Explaining the "Hospitalization Paradox"
How a negative PCR test can serve as a marker for systemic inflammation and spike protein toxicity, creating a widely exploited statistical anomaly to make misleading claims about hospitalization.
This is not medical advice. See full disclaimer at the bottom.
All of the below only makes sense when we realize that virtually every report we have ever seen ignores those with PCR-negative COVID-like illness. This ignored portion represents 79% of those in the hospital with this illness.
“COVID-like illness” refers to the signs and symptoms of COVID, regardless of the results of a PCR test. We do not know whether this phenomenon of “COVID-like illness” is true COVID that tests negative, other respiratory viruses, spike protein toxicity, vaccine side effects, other diseases altogether (such as exacerbations of COPD), or some collection of all of this. We also have no idea what the rate of disability, ICU admission, and death is for PCR-negative COVID-like illness. We simply know that only 21% of those hospitalized with COVID-like illness test positive for COVID, and the rest our media and public health establishment ignore.
Keeping this focus on the poorly understood total COVID-like illness, I now bring to you the “Hospitalization Paradox.”
The “Hospitalization Paradox” is my name for the following seemingly paradoxical observations:
The COVID vaccines strongly reduce the chance of a positive PCR nasal swab among anyone suffering from COVID-like illness.
By contrast, they have little to no effect in reducing total COVID-like illness of any severity, nor in reducing hospitalization for it.
During the first two to three months after vaccination while the vaccines maintain high efficacy against a positive test, they do not have any apparent effect on hospitalization, even among those who test positive.
As the vaccines begin declining in efficacy against testing positive, they still have no meaningful impact on hospitalization for total COVID-like illness among the vaccinated population at large.
And here is the paradoxical part: during this waning phase, specifically among the growing number of vaccinated people who do test positive, they become associated with a lower risk of hospitalization.
That is, before the phase of declining efficacy, the vaccines don’t do anything except make people test negative.
Once the waning phase kicks in, the vaccines create a strange effect where a positive PCR nasal swab becomes a marker for a mild case of COVID-like illness that will not lead to hospitalization.
The positive test never serves as such a marker in the unvaccinated.
That is, the vaccines do not seem to be keeping people out of the hospital for COVID-like illness at all, but do seem to be doing something peculiar to make a positive test serve as a marker for a mild illness, only among the vaccinated, and only after the phase of waning efficacy takes hold.
This peculiar effect on the test allows for enormous obfuscation. By ignoring all the people with COVID-like illness who test negative and zeroing in on those who test positive, the media and public health authorities consistently exploit this statistical anomaly to claim the vaccines protect people from “COVID-19-associated hospitalization.”
And yet the CDC data show that what this means is not that they are keeping people who get COVID-19 out of the hospital, but rather that they are keeping people hospitalized for COVID-like illness from testing positive for COVID-19.
How can this peculiar effect be explained?
In this article, I propose the following hypothesis: during the phase of waning efficacy against a positive test, a negative test among a vaccinated person with COVID-like illness becomes a marker for above-average systemic inflammation and spike protein toxicity; conversely, the positive test becomes a marker for more mild inflammation or spike protein toxicity. The test never plays any such role in those who did not receive COVID vaccines since they are afflicted neither by spike protein toxicity nor by vaccine-induced inflammation.
Understanding this is critical: if the only thing the vaccines are doing is generating a negative test among the ill and creating this statistical anomaly, then whether they are doing anything clinically useful at all hinges entirely on the clinical fate of the PCR-negative COVID-like illness. What is their rate of disability? Of ICU admission? Of mortality? CDC has not released this data.
Since my description of this paradox is at odds with virtually everything said about the vaccines, first let me support the observations with evidence before solving the paradox.
What Is PCR-Negative COVID-Like Illness?
Before analyzing all the data on COVID-like illness, let’s first try to get a better grasp of what it is.
This section was added on April 1, 2022, based on a paper I originally wrote about on February 25, 2022.
We assume for the sake of this section that PCR-positive COVID-like illness is “COVID.” The question then becomes, what is PCR-negative COVID-like illness?
The only study to look at that was done before the vaccine rollouts, at Rutgers University Hospital in New Jersey, from April to October, 2020. It suggests that 44% of PCR-negative patients hospitalized for COVID-like illness have a compelling alternative diagnosis, and in 69% of the remaining 56%, or 39% of the total, it is genuine COVID that has been missed by the PCR test.
The alternative compelling diagnoses from this study were a very long list that included COPD, heart failure, bacterial pneumonia, lupus, anemia, diabetes, and much more.
However, there are good reasons to think the vaccines could increase the proportion of PCR-Negative COVID-like illness:
As this article justifies in great depth, the vaccines seem to give people with genuine COVID a negative test.
They may cause non-viral COVID-like illness, which is shown using isolated spike protein in mice and discussed in detail here.
They may also exacerbate existing inflammation, as shown in many case reports.
They may increase the likelihood of acquiring a different infection, a phenomenon known as “viral competition” but speculative in this case.
They may cause other forms of spike protein toxicity, to be discussed in detail in my ongoing series that starts here.
They may cause autoimmunity, hypothesized for vaccines and known to occur in severe COVID cases.
So, prior to the vaccine rollout some 39% of PCR-Negative COVID-like illness seems to have been actual COVID. As we will explore below, the only clear thing the vaccines are doing is giving people with COVID a negative test. The post-rollout proportion that is genuine COVID is therefore probably much higher than 39%. Some additional remainder of this is likely to be other side effects of the vaccines listed above. Some final remainder of this is likely to be the many other alternative compelling diagnoses found in the Rutgers study, yet likely much lower than the 44% originally found in that study.
COVID-Like Illness in the Pfizer Trial
COVID-like illness in the Pfizer documents was referred to as “suspected COVID-19” and was driven by volunteers believing they may have had COVID and telling a doctor who would then decide whether to test them.
None of the trials, including Pfizer, reported COVID-like illness in their peer-reviewed trial reports. They only submitted this data to the FDA. We only have it publicly available for the 2-month results of the Pfizer trial, and the only reason we have that is because the FDA’s advisory board met to vote on the Emergency Use Authorization (EUA) and released a briefing of their meeting containing the data. The advisory board did not meet for the Comirnaty approval, so we do not have COVID-like illness data for the six-month followup, although hopefully we will have this on March 1 when the next 55,000 pages of data drops.
As originally pointed out by Peter Doshi, in the 2-month data from the Pfizer trial, there were 3,580 cases of COVID-like illness, 95.3% of which tested negative for COVID.
The vaccine only reduced the incidence of COVID-like illness by a relative 9.4% from an absolute 18% to an absolute 16.3%, yet it reduced the likelihood of getting a positive test after one became ill by a relative 95% from an absolute 1.6% to an absolute 0.08%.
This 95% efficacy means the vaccine is 95% effective at giving you a negative test after you become ill.
This COVID-like illness, whether testing positive or negative, was overwhelmingly mild. According to the FDA report, there were only six serious cases of COVID-like illness, only four of which led to hospitalization.
The six serious cases were spread evenly across the two groups, with three cases in each.
The hospitalizations were spread evenly as well, with two cases in each group.
However, two of the three serious cases in the vaccine group tested negative, while all three in the placebo group tested positive. Both of the hospitalizations in the vaccine group tested negative, while both of the hospitalizations in the placebo group tested positive. These numbers are too small for stats, but this is consistent with the vaccine having no effect whatsoever on seriousness or hospitalization, while decreasing the likelihood of a positive test among those seriously ill by 67% and decreasing it among those hospitalized by 100%.
COVID-Like Illness in CDC Data
For the first time in late January, 2022, the CDC released COVID-like illness numbers for a large set of data in US hospitals. In this report it is called “COVID-19-like illness” and is defined as a collection of codes within electronic health records representing respiratory failure, pneumonia, dyspnea (trouble breathing), cough, fever, vomiting, or diarrhea.
The report covered 87,904 hospitalizations from 259 hospitals across ten states between late August, 2021 and early January, 2022.
79% of the hospitalizations for COVID-like illness tested negative for COVID.57% of the hospitalizations were vaccinated. An mRNA booster shot was 94% effective against testing positive during the delta-dominant period and 90% effective during the omicron-dominant period.
This 90-94% efficacy meant the vaccine helped you get a negative test despite being hospitalized for COVID-like illness.
This study was not designed to see if the vaccine had any effect on the likelihood of being hospitalized for COVID-like illness, but, as I outlined here, 57% of those hospitalized being vaccinated is perfectly consistent with the vaccine having no effect at all.
COVID-Like Illness Summarized
Between the Pfizer trial and the CDC data, the vaccines are 90-95% effective at getting a negative test despite having little to no effect on mild to moderate illness (virtually all of the COVID-like illness in the Pfizer trial), or severe and hospitalized illness (six people in the Pfizer trial and everyone in the CDC study).
Severity Among Those Testing Positive
As we move into those testing positive, we have to keep in mind that the vaccines, especially the mRNA vaccines, are remarkably effective at preventing a positive test among those who have COVID-like illness. So vaccinated people who test positive are the overwhelming minority of vaccinated people with COVID-like illness.
It is in this minority that the vaccines seem on the surface to be preventing hospitalization.
What is strange, however, is this effect seems to be found exclusively in situations where the vaccines have sub-par efficacy against testing positive, such as with the J&J vaccine, or with the mRNA vaccines after they start declining in efficacy in the face of time or in the face of emerging vaccine-resistant variants.
We have to remember, moreover, that association is not necessarily causation. While the vaccines could be preventing hospitalization specifically in those who test positive at the expense of greater numbers of vaccinees who test negative winding up in the hospital, I will argue here that the positive test among vaccinees is simply acting as a marker of a more mild inflammatory response and more mild spike protein toxicity, and merely serves a predictor that they will stay out of the hospital.
To the extent this is true, this represents the remarkable fact that the vaccines may not be doing anything clinically useful at all.
PCR-Positive Severity in the Vaccine Trials
Throughout our analysis, we have to remember that for the vaccines to specifically help with severity once you get a positive test, they need to show a greater effect on hospitalized cases than they show on the positive test. Otherwise, fewer PCR-positive hospitalized cases is merely a result of fewer PCR-positive tests.
We can start our analysis of severity among those testing positive by going back to the Pfizer trial. Among the serious cases testing positive, three were in the placebo group and only one was in the vaccine group. Among the hospitalized cases testing positive, two were in the placebo group and none were in the vaccine group. These numbers are too small for stats, but they give the appearance that the vaccine is 67% effective against severe cases and 100% effective against hospitalization.
This is a mirage. We know from the FDA briefing document cited above that there was no difference at all in serious or hospitalized cases of COVID-like illness, just a 67%-100% drop in testing positive among them.
The numbers of serious cases are so small, however, that it is impossible to predict what they would have looked like if they had been larger.
For the Moderna trial, we don’t have data on total COVID-like illness. All of the efficacy data are restricted to those who tested positive. The relative efficacy for any COVID-19 was 93.2%, for severe was 98.2%, and for death was 100%. The efficacy against hospitalization wasn’t calculated but the supplementary materials show that one person was hospitalized for COVID-19 in the vaccine group and 27 were hospitalized in the placebo group, suggesting efficacy around 96%.
While the Moderna stats for severe and hospitalized cases are not statistically different from any COVID-19, it is possible that the study was underpowered to detect a small effect on severity. 98.2% is indeed somewhat greater than 93.2%, and to a lesser extent so is 96%. Still, these differences are not much to write home about.
We must keep in mind that, if we had data for COVID-like illness, this “efficacy” would probably be in simply achieving a negative test, as it was in the Pfizer trial.
The J&J vaccine is less effective at preventing a positive test, yet seems to show a specific effect on severity. Although they reported very few mild cases, they reported 93.1% efficacy against hospitalization, 85.4% against severe-critical COVID-19, 62% against moderate COVID-19, and 66.5% against any COVID-19. The difference between hospitalization and moderate COVID-19 was statistically significant, and the difference between hospitalization and any COVID-19 almost reached significance. This trial, then, offers modest suggestion that being vaccinated protects against hospitalization among those who test positive.
We must continue to keep in mind that, if we had data for total COVID-like illness, this “efficacy” would probably be in simply achieving a negative test, as it is in the Pfizer trial.
Nevertheless, it is notable that the one trial among the US-approved vaccines to show an apparent effect on severity is in the trial with the vaccine that is weakest overall. This seems to foreshadow what we will see in the “real-world” observational data below.
PCR-Positive Severity in the Observational Studies
Observational studies do not unanimously support a specific effect of the vaccines on hospitalization. In fact, a meta-analysis of observational studies found 87% efficacy against testing positive during illness and 89% against hospitalization. These are nearly identical numbers, suggesting that the effect on hospitalization is merely a result of the effect on the positive test. In other words, once you get “COVID” (symptoms plus a positive test), the vaccine does nothing to alter your likelihood of being hospitalized.
However, when we look at specific studies that were able to witness the waning of vaccine efficacy against a positive test, a specific protection against hospitalization appears to emerge. For example:
In Finland, efficacy against testing positive waned from 82 to 62% and lost statistical significance after three months; by contrast, efficacy against hospitalization stayed above 88%.
In New York State, efficacy against testing positive waned over the course of three months from 93 to 67% for Pfizer, 96 to 77% for Moderna, and 89 to 69% for J&J. By contrast, efficacy against hospitalization stayed in the mid to high 90s for all three vaccines.
In Israel, efficacy against testing positive and hospitalization was similar during the pre-delta period. However, once the delta variant emerged, efficacy against testing positive declined from 95 to 64%, while efficacy against hospitalization only declined from 98 to 93%.
In California, as delta took over between May and November of 2021, efficacy against testing positive declined from 95 to 86.3%, while efficacy against hospitalization only declined from 96.6 to 95.6%.
In LA County, as delta gave way to omicron, efficacy against testing positive fell from 74 to 50%, while efficacy against hospitalization only fell from 92 to 81%.
In all of these studies, as the vaccine efficacy against testing positive waned, the efficacy against hospitalization either stayed the same or declined at a slower rate. Thus, the gap between these two metrics emerged and grew over time. This caused an apparent independent effect on hospitalization to emerge within those who tested positive.
This is true despite the fact that the most recent CDC data, as cited above, show that 57% of those hospitalized for total COVID-like illness are vaccinated, suggesting there is little to no effect of the vaccines on being hospitalized for COVID-like illness.
Considering the Possibilities
If we ignore the PCR-negative COVID-like illness — as is done systematically almost everywhere — it appears that the vaccines are simply losing their potency around the edges, allowing some infection to occur, but staying strong in their most important task: keeping you out of the hospital.
Yet once we throw the PCR-negative COVID-like illness into the mix, this appears completely spurious. They aren’t keeping anyone out of the hospital. They’re just causing the ones who wind up in the hospital to test negative.
But if they’re doing nothing, why is it that specifically during the phase of waning efficacy vaccination is associated with a lower risk of hospitalization specifically in those who test positive?
Clearly they’re doing something. And the two most apparent interpretations are these:
They are protecting those who test positive from winding up in the hospital.
Or, they are causing a positive test to become a predictor of a mild case that will not lead to hospitalization.
The first interpretation has some challenges.
First, why would their effect on severity get better while their effect on testing positive (often deemed “infection”) is getting worse? The idea that they’re focusing on their most important job is rather silly. These aren’t two separate jobs. They are both functions of immunity, which is declining.
Second, if the vaccines are causing the lower risk of hospitalization among those who test positive, are they causing a proportionate increase in hospitalization among those who test negative? The CDC data do not make it clear at all that the vaccines are in net reducing the number of people hospitalized for COVID-like illness, so it seems like the math would have to balance out.
I will now argue for the second interpretation: as the vaccines start losing their potency against a positive test, the positive test becomes a marker for a more mild illness that will not lead to hospitalization. This is a result of the negative test acting as a marker for systemic inflammation and spike protein toxicity that increases the risk of hospitalization. Before the waning phase, the test does not act as such a marker. In unvaccinated people, the test never acts as such a marker.
Explaining the Paradox
As we attempt to explain this paradox, we need to keep in mind that when we say the vaccines generate a negative test, this may simply mean that they make the negative test come faster. It is quite possible that if we were testing everyone every single day we would not see any effect of vaccination.
In the vaccine trials, the negative test delivered by the vaccines occurred after someone developed symptoms of COVID-like illness.
Only the Moderna trial provided data on testing without symptoms. They added it in at the end, right before the unblinding and the offering of vaccination to the placebo group. When everyone was tested, efficacy against a positive test was only 41%. It was after someone developed COVID-like illness that Moderna reported 93% and Pfizer reported 95%.
That means the vaccines are more than twice as effective at delivering a negative test after one develops COVID-like illness than they are when one is asymptomatic.
While the vaccines may be reducing the incidence of COVID, these results could also be explained by them delivering a negative test much faster. The mediocre results when everyone was tested may betray that they just can’t deliver the negative test into the presymptomatic phase.
Taking the Pfizer protocol as an example, volunteers who thought they had COVID would get a telehealth visit “optimally within three days” of symptom onset, in which they would be advised to self-collect a nasal swab and ship it in for analysis. If all things went “optimally” (we actually know they went FAR from optimally) and the swab was collected within a day, the negative test was being delivered within four days after symptom onset. With the known incubation period, this would usually be within 8-9 days of initial infection but could be up to three weeks after initial infection.
Why would the vaccines help deliver a negative test faster?
This can be explained by the differences in natural immunity and vaccine-induced immunity.
Natural immunity, as reviewed here and here, is fundamentally different from immunity induced by an injected vaccine.
While there is certainly a role for cellular immunity in all of this, the T cell response to vaccination and natural infection seems to be largely similar as far as it has been studied, and I focus here on the very clear distinctions in the antibody response.
Natural Immunity: The Centrality of Mucosal IgA
When you encounter a respiratory virus naturally, it enters through the mucous membranes of your eyes, nose, or mouth.
Before you were ever exposed to it, you were already equipped with some IgA antibodies that are relatively nonspecific and capable of binding to the virus and all kinds of other things, as well as some cross-reactive IgA antibodies that you had gained from exposure to similar viruses in the past.
It is your local mucosal immune system that makes these antibodies. They are unique to the mucosa (the lining of your mucous membranes) and different from what circulates in your blood. They are multimeric (more than one antibody bound together) secretory (released from the cells into the fluid) IgA. Multimeric secretory IgA are vastly superior to any other type of antibody in binding up viral proteins and preventing them from infecting cells. IgA antibodies are also unique among all antibody classes in that they do not produce inflammation.
If your “innate” or preexisting mucosal IgA is stellar, it will stop the virus in its tracks and you will never get sick. These are the kids who seem impervious to COVID. These are the people who wound up with positive antibody tests and said to themselves, “when did I ever get sick?”
If the preexisting mucosal IgA is anything less than stellar, some virus will leak through and you will get some degree of illness. But as soon as you are exposed, your mucosal immune system is on it, making more specific multimeric secretory IgA that will stop the virus even more effectively. These will, if they are made fast enough, help restrain the severity of your illness. Regardless, they will be your first and foremost defense the next time you encounter the virus to make sure the second time you don’t get sick.
As the virus passes the mucosal immune system, your systemic immune system starts to step in. You will produce other types of antibodies in your blood, and some of them will leak into your mucous membranes. Additionally, much smaller amounts of other types of antibodies are made locally in the mucosa. These, as well as cells of the innate immune system or virus-specific T cells, are responsible for inflammation you experience in your mucous membranes. If your mucosal defense is inadequate, the virus spreads farther and you develop a much stronger systemic response. But the mucosal IgA has first dibs against the virus, and the stronger its response is, the less inflammation you will experience in clearing the virus.
The mucosal IgA is also the main thing binding up the virus in your nose, and should be the main determinant of a negative test.
Vaccine Immunity: The Centrality of Systemic IgG
Vaccinated people can develop mucosal IgA in response to the virus when they are exposed, but this is not a function of the vaccine. It’s a function of being human. What the vaccine adds is completely different.
When you get a vaccine injected into your arm, it generates primarily a systemic IgG response. Unlike IgA antibodies, IgG antibodies are inflammatory. Unlike mucosal antibodies, vaccine-induced IgG mainly circulate in your blood. Antibodies from the blood have to reach very high levels to spill into your mucous membranes. When they do, they are weaker and less abundant than what is caused by natural exposure, and completely unlike the natural secretory IgA, they are inflammatory.
Saliva is usually used as a representative of mucosal fluid when studying responses to infection or vaccination.
Using saliva in this way, most people who get COVID develop mucosal IgA, which dominates over mucosal IgG and seems to last for around 50 days based on cross-sectional data. This would be expected, of course, to recover quickly with additional stimulation from natural virus.
In response to the Pfizer vaccine, the mucosal response is weak and mostly IgG. The mucosal IgG is 163 times higher than the mucosal IgA, but almost 1800 times lower than the IgG in serum. Only 18% of vaccinated people develop a mucosal response significant enough to neutralize the virus in vitro, unless they have already had COVID before, in which case the vaccine provokes a neutralizing mucosal response in 60% of them. The antibodies only appear in the saliva when the serum levels reach a certain threshold, suggesting that high levels of serum antibodies are required to cause some to spill into the mucosa.
Within the Moderna trial, the vaccinated people who were least likely to test positive after developing COVID-like illness were those with the highest concentrations of spike protein-neutralizing IgG in their blood. Since the negative test is in their nose, this supports the idea that high concentrations of IgG in the blood leak into the nasal mucosa to bind to the RNA being tested for with PCR.
It would be hard to explain how the vaccine could help someone test negative, however, if only 20% of vaccinees develop a neutralizing response in their mucosa, as suggested by the previous study with the Pfizer vaccine. However, the serum antibodies in a “breakthrough case” go up ten-fold. Most likely, then, the vaccine primes the body for a very rapid ramping up of systemic IgG in response to viral exposure. Upon such exposure, the systemic IgG reaches sufficient concentrations that what leaks into the nasal mucosa is capable of binding up the virus and generating a negative PCR test.
The key difference between natural infection and vaccination here is that after vaccination, the ability of the mucosa to bind up the virus is dependent on a very high systemic response. This is because it is getting its antibodies into the nose by skimming off the top of what is present in the blood. Natural infection is relying on locally produced IgA and does not depend on the systemic response at all.
However, the vaccinated person is primed to respond by ramping up the IgG they have already prepared, so, although this depends on a high systemic response, it happens a lot faster.
Negative Tests May Correlate With Inflammation Specifically in the Vaccinated
This dependence on the magnitude of the systemic response suggests that, specifically among the vaccinated, the ability to quickly generate a negative test will also correlate with the magnitude of the inflammatory response to the vaccine. In response to Pfizer, interferon-gamma (IFN-gamma) goes up 2.5-fold after the first shot and 20-fold after the second. IL-6 increases 50% after the first shot and roughly doubles after the second. IFN-gamma is the most elevated out of all the cytokines and itself is correlated with the strength of the antibody response, explaining about 19% of the variation in it (P<0.001, r=0.433). The correlation with IL-6 is present, but weaker, and not statistically significant.
Among COVID patients, IFN-gamma is associated with severe disease, and IL-6 is strongly associated with both severity and death. That the second shot of Pfizer, on average, provokes a 20-fold increase in IFN-gamma and roughly doubles IL-6 raises the possibility that it, too, can cause a COVID-like cytokine storm, as there will obviously be some people whose response is much more extreme than the average. These are just the levels reached after vaccination, and they could be much higher in response to a subsequent illness.
This effect on IFN-gamma, a type II interferon, is in contrast to the effect of vaccination on IFN-alpha, a type I interferon. The Pfizer vaccine actually mildly suppresses IFN-alpha. IFN-alpha levels in general do not have any clear relationship to disease severity, but there is some evidence that early treatment with nebulized IFN-alpha is beneficial, and autoimmune antibodies to IFN-alpha are a major contributor to COVID severity. One extensively justified hypothesis paper documents many ways in which the vaccines may compromise the response to IFN-alpha, which might be much more important than their mild suppression of its production. It would seem, then, that the effect on type I interferon is likely to, if anything, worsen COVID severity.
Since the ability to generate a negative test in vaccinated individuals depends on systemic IgG reaching high enough concentrations in the blood to spill into the nose in adequate quantities, and since systemic IgG correlates with the undesirably balanced inflammatory response as reflected in the IFN-gamma spike, a negative test could become a marker of a greater level of undesirable inflammation.
The Duration of the Negative Test Benefit May Correlate to the Duration of Spike Protein Toxicity
The spike protein is a toxin. It alone is sufficient to break mitochondria into fragments and cause lung damage in hamsters. In fact, the spike protein alone causes COVID-like illness in mice.
The spike protein also has the potential to generate autoimmunity after vaccination, which is known to occur in severe COVID cases.
Previously, it had been shown that spike protein remains in the blood of humans up to 28 days after vaccination. A paper released at the end of January provided the first evidence that the spike protein stays in the human body for at least 60 days after vaccination. It is found in the lymph nodes of the armpits. It is harder to detect in the blood, but this paper provided evidence that this is because the high levels of antibodies in the blood bind to it and help it evade detection.
The spike protein is not, by contrast, found in the armpit lymph nodes of previously infected but unvaccinated individuals.
In fact, virus only gets into the blood in severe cases of natural infection. This includes 44% of those on a ventilator, 27% of those hospitalized, and 13% of those treated as outpatients. Almost certainly the incidence is even lower in those with mild cases who never seek hospital treatment, and it is almost certainly non-existent in those who were exposed without ever feeling ill.
The spike protein in the vaccines is also radically different from the spike protein in the natural virus, modified to increase its persistence in the body and the quantity of its production, with unknown health consequences:
The four nucleotides in RNA, the “letters” that make up the “code,” are adenosine (A), guanosine (G) uridine (U), and cytidine (C). In mRNA vaccines, all the uridine is replaced by a modified form called pseudouridine to prevent the innate immune system from destroying the mRNA.
The natural spike protein changes shape as it binds to our cell membranes but the vaccine spike protein has two amino acids changed to stabilize the initial shape, which makes it stimulate the immune system more effectively.
Regulatory regions from the mRNA that code for proteins that our red blood cells make were added to the vaccine spike protein to make it get produced in higher quantities for longer.
The “G” and “C” letters were used to replace the “A” and “U” letters whenever they could do so without changing the amino acid sequence of the resulting spike protein. The GC content of Moderna is 47% higher than that of the natural spike, and it is 69% higher in Pfizer. This may increase the amount of spike produced by anywhere from several-fold to more than 100-fold, and is likely to create many differences in the way the mRNA can fold into three-dimensional shapes with broad capacity to cause cellular dysfunction as outlined here.
Altogether, then, spike protein is only likely to enter our system in severe natural disease, whereas it is guaranteed to circulate systemically after vaccination. The vaccine version of the mRNA for it is, moreover, highly modified to produce large quantities of the protein for a long duration, making it persist in vaccinated individuals for at least 60 days. In animals, it alone is sufficient to cause COVID-like illness through its direct toxic effects on cells.
Although the paper showing the 60-day duration did not report correlations with antibody levels, it seems very likely that persistence of the spike protein in the lymph nodes would be a major driver of persistence of the antibody response to it.
Since the persistence of the antibody response would drive persistence of the negative test advantage, then a persistent negative test advantage months after vaccination may act as a marker for the persistence of spike protein within the body, to spike protein toxicity, to the possibility of spike-induced autoimmunity, and perhaps even to spike protein-induced COVID-like illness.
The Solution to the Paradox
Here is what I propose:
When the vaccines are in their early, high-efficacy phase, they have no impact on the incidence or severity of COVID-like illness, but they generate a negative test rapidly. This is a result of very high levels of IgG antibodies spilling over from the blood into the nasal mucosa, where they bind to the viral spike protein and prevent the virus from locally replicating.
During the high-efficacy phase, the ability to deliver a negative test this rapidly is so nearly universal (93-95%) that a negative or positive test has no power to discriminate between those who have clinically relevant differences in their level of inflammation or spike protein toxicity.
During the waning phase, the loss of efficacy against the PCR test is a result of declining IgG in the blood combined with loss of neutralizing power against newer vaccine-resistant variants. Less excess over the threshold required to spill into the nasal mucosa, or less efficient neutralizing power of those antibodies, drives a higher incidence of positive tests. Those who continue to test negative in this phase are selectively those whose antibody response remains persistently high.
This persistence correlates with persistence of the undesirably imbalanced inflammation, cumulative spike protein toxicity, acute spike protein toxicity at the time of any later illness, and the possibility of spike-induced autoimmunity.
A persistence of these undesirable effects makes someone more likely to be hospitalized with COVID-like illness. The COVID-like illness could be COVID itself despite the negative test, another virus (with the vaccine enhancing infection through suppressing viral competition), a result of spike protein toxicity or spike-induced autoimmunity, or could be another disease altogether that is aggravated by any of these factors.
During the phase of waning efficacy, the persistence of these effects correlates with persistent ability to generate a negative PCR test. This makes a positive test a marker for a mild case of COVID-like illness that will not lead to hospitalization.
By focusing exclusively on those with a positive test, the media and public health establishment exploit this statistical artifact and use it to misleadingly claim that the vaccines are protecting those who test positive from being hospitalized.
Are the Vaccines Doing Anything Clinically Useful?
Unfortunately it is impossible to answer this question. It all hinges on whether PCR-negative COVID-like illness is more, less, or equally dangerous compared to PCR-positive COVID-like illness.
In the Pfizer trial, among the six people who developed serious COVID-like illness, neither a positive test nor vaccination made any difference at all. Unfortunately, six is too small a number from which to conclude anything.
In the CDC data, we do not know the rate at which PCR-negative COVID-like illness leads to disability, ICU admission, or death.
Without knowing the clinical consequences of PCR-negative COVID-like illness, it is impossible to know whether the vaccines are doing anything clinically useful.
Right now, it is possible that their apparent benefits are completely explained by these two phenomena:
Making those with COVID-like illness get a negative PCR test.
During the waning phase of efficacy against the PCR test, making the more severe cases test negative and allowing the less severe ones to test positive.
We must demand to know the clinical consequences of PCR-negative COVID-like illness to know whether the vaccines are doing anything clinically useful.
The Bottom Line
The “Hospitalization Paradox” refers to the fact that the COVID vaccines do not meaningfully protect against development of COVID-like illness or hospitalization for it, yet specifically in the phase of waning efficacy, they appear to modestly protect those who test positive, but not those who test negative, from hospitalization.
This can be explained by the vaccines producing a more rapidly obtained negative test through the assistance of systemic antibodies that leak into the nasal mucosa. This correlates with undesirable inflammation, spike protein toxicity, and possibly spike-induced autoimmunity, all of which can cause or worsen a case of COVID-like illness. During the waning phase, the negative test becomes highly correlated with these adverse effects, causing a positive test to become a marker of a mild case of COVID-like illness that will not lead to hospitalization. This is a statistical artifact.
This is distorted throughout the media and by public health agencies, which ignore all PCR-negative COVID-like illness. This allows the initial extreme effectiveness against a negative test to be claimed as an effect on illness. As the statistical artifact causing the “hospitalization paradox” emerges in the waning phase of efficacy, this allows them to claim they are still highly effective against hospitalization.
If we include the PCR-negative COVID-like illness, however, they are revealed to be effective neither against illness nor against hospitalization.
To know whether the vaccines are doing anything clinically useful, we must demand from our government the data on disability, ICU admissions, and mortality for total COVID-like illness and from all causes, all separated by age and status of PCR test, vaccination, and comorbidities.
I am not a medical doctor and this is not medical advice. My goal is to empower you with information. I will not take a position on whether you should or should not get vaccinated. Please make this decision yourself, consulting sources you trust, including a caring health care professional.
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This is potentially the most important article I have read on the covid vaccines. Thanks a lot, Chris! I became a paid subscriber to your Substack.
Thanks Chris, I've been following your work since 2008. You're an inspiration. May I suggest that anyone fragile enough to die from the vaccine has already been removed from the potential pool of people to die from COVID and this gives an artificial reduction in deaths. Similar to your hypothesis in 2010 for The China Study, you don't die from COVID if you're already dead. Since a death less than 14 days after vaccination is counted as "unvaccinated" this data is hidden from the public. Providing the false appearance that the vaccine reduces mortality.