Test-negative case control studies are abundant in the era of COVID, and are the primary type of observational study used to calculate vaccine efficacy.
As reviewed here, this design was first used in in 1980 for the pneumococcal vaccine. Its use rapidly increased in the last decade, and since 2011 it has been the design of 90% of vaccine efficacy studies.
The definition of the test-negative design is a design in which “the same clinical case definition is used for enrollment of both cases and controls, and laboratory testing is subsequently used to distinguish which patients were cases and which were controls.”
Notice in this definition that the same clinical case is used to enroll the cases and the controls. In other words, the cases and controls are all cases.
At first glance this may not seem to make sense. How can the cases and controls all be cases?
The key word is clinical.
For enrollment, everyone is equally sick. But for analysis of vaccine efficacy, the clinical picture becomes irrelevant and suddenly we switch to defining a case as someone who tests positive for the pathogen of interest and a control as someone who tests negative. Hence the design is called the “test negative” design.
Everyone is what?
Everyone is equally sick.
Now, I understand that the word “scam” may seem pejorative. This is science, after all, and we should keep our emotions out of it.
I truly believe the word “scam” applies here. Not among scientists. Scientists who conduct, publish, read, and analyze test-negative case control studies all know what's going on. They understand the design. They aren't scamming each other.
In fact, they have good reasons for conducting these studies and sharing them amongst themselves:
It is more efficient to enroll people. You can just enroll everyone in a hospital for some illness and, voila, you already have your cases and your controls.
Differences in health care-seeking behavior can be controlled for. For example, if everyone is hospitalized, then you know they are all equally likely to seek out the hospital.
The reason I believe the word “scam” is appropriate is because all public health messages derived from these studies are clearly scamming the public. If a vaccine is said to be such-and-such percent effective against being hospitalized for disease X, absolutely no non-scientist in the general public will think this means that you will instead be hospitalized for something else. Every non-scientist in the general public will hear this and think that it is roughly that percent effective at actually keeping you out of the hospital.
For example, in The Pandemic of PCR-Negative COVID-Like Illness, I covered the recent test-negative case control study from the CDC wherein the 87,904 hospitalizations for COVID-like illness were 57% among the vaccinated and wherein 79% of them tested negative for COVID. They all met the same clinical case definition — hospitalization for COVID-like illness — but, in the words of the test-negative definition “laboratory testing [the PCR test] is subsequently used to distinguish which patients were cases [PCR positive] and which were controls [PCR negative].”
Because those who had received an mRNA booster shot were, assuming correlation is causation, 94% effective at causing someone to test negative during the delta-dominant period and 90% effective during the omicron-dominant period, the authors concluded that they were 90-94% effective against “COVID-19–associated hospitalizations.”
Absolutely no non-scientist in the public will hear this and intuitively grasp that this means the vaccines would give them a roughly equal chance of winding up in the hospital with COVID-like illness but would be highly effective at preventing them from testing positive. Almost anyone would think that this means if they are exposed to COVID, they are 90-94% likely to stay out of the hospital.
Hence, it is a scam.
None of the scientists or public health bureaucrats sharing these numbers with the public think the public will understand them. They know the perception will be that the vaccines keep people out of the hospital. It is too obvious that “preventing COVID-19–associated hospitalizations” sounds like the vaccine is “preventing hospitalizations” for anyone involved not to know this is what people will hear.
This is not just about COVID vaccines. Up through 2018, there were 348 such studies published, and between 2011 and 2018 these constituted 90% of vaccine efficacy studies.
The review I cited above cites four polio studies in which everyone involved was paralyzed.
Surely, the worst example of this design (apart from everyone in the study being dead) would be if everyone was equally paralyzed but the vaccine was effective at getting them a negative stool test for polio.
Could it really be that bad?
Here are the four studies:
Grassly, 2007: Children in India who developed acute flaccid paralysis between 1997 and 2006 were included. Acute flaccid paralysis is the specific type of paralysis that classically was attributed to polio but, when it persisted after the near-eradication of polio with the polio vaccine, was later realized to have other causes as well. Cases had a positive stool test for type 1 wild poliovirus. “Wild” means it wasn't the poliovirus included in the vaccine itself. Controls were equally paralyzed, but had a negative stool test and were matched to each case by district, age of onset, and date of onset. Vaccine efficacy was calculated as the likelihood that the paralyzed child would get a negative stool test.
Jenkins, 2008: Children in Nigeria who developed acute flaccid paralysis between 2001 and 2007 were included. From 27,379 cases of paralysis, 16.2% were excluded for insufficient data and 5.4% were excluded because the vaccine virus was found in their stool (raising the obvious question of whether the vaccine caused their paralysis). From among the remaining cases of paralyzed children, cases were those with at least one positive stool test for type 1 or type 3 wild poliovirus and controls were those who tested negative for both wild polioviruses and matched to the cases by region, age of onset, and date of onset. Vaccine efficacy was calculated as the likelihood that the paralyzed child would get a negative stool test, with separate estimates for the two types of wild poliovirus.
Mahamud, 2014: This study looked at cases of childhood acute flaccid paralysis in Somalia between May and December of 2013. It used two approaches, one was the test-negative design and one was a more traditional type of case-control study. They first defined cases of acute flaccid paralysis, and then separated these into wild poliovirus type 1 cases and nonpolio cases. For both parts of the study, the wild poliovirus type 1 cases served as cases. In the test-negative portion, the nonpolio cases served as controls. In a second comparison, neighborhood contacts with no symptoms served as the controls. Vaccine efficacy was calculated in the first comparison as the likelihood the paralyzed child would test negative, and in the second comparison the likelihood the child would be asymptomatic. Notably, the comparison to neighborhood controls seems at first glance far more reasonable than the comparison to nonpolio paralysis, but this comparison is still specifically with the wild type 1 cases. Nowhere in the paper, even in the section on neighborhood controls, do they give us any sense whether vaccination is related to a reduced risk of acute flaccid paralysis.
O'Reilly, 2012: Just under 47,000 children in Pakistan and Afghanistan who developed acute flaccid paralysis between 2001 and 2011 were included. Vaccine-derived poliovirus was only found in six children's stool and those children were excluded. Cases were paralyzed children who tested positive for type 1 or type 3 wild poliovirus and controls were chosen from among the paralyzed children who tested negative, matched to the cases by district, age of onset, and date of onset. Vaccine efficacy was calculated based on the likelihood of the paralyzed child testing negative.
All four studies considered a vaccine effective in proportion to how well it made a paralyzed child likely to test negative for wild poliovirus.
Only Mahamud, 2014 also included neighborhood asymptomatic controls. However, even in this comparison, only the likelihood the vaccine protected against type 1 wild poliovirus was calculated. No comparison was made to see if the vaccine made children in the neighborhood any less likely to get paralyzed.
The most bizarre statement found in any methods section of these four papers is found in O'Reilly, 2012:
To calculate vaccine-induced population immunity, children with non-polio acute flaccid paralysis (control children) were assumed to represent a random sample of children in the population of the corresponding age.
Really? A random sample of children from the population has a 100% rate of acute flaccid paralysis???
While it is certainly an important scientific question to see if a vaccine protects against a positive test for the specific pathogen or strain of pathogen it is designed to protect against, it is scientific malfeasance to only look at this without looking at whether the intervention causes a reduction in the clinical presentation being targeted. While there are many other causes of acute flaccid paralysis than type 1 or type 3 wild poliovirus, for example, and while it is interesting to know if the vaccine is effective at reducing those specific causes, the design of these four studies allows for the possibility that the vaccine causes paralysis through viral competition (making children less likely to get wild poliovirus but more likely to get a different virus that causes paralysis), vaccine side effects (for example, causing Guillain-Barre syndrome), or antibody-dependent enhancement (perhaps causing a worse infection of nervous tissue, while also causing more effective clearance of the virus from stool).
Similarly with COVID, why is the vaccine having no evident effect on hospitalization for COVID-like illness? Viral competition? Vaccine side effects? Antibody-dependent enhancement?
It is ironic that so many people who claim to be “evidence-based” are so wrapped up in the mainstream narrative around vaccines that they hold them up as a sacred cow, yet also claim to be concerned with “clinical outcomes,” when the 90% of vaccine efficacy studies since 2011 using test-negative case control designs effectively treat clinical outcomes as totally irrelevant to the intervention being studied.
Test-negative case control studies reveal a huge portion of modern medicine that clearly has nothing at all to do with achieving health, but rather is preoccupied with achieving results on specific lab tests. It is about engineering blood and stool characteristics without regard to whether you are suffering from respiratory failure or paralysis.
The Bottom Line
While test-negative case-control studies make sense for scientists to use to ask very specific questions about how vaccines affect processes within the body, public health messages derived from them constitute a scam. These messages are crafted with intent to deceive the public.
When analyzing the efficacy of COVID vaccines or any other vaccine, the very first thing we should ask is, “is this a test-negative case control study?”
If it is, we should draw our attention to the fact that the study provides no information about health or disease, and that it's message is almost certainly deceptive.
The kernels of truth will be found in studies of other designs. Unfortunately, such studies are the minority, and we must sift through them carefully.
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