To recap what we have written so far. We have seen that good data do not support the idea that there is only one viral respiratory agent around, that its name is influenza (A or B) and that influenza causes mayhem around winter time every year.
In our Riddles series, we reported on the multiple logical gaps in germ theory. We often cite the failure to infect volunteers during challenge studies at the MRC Common Cold Unit when conditions are ideal for such an infection. A proportion of quarantined volunteers with no history or laboratory evidence of recent influenza illness were not infected by squirting viruses up their nostrils.
Other modes of transmission have not been studied with modern molecular diagnostics, so we are left with the evidence from the kissing and poker games studies to try and understand precisely how these bugs infect or activate (wake up).
There are several problems with understanding precisely what is going on. First, the clinical similarity between influenza-like illness (ILI, a syndrome caused by 200-odd known and X unknown microorganisms) and influenza (caused by influenza A and B) makes it easy to play on the F word “flu”. According to the media and politicians, everything is “flu”, but what do they mean by this term? You cannot identify a particular pathogen by its symptoms, as they are all the same.
In any year, relatively few cases of influenza-like illness are caused by influenza viruses and, as such, would be amenable to prevention by specific vaccines. The two – influenza and non-influenza ILI – are not clinically distinguishable, and even periods of known higher influenza virus circulation are not predictive, as other organisms (such as rhinoviruses, RSV and parainfluenza viruses) are co-circulating.
To understand the microbiology of all this, consider ILI cases (the F word) as a yearly pie, which shows just 11% (77 of 700) of ILI cases actually being caused by the influenza virus.
We explained this in one of our earliest posts.
Data from the control arms of studies in our Cochrane review and proportional epidemiology studies (PIE) are likely to yield reliable data because they are designed to follow those up with symptoms and test them. You can also check the comings and goings of these agents in our Week in Numbers series, which shows that most of those tested with symptoms are not due to influenza.
The second problem is that no one knows the precise burden of influenza morbidity or mortality, as no surveillance system is capable of routinely distinguishing influenza and influenza-like illness, and no one carries out routine autopsies to identify a microbiological cause of death. So, guesswork rules. This explains, in part, the wildly inflated CDC estimates, which not even Dr. Fauci believed.
These simple biology facts are seldom mentioned by physicians and the media, who are instead told that current measures (e.g. vaccination) are sufficient to control the problem, although no one quite knows the size of the problem, and few understand its multiagent nature.
Add the fact that influenza viruses mutate continuously, and by vaccinating, you are essentially chasing a moving target: you begin to understand why auntie, who had been vaccinated against the F word, still gets the F word.
For politicians, the value of this ignorance and confusion is great. By referring to “flu” and their yearly prevention programme with “flu vaccines”, they are seen to have acted and fixed the problem, especially if they can bolster their nonsense with a dollop of extra cash for health services. The cash, as you well know, does not come from their pockets.
It remains to be seen whether the public will smell a rat as they are suddenly pressed into influenza, Covid and RSV vaccines: “Wait, was there not just a single agent five years ago? Where have the other two come from? Are there others? What? There are? Does it mean everyone will be vaccinated against 60 more bugs in a few years?”
A critical evaluation of vaccine effects is complex as systematic reviews show the studies are often of poor quality. There is a lack of randomised controlled trials of sufficient duration and too small a sample size to detect an effect on serious outcomes (such as hospitalisation and death). That is the observation which fits the evidence: a small sample size means they are comparatively rare events.
As a consequence of the poor evidence base there is an over-reliance on non-randomised studies and models, which, as you know, can be made to tell you just about anything you want. For example, some widely referenced non-randomised studies in people aged 65 years or older systematically report an implausible sequence of effects, with trivalent influenza vaccines apparently effective for the prevention of non-specific outcomes, such as death from all causes, but not for the prevention of influenza or death caused by pneumonia and influenza.
The bulk of evidence (hundreds of thousands of observations) comes from poor quality, large, retrospective, data-linked cohorts in which data had been collected for other purposes (usually reimbursement). Twenty-two out of 40 retrospective cohort studies published up to 2006 failed to report either vaccine content, degree of antigen matching, or both, making generalising from these datasets an arduous task.
So how do we know about these problems? Because, unlike the media, politicians, lobbyists and influencers, we read and assessed these studies before deciding that they were simply not worth the effort. We kept them on in our updated Cochrane reviews as legacy appendices.
To finish off we now come to another set of questions.
- In a similar situation, how are decision makers justifying pushing the yearly mammoth undertaking of influenza vaccination?
- Why have influenza vaccines played such a prominent role in the last two decades?
- Does this dubious and costly enterprise apply to Covid vaccines?
In the next installments, we will see the justification CDC and friends gave for their actions and provide evidence that everything is not going well – we are being fleeced.
This post was written by an old geezer who’s been working on this for three decades and hopes that the content of posts like these will be his legacy. The other old geezer just shakes his head.
Dr. Carl Heneghan is the Oxford Professor of Evidence Based Medicine and Dr. Tom Jefferson is an epidemiologist based in Rome who works with Professor Heneghan on the Cochrane Collaboration. This article was first published on their Substack, Trust The Evidence, which you can subscribe to here.
To join in with the discussion please make a donation to The Daily Sceptic.
Profanity and abuse will be removed and may lead to a permanent ban.