🔥 BREAKING 🚨 - UK ONS All-Cause Mortality Data for England Reveals:
‼️ The vaccine has never significantly protected the vulnerable 70+ from death!
‼️ The vaccine seems to lead to more deaths in 2022+! #COVID19#Covid#AllCause#ONS#DiedSuddendly#Corona#Coronavirus
🔥🔥🔥🔥🔥
Want to know how the Pfizer Vaccine fraud worked?
Yes, we can actually call it fraud now!
Read this thread 🧵 ⬇️⬇️⬇️
Pfizer told us their vaccine is 95% effective (🤡).
What that really means is it's effective against testing positive - they never published the actual rate of illness.
Corona-like-illnes (CLI) is the actual relevant endpoint, that should have been measured in the RCT's.
Now we have more data:
"The vaccine only reduced the incidence of COVID-like illness by a relative 9.4% from an absolute 18% to an absolute 16.3%, [..]"
--> That's a reduction 1.7%, or 9.4% in relative terms - but what a minute, what about the vaccine side effects?
Diamond Princess 2020 - only 17% of passengers were PCR positive, less than 9% symptomatic.
83% were not infected and already immune, hence PFR = IFR = 7/3700 = 0.19%!
0.19% is exactly in line with a regular flu. 83% not infected is also in line with a regular flu season. There was basically no flu in 2020..
Here's a detailed age break down.
Eric Feigl-Ding, and others, spreads vaccine propaganda with supposedly scientific models.
I explain why this is clear unscientific misinformation here in the thread!
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Ein Molekularbiologe verbreitet mit angeblich wissenschaftlichen Modellen Impfpropaganda.
Warum es sich hier um klare unwissenschaftliche Missinformationen handelt, erkläre ich hier im Thread!
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In weniger als einer Stunde und mit ein paar Zeilen R Code habe ich ein ähnliches Modell - welches auf Fehlannahmen beruht - nachgebaut: github.com/USMortality/ch…
Also, wie funktioniert es?
Ganz einfach, es beruht auf der - nie wissenschaftlich belegten Annahme, dass die Impfung zu ~90% vor dem Tod schützt.
So können wir ein Modell erstellen, das die Case Fatality Rate (CFR) ohne angeblichen Impfeffekt berechnet.