striving to improve it. I apologize for its flaws. Thank you for reading.

Paul Conway

 

 

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