Ok. So I finally automated my Z-score analysis of Israeli case data. I have yet to automate publishing the generated graphs to Twitter... but here comes 9 weeks of the same analysis methodology... so you can easily compare. First up 29th August to 4th September inclusive
2021-08-22 to 2021-08-28
2021-08-15 to 2021-08-21
2021-08-08 to 2021-08-14
2021-08-01 to 2021-08-07
2021-07-25 to 2021-07-31
2021-07-18 to 2021-07-24
2021-07-11 to 2021-07-17
2021-07-04 to 2021-07-10
What does all that mean? Well there are a number of questions. First off this data includes those who have recovered. There is a dataset that separates out positives of recovered, but the IMoH does not seem to provide the population numbers that would allow analysis with them
Second, we have that case detection is a determined (in part) by symptom expression. As we know the 💉 suppresses symptoms, cases in the vaccinated will be less likely to be detected, and that is pretty much what the z-scores show... however...
There is the very strange anomaly of cases in those who have received their 3rd shot but are not yet considered fully vaccinated. These are consistently significantly higher (but not higher than the unvaccinated). Why?
A not unreasonable assumption is that we would expect a similar level of presenting for testing across everyone who has at least 2 shots. Thus EITHER the "3rd dose puts you at a greater risk of infection during the first 2 weeks" conspiracy is true OR ...
The side-effects overlap with symptoms. If you have just got your 3rd dose, you are more likely to have the side-effects, you might confuse them with symptoms and present for testing, and so the hidden infection level is more likely to be exposed.
I think the second explanation is more likely and the implication would be that the positive case detection rate among the vaccinated is significantly lower than for the unvaccinated... perhaps by a factor of 5 to 10 if not more!
But who knows... unless we have whole population random testing, positive case numbers are not really all that useful in my opinion... but it's what we have
I see @duolingo didn’t practice “never deploy to production on a Friday”. They’ve managed to break all family plans. My wife is very very annoyed at having lost her ad free experience.
Any ETA on restoration? (hopefully not a case of disgruntled ex-employee on their way out!)
Remember folks, science can *never* prove something is true, it can only prove something is false, and like Sherlock, whatever is left standing must be true (until we prove even that false) @1000Frolly is saying that the data proves a hypothesis false… I see science at work
And if you want to explore some of the ways data can support @1000Frolly claiming a hypothesis is false, I suggest you have a look at the radiosonde data. Plot molar density against pressure and explain how you always get two linear regions (and sometimes a third)…
Also remember that the hypothesis @1000Frolly is claiming is false specifically requires that molar density vs pressure will be non linear as it critically relies on the absence of thermodynamic equilibrium vertically in the atmosphere, so linear regions are completely counter