Latest UKHSA report shows the Covid-19 jab has an average real world effectiveness of MINUS 73%

From The Daily Exposé.

Pfizer were able to claim that their Covid-19 mRNA injection is 95% effective. We don’t need to go into the fact that this calculation was extremely misleading and only measured relative effectiveness rather than absolute effectiveness. Neither do we need to go into the fact that Pfizer chose to ignore thousands of other suspected infections during the ongoing trial and not perform a PCR test to confirm the infection because it would have thrown efficacy below the required minimum of 50% to gain regulatory approval.

Now, thanks to a wealth of data published by the new UK Health Security Agency we are able to use the same calculation that was used to calculate 95% effectiveness of the Pfizer vaccine, to calculate the real world effectiveness of the Covid-19 vaccines.

Full story here

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(Please see Edited bit in square brackets. ED)

Thanks Pat. I’ve been puzzling about this.

The Expose do have a point. This Infection Rate data is the way Pfizer calculated their vaccine efficacy in the trials. If you do it the same way now, in the real world as the Expose say, using the official data, this table is what you get. The vaccine was sold on this basis; not on covid deaths or covid hospitalizations - there were too few of those, due to picking healthy patients that were younger on average than the main target. And it was not sold on the basis of overall deaths (all cause mortality) or all-cause morbidity (these last two being the only meaningful measures of efficacy, that allow you to make an educated guess at risk versus benefit, and not just the (claimed) covid benefit alone.

So yes, this new Infection Rate data should be a problem.

The two data columns come from a bigger table, Table 5 in the govt report

The wider picture gives strident vaxxers some crumbs of comfort (but that’s misleading too). Before looking at this, let’s just look at the discomfort that is on show. This stems from the Infection Rate data shown by the Expose, which is still visible in Table 5.
Right underneath Table 5 is some real squirming for the connoisseur, have a look:


The first sentence here translates as “On no account use this table to calculate vaccine effectiveness - or you will end up with embarrassing, negative numbers! As in that horrid Expose thing”

There are crude statistical biases! (squirm, squirm…)

Like (first bullet point)…"people who are fully vaccinated may be more health conscious and therefore more likely to get tested for COVID-19 and so more likely to be identified as a case (based on the data provided by the NHS Test and Trace) "

This isn’t a crude statistical bias - it’s a piece of nonsense speculation.
People who are(…) MAY BE (…) in which case (…)
Yes and they MAY NOT be, in which case - the opposite will apply.

In the second bullet point, the reference to age is a bit of a red herring in a table broken down by age. So the supposed significance of being head of the vaccine queue isn’t clear.

The third bullet point excuse is another (…) MAY BE (…) THEREFORE…
Again, the ‘therefore’ being premised on the ‘may be’ cuts no ice! So is misleading.
Also, IF the vaccinated do behave less cautiously, what then of the ‘pandemic of the unvaccinated’? Those goalposts seem to have moved.

The last bullet point excuse is a rare acknowledgement of natural immunity MAYBE (lol!) contributing to a lower case rate. And only acknowledged in order to explain away the bad data!
Yes that is a great reason to take the vaccine, that is.
And, shouldn’t they be saying then, that you don’t need the vaccine if you’ve had covid?

Note that none of these caveats (in what is a right furball of excuses) refer to an actual ‘crude statistical bias’.

Table 5
The Table 5 does a partial rescue job, by focusing on people who actually test positive for Covid, but doesn’t take the data to the claimed level of protection:


The first two columns are as above; the others are Vaxed vs Unvaxed comparisons, in pairs, firstly for Emergency Care, and then for deaths, using two timescales.
Okay these look better for the vaccine, with the unvaxed numbers being higher than the vaxed (the number preceding in the table). But:

  1. there isn’t any sign of these touted 90+ percent drops, and
  2. these timescales are all based on a positive covid test. This is a bit sleight of hand, because the first two numbers show that this positive test result is less likely in the unvaccinated.
  3. Why are children being included? They aren’t getting dangerous covid. They aren’t heeding @CJ’s warning that child data will dilute the adverse vaccine data. Or rather, they ARE heeding it :wink:
  4. In fact if you look where the covid risk is, the picture isn’t good. For example if you add up the 40 pluses (say in deaths within 28 days of a positive covid test), you see that the covid rate in the vaxed is more than double than in the unvaxed.

[EDIT To bit shown in italics:
“The drops in deaths is these age ranges might be about two thirds if you look at them…but to get a real measure of covid death risk you need to divide by two as there is twice the chance of getting covid in the vaccinated. So rather than that fabled 90% drop in bad things, we’re maybe looking at a drop of about a third if efficacy was measured in covid deaths (which, of course, ignores all vaccine-caused deaths).”

EDIT, continued: This ‘divide by two’ was hasty, and I think is incorrect in this table. (I was thinking of a previous table that was set up differently). So according to the table, the drop of about two thirds in deaths in the age ranges should not be a third as I concluded but remains at two thirds. Apologies]

In summary, the Expose is correct that the goalposts have been moved away from the evidence base (covid cases per vaxed vs unvaxed) to one that wasn’t in the trials (death rates among covid cases, vaxed vs unvaxed), because the original goalposts appear to show statistical disaster.

And in the myopic focus on covid cases, deaths outwith covid are ignored. Any analysis that focuses only on covid can not indicate that benefits of ‘vaccines’ exceed risks.



Hi @Evvy_dense , From:

Public Health England


11 January 2021

Last updated

29 March 2021 — See all updates


COVID-19 vaccine surveillance strategy

Ref: PHE gateway number GW-7853 , 716KB, 23 pages

“in order to maintain public and healthcare professionals’ confidence in the vaccine and to ensure that surveillance systems are in place for long-term monitoring of the programme, it is important that post-marketing surveillance is led by independent public health agencies without association with vaccine manufacturers. This document provides a high-level oversight of the post-implementation surveillance strategy that PHE will be implementing, in collaboration with the MHRA, NHSEI and academic partners, to monitor and evaluate a future COVID-19 vaccination programme. The outcomes of this surveillance will be reported as soon as they become available to the JCVI, to support vaccine policy recommendations, and to SPI-M to support dynamic modelling to understand the impact of the vaccination programme on the need for non-pharmaceutical interventions. “

COVID-19 vaccine surveillance reportWeek 44 of HSA

most of the references page 29 to 30 in sub links are to pre-prints or peer reviewed articles or research conducted by authors mostly working for PHE itself

also note some of the data limits in the strategy report:

“5.4.2 Vaccine effectiveness against severe disease

….Hospitalisation will be used as a marker of how effective the vaccine is at preventing severe disease….The population will be restricted to those with respiratory admissions.

Given the fact that most patients with covid who are admitted late in the illness are admitted with vascular problems and not respiratory problems it seems certain that hospital admissions for “covid” are going to be viewed with a narrow yardstick for the purposes of this “surveillance” - and of course as time goes on most people will be vaccinated so this means all vaccined sufferers with vascular symptoms will not be classified as hospitalised due to covid symptoms.

And of course **nowhere in the “**surveillance“ strategy report is there a reference to vaccine damage, injury, or side-effect and only 1 reference to side-effect in the 44 report with 1 annotation to a paper that isn’t hyperlinked but is the focus of a critical report in theExpose:

Just skimming through all this stuff I get the impression of a dog’s breakfast of alphabet agency reports of what they may be doing or will be doing or have started all in relation to procedures and planning with emphasis on vaccine take-up and non-pharma intervention analysis. No procedures for examination of the numbers of experts engaged in looking at adverse events case by case in fact no reports on any autopsies looking at vaccine damage. The whole health care data system is set up to confuse and obfuscate so as to enable any conclusion to be pulled from its numbers by “favoured journalists” and “celebs”.

My thanks to you @Evvy_dense and theExpose for shining lights on the key elements.



Please note I have edited my post above where I seem to have been unfair to our friend the covid vaccine. The part where I said the reduction in covid deaths in the vaccinated should be adjusted from a reduction of two thirds to a reduction of one third (to take into account the fact that the chance of getting covid was twice as high in the vaccinated) is wrong.
Just to re-iterate, focussing only on covid deaths doesn’t show the vaccine is reducing deaths or illnesses from other causes.

To recap and add a bit.
The vaccine trials only showed a reduction in ‘cases’ (not hospitalisations or deaths), and only as measured by PCR testing. So it should be a very big deal that this is not showing in the data. Hence what I called ‘squirming’ explanations (and I still do).
It’s odd that there should be reductions in (covid) hospitalisations and (covid) deaths despite in the vaccinated despite the cases increasing.
This means the vaccination policy is doing exactly the wrong thing. The vaccinated are still getting covid (in fact in greater numbers than the unvaccinated) and are transmitting it. So there is no justification for manadatory vaccination in any setting as the only possible benificiary is the person being vaccinated.
It would make sense to let people take the vaccine that wanted it but to make them take it to try to keep cases down does not make sense and is likely just spreading covid.

To re-iterate, the most obvious interpretation of this data is that it is vaccinated people that are spreading covid. This might be because of mass events like football matches, or packed indoor events like nightclubs, from which the great unvaxed are excluded. In my view the covid numbers are very likely being boosted by international travellers, most of whom are vaxed.
It is also likely the confidence instilled in the vaccine by the incessant claims and spin is leading to different behaviours in the two groups.

Jamie just posted a Peter Doshi video clip in which he talked about critical thinking. Dr Doshi (an associate editor or some such of the BMJ) has been exercising his skills in this area since the start of the vaccine trials. He was about the first to draw attention to the following issue, which offers an explanation for apparent anomaly of vaccine not reducing cases after all, despite appearing to do so in a trial of nearly 40,000 people.

The issue is this. Despite there being (from memory) about 18,000 in both the placebo group and the vaxed group, since the trial population was young and healthy, there still weren’t a huge number of covid cases in the two-month period measured. It boiled down to 162 cases in the placebo and 8 in the vaxed group.
Hence the claimed 95% efficacy, as 8 is about 5% of 162.

But Doshi spotted an issue that wasn’t noted in Pfizer’s press release. He found somewhere (not in Pfizers’ press releases, that were the basis of approval of their vaccine) that there were 3400 people excluded who had covid symptoms - and they seem to me not to have been tested for covid, but what do I know.
Doshi presumes that they were, though no results were given. Obviously I’ll run with Doshi, who knows what he is talking about.
It was said that they were probably roughly split, so wouldn’t favour the vaccine more than the placebo.
Not true, says Doshi. If you added a significant number to both sides you would not get this 95% reduction.
Even if they were tested and were all negative, even a false negative rate of 10% in the PCR would affect the efficacy.
Eg in two groups of 1700 (all negative PCR, but with a 10% false negative rate) another 170 true positives on each side would lead to a new ‘cases’ calculation:

Placebo: 162+170=332
Vaccine: 8+170=178
The reduction/efficacy would be 46%, below the minimum threshold of 50%.

As even a 1% false positve rate would by my calculation reduce the ‘efficacy’ as calculated by Pfizer to 80%, it’s clear there is a sensitivity issue with their proclamation, which depends on getting doen to small numbers of ‘cases’. And the mysterious missing category of people with covid symptoms numbering thousands, leaving conveniently small numbers and apparently big reductions, is suspicious.

This measure of efficacy is in ideal conditions, and would likely not be seen in the real world where people are older, have co-morbidites and also immunological problems.
In addition, of course, we have the delta variant reducing vaccine efficacy, as well as efficacy waning after a few months.

Thanks for the explanations. I watched the Doshi press conference on this and didn’t understand which I think I now do. But I still have this massive elephant in my room which you pointed out above. While all the analysis depends on PCR “testing”, it all seems to me to be meaningless.