Professor Norman Fenton – “We cannot trust any of the ‘official’ statistics driving the Covid-19 narrative.”
The entire Covid-19 pandemic response has been driven by numbers. From the start, in March 2020, we have been bombarded with statistics primarily aimed at keeping us as confused as possible and in a sustained state of fear. Few academics have been as outspoken as Professor Norman Fenton and he regularly speaks out against the blatant manipulation of data.
Prof. Fenton is professor of risk information management at Queen Mary London University. He is also a chartered engineer and a fellow of the British Computing Society. He specialises in using Bayesian statistical methods to challenge data and predict probabilities and — despite academic media censorship — has applied his methods to the Covid numbers and consistently found them wanting.
He was one of the speakers at the ‘Question Everything, Lockdowns Summit’ in London. Below is his presentation at that event:
Alexander tweeted at Prof Fenton, “as someone who really valued your lectures at QM (risk and decision making), would you say your policy stance on COVID-19 protocol is primarily influenced by academic findings or personal philosophy regarding individual liberty?”
Prof. Fenton responded, “Alexander asks a very good question which requires a thread to answer.” So begins his thread in response and the tenth and final tweet in the thread said, “Finally I’ve come to the conclusion that we cannot trust any of the ‘official’ statistics driving the Covid19 narrative.”
Should Twitter censor or remove Prof Fenton’s thread we have attached a PDF copy of it immediately below. The links to articles and videos attached in his thread can be found listed under ‘further reading/viewing’ at the end of this article.
During the recent interview below Prof. Fenton discussed the flaws in the statistics, what that means in terms of “managing the pandemic” and the personal attacks he has been subjected to for speaking out.
Below are a few of the points Prof. Fenton discussed in his interview.
Flawed Covid-19 Statistics
At the beginning of the pandemic, in the UK, the only people who were being tested and classified as a Covid case where those who were already hospitalised with serious symptoms, said Prof. Fenton, and that meant that the population infection rate was being underestimated, while the infection fatality rate was being overestimated. Prof. Fenton published articles in peer-reviewed journals that argued that – to get the true infection and fatality rates there had to be widespread random testing. Subsequently this did happen, said Prof. Fenton, “but ironically, I now believe that’s been the biggest mistake of all.”
In May / June 2020, Prof. Fenton and his team found that the case fatality rate was much lower than originally assumed. “And I thought it was increasingly strange that the government was using very simplistic case numbers to drive policy decisions at that time, like lockdowns, without any kind of cost benefit analysis,” said Prof. Fenton.
His first concerns about “the narrative” began when they realised that “the widely publicised government Office for National Statistics data which claimed that black and minority ethnic [BAME] people were over four times more likely to die than whites was massively exaggerated” which was causing unnecessary fear within the BAME community. From then on, more and more questions arose regarding Government statistics and policies culminating in:
How many cases have there been?
How many hospitalizations have there been?
How many deaths have there been?
We really do have no idea about what those figures really are, said Prof. Fenton, because it’s all driven through PCR testing. “All those key graphs that they show, it’s all driven by this definition of a case being a positive test. And because of this failure to distinguish, or at least to provide us with the data that distinguishes, between symptomatic and asymptomatics who test positive … In fact, we don’t know how many people are actually currently ill with Covid symptoms or have been ill with Covid symptoms.”
The Great Reset and Climate Change
In the summer of 2020, Prof. Fenton attended a meeting of academics regarding the “Covid crisis.”
“People talk about conspiracy theory but actually the first time I ever heard about the World Economic Forum’s Great Reset agenda was, and it came from the other academics, at that meeting. In fact, all the other academics on that panel spoke about the Covid crisis being the perfect opportunity for a Great Reset which they felt was necessary to usher in a new improved world order and, especially, to combat what they saw as the greatest existential threats of the world which was, namely: climate change,” said Prof. Fenton, “and I think there are many academics who are openly suggesting that Covid lockdowns are a necessary precursor for climate lockdowns.”
Prof Fenton said it’s important to note that the such academics not only dominate the government scientific advisory committee but are also on the editorial boards of journals etc.
“Academics are supposed to be the ones who question the official narrative, who dig deep,” said Prof. Fenton, “because they would naturally reject infringements of civil liberties and government interventions, especially when those interventions most adversely affect the poorest in society.” But they’re not.
It’s academics who have been the key drivers of the “hysterical narrative” to support lockdowns. “In fact, they’re the ones who are basically pushing the narrative for even harsher restrictions like the Covid passports,” said Prof. Fenton, “there’s a handful of us [demanding data] and analysing, [the rest] attempt to delegitimise us.”
Prof. Fenton goes on to say that it’s not just academics, it’s the civil servants as well. All the people who are continually pushing for the restrictions based on flawed statistics are completely unaffected by the negative consequences of those decisions.
Censorship, Shadow Banning and “Hit Pieces“
“As I started to report on my blog and on my twitter the serious concerns about the PCR false positives and the over testing of asymptomatics, which I believe was creating a flawed narrative for more lockdowns, that’s when not just the censorship started but also the personal attacks,” said Prof. Fenton.
Prof. Fenton started to receive abusive postings on twitter and a fair number of people were reporting him to twitter as a spreader of lies and misinformation or tagging Queen Mary University demanding that he be sacked. Although they didn’t succeed in having his twitter account closed, he was “shadow banned.”
When he exposed the statistical flaws in the government messaging about one in three people with the virus having no symptoms, things got worse for Prof. Fenton. “Despite the fact that our paper was a rigorous Bayesian statistical analysis of that – and the statistics and our method has never been challenged – it was rejected immediately from all the major journals without review. For example, the BMJ said that the subject matter – despite the fact that this was like the big message of the time – they said the subject matter was of no interest,” Prof. Fenton said, “and the pre-print servers rejected our papers without any obvious explanation.” Prof. Fenton has done several papers since and “they’ve rejected every single thing that we’ve submitted on Covid since.”
The censorship of Prof. Fenton’s papers worsened when he attempted to publish papers on “vaccine” effectiveness and treatments for Covid. The Lancet has even refused to publish one of his letters, on their letter pages, without explanation.
A colleague analysed data from the American VAERS database and Prof. Fenton played a minor role in the analysis. His colleague had his twitter account hacked and he was subjected to author abusing, including a ludicrous “hit piece” by a BBC documentary producer “which, incidentally, also included a bizarre attack on me as a person who was they said ‘red flag’,” Prof Fenton said, the “private chat system of the HART group, of which I’m a member, was the victim of a sophisticated criminal hacking which resulted in all the private messages being posted on a public website. The interesting thing is that the only message by me which has been publicly flagged by our opponents as being incriminating was one where I simply said that Julia Hartley-Brewer had retweeted one of my tweets.”
Being a member of HART also gets you labelled as anti-vaccination. “I had no interest in in looking at the subject [of vaccines] … but The Sunday Times, in a front-page article, singled me out as an anti-vaxxer … simply because another member of HART wrote a report in which it, all it did was identify that there’d been a spike in death following the first round of vaccinations. In fact, it was because of that, being called an anti-vaxxer when I wasn’t, that actually spurred me to look at the vaccine data more closely,” Prof. Fenton said.
“I’d like to say there’s a silent majority like us, but actually there isn’t. We are a silent minority of whom there’s an even smaller minority who are actually prepared to speak out about it. Because the others, the rest, have seen what happens to those who do, as you say, ‘stick their head above the of the parapet’, they become essentially persona non grata within academia and they’re sort of forever discredited,” said Prof. Fenton.
- Read and sign the ‘Together Declaration’ #Together
- Lockdowns Summit, London, 17 July 2021
- Alexander asks a very good question which requires a thread to answer, a twitter thread by Prof Norman Fenton. Links to articles and videos included in Prof. Fenton’s thread below:
- Bayesian network analysis of Covid-19 data reveals higher infection prevalence rates and lower fatality rates than widely reported
- Why we know so little about COVID-19 from testing data – and why some extra easy-to-get data would make a big difference
- As London goes into Tier 4 COVID lockdown here is proof that the government data for London is flawed
Follow Professor Norman Fenton:
- HART Group: Health Advisory & Recovery Team
- Norman Fenton on Twitter
- Norman Fenton website
- Norman Fenton on YouTube
Analysis of COVID-19 vaccine death reports from the Vaccine Adverse Events Reporting System (VAERS)
by Dr. Norman Fenton, Jun 30 2021
There have been multiple conflicting claims made about the safety of the COVID-19 vaccines that were rolled out world-wide from Dec 2020. However, there is no universally agreed system for reporting either deaths or serious side-effects for which these vaccines may have been the cause or a contributory factor, and hence, as a result, there are concerns about variability in the quality of reports and the credibility of the sources submitting them. Reports can be submitted by physicians involved in administering the vaccine or helping treat side effects that may have consequentially arisen, clinical and non-clinical health service employees, or pharmaceutical professionals involved in the investigation. Likewise, lay people, such as the patient or their family and friends, may have submitted a report independently of medical carers. It has been suggested that a third category of submission may have been made by members of anti-vaccine, or other groups, motivated by ill-intent, who may exaggerate case numbers reported. Critics of safety reporting cite the fact that lay people, or those with malign intent, may form the bulk of reports and hence statistics on side effects must therefore be exaggerated because they come from non-credible sources. Set against this, research suggests that as few as 1% of the true adverse reactions ever get formally recorded.
In early April 2021 Scott McLachlan and colleagues downloaded the 2021 Vaccine Adverse Events Reporting System (VAERS) dataset (this is the US dataset) with the aim of analysing these reports to determine the range and frequency of health problems potentially caused by the vaccines as well as also the quality of the reports and, by inference, the credibility of the reporters lodging them.
For each patient cited in a report, a clinically trained reviewer manually examined the report to determine its source and clinical credibility and to identify and record medical history, current illness, and symptoms. Each was then checked by a second reviewer. This process is ongoing, as there are 1644 deaths in the April VAERS deaths dataset that have been reported in patients who had recently received their first or second COVID-19 vaccination, and over 28,000 serious adverse events that did not result in death.
They identified health service employees as the reporter in at least 67% of the reports, while pharmaceutical employees were identified as the reporter in a further 5%. Lay people were identifiable as the reporter in only 28% of the reports. This suggests an intention for clinical applicability and usefulness and goes some way towards addressing the common disclaimer that many VAERS reports are made by aggrieved family members and anti-vaxxers, both with an axe to grind. The sample is heavily biased because these were all people vaccinated very early in the programme when only the elderly, those with significant or chronic health conditions and frontline health service staff were being vaccinated. Yet, the analysis shows that the patients can be grouped into three main types:
- Those where the vaccine was most likely not a factor;
- Those where the vaccine may have been a factor; and
- Those where the vaccine was the most likely factor in their deaths.
They found that in 34 of the 250 deaths (14%) a vaccine reaction could be ruled out as a contributing factor in their death; these were all patients either already bedridden and expected to die from a serious medical condition like lung cancer, or were described as at end of life or receiving palliative hospice care. For 203 of the 250 (81%) the vaccine may have been a factor in their death; however, many of these patients had one or more chronic or age-related comorbid conditions. Finally, for at least 13 of the 250 deaths (5%) the vaccine was the most likely cause of death; these patients had strong reactions soon after vaccination and died either on the same day, or during the next couple of days.
The full report:
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