There were lists of symptoms on the NHS website, in msm, appearing regularly to remind people of the 'raging pandemic'... many people must have looked at those changing lists ( new symptoms added) and thought " sounds just like what gran/grandad/ auntie/ uncle/ the lady next door said they had experienced. All driven by the relentless propaganda. As those symptoms cross over with colds, flu like illnesses, flu, 'chills', stomach bugs and so forth, it was like a big net had been cast to prove a symptom listed was 'Covid-19'.
The PCR and LFTs were used to establish( falsely) that there were 'cases' of 'covid', usually growing exponentially. The propaganda was the tool to 'subjectify' symptoms, so people would speak its name with fear, and say, "I've had it", "I've tested 'positive', joining the great "Covid-19' club, like a badge of honour.
I have questions. Their “covid symptoms” are symptoms of colds, allergies, flu, drunkenness, hangovers, and, inexplicably, chafing. Can’t the “study” authors vague that up at all? Shouldn’t the fact that the authors didn’t provide basics like their raw data, methodology, and some kind of control automatically make the whole exercise a farce to be laughed out of the room? The people who responded to that survey were just ret-conning themselves into “having covid” a year earlier because that’s what they were being asked about. If they’d been asked about having any of those symptoms at any other time from the previous three years through the day before they filled out the survey, they’d have said the same thing. How did the “study” authors correct for expectation bias in the respondents? That's rhetorical; they obviously didn't. Did they ask how many times the respondents experienced those symptoms in the preceding period, or would that have been too much like acknowledging that “covid” symptoms are cold symptoms and no one can tell them apart? They just assumed that these people experienced a single episode of them and that it was therefore “covid.” That’s in the dictionary under “confirmation bias.”
Not that I believe anything based on rapid antigen “testing.” If the human immune system treats all coronaviruses the same by generating BOGO crossover immunity after it’s coped with one of them, what makes the REACT “researchers” so sure that the LFT can tell the resulting antibodies apart? Has it been established that the immune system generates antibodies for one coronavirus that are distinct from another, and capable of being told apart with a mailed-out, at-home blood test? Isn't that like trying to emerald-cut a diamond with a cold chisel from Home Depot? And anyway, isn’t there an aphorism to the effect that the plural of anecdote isn’t data, or did I just dream that?
I majored in English so I wouldn’t have to take statistics because I’d have flunked it repeatedly. If I can see that many obvious flaws in someone’s “study” then I have to conclude that the reason it’s being cited as quality evidence of anything is because it serves someone’s agenda of keeping the psyop in play. To rule? To save face? It doesn’t matter.
An English major is actually better-equipped to read and spot the nonsense in most studies than are many who have taken the full panoply of statistics courses. Every word matters.
Very thoughtful and thorough analysis of what is at its essence, an irresponsible, unscientific, unverifiable study. This due to the fact it utilized an uncontrolled, inconsistent, non medical means to obtain the data, rendering the data useless.
'Omicron' was an interesting moment: until that scare campaign was started, and they were pushing it hard, many lived in fear of Covid who hadn't tested positive at any time.
And this is how it went: they felt ill with something not very unpleasant, merely 'coldy', dutifully tested, got a positive, and when nothing bad happened to them, that was the end of the fear of 'Covid' in general, not just Omicron.
This suggests that by that stage, 'peak susceptibility' to fear propaganda had already passed in much of the population.
Not, of course, that they had actually seen through the fraud entirely.
Omicron was weak because some time had passed from the vaccinations (and most didn't do the boosters, so they weren't up to date).
On the other hand, "Delta" came around after big waves of vaccination.
Yes, people are seeing through the fraud. Many still believe in it but thankfully, their bodies/subconscious are keeping them away from taking boosters.
It's astonishing COVID sceptics are STILL intent to debate the nature of 'the pandemic' in 2025 given the Scottish and now even in part UK COVID inquiry evidence submitted under oath. Take just 7 minutes to watch this video folks then ask why those most 'outspoken' are content to relegate this information in discussions when it comes to exposing what really went on from 2020.
Love you guys. I love your catch that the August 2019 sample set had no internal positive control, i.e. that the researchers were capable of detecting a signal that should have been there, thus confirming the integrity of the sample. Basic bench work science.
Unlike PCR testing, which wasn’t invented until I’d left the academic world for industry, so what I know about it derives from having hired people who had hands on experience of using the technique, I have personally developed tests for substances in biological fluids using antibody based systems.
I’ve looked for “the seminal paper” which describes the first antibody based analytical method to detect (allegedly) “the virus”. I’ve failed to find it. Does anyone have that foundational paper? It ought to have been as famous as the Corman-Drosten paper on PCR based (alleged) detection of “SARS-CoV-2”.
In order to have an antibody to evaluate, an antigen is required, in quantity and in a pure or at least purified form (meaning that substantially everything else to which an immune response might be possible has been removed). This is required in order to “raise antibodies” to “the virus” in a suitable species. Typically, a large animal is used, such as a donkey, because very large volumes of what’s called “antisera” can be obtained after usually two injections of the alleged virus, two weeks apart, by drawing blood in an unheparinised tube and allowed to clot. The resulting clear to straw coloured serum is drawn off, divided into small volumes in special tubes and frozen.
Then you can begin to characterise what you have. It’s that paper I’d like to read. Without such a detailed Methods paper, we cannot say anything about what the alleged tests are detecting. Nothing at all.
By the way, these are known as polyclonal antisera, because the animal makes a variety of antibodies to whatever they’ve been injected with.
There are other ways to generate antibodies using, for example, synthetic antigens. It’s important to note that these are very unlikely to mimic the alleged natural antigens, because the latter is subject to post-transcriptional modifications in the body, additions of sugar moieties for example are commonplace and these can and do radically alter the ability of antibodies to recognise antigens in the sample.
The technique is fraught with technical hurdles and it’s not unusual for there to be cautions associated with any large scale testing system developed using this principle.
For example, cross-reactivity to things you didn’t guess might be problematic. Even if an honest, competent job was ever done on this (& I’m confident it wasn’t & couldn’t have been, because the entire scenario that they’re pretending to study doesn’t even happen), you don’t know what you don’t know. You can easily get spurious results and not even know it.
It stands to reason that after everything I’ve learned about the virus-disease model as portrayed, I regard “viral load” as a measure of clinical significance as nonsense.
Interesting how peoples memory of illness over a year later did not seem to introduce significant time smearing in the distribution. The covid designation helps this — I can tell you I had respiratory symptoms in February 2020, but that is because I have the time-marker of the events of the months following to reinforce that memory, and have been told such symptoms are worth remembering to place me among the hard fought veterans of the terrible disease. I do know I’ve also had some of these symptoms in the past year with quite a bit of certainty. I could not tell you what month without spending some time remembering what else was going on.
I think that the non positive data is at a per month resolution tells me its not included in the plot. Either there would be visible monthly spikes, or maybe a bar like structure. Personally If I were to combine them I’d bin both in 1 month chunks. Rolling averages are always sketchy without the actual datapoints also plotted. Would be interesting to see the data. Actually does the integral work for this? This can’t be from ~100k people
Completely agree, of course, with the memory reinforcement and that's something we allude to here and have all spoken to in other articles, in different ways.
Would people have thought their storied late 2019/early 2020 "I think it was COVID" illness was remarkable at all were it not for the events of the period? I doubt it. (Reminds me of the points I was making here regarding the Apple Watch app. I said 'nocebo effect' but it's more Pavlovian than that. https://www.woodhouse76.com/p/apple-enters-the-nocebo-effect-business)
With apologies to the gentlemen, there's also this, which I have observed occur with my spouse of 27 years more than once: https://en.wikipedia.org/wiki/Man_flu :)
Agreed that the non-positive data aren't in the plot. Why the plot doesn't specify "unvaccinated" as mentioned in the prose, we're not sure. Obviously, no one would've been vaccinated (with the COVID shot, that is!) prior to December 2020, so I can sort of see why only the unvaxed were used.
I also agree re: rolling average. As to why,I initially speculated to JE that the plot took the average of the two dates respondents gave: onset and resolution, but the prose says "onset" so we went with that.
The email to the authors is an attempt to avoid a bunch of guesswork...we'll see if they respond.
So I uploaded a screen grab of the plot to grok and told it to integrate it. It sums to about 5590 (I guessed around 5k, so sounds good). Can’t find reference to a similar number in the text, so would say we have no idea what thats actually plotting 🍒⛏️
The authors should absolutely be able to reply to your query with code + data to reproduce the plot.
First I’ve heard of “Man-flu”. Interesting, and matches male vs female observations around this household. Lotsa unconstrained variables in that problem though, including daily habits (work/school/home), even bathroom use.
BTW a grok conversation regarding this paper was sorta interesting — it kept trying to bring in external case data and consistency thereof to justify the plot. If you guys fail to extract what you need to reproduce the plot from survey data I’d assume some manipulation of UK case data as the ultimate source.
No idea at all - ergo, "In summary, the curve from the REACT-2 report appears to be meaningless."
The authors are from Imperial College, so hopefully they will reply. If they didn't use the data they gathered, or did but used some kind of back-projection of cases to force-fit, that would be a no-no.
Technically, some number of people – as participants (useful lab rats) in the various clinical trials – would have been "vaccinated" with the various "vaccines" for "covid" prior to December 2020.
So the testing started in October ! How odd , the same month as rumours of a Reset event would take place on October 18, 2019 at the Wuhan military games coincidentally the same day as the John Hopkins & Bill & Melinda gates foundation executed Event 201 a simulation where a bat covid virus outbreak would lead the world into lockdown .
The AB (self)testing reported in the study occurred in early 2021. As best we can tell, Figure 1 is "constructed" from the dates that respondents with positive AB results estimated as their onset date for the symptoms they said they had.
Not sure what your perspective is on the other events you've mentioned (i.e., what you believe they are or aren't "evidence" of), but incidence of "COVID-like illness" among U.S. participants in World Military Games in Wuhan cannot be cited as evidence of early spread of a new thing. https://www.woodhouse76.com/p/department-of-defense-2019-world
Wow. I read it. to be honest... Not quite what you both are seeing that others don't or others seeing what you don't when you said it's not totally wrong or counteproductive? In my view it's like this. There is something called as antibodies. Claim.. evidence doesn't support the existence. Period. Will be following you though.
Wow that study is junk science.
I don’t think “science” at the end of your statement is appropriate. That said, I’m interested in the tests’ cross reactivity with Coke and OJ.
https://www.researchgate.net/publication/349881372_Effect_of_Coronavirus_Worldwide_through_Misusing_of_Wireless_Sensor_Networks
http://pervasivecomputinginfo.blogspot.com/2018/10/ieee-802156-standard.html
There were lists of symptoms on the NHS website, in msm, appearing regularly to remind people of the 'raging pandemic'... many people must have looked at those changing lists ( new symptoms added) and thought " sounds just like what gran/grandad/ auntie/ uncle/ the lady next door said they had experienced. All driven by the relentless propaganda. As those symptoms cross over with colds, flu like illnesses, flu, 'chills', stomach bugs and so forth, it was like a big net had been cast to prove a symptom listed was 'Covid-19'.
The PCR and LFTs were used to establish( falsely) that there were 'cases' of 'covid', usually growing exponentially. The propaganda was the tool to 'subjectify' symptoms, so people would speak its name with fear, and say, "I've had it", "I've tested 'positive', joining the great "Covid-19' club, like a badge of honour.
The "worried well" were definitely weaponised. First insisting on their own treatment and secondly, insisting everyone else be too.
Indeed. The PCR and LFTs were also used to make money for someone.
Read the short abstract. 👇
https://www.researchgate.net/publication/349881372_Effect_of_Coronavirus_Worldwide_through_Misusing_of_Wireless_Sensor_Networks
http://pervasivecomputinginfo.blogspot.com/2018/10/ieee-802156-standard.html
The "test" has spread, nothing else.
I can't believe Clare Craig doesn't understand that.
Excellent critical work! Thank you.
I have questions. Their “covid symptoms” are symptoms of colds, allergies, flu, drunkenness, hangovers, and, inexplicably, chafing. Can’t the “study” authors vague that up at all? Shouldn’t the fact that the authors didn’t provide basics like their raw data, methodology, and some kind of control automatically make the whole exercise a farce to be laughed out of the room? The people who responded to that survey were just ret-conning themselves into “having covid” a year earlier because that’s what they were being asked about. If they’d been asked about having any of those symptoms at any other time from the previous three years through the day before they filled out the survey, they’d have said the same thing. How did the “study” authors correct for expectation bias in the respondents? That's rhetorical; they obviously didn't. Did they ask how many times the respondents experienced those symptoms in the preceding period, or would that have been too much like acknowledging that “covid” symptoms are cold symptoms and no one can tell them apart? They just assumed that these people experienced a single episode of them and that it was therefore “covid.” That’s in the dictionary under “confirmation bias.”
Not that I believe anything based on rapid antigen “testing.” If the human immune system treats all coronaviruses the same by generating BOGO crossover immunity after it’s coped with one of them, what makes the REACT “researchers” so sure that the LFT can tell the resulting antibodies apart? Has it been established that the immune system generates antibodies for one coronavirus that are distinct from another, and capable of being told apart with a mailed-out, at-home blood test? Isn't that like trying to emerald-cut a diamond with a cold chisel from Home Depot? And anyway, isn’t there an aphorism to the effect that the plural of anecdote isn’t data, or did I just dream that?
I majored in English so I wouldn’t have to take statistics because I’d have flunked it repeatedly. If I can see that many obvious flaws in someone’s “study” then I have to conclude that the reason it’s being cited as quality evidence of anything is because it serves someone’s agenda of keeping the psyop in play. To rule? To save face? It doesn’t matter.
An English major is actually better-equipped to read and spot the nonsense in most studies than are many who have taken the full panoply of statistics courses. Every word matters.
https://www.researchgate.net/publication/349881372_Effect_of_Coronavirus_Worldwide_through_Misusing_of_Wireless_Sensor_Networks
http://pervasivecomputinginfo.blogspot.com/2018/10/ieee-802156-standard.html
All made up!
No evidence of any pathogen!
Review the Control Studies Project for valid control research!
https://open.substack.com/pub/controlstudies/p/we-have-proved-viruses-dont-exist?r=yz29c&utm_campaign=post&utm_medium=web&showWelcomeOnShare=false
Truth, Love, Justice and Freedom!
Nothing new but a renamed flu!
Very thoughtful and thorough analysis of what is at its essence, an irresponsible, unscientific, unverifiable study. This due to the fact it utilized an uncontrolled, inconsistent, non medical means to obtain the data, rendering the data useless.
'Omicron' was an interesting moment: until that scare campaign was started, and they were pushing it hard, many lived in fear of Covid who hadn't tested positive at any time.
And this is how it went: they felt ill with something not very unpleasant, merely 'coldy', dutifully tested, got a positive, and when nothing bad happened to them, that was the end of the fear of 'Covid' in general, not just Omicron.
This suggests that by that stage, 'peak susceptibility' to fear propaganda had already passed in much of the population.
Not, of course, that they had actually seen through the fraud entirely.
Omicron was weak because some time had passed from the vaccinations (and most didn't do the boosters, so they weren't up to date).
On the other hand, "Delta" came around after big waves of vaccination.
Yes, people are seeing through the fraud. Many still believe in it but thankfully, their bodies/subconscious are keeping them away from taking boosters.
Omicron was moronic, the anagram which was a clue to the wise.
It's astonishing COVID sceptics are STILL intent to debate the nature of 'the pandemic' in 2025 given the Scottish and now even in part UK COVID inquiry evidence submitted under oath. Take just 7 minutes to watch this video folks then ask why those most 'outspoken' are content to relegate this information in discussions when it comes to exposing what really went on from 2020.
https://biologyphenom.substack.com/p/newnever-forget-2025?utm_source=publication-search
Love you guys. I love your catch that the August 2019 sample set had no internal positive control, i.e. that the researchers were capable of detecting a signal that should have been there, thus confirming the integrity of the sample. Basic bench work science.
Thanks. BTW the "Aug 2019 samples" were actually collected a long time before then...as per footnote 8.
Aug 2019 is just the latest date which satisfies the MHRA suggestion that samples be from 6 months prior to "the pandemic".
Your comment here prompted me to make that clearer in the main text - which I have just done.
Unlike PCR testing, which wasn’t invented until I’d left the academic world for industry, so what I know about it derives from having hired people who had hands on experience of using the technique, I have personally developed tests for substances in biological fluids using antibody based systems.
I’ve looked for “the seminal paper” which describes the first antibody based analytical method to detect (allegedly) “the virus”. I’ve failed to find it. Does anyone have that foundational paper? It ought to have been as famous as the Corman-Drosten paper on PCR based (alleged) detection of “SARS-CoV-2”.
In order to have an antibody to evaluate, an antigen is required, in quantity and in a pure or at least purified form (meaning that substantially everything else to which an immune response might be possible has been removed). This is required in order to “raise antibodies” to “the virus” in a suitable species. Typically, a large animal is used, such as a donkey, because very large volumes of what’s called “antisera” can be obtained after usually two injections of the alleged virus, two weeks apart, by drawing blood in an unheparinised tube and allowed to clot. The resulting clear to straw coloured serum is drawn off, divided into small volumes in special tubes and frozen.
Then you can begin to characterise what you have. It’s that paper I’d like to read. Without such a detailed Methods paper, we cannot say anything about what the alleged tests are detecting. Nothing at all.
By the way, these are known as polyclonal antisera, because the animal makes a variety of antibodies to whatever they’ve been injected with.
There are other ways to generate antibodies using, for example, synthetic antigens. It’s important to note that these are very unlikely to mimic the alleged natural antigens, because the latter is subject to post-transcriptional modifications in the body, additions of sugar moieties for example are commonplace and these can and do radically alter the ability of antibodies to recognise antigens in the sample.
The technique is fraught with technical hurdles and it’s not unusual for there to be cautions associated with any large scale testing system developed using this principle.
For example, cross-reactivity to things you didn’t guess might be problematic. Even if an honest, competent job was ever done on this (& I’m confident it wasn’t & couldn’t have been, because the entire scenario that they’re pretending to study doesn’t even happen), you don’t know what you don’t know. You can easily get spurious results and not even know it.
To your point “cross-reactivity to things you didn’t guess might be problematic” I assume you saw footnote 7?
Cross-Reactivity, seems to be echoed in Matt Irwin's paper on PCR & RNA Assays. You may be familiar with already - https://www.drmattirwin.com/uploads/5/5/3/4/55349259/false_positive_pcr_viral_loads.pdf (Irwin, 2001) 17 pages. He references - Piatek et al 1993, and others. You really only need to see 3-5 pages of Irwin's Review to get the idea.
Page 1, his hypothesis: "... much of the RNA measured by viral load assays does
not come from HIV, but rather comes from other microbes and from normal human
cells."
Page 2: "False positives occur with all of the available RNA assays, including the newer
generation of tests (Mendoza et al 1998)"
I think False Positives is good for business.
I wasn't actually aware of Matt Irwin, so thanks.
Interestingly, that was apparently a medical school elective project!
https://www.drmattirwin.com/pcr.html
Here's a more recent essay of his on the nature of pandemics:
https://www.drmattirwin.com/epidemics.html
It stands to reason that after everything I’ve learned about the virus-disease model as portrayed, I regard “viral load” as a measure of clinical significance as nonsense.
Interesting how peoples memory of illness over a year later did not seem to introduce significant time smearing in the distribution. The covid designation helps this — I can tell you I had respiratory symptoms in February 2020, but that is because I have the time-marker of the events of the months following to reinforce that memory, and have been told such symptoms are worth remembering to place me among the hard fought veterans of the terrible disease. I do know I’ve also had some of these symptoms in the past year with quite a bit of certainty. I could not tell you what month without spending some time remembering what else was going on.
I think that the non positive data is at a per month resolution tells me its not included in the plot. Either there would be visible monthly spikes, or maybe a bar like structure. Personally If I were to combine them I’d bin both in 1 month chunks. Rolling averages are always sketchy without the actual datapoints also plotted. Would be interesting to see the data. Actually does the integral work for this? This can’t be from ~100k people
Completely agree, of course, with the memory reinforcement and that's something we allude to here and have all spoken to in other articles, in different ways.
Would people have thought their storied late 2019/early 2020 "I think it was COVID" illness was remarkable at all were it not for the events of the period? I doubt it. (Reminds me of the points I was making here regarding the Apple Watch app. I said 'nocebo effect' but it's more Pavlovian than that. https://www.woodhouse76.com/p/apple-enters-the-nocebo-effect-business)
With apologies to the gentlemen, there's also this, which I have observed occur with my spouse of 27 years more than once: https://en.wikipedia.org/wiki/Man_flu :)
Agreed that the non-positive data aren't in the plot. Why the plot doesn't specify "unvaccinated" as mentioned in the prose, we're not sure. Obviously, no one would've been vaccinated (with the COVID shot, that is!) prior to December 2020, so I can sort of see why only the unvaxed were used.
I also agree re: rolling average. As to why,I initially speculated to JE that the plot took the average of the two dates respondents gave: onset and resolution, but the prose says "onset" so we went with that.
The email to the authors is an attempt to avoid a bunch of guesswork...we'll see if they respond.
So I uploaded a screen grab of the plot to grok and told it to integrate it. It sums to about 5590 (I guessed around 5k, so sounds good). Can’t find reference to a similar number in the text, so would say we have no idea what thats actually plotting 🍒⛏️
The authors should absolutely be able to reply to your query with code + data to reproduce the plot.
First I’ve heard of “Man-flu”. Interesting, and matches male vs female observations around this household. Lotsa unconstrained variables in that problem though, including daily habits (work/school/home), even bathroom use.
BTW a grok conversation regarding this paper was sorta interesting — it kept trying to bring in external case data and consistency thereof to justify the plot. If you guys fail to extract what you need to reproduce the plot from survey data I’d assume some manipulation of UK case data as the ultimate source.
Thanks. Nice - didn't know Grok could do that.
No idea at all - ergo, "In summary, the curve from the REACT-2 report appears to be meaningless."
The authors are from Imperial College, so hopefully they will reply. If they didn't use the data they gathered, or did but used some kind of back-projection of cases to force-fit, that would be a no-no.
No further comment on Man Flu. :)
These LLM tools can be useful, but like chainsaws need to be wielded with great care.
https://m.youtube.com/watch?v=-k3ABfmCr2I&pp=0gcJCfcAhR29_xXO
Exactly
Technically, some number of people – as participants (useful lab rats) in the various clinical trials – would have been "vaccinated" with the various "vaccines" for "covid" prior to December 2020.
There were roughly 165K respondents who provided usable results
What % do we think happened to be in a vaccine trial?
So the testing started in October ! How odd , the same month as rumours of a Reset event would take place on October 18, 2019 at the Wuhan military games coincidentally the same day as the John Hopkins & Bill & Melinda gates foundation executed Event 201 a simulation where a bat covid virus outbreak would lead the world into lockdown .
The AB (self)testing reported in the study occurred in early 2021. As best we can tell, Figure 1 is "constructed" from the dates that respondents with positive AB results estimated as their onset date for the symptoms they said they had.
Not sure what your perspective is on the other events you've mentioned (i.e., what you believe they are or aren't "evidence" of), but incidence of "COVID-like illness" among U.S. participants in World Military Games in Wuhan cannot be cited as evidence of early spread of a new thing. https://www.woodhouse76.com/p/department-of-defense-2019-world
That’s not quite right. The earliest date on the graph is the earliest date of the self-reported symptoms.
Everything about Covid was fake - a meticulously planned fraud.
flurebranded
The question is ... What is antibodies??? 😄
https://open.substack.com/pub/mikestone/p/the-antibody?utm_source=share&utm_medium=android&r=4adbpr
I’m with you, but read the disclaimer please.
Wow. I read it. to be honest... Not quite what you both are seeing that others don't or others seeing what you don't when you said it's not totally wrong or counteproductive? In my view it's like this. There is something called as antibodies. Claim.. evidence doesn't support the existence. Period. Will be following you though.