Don’t get fooled again

The eye is so easy to fool! I’d posted the featured photo in colour before. Just for fun I decided to convert it to black and white. I was surprised that it works. Perhaps because the yellow of the tiny flowers is so luminous that although the whole plant is in shadow there is enough contrast there. That got me thinking about decomposing it by colour. I dialled down the saturation of everything except yellow, and the eye still saw it as not very different from before. You really have to put the two next to each other to remind yourself what the difference is. And even then you may not notice that in one photo the leaves are not green.

Are we thinking right in our response to the pandemic? The world locked down again and again to flatten the curve, to prevent hospitals from being overrun. Wuhan was absolutely locked down at the beginning, and that stamped out the disease in that city completely. In other cities we thought it wouldn’t hurt to go for a walk, and perhaps talk to the people we see. Surely meeting one acquaintance in a couple of weeks would not change things, we reasoned. Was that right?

June Almeida was the first scientist to image a human coronavirus (for bio, click on pic)

If the disease spreads evenly, that is every infected person has the same chance of passing on an infection, then even very mildly leaky lockdowns do not prevent a single death! When you study the total number of deaths, it seems to make no difference whether the lockdown was leaky, or whether there was no lockdown. The only difference is the availability of health care, and whatever that implies. Strange!

So lockdowns were thought of as a tool to “flatten the curve”, not as a long-term solution. But that step involved an assumption. It turns out that if you have epidemics (like the flu or COVID-19) which depend on super-spreading events, then the situation could change. The simple expedient of closing every place in which, say, more than 20 people can gather, can cut the transmission of the disease by a large factor. This saves many lives. Strange!

John Snow is widely regarded as the founder of the field of Epidemiology (for bio, click on pic)

It seems that the maths works out. Not quite as transparent as 2+2=4, but apparently quite as definite. But I am always left a little doubtful by mathematical arguments in which every assumption cannot be tested in real life. Maths is a bit like that photo in yellow; an approximation of the real world. Some scenes can be captured in yellow, others not. Believing blindly in mathematical models of the world led people to theories of the aether once. It leads others to believe in market economics today. Both could have been right, but without extensive testing we would not have known better. You don’t want to make the same missteps again with epidemics. The world is stress-testing epidemiology now. I wonder how the subject will change in a couple of years.