This one is for the real stats folks.

Let's deal with some objections to the deaths after flu vax/deaths after Covid vax comparison.

1) I agree Covid vaccine deaths are probably more likely to be reported than flu vaccine deaths. Are they 900 times more likely? Very doubtful...

2) Here's one good reason to think the gap may be small. The ratio of non-serious to serious Vaers reports is far HIGHER for the flu vax than for Covid. In other words, people have basically STOPPED filing non-serious event reports after Covid shots, because they are so common...
3) If people were clogging VAERS with Covid vaccine side effects reports because they are so sensitized to them, we'd see the opposite - tons of reports in every category. We aren't, though.
4) Children aside (and children do receive a lot of flu shots), the idea that the Covid vaccine is going to a meaningfully different population than the flu vaccine is nonsense. Flu campaigns are targeted at the elderly and healthcare workers, just like the Covid vaccine...
5) The correct area under the curve at risk post-Covid vaccinations is not 41 million doses x 8 weeks of followup. It's more like 41 million doses x 3 days. READ THE VAERS REPORTS YOURSELF. I have. The "he was hit by a bus a week after being vaccinated" isn't what's in there...
6) Nearly all of the deaths are under a week out from the vaccine (occasionally sequalae more than a week out to illness that began sooner). This is meaningful because the vaxxers keep saying, 50,000 people out of 41 million would have died anyway in 8 weeks, nothing to see here.
7) In reality, in the US, in a population of 41 million, about 1,000 die every day (this is VERY age-stratified, but it is also, HEALTH stratified, and making a real comparison to the vaccinated population is tricky). The point is that 1,170 deaths is NOT a trivial number...
8) Once you use the correct denominator. Especially since I don't think anyone believes VAERS is capturing all post-vaccination severe adverse events, including deaths. Is it capturing 10%? 20%? Can anyone guess?
9) Ultimately, we have many, many unknowns in the statistics. That's why examining THE REPORTS THEMSELVES is so important. Read a sample for yourself before you tell me, nothing to see here.

More from Health

1/
Remember woman who tuk multiple @SriSriTattva products 4 range of problems frm diabetes 2 gas 2 liver disease & developed liver failure, listed for liver transplant?
Here is original thread:
https://t.co/PXxI1Slyv2
23 samples, Analysis results
#MedTwitter #livertwitter


2/
Before I go into results, I must say this was overwhelming. There was SO MUCH the lab identified, impossible to put everything here. So I made a summary. At the end of this thread, I have linked a full analysis described in Excel format. Some results were VERY concerning

3/
How did we analyse?
Here R links 2 methods
They R high end, done under strict protocols
Frm Ministry of Forest, Environment, Climate / NABL approvd Lab
ICP-OES https://t.co/O1CLhqVQAu
GC MSMS https://t.co/zRJoXyWQIr
FTIR https://t.co/goAembQ08p
Here is list V analysed 👇


4/
Sample names written on top (each column).
First 5 samples: C what we identified in #Ayurveda #medicines
Antibiotics
Steroids (anabolic/synthetic)
#NARCOTICS - LSD, Morphine
Blood thinners (possible reason Y bleeding tests were off the roof in the patient)
Heavy metals!


5/
Next 5 samples (total 10 now)
Mercury is clear winner. Almost all samples
See controlled substances - Butyrolactones https://t.co/CPz0FwPEOm, methylamine https://t.co/OZnXY7U9UQ
Alcohols, industrial solvents
Rare metals - cobalt, lithium
Again lots of blood thinners
#Ayush

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