The weaponisation of data has been ‘mostly peaceful’
The statistical jiggery-pokery employed since 2020 is so outrageous it is perhaps best viewed through the lens of (dark) comedy, so we forewarn you in advance that — in a change from our usual (possibly over-sober) tone — the following article has been written in a somewhat jocular manner, despite covering a topic that is very much not a laughing matter.
Lies, damn lies and statistics. Three years after ‘that’ fateful announcement in March 2020 that should never have taken place, it is worth remembering how numbers were twisted to support the official narrative.
We have compiled a hit-list of some of the worst statistical offences committed by those who should otherwise have been fighting to protect both individual citizens and the society they inhabit.
Stats criminal! Who can forget the ludicrous modelling deliberately used to ratchet up fear levels? Despite a boat-load of senior cruise-goers demonstrating in February 2020 that the respiratory disease-causing virus of the day was not worth stopping the world for due to the harm it would cause to billions of people, the powers that be decide that this was too good an opportunity to miss, stats be damned. Correlation (‘with’) was quickly switched to causation (‘of’), and a global pandemic was declared, much to the delight of the pandemic preparedness industry that thrives on, er, pandemics.
Stats unbelievable! The first day of Autumn 2020 – 21 September – introduced ‘exponentiality’ as if it was a harbinger of ‘infinite doubling’ Armageddon. The Chief Scientific Advisor, Patrick Vallance, belied his title with a marketing campaign that even amateur scribes pointed out was unscientific: yes, they had ignored recent data, plucked numbers out of the air and then arbitrarily applied a fixed doubling time (eek, it’s exponential!) to sow their seeds of doom. The Institute of Mathematics and its Applications was unequivocal: “a simple equation like the exponential model is easy to solve but not very realistic”. Even good news got the treatment: Robert Peston put out a tweet in the early hours of 1 October 2020 that case growth had slowed markedly yet was still “only mildly exponential”. What exactly is a ‘mild exponent’, please?
Stats ridiculous! Glossing over a period of data torture in early 2021 (remember “the magic has started”?) and leaping ahead past the summer, a particular vignette of the year came in September when various newspapers trotted out carbon copies of a pharma puff piece claiming that three quarters of people under 50 who were admitted for treatment over the previous seven days were unvaccinated. In fact, the data period was seven months. To continue the numerical theme, there were in fact seven statistical clangers in the
pharma press release newspaper articles. I guess we do not need to ask who was writing that particular script: so much for a fourth estate acting as a societal safeguard.
Stats egregious! November 2021 was the warm-up act for the government’s ‘Plan B’: a backdrop to coerce as many people into vaccination as possible. Why? Well, we’ve covered that elsewhere. Back to the story: on the first of the month, a new official-looking factoid from the bean-counters at the Office for National Statistics (ONS) was wheeled out to great fanfare:
This is wrong on numerous levels but at its most simple was a comparison of summer covid deaths in the vaccinated with winter covid deaths in the unvaccinated. Suffice it to say that a complaint by James Wells was upheld by the Statistics Regulator, who deemed this particular data crime a step too far. You may not be surprised to find, though, that despite this being a period of heavy censorship for anyone that dared speak against the elixir of life (those pharma companies had vials to sell, after all), this tweet has still not been deleted by the ONS, all of 18 months later. Plus ça change.
Stats not true! This minor setback was a mere bagatelle for the vaccinators, as they were quickly able to latch on to a juicy stat: on 8 November, Amanda Pritchard, the then newly installed CEO of NHS England, urged people to come forward for boosters as there were ’14 times’ more coronavirus patients in hospital compared to ‘this time last year’. This was an outright, blatant lie (an “abuse of statistics”) excused by officialdom as referring to a date back in August.
Stats absurd! The newly
militarised renamed UK Health Security Agency (UKHSA) was in the headlines as it continued to trumpet its predecessor’s (Public Health England) vaccination statistics. While none of the reported matter in this article can in any way be described as funny, there is a high degree of slapstick comedy about this story. Having first appeared in May 2021, the “Covid Surveillance Report was produced as an exercise in self congratulation, promulgating the success of the vaccines at eliminating a plague that had caused immense harm to the countries and populations of the world (mainly as a result of the various non-pharmacological interventions that nearly all western governments seemed very keen to implement)”. But the data didn’t play ball, in particular, case rates in the vaccinated were similar to (or even higher) than in the unvaccinated. This led to escalating levels of convoluted and excruciating apologetics. In true dogma enforcement mode, Ed Humpherson of the Office for Statistics Regulation, chastised UKHSA in November that “that these data have been used to argue that vaccines are ineffective”. Trapped in a paradox with nowhere to go, the best he could suggest is that the Vaccine Surveillance Report format be changed such that it makes “clear in the table, perhaps through formatting, that the column showing case rates in unvaccinated people is of particular concern”. The sign-off, though, is a priceless absurdity straight out of an Orwellian hellscape: “I recognise that you want to maintain transparency and consistency, but these qualities should not be at the expense of informing the public appropriately”.
Buffeted from all sides, the resultant Vaccine Surveillance Report compendium – which still comes out on a monthly basis – is a jumbled word & number salad that seeks to post-rationalise its raison d’être with gems such as “we have previously found that using broader definitions of hospitalisation has given lower vaccine effectiveness estimates”, which of course can be paraphrase more succinctly: ‘we tortured the data until it told us what we wanted to hear’.
Stats opaque! The various data guardians are committed to being highly transparent – we know this, because they have told us so (and Brutus was an honourable man). Despite these assurances, it has been incredibly difficult to obtain access to underlying data that might help shed light on the many confusing events of the last three years. It is a mystery why this data cannot be released, given how fortunate we are to have data guardians who are committed to full transparency. I guess we must take into account that these senior health bods are very busy curating this data (which has been collected at taxpayers’ expense) in order to publish high impact career-furthering papers in the likes of Nature that contain curious phrases such as “milder Omicron disease contamination of hospitalisations with incidental cases is likely to reduce VE [Vaccine Effectiveness] estimates”. Eh? Fear not, our intrepid public health guardians have this one licked: “VE estimates increase, and waning is reduced, when specific hospitalisation definitions are used”. Again, the data is being tortured to get the desired results. But there is an inevitable side-effect – only found in the supplementary data, for some reason – that those who have received at least one Covid injection were being admitted to A&E (for non-covid reasons) at a rate of five times more than those who have not:
(VE estimates greyed out (“perhaps through formatting”) in line with the wishes of Ed Humpherson at the Office of Statistics Regulation).
Stats been adjusted! The above paragraph reminds us of the importance of adjusting data to
give the outcome we want correct for bias. One of the key ONS statisticians states explicitly that his “worry is that the NIMS population will lead to overestimate the population of unvaccinated, hence underestimate their mortality rate”. Heaven forefend! (The ONS have still failed to explain how their estimates for the number of people who exist in particular age groups and regions is lower than the number who are vaccinated). After a substantial delay, ONS published an update to its ‘deaths by vaccination status’ report in February 2023: the data is hideously flawed and confounded (see ‘Stats Egregious!’ above) but somehow still managed to salvage a pro-narrative ‘line to take’. Fancy stat. Hush thy mouth, lowly citizen: do not jump to conclusions that might contravene the orthodoxy.
Stats just farcical! In March 2023, the ONS released further analysis that attempts to reconcile its data to the 2021 Census to estimate Vaccine Effectiveness, as Humpherson had declared in January 2023 that this “will substantially increase the sample size, meaning that the sampling frame will be much more representative of the general population”. The result is a farcical mess, as the ONS candidly admits – despite adjusting for a myriad of confounding variables, they conclude that the miracle injections confer unexpected life-saving properties – a clear sign of inherent bias in the data. (ONS observes “a reduction in risk of non-COVID-19 death for vaccinated groups compared with the unvaccinated population”), i.e. they stop you dying from non-Covid-related causes. Stats magic.
Stats product placement! The tin-eared post-rationalisation being employed by the vocal spokespeople for the pandemic preparedness industry is truly a thing to behold. The BBC’s Hannah Fry was a key part of a ‘citizen science’ experiment in Haslemere in 2018 that served as a blueprint for much of the UK’s disastrous and eye-wateringly expensive actions in 2020 and beyond. That could just have been an unfortunate mistake, but why would the BBC then engage in active marketing on behalf of pharmaceutical companies, deploying Fry to spearhead a programme (“Unvaccinated”) that has a litany of failings? A particularly obnoxious untruth was an attempt to marginalise those who had not been injected as being a small minority of 8% of the population, despite their own survey showing it was nearer 26%. Stats wrong.
Stats officially bad! In case there was a perception that faults in the stats-time continuum were limited to the UK, one need only highlight the heroic work of activist citizen and independent (and unpaid) analyst Kelly Krohnert, whose story is – perhaps – one of hope for the future. Picture David taking on Goliath: Krohnert’s efforts in calling authorities in the US to book for gross (yet very simple) errors on covid data claims is one for the history books – Krohnert was publicly ridiculed by former US Surgeon General Jerome Adams and censored for her troubles. But she was right, and has been spectacularly vindicated. In collaboration with well-known biostatistics researchers at the University of California San Francisco, Krohnert has just had a pre-print published that highlights instances of numerical and statistical errors made by the CDC and how a clear majority (20 out of 25) of those documented errors exaggerated risks to the general public: for example, the CDC managed to claim that 4% of Covid-19 deaths were in children (U18s), which was out by two whole orders of magnitude. For context, this is from the same CDC whose director declared in April 2021 that “data from the CDC suggests that vaccinated people don’t carry the virus, don’t get sick and that it’s not just in clinical trials, but it’s also in real world data”.
Stats not punny. In fact it is appallingly bad, and demonstrates how quickly ‘public health’ can turn sour when groupthink and vested interests take control of the narrative.
Perhaps we are just living in a deranged puppet show, with other entities pulling the strings: “stats the way to do it!”.
And stats why they (the sceptics, that is) call it the blues.