by Suavek
AI can indeed disprove the entire germ theory step by step. This article is one of those steps. While the propaganda-based falsehoods programmed into this robot are one aspect, the AI also possesses vast epistemological knowledge and an understanding of the fundamental principles of sound science. It is therefore a veritable treasure trove of evidence that can be used—with relatively little effort—to expose almost all the lies of profit-driven medicine and to reveal them as mere fabrications through impeccable, expert argumentation.
I didn’t think any additions were needed to the article published in July on FRAUD PREVENTION HOTLINE ( https://suavek1.substack.com/p/a-guide-to-dismantling-germ-theory-0e3 ). Fortunately, I found further evidence of the disease transmission hoax, which I naturally want to share with you. The article at the time addressed the false study results that the pharmaceutical industry deliberately funds and disseminates through its propaganda, including the use of internet trolls. Specifically, it concerned those studies that claim to have proven the alleged “contagion” or “infection” but completely “forgot” to consider the nocebo effect. You might wonder why this effect is generally much less well-known than, for example, the placebo effect. It’s a valid question, suggesting that it would be detrimental to the pharmaceutical industry if this phenomenon were widely known. Accordingly, the bought media shape their one-sided information and propaganda. Both effects are equally easy to understand, but in my opinion, they are deliberately discussed unevenly in public. Could this be pure coincidence?
The appearance of symptoms solely due to expectation, for example, after a person believes they have been injected with a supposed “virus” in their nose as part of a study—the nocebo effect—is just as well known to medical professionals as the placebo effect. The difference is that the study results incorrectly attribute most nocebo effects to alleged disease transmission, thus downplaying the problem of the effect.
The research results either exhibit serious methodological flaws, and misinterpret the onset of symptoms, or the studies are not representative because too few participants were involved. This shortcoming doesn’t seem to bother the fraudsters because they possess a massive propaganda machine with which they can claim to have irrefutably proven disease transmission. Should anyone point out the methodological errors, for example, by claiming online that the results are worthless, countless paid trolls will quickly appear, using specious arguments to assert the opposite. Refuting these “arguments” unfortunately requires some work, but you will soon read in this article that it is not difficult and does not require hours of work.
Of the many options available to pharmaceutical companies to present false study results as correct, I have selected only the following three here to avoid unnecessarily complicating the topic:
The nocebo effect is miscalculated, leading to incorrect reinterpretation of disease causes, resulting in the claim of alleged “disease transmission”. For this fraudulent purpose, a completely unsuitable control group is deliberately created. A placebo control group is insufficient to calculate the number of illnesses attributed to the nocebo effect within a study. This is concealed, for example, in this study, rendering the entire results worthless: https://www.thelancet.com/journals/eclinm/article/piis2589-5370(24)00421-8/fulltext . Several criteria must be met to correctly calculate the nocebo effect, but these are disregarded by the study leaders. Unfortunately, the pharmaceutical industry has no interest in fulfilling all of these criteria. One of these criteria is a completely untreated control group. This means they must not receive a placebo, a simulated "virus," or anything similar. Detailed information on this can be found later in the article.
Small sample size. If the number of test subjects is relatively small, then the study results are left to pure chance. The respective study is then not representative. It should be mentioned here that numerous results that, for example, failed to demonstrate “contagion” or “infection” remain unpublished and disappear into the filing cabinet of the respective pharmaceutical company. In contrast, the perhaps only study in which it was accidentally possible to make a corresponding number of participants ill because they were particularly susceptible to the nocebo effect is all the more intensely disseminated by the media. Since we are unaware of the unpublished studies that, despite the greatest efforts, failed to demonstrate disease transmission, we are often willing to believe that the published study results have some connection to reality. This is one of the oldest tricks in world history: what we don’t see remains unconsidered by our imagination. The picture of supposed “reality” then arises solely from what the pharmaceutical industry presents to the public.
Inappropriate mathematical and statistical tools are being invented to help the pharmaceutical industry simply fabricate non-existent evidence. For example, a modeling program is designed to calculate nocebo effects as being significantly lower than they would normally be. But scientists know that no modeling, and no fabricated tables, can undo the methodological flaws of a study. If study results are based on false scientific principles, they are always worthless, regardless of the mathematical tools used. If a proper control group is missing when calculating nocebo effects, then the symptoms will always be wrongly attributed to alleged disease transmission. Don’t be fooled by the pharmaceutical trolls posing as “truth fighters” who present you with absurd tables that supposedly prove the transmission of the non-existent “SARS-CoV-2.” Please see which criteria must be met in order to correctly calculate all nocebo cases, which are known to indicate no “virus” transmission at all.
The criteria required to measure nocebo effects were provided by AI, which is typically a propaganda tool of the profit-driven medical establishment. The links it provides may contain propaganda, for which I apologize. However, since they constitute evidence, they are also published. Based on these necessary criteria, any layperson can easily determine that the studies claiming to prove an “infection” or “contagion” are all worthless and should be considered pure propaganda. They simply do not meet the criteria listed below.
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To accurately measure the nocebo effect, a control group must overcome complex methodological, statistical, and ethical hurdles. Researchers must isolate psychological expectations from biological and external confounding variables. [1]
The Three-Arm Trial Design Requirement
A standard placebo group is insufficient to measure the true nocebo effect. A trial must include an additional no-treatment control group. [1, 2]
The Active Group: Receives the real drug or intervention.
The Placebo/Nocebo Group: Receives an inert substance alongside negative verbal suggestions or side-effect warnings.
The No-Treatment Control Group: Receives absolutely nothing but undergoes identical observation. [1, 2, 3]
The true nocebo effect is calculated by subtracting the adverse outcomes of the no-treatment group from the adverse outcomes of the placebo group. [1, 2]
Differentiating True Nocebo from Confounding Factors
The control group design must separate psychological side effects from natural variations. [1]
Natural History of the Disease: Symptoms like headaches or fatigue fluctuate naturally. The no-treatment control group establishes a baseline to ensure spontaneous symptom worsening is not misattributed to the nocebo effect. [1, 2, 3]
Regression to the Mean: Statistically, extreme symptoms tend to naturally moderate over time. Continuous tracking of an untreated group filters out this statistical artifact. [1, 2]
Symptom Misattribution: Daily physical anomalies, such as mild dehydration, are often blamed on a dummy pill. The control framework must determine if a participant is merely paying closer attention to normal bodily functions because they are in a trial. [1, 2]
The Information and Expectation Dilemma
Managing how information is presented to the control groups is structurally challenging. [1, 2]
Standardizing Verbal Suggestions: The exact phrasing, tone, and non-verbal cues from clinicians must be identical across the intervention arms. Small alterations can completely shift patient expectations and ruin the data. [1, 2, 3]
Framing Side Effects: To evoke a nocebo response, researchers must warn patients about potential side effects. However, explicitly telling a control group that they might experience pain can trigger localized hyperalgesia, altering the baseline data. [1, 2, 3]
Ethical and Blinding Constraints
Maintaining scientific integrity while protecting human subjects creates friction. [1, 2]
The Informed Consent Paradox: Ethical guidelines require informing participants about potential experimental harms. This mandatory disclosure automatically triggers the expectations that cause the nocebo effect, making an unprimed control state difficult to achieve.
Blinding Imperfection: In a three-arm trial, a no-treatment group cannot be blinded. Patients know they are receiving nothing. This introduces reporting bias, as untreated individuals might underreport or overreport symptoms compared to those taking a physical dummy pill. [1, 2, 3, 4, 5]
For a deeper dive into managing these experimental protocols, you can read the comprehensive methodological analysis published on Frontiers in Psychiatry. Additionally, clinical framework overviews are available through The Lancet Psychiatry. [1, 2]
[Editor’s note:
It is a well-known fact that modeling can easily be used for deception. Dr. Mike Yeadon also commented on this, stating that modeling attempts are always used when real evidence is lacking.
The AI has provided us with very useful information so far. Only here, at the end of its statement, does it attempt to mention the aforementioned tools, which are usually used to fabricate non-existent evidence. However, if we nevertheless assume that modeling should be considered a valid tool in a study, then this would only be the case if all the aforementioned criteria were met. I fear, however, that modeling will always distort the final results of a study to the advantage of the pharmaceutical industry. Ultimately, it always comes down to the question of how independently the programmer of software designed for modeling worked. For the sake of completeness, the AI’s highly questionable concluding statement is also published below.]
Would you like to explore the specific statistical models used to subtract natural disease progression from these control groups?
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The following study has already been mentioned above. It is an example of the fraud involving the so-called “infection” and, of course, does not meet the criteria mentioned above: https://www.thelancet.com/journals/eclinm/article/piis2589-5370(24)00421-8/fulltext . The following article about this study has already been published here : https://suavek1.substack.com/p/a-guide-to-dismantling-germ-theory-b4e. However, I must admit that it is rather long-winded, so I will shorten it considerably soon. Please excuse this. Nevertheless, I do not consider it completely useless even in its current form. In it, I was able to demonstrate that the results of this study are worthless for several reasons.
We are already familiar with scientific fraud based on modeled data. For criminal purposes, among other things, specially programmed software is used that already contains statistical models or tables, ensuring the result aligns with the criminal intent. This is how the alleged climate change was modeled for us, along with the millions of supposed “Covid” deaths that were predicted, so that billions of people would panic and submit to the highly toxic “Covid” injections. Recently, someone on Substack tried to use Killingley’s tables to strengthen the credibility of one of the falsified studies that allegedly proved an “infection” with the never-existing SARS-CoV-2 “virus”. However, this study did not meet the aforementioned criteria and was therefore, for this and other reasons, completely worthless. Consequently, I sent him this short AI query :
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No, “Killingley’s Table” is not an established scientific tool or an accepted methodology used to isolate the nocebo effect when an untreated control group is missing.
Without an active no-treatment control group, separating true psychological nocebo responses from independent, non-specific confounding factors remains statistically impossible within a single trial.
Why a Single Table Cannot Substitute an Untreated Group
No mathematical matrix or static data framework can definitively compensate for a missing control arm because it cannot dynamically capture the unique trial environment.
Confounding Variables are Context-Specific: Natural disease progression, regression to the mean, and spontaneous symptom fluctuations differ drastically across distinct patient cohorts, geographic regions, and seasons. A generic reference table cannot accurately predict these baseline changes for an unrelated study.
Environmental Variance: The physical environment of a clinical trial—such as a researcher’s unique tone of voice, the specific layout of the clinic, or local media coverage regarding a drug—shapes patient expectations. This localized anxiety cannot be calculated using predefined baseline values.
Methodological Workarounds for Missing Control Groups
If an untreated control group cannot be included due to logistical or ethical constraints, researchers rely on alternative study designs rather than reference tables to estimate the nocebo effect.
Historical Control Data: Researchers sometimes extract data from previous, identical clinical trials that did include a no-treatment arm. However, this approach decreases internal validity due to historical and demographic variations.
[Editor’s note: By resorting to the results of old studies, the falsified data is reproduced with impunity. A study leader who does this is not guilty of falsification because they did not participate in the original study and cannot be expected to know the exact research methods used at the time. In this way, both genuine errors and an age-old fraud are replicated endlessly. What a stroke of luck for the pharmaceutical industry! ]
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Editor’s note: At this point, I’ve shortened the AI’s statement to ensure the article remains clear.
If a study lacks even a suitable control group, then all the strange, well-conceived mathematical research rules can be misused for fraudulent purposes. This applies to any additional auxiliary techniques, which are supposedly helpful in mathematical calculations when genuine evidence is lacking.
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by Suavek
This article has not yet been able to address all the important topics. One of them is the false assumptions on which the completely worthless study results claiming the “infection” of animals are based. This is a completely different issue that requires entirely different evidence. I have not yet completed my work on this topic, so an article on it will have to wait. However, I would like to offer a few thoughts from a psychological perspective.
A person is always free to end their participation in a study and simply say “goodbye” to the study leader. An animal that has already had to live in captivity for a long time under extremely unhealthy conditions is already severely psychologically compromised. We know how closely the psyche is linked to health: often, or perhaps even always, they are two sides of the same coin. Such animals cannot run away, so their stress level is logically incomparably higher than that of a human subject. The general living conditions of such an animal suggest that even a seemingly minor additional stressor during a complex examination can be the proverbial straw that breaks the camel’s back. Only when one can empathize with such a laboratory animal can the extent of its heightened sensitivity be truly grasped.
The detection of an animal’s alleged “infection” is carried out under extremely difficult conditions, where the stress level is crucial in determining whether the animal will soon become ill or not. This is not rocket science and can be understood by anyone. When the limits of unimaginable suffering are exceeded, the health of any animal collapses, just as it would have any human. The only difference is that such limits are rarely exceeded in humans, but in a laboratory animal, its health can hang by a thread even before the crucial examination, a thread that can snap at the slightest additional stress. Under such circumstances, no one should be surprised if an animal becomes ill after suddenly having to inhale aerosols containing a supposed “virus” for minutes on end without access to properly fresh air.
The mere fact that the animal suddenly has to leave its familiar cage and is confined to an unfamiliar box filled with foul-smelling aerosols can have serious consequences for an animal with a weakened immune system, even if the aerosols were completely harmless. Furthermore, fraudulent PCR tests, which can produce positive results even without illness, are also used in animal studies.
I admit that this topic seems so horrific to me that I’m reluctant to research it. But I would like to add one more thing: Animals have feelings just like we humans do. Scientists who conduct such animal studies without any scruples are capable of any kind of scientific fraud simply because of their corrupt nature and lack of empathy. Logically speaking, such despicable individuals cannot be considered credible in the slightest. Of course, they will do anything for money that doesn’t cause them personal pain, but “only” pain for an animal. I’m quite certain that any trained police profiler with a background in psychology would confirm my assertion. Connecting these dots is surprisingly simple. Not a single word from modern-day Drs. Mengele can be considered credible.
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https://suavek1.substack.com/p/a-guide-to-dismantling-germ-theory-f34/comment/321930102
Weiß die Kontrollgruppe, dass sie keine Behandlung erhält? Erhält sie dieselben Empfehlungen wie die Nocebo-Gruppe? Denn warum sollten Nebenwirkungen auftreten, wenn sie weiß, dass sie keine Behandlung erhält und auch keine Empfehlungen bekommt?
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https://suavek1.substack.com/p/a-guide-to-dismantling-germ-theory-f34/comment/322094711
Hi Francine,
There is no “nocebo group” as such; instead, there is a treatment group and two control groups: a placebo group and a group that remains completely untreated—and is aware of this fact. If you call this group the “nocebo group,” that is still fine and completely understandable. This latter group must not be subjected to any additional stress resulting from study participation (which is admittedly quite difficult to achieve). To ensure this group does not develop fears about illness, they must know they are receiving no treatment; consequently, they cannot be blinded. This is the specific prerequisite for accurately measuring the nocebo effect. The incidence of illness within this group is then considered the baseline or “normal” rate. The placebo group develops significantly more illnesses because the participants fear becoming sick, thereby experiencing additional stress. This excess incidence of illness—compared to the untreated group (which experiences no such stress)—is attributable to the nocebo effect. The group receiving actual treatment with a substance is irrelevant in this specific measurement context, as the focus here is exclusively on the nocebo effect. Any calculation that fails to meet these prerequisites is incorrect or even fraudulent. While a placebo control group may suffice for other types of studies, it is inadequate for measuring the nocebo effect. If a study is blinded and all participants undergo some form of treatment—whether real or simulated—the factor of uncertainty and the participants’ anxieties can only intensify the nocebo effect. In this instance, a fully blinded study is counterproductive; the rules governing this type of investigation differ from those applicable to other studies.
The myth of “contagion” or “infection” stems from completely erroneous calculations regarding the nocebo effect, and any good scientist should know this. As this article shows, the correct calculation of the nocebo effect is no secret, but rather common knowledge.
Best wishes,
Suavek
P.S.
We should not forget that toxic substances can be used in an attempted “infection.” The alleged “virus isolate”—which is, for instance, inoculated into a human via the nose—contains significant amounts of them. Test animals are also forced, in agonizing experiments, to inhale such substances (for example, via aerosols), or the substance is injected directly into the animal’s brain in order to “demonstrate” the alleged “viral infection.”
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“Full disclosure, I sold my soul to the devil, who then leased it to big pharma.”
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Dr. Mike Yeadon’s Substack #1 :
https://drmikeyeadon.substack.com/
( Notes : https://drmikeyeadon.substack.com/notes, and other activities on Substack : https://substack.com/@drmikeyeadon )
The Telegram channel of Dr. Mike Yeadon ( other Telegram channels with his name are fake ! ) :
https://t.me/DrMikeYeadonsolochannel
A collaborative Substack by Dr. Yeadon and Suavek ( Dr. Mike Yeadon’s Substack #2 ) :
Fraud Prevention Hotline / suavek1.substack.com
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Source :
https://drmikeyeadon.substack.com/p/reminder-suaveks-substack-the-fph
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Source :
https://drmikeyeadon.substack.com/p/scorpions-in-the-dock
Consider subscribing to my friend Suavek s publication an essential move please. There you can find many posts from my Telegram channel collated with other material in a skilful way. Fraud Prevention Hotline
Best
Mike
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DEAR FRIENDS,
The two Substacks, Dr. Yeadon’s and Suavek’s, have merged into a single, highly informative entity. The Fraud Prevention Hotline is now officially Dr. Yeadon’s Substack No. 2. You can find his statement on this at the following link :
https://drmikeyeadon.substack.com/p/my-other-substack
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Before publishing an article, there isn’t enough time during the editorial process to discuss every detail. In case of doubt, each author is therefore only responsible for their own statements.
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We urge you, if possible, to add both Substacks to your recommended list in your Substack. Thank you very much in advance,
Mike & Suavek
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The possible support goes to Suavek. Any support is especially welcome at this time, and is VERY appreciated, but of course is not mandatory, as this Substack is free. I extend my sincere thanks to those who have supported me so far.
You can either do something against or for something :
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