The title is lifted from an email I received, one of many asking me to look into the paper “A calibration of nucleic acid (PCR) by antibody (IgG) tests in Germany: the course of SARS-CoV-2 infections estimated” by Michael Günther Robert Rockenfeller, and Harald Walach in Frontiers: Epidemiology.
Their idea is simple enough. PCR tests only say, with some error, in both directions, whether viral material made it up your nose. They do not say you were infected. Viral material in your nose does not mean you are infected, just as a box of matches on your arm does not mean you were burned. It takes something to set the virus or matches off, as it were.
If you do become infected, some period after, say eight weeks or so, your body, if you live, will develop certain antibodies. The authors had data on one antibody called IgG, which is also measured with some error. It can be made by your body if you are infected or if you got “the vaccine”. There is no way to tell after vaccination whether the IgG was there because of prior infection or because of “the vaccine”. Unless you are measured for prior infection first, which not many were.
Long-time readers will recall me during the panic screaming very very loudly about this, over and again, all in vain. People were injected in a mad blind panicked hersterical (there is no misspelling) rush, and only a small few had tests to see if they had prior infections.
This monumental blunder is extremely important because if you look long after the panic, as we do now, and check for IgG, you will give “the vaccine” more credit than it deserves. You will say “Lo! The vaccine caused this IgG.” Which may be true or false. Because a prior infection may have caused it instead. Now it is too late to check. We will never know for certain because of idiot panic.
I repeat for emphasis: Recall those stories of doctors lamenting people weren’t taking the panic seriously enough, because many didn’t even know they were infected? And that others thought their infections were mild allergies? Covid did not affect all equally. Most were not tested prior to being vaccinated.
Lack of individual-level data is a sin. It’s hard to find anywhere. Even impossible. And in England, in the name of The Science, the government is actively suppressing it. Lest—and you’re not going to believe this—anybody get sad. Yes, really.
Without individual-level data, any claim of causality cannot be believed. Even in this paper. If all that is available is shaky group-level data, the best we’ll get is correlation, and weak ones at that. There is no escaping this, as I have been trying to teach in the Class.
Our authors downloaded some group-level data on PCR tests and IgG tests for some people and sites in Germany. And then—and you’re not going to believe this—that data disappeared from the source which provided it. Luckily, they kept a copy. And, rarely, they made it available to all. I grabbed it and made my own analysis below.
The idea is this: PCR tests only indicate viral matter, which sometimes leads to infection. Presumably, those who do become infected would have positive PCR tests (but that doesn’t always happen: the test is not perfect). Some of those who think they, or their “medical professionals” think, may be infected, go on to have IgG tests. And some get IgG tested with no PCR. The presumption again is that a positive test indicates a prior infection (but also doesn’t always happen: the test is not perfect).
The authors basically (ignoring the strange and, at points, dubious math; see below) correlated the positive fraction of PCR tests with the positive fraction of IgG tests some weeks later. But not on individuals, you understand. Summed across groups. If the entire system worked perfectly, according to the authors’ vision, the fraction of positive PCR tests would match up to some constant the fraction of positive IgG tests.
Their conclusion: “This suggests that, on average, only approximately 14% of those who tested PCR-positive were actually infected.” But there are problems with this, as the authors well recognize:
This interpretation is based on a key assumption, made due to a lack of a priori knowledge regarding selection criteria for IgG testing: we assume, for the moment, that those tested for IgG were drawn from among those previously PCR-tested. However, as discussed in Section 3.1, this assumption is almost certainly incorrect. In reality, the ALM-reported IgG-positive fraction is close to population-representative, which lends further transparency to the analysis in Equation 1. The pre-selection bias inherent to PCR testing thus remains unquantified, but is effectively encapsulated by the proportionality factor PPCR in a phenomenological sense.
Another problem, which the authors also note is that those who sought, or were recommended, for antibody testing might have been symptomatic, hence we’d expect higher positive test rates in IgG than PCR. Another problem was that people were PCR-happy at times during the panic. “Get tested! Get tested! How else you can you know!” We’d therefore expect lower positive rates of PCR tests, especially early on.
Another problem is that because this is group-level data. we don’t know how many duplicates there on. Those test-mad hersterics pushed numbers up a lot. Another problem is that they had to stop this analysis after the introduction of “the vaccine”, for obvious reasons. But it’s not clear to me they did. It looks like they used some data after “the vaccine” was introduced. Anyway, the IgG data quits after mid 2021.
There are few other whereases, whatnots, this-and-thats and caveats, too. But you get the idea.
And, of course, there is no way to incorporate in this analysis the false positives and false negatives of both PCR and IgG tests, because, again, we lack individual-level data.
Thus, this paper, even if that 14% number is right, which we can’t put too much confidence in, is not earth shaking.
Wait. Let me correct that. That number is not earth-shaking to those who were sober and not grasping, avaricious, or panicked. Those who kept their calm from the beginning will only shrug at a result, which to them, was already anticipated.
We should never have believed PCR tests were perfect in the first place. So many people tried pointing it out at the time, but all—including their inventor!—were shouted down, or were canceled, or had patients taken away. Of course viral matter did not mean infection. Of course PCR tests produced false positives.
Of course lockdowns were idiotic. Of course prior infections conferred standard immunity. Of course, Of course, Of course.
We were lied to so hard and so often and so obviously by Experts, politicians, doctors and, worst of all, celebrities that it’s hard to look back on any of this and not grow angry.
My Analysis
Here are the positive test rates for IgG and PCR, from their Supplementary data. I’m ignoring the number of tests here.
Obviously, the IgG cuts off early, and that more PCR tests were positive well into the panic, after almost everybody was infected. PCR tests were rare at first, and it looks here like people more likely to be suspected as sick were tested early on. Then the panic seized everybody and testing mania hit. You can see the original paper for number-of-tests plots.
You can see the IgG early bump came about five weeks after the early PCR bump. Remember this.
Here is the contemporaneous ratio of PCR positive tests to IgG positive tests:
These are the ratios as they occurred, week by week. PCR positive test rate is the numerator, IgG the denominator. The high number at the beginning again likely reflects that only those really suspected of being ill were more likely tested.
The dashed red line is the authors’ 0.14. It crudely fits this contemporaneous ratio data. But this is not how they got that number; I mean, they used math, and this is only a simple plot of raw data.
Lastly, here is the same ratio of positive test rates, PCR/IgG, but matching up the lag from those two early peaks. The peak in PCR came in week 14 of 2020, whereas the peak in IgG came in week 18 of 2020. This is, of course, not an eight weeks difference, but a 5 week difference (I did the 8 week plot too, and it’s not that different).
That 0.14 ratio fits a bit better here.
The authors did try to account for that large initial bump in their curious math. But that is neither here nor there, I think. All acknowledge the rapid change from the early stages of the panic (where people like Chuck Schumer were insisting you head on down to China town for the far east victuals) to the full-blown panic (where people like Chuck Schumer said that venturing outside meant death).
You can view this as, more or less, a corroboration of their result, with all the same caveats and cautions, of course. We are still left with correlating group-level data, with all the attendant problems.
Our lesson, then as now: panic kills.
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It wasn’t a blunder.