The Zoe app is now clearly indicating a sudden peak in the cases, a very familiar signature in the data, the we have seen several time already.
Here's the raw plot
And here is another plot that zooms in on the peak to see each daily change
In a week, growth collapsed from 12k extra new cases per day to just 5k extra new cases per day. It's another sudden end to a long explosive burst of infection, it's typical corona virus, end of surge behaviour that we have seen so often before. I still have no idea what causes these sudden lunges and lurches. To me the closest analogy are those motorway conditions where the traffic is moving well and a small incident causes it to suddenly all to come to a juddering halt.
The most obvious regional beneficiary of this collapse in cases is scotland, shown here as cases collapse.
I think the third wave is washed up.
This plot is from the main page of LS, and I'd like to offer view on what it portrays:
Screenshot 2021-07-10 at 21.18.07.png
You can't split the impact of herd immunity between vaccinated and unvaccinated like that; there is one human population and one set of infected humans that might infect others.
Thus the delayed peak in vaccinated is very odd. Normal theories of disease propagation don't explain it.
It might be explained by the vaccinated population having a much longer period of pre-symptomatic covid compared with the unvaccinated.
If this is the case then pertinent questions might be whether they are infectious in that period, and for how long it lasts.
We still know very little about the behaviour of covid in the vaccinated, and particularly the behaviour of the new partial escape variants. This is rather worrying given how many have been vaccinated.
But that's what you get when you compress years worth of clinical trials into 6 months and then try to jab everyone in sight.
there is one human population and one set of infected humans that might infect others.
Yet that is what appears to have occurred . And it is a slightly inconvenient fact.
Normal theories of disease propagation don't explain it.
That is normally regarded as the point when "Normal theories of disease" are rejected, and a new theory is adopted. Your theory only needs to be disproved once, and it is game over for your theory.
It might be explained by the vaccinated population having a much longer period of pre-symptomatic covid compared with the unvaccinated.
Might be? But that is not the Normal theory of disease propagation, so you are stuck in a rut. But even if it were so, which it you think it might be, why would cases in the unvaccinated suddenly surge downward at the exact same instant? It's worse than a rut for you, it's a dead end for your illogical ideas.
are they infectious in that period, and for how long it lasts.
As I say, that is not the Normal theory of disease propagation. You are hoist by your own Petard.Perhaps you are saying things you don't really mean? Perhaps we have uncovered have your hidden agenda against vaccination. There is am economical explanation for your antics, if you could only answer one question honestly: would you prefer vaccines to not work?
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Forget population wide herd immunity - most of the 40+ age group as
Astrazenica which efficacy against infection is far far too low to ever do it.
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AZ is what it is (you are on as hobby horse there) but there is also the huge difference in social habits between people of say 20 an people if (e.g. )55 or so,
Herd immunity is going to take years
Perhaps, but I only care once people stop dying of it, which is now onwards. btw: long covid is a crock of shit, people need to be much less lazy.
the third wave is washed up ..
The other, famous physical world analogy to this abrupt reversal in a trend is the transistor, the transistor affects enormous change to throughput (current .)Via tiny alterations in the control, hence the transistor is referred to as an amplifier. The device is better described as an inverse amplifier. It certainly amplifies the control signal. Hence it seems to me that the theory wrt growth in disease needs an update. When an infectious disease is close to its maximum capacity of growth, only very slight increase in the control factor causes an instant slump in cases. Such as we see here, today:
Students of electronics will recognise the curve at once of course. but for those who are a bit rusty:
So strangely the virus has somehow got itself into a configuration where we see typical signatures of amplification. Here is a real signature of a transistor.
