New UK government data shows the COVID vaccines kill more people than they save

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Choo Choo

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I’ve been asking everyone: Show me the all-cause mortality data proving the vaccines are safe. I finally got some data. It’s from the UK government and it’s devastating. REALLY devastating.

Thank You Brother, Ricin

“O come, let us worship and bow down: let us kneel before the LORD our maker.”  Psalms 95:6 (KJV) 

New UK government data allows us to analyze the data in a way we couldn’t before. This new analysis shows clearly that the COVID vaccines kill more people than they save for all age groups. In other words, they shouldn’t be used by anyone. The younger you are, the less sense it makes.

Anyone can validate the data and methodology. The results make it clear that the COVID vaccines should be halted immediately.

Not a single public health authority in any country will have a conversation with us on the record to justify their vaccine recommendations or explain how this analysis is wrong. I wonder why?

What this means is that if you are 25 years old, the vaccine kills 15 people for every person it saves from dying from COVID. Below 80, the younger you are, the more nonsensical vaccination is. The cells with * means that the vaccine actually caused more COVID cases to happen than the unvaccinated.

Above 80, the UK data was too confounded to be useful. Until we have that data, it’s irresponsible to make a recommendation.

I describe below how you can compute this yourself from the UK data.

Please share this result on all your social media platforms.

Introduction

One of my friends recently sent me a link to the mortality data from the UK government Office of National Statistics from January 1, 2021 to January 31, 2022. I had not seen this data before so I analyzed it.

What I found was absolutely stunning because it was consistent with the VAERS risk-benefit analysis by age that I had done in November, 2021.

Where to get the UK government source data

The government data is archived here. You want to open the spreadsheet, and look at the spreadsheet tab labeled Table 6.

You can also access the original source at: https://www.ons.gov.uk/peoplepopulationandcommunity/birthsdeathsandmarriages/deaths/datasets/deathsbyvaccinationstatusengland which you can see at the top of the page.

In either case, you click the green button labeled “xlsx” to get the spreadsheet, then go to tab “Table 6”:

To visualize it, see the tweet below:

Note: The data is from England only, not all of the UK.

Where to get my analysis of the data

I annotated the UK source data and you can download it here. This makes it easier to see what is going on. You can see all the original data and my formulas for calculating the ACM ratios and risk benefit analysis on the Table 6 tab.

It is all in plain sight for everyone to see. I then copied values to the Summary and Exec Summary tabs.

Methodology

I compared the all-cause mortality (ACM) for people who got 2 shots at least 6 months ago with the unvaccinated. The 6-month time frame provides a minimum reasonable “runway” to observe the outcomes for the typical “fully vaccinated” person.

Summary of the data

This summary below (which I put on the Summary tab which is to the right of the Table 6 tab) shows the rates of all-cause mortality per 100,000 person-years for each age range and also shows the risk benefit ratio.

Here’s the legend for each column:

  1. A: age range for the row
  2. B: ACM rate for unvaxxed
  3. C: ACM rate for vaxxed
  4. D: Risk benefit calculation which is # non-COVID lives lost due to the vaccine / # of COVID lives saved from the vaccine. This is the single best metric for justifying the use of an intervention. The larger this number is, the less sense the intervention makes. A value >1 means the intervention should never be used. The cells with * means that the vaccine actually caused more COVID cases to happen than the unvaccinated. Note: you need to view the full spreadsheet to see the data used to calculate this number. You cannot do it from the summary data on this screen.
  5. E: ACM of vaxxed/ACM unvaxed, i.e., Column C/ Column
    B. A value >1 means the intervention should never be used since it is costing lives. This is a crude measure of the effectiveness of an intervention as we explain below.
  6. F: % of ACM deaths due to COVID, i.e., the fraction of all the ACM deaths that were caused by COVID.

The data clearly shows that any mortality benefit you get from taking the vaccine and lowering your risk of death from COVID is more than offset by the mortality you lose from the vaccine itself. This isn’t new. It is something I have been saying since May, 2021. But now I finally found the data where I could calculate it reliably.

In the Pfizer Phase 3 trial, there was a 40% increase in ACM in the vaccinated group. They killed an estimated 7 people for every person they saved from COVID!

In the Pfizer Phase 3 trial, there were a total of 21 deaths in the vaccine group and 15 deaths in the placebo group.

This 40% increase in the all-cause mortality in the trial (21/15=1.4) was of course dismissed as not statistically significant. While that is true, that doesn’t mean we shouldn’t pay attention to the number.

But now, based on the UK data, we know that the result in the Phase 3 trial wasn’t a statistical flu…

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