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Yup, all the search results I find quote (or misquote) Boris. WITH not OF omicron.
South Africa still say no deaths OF it : https://www.express.co.uk/news/world/1536157/south-africa-official-deaths-variant-omicron-covid
I'm no diseaseologist, but for delta, the average, most common case may be a few days ill, while some don't feel it at all and some die.
I know it varies by age etc etc but there must be some sort of distribution.
Let's assume it's a normal distribution.
Your stiffs are going to be up at the top end of illness. They're of the order of 1% at some some age so that's about 2.5 standard deviations from the mean, and higher. Black.
You can argue about the numbers...
The area under the curve represents the number in that illness group.
Now let's say omicron is two thirds as "dangerous" as delta. It must be some sort of function. A simple multiple may not be right but it's not utterly wrong.
If you have a better one, please show it.
So I've got the average/peak number, about two thirds across the graph, for omicron.
The vertical axis is the proportion for each variant. (I should have removed the numbers). That's why the heights are the same. If it was the number for each variant, then blue would, we're told, be many times higher.
But look at the blue curve, you have a very small number of people that far away from the blue average, far enough along the pathogenicity axis to die. There are tables to look the proportions up; 3SDs is something like 0.15%, and so on.
The shape of the curve won't be correct, it would be flatter and the two curves would overlap, but you can see how a one-third-less severe disease can have much less than one third fewer people getting to the same illness/dying.
If you don't like it, draw your own curves, but the effect will be there.
I don't mind being wrong - tell me, as long as you're civil about it!
South Africa still say no deaths OF it : https://www.express.co.uk/news/world/1536157/south-africa-official-deaths-variant-omicron-covid
I'm no diseaseologist, but for delta, the average, most common case may be a few days ill, while some don't feel it at all and some die.
I know it varies by age etc etc but there must be some sort of distribution.
Let's assume it's a normal distribution.
Your stiffs are going to be up at the top end of illness. They're of the order of 1% at some some age so that's about 2.5 standard deviations from the mean, and higher. Black.
You can argue about the numbers...
The area under the curve represents the number in that illness group.
Now let's say omicron is two thirds as "dangerous" as delta. It must be some sort of function. A simple multiple may not be right but it's not utterly wrong.
If you have a better one, please show it.
So I've got the average/peak number, about two thirds across the graph, for omicron.
The vertical axis is the proportion for each variant. (I should have removed the numbers). That's why the heights are the same. If it was the number for each variant, then blue would, we're told, be many times higher.
But look at the blue curve, you have a very small number of people that far away from the blue average, far enough along the pathogenicity axis to die. There are tables to look the proportions up; 3SDs is something like 0.15%, and so on.
The shape of the curve won't be correct, it would be flatter and the two curves would overlap, but you can see how a one-third-less severe disease can have much less than one third fewer people getting to the same illness/dying.
If you don't like it, draw your own curves, but the effect will be there.
I don't mind being wrong - tell me, as long as you're civil about it!