Great article! This is what we should have, an exchange of thoughts and open disagreement.
The so called "science" should give reinfections a very close look, and look at them in the context of many things, one of them being vaccination status. Unfortunately, very few of such studies are done because, probably, they are not financed by whoever wields the purse strings.
I would personally be delighted if more people were studied and the studies dissected participants along many angles better.
Your question about reinfections such as infection --> vaccination --> reinfection vs vaccination --> infection --> reinfection is a good one.
Defining reinfections using PCR tests misses two things:
- People who did not test one of their illnesses with PCR and used a rapid test, more applicable to the later time in the pandemic
- PCR tests with too high cycle thresholds can give false positive, especially if people are tested repeatedly. For example, if 1 out of 50 tests is a false positive, and some people are tested weekly, then those people will be reported "infected" once a year even if they never are ill at all.
But, sadly we have what we have. Results of this study agree with what many of us observe, UKHSA case rates when they were published, etc
Yes I think there's far too many issues with this study, hence why I'm not sure why many people reported on it or reported without providing some concerns. The Qatar study suffered from the same issue in which they used PCR and antigen testing, but they also measured severity of illness. Measuring purely on PCR tests without any additional context does nothing.
And like I said, when we have what we have we should make sure that we look at things within the proper context, and with this paper I don't find it too be worth much of significance.
This finding should be interpreted with caution because of limitations of our study, which include the inability to adjust for the complex relationships among prior infection, vaccine eligibility, and underlying conditions.
Thanks for interpreting with caution, cause I’ve seen quite a few who did not. A very underwhelming study. And quite frankly a useless attempt at science- are there no great thinkers left? Why are such basic questions left unanswered?
Ironically, I kind of glossed over the Discussion section. I guess I got tired of the rest of the study by then! Thanks for pointing that out Clarisse.
I'm not quite sure. Ironically, we should all be acting as peer reviewers to some degree and when these things keep happening it kind of represents the failures of peer review when people may publish or cite studies that fit narratives rather than try to examine them from a position of good science.
Hahaha thanks Robin! I do wish people spend a bit more time and look at studies a bit more. It doesn't have to be perfect, but when a study says that we found these results, and you notice that there's hardly any information that should throw up some red flags.
A righteous rant. Funnily, I sent my thoughts on the Iceland study at Igor's post before seeing the email for yours.
"Ok, so this one is probably driven by the "Iceland dashboard bias," discussed here - https://unglossed.substack.com/p/the-ny-kids-paper#footnote-4 - to be recorded as either vaccinated or infected, Icelanders have to be in Iceland. Likewise for being "reinfected." So "unvaccinated" (or in this case ≤ 1-dosed) Icelanders are going to include all registered infected in 2020-early 2021 who were no longer in Iceland by December 2021. Some will contribute to the ≥2 doses denominator and reduce apparent reinfections but most are probably miscategorized into the ≤1-dosed group. This is driven purely by Icelanders who leave after the harshest lockdown period to study or work abroad. And so that is why the bias skews results for the young and not the old."
So the reason young, "unvaccinated" previously-infected Icelanders can't get infected again is because they aren't even in Iceland during the study period (or before, to have their vaccinations recorded).
"Less" communicates the idea of there being not as much of something. I therefor employ it rather than "fewer" in conversation as the latter is both superfluous and stodgy, haha.
That's very fascinating Brian. There's possibly a good deal of inconsistencies going on in the study. As some people mentioned to go from hundreds of thousands of Icelanders to just a select few thousand seems like a huge, giant gap being missed out on. It's interesting to think that this is an issue of the travelling young Icelander.
I probably shouldn't be casting aspersions on people's grammar since my grammar is no better, but I guess the difference between fewer and less is one that bothers me for some strange reason. Less is immeasurable, fewer is measurable is my go-to response.
Nice rundown on the flaws of this paper. It reads like something rushed into publication. That's a trend that seems to be getting worse with technical papers, though it's not new. It looks great on your resume to have a list of publications. Even if they're crap, because most people won't really poke into your methods and how they affect your conclusions. This one is going to be picked up and used as "proof" of the vaccines causing susceptibility to future infection. It suggests that in some cases, such as the 18-29 group.
If I were the reviewer I'd have flipped this back at the authors and asked them to clarify everything you flag here. And I think in answering the questions it would take them a few months to get the thing revised and resubmitted.
In fact, here's an idea: why not contact the authors with your questions?I bet you'd hear from them and it might actually result in a clearer picture of what the hell happened.
I think one important factor is that this study itself provides its own limitations. The researchers kind of state, "well, don't get carried away with this information," and yet everyone has decided to do so. This study had so many flaws, the researchers try to reel it in a bit but everyone just ran away with what they wanted to hear.
That's interesting, I may consider doing so as this appears to be a growing concern with many of these studies.
I've published a number of papers in my area of physics and was always really excited to get questions from people, whether challenging the work or asking for help in any way in understanding what got published. It doesn't happen often enough. Part of why we publish is to stimulate discussion and challenge though people tend to forget that. That's the backbone of science.
I'm glad you mention this, as when I read it I had pretty much the same thoughts. This is an extremely poor study. I mean we are talking 'CDC level bad'.
Mixing 1 and non-vax and mixing 2 and 3, and indeed not ordering vax first vs infection first. Plus, as I happen to make a living on modeling, my warning bells went off when I say this same (a) caveat. In order to do logistic regression, there can be no or only little relation between the so-called predictor variables. This means there should not be a high correlation between the independent variables. But just the plots done shows there is! I mean it is pretty obvious there is a possible relationship (causal even) between time and reinfection risk or possibly vaxed vs non-vaxed in relation to infection risk. So are we sure a logistic regression model is applicable? It can be, but without explaining details, this is non trivial, so they should have explained.
Especially since this regression model is effectively the conclusion! Without the model the conclusion would be "vax works", but now it is in their own words "highly surprising" ...
I suspect this correction is in part for the age groups, but age = behaviour. After all higher reinfection risk is also likely just behaviour, like going to bars, etc.
Another problem is that their non-vaxed/1-vaxed total population is larger than the 2-vax/3-vax, while in Iceland as a whole most are vaxed. Even if you deduct children! So this makes it possible they used a non-representative recruitment method.
All in all, this is no bad I'd consider it a waste of time. Without splitting up the no, 1, 2 and 3 vax and the vax first vs infect first, you have more questions than answers. Especially since they should have all this data! No seriously, either they are highly incompetent or hiding something. In essence CDC style research ...
I just can't get over the 1 dose people because from what I can tell their numbers suggest only 4 people had 1 dose. I would have just scrapped that whole group! But by lumping them together you now have to deal with people interpreting the study in a different manner who may not have looked into the numbers and noticed. Same goes for the 2 or more group. It's difficult to figure that group out but it's assumed that a majority of triple vaccinated people are among the elderly so why not separate the data out that way? There's no way this information can correlate more doses with higher rates of reinfection because we don't know who fell where.
To your regression model question, when I saw the reference used I was really curious why the 18-29 group, and I wrote a comment suggesting that using someone from that group possibly should have alerted readers to the fact that the researchers were insinuating that the 18-29 group was the one with the largest effect size.
As to behavior, I was going to mention why they got these results, and it's very likely that this is a consequence of hangouts and partying over the holiday seasons. It makes sense why the 50-75 age group are comparable likely because they did not go out. The slightly higher number among the >75 group may be due to them being in nursing homes which may require vaccination but also are in a setting with many people crammed together, including employees that come in and out of the residence.
There's so many things to pick apart so thanks for your perspective! Again I'm not sure why this study was picked up to the degree that it has been. It's such a short study as well, and yet it has made its rounds all over Substack already.
"Nosek and colleagues recruited 29 teams of expert researchers to analyze one data set to answer one simple question [...] The 29 teams of researchers analyzed the same data in 29 different ways. [...] Two-thirds of the expert teams of data scientists detected a significant result and one-third found no statistical difference. Two teams of experts found results that [strongly departed from others]"
"Let’s say you read a study that finds a statistically significant association. [...] The researchers will make positive conclusions. Media may cover it as a positive study, potentially a breakthrough. Public or medical opinion may change. Yet this result came from the researchers’ chosen analytic method."
Interesting I'll take a look! I remember Vanay Prasad (I can't remember his last name) was a co-author on a paper where they reviewed science papers and I believe looked to see what was reproducible or what had fatal methodology errors and the numbers were crazy high. I may try to find it again and make a post some time in the future.
I think I heard of Ioannidis from a feature in science or salon while I was researching for one of my monthly paid posts. I'll save that and take a look later. Thanks!
Much of what medical researchers conclude in their studies is misleading, exaggerated, or flat-out wrong. So why are doctors—to a striking extent—still drawing upon misinformation in their everyday practice? Dr. John Ioannidis has spent his career challenging his peers by exposing their bad science.
You know what, I think that was the article I was referring to! Can't remember which news outlet is which now I suppose 🤷♂️
I would argue that it's an issue in figuring out what role doctors exactly play. Are doctors scientists, or are doctors practitioners of medicine. How much science should doctors really know in order to have a grasp on the field?
I mainly was concerned about lumping 0-1 and 2-3. Also nothing about Ct value to confirm infection. A positive result with Ct over 30 alone is not proof of infection or reinfection .
Good point about the magnitude of the adjustment in in the odds ratio. Beware of adjusted numbers especially when they paint the opposite picture of the raw numbers
The 1 point was made pretty moot because their numbers insinuate only 4 people had 1 dose, so why not just throw out those numbers instead of marking the group as 1 or fewer? I find that a little weird (or very weird). I didn't make a big fuss about the Ct because it was something I've mentioned before many times, especially as someone who used to do COVID testing so that point was at least hammered down sufficiently at this point.
I would like some remarks on the odds ratio. I don't know how often it happens but to go from one interpretation to another should raise some questions. The problem is that the Supplemental material contains one page of material and methodology and over 25 pages of scripts for their program and so I have no idea what to do with that information.
I am always wary on large adjustments. I learned early on the best way to wake to top management during a presentation is mention your figures were adjusted
The study is rather useful in providing evidence to show that vaccination has no effect on reducing the number of positive PCR tests in the Age of Omicron. Thats about it.
Yes, I did read it and as it was only two pages long, I didn't give it much credence nor dig deeper as you have. Thanks for the analysis, and pointing out that bad science gets published, and quoted, without much thought.
I think sometimes we need other people to point things out for us to notice things. When I wrote the immune imprinting paper Brian Mowrey alluded to it in my comments section once but I didn't give it much thought, saw Dr. Malone write about immune imprinting and was concerned about some of his citations but didn't give much thought to his assessment. It wasn't until I saw Brian's criticism and looking at the paper that I asked myself, "OK, Brian is seeing something that I'm not, what am I missing?" And that's kind of when I noticed a lot of the flaws with the study which took a bit of taking apart. Then Clarisse added even more information about the T-cell study as well. So I think sometimes we need other people to check and see if something makes sense before we may notice it, and that's probably why we need more people within this group peer reviewing one another and making sure the information is being assessed properly.
Yes so the paper essentially looked at infection during the Omicron wave, looked at people's prior history and saw when they were previously infected (everyone's information is in a healthcare database I believe). So that's how they knew people were reinfected during the Omicron wave.
The problem is really figuring out where vaccination fits into this study and in what context. The study just tells us these people were vaccinated, the Supplemental information tells us when vaccines were available, but they don't tell us when people were infected and when they got vaccinated, so we're working with essentially no timeline (or we're at least dealing with a missing middle).
OK, my takeaway is that not only do the vaccinated get Covid, it is the gift that keeps on giving. Since I take a supplement for AMD containing zinc, C, E, plus I add D and Quercetin dare I hope it has kept me from contracting the demon virus?
There's a lot of questions as to what exactly is happening. I've tried rebutting the argument that reinfection is not impossible with COVID, and we probably shouldn't ahve thought that to be the case. Omicron was also its own mess because it had so many mutations that it escaped nearly all forms of prior immunity, including natural immunity so I've made comments that Omicron is almost like a blankish slate position.
In all honestly, most people have probably contracted it at this point with a good deal being unaware. Remember that they were messaging that 40% of all infections were asymptomatic, and on that front it really made it hard to argue the lockdown procedures we had given that fact.
I'm unvaxxed and have had it three times, Delta, Omicron ba1 and then ba5 I'm guessing. My obgyn is vaxxed and has had it three times. There's a paper in there somewhere I am pretty sure.
There's plenty of factors including one's own immune system. There are people that can be vaccinated up the wazoo but they just never respond to a vaccine, and so there's a serious issue in finding out to what extent an individual gains immunity after infection.
I read the studies whenever I can. Granted, sometimes I don't completely understand all of it, but sometimes I'm now convinced they are presenting it in a convoluted way because they want a particular result. This study is a perfect example. I would not have gleaned all of those glaring omissions of data but I would have wondered why it was so short and the inability to separate the course of vaccinated, then infected, or infected and then vaccinated, plus there is almost always a theme of not including the unvaccinated as a group right now. They end up comparing 2 shots versus boosted and separate that data so even if there is an unvaccinated column, it looks like more unvaccinated are at risk.
Another point of contention I have with all of the vaccination studies is how they try to hide the myocarditis/pericarditis info. Very frustrating. It's crazy it took this long for an Israeli study to confirm that unvaccinated people who catch covid do not get myocarditis- it is practically an exclusive thing for vaccinated.
I've come to expect that abstracts aren't bite-size summaries but selling points, almost serving as scientific clickbait really. There's so much that you see in an abstract but then read the paper and go, "wait, how did you get to that point?" It becomes hard to disagree with the researchers- do you know better than the actual researchers who conducted the study? But sometimes you notice something and have to wonder what's really happening.
A lot of the adverse reactions are hard to parse, and it's hard to tell what exactly is signal amongst the noise. So one wonders if the information is intentionally obfuscated or if there's just so much to deal with it all kind of gets lost and mixed together, but I do wish we had far more transparent data on the myocarditis. I came across this hypothesis that I didn't look at in full yet adding further support to catecholamines playing a role in myocarditis, which ties in with that coronary data from a few months ago about the two young male teens who died in their sleep and saw catecholamine-associated heart issues.
I have no desire to avoid reinfection. I’d like to be infected at reasonable intervals, to keep my natural immunity primed and up-to-date. Nature’s vaccine works pretty well, in my experience. I don’t know why we are trying to outrun an endemic virus.
I don't think anyone wants to get reinfected, but at least from the perspective of this study I was trying to argue that the evidence here leaves me more wanting than compelled.
But that's also why I've written my posts on exercise and sleep since we should do what we can to make sure our health is in order using basic, fundamental principles rather than try to solves things from a purely modern standpoint.
Well reinfection leads to worse long covid outcomes for one. See an excellent analysis of neurological implications of long covid (and spike from jab) by Suzanne Garza MD https://www.suzannegazdamd.com/blog---long-covid
I’ve had it twice, 18 months apart. I guess it depends on the person, but I handled it fine both times. And I’m no spring chick. I’m not overweight or anything tho, and I don’t eat junk food. Another reason why the one-size-fits-all approach is dumb. Medicine requires an individual approach. Each of us is unique.
It's different for each person. We probably should have learned more about individual medicine from COVID but it still feels like there's a one size fits all approach to some degree right now.
There can be no generalizations at this point. My observations are all over the map. Vaxxed getting really slugged by covid young or old; unvaxxed getting slugged just as hard, young or old. People get light cases: I've had extremely mild and then not very nice and I'm healthy as an ox. I no longer think I have any answers.
I really think Vitamin D levels play a big part, and who knows what else because doctors don’t seem very interested in actually figuring it out. Aside from Dr. Kory and Dr. Stella Immanuel and other banned front liner’s. They all seem to have protocols that work very well, and they do try different things for different people, depending on their situation. I think that’s important.
I did read the original paper sited but after your poll closed so couldn’t vote. It was confusing to say the least; convoluted and obtuse. The waters were muddied. I found the data presented in a bizarre, unclear manner. Even if I wanted to do so, I really couldn’t explain to anyone what was presented other than there are some interesting questions. I am concerned as usually that PCR was used as a diagnostic test. All this is said with a sincere , well thought out effort to dissect the papers presented.
Great article! This is what we should have, an exchange of thoughts and open disagreement.
The so called "science" should give reinfections a very close look, and look at them in the context of many things, one of them being vaccination status. Unfortunately, very few of such studies are done because, probably, they are not financed by whoever wields the purse strings.
I would personally be delighted if more people were studied and the studies dissected participants along many angles better.
Your question about reinfections such as infection --> vaccination --> reinfection vs vaccination --> infection --> reinfection is a good one.
Defining reinfections using PCR tests misses two things:
- People who did not test one of their illnesses with PCR and used a rapid test, more applicable to the later time in the pandemic
- PCR tests with too high cycle thresholds can give false positive, especially if people are tested repeatedly. For example, if 1 out of 50 tests is a false positive, and some people are tested weekly, then those people will be reported "infected" once a year even if they never are ill at all.
But, sadly we have what we have. Results of this study agree with what many of us observe, UKHSA case rates when they were published, etc
Yes I think there's far too many issues with this study, hence why I'm not sure why many people reported on it or reported without providing some concerns. The Qatar study suffered from the same issue in which they used PCR and antigen testing, but they also measured severity of illness. Measuring purely on PCR tests without any additional context does nothing.
And like I said, when we have what we have we should make sure that we look at things within the proper context, and with this paper I don't find it too be worth much of significance.
I wrote an article about something else, but I include a link to your article above
https://igorchudov.substack.com/p/another-ivermectin-study-shows-benefit
All 'positives' are false 'positives'. These 'tests' are not even remotely evidence of a "infection" with "sars-cov2".
https://yummy.doctor/video-list/dr-andy-kaufman-and-dr-amandha-vollmer-expose-covid-test-fraud-brain-ai-5g-agenda/
Right out of author’s mouth:
This finding should be interpreted with caution because of limitations of our study, which include the inability to adjust for the complex relationships among prior infection, vaccine eligibility, and underlying conditions.
Thanks for interpreting with caution, cause I’ve seen quite a few who did not. A very underwhelming study. And quite frankly a useless attempt at science- are there no great thinkers left? Why are such basic questions left unanswered?
Ironically, I kind of glossed over the Discussion section. I guess I got tired of the rest of the study by then! Thanks for pointing that out Clarisse.
I'm not quite sure. Ironically, we should all be acting as peer reviewers to some degree and when these things keep happening it kind of represents the failures of peer review when people may publish or cite studies that fit narratives rather than try to examine them from a position of good science.
Tip: To reduce the risk of Substackitis, wait for the Modern Discontent perspective.
Hahaha thanks Robin! I do wish people spend a bit more time and look at studies a bit more. It doesn't have to be perfect, but when a study says that we found these results, and you notice that there's hardly any information that should throw up some red flags.
A righteous rant. Funnily, I sent my thoughts on the Iceland study at Igor's post before seeing the email for yours.
"Ok, so this one is probably driven by the "Iceland dashboard bias," discussed here - https://unglossed.substack.com/p/the-ny-kids-paper#footnote-4 - to be recorded as either vaccinated or infected, Icelanders have to be in Iceland. Likewise for being "reinfected." So "unvaccinated" (or in this case ≤ 1-dosed) Icelanders are going to include all registered infected in 2020-early 2021 who were no longer in Iceland by December 2021. Some will contribute to the ≥2 doses denominator and reduce apparent reinfections but most are probably miscategorized into the ≤1-dosed group. This is driven purely by Icelanders who leave after the harshest lockdown period to study or work abroad. And so that is why the bias skews results for the young and not the old."
So the reason young, "unvaccinated" previously-infected Icelanders can't get infected again is because they aren't even in Iceland during the study period (or before, to have their vaccinations recorded).
"Less" communicates the idea of there being not as much of something. I therefor employ it rather than "fewer" in conversation as the latter is both superfluous and stodgy, haha.
That's very fascinating Brian. There's possibly a good deal of inconsistencies going on in the study. As some people mentioned to go from hundreds of thousands of Icelanders to just a select few thousand seems like a huge, giant gap being missed out on. It's interesting to think that this is an issue of the travelling young Icelander.
I probably shouldn't be casting aspersions on people's grammar since my grammar is no better, but I guess the difference between fewer and less is one that bothers me for some strange reason. Less is immeasurable, fewer is measurable is my go-to response.
Haha - but you can accurately measure "less" in volume, mass, and time as three quick examples.
Excellent information- thanks for sharing!
Excellent 👍
Nice rundown on the flaws of this paper. It reads like something rushed into publication. That's a trend that seems to be getting worse with technical papers, though it's not new. It looks great on your resume to have a list of publications. Even if they're crap, because most people won't really poke into your methods and how they affect your conclusions. This one is going to be picked up and used as "proof" of the vaccines causing susceptibility to future infection. It suggests that in some cases, such as the 18-29 group.
If I were the reviewer I'd have flipped this back at the authors and asked them to clarify everything you flag here. And I think in answering the questions it would take them a few months to get the thing revised and resubmitted.
In fact, here's an idea: why not contact the authors with your questions?I bet you'd hear from them and it might actually result in a clearer picture of what the hell happened.
I think one important factor is that this study itself provides its own limitations. The researchers kind of state, "well, don't get carried away with this information," and yet everyone has decided to do so. This study had so many flaws, the researchers try to reel it in a bit but everyone just ran away with what they wanted to hear.
That's interesting, I may consider doing so as this appears to be a growing concern with many of these studies.
I've published a number of papers in my area of physics and was always really excited to get questions from people, whether challenging the work or asking for help in any way in understanding what got published. It doesn't happen often enough. Part of why we publish is to stimulate discussion and challenge though people tend to forget that. That's the backbone of science.
I'm glad you mention this, as when I read it I had pretty much the same thoughts. This is an extremely poor study. I mean we are talking 'CDC level bad'.
Mixing 1 and non-vax and mixing 2 and 3, and indeed not ordering vax first vs infection first. Plus, as I happen to make a living on modeling, my warning bells went off when I say this same (a) caveat. In order to do logistic regression, there can be no or only little relation between the so-called predictor variables. This means there should not be a high correlation between the independent variables. But just the plots done shows there is! I mean it is pretty obvious there is a possible relationship (causal even) between time and reinfection risk or possibly vaxed vs non-vaxed in relation to infection risk. So are we sure a logistic regression model is applicable? It can be, but without explaining details, this is non trivial, so they should have explained.
Especially since this regression model is effectively the conclusion! Without the model the conclusion would be "vax works", but now it is in their own words "highly surprising" ...
I suspect this correction is in part for the age groups, but age = behaviour. After all higher reinfection risk is also likely just behaviour, like going to bars, etc.
Another problem is that their non-vaxed/1-vaxed total population is larger than the 2-vax/3-vax, while in Iceland as a whole most are vaxed. Even if you deduct children! So this makes it possible they used a non-representative recruitment method.
All in all, this is no bad I'd consider it a waste of time. Without splitting up the no, 1, 2 and 3 vax and the vax first vs infect first, you have more questions than answers. Especially since they should have all this data! No seriously, either they are highly incompetent or hiding something. In essence CDC style research ...
I just can't get over the 1 dose people because from what I can tell their numbers suggest only 4 people had 1 dose. I would have just scrapped that whole group! But by lumping them together you now have to deal with people interpreting the study in a different manner who may not have looked into the numbers and noticed. Same goes for the 2 or more group. It's difficult to figure that group out but it's assumed that a majority of triple vaccinated people are among the elderly so why not separate the data out that way? There's no way this information can correlate more doses with higher rates of reinfection because we don't know who fell where.
To your regression model question, when I saw the reference used I was really curious why the 18-29 group, and I wrote a comment suggesting that using someone from that group possibly should have alerted readers to the fact that the researchers were insinuating that the 18-29 group was the one with the largest effect size.
As to behavior, I was going to mention why they got these results, and it's very likely that this is a consequence of hangouts and partying over the holiday seasons. It makes sense why the 50-75 age group are comparable likely because they did not go out. The slightly higher number among the >75 group may be due to them being in nursing homes which may require vaccination but also are in a setting with many people crammed together, including employees that come in and out of the residence.
There's so many things to pick apart so thanks for your perspective! Again I'm not sure why this study was picked up to the degree that it has been. It's such a short study as well, and yet it has made its rounds all over Substack already.
Interesting post today by John Mandrola:
https://sensiblemed.substack.com/p/study-of-the-week-choices-oh-my-the
"Nosek and colleagues recruited 29 teams of expert researchers to analyze one data set to answer one simple question [...] The 29 teams of researchers analyzed the same data in 29 different ways. [...] Two-thirds of the expert teams of data scientists detected a significant result and one-third found no statistical difference. Two teams of experts found results that [strongly departed from others]"
"Let’s say you read a study that finds a statistically significant association. [...] The researchers will make positive conclusions. Media may cover it as a positive study, potentially a breakthrough. Public or medical opinion may change. Yet this result came from the researchers’ chosen analytic method."
Interesting I'll take a look! I remember Vanay Prasad (I can't remember his last name) was a co-author on a paper where they reviewed science papers and I believe looked to see what was reproducible or what had fatal methodology errors and the numbers were crazy high. I may try to find it again and make a post some time in the future.
Ioannidis has been all over that topic for years.
John Ioannidis: The Pandemic as of 7/28/2022
Interview with Vinay Prasad, MD MPH
https://sensiblemed.substack.com/p/john-ioannidis-the-pandemic-as-of?
I think I heard of Ioannidis from a feature in science or salon while I was researching for one of my monthly paid posts. I'll save that and take a look later. Thanks!
Here’s an earlier article you might also enjoy:
Lies, Damned Lies, and Medical Science
Much of what medical researchers conclude in their studies is misleading, exaggerated, or flat-out wrong. So why are doctors—to a striking extent—still drawing upon misinformation in their everyday practice? Dr. John Ioannidis has spent his career challenging his peers by exposing their bad science.
https://www.theatlantic.com/magazine/archive/2010/11/lies-damned-lies-and-medical-science/308269/
You know what, I think that was the article I was referring to! Can't remember which news outlet is which now I suppose 🤷♂️
I would argue that it's an issue in figuring out what role doctors exactly play. Are doctors scientists, or are doctors practitioners of medicine. How much science should doctors really know in order to have a grasp on the field?
I mainly was concerned about lumping 0-1 and 2-3. Also nothing about Ct value to confirm infection. A positive result with Ct over 30 alone is not proof of infection or reinfection .
Good point about the magnitude of the adjustment in in the odds ratio. Beware of adjusted numbers especially when they paint the opposite picture of the raw numbers
The 1 point was made pretty moot because their numbers insinuate only 4 people had 1 dose, so why not just throw out those numbers instead of marking the group as 1 or fewer? I find that a little weird (or very weird). I didn't make a big fuss about the Ct because it was something I've mentioned before many times, especially as someone who used to do COVID testing so that point was at least hammered down sufficiently at this point.
I would like some remarks on the odds ratio. I don't know how often it happens but to go from one interpretation to another should raise some questions. The problem is that the Supplemental material contains one page of material and methodology and over 25 pages of scripts for their program and so I have no idea what to do with that information.
I am always wary on large adjustments. I learned early on the best way to wake to top management during a presentation is mention your figures were adjusted
The study is rather useful in providing evidence to show that vaccination has no effect on reducing the number of positive PCR tests in the Age of Omicron. Thats about it.
Yes, I did read it and as it was only two pages long, I didn't give it much credence nor dig deeper as you have. Thanks for the analysis, and pointing out that bad science gets published, and quoted, without much thought.
I think sometimes we need other people to point things out for us to notice things. When I wrote the immune imprinting paper Brian Mowrey alluded to it in my comments section once but I didn't give it much thought, saw Dr. Malone write about immune imprinting and was concerned about some of his citations but didn't give much thought to his assessment. It wasn't until I saw Brian's criticism and looking at the paper that I asked myself, "OK, Brian is seeing something that I'm not, what am I missing?" And that's kind of when I noticed a lot of the flaws with the study which took a bit of taking apart. Then Clarisse added even more information about the T-cell study as well. So I think sometimes we need other people to check and see if something makes sense before we may notice it, and that's probably why we need more people within this group peer reviewing one another and making sure the information is being assessed properly.
How does this work? Vaccination >> reinfection. Shouldn’t there be “infection” in there somewhere?
Yes so the paper essentially looked at infection during the Omicron wave, looked at people's prior history and saw when they were previously infected (everyone's information is in a healthcare database I believe). So that's how they knew people were reinfected during the Omicron wave.
The problem is really figuring out where vaccination fits into this study and in what context. The study just tells us these people were vaccinated, the Supplemental information tells us when vaccines were available, but they don't tell us when people were infected and when they got vaccinated, so we're working with essentially no timeline (or we're at least dealing with a missing middle).
OK, my takeaway is that not only do the vaccinated get Covid, it is the gift that keeps on giving. Since I take a supplement for AMD containing zinc, C, E, plus I add D and Quercetin dare I hope it has kept me from contracting the demon virus?
There's a lot of questions as to what exactly is happening. I've tried rebutting the argument that reinfection is not impossible with COVID, and we probably shouldn't ahve thought that to be the case. Omicron was also its own mess because it had so many mutations that it escaped nearly all forms of prior immunity, including natural immunity so I've made comments that Omicron is almost like a blankish slate position.
In all honestly, most people have probably contracted it at this point with a good deal being unaware. Remember that they were messaging that 40% of all infections were asymptomatic, and on that front it really made it hard to argue the lockdown procedures we had given that fact.
I'm unvaxxed and have had it three times, Delta, Omicron ba1 and then ba5 I'm guessing. My obgyn is vaxxed and has had it three times. There's a paper in there somewhere I am pretty sure.
There's plenty of factors including one's own immune system. There are people that can be vaccinated up the wazoo but they just never respond to a vaccine, and so there's a serious issue in finding out to what extent an individual gains immunity after infection.
I read the studies whenever I can. Granted, sometimes I don't completely understand all of it, but sometimes I'm now convinced they are presenting it in a convoluted way because they want a particular result. This study is a perfect example. I would not have gleaned all of those glaring omissions of data but I would have wondered why it was so short and the inability to separate the course of vaccinated, then infected, or infected and then vaccinated, plus there is almost always a theme of not including the unvaccinated as a group right now. They end up comparing 2 shots versus boosted and separate that data so even if there is an unvaccinated column, it looks like more unvaccinated are at risk.
Another point of contention I have with all of the vaccination studies is how they try to hide the myocarditis/pericarditis info. Very frustrating. It's crazy it took this long for an Israeli study to confirm that unvaccinated people who catch covid do not get myocarditis- it is practically an exclusive thing for vaccinated.
I've come to expect that abstracts aren't bite-size summaries but selling points, almost serving as scientific clickbait really. There's so much that you see in an abstract but then read the paper and go, "wait, how did you get to that point?" It becomes hard to disagree with the researchers- do you know better than the actual researchers who conducted the study? But sometimes you notice something and have to wonder what's really happening.
A lot of the adverse reactions are hard to parse, and it's hard to tell what exactly is signal amongst the noise. So one wonders if the information is intentionally obfuscated or if there's just so much to deal with it all kind of gets lost and mixed together, but I do wish we had far more transparent data on the myocarditis. I came across this hypothesis that I didn't look at in full yet adding further support to catecholamines playing a role in myocarditis, which ties in with that coronary data from a few months ago about the two young male teens who died in their sleep and saw catecholamine-associated heart issues.
https://www.cureus.com/articles/110419-catecholamines-are-the-key-trigger-of-covid-19-mrna-vaccine-induced-myocarditis-a-compelling-hypothesis-supported-by-epidemiological-anatomopathological-molecular-and-physiological-findings
I have no desire to avoid reinfection. I’d like to be infected at reasonable intervals, to keep my natural immunity primed and up-to-date. Nature’s vaccine works pretty well, in my experience. I don’t know why we are trying to outrun an endemic virus.
I don't think anyone wants to get reinfected, but at least from the perspective of this study I was trying to argue that the evidence here leaves me more wanting than compelled.
But that's also why I've written my posts on exercise and sleep since we should do what we can to make sure our health is in order using basic, fundamental principles rather than try to solves things from a purely modern standpoint.
Well reinfection leads to worse long covid outcomes for one. See an excellent analysis of neurological implications of long covid (and spike from jab) by Suzanne Garza MD https://www.suzannegazdamd.com/blog---long-covid
I’ve had it twice, 18 months apart. I guess it depends on the person, but I handled it fine both times. And I’m no spring chick. I’m not overweight or anything tho, and I don’t eat junk food. Another reason why the one-size-fits-all approach is dumb. Medicine requires an individual approach. Each of us is unique.
It's different for each person. We probably should have learned more about individual medicine from COVID but it still feels like there's a one size fits all approach to some degree right now.
There can be no generalizations at this point. My observations are all over the map. Vaxxed getting really slugged by covid young or old; unvaxxed getting slugged just as hard, young or old. People get light cases: I've had extremely mild and then not very nice and I'm healthy as an ox. I no longer think I have any answers.
I really think Vitamin D levels play a big part, and who knows what else because doctors don’t seem very interested in actually figuring it out. Aside from Dr. Kory and Dr. Stella Immanuel and other banned front liner’s. They all seem to have protocols that work very well, and they do try different things for different people, depending on their situation. I think that’s important.
Ivermectin worked for us. I think. At least it didn't seem to hurt us. At this point that's about all I'm prepared to say.
I did read the original paper sited but after your poll closed so couldn’t vote. It was confusing to say the least; convoluted and obtuse. The waters were muddied. I found the data presented in a bizarre, unclear manner. Even if I wanted to do so, I really couldn’t explain to anyone what was presented other than there are some interesting questions. I am concerned as usually that PCR was used as a diagnostic test. All this is said with a sincere , well thought out effort to dissect the papers presented.