A great post Rudolph rigger. It explains it well to lay people like me. It reminds me of a conversation I had with someone re electric car batteries when charging.
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But I am not looking at a function, although it looks surprisingly like a function's output.

But you are looking at a function. The mortality curve is a function - and although we might not be able to write out a simple closed mathematical expression that generates the shape of the curve, it absolutely is a function in a mathematical sense.
I am looking at the superposition of some exponential function (natural virus behaviour) with the effects of law making layered in, and the individual choices of 70 individual million people as well. Hence I am not trying to understand a mathematical curve, it would be fruitless.

No idea what you mean by a "superposition of some exponential function . . . with the effects of law making layered in". This is just gobbledegook.

Obviously, to understand why the mortality/time function is the shape it is, is far from a trivial task. This is where modelling can be a very useful thing - it can give us some insight into this. I'm no mathematical epidemiologist (I'm a theoretical physicist) but I'm pretty certain you're going to have a set of coupled differential equations to solve for the various dynamical variables you include. One of those variables you may wish to analyse would be mortality as a function of time. Another might be the R number. And so on. These variables are all going to be dynamically coupled and parametrized by time.

Lockdown measures would be modelled by limiting population mobility in the model, which would tend to have the effect of reducing 'collisions' of infected people with non-infected people. But again you're looking at a complex set of coupled differential equations to solve - and models of this kind of multivariate complex interactive behaviour are notoriously difficult to get right. You have to be very careful with them.

But understanding this dynamical behaviour mathematically is the key to the whole thing - and not at all fruitless.

I'm sorry to be so blunt, but one is just 'pissing in the wind' by eyeballing features of a curve that has been generated by complex interactive dynamical behaviour and trying to disentangle cause and effect. And let's be fair here - I've done this kind of first-level simplistic analysis too when arguing about lockdowns and their efficacy.
I am pointing at 2 or 3 obvious and dramatic features in the path the virus took, and correlating as best I can those abrupt features to obvious, large legal changes. And they seem to fit. It may be chance, but I don't buy that. It is likely that such all encompassing legal constraints on behaviour would alter virus transmission, it's not proof I seek, but mere confirmation. And that is what I saw.

This is the problem with many of the 'mainstream' arguments regarding the lockdowns. They're also doing this naïve business of looking at a few salient features and trying to "correlate" these with policy changes. This is associational and far from any kind of confirmation at all. As you say, they simply "seem to fit".

For example, you'll see people argue that the long quiescent period in the mortality curve over Summer was due to the success of lockdown policies. This might be true, of course, but it also might simply be a reflection of the virus' seasonality. How are you going to determine which of these is closer to the truth? Is it some combination of these things? Are there other factors (variables) at play?

Without doing a closer (and more mathematical) analysis of these things all you do when you pick out a few key points is to draw correlations, which may or may not be causational.

A great post Rudolph rigger. It explains it well to lay people like me. It reminds me of a conversation I had with someone re electric car batteries when charging.
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Thanks Mia,

I distrust simplistic assertions (including my own) when talking about what is a very complex problem to understand. Lockdowns are going to have some effect, but nowhere near the rosy "aren't they just a wonderful thing to save lives and protect us from this virus" type of mindset we see in the mainstream media.

What is disturbing is the widespread adoption of things like 'masks work' and 'lockdowns work' when only a year or two previously most people would have been somewhat more dismissive of these questionable assertions.

I keep returning to my central conundrum. We know flu and covid are different - but somewhere on the line between flu and covid we decided to become mask morons and lockdown loons. Is covid sufficiently different (and more threatening) than flu that such a drastic remodelling of our entire approach to respiratory infections was warranted?

I keep returning to my central conundrum. We know flu and covid are different - but somewhere on the line between flu and covid we decided to become mask morons and lockdown loons. Is covid sufficiently different (and more threatening) than flu that such a drastic remodelling of our entire approach to respiratory infections was warranted?

From the clinical and epidemiological point of view there is ZERO difference between Influenza and SARs CoV 2. Absolutely ZERO. They have the same sort of infection rates (Influenza is higher). They seem to have the same kind of asymptomatic infection rates. 30% to 70% depending on flu strain. The symptoms and symptom progression is pretty much the same. Except no sneezing and wet cough with SARs CoV 2 (only dry cough) which makes it far less environmentally contagious. In fact human-corona viruses infections and influenza infections are so alike that they often get lumped together as the "common cold".

The rate of development of more severe symptoms is about the same for Influenza and human-corona virus infections. They can both cause viral pneumonia. And the severe infection rate and death rate is about the same. There is no huge order of magnitude difference between the clinical effects and risk of SARs CoV 2 and any of the current non pandemic Influenza variants. In fact the last influenza pandemic, Swine Flu in 2009 (H1N1-09) killed the under 60's at up to ten times the rate of SARs CoV2. For example a few dozen < 18 have died in the US from SARs CoV 2, well over a thousand < 18 died from H1N1-09 in 2009/2010.

The only difference between Swine Flu in 2009 and SARs CoV 2 in 2020 has been the media driven mass hysteria and the catastrophic response of western governments. In the initial phase of the Swine Flu outbreak a rerun of the Spanish Flu of 1918 was feared because the new variant was from the same family and had not been seem in many many decades since 1918. There was a real sense of panic at the time among public health officials. But in the end it turned out that although Swine Flu was nasty, biggest death toll since 1968. It did not trigger the cytokine storms like the 1918 variant which killed all the young people. And the over 60's, who have the highest mortality rate from influenza and corona-virus infections, had pretty good cross immunity to Swine Flu. Which was complete unexpected. Without that cross immunity at least 3 to 4 time more people would have died in 2009/10. So well over 200,000 plus in US. At least 40,000 in the UK.

Fundamentally the biggest difference between 2009 and 2020 is the key medical statistics regarding the infectious agent were basically correct and true in 2009 and utterly fraudulent in 2020. The basic data regarding just how infectious and dangerous the original SARs Cov 1 infection was in 2003 ,the numbers published by WHO, CDC, and the medically literature, were based on deliberately fraudulent data published by Chinese Government as part of the wide spread cover up of the outbreak in mainland China in 2003.

The single most important number for any infectious diseases, its meedical risk to the general population, is the Infection Fatality Rate (IFR). The IFR number published for SARs CoV 1 by the WHO etc from the 2003 outbreak had zero reliable data available to support the value they published. They just used the much much higher Clinical Fatality Rate for which there was actually reliable data from outside China.

So the initial lockdown etc were based on a completely wrong value of the potential risk of a novel SARs CoV variant. Ten times higher than the actual risk. A value that was completely fraudulent because of the Chinese cover up in 2003. And more importantly, a number that those public health officials and medical researchers in the area would have known in January / February this year to be utterly unreliable and completely untrue.

I think they have some effect, sure. After all, if a country implements a brutal lockdown (maybe even welding people into their homes) you would expect this to have a very significant effect on transmission and infection/mortality rates.

Oh good, so I was right then? lockdowns do alter the course of the disease. I said that in my original post: lockdowns work to delay disease progress, lifting the lockdown allowed disease to resume from the same place. Lockdowns have some effect, sure, that's what the plots show.