- Models tell you only what you tell them to tell you.
- Solutions, reactions, decisions, and so on, related to model output, are also models
- Ferguson, the professional panic-monger who started all this with his insane, unvetted model, has a 20 year history of promoting panic via insane, unvetted models that fail to match reality.
- If you do not run your model against independent data collected from objective reality, it holds no weight. It means nothing.
- Common knowledge among modelers: you can always build a model for any set of test data that matches the test data perfectly – and this means nothing, except that you need to run it up against reality.
And, on the Kung Flu specifically:
- When the models that predicted coronadoom ran up against reality, they all proved disastrously, ridiculously wrong.
- A case used to mean ‘someone with symptoms who needs medical care’, not ‘someone with a positive test result, but no symptoms or need for medical care.’ Counting cases is misleading at best.
And here’s my favorite graph, from the CDC data:
Deaths peaked during the Great Depression, possibly because financial panics are stressful, and stress kills, then slowly declined until about 2010, when it began to slowly rise again. Look at that nasty uptick in deaths at the end there! Oh no! Based on where the uptick began, it looks like the Coronadoom started taking out people in 2014 – the damn thing can time travel? Is there no evil this virus can’t do? Compare this to the UN data and projections since 1950, which specifically does not take the Coronadoom into account:
You will note that the UN projected an increasing death rate starting around 2013, 7 years before the COVID panic was a gleam in Ferguson’s eye. Why? As the US populations ages, a larger percentage of people will die each year. The US population has historically skewed younger: immigrants tend to be younger, and when the birth rate is higher than replacement rate, more babies enter the population than oldsters exit it. But now the US population is getting older, as fewer babies are born. Therefore, the death rate will rise. Not rocket science.
Now let’s break out the two relevant sections of the two graphs, the annual death rates from 1950 – now, in the CDC numbers, we can see the dramatic uptick in deaths caused by the most horriblest viral outbreak in History that we’re now in the middle of, versus the UN numbers which exclude the effects of the pandemic. Top graph is actuals including the Kung Flu deaths; the lower is projections without Kung Flu, as the banner says:
Wow, just looking at the graphs! The supposed massive uptick in death caused by the Cornonadoom IS INVISIBLE. Put it the other way around: if 400K more people had died in 2020 than was expected, the 2020 death percentage would go from 0.888 to 1.012. (.888 X 330M = 2.94M; add 400K dead, it would be 3.34M dead; divide by 330M = 1.012 death percentage.) * It would look like this:
So the CDC graph (which I didn’t use because the y-axis scale is inconvenient for this purpose, but the graphs are the same) should show a dramatic increase over the UN projections if, in fact, the virus killed a bunch of people. But it doesn’t look like this at all! It looks like NOBODY MUCH EXTRA DIED IN 2020.
One of my complaints with the numbers and reports coming out of the CDC is how needlessly complex (and difficult to find) they are. ‘Excess deaths’ are calculated on a weekly basis using all kinds of assumptions and math that make answering the simple question: how many more people have died this year than last? or, better, how many more people died in 2020 than could reasonably be expected? needlessly difficult to answer. Why is a simple total of deaths in 2019 versus deaths in 2020 not posted on the CDC’s home page? Seriously, why, if we’re supposedly in the middle of a pandemic, not post totals so that people can get a feel for the magnitude of the problem?
Unless, of course, there isn’t a problem. Or rather, if people knew, there would be a big problem for certain people.
*Note – it’s estimates all the way down on population #, so it is simply pointless to try to get much more accurate than this.