Introduction

This is a wonderful book, marred by the virtual absence of copy-editing. There are more than twenty errors, spelling and stylistic, in the first ten pages, making it annoying to read; this is very odd, as West is himself the editor of the series.

The story it tells is a familiar one to this E:CO audience. The medical profession has put all its money on bell-shaped—Gaussian —curves and linear mathematical argument, and has missed the (mostly nonlinear because nearly all mathematics is nonlinear) contexts for physiology. Missed it partly because it isn’t physics: West himself started as a physicist, and the tear marks where he had to completely revise his assumptions are still visible; he has been singing this song for a long time (since the early 1980s), and the story is nearly complete. What a pity it isn’t more elegantly put.

He starts by showing how the law tried to treat farmers and city gents similarly (‘feudal’ and ‘agrarian’), and how this led to ‘egalitarian’ philosophies that in turn led inexorably to Gaussian—bell-shaped—curves. From de Moivre and Bernoulli he distils that radical difference of philosophy that predicts, from that which aggregates: he uses the vaccination procedure, its odds on individual death from vaccination compared to the vaccination of the populace, to make this point. (And I can make the copy-editing point: “The Turkish method was to impregnate the skin with puss from live smallpox putules from which most recipients would subsequently become immune to the disease.” Apart from puss, putule, recipient, impregnate is the wrong word and subsequently is unnecessary!) The difference is less important now than it was to the physicist that he was in the 1980s. He describes a variety of clinical systems—heart, locomotion, gut etc. and makes the point that homeostasis, even cybernetics, isn’t enough to handle the contextual feedback in these systems.

He goes on to elaborate four ways in which science (at least his science) has changed: firstly, all science was quantitative (he quotes Rutherford that if it’s not, it’s “just stamp-collecting”)—but from D’Arcy Thompson to Thom, from embryology to psychology, that can’t be carried: qualitative is at least as important. Secondly, explanation came from “natural laws” via essentially linear functions—but we now realize that nearly all ‘real’ maths is nonlinear, and complexity studies break the links between laws and events, not least by changing scale. The third ‘truth’ is—was—that dynamics of systems are predictable from their laws of motion—chaos upsets this, but so does the very act of transferring the dynamics into (nonlinear) phase spaces—he explicates the Lorenz story quite prettily. The fourth ‘truth’, that physical systems have fundamental scales in space and time, provided the characteristic Gaussian distributions… leads him off into inverse power-law systems such as those of Pareto (the scale for incomes, city-populations, etc…), Zipf, etc. He is sure that the (more) modern versions of these truths, which lead to different uncertainties, are where medicine should have gone, but in general has not. He dances about among Pareto systems, showing in each case how Gaussian interpretations are false-to-fact in diverse ways.

He has a cute classification of scientists, into sleepers, keepers, creepers, leapers, and reapers, which is quite amusing and to some extent illuminating—it’s used elsewhere in the book, but not to great purpose. There is a very interesting transcript of a long conversation with Jonas Salk, which makes these points and others, emphasizing the radical between physics-thinking and biology-thinking.

This is followed by a really interesting series of clinical (and quasi-clinical, like gait) examples, in which we learn that homeostasis is only the approximate, linear, interpretation of many regulatory functions—that it’s more important for clinical analysis to look for the differences between heart-beat intervals than for the ‘regular’, or ‘mean’, interval (this is a very-well-attested example). Lots of other convincing examples follow. The last chapters go overboard in several directions, and are difficult (for me…) to follow. Peculiarly, they are mostly difficult analyses of clinical issues, most of which don’t resolve neatly—I think he hasn’t quite lost his old-physics belief that if biological phenomena don’t fit a mathematical analysis then either they’re badly aggregated or we need some new/different maths; he’s very reluctant to accept the idea that some data might not (yet?) be resolvable…

My feeling is different: as an animal who’s about half-way between Australopithecus and human, I don’t expect to be able to explicate everything!

This is a very difficult book, not least because it’s not been copy-edited (we learn that ‘a’ genera is within a species, for example!). But it’s bang-on about medicine having gone the wrong way; it won’t mediate the necessary change, however. That’ll be up to the rest of us!