There follows a guest post by Daily Sceptic reader ‘Amanuensis’, as he is known in the comments section below the line. He is an ex-academic and senior Government researcher/scientist with experience in the field, who says he is “a bit cross about how science has been killed by Covid”. It was originally posted on his Substack page, but I thought it was such an excellent analysis of the UKHSA’s favoured test-negative case-control approach and its problems – especially why it seems consistently to exaggerate vaccine effectiveness – that Daily Sceptic readers should be treated to it too.
There has been much consideration in recent months about the effectiveness of the Covid vaccines, and this leads to thoughts about how vaccine effectiveness is calculated in the first place. The trouble with any attempt to calculate vaccine effectiveness is bias – that is, are the vaccinated and unvaccinated similar enough to make the calculation, or, rather, can we remove any bias to get an unbiased estimate.
As an example of bias, in the early days of the Covid vaccinations the majority of the vaccinated were old, and the unvaccinated were young – so if there was an effect of age then we’d get a biased result simply by comparing overall case rates (per 100,000) in the vaccinated versus the unvaccinated groups. In this case the bias might be resolved by splitting the analysis into different age groups, but what about other factors? Most of all, what is the bias associated with willingness to become vaccinated (maybe the vaccinated are in general more likely to be the healthy ones, say)?
Some time ago, statisticians came up with a really great way to remove rather a lot of the ‘difficult’ bias – it is called the Test Negative Case Control approach (TNCC). With this approach you don’t simply count infections, but compare the rates of infections amongst those who get tested – more specifically, you compare the ratio of positive to negative results in the vaccinated against the positive-to-negative ratio in the unvaccinated groups.
The great thing about this method is that it automatically compensates for many behavioural effects in the vaccinated compared with unvaccinated groups – so, say the unvaccinated are half as likely to go and get tested compared with the vaccinated, the TNCC should remove most of this effect. Of course, many demographic things are of interest (particularly the impact of age and gender), so you’ll usually separate out these variables, but the advantages of the TNCC method remain.
Anyway, pretty much every study on Covid vaccine effectiveness makes use of TNCC – it gives such a powerful and unbiased estimate. You can read more about it in this review article.
Oh, but what’s this I see in that paper?
A key characteristic of the test-negative design is the use of a control group with the same clinical presentation but testing negative for the pathogen of interest. This group of individuals may either be positive for alternative pathogens or negative for all pathogens (pan-negative or undiagnosed). As with any case–control study, the selection of controls should be made independently of exposure status to avoid selection bias. A situation where this assumption may be violated is the presence of viral interference, where vaccinated individuals may be more likely to be infected by alternative pathogens. (Emphasis added.)
Hmm. So it is vitally important that the vaccinated cohort don’t suffer from a different disease that might impact on testing in increased numbers compared to the unvaccinated – if they do then you’ll get a misleading estimate of vaccine effectiveness.
To explain further – the odds-ratio (which is then used to estimate vaccine effectiveness) is dependent on the calculation of (vaccinated testing positive) / (vaccinated testing negative). Thus it would be a problem if you had the same number of positive results but an increased number testing negative – such as if more people are going forwards for testing because of a different disease with similar symptoms.
What’s all that I keep hearing about the ‘worst cold ever’..?
Are we in a position where the vaccinated are getting some other viral infection causing symptoms similar to Covid, are getting tested because the symptoms are right but are then testing negative? If we are then any estimate using the TNCC approach will give a misleading result, and overestimate the vaccines’ effectiveness.
Note that this doesn’t mean that all ‘bad colds’ need to be in the vaccinated group – all that is needed is for the propensity to have a bad cold to be higher in the vaccinated group.
All we need to identify this happening is to look at the relative rates of those seeking testing, comparing vaccinated with unvaccinated (both per 100,000), and try to identify any trends in the data suggesting that the vaccinated are changing their test-seeking behaviour relative to the unvaccinated. Oh. Sorry. Those data are not available… The usual problem.
Hmm. Can we work with other data to try to identify if this particular problem is occurring?
I’d note first of all that it is no good just looking at ‘is there a lot of cold going around?’ While there does appear to be some increase in ‘coughs’, (for example, see figures 28 and 32 of the most recent Government influenza survey), you absolutely need to compare vaccinated with unvaccinated to identify the problem. Without this type of data we’re stuck.
But hold on – what about comparing those getting tested without symptoms? That way the data won’t be affected by any increase in Covid-like disease. Conveniently, there’s a nice paper out fairly recently that does provide these data, from Qatar. In this paper they provide data on both symptomatic disease (which would be affected by a worst cold ever effect if it was occurring more in the vaccinated) and asymptomatic infection (which wouldn’t).
There it is – a significantly reduced (negative for six-plus months) vaccine effectiveness for asymptomatic infections. (The middle column gives the vaccine effectiveness for symptomatic disease, the rightmost column for asymptomatic disease. The rows give vaccine effectiveness by time, with the lowest row vaccine effectiveness after seven-plus months.)
This might be the information we’re after. This would definitely occur if there were more people being tested for non-Covid (but Covid-like) disease in the vaccinated cohort.
Or alternatively it might simply indicate that the vaccines have a negative effectiveness against asymptomatic disease and a positive effectiveness against symptomatic disease. Sure, that’s a terrible result and indicative of problems to come, but it doesn’t prove that the TNCC approach is giving misleading results.
Is there anything else we can do? Let’s go back to that TNCC review paper I linked to early on in this post. In the introduction to that paper is the actual reason why we use TNCC:
Case–control studies present a particularly efficient approach for monitoring VE because they tend to be faster and cheaper than cohort studies.
Okay. What about slower and more expensive approaches? Well, the ‘old-fashioned’ way of doing this is to try to compensate for every potential bias (variable) – this is more complex and requires more data (takes more time/money), but does work well – and is the way it used to be done before TNCC came along. The best way to compensate for bias is using proper cohort studies, where you recruit a number of people, split into two groups with well understood characteristics, and investigate them fully for longer periods of time. Now, this method is expensive and time consuming, but it really does give an indication of how things are going. Even better, if you have enough participants you also get indications of the level of side effects.
I suggest that this should have been done with the Covid vaccine – the initial clinical trials were time limited for understandable reasons, but that didn’t mean we should have stopped looking. In fact, it is usual to have a period of extended pharmacovigilance for newly approved medical drugs/treatments (sometimes called ‘phase IV trials’) and it is rather strange that this wasn’t done for the Covid vaccines. However, it is too late for that now – we’ve vaccinated everyone without taking the effort of selecting a set of subgroups for longer term analysis of the vaccines’ safety and effectiveness.
Luckily, though, it isn’t too late to do anything at all, because there is a way of adjusting for bias in the data using other techniques. The most common way of doing this is the Multivariable Logistic Regression (MLR) using survey data in a retrospective study.
The important thing about MLR is that it does actually work. It could be argued that TNCC is better, but it should at least give similar results – the main advantage of TNCC is mainly that it is faster and cheaper. In particular, having a TNCC that gives markedly different results to a MLR should result in questions being asked, and not simply ‘TNCC is better. The End.’
Is there one? Or, even better – has anyone done an MLR and TNCC on the same data? Amazingly, the Qatar study also includes a MLR. Sure, it is tucked away in its supplementary materials, but it is there in Table S11.
And there it is. Markedly worse vaccine performance for the MLR analysis than the TNCC analysis shown earlier. It is worth repeating that this is for the same data – all that is changed is the type of analysis used.
It is important to note that this isn’t simply ‘well, let’s just add all the numbers up’, as is being done with the UKHSA tables (albeit with age being taken out as a variable) – this is a proper analysis that takes into account age, sex, nationality, reason for testing and calendar week of test (i.e., it tries to remove Covid wave effects). Thus it counters the complaint about the simple analysis done on the UKHSA tables – that biases lead to misleading results.
What’s more, there’s a time effect. The vaccine effectiveness for the MLR is broadly similar to the TNCC estimate up to month four – that’s good, because really you want MLR to be similar to TNCC. This suggests that the residual biases in both types of analysis are low – the two very different methods give the same results, which is excellent. But differences do appear from month five; because the results were similar in earlier months this is less likely to be a simple behavioural (or similar) bias – and that leaves the question I started with – is the TNCC approach failing because of the worst cold ever effect?
I’d also note another aspect to all this. While it is true that we like to ‘do things properly’ to remove bias in important things like ‘estimate vaccine efficiency’, as a general rule it doesn’t make that much difference when you look at a population scale – the larger the numbers you look at the more likely it is that a simple approach will get you close to the truth (so long as the really important factors are considered – usually age). The problem being that population-wide estimates of vaccine effectiveness (e.g. the UKHSA tables) are just so very different from the official estimates from ONS. The MLR results given in the Qatar study suggest that the problem is with the TNCC approach that everyone is using, and that the truth is closer to the UKHSA estimate than the ONS estimate.
One more point. The risk of viral interference, that is, of the vaccine increasing the risk of infection with alternative pathogens, is just one mechanism whereby the TNCC method might give erroneous results. The basic concept of the TNCC method is that the vaccinated and unvaccinated groups are similar; as noted in the discussion of the original review paper I linked to at the start:
Simulation studies have shown that biases may arise under several circumstances, including if the study fails to adjust for calendar time, if vaccination affects the probability of non-<target disease> infections, if vaccination affects the probability of seeking care between cases and controls, if healthcare-seeking behavior differs substantially between cases and controls, and if misclassification bias is present.
And:
The test-negative design may be more appropriate for some vaccines and pathogens, but less appropriate in some scenarios for example if vaccination reduces disease severity in breakthrough infections.
Oh dear. Perhaps it isn’t simply the fault of the worst cold ever – perhaps any number of problems might be resulting in an erroneous estimate of vaccine effectiveness, some of which sound a little too familiar, such as the vaccines reducing disease severity…
Is this analysis enough to conclusively prove that the official estimates are wrong? No. But there are clear indications that something serious could be going wrong and that a much deeper analysis with more data, and perhaps a more appropriate method, is required. Until that is done I’d suggest that any estimates of Covid vaccine effectiveness using the TNCC method should be treated with caution.
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Have you raised an official complaint?
I have in the past made several complaints to the BBC about things like factual inaccuracies, religious bias and inappropriate content for toddlers.
In every instance, my complaint has been brushed aside with platitudes (the inappropriate content was “vital” for toddlers) or more lies.
There is no point complaining to the BBC about anything.
There is no way they can be penalised or punished for spreading lies or working to an agenda (in direct contravention of their charter).
They are, to all intents and purposes, untouchable.
Which is why I don’t go near them
The only point is really to remind them that someone is watching them. The same as writing to your MP. It may or may not have an impact, but if you don’t write then they’ll assume no-one is watching and there is zero chance of anyone’s conscience being pricked. If enough people complain/write, more notice may be taken.
Anyone who relies on the BBC for “facts” has clearly had some kind of lobotomy.
Your point about Sweden is so often missed in pointless bickering around minutea: We were promised an apocalyptic disaster if we didn’t lockdown hard and fast. This was the justification for the extreme measures and utter loss of liberty. Even if, say, Sweden had done twice as bad as us then they would only have seen 0.4% of their population die – is that enough to destroy liberty? It’s on a par, frankly, with prior epidemics which had seen very light touch public health measures, and well within our pandemic preparedness plan which allowed up to 375000 UK deaths (0.55% of population). So even if they had been twice as badly affected they would have been justified under pre-pandemic planning to have stuck to their guns.
But they didn’t – they actually saw fewer deaths than us.
Then to quibble over them being lower density (debatable, and not correlated to COVID deaths anywhere) and more people living alone (something like 22% compared to 17%) is sophistry, and in any case all these two things do is reduce contacts slightly – and similar effect could very likely have been arrived at in UK under much lighter lockdown conditions, such as public health information, maybe max gatherings reduced – life would have been really quite tolerable though.
I think more desperation than sophistry
The UK’s pandemic plan estimated up to 750,000 deaths, an order of magnitude more than the alleged figure and Ferguson GIGO computer model
“pointless bickering around minutiae”
A trap that we can easily fall into (see my last post).
It’s the secure big data picture that is our strength, and sticking to basics when it comes to scientific justification : the refutation of a null hypothesis against credible probability levels. (Only the fascist insane can argue that lock-ups are justifiable without a massive weight of evidence for benefit).
Similarly on vaccines. Don’t argue about decimal points regarding risk (we know that, so far, the absolute risk reduction seems vanishingly small) – just point out the two key issues:
Like being told when coming from outside “soaking wet” and saying “it’s raining” that you are mistaken and have “got it wrong” because you are not educated to university degree level
Patronising or what?
Best to turn off MSM, including the taxpayer funded bbc.
BBC: The long-term effects of Covid can also be much more severe for many people and it’s more infectious than flu…
Human being after 5 minutes on Google: ‘Human rhinoviruses (HRV) are RNA virus from the Picornaviridae family……. Currently, more than 100 distinct serotypes have been identified. Every year, these viruses cause both upper and lower respiratory tract infections in young children and adults.
Despite the clinical importance of HRV infection, the clinical characteristics and mortality risk factors have not been well described.’
‘Rhinovirus infection in the adults was associated with significantly higher mortality and longer hospitalization when compared with influenza virus infection. Institutionalized older adults were particularly at risk.’
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5343795/
Holmes: Does that mean that the common cold is more deadly for the elderly and infirm than influenza? And that ‘covid 19’ is now another endemic common cold coronavirus?
Dr Watson: No shit……..
Last year the public seemed to forget the old harsh, but true saying ” even a cold will finish them off”
The BBC has never been reliable when it comes to science reporting, especially medical science. I can still remember when any serious infection was invariably attributed to a ‘virus’ including TB, anthrax and leprosy!
the newspapers are terrible too. even New Scientist seems to have arts grads as science reporters
In this harsh commercial world, such moves are sadly inevitable. Magazines feel they need to appeal to the widest possible readership, so they employ arts graduates to make their dumbed down content “more accessible”.
any other steves wish to comment?
Don’t get diverted into alternative mickey-mouse arguments about ‘science vs arts graduates’.
Instead, have a look at those highly qualified and honoured ‘scientists’ who populate that cesspit of bad science – SAGE.
A close member of my family (admittedly more sceptical than most of the population) constantly argues with me about the actual data and its implications : he has a university fellowship in one of the hardest of hard sciences.
For myself – I straddle the fence with qualifications tagged both ‘..A’ and ‘..Sc.’ There is much commonality in the relevant forms of logical analysis employed – or not, as is the case for poor practioners on both sides of the fence, be they in public health or journalism.
Its true that you get bad scientists and good people from the humanities. It’s more about credulity and the ability to absorb data and organise it. I’ve known some terrible ‘science’ academics. But academics are a pretty poor bunch anyway. They know a lot about their subject area and like to expound outside it.
I don’t know the full make up of SAGE but they don’t really stand out as scientists to me. Behaviouralists, psychologists, some public health ‘5 a day’ poster designers, a couple of medics. Many people in epidemiology are code monkeys with no deep understanding (I know a few) – its one of those areas where all you need to have is a computer and you can be a computational epidemiologist. Ferguson was a Physicist once but he’s just a coding clown now. The good epidemiologists will be medics turned epidemiologists – Heneghan, Jefferson etc
I saw a good youtube early in the pandemic – by a historian of pandemics. That was great because it put it into its historical context (ie nothing to worry about)
My company employs a medic turned epidemiologist and unfortunately he’s as idiotic as SAGE.
Either that, or he’s towing the line to keep his job & pension intact.
“But academics are a pretty poor bunch anyway”
Stay away from generalisations, Steve – they are dangerous and almost always inaccurate. You end up with guff such as ‘The working class are all heroes” and “The middle class are all comfortable with lockdowns” – i.e what is known in technical rhetorical terms as ‘Shite’.
The point I’m making is that ‘scientists’ and ‘academics’ – like any other broad grouping vary as much as the population as a whole.
Some general statements do have broad validity – such as highlighting the general decline of journalism, or noting the innumeracy of broad swathes of the population – particularly when it comes to risk assessment.
Similarly, one can regret the poor grasp of good scientific method within the academic-scientific community, and the related distortions of data.
But specifics where possible. And yes – the imbalances of SAGE in terms of expertise are well-known – but have little to do with inherent flaws in the disciplines per se. Ferguson, and other ‘code monkeys’, for instance are just driven too much by confirmation bias and self interest – this is the sense in which they neglect ‘good’ science as much as any ignorant arts graduate.
A lot of it comes down to the willingness to go outside groupthink – courage. And integrity in not exploiting your position for dishonest gain. Scientists, doctors, public health experts etc are as likely to be flawed human beings as the rest of us.
I work with real epidemiologists – including those involved in the investigation of the effects of exposure to lead on the cognitive development of children. They unanimously regard Ferguson as alarmist. That is evidenced by his consistent track record since the 2001 F&M fiasco.
I think the 99.97% claim at the start, is quite revealing. It’s more proof, if needed, that Twitter and social media have become the go to source for most news coverage. The dangers of reliance on these tech giants for news and decision making, was warned of long before C19 was a droplet on a dead bat.
with the 99.97% claim – it just depends how you cut it.
whole population? normal ‘man in the street’ etc
the person at the rally holding the banner is probably correct if applied to themselves or their family
it wouldn’t apply to a resident of a care home
THIS is what you do best , refute ,refute,refute.
Coupled with Toby Young articulate disappointment in those Press Conferences et al.
Keep up the good work
If “The death rate is much higher for older and more vulnerable people.” then by definition the death rate for everybody else must be much lower
The longer you live the sooner you die…
Thanks for this. We should all know raise an official complaint to the BBC using this information. Also hopefully one of the mainstream press will pick up on ot. The DM seems to be starting to smell the coffee, or the Spectator.
Maybe JHB would raise it on her show?
I think your last sentence is more to the point – until other MSM outlets start picking up on this sort of thing, not much will happen. Letters of complaint on the issue are just the proverbial water off a duck’s back.
IFR is hugely dependant on who is being infected.
It’s been suggested that lockdowns increase the probability of an older vulnerable person becoming infected relative to a much younger, less vulnerable individual. There is some logic to this.
Even Fergusons modelling shows lockdown kills more from covid. It slows down the herd immunity from the unaffacted part of society
https://www.bmj.com/content/371/bmj.m3588
So was it really all about greed, hyping up the promotion period of the vaccine before the big sell?
Greed may have played a part but I think conceit and fear were major drivers. Realising they had made a huge cock up by going against the researched and agreed Pandemic plan Boris and his Clowns had a choice. Admit it and face the consequences, which at the time would have been manageable, (Hancock under a bus), or continue the deadly charade. Fear of possible political fallout coupled with the conceit of believing they could get away with it drove them into where we are now. BS upon BS until the ‘calvary’ of the vaccine.
Remember Watergate? The incident itself was minor and could have easily been managed. It was the cover up that toppled a president.
Good point.
For Boris and co it is as eastender sez. Though ambition can be a form of greed.
But for Whitty, Ferguson, Vallance, Fauci etc yes. That is the clearest explanation for their ruthless behaviour. And it is intensifying. And China is milking the advantage economic collapse is giving them.
Notice BBC does not “correct” anything that goes in favour of lockdown/vaccine? Where’s the supposed impartiality?
Sadly, that ‘impartiality’ went out of the window a while ago.
Of course, it was never absolute, by a long chalk. No outlet does absolute ‘impartiality’, and the state broadcaster is always going to be aware of the state’s/establishment’s interests.
But there has been a notable – and noticeable – shift towards sheer unbalanced propaganda in the BBC’s News and Current Affairs where there was once a manageable (to the audience) bias.
First of all the death rate isn’t a fixed value. It varies according to several variables. My guess it is between 0,5% and 1 – this is huge for a non seasonal virus for which no one has previous immunity. Unchecked it surely collapses the hospitals with a hospitalisation rate much higher than that and an R higher than 2
The fact that “only” 388 people died bellow 60 years old with no underlying conditions, says very little. First of all many people of all ages have underlying conditions. Secondly are we suggesting their lives don’t matter? Lastly this says nothing about hospitalisation rates in this age group
Evidently countries are not all the same due to a number of reasons. Is hard to explain India’s numbers for example. On the other hand countries with higher healthcare quality seem more affected.
Sweden is number one in the world with the highest percentage of one person households. It is in the household where a large chunk of infections occur.
Furthermore there’s an oddity in Sweden’s second wave – lots of cases and almost no deaths. This pattern is not observed anywhere else, thus probably unrepeatable.
With all that said, I’m not cheerfully welcoming lockdowns, I think they are the atom bomb and should only be used as a last resort.
I prefer the South Korean approach. Test cases and contacts and mandatory isolation of positives. Effective and aggressive surveillance. This has the benefit of controlling the epidemic and minimising the economic impact.
On one hand we cannot be in lockdown for a long time, is unsustainable. This lockdown lasted for too long already. On the other hand we cannot afford to be in Brazil situation which became isolated from the rest of the world with a caotic response to the pandemic, no really enforced nationwide lockdown and chaos in hospitals and a huge death toll.
Even if we do not lockdown and the situation spirals out of control the rest of the world will lock us out which will have the same negative economic impact.
I prefer the approach of ignoring it – or making your own risk assessments as you see fit. Nationwide lockdown should never be on the cards.
“Secondly are we suggesting their lives don’t matter?”
No – quite the reverse if you have a sane view of the term ‘life’.
In outcome, this episode is nothing particularly exceptional. Not Ebola. How have we ever coped with something as bad or worse every 3 to 5 years???
You really don’t want the South Korean approach, trust me. You can’t buy that pizza by the slice, you get the whole thing, most of which you would find unpalatable.
I still can’t believe the BBC put this piece out, it was so laughably bad. Especially the part about Sweden; beginning your fact check with “it’s true” isn’t exactly a stunning rebuttal.
BBC? Have you seen that Eastenders clip doing the rounds? https://youtu.be/CiKntfB4kFY
Par for the course for the BBC.
If they told me the sky was blue, I’d look up to check
The problem is that the BBC is believed by many people, even tho’ it has become the propaganda arm of government as never before (i.e. that always-present role has been massively intensified). Almost everything it touches regarding Covid is misinformation.
Piddling around with ‘Covid’ statistics is a black hole, as can be seen by the misleading ‘refutations’. Forget them; as John Lee has consistently pointed out (at least until the Spectator went native), the revised death registration process meant that ‘Covid deaths’ were nonsense from the start.
So – stick with the ‘all-cause’ mortality figures as refutation of the ‘disaster’ scenario. The only ways the Covidiots can wriggle out of that data of ‘no (or small) signal’ is by bent modelling adjustments or bare-faced lying.
The only way to show your displeasure to the BBC is to cancel your TV license. I really do like the term ‘old media’ when referring to them. I have great hope for the up and coming GB News. Here’s hoping I’m not disappointed.
Some years ago I had need to complain to my local authority about themselves. Realising that any such complaint would be pointless I encouraged them along a route that would end with them taking me to Court.
We duly ended up in Court (multiple times due to their incompetence) where I won which was in itself satisfying especially after the magistrate expressed his dim view about the way the local authority had handled it’s own case by offering me costs.
The info around suicides used by the BBC was taken from this blog from the BMJ;
https://blogs.bmj.com/bmj/2021/03/10/louis-appleby-what-has-been-the-effect-of-covid-19-on-suicide-rates/
But I think I would trust these guys;
https://twitter.com/Ldn_Ambulance/status/1321566876732952581?s=20
Thank God someone has the patience to Fisk – is that still a phrase? – the BBC. Only thing I would say is that’s its shame there aren’t more references generally in this and across lockdown sceptic pieces generally to the places which technically had lockdowns, but which were either poorly enforced/non existent or less severe than in say the UK. As it is this piece and some others seem a little too reliant on a few examples like Florida – possible to live outdoors a lot and have windows open, through winter – and South Dakota, where nobody lives. For the latter I find it impossible to believe that the scale of the unit under analysis does not matter. Such that it probably wouldn’t have fared any different if it had or hadn’t locked down, but don’t think this can be extrapolated to larger population units.
Thank you for this. Debunking the ‘debunkers’ is so necessary in this intellectually-challenged shit show.
But why oh why can’t 99% of people see the guff for what it is? How have people got through life being so thick?!
Just been blanked by Faecebook for 30 days for posting a quote from Mein Kampf about the ‘Big Lie’. I believe it’s still possible to buy Mein Kampf so the quote is not illegal. I referenced the source so it’s not plagiarism.
When I complained I received a message that because of the Pandemic (which they perpetuate) they may not be able to address my complaint.
What a world awaits us!
I hope you used an unimpeachable source for the quote:
https://www.jewishvirtuallibrary.org/joseph-goebbels-on-the-quot-big-lie-quot
P134 of Mein Kampf. Goebels was a disciple. Mein Kampf is a very very dangerous book. It leads to a society where by blaming a virus (oops, the Jews) for all ills it is possible to not just coerce society but actually make them willing participants in their own slavery.
THE ‘PCR is the gold standard’ is total BS. In early 2020, the Chinese authorities publicly released their protocols for diagnosis, treatment, triage, etc. Their protocol for confirming a diagnosis of SAR-CoV-19 in symptomatic, hospitalized patients was ‘positive results from two PCR tests at two weeks interval and a chest x-ray’. Clearly, a single PCR test on asymptomatic non-hospitalized individuals has no merit whatsoever, unless the inevitable false positives produced was an intended outcome.