Better to Not be "Vaccinated" Unless You're Over 64?
Somebody got some ‘splainin’ to do!
According to “the” science, the so-called “vaccinated” have a higher rate of covid-19 than the so-called “unvaccinated”. Aegis Sciences Corporation and Walgreens has a Covid-19 Index. On page 2 there is the following chart.
Note that they divide between “2 doses greater than 5m ago” and “2 doses less than or equal to 5m ago, therefore it is helpful to average those figures as I have.1
According to this, the lowest positivity rate for Covid-19 is for those who did not receive the injections. People with 3 doses have the highest rate.
The only exception would be if you isolate for people 65 and older. According to this data, people of that age group with 1 dose are at the lowest at 18.3%, next would be people in that age group that have had no doses at 19%, then comes 2 doses averaging to 20.5% and the highest would be 3 doses at 21.3%.
This data suggests that the rate of covid-19 positivity among people 65 and older, 1 dose is better than none by 0.7%, but getting a 2nd is worse than no doses by 2.2% and getting a 3rd dose is worse than no doses by 3%.
Of course, it is fair to say that this study is not conclusive, as long as it is acknowledged that no studies are.
So, although it was reported that “Official Data shows Children are up to 52 times more likely to die following Covid-19 Vaccination than Unvaccinated Children & the ONS is trying to hide it”, that data is not conclusive. But there’s some ‘splainin’ to do.
Ultimately, the burden of proof lies belongs to the person making the initial claim. In this global covid-19 situation, the initial claim is that it is deadly enough to justify vaccine mandates, mask mandates and lockdowns. The truth of that initial claim has not been established provisionally, let alone conclusively.
I refer to the “so-called “vaccinated”” with quotes around “vaccinated” because these experimental drugs did not fit the definition until, for example, the CDC and Merriam-Webster’s Dictionary artificially altered the definition. These alterations are artificial because they have no authority to do so. Definitions are formed by the speakers of the language. Dictionaries describe the meanings of words in a given language. They do not decide. The do not proscribe. The describe. The CDC also has no authority to decide or proscribe alterations in the language.
In trying to explain this fact away, USA Today, for example, or the Miami Herald, Politifact, or Forbes only lay out that this fact is true. If you only read the headline you might think otherwise but if you actually read the body you will se that like many other such partisan “fact-checking” they tell the truth in the body so they can say they told the truth but they are hoping you only read the misleading headline and remain ignorant.
Don’t.
By the way, the Washington Post reported, “Mask Mandates Didn’t Make Much of a Difference Anyway”, Fauci acknowledged that lockdowns don’t help and Bill Gates admitted that covid-19 is not any more serious than other varieties of the flu.
What about that death count? It’s BULLSHIT!
First of all, the CDC and NCHS has made it perfectly clear to the medical profession that a person doesn't have to die from covid or even HAVE covid to be marked down as having died from covid (see the screen shot below).
Secondly, it is profitable to artificially inflate the death count because the government in-effect, pays them to claim that patients who did not die from covid-19 did die from covid-19.
When given the opportunity to legally make a lot of money, they will take that opportunity because they are not saints or angelic beings. In fact, as corporations, hospitals are OBLIGATED to profit. They are obligated by structure and motivated by money to lie about the death count of covid-19.
The death counts are based on lies, the lockdowns are counter-effective, the masks don’t work and the vaccines are dubious. See here, here, here, here, here, here, here and so on.
Thank you for reading. ~ Justin Case
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People with 0 doses are at 18.3%
People with 1 dose are at 24.4%
People with 2 doses average to 23.75%
People with 3 doses average to 25%
If you isolate it to 5-11 year old subjects…
People with 0 doses are at 23.6%
People with 1 dose are at 27.9%
People with 2 doses average to 26.6%
No data for 3 doses.
If you isolate it to 12-17 year old subjects…
People with 0 doses are at 27.2%
No data for 1 dose
People with 2 doses average to 27.95%
People with 3 doses average to 31.55%
If you isolate it to 18-44 year old subjects…
People with 0 doses are at 17.4%
People with 1 dose are at 24.2%
People with 2 doses average to 23.3%
People with 3 doses average to 26.5%
If you isolate it to 45-64 year old subjects…
People with 0 doses are at 16.2%
People with 1 dose are at 24.4%
People with 2 doses average to 22.9%
People with 3 doses average to 24.7%
If you isolate it to subjects who are 65 or older…
People with 0 doses are at 19%
People with 1 dose are at 18.3%
People with 2 doses average to 20.5%
People with 3 doses average to 21.3%