Data Avalanche Provides Proof of mRNA Disaster.

A “buried England” mRNA data avalanche has been exposed which means we can now compare the percentage of all-cause death by vaccination status with the percentage of Vaccine Uptake.

Comparisons have been made by a Substack author, who goes by the name of The Nobody who Knows Everybody, who asserts that the data “provides proof of a mRNA disaster.”

The author who describes themselves as “a logical and strategic thinker; now well connected with heroic doctors and politicians” writes that “Any Religious Body, Health Authority, Health Worker, Politician, Pharmacy Executive, Statistician, Judge, or any Adult for that matter now has a Duty to Protect their communities from mRNA,” shows why they have come to that conclusion in the work below.

Proof of a mRNA Disaster! 

The following charts show Vaccine Uptake rates of 18 years and over Adults in the population of “England” versus the percentage of all-cause deaths represented by the different Vaccine Uptake Groups of that same population.

Vaccine Uptake Groups of “England”
Unvaccinated
1 Dose or more
2 Doses or more
3 Doses or more
The sample size we are dealing with is the 18 years and over Adult population of England which is a sample size in excess of 50 Million People
The Covid-19 “mRNA” based Vaccines and their rollout were based on a sample size trivial in comparison with Data and its interpretation controlled by the Companies standing to profit Billions from their indemnity-free sales.

The Graphs will represent one of three scenarios:

Scenario 1

The  “Vaccination” has ZERO impact on one’s likelihood to die (from all causes):
When looking at the percentage of Vaccine uptake in a given population and when looking at the percentage of deaths (from all causes) in that same population these percentages would simply match.

Example: A population comprises 100,000 people
85% of that Population is Vaccinated
In one month there are 100 Deaths (from all causes)
85% of the Deaths would be among people that were Vaccinated (85) – This is the SAME as the 85% of the population represented by the Vaccinated
15% of the 100 deaths would be among people that were Unvaccinated – This is the SAME as the 15% of the population represented by the Unvaccinated

***IMPORTANT***
COMPARED TO THE PERIOD PRIOR TO VACCINATION YOU WOULD NOT EXPECT TO SEE AN INCREASE IN DEATHS (ALL-CAUSE)

Scenario 2

“Vaccination” REDUCES one’s likelihood to die (from all causes) – as is the claim by indemnified mRNA merchants
When looking at the percentage of Vaccine uptake in a given population and when looking at the percentage of deaths (from all causes) in that same population there would be a LOWER percentage of Deaths with a vaccinated Status
Example: A population comprises 100,000 people
85% of that Population is Vaccinated
In one month there are 100 Deaths (from all causes)
75% of the Deaths would be among people that were Vaccinated (75) – This is LOWER than the 85% of the population represented by the Vaccinated
25% of the 100 deaths would be among people that were Unvaccinated – This is HIGHER than the 15% of the population represented by the Unvaccinated

***IMPORTANT***
COMPARED TO THE PERIOD PRIOR TO VACCINATION YOU WOULD NOT EXPECT TO SEE AN INCREASE IN DEATHS (ALL CAUSE) IN THIS SCENARIO YOU WOULD EXPECT TO SEE A DECREASE IN ALL CAUSE DEATHS

Scenario 3

“Vaccination” is NEITHER SAFE NOR EFFECTIVE and INCREASES one’s likelihood to die (as is the Hypothesis* to Explain Excess Deaths that track the release of these products onto the public and as could be predicted with the amount of risk in the technology):
When looking at the percentage Vaccine uptake in a given population and when looking at the percentage of deaths (from all causes) in that same population there would be a HIGHER percentage of Deaths with a vaccinated Status
THIS WOULD BE A DISASTER!
Example That would Match this DISASTER scenario:
A population comprises 100,000 people
85% of that Population is Vaccinated
In one Month there are 100 Deaths (from all causes)
95% of the Deaths would be among people that were Vaccinated (95) – This is HIGHER than the 85% of the population represented by the Vaccinated
5% of the 100 deaths would be among people that were Unvaccinated – This is LOWER than the 15% of the population represented by the Unvaccinated

***IMPORTANT***

Further, with a VACCINATION DISASTER SCENARIO, you would expect to see an increasingly disproportionally higher representation of the all-cause deaths within each vaccination group with each additional dose.

Below is the UK Government Data Avalanche graphed with three simple graphs.
You can’t conspire to produce Government Data.
SCENARIO 3 is VERY CLEAR.

1+ Dose(s) is Bad

2+ Doses is Worse

3+ Doses is worse

Data Source
All Cause Deaths by Vaccination Status of the Specific Population
UK’s Office for National Statistics

“We are the UK’s largest independent producer of official statistics and its recognised national statistical institute. We are responsible for collecting and publishing statistics related to the economy, population, and society at national, regional, and local levels. We also conduct the census in England and Wales every 10 years.”

6 July 2022 Report: Deaths occurring between 1 January 2021 and 31 May 2022
25 August 2023 Report: Deaths occurring between 1 April 2021 and 31 May 2023
These two reports found here stitch together well to give the All-Cause Deaths Data over the Vaccine Roll out Period Starting in January 2021.

Data Source
Vaccine Uptake of the Specific Population
Buried deep in The UKHSA Fortnightly National Influenza and COVID-19 Report
“National flu and COVID-19 surveillance data report: 6 July 2023 (week 27)”.
Found on the UK Government website here
The actual data is buried in a supplementary ODS-type file (It can be opened in Excel)
This ODS Data file, when you know where to look, holds data that has been effectively withheld from the common public knowledge until now.
There is an obscure tab (one of more than 40 Tabs in this data file) called “Figure_19__COVID_Vac_Uptake”
Looking at Fig 19 of the week 27 report there is ABSOLUTELY NO WAY anyone “on the outside” of the organisation that prepared this report or those collaborating with this organisation would have known to look for this CRITICAL COMPARISON DATA
I Illustrate this point below:

Figure 19 of the report ONLY indicates a focus on the over 75’s and immunosuppressed vaccine uptake of the spring 2023 boosters.

But the data of this table in the buried “public domain” contains the data in this sheet which is critical and MUST BE MADE PUBLIC KNOWLEDGE rather than remain deeply buried information in the “public domain”.File link: Week 27 report vaccine Uptake

Data Files

The above-referenced three data files are also uploaded to this Substack should they be altered or removed from their current locations and for the convenience of others to easily download.

Referencetable06072022accessible 538KB ∙ XLSX file Download

Referencetableaug2023 887KB ∙ XLSX file Download

Weekly Influenza And Covid19 Report Data Summer W27 Report 1.09MB ∙ XLSX file Download

The last file was converted to an Excel File as Substack does not support ODS files

The following three files are the above three files where the relevant sheet within the worksheet has columns added to arrange and present the data into a meaningful series of relevant data for the critical charts above.

Data Files Workings:

Referencetable06072022accessible With Workings On Sheet Table 2 See Extra Columns L Onward 794KB ∙ XLSX file Download

Referencetableaug2023 With Workings On Sheet Table 2 See Extra Columns L Onward 1.58MB ∙ XLSX file Download

Weekly Influenza And Covid19 Report Data Summer W27 Report With Workings On Sheet Figure 19 Covid Vac Uptake See Extra Columns Et Onward 1.29MB ∙ XLSX file Download

Compiled Data File:

Uk Vaccine And Deaths Datasets Compiled For Charats Data Jan2021 Through May 2023 51.9KB ∙ XLSX file Download

*HYPOTHESIS

The “Vaccination” is Neither Safe Nor Effective
The Covid-19 mRNA vaccines are more accurately described as Lipid Nano Particle Synthetic Messenger RNA Genetic Instruction products that have the following wild cards:

i) A delivery system of highly inflammatory Lipid Nano Particles (LNP)
ii) An Uncontrolled body-wide biodistribution of the LNPs
iii) The LNPs carry Genetic Instruction in the form of synthetic messenger RNA
iv) The synthetic nature of the messenger RNA carries the following known risks

a) Synthetic messenger RNA have an uncontrolled extended life of protein-producing instructions that is ORDERS OF MAGNITUDE longer than natures messenger RNA
Life, as it has evolved for mammals, has a natural off switch for the protein-producing messenger RNA it creates that is limited to two days and usually a lot shorter.
b) Synthetic messenger RNA produced with warp speed indemnity has fragmented genetic instructions that come from a human factory environment compared to natural messenger RNA that is produced deep in the Nucleus of our bodies with a purity beyond comparison with a Pfizer or Moderna laboratory or manufacturing facility
c) With the uncontrolled biodistribution of Synthetic messenger RNA there is an endless combination of extra protein-producing burdens throughout the body and its various cell types already dedicated to maintaining a delicate system and schedule of producing natural proteins such as hormones and enzymes; critical for the healthy functioning of our body.
v) The genetic instructions of the Synthetic messenger RNA are instructions to produce a known antigen (The Covid-19 Spike Protein) and it is a known cause of vasculitis and autoimmune reactions. Combining this instruction with an uncontrolled biodistribution is a predictable recipe for disaster;
a disaster that will show itself in deaths and hospitalizations when regulatory authorities fail and the Avalanche of Data is compiled.
vi) No long term safety data. Given the combinations of what is uncontrolled, unknown, and divorced from the bodies natural balance remotely sufficient safety data would take a millennium to obtain; even with billions of guinea pigs.

For the Data Sceptics and the Die Hard mRNA Investors/Cabal:

There will be attempts to muddy the water and for claims to be made that there are significant variations and differences of populations sets in the data compiled.
None of them will hold up to a bright light and to quickly dispel the notion that the Data is taken for different regions or different populations:

Data Source
All Cause Deaths by Vaccination Status of the Specific Population
UK’s Office for National Statistics (ONS)
In the Cover sheets to both files used
“Age-standardised mortality rates for deaths by vaccination status, England”
The reported Deaths are also limited to Age Group 18 and over
The ONS have the following “User guide to mortality statistics”
Chapter 5 of this guide states:
“Published mortality statistics are based on deaths registered in England and Wales, so include some deaths of residents of other UK countries and of visitors, where the death occurred in England and Wales.”
To see the extent of how this might affect the comparative populations it then produces a table that shows this will affect the number of deaths reported by between 0.1 and 0.2 %

Data Source
Vaccine Uptake of the Specific Population
As Figure 19 states the Population base for the Data Base the figure is drawn from is for is “For those living and resident in England”
Further, the Data was divided into age groups so it was possible to restrict the used data to the Age groups 18 and over to match the all Cause Deaths by Vaccination Status dataset.

It is helpful to appreciate just how delicate the Genetics of our bodies are and how reckless it is to deploy genetic instructions with unknown duration, unknown biodistribution, unknown deviation from natural purity, and unknown impact on all the cell types and the bodies related functions that rely on those cell types to operate without interference and without the production of synthetic-foreign proteins that can easily have the body attack its own cells that express these synthetic foreign proteins.

Source The Nobody Who Knows Everybody on Substack