The PfizerGate Scandal: A Shocking tale of a Global Government Plot to hide the COVID Vaccine’s Immune System Destruction

Are you ready to learn the shocking truth about the Covid-19 vaccines?

Health authorities around the world have been caught red-handed manipulating figures in an attempt to keep the public in the dark about the devastating side effects of the injections.

Don’t believe the lies and propaganda being spread by the mainstream media – keep reading to discover the full extent of this cover-up and the real impact the vaccine is having on people’s health.

Get ready for a bombshell revelation that will shake the foundations of everything you thought you knew about the pandemic.

Let’s not lose touch…Your Government and Big Tech are actively trying to censor the information reported by The Exposé to serve their own needs. Subscribe now to make sure you receive the latest uncensored news in your inbox…

In November 2021, the Chairman of the South African Medical Association, Dr. Angelique Coetzee, made a “shocking” discovery: the Omicron variant of Covid-19 was causing a mild form of the flu in South Africa.

As a practicing GP during the pandemic, Coetzee had seen plenty of Omicron cases and deduced from her observations that it led to a mild form of illness comparable to the common cold.

But what does “mild” mean in the context of medicine?

Coetzee explained to the German newspaper Die Welt that, according to the World Health Organization’s definition, “mild COVID-19 disease” is characterized by patients who can be treated at home and do not require oxygen or hospitalization.

In contrast, serious illness is defined by acute pulmonary respiratory infections that require oxygen or even artificial respiration.

Coetzee went on to reveal that “European officials” had pressured her to deny this truth, likely because it was not what the “gene-corrupting drug pushers” wanted the public to hear.

Despite the pressure, Coetzee remained steadfast in her belief that Omicron was a mild form of the flu that did not cause hospitalization or require oxygen, and was not an acute respiratory infection like the alleged Delta variant.

“I was told not to publicly state that it was a mild illness. I have been asked to refrain from making such statements and to say that it is a serious illness. I declined,”

Who were the mysterious “European officials” who pressured the Chairman of the South African Medical Association, Dr. Angelique Coetzee, to keep quiet about the Omicron variant’s mild symptoms?

Coetzee did not specify, but she did reveal that she faced criticism from authorities in the United Kingdom and the Netherlands.

South African officials, on the other hand, did not try to pressure her into hiding the truth.

It appears some powerful players were determined to keep the public in the dark about the true nature of the alleged Omicron variant.

What could they be hiding, and why were they so eager to suppress this information?

These are just a few of the questions that beg for answers in this intriguing tale of cover-ups and corruption.

Dr Coetzee explained –

“What I said at one point—because I was just tired of it—was: In South Africa, this is a mild illness, but in Europe, it is a very serious one. That’s what your politicians wanted to hear.”

These things were reported in several news sources on February 10th. 

In November 2021, 23% of South Africa’s population was fully vaccinated against Covid-19. This meant that the Omicron variant, which caused a mild form of the flu, only affected the unvaccinated population.

Unlike the Delta variant, Omicron did not cause hospitalization, did not require oxygen, and did not result in acute respiratory infection.

However, these facts were being covered up by European governments, according to Dr. Angelique Coetzee, the Chairman of the South African Medical Association.

During November, South Africa was in the midst of summer, a time when mild flu cases are not typically severe enough to send people to the hospital in large numbers. Yet, in Australia, another Southern Hemisphere country, many people were being hospitalized with Omicron.

The correlation between vaccination and severe flu symptoms during the summer months raises important questions about the safety and effectiveness of the Covid-19 vaccine.

This anomaly can be explained by the fact that these individuals were fully vaccinated, and therefore more susceptible to VAIDS (vaccine-induced immune deficiency syndrome).

The first reported evidence of full-blown VAIDS occurred in New South Wales (NSW) from January 1st to 8th, 2022, among official Government data related to the Omicron variant.

The Australian Cover Up

The Expose published shocking figures on January 28th, 2022 that revealed a staggering case rate ratio of 10.72 to 1 among fully vaccinated individuals versus unvaccinated individuals in New South Wales (NSW) during the first week of January 2022.

In other words, 99.5% of Omicron cases were in the fully vaccinated population, while only 0.5% of cases were in the unvaccinated population.

But as soon as these figures were made public, the State Government began manipulating them in an attempt to cover up the vaccine-generated catastrophe. The government’s efforts to obscure the truth only served to deepen the mystery surrounding the true impact of the Covid-19 vaccine on public health.

https://www.health.nsw.gov.au/Infectious/covid-19/Documents/covid-19-surveillance-report-20220113.pdf
https://www.health.nsw.gov.au/Infectious/covid-19/Documents/covid-19-surveillance-report-20220120.pdf
https://www.health.nsw.gov.au/Infectious/covid-19/Documents/covid-19-surveillance-report-20220201.pdf
https://www.health.nsw.gov.au/Infectious/covid-19/Documents/covid-19-surveillance-report-20220204.pdf

In the first week of January 2022, the number of unvaccinated individuals with Omicron in New South Wales (NSW) rose from 2,775 to 3,552, and by the third week, it had reached 72,772.

Meanwhile, the number of fully vaccinated individuals with Omicron increased from 108,056 to 267,381 in the first week, and by the third week, it had reached 438,255. This represented a case ratio of 202.5 to 1 between the fully vaccinated and the unvaccinated.

However, the NSW government began manipulating these figures as soon as they were called into question by The Expose on January 28th.

By February 8th, the case ratio between the fully vaccinated and the unvaccinated had fallen to 0.95 to 1, with more Omicron cases reported in the unvaccinated population. This was despite the fact that 95% of the population of NSW was fully vaccinated.

This blatant fraud by the government of NSW demonstrated that the health of Australians was not as important to them as selling vaccines.

The government’s actions made it no different from a profit-driven drug pusher, willing to sacrifice the well-being of its citizens for financial gain. This was just one example of the Pfizergate vaccine damage cover-up, but it was by no means limited to Australia. The situation in Canada, the land of the moose, is also worth examining.

The Canadian Cover Up

The Canadian government employed a multi-stage cover-up to hide the truth about the impact of the Covid-19 vaccine.

Firstly, it is nearly impossible to obtain past issues of its Epidemiological summaries. While the Australian government makes all of its past reports easily available as links to pdfs, the Canadians make nothing available beyond the current report.

The only way to access past reports is through the Wayback Machine at web.archive.org, but this process is extremely difficult and time-consuming. The Wayback Machine often fails to load pages, loads only part of a page, or mixes up information from different reports, making it a frustrating and tedious task to piece together the data.

If you wish to spend a few millennia wrestling with a really annoying AI please visit –  https://web.archive.org/web/*/https://health-infobase.canada.ca/covid-19/epidemiological-summary-covid-19-cases.html 

Secondly, the Canadian government provides cumulative figures dating back to the start of vaccination, which makes it hard to see the fine details of the current week’s data amidst all the other weeks’ data since vaccination began in December 2020.

To work around this, we can subtract two cumulative figures ending on dates one week apart.

Thirdly, and most cynically, the government applies the European 2013 age-standardizing mortality formula to case numbers and hospitalizations. This is outright fraud, as case rates are not affected by the age of the patient in the same way that death rates are.

It is like trying to compensate for case rates by looking at how well people cook spaghetti in different age bands – it is completely invalid.

To obtain the unvaccinated case rates per 100k of the unvaccinated population in Canada, we need to first determine the total population of Canada, as well as the population of those aged 12 and over and those aged 5 and over.

Based on data from statistique.quebec.ca, the total population of Canada is 38,246,108, with 33,482,789 aged 12 and over and 36,363,537 aged 5 and over.

The Reports used for the analysis can all be viewed here –

• Oct 2 – https://web.archive.org/web/20211020075926/https://health-infobase.canada.ca/src/data/covidLive/Epidemiological-summary-of-COVID-19-cases-in-Canada-Canada.ca.pdf 
• Oct 9 – https://web.archive.org/web/20211027154438/https://health-infobase.canada.ca/covid-19/epidemiological-summary-covid-19-cases.html#a9 
• Oct 9 – https://web.archive.org/web/20211102202548/https://health-infobase.canada.ca/src/data/covidLive/Epidemiological-summary-of-COVID-19-cases-in-Canada-Canada.ca.pdf
• Oct 16 – https://web.archive.org/web/20211104153557/https://health-infobase.canada.ca/covid-19/epidemiological-summary-covid-19-cases.html 
• Oct 23 – https://web.archive.org/web/20211112151805/https://health-infobase.canada.ca/covid-19/epidemiological-summary-covid-19-cases.html 
• Oct 30 – https://web.archive.org/web/20211120122253if_/https://health-infobase.canada.ca/src/data/covidLive/Epidemiological-summary-of-COVID-19-cases-in-Canada-Canada.ca.pdf 
• Nov 6 – https://web.archive.org/web/20211128152117/https://health-infobase.canada.ca/covid-19/epidemiological-summary-covid-19-cases.html (incorrectly labelled as Nov13)
• Nov 6 – https://web.archive.org/web/20211128000628/https://health-infobase.canada.ca/covid-19/epidemiological-summary-covid-19-cases.html  (Nov6 pop Nov13 Cases)
• Nov13 – https://web.archive.org/web/20211207205042/https://health-infobase.canada.ca/covid-19/epidemiological-summary-covid-19-cases.html  
• Nov 20 – https://web.archive.org/web/20211211000508/https://health-infobase.canada.ca/covid-19/epidemiological-summary-covid-19-cases.html 
• Nov 27 – https://web.archive.org/web/20211218044638/https://health-infobase.canada.ca/covid-19/epidemiological-summary-covid-19-cases.html 
• Dec 4 – https://web.archive.org/web/20211223170506/https://health-infobase.canada.ca/covid-19/epidemiological-summary-covid-19-cases.html
• Dec 4 – https://web.archive.org/web/20211223231903/https://health-infobase.canada.ca/covid-19/epidemiological-summary-covid-19-cases.html   
• Dec 11 – https://web.archive.org/web/20220103173009/https://health-infobase.canada.ca/covid-19/epidemiological-summary-covid-19-cases.html 
• Dec 18 – https://web.archive.org/web/20220108083517/https://health-infobase.canada.ca/src/data/covidLive/Epidemiological-summary-of-COVID-19-cases-in-Canada-Canada.ca.pdf 
• Dec 25 – https://web.archive.org/web/20220117211207/https://health-infobase.canada.ca/covid-19/epidemiological-summary-covid-19-cases.html 
• Jan 1 – https://web.archive.org/web/20220124194636/https://health-infobase.canada.ca/src/data/covidLive/Epidemiological-summary-of-COVID-19-cases-in-Canada-Canada.ca.pdf 
• Jan 8 – https://web.archive.org/web/20220201164337/https://health-infobase.canada.ca/covid-19/epidemiological-summary-covid-19-cases.html 
• Jan 15 – https://web.archive.org/web/20220206015044/https://health-infobase.canada.ca/src/data/covidLive/Epidemiological-summary-of-COVID-19-cases-in-Canada-Canada.ca.pdf 
• Jan 22 – https://web.archive.org/web/20220209162204/https://health-infobase.canada.ca/src/data/covidLive/Epidemiological-summary-of-COVID-19-cases-in-Canada-Canada.ca.pdf

Here are the raw cumulative data from the Epidemiological-summary-of-COVID-19-cases produced by the Canadian Government from October 2nd 2021 to January 22nd 2022 –

The following table shows the cases, hospitalizations, and deaths by vaccine status by week in Canada, deduced by subtracting one week’s cumulative figures from the previous week’s cumulative figures.

The rates of cases, hospital visits, and deaths per 100k are then calculated using the population figures in column 2.

The immune/vaccine efficiency percentage is calculated using the normalised case rate ratio formula of Pfizer.

This data excludes the 14-day period from December 4th to 18th, during which the data for December 11th was omitted due to it being prepared around Christmas.

he data from Canada reveals an interesting anomaly: it appears that only the unvaccinated population celebrated Christmas, as the blue line (representing the unvaccinated) dropped to zero during the Christmas week before bouncing back above the purple line (representing the single vaccinated).

This could be due to Jesus protecting the unvaccinated from Omicron over the holiday, or it could be a statistical quirk.

Until Omicron hit in December, the unvaccinated population (blue line) did slightly better than the single-vaccinated population (purple line).

This is because one dose of the vaccine does not cause VAIDS (vaccine-induced autoimmune deficiency syndrome).

The double vaccinated population (red line) did better than all other groups until Omicron when it experienced a dramatic increase in cases – a clear indication of VAIDS.

This graph clearly shows the degradation of the immune system from 60% to 20% in just 10 weeks, followed by a dramatic drop to -98.8% in the Christmas week (likely due to the unvaccinated population celebrating Christmas more than the vaccinated, as seen in the line graph above). The immune system then stabilizes at around -75%.

In January, 2022 the Expose published an article using Canadian government statistics to demonstrate the progression of VAIDS in the double-vaccinated population.

In response, the Canadian government manipulated its figures for the week from January 15th to 22nd in an attempt to disprove the existence of VAIDS. They also deleted the pdf dated January 21st, which was used for the statistics in the original article.

During the pre-Christmas week when Omicron hit Canada, the vaccine’s efficiency, as measured by the normalised case rate ratio between the double vaccinated and the unvaccinated (as used in Pfizer’s Phase III vaccine trial), dropped from +23.8% to -98.8%.

There was a -23.8% Christmas factor included in these figures, which then stabilized at -75%. This happened because the initial, minimal vaccine efficiency against Omicron is quickly obliterated by the 4% reduction in the immune system of the double-vaccinated population each week.

Omicron uncloaked this immune degradation.

However, for the immune system to recover and for the vaccines to suddenly become more effective against Omicron than they were against Delta in one week is highly unlikely and goes against what Pfizer CEO Albert Bourla previously stated about the limited protection offered by the vaccine against Omicron.

The Canadian government is asking us to believe in this absurd scenario, which is an insult to anyone with more than two functioning brain cells. This is the Canadian arm of the Pfizergate cover-up.

The German Cover Up

On December 30, 2021, the Robert Koch Institute in Berlin released statistics showing that in the week from Monday, December 20 to Sunday, December 26, unvaccinated Germans were 8.12 times more likely to catch Omicron than those who had received two doses of the vaccine.

This corresponded to an immune system degradation of 87.7%, and this was covered in The Expose of January 2nd 2022.

This data correlated closely with Australian and Canadian data from January and December, respectively, which also showed significant immune degradation in those who had received two doses of the vaccine.

However, on January 3rd, the institute announced that it had made a mistake and suddenly found 911 additional unvaccinated Germans who had caught Omicron. The institute clearly rigged the figures in order to protect the credibility of Pfizer and Moderna’s vaccines.

So once again the same pattern is seen.

A government stats department produces figures proving that the vaccines have become anti-vaccines and are seriously degrading the immune systems of recipients. But rather than hold an enquiry to determine how recipients can best be protected from these toxins, they instead just rig the figures.

The Germans, being one of the more efficient governments in this world, rigged their figures more quickly and more decisively than most of their competitors in Covid cover-ups.

The PHE Cover Up

In July 2021, I wrote to various branches of Public Health England (PHE) and Sajid Javid.

Sir,

https://assets.publishing.service.gov.uk/government/uploads/system/uploads/attachment_data/file/997418/Variants_of_Concern_VOC_Technical_Briefing_17.pdf 
https://assets.publishing.service.gov.uk/government/uploads/system/uploads/attachment_data/file/997414/Variants_of_Concern_VOC_Technical_Briefing_16.pdf 

Here are the PHE data for Delta deaths in the week from June14-June21. Vax status on June 17 was…22% 1 jab and 63% 2 jabs and 15% 0 jabs (at least 21 days previously) – https://www.bbc.co.uk/news/health-55274833 

0 Jabs 38-34 = 4 dead from 3.5m over 50s (15%)
1 Jabs 17-10 = 7 dead from 5.2m over 50s (22%)
2 Jabs 50-26 = 24 dead from 14.9m over 50s (63%)

0 Jabs are 4×63/15×24 = 0.70x more likely to die than 2 Jabs
0 Jabs are 4×22/15×7 = 0.83x more likely to die than 1 Jab
2 Jabs are 24×22/63×7 = 1.20x more likely to die than 1 Jab

So in the week from June14-21, the latest published PHE data, you were better off not being vaccinated. And 1 Jab was better than 2 Jabs.
These data are for death with COVID rather than deaths from COVID. There are 23.6m people over 50 in the UK. 1350 of these die every day of all causes. So during 7 days 9450 would die. This is a rate of 0.4 per 1000. Total cases were 976 (0Jabs), 3865 (1Jab), 3546 (2Jabs). So if we deduct those who would have died anyway we get.

0 Jabs 4 – 0.4 = 3.6 dead from 3.5m over 50s (15%)
1 Jabs 7 – 1.5 = 5.5 dead from 5.2m over 50s (22%)
2 Jabs 24 – 1.4 = 22.6 dead from 14.9m over 50s (63%)

0 Jabs are 3.6×63/15×22.6 = 0.67x more likely to die than 2 Jabs
0 Jabs are 3.6×22/15×5.5 = 0.96x more likely to die than 1 Jab
2 Jabs are 22.6×22/63×5.5 = 1.44x more likely to die than 1 Jab

So the best we have for the week from June14-21 from PHE data is that 1 Jab gives the same protection a 0 Jabs. And 2 Jabs make things worse.
24 delta deaths from 2 Jabs compared to 4 delta deaths from 0 Jabs is a disaster.

Regards…

Their response was to delay the publication of Technical Bulletin 18 until July 9th and change the frequency of publication to biweekly instead of weekly.

This was a significant deviation from the practice of other countries, which consistently published weekly reports. From then on, PHE figures never again showed that being unvaccinated resulted in a lower death rate than being fully vaccinated.

This cover-up is a key example of the Pfizergate scandal.

The appropriate action would have been to immediately investigate the relative benefits of one dose versus two doses and no doses.

However, all of the data I have seen from various countries since then consistently indicates that one jab is superior to two. The reason for this is that one jab does not produce enough spike proteins to significantly weaken the immune system, while two jabs do.

There is no data indicating that individuals who received one jab will develop VAIDS.

A common feature of all Covid stats cover-ups is that the initial statistics for each new variant are usually accurate, as the politicians have not yet determined their response and the technicians producing the statistics are not yet pressured to manipulate the data.

However, these technicians are aware that their statistics show vaccines to be dangerous, but they do not share this information with politicians. The politicians are either too ignorant, lazy, or disinterested to realize that their own statistics are undermining their vaccine propaganda.

As a result, they continue to push vaccines even as the data shows that they are causing harm, and when independent media (mainly The Expose) exposes these deaths, they simply manipulate the statistics to hide them.

The UKHSA Cover Up

On October 10, 2021, The Expose published an article that claimed that vaccines were causing a form of AIDS. The article went viral and was eventually quoted by Alex Jones through the Reese report and by Brazilian President Bolsonaro. Here is the data which showed the progressive immune system destruction….

On October 15, The Expose published a follow-up piece that confirmed the original article. Then, on October 23 and October 27, The Expose published two more follow-up pieces.

The last table of data from the UKHSA before it was corrupted showed the weekly decline in the immune system performance of doubly vaccinated individuals compared to unvaccinated people. This data was measured using Pfizer’s vaccine effectiveness formula.

(Unvaxxed case rate – Vaxxed case rate / the Larger of Unvaxxed or Vaxxed case rate)

We are using the normalised absolute ratio of vaxxed to unvaxxed case numbers to determine vaccine efficiency just as Pfizer itself did in the Supplementary Appendix to their Phase III clinical trial results.

• A vaccine efficacy of +50% meant that doubly vaccinated people were 50% more protected from Covid than unvaccinated people. It meant that the delta case rate in the vaccinated was half the delta case rate in the unvaccinated.
• A vaccine efficacy of -50% meant that unvaccinated people were 50% more protected from Covid than doubly vaccinated people. It meant that the delta case rate in the vaccinated was double the delta case rate in the unvaccinated.
• A vaccine efficacy of 0% meant that doubly vaccinated people were 0% more protected from Covid than unvaccinated people. It meant that the delta case rate in the vaccinated was equal to the delta case rate in the unvaccinated. It meant that the vaccines had lost all their effectiveness.

“Everyone over the age of 30 will have lost 100% of their entire immune capability (certainly for Covid and most likely for viruses and certain cancers – following the evidence from Cole Diagnostics in Idaho and Dr Nathan Thompson and Dr Ralph Baric) within 13 weeks,” according to accurate figures from the UKHSA.

These figures showed progressive week-on-week immune system degradation, similar to the Canadian figures that showed degradation in the last 10 weeks before Omicron hit Canada. This was the techies at the UKHSA telling us the truth.

However, after 4 hard-hitting articles in The Expose showed that these vaccines caused a form of AIDS, the politicians intervened.

On November 2nd 2021, the Daily Mail published an article revealing that…

1. UK statistics watchdog scolds PHE’s replacement body for publishing ‘misleading’ figures which anti-vaxxers have seized as proof that Covid jabs don’t work
2. Over the past few weeks, the agency’s data shows infection rates are higher in fully-vaccinated adults compared to the unjabbed. 
3. Anti-vaxx commentators and campaigners have seized the data as proof that Covid vaccines don’t work.

The UK’s Statistics Watchdog is The Office of Statistics Regulation (TOSR for short). Yes, Offstats told the UKHSA that their Stats were off. 

TOSR director general Ed Humpherson wrote to the UKHSA’s boss Dr Jenny Harries on November 1st 2021 thanking her for the changes she had made and is quoted in the Daily Mail as saying –

‘It remains the case that the surveillance report includes rates per 100,000 which can be used to argue that vaccines are not effective,’

‘I know that this is not the intention of the surveillance report, but the potential for misuse remains.

The government admitted that the purpose of their statistics was not to allow the public to determine for themselves whether the vaccines were effective or not. In fact, their statistics should not even be able to support an argument that vaccines are ineffective.

The Director General candidly admitted that the use of all UKHSA data was exclusively to prove the effectiveness of the vaccines and that any government statistics agency that strayed from this line would be re-adjusted by TOSR.

He defined the UKHSA as a pro-vaccine propaganda outlet, a sales arm of Pfizer Inc., whose mandate was only to provide information for one side of the debate.

No one in the UK could be expected to make an informed choice about whether to take Pfizer’s experimental, gene-corrupting vaccine when it was presented to them by the government as unquestionably effective against Covid.

So here was the UKHSA cover-up ordered by the TSOR. Here was the UKHSA arm of Pfizergate.

The PHS Cover up

Here is Table12 from the latest PHS Weekly Covid Statistical Reports – https://publichealthscotland.scot/publications/covid-19-statistical-report/covid-19-statistical-report-9-february-2022/ 

The red warning appeared after The Expose used Public Health Scotland (PHS) figures to prove that vaccines increased the chances of being infected with Covid, being hospitalized with Covid, and dying from Covid. https://expose-news.com/2021/12/09/distracted-by-christmas-party-data-shows-9-in-10-covid-deaths-vaccinated/

If PHS had cared about the lives of their fellow Scots, they would have halted vaccination pending a full public inquiry.

However, they did not seem to care whether Scots lived or died, as long as they were fully vaccinated. But even that term was a total fraud, as nobody who received the Pfizer or Moderna vaccine was truly “fully vaccinated” at all.

If they were truly fully vaccinated, they would not get infected with Covid, right?

If they were truly fully vaccinated, they would not need booster shots, right?

Fully vaccinated people were simply duped, conned, and on their way to having their genes corrupted and their immune systems compromised. The one thing they were not was truly fully vaccinated.

As for Public Health Scotland, to paraphrase Sir Winston Churchill, they were no longer in the business of public health and no longer represented Scotland. They were in the business of pushing gene-corrupting drugs through fraudulent statistics, and they represented the interests of American pharmaceutical companies, not the interests of Scotland or its people.

The notes underneath Table 12 above referred to Appendix 6 of the report, which stated: “Age-standardized case, hospitalization, and mortality rates are used to allow comparisons of case, hospitalization, and mortality rates between populations that have different age distributions.”

The 2013 European Standard Population is used to standardise rates. For more information – see the ONS methods. Here is the full link – https://www.ons.gov.uk/peoplepopulationandcommunity/birthsdeathsandmarriages/deaths/methodologies/weeklycovid19agestandardisedmortalityratesbyvaccinationstatusenglandmethodology 

Notice that it refers to Age Standardised Mortality Rates. Here is some of what it says: 

Age-standardised mortality rates: Age-standardised mortality rates (ASMRs) are used to allow for comparisons to be made between populations that may contain different overall population sizes and proportions of people of different ages.

These are clearly age-standardized mortality rates. They are not age-standardized hospitalization rates, and they are not age-standardized case rates. There is no need for age standardization for case rates or hospitalization rates.

And even if there were, these rates would not have been known in 2013 when the mortality rates were calculated, because there were no Covid cases in 2013 and there were no Covid hospitalizations in 2013.

To apply a 2013 European mortality rate to a 2019 Covid case rate is a blatant fraud being committed by PHS and the Canadian government in broad daylight. Even the UKHSA does not treat its taxpayers with such studied intellectual contempt.

Age-standardized mortality rates are a compensation method designed to account for age discrepancies in mortality rates between different statistical groups (such as groups with different vaccine statuses). They are merely corruption when applied to statistical groups who are not dying.

As mentioned above: one cannot apply a mortality compensator to a statistic that does not involve mortality. THAT IS FRAUD, PURE AND SIMPLE.

It would be no less valid to compensate the case rates with how good people in the 5-year age bands are at singing Whitney Houston.

But if one does apply 2013 European age-standardized mortality rates to case rates and hospitalization rates, then since the unvaccinated are slightly younger than the vaccinated, it makes the numbers look better for the vaccinated.

Furthermore, since neither PHS nor the UKHSA nor Canada provide data by vaccine status by age band (despite FOI requests by Professors Fenton and Neil of QMC to do so), they can do what they want with those numbers.

Here is an example of PHS using this fraud to persuade Scots to get vaccinated…

“In the past four weeks from 08 January 2022 to 04 February 2022, the age-standardised rate of hospital admissions per 100,000 was 2.9 to 3.8 times lower in individuals with their third dose or booster dose of vaccine compared to unvaccinated individuals or have received one or two doses of a COVID-19 vaccine”. –  PHS Covid19 Statistical Report Feb9

But the fact that both Canada and PHS apply 2013 European age-standardized mortality rates to non-mortality statistics shows us all we need to know about what is going on here.

It is wholesale fraud and it is happening worldwide. This brings us back to the observations of Dr. Coetzee that Omicron is mild in the unvaccinated (77% of South Africans in November 2021) and does not lead to hospitalization or acute respiratory infection (in the Southern Hemisphere summer).

The reason that European politicians tried to not only silence her but also persuade her to say the opposite of what she had found in her medical practice, was because she was threatening the basis for further vaccinations.

She was actually announcing deliverance from a pandemic, which would be great for the health of Europe.

However, the politicians were not interested in health. Vaccination was the end they sought, not good health. Dr. Coetzee exposed their true motivation.

UKHSA and PHS Interpretation Warnings are Outright Frauds

UKHSA Note1 to Table13: Comparing case rates among vaccinated and unvaccinated populations should not be used to estimate vaccine effectiveness against COVID-19 infection. Vaccine effectiveness has been formally estimated from a number of different sources and is summarised on pages 4 to 15 in this report.

PHS Note1 to Table12: Data in this table should not be used as a measure of vaccine effectiveness due to unaccounted for biases and risk factors in different populations. For more information, please see the Interpretation of data and Vaccine effectiveness summary sections above.

On Page 13 of the Supplementary Appendix to Pfizer’s seminal Phase III clinical trial of their BTN162b2 mRNA Covid19 Vaccine, Pfizer defined and calculated the effectiveness of their vaccine as the normalised case rate ratio between the vaxxed and the unvaxxed as follows..

VE against severe occurrence after dose 1 was 1-1/30 = 29/30 = 0.96666 or 96.7%
VE against severe occurrence after dose 1 and before dose 2 was  1-0/6 = 1 = 100%
VE against severe occurrence from <7 days after Dose 2 was  1-0/1 = 1 = 100%
VE against severe occurrence >=7 days after dose 2 was 1-1/23 = 22/23 = 0.9566 or 95.7%

Pfizer defined calculated and claimed Vaccine Efficacies of 96.7% for 1 dose and 95.7% for 2 doses using the very normalised case rate ratio that the UKHSA and PHS instruct readers NOT to use.

The numbers in the table 1, 0, 0, 1 for the vaccinated and 30, 6, 1, 23 for the unvaccinated, were actual case numbers not calculated case ratios. But they were also the respective case rates per 23k people because the numbers in each group were almost identical (23,040 vaxxed and 23,037 unvaxxed) as shown above under BNT162b2 and Placebo.

So Public Health Scotland (PHS) and the UK Health Security Agency (UKHSA) were instructing their readers not to use the definition that all regulatory agencies relied upon in granting their emergency use authorizations for the vaccines.

They were therefore instructing their readers not to use the correct definition of vaccine efficiency. That was a fraud. PHS went further in this fraud and represented that Pfizer’s formula should not be used on their raw data “due to unaccounted-for biases and risk factors in different populations”.

It is true that any two populations, unless randomly chosen, will have unaccounted-for biases and risk factors influencing infection rates, such as ethnicity, time vaccinated, age, etc.

But no government department has ever compensated for any of these confounding factors except for the factor of age using the irrelevant and inapplicable 2013 European age-standardized mortality rates.

Cases are not deaths.

One cannot successfully compensate for age in Covid case numbers using 2013 European all-cause mortality figures.

All-cause 2013 European death rates do not vary with age in the same manner as 2019 Covid infection rates. Nobody in Europe in 2013 even knew there would be a pandemic in 2019 (although some Americans and some Chinese may have known). PHS was just setting up the less statistically-minded reader for a compensation fraud.

What these UKHSA and PHS warnings should say is that normalized case rate ratios are the correct way to calculate vaccine efficiencies, and all the other figures in this report that do not equate to this correct calculation are inaccurate to the extent of their disparity from it.

The Danish Cover Up

Here are the Danish figures from their Statens Serum Institut: Nov21 to Dec25 – https://files.ssi.dk/covid19/omikron/statusrapport/rapport-omikronvarianten-31122021-ct18 

The ratio of double or triple vaccinated Omicron cases to unvaccinated cases was 37,111 to 3,500, or 10.6 to 1. While the vaccination rates at the midpoint of the 34-day period on December 8 were 76.83% fully vaccinated, 0.14% singly vaccinated, and 23.03% unvaccinated.

So the case rate ratio between fully vaccinated and unvaccinated was 10.6 x 23.03/76.83 = 3.18x.

Therefore, the anti-vaccine efficiency against Omicron in Denmark was (1-3.18)/3.18 = -68.6%.

The Expose published this on January 28, 2022. The response of the Statens Serum Institut in Denmark was to cease publication of their Omikron Status Report nine days later on February 6, 2022.

That was the Danish version of the Pfizergate cover-up.

Conclusion

In Germany, Australia, Canada, Denmark, Scotland, and England, the same pattern of events occurred. A new variant emerged and the techies of the respective government stats departments did their job and got reasonably accurate statistics out for the new variant.

Then, The Expose published an analysis of these virgin statistics, which had not yet been defiled by politicians. That analysis revealed the truth that doubly vaccinated people now had almost fully blown VAIDS (vaccine-induced autoimmune diseases), and therefore the vaccines led to more infections, more hospitalizations, and more deaths than in the unvaccinated.

The politicians were then told about these articles. So all government stats departments must be avid readers of The Expose!

Public Health England (PHE) certainly wasted no time in responding to my email. 24 hours later, I rang them to speak to their chief statistics whizz about their figures. The response from their Public Accountability Office was to ban me from communicating with them for six months.

I paid no attention to their ban, of course, because they are supposed to be the Public Accountability Office, and I am a member of the public to whom they are supposed to be accountable!

So some bright spark then explained to the politicians that their statistics defeated their drug-pushing narrative and destroyed the scientific basis for their snake bite genetic corruption mandates (not perhaps in so many words). The politicians then responded by instructing their statistics departments to commit medical fraud and cover up the death, disability, pain, and suffering that these vaccines cause.

That was the international Pfizergate cover-up.

We know that government statistics people bend the truth to order because Professor Graham Medley, the Head of Covid modelling for SAGE, admitted as much to Fraser Nelson of the Spectator Magazine.

Yes, and as Fraser succinctly declared, government statistics departments indulge not in evidence-based policy making but in policy-based evidence-making.

Pfizergate was the cover-up of a multi-level, five-level fraud. Their gene-corrupting Trojans were a statistical fraud on top of a medical fraud on top of a hospital administration fraud on top of a regulatory body fraud on top of a genetic fraud.

I say to all those caught up in this five-level fraud: There is no wealth without health. Therefore, there is no economic security in corrupted healthcare.

And I say to all those in the mainstream media who were and still are sitting on the fence: This is bigger than Watergate.

So, who’s going to step up to the scoop?

Appendix – Canada’s Figures

October 02 – https://web.archive.org/web/20211020075926/https://health-infobase.canada.ca/src/data/covidLive/Epidemiological-summary-of-COVID-19-cases-in-Canada-Canada.ca.pdf 

12+ years (33.5m)
11.1 million people (12 and over) have achieved victory over vaccination pushers
22.4 million people have received at least one dose
22.0 million achieved partial vaccination status, of which 46,083 (0.21%) were diagnosed with COVID-19 while partially vaccinated
20.2 million achieved full vaccination status, of which 43,266 (0.21%) were diagnosed with COVID-19 while fully vaccinated

October 09 – https://web.archive.org/web/20211027154438/https://health-infobase.canada.ca/covid-19/epidemiological-summary-covid-19-cases.html#a9 

October 9 – https://web.archive.org/web/20211102202548/https://health-infobase.canada.ca/src/data/covidLive/Epidemiological-summary-of-COVID-19-cases-in-Canada-Canada.ca.pdf

12+ years (33.5m)
10.9 million people (12 and over) have achieved victory over vaccination pushers
22.6 million people have received at least one dose
22.2 million achieved partial vaccination status, of which 47,230 (0.21%) were diagnosed with COVID-19 while partially vaccinated
20.5 million achieved full vaccination status, of which 48,555 (0.24%) were diagnosed with COVID-19 while fully vaccinated

October 16 – https://web.archive.org/web/20211104153557/https://health-infobase.canada.ca/covid-19/epidemiological-summary-covid-19-cases.html 

12+ years (33.5m)
10.8 million people (12 and over) have achieved victory over vaccination pushers
22.7 million people have received at least one dose as of October 16, 2021.
22.4 million achieved partial vaccination status, of which 48,216 (0.22%) were diagnosed with COVID-19 while partially vaccinated
20.8 million achieved full vaccination status, of which 53,330 (0.26%) were diagnosed with COVID-19 while fully vaccinated

October 23 – https://web.archive.org/web/20211112151805/https://health-infobase.canada.ca/covid-19/epidemiological-summary-covid-19-cases.html 

12+ years (33.5m)
10.6 million people (12 and over) have achieved victory over vaccination pushers
22.9 million people have received at least one dose
22.6 million achieved partial vaccination status, of which 49,028 (0.22%) were diagnosed with COVID-19 while partially vaccinated
21.0 million achieved full vaccination status, of which 57,684 (0.27%) were diagnosed with COVID-19 while fully vaccinated

October 30 (got pdf) – https://web.archive.org/web/20211120122253if_/https://health-infobase.canada.ca/src/data/covidLive/Epidemiological-summary-of-COVID-19-cases-in-Canada-Canada.ca.pdf 

12+ years (33.5m)
10.5 million people (12 and over) have achieved victory over gene corrupting vaccination pushers
23.0 million people have received at least one dose
22.7 million achieved partial vaccination status, of which 49,670 (0.22%) were diagnosed with COVID-19 while partially vaccinated
21.3 million achieved full vaccination status, of which 61,825 (0.29%) were diagnosed with COVID-19while fully vaccinated

Nov6 – https://web.archive.org/web/20211128152117/https://health-infobase.canada.ca/covid-19/epidemiological-summary-covid-19-cases.html (incorrectly labelled as Nov13)
Nov6 – https://web.archive.org/web/20211128000628/https://health-infobase.canada.ca/covid-19/epidemiological-summary-covid-19-cases.html  (Nov6 pop Nov13 Cases)

12+ years (33.5m)
10.5 million people (12 and over) have achieved victory over gene corrupting vaccination pushers
23.0 million people have received at least one dose
22.9 million achieved partial vaccination status, of which 50,261 (0.22%) were diagnosed with COVID-19 while partially vaccinated
21.5 million achieved full vaccination status, of which 66,709 (0.31%) were diagnosed with COVID-19 while fully vaccinated

Nov13 – https://web.archive.org/web/20211207205042/https://health-infobase.canada.ca/covid-19/epidemiological-summary-covid-19-cases.html  

12+ years (33.5m)
10.4 million people (12 and over) have achieved victory over gene corrupting vaccination pushers
23.1 million people have received at least one dose
23.0 million achieved partial vaccination status, of which 50,789 (0.22%) were diagnosed with COVID-19 while partially vaccinated
21.8 million achieved full vaccination status, of which 71,822 (0.33%) were diagnosed with COVID-19 while fully vaccinated

November 20 – https://web.archive.org/web/20211211000508/https://health-infobase.canada.ca/covid-19/epidemiological-summary-covid-19-cases.html 

12+ years (33.5m)
10.3 million people (12 and over) have achieved victory over gene corrupting vaccination pushers
23.2 million people have received at least one dose
23.0 million achieved partial vaccination status, of which 51,277 (0.22%) were diagnosed with COVID-19 while partially vaccinated
21.9 million achieved full vaccination status, of which 76,925 (0.35%) were diagnosed with COVID-19 while fully vaccinated

Nov 27 – https://web.archive.org/web/20211218044638/https://health-infobase.canada.ca/covid-19/epidemiological-summary-covid-19-cases.html 

12+ years (33.5m)
10.2 million people (12 and over) have achieved victory over gene corrupting vaccination pushers
23.3 million people have received at least one dose
23.1 million achieved partial vaccination status, of which 51,728 (0.22%) were diagnosed with COVID-19 while partially vaccinated
22.1 million achieved full vaccination status, of which 82,513 (0.37%) were diagnosed with COVID-19 while fully vaccinated

Dec 4 – https://web.archive.org/web/20211223170506/https://health-infobase.canada.ca/covid-19/epidemiological-summary-covid-19-cases.html
https://web.archive.org/web/20211223231903/https://health-infobase.canada.ca/covid-19/epidemiological-summary-covid-19-cases.html   

12+ years (33.5m)
9.9 million people (12 and over) have achieved victory over gene corrupting vaccination pushers
23.6 million people have received at least one dose
23.2 million achieved partial vaccination status, of which 52,116 (0.23%) were diagnosed with COVID-19 while partially vaccinated
22.2 million achieved full vaccination status, of which 88,742 (0.40%) were diagnosed with COVID-19 while fully vaccinated

Dec 11 – https://web.archive.org/web/20220103173009/https://health-infobase.canada.ca/covid-19/epidemiological-summary-covid-19-cases.html 

Dec 18 – https://web.archive.org/web/20220108083517/https://health-infobase.canada.ca/src/data/covidLive/Epidemiological-summary-of-COVID-19-cases-in-Canada-Canada.ca.pdf 

12+ years (33.5m)
9.4 million people (12 and over) have achieved victory over gene corrupting vaccination pushers
24.1 million people have received at least one dose
23.6 million achieved partial vaccination status, of which 53,171 (0.23%) were diagnosed with COVID-19 while partially vaccinated
22.4 million achieved full vaccination status, of which 122,843 (0.55%) were diagnosed with COVID-19 while fully vaccinated

Dec 25 – https://web.archive.org/web/20220117211207/https://health-infobase.canada.ca/covid-19/epidemiological-summary-covid-19-cases.html 

12+ years (33.5m)
9.3 million people (12 and over) have achieved victory over gene-corrupting vaccination pushers
24.2 million people have received at least one dose
23.9 million achieved partial vaccination status, of which 54,772 (0.23%) were diagnosed with COVID-19 while partially vaccinated
22.5 million achieved full vaccination status, of which 219,445 (0.98%) were diagnosed with COVID-19 while fully vaccinated

Jan1 Canada (from Jan24 report) https://web.archive.org/web/20220124194636/https://health-infobase.canada.ca/src/data/covidLive/Epidemiological-summary-of-COVID-19-cases-in-Canada-Canada.ca.pdf 

12+ years (33.5m)
9.2 million people (12 and over) have achieved victory over gene-corrupting vaccination pushers
24.3 million people have received at least one dose
24.1 million achieved partial vaccination status, of which 56,831 (0.24%) were diagnosed with COVID-19 while partially vaccinated
22.5 million achieved full vaccination status, of which 354,940 (1.57%) were diagnosed with COVID-19while fully vaccinated

Jan 8 – https://web.archive.org/web/20220201164337/https://health-infobase.canada.ca/covid-19/epidemiological-summary-covid-19-cases.html 

12+ years (33.5m)
9.1 million people (12 and over) have achieved victory over gene corrupting vaccination pushers
24.4 million people have received at least one dose of the COVID-19
24.2 million achieved partial vaccination status, of which 59,073 (0.24%) were diagnosed with COVID-19 while partially vaccinated
22.6 million achieved full vaccination status, of which 479,143 (2.12%) were diagnosed with COVID-19 while fully vaccinated

Jan 15 – https://web.archive.org/web/20220206015044/https://health-infobase.canada.ca/src/data/covidLive/Epidemiological-summary-of-COVID-19-cases-in-Canada-Canada.ca.pdf 

5+ years (36.4m)
11.8 million people (5 and over) have achieved victory over gene corrupting vaccination pushers
24.6 million people have received at least one dose
24.3 million achieved partial vaccination status, of which 61,209 (0.25%) were diagnosed with COVID-19 while partially vaccinated
22.6 million achieved full vaccination status, of which 581,635 (2.57%) were diagnosed with COVID-19while fully vaccinated

Jan 22 – https://web.archive.org/web/20220209162204/https://health-infobase.canada.ca/src/data/covidLive/Epidemiological-summary-of-COVID-19-cases-in-Canada-Canada.ca.pdf

5+ years (36.4m)
11.7 million people (5 and over) have achieved victory over gene-corrupting vaccination pushers
24.7 million people have received at least one dose
24.4 million achieved partial vaccination status, of which 79,683 (0.33%) were diagnosed with COVID-19 while partially vaccinated
22.7 million achieved full vaccination status, of which 648,271 (2.85%) were diagnosed with COVID-19 while fully vaccinated

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