by Rhoda Wilson, Expose News:
Batch analysis of the Czech Republic data comparing one-year post-injection all-cause mortality rates shows some Pfizer batches are 3 times deadlier than other batches from the same manufacturer when given at the same time to the same 5-year age group.
And a Moderna batch can be 8 times or more deadlier than a Pfizer batch given at the same time to the same age group.
This cannot happen if the vaccines are safe, Steve Kirsch writes.
TRUTH LIVES on at https://sgtreport.tv/
Covid Vax: Some Batches Increase Your All-Cause Mortality By 9x Or More
By Steve Kirsch
Note: You can generate the CSV file with the batch analysis (vax_4.csv) by cloning the Github repo, going to the code directory and typing “make vax.” If you just want to work with the data without regenerating it from the source, you can download the vax_4.xlsx file here. Feel free to analyse the data and publish your own analysis.
Over a 9x Increase in All-Cause Mortality Across Brands
Whenever you do batch analysis, the fairest way is to compare the one-year mortality rate between batches given in the same month to the same 5-year age range. This minimises confounders.
For example, let’s look at all the Pfizer and Moderna batches given to more than 100 people in February 2021 aged 70-74 and compute the one-year mortality from the time of the injection.
Do you see how there is a huge variation within the same brand? And an even larger variation across brands? For a safe vaccine, the one-year mortality rates should be very similar to each other. They are not. The Pfizer brands were within 2x of each other, but Moderna had over a 9x higher all-cause mortality.
Moderna public relations will tell you, “Nothing inspires safety like knowing you are getting a 9x higher all-cause mortality by choosing Moderna!” They should do this … people will eat it up.
Of course, health officials refuse to look at the data and the public is never told of the quality control problem.
More Than 3x All-Cause Mortality Variation Between Pfizer Batches
You can’t have a 3x higher all-cause mortality that depends on which batch you get. That’s insane. Here are two batches given in the same month to the same 5-year age range. You can repeat this for other younger 5-year age ranges and you get the same factor of 3 so this is not a fluke.
[The Fisher exact test is a statistical procedure used to determine whether there is a statistically significant association between two categorical variables.] The Fisher exact test shows it is highly unlikely that the two different batches are the same vaccine.
This means that the quality control is awful and is killing people.
If the safer batch is a placebo, the unsafe batch has a 3x higher one-year mortality risk. That is a train wreck.
Also, they can’t argue that this is because the “FC” batch was distributed to those in nursing homes because the effect happens in those 64 and younger and it isn’t there for older people!
The Batch Analysis
Pandas and dataframes make it so easy to analyse data like this. It was just one line of Python code to add the batch analysis the analysis already there:
[‘age’, ‘brand_2’, ‘batch_2’, ‘date_2’]
To keep things compact (the .xlsx file is just 1.2MB in size), I just looked at the codes for injection 2, but I could have looked at any injection number.
So, there is no excuse for the health authorities not having the resources to look at their own data.
Summary
This isn’t a close call.
The examples here took just minutes to find and they are not the only examples.
The data shows that there is no quality control on these vaccines. Getting these vaccines can triple or more your risk of dying from your baseline risk. This is unprecedented.
We know by now that the health authorities are never going to look at their own data, they are never going to admit they should have known from the data that they clearly had, they aren’t going to warn people, and they will not put any quality controls in place.
