The Problem With the Covid Inquiry’s Claim That the Vaccines “Saved 475,000 UK Lives”

The Covid Inquiry’s Module 4 report, published this week, claims that 475,000 lives were saved by vaccination in England and Scotland. A further 7,000 are attributed to Wales. These figures are presented as findings. They are not findings. They are the outputs of a WHO model.

The inquiry itself has already identified this as a problem in a different context.

In its Module 2 report, Baroness Hallett found that scenarios were wrongly treated as forecasts, that ministers failed to grasp the distinction and that the reasonable worst-case scenario was what Professor Whitty called a “slippery concept”. The inquiry recommended multiple scenario planning precisely to guard against treating a single modelled worst case as a prediction.

In the same report’s executive summary, the inquiry stated that modelling had “established” that locking down one week earlier would have reduced deaths by 48% – approximately 23,000 fewer deaths. The Office for Statistics Regulation wrote to the inquiry, noting that this language risked being “a misleading representation of the underlying analysis”. The inquiry’s own secretary accepted that “established” was “too definitive” and did not reflect the uncertainty inherent in all modelling.

Module 4 does the same thing again, with a number 20 times larger.

What would have happened without the vaccine?

The 475,000 figure depends on assumptions about how many people would have died without vaccination. That, in turn, depends on how many people were susceptible in the first place. What would have happened without the vaccine? That is the key question to which I dedicate a chapter in my book, Spiked.

The model behind the inquiry estimate inherits the same foundational belief that drove the Imperial College projections: that the vast majority of the population was susceptible without interventions. From that starting point, Imperial produced the well-known estimate of up to 500,000 deaths in the UK in an unmitigated epidemic.

Once you assume that level of susceptibility, a large epidemic becomes inevitable. The model assumes that outcome then concludes it. 

The question is whether that assumption was ever consistent with what we could observe. Very early on, we had two ways of testing it. 

1. The £37 billion test and trace programme produced data on the percentage of household contacts who later tested positive. This secondary attack rate was around 10% by PCR over the course of the whole wave, which works out at about 8.5% symptomatic and lateral flow test positive. That is a measure of the percentage who were susceptible in any one wave.
2. PHE and UKHSA also carried out random testing of blood donor blood for antibodies. Around 6% developed antibodies at the end of each wave.

Both these measures were the same before and after the vaccinations in 2021. They did change with Omicron from January 2022 but that is not a vaccine effect. 

If you begin with a population that is 10 times more susceptible than reality –  the 85% susceptible Imperial claim – everything that follows will be inflated by a similar margin.

Where is the signal?

If vaccination had prevented hundreds of thousands of deaths, you would expect to see it. Not in a model, but somewhere in the data. A change in their magnitude or duration of the waves that could not be explained by natural dynamics, or a low vaccination country that fared badly. There is nothing to see. The only observations from the US wastewater data (Figure 1) are:

1. The first Omicron wave was rapid in onset and over quickly – but with a similar number affected as subsequent waves
2. The low between waves never returns to baseline once vaccines are rolled out
3. The waves are of similar magnitude and duration

The waves persisted throughout the ‘pandemic’ period – before vaccination, during rollout and after widespread vaccination. They did not disappear. They did not change in fundamental shape when examined using measures relatively robust to testing changes, such as hospital admissions or excess mortality. The pattern is one of continuity, not interruption.

The arithmetic

Even on the inquiry’s own terms, the numbers do not hold together.

The original modelled scenario projected up to 500,000 deaths in the UK without mitigation. Around 150,000 deaths were recorded as involving Covid. That leaves approximately 350,000 modelled deaths that did not occur, not 475,000.

Yet the inquiry now presents a figure of 475,000 lives saved in England and Scotland with 7,000 further in Wales – exceeding the number of deaths that were ever at risk even under the original, inflated assumptions.

Do not forget that the inquiry also claims that lockdowns “undoubtedly saved lives” so the cardboard cut-out lives claimed by the inquiry to have been saved are way higher even than this inflated figure.

Hypocrisy

The contradiction deserves to be stated plainly. The inquiry criticised ministers for treating worst-case modelling as forecast. It was rebuked by the UK’s statistics regulator for doing the same thing itself. And now, in Module 4, it has done it again – with an even larger number, presented with even less qualification.

Where modelling supported the conclusion that the government acted too slowly, the inquiry treated it as established truth and had to be corrected. 

Where modelling supports the conclusion that vaccination saved hundreds of thousands of lives, it again treats it as established truth. 

To understand the scale of what the claim is, here it is plotted along with Covid-attributed deaths. (Note that in every country that had had Covid mortality in 2020 and 2021, deaths accumulated more slowly from 2022 with the Omicron variant, complicating any attempt to credit the vaccine with the slowdown.)

People did die

It is also important to recognise that the excess death waves attributed to Covid and treated by the inquiry as entirely preventable by vaccination were, in reality, neither wholly attributable to Covid nor susceptible to being eliminated by vaccination.

The inquiry itself has heard extensive evidence on this. Its Module 3 report, published last month, found that blanket ‘Do Not Attempt CPR’ notices were imposed inappropriately on groups of people including those with learning disabilities and older people, often without the knowledge of the patient or their family. These notices led to denial of hospital care. It found that the public messaging “Stay Home, Protect the NHS, Save Lives” contributed to a decline in emergency department attendances “even for life-threatening medical emergencies such as heart attacks”. It found that cancer screening programmes were paused, that missed and late diagnoses of colorectal cancer “resulted in loss of life and increased mortality rates”, and that some patients had their diagnoses and treatments delayed “to the point where their conditions became untreatable”. It found that many Covid patients “did not receive the care they would otherwise receive”. It found that at points healthcare systems came close to collapse, not because of the virus alone, but because they entered the pandemic already overstretched.

These are the inquiry’s own findings, from its own witnesses, published four weeks before Module 4. They describe a population in which people died not only from a virus but from the response to it – from policies that denied them treatment, from fear that kept them from seeking help.

On top of this, there was significant overdiagnosis. A striking 47% of people who die of any cause have a detectable respiratory virus in their nasopharynx — when the body is dying and the organs are failing, the immune system fails too. Swabbing the dying and the dead will inevitably produce positive results that have nothing to do with the cause of death. Only around 55% of deaths certified as Covid had any mention of acute respiratory infection on the death certificate, and in the winter 2020-21 wave that figure fell to just 38%. The overdiagnosed deaths do not simply inflate the Covid count — they hide excess deaths from other causes in the statistics, making it impossible to see the true scale of harm done by the response itself.

And yet the model behind the 475,000 figure treats the entire recorded Covid death toll as deaths caused by the virus – deaths that vaccination could, in principle, have prevented. It does not subtract the deaths caused by policies and fear of accessing healthcare.

Cardboard cut-out lives

What we are left with is a figure that represents only cardboard cut-out lives. Lives ‘saved’ that in truth were never at risk. Lives ‘saved’ that bear no relationship to reality. 

An inquiry that has already been told by the statistics regulator that it overstated the certainty of modelled claims should not be building its most consequential conclusions on the same foundation.

Dr Clare Craig is a diagnostic pathologist and Co-Chair of the HART group. She is the author of Expired – Covid the untold story and Spiked: A shot in the dark.