Bonfire of the Straw Masks
There have been some crackles in recent days on twitter, as the Bangladeshi mask trial caught light again. The crackling started with the publication of a ‘short note‘ that provided a ‘simple analysis’ of the recently released raw data from the Bangladeshi trial that claimed that, given the new ‘simple analysis’, the trial failed to show any covid protection benefit from mask wearing. Not content with blowing holes in masks, the authors of the ‘simple note’ also report that they did nonetheless find some other highly significant differences between the intervention and control groups, including one that could introduce more than enough bias to explain the original trial report’s marginal benefit from wearing surgical masks. In the limp language of academic writing, the authors suggest their findings ‘urge caution’ (sic) in interpretation of small differences, and that ‘bias-susceptible endpoints…should be used with care’. Translating into plain English, the masks don’t work, and the mandates should go.
The authors of the original report, who deserve full credit for releasing the raw data, have fought back in gentlemanly fashion. Much of the argument is focused on statistical niceties, in particular the type of analysis used to assess the statistical significance of the findings. These are complex academic matters, and, for those keen to avoid the pain of a four week crash course in medical statistics, not readily grasped in detail, though the crux is straightforward enough: have the necessary conditions needed for more sophisticated statistical analysis been met? The original report’s authors think they have, and so used more powerful (parametric) statistical methods on rates, while the authors of the ‘short note’ think they have not, and so used less powerful (non-parametric) methods on counts. Dr No takes the middle ground on this debate: it is useful to have both analyses. Such largesse is more than reasonable because there are other much more compelling reasons in the study for concluding that masks are to covid what the fig leaf was to Adam in the Garden of Eden — a cover-up, and not much else.
There are a number of clues in the original report that suggest something is amiss. This first is that something is amiss: the raw counts are missing. Neither the 111 page pre-print, nor the 19 page peer-reviewed version of the report, include numerators and denominators for the primary outcome, covid seropositivity following covid symptoms; instead, just the computed rates are reported. Authors (and so the media hacks that report the findings) omit raw counts for a reason: they flag up hotspots that suggest the conclusions may be suspect. This is our old enemy at work, presenting results only as relative risk reductions, rather than as, or at least with, absolute risk reductions. It allows utterly inconsequential differences to sound jolly impressive: a reduction from two in a million in the control group to one in a million in the intervention group yields a jolly impressive relative risk reduction of 50%, while the absolute risk reduction is a rather less impressive 0.000001 (2/1,000,000 minus 1/1,000,000). More pragmatically, among 2 million people, one person benefited. Even if such a result could ever achieve statistical significance (perhaps there were trillions of people in the study), it will never achieve practical significance.
This is such an important point that there are times when Dr No thinks the first rule of appraisal of clinical reports should be if there are no absolute numbers, only relative risks, then the paper goes in the bin there and then. On this first rule, the original Bangladeshi report fails, and that would in a sensible world be the end of the matter, were it not for the fact the establishment, the mainstream media, and a shocking 83% of respondents in a recent poll approve of government’s recent mask mandate for shops and public transport, presumably because the masks stop covid infection. No doubt the same people, polled on whether fig leaves stop men raping women, would reply yes, even in the face of millennia of evidence to the contrary.
Back to the Bangladeshi study. First, let’s take it at face value, and assume that the parametric statistical methods the authors of the original report used were valid. The first thing to note is that the study was a randomised trial, albeit a clustered one, in which villages rather than individuals were randomised, but it is still a randomised trial — or is it? The whole point of randomisation is that all the factors, known and known, that might influence the outcome of a study are randomly allocated to both the intervention and the control groups, and so, being present in equal measure in each group, they cannot explain any differences in outcome. So far so good, but there is a problem in the Bangladeshi study. The villages were randomised, but the recruitment of volunteers to the study suffered a significant bias. Individuals in villages allocated to the intervention were significantly more likely to be recruited to the study than those in villages allocated to the control group. This can be seen in the numbers in each group: 170,497 in the intervention group, compared to 156,938 in the control group. With true randomisation, the numbers should be much closer, and the fact that they are not tells us that recruitment was not random.
We have a trial that was randomised in name, but not in practice. The reason for the differential recruitment was almost certainly greater zeal on the part of the non-blinded recruiters (they knew whether the village was an intervention or a control group) in intervention villages. It matters because of the very real possibility that the difference in numbers is also reflected in differences in behaviour in those recruited, particularly in the marginal volunteers, the ones sucked into the trial in the intervention villages, but left out in the control villages. Let us consider how this might affect results in practice.
Imagine two identical villages each with 100 inhabitants. Everything about the villages is identical, even down to the number of covid infections, say every tenth person gets infected, and so the incidence in each village is an identical 10%. Now imagine the two villages were selected for a mask trial, with one village getting masks and the other not getting masks. At the same time — as happened in the Bangladeshi trial — the recruiters in the mask village were more zealous, and managed to recruit 60 volunteers, compared to only 50 in the control village. As it happens, those 10 marginal recruits were inevitably more indolent than the more easily recruited, and so when the time came to report their symptoms and undergo a blood test, they simply didn’t bother. The trial runs its course. Let’s see what happens.
In the control village, 5 of the 50 willing participants get infected and test positive, giving a rate of 10%, (5/50) as expected. But something different happens in the mask village. The 5 infected willing participants come forward and become cases, but the sixth infection in the 10 marginal participants doesn’t appear, because that marginal participant fails to report his infection, giving an apparent infection rate of 5 out of 60 subjects, or 8.3%, even though the underlying infection rate was an identical 10%. This is another example of lies, damned lies and denominators. The differential behaviour in the mask village bumped up the denominator (from 50 to 60) but the number of cases that came forward remained the same (the 5 willing participants in each village), and so the apparent rate appears lower in the mask village, 8.3% compared to 10%, even when the underlying true rate is identical in both villages.
Now, as it happens, the relative risk reduction of 17% in this hypothetical study with identical underlying rates is actually considerably larger than that reported by the authors of the Bangladeshi study, which also had unbalanced denominators (170k to 157k), of around 10%. It is eminently plausible that the observed effect in the Bangladeshi study appeared solely because such a bias was at work. We have to conclude that the Bangladeshi study — the biggest, most ambitious study of its kind ever undertaken — failed to demonstrate that masks do anything to prevent the spread of covid infection.
In a sane world, that would be a big enough nail to keep the mask coffin shut forever. But we are not in a sane world, so Dr No is going to bang in another nail, just to make sure the coffin remains forever shut. Recall that the authors reported a headline relative risk reduction, of around 10% (the exact percentage varies slightly, depending on how it is presented). This, of itself, is a marginal reduction — 10% is hardly impressive — and furthermore, it is of marginal statistical significance: the reported adjusted prevalence rate of 0.91 has a confidence interval of 0.82 to 1.00, which just includes 1, meaning marginal significance. But what about the absolute numbers, and so absolute risk reduction and number needed to treat?
As we noted earlier, neither the pre-print nor the peer reviewed published report contains these numbers, though they did report symptomatic seropositive rates: 0.76% in the control villages, against 0.68% in the intervention villages. This gives us again a 10% or so relative risk reduction (0.08/0.76 = 0.105, or 10.5%) and an apparent absolute risk reduction of 0.08% (0.76 – 0.68), but we still don’t have the absolute numbers, that is, how many individuals benefited. We get the same percentages from 76 out of a thousand against 68 out of a thousand (8 individuals benefit) as we do from say 760 out of ten thousand against 680 out of ten thousand (80 benefit). They did however become available when the authors, to their credit, released the raw data. The absolute numbers (see page 3) of seropositives in the control group was 1,106, and 1,086 in the intervention group, an absolute difference of only 20 individuals. Not exactly a corking result from a study that enrolled over a third of a million subjects.
It is not clear what denominators the authors used to generate their rates of 0.68% and 0.76%, but by reverse engineering it appears they used a number close to all subjects in each arm. In doing this, they have perhaps done themselves a disfavour, in that only around one third of those with symptoms had their blood tested for antibodies, but if we run with these numbers (1,106/145,526 = 0.76% in the control group, 1,086/159,706 = 0.68% in the intervention group) we (unsurprisingly, Dr No has done the standard sums just to confirm everything adds up, and that there is no numerology involved) find the absolute risk reduction again to be 0.08% (0.76 – 0.68), a rather less impressive result than the already far from impressive 10% or so relative risk reduction. The number needed to treat, in this case submit to a eight week intensive mask promotion exercise, is well over a thousand, 1250 individuals, to prevent one extra case of seropositive covid infection. That is a monumental amount of work to achieve one less covid infection. And to cap it all, the study result includes the possibility that the one less case may have arisen because of bias, or even merely by chance.
There are a number of other flaws in the study, but this post is getting over-long, and has already made the key point: the Bangladeshi Mask RCT, the biggest, most ambitious of it kind ever done, failed to demonstrate that masks prevent covid infection. Let those who believe in masks wear masks. For the rest of us, it is time, Dr No thinks, to have a bonfire of the straw masks.
I quite agree, it’s ? time; woteva else, trying to stop ‘a virus’ (for it has not legs nor wings) with a mask is like trying to stop a flea with a tennis net; relative size surely says all we need to know….until singers go on about droplets, and then we need to remember that 99.9999% of the population don’t communicate through articulation and volume designed to carry across a 60 piece orchestra into a softly furnished and non-resonant auditorium (where the front row do, indeed, need an umbrella). Yer’average visit to Sainsbugs will be very largely droplet-free. Yep, ? masks and reveal smiles!
The uselessness of surgical masks for stopping inward bound and outward bound infection was well established long before the pandemic came along. Studies done during the pandemic are therefore worthless – unless someone has good evidence that the dispersion of aerosols depends on the virus that the tiny droplets are host to.
In which case this hypothetical person should drop a line to the Nobel committee immediately.
Yes, plenty of pre-covid studies showing masks don’t work. That’s why the early pandemic advice went against masks. But it has to be said the trials weren’t perfect, because trials of mask effectiveness are not easy to do well – something the Bangladeshi study shows as well. And then, early in the pandemic, we had the Milk Curdler and her ilk, and their bonfires of the straw men…
The Bangladeshi study was almost certainly a we know the answer now let’s find the evidence study. There are many more red flags. The investigators didn’t use intention to treat analysis (risk: drop ‘awkward’ subjects from the study). They deviated from the pre-published analysis plan (risk: adapt the analysis to suit purposes). They conducted multiple sub group analyses (risk: data dredging, until you find something interesting, which sooner or later you will, just by chance). It also had ‘odd’ funding: a charity which leaves one wondering whether there was an agenda, and economists as principal investigators, ie PIs from the discipline that make astrology look rigorous (and so on to maskology, the discipline that makes economics look rigorous). When a study has more red flags than an army gunnery range then it usually means there will be something wrong with the published conclusions.
I really can’t see how one would get past the behavioural issues that would confound any mask study, as they clearly have profound psychological impact (as our spi-b overlords keep droning on about), so even if prior behaviour is controlled for, a village of masked people is much more likely to be a fearful and fretful place as everyone signals their status as plague spreading sub humans to each other, all the time.
Unless the effect is vast there will never be any signal discernable in the noise.
“The uselessness of surgical masks for stopping inward bound and outward bound infection was well established long before the pandemic came along”.
Yes indeed. To coin a phrase, the science was settled.
Pity that particular cliche seems to cut one way only.
Thanks very much for yet another thorough and incisive study, Dr No! No doubt like many others, I look foward with great interest to your articles.
At the risk of being really boring, I feel the need to repeat some of my previous remarks.
It is useful to dissect studies like the Bangladesh one – but it seems to me that the study was based on PCR testing (mostly). To my mind, that makes the whole thing completely pointless right from the start.
Perhaps all discussion of anything Covid-related should be prefaced with a declaration of whether the treatment will be medical/scientific or political/business. From the medical/scientific point of view, it seems to me that there is no case at all for wearing masks to protect against any virus except in special circumstances (operating theatres, etc.) And even in an operating theatre, I understand the purpose of masks is to prevent the theatre staff from depositing lumps of mucus in the patient – not to contain viruses.
From the political/business point of view, there is no point at all in advancing any scientific or mathematical or logical arguments at all. They will simply be ignored or swept aside with vigorous gestures of the arms.
A fine example of all this can apparently be found in “A Plague Upon Our House: My Fight at the Trump White House to Stop COVID from Destroying America” by Dr Scott Atlas. (I haven’t read it myself). I did read the following review, though:
https://www.city-journal.org/review-of-a-plague-upon-our-house-by-scott-atlas
‘Atlas expected to spend his time at the White House discussing scientific data and debating the best strategies for protecting public health. Instead, he found that the Task Force included “zero public health policy experts and no experts with medical knowledge who also analyzed economic, social, and other broad public health impacts other than the infection itself.” Vice President Mike Pence chaired the Task Force, but Atlas says that Pence and the other members were regularly cowed into submission by three doctors who dominated from the start: Deborah Birx, the Task Force’s coordinator, along with Anthony Fauci, director of the National Institute of Allergy and Infectious Diseases, and Robert Redfield, director of the Centers for Disease Control…
‘For what I anticipated would be a data-filled discussion about opening schools and the risk to children,” Atlas says, “I brought approximately fifteen different studies and a summary sheet of the research. For what I hoped would be a discussion about testing guidance, I brought and distributed articles and other documents about the role and pitfalls of PCR testing and concerns about cycle thresholds. Even though I handed out a number of these published studies to everyone at the table, no one ever mentioned them in the Situation Room. My guess was that no one in the Fauci-Redfield-Birx troika ever opened them.”
Instead, the troika of bureaucrats obsessed over Birx’s charts showing how many Covid tests had been administered and what percentage were positive. They proclaimed success for their strategies when infections started to wane in states like New York and Arizona—never mind that the downward trends began before the lockdowns and mask mandates were imposed. They ignored inconvenient data, like the chart that Atlas reproduces comparing the rates of Covid cases in states with and without mask mandates: the two curves remained virtually identical throughout the pandemic. “The doctors in the Task Force showed no study about mask efficacy or any other of their policies, and they never once mentioned the harms of the lockdowns that I witnessed,” Atlas says’.
According to Wikipedia, Deborah Birx looks like a clever and hard-working doctor; but my heart sank when I read that she “specializes in HIV/AIDS immunology, vaccine research, and global health”.
Hmmmmmm. To my mind, HIV/AIDS is essentially a huge racket mainly orchestrated by Dr Fauci (for whose disastrous self-seeking career, see Robert Kennedy’s new book). Vaccine research… hmmmm. And of course “global health” – which chimes with “vaccine research” and “HIV/AIDS” as basically about making enormous piles of money by experimenting on poor ignorant people from backward countries.
There is, however, one bright glow on the horizon:
“Bill Gates Charged with Murder for COVID-19 Vaccine Death in India’s High Court – Death Penalty Sought”
https://conservativechoicecampaign.com/bill-gates-charged-with-murder-for-covid-19-vaccine-death-in-indias-high-court-death-penalty-sought/
May I recommend this post, at another blog, to your readers?
https://churchmousec.wordpress.com/2021/10/05/dairy-farmer-explains-the-scam-and-sham-of-coronavirus/
Tom – rather bizarrely, and as far as Dr No can see, without explanation, the Bangladeshi study used antibody tests (serology), bizarre because serology looks for evidence of past (including recent past) infection, so the positives will include some who got infected before the study even started. Seropositivity in nearby India was just under one in four around the time the trial happened, so perhaps 250 or so of the positives in each arm of the study were in a way false positives, insofar as they were markers of previous infection, and so not relevant to the trial period (a trial intervention that hasn’t started generally can’t have any effect…).
One possibility is the investigators favoured bumping up the numbers of positives (by using a test that would detect past infections) but against that, they missed out on using the uncannily sensitive PCR test, which can detect broken needles in haystacks at a hundred paces, many days after the broken needle disintegrated into rust fragments. Surely that’s the way to bump up positive numbers…
The other big point about the blood tests is that only around one third of those who reported symptoms actually ended up having their blood tested. For the analysis to be valid, this requires an assumption that those who ended up having their blood tested were representative of the two thirds of those who reported symptoms who didn’t have their blood tested. If the one third sample got skewed in one direction or the other, then the results and conclusions start to wobble…
But this is all a political game, as we have known for a long time. In Dr No’s view, covid masks are 0% about health, and 100% about politics, in particular the politics of compliance. Although visually different, they serve precisely the same social and political functions as a Nazi armband. They signal allegiance, conformity, and, sadly but increasingly, a willingness to thump those who do not display signals of allegiance and conformity.
But in another bizarre twist, the general effect of a mask mandate (over a recommendation) is that it dilutes the allegiance signal, because some of those wearing masks will, under cover of their masks, be anti-maskers, even if those who still, despite mandates, remain maskless are clear enemies of the state (unless they happen to be hapless individuals with a permitted reason for not wearing mask).
Or perhaps covid masks are BoJo’s modern version of Marie-Antoinette’s apocryphal ‘Let them eat cake’…
dearieme – a very interesting post, especially the idea of ‘Immunity as a Service’/subscription based model as in software. You could even call the boosters security patches, like Windows Updates. Now where did they come from? But let’s not go there. Yet the fallibility of flu vaccines in particular and respiratory vaccines in general has been staring those of us willing to look in the eye right from the beginning of the pandemic. Dr No was almost surprised they even managed to make a vaccine for covid – and now it turns out it they haven’t, except possibly as a porous temporary finger in the dyke job.
Dr No wonders if the Canadian dairy farmer did something else before becoming a dairy farmer…
It is worth remembering the purpose of surgical masks. They were intended to limit water droplets which may contain bacteria from the respiratory tract, exhaled from medical/nursing staff standing directly over or next to a patient, from falling into an open wound and despite such bacteria being harmless in the respiratory tract, they may cause infection of the wound.
The N95 respirator mask is the gold standard, and so named because the manufacturers state they will stop 95% of exhaled particles of 3 micron and above, this being the size of expired water droplets. Of course no claims are made for particles arriving at the exterior surface of the mask, because these masks were never intended to protect the wearer.
Regular paper masks have about a 50% to 70% effectiveness, when dry, cloth masks are just decorative.
But even 95% effective means 5% gets through and that’s not really good enough for infection control of airborne virus. Also it means water droplets broken down or virus deposited on either surface of the mask, will migrate will through the damp material to be either inhaled if incoming, or pushed off into the air by expired breath and speech through the mask or by air currents flowing over the mask surface.
When talking into a mask, it’s like throwing tomatoes at a tennis racket.
Just because a device is fit for use in a particular circumstance, does not mean it is for all. Water based fire extinguishers put fire out, but just because it will extinguish flames if your sofa catches fire, doesn’t mean you should use it if your chip pan catches fire… if you do, results are spectacular, and it makes matters worse – just like the general public using surgical masks for a purpose for which they were not intended, and in any case not wearing and handling them properly increasing spread of infection more than not wearing them.
Any ‘study’ that requires ‘statistical analysis’ to ensure the results the studiers wanted or expected, is not science. If it’s not in the raw data but is in the derived output, then it is the manipulation of the data creating the result.
Like climate ‘science’ and the Global Mean Temperature Anomaly record which has an output of greater accuracy to the decimal place than the input raw temperature data. Hence they are able to show ‘global warming’ of tenths, even hundredths of a degree that actual instruments cannot detect and do not report. Manmade global warming indeed.
As Dr No says, it all seems to be political with just a thin decorative layer of medical jargon.
Both with the wearing of masks and with the PCR non-test, they didn’t have anything remotely effective. So they pretended they did.
Oh for Christ’s sake!
‘The British Medical Association (BMA) has declared that those who suffer from asthma should still abide by mask mandates and guidelines, with the trade union’s Dr. Alan Stout stating that “99% of people who have those conditions can wear a face mask”. The charity Asthma U.K. also agree with the BMA’s view, saying that asthma suffers “can manage to wear a face mask or face covering”.’
It’ll be cadavers next. And/or bats.
Even using the results they gave us showing “9% benefit from mask usage”, summarised as 0.76% rate in unmasked group (150,000 people), 0.76% cloth mask group (50,000) and 0.68% paper mask group (100,000), this is too trivial a benefit to mandate mask usage. Your work in clarifying the whole study makes an even more compelling case. How can the Sage-ists ignore this??
I questioned the Welsh government as to what information they used to justify their advice, and was referred to the 60 page UK government summary of mask evidence, which I read through. The overall finding even in their own document was” Low quality evidence of slight benefit”
(paraphrase).
Its all mindbogglingly mindboggling, the mind just boggles Dr No. Thanks so much for your work, it lifts morale.
(PS your subscriptions page says my email is not valid, I assure you it is!)
Dr No’s mind got boggled some time ago. In brief moments of unbogglement, the only thing that makes sense is that masks aren’t about disease control, they are about subject (of the state, not trial) control, the Nazi armband re-invented for the 21st century.
Thank you very much for mentioning the email subscriptions page problem, and sorry to hear you had the problem. Your email must be valid, it’s what allows you to comment (after perhaps a first moderated one). I have contacted the subscription plugin developers, asking them if they can fix this off-putting behaviour. In the meantime, if anyone else has had the same problem, please do accept my apologies, and if possible let me know, via the Contact Form, as there is an option to add subscribers manually.
PS an adaptation of the old chemotherapy joke: Why do coffin lids have nails? To stop the covid police putting a mask on the body.
You heard it here first! Good news! Good News! (Well, actually very BAD news but the fact that it is now news is good).
“Court-Ordered Pfizer Documents They Tried to Have Sealed for 55 Years Show 1223 Deaths, 158,000 Adverse Events in 90 Days Post EUA Release”
https://www.globalresearch.ca/court-ordered-pfizer-documents-they-tried-sealed-55-years-show-1223-deaths-158000-adverse-events-90-days-post-eua-release/5764094
Tom – well spotted, and it’s an important document, but we need to be careful. Although Pfizer (Pfuzer?) redacted the number of doses, they did say where most of the reports came from, and so we can get a good idea of the number of doses from Our World in Data. It’s over 100 million doses by 28th Feb 2021 for all vaccines:
OWID also have a breakdown by vaccine manufacturer for the US, but not the UK, with an almost 50:50 Pfizer/Moderna split, so lets say 40 million Pfizer doses. The UK Weekly Yellow Card Report for 11 March 2021 (WayBack Machine) gives us another 11.5 million or so Pfizer doses in the UK:
“This safety update report is based on detailed analysis of data up to 28 February 2021. At this date, an estimated 10.7 million first doses of the Pfizer/BioNTech vaccine and 9.7 million doses of the Oxford University/AstraZeneca vaccine had been administered, and around 0.8 million second doses, mostly the Pfizer/BioNTech vaccine, had been administered.”
Lets say something around 55 million total Pfizer doses up to and including 28th Feb 2021. We have 1,223 reported deaths for 55 million doses. And many of those early doses went in to the elderly and the clinically vulnerable, folks more likely to die sooner rather than later…
Regrettably, the Pfizer report doesn’t give an age/sex breakdown for the 1223 deaths (they surely have the data, and it could have been their get out of jail card, if most of the deaths were in the (very) old – so why didn’t they report deaths by age???) but they do give a sex and then age breakdown for all reports. Curiously, women were three times more likely than men to report side effects, and even more curiously the mean (median would have been better) age of those reporting side effects was is 50.9 years old – seems very ‘young’ when mostly older folks got vaccinated. Perhaps the US jabbed a lot of middle aged female healthcare workers early on, and that skewed the figures?
Dr No’s hunch that we don’t have anything like a full picture on vaccine side effects including deaths remains as strong as ever, but this Pfizer document, though interesting, doesn’t really tell us very much. Rather like the ONS deaths by vaccination status data, we need more detailed data, especially by age.
Less than the content, I was pleased that a judge could order all that material to be released immediately when the FDA were going to hold it back for 55 years (obviously, until all the guilty were dead).
I am emboldened to suggest this rather good presentation by Dr David Healy which I saw yesterday. Although some of the statistics went over my head, I was astonished at the sheer duplicity and cynicism of Big Pharma and its government adjuvants.
https://davidhealy.org/where-does-the-misinformation-come-from/
Great and informative ‘conversation’ – thanks all!
Can anyone please tell me what the hell is (supposedly) going on with the new phrase about Pfffffizer’s juice, which (apparently) ‘neutralises’ O-mi-god-i-crom??? (‘Three doses of Pfizer vaccine ‘can neutralise Omicron variant’ – London Evening Standard – which already beggars belief.) Since when has the term ‘neutralise a virus’ appeared in science? Of course, ‘The Science™️’ has its own lexicon, but its new addition takes me way beyond irritation.
Annie – yes, it is all rather tedious euphemistic jargon which no one outside the labs came across until covid came along, and suddenly everyone in the MSM is a desktop immunologist! Neutralising antibodies are the ones that are supposed to give you sterilising immunity, ie no infection or illness at all, because the antibodies have ‘neutralised’ (‘nuked’) the virus, effectively sterilising it (sterile in the sense that it can’t replicate). Back in the real world, we have vaccines that are supposed to produce neutralising antibodies, but clearly either they don’t, or the ‘neutralising’ antibodies don’t in fact neutralise, or they wane, or whatever. Perhaps they should be called Macavity antibodies.
The Standard appears to be talking out of its backside, so nothing new there.
“The Standard appears to be talking out of its backside, so nothing new there”.
The situation reminds me of the old joke about the two men out hiking in the woods when they see a grizzly bear approaching them. One man kneels down and starts changing his boots for a pair of running shoes. “What on earth are you doing?” the other man asks. No one can outrun a grizzly!” “I don’t have to outrun the bear,” replies the runner; “I just have to outrun you”.
Similarly (if you can detect a tiny glowing spark of resemblance) the MSM don’t need to be truthful or accurate, as long as they tell stories that the broad masses find attractive and plausible.
Thank you Dr No – now I see it. And (Macavity anti-bodies they now are!) A friend has just suggested however that ‘they’ had to find a new word because ‘they’ now know ‘they’ can’t say it protects or immunises, because one heck of a lot of people know that ‘a the case now. Just a thought.
Tom, I love that story. My version has a tiger, but it’s very apt, no matter the creature!