Why the Independent Variable in Virology Remains Unestablished
Virology rests on a foundational methodological flaw, one that has persisted since the very birth of the field, and it strikes at the core of scientific inquiry itself: how causation is established
The flaw is so severe that it erodes the very ground upon which virology stands.
Exposing it completely dismantles the claims that sustain the discipline.
This is why the question of what it takes to scientifically demonstrate causation has remained central to my critique of virology.
However, before examining virology’s reliance on this error, we must first clarify what it actually means to demonstrate that something causes a specific outcome. Not merely suggest it.
Not simply correlate with it. But prove it as a true cause‑and‑effect relationship. That question lies at the heart of what makes a hypothesis scientific, and understanding this process makes virology’s fatal flaw impossible to overlook.
The Anatomy of a Hypothesis
Evaluating any claim of cause and effect requires a clear definition and understanding of what constitutes a scientific hypothesis. As defined by Britannica, a scientific hypothesis is a tentative explanation about a phenomenon or a narrow set of phenomena observed in the natural world.
At its core, it proposes that a specific, identifiable factor produces a particular outcome. But testing that proposal requires one essential step: the cause must be isolated and manipulated on its own, clearly distinct from alternative explanations.
To see how this works in practice, a scientific hypothesis begins with an observed natural phenomenon—an effect or outcome that occurs in the natural world and requires explanation. This observed outcome is known as the dependent variable (DV), the phenomenon the researcher seeks to understand. For example, if a tree catches fire, the fire itself represents the observed outcome (DV) the researcher wants to explain.
The next step is to identify a proposed cause, known as the independent variable (IV). In this example, the hypothesis might propose that lightning striking the tree caused the fire. For this proposed cause to be scientifically tested, it must be identifiable, present, and capable of being independently controlled or manipulated to determine whether it can actually produce the observed effect.
In addition, all other possible causes, known as confounding variables (CV), must be accounted for. In this example, that could include a lit match, a discarded cigarette, or even environmental factors like heat buildup from dry leaves.
Only by isolating the proposed cause and controlling for alternative explanations can the researcher determine whether the effect is truly the result of that cause, rather than an assumption based on correlation or incomplete evidence.
This principle is reflected in the 2018 paper From Ideal to Real Risk: Philosophy of Causation Meets Risk Analysis. In section 4.2. Causation Must Be Studied by Comparison and in Isolation, it is emphasized that causal factors must be isolated or controlled in order to determine their specific contribution to an outcome.
The authors write:
“In the lab, one will try to isolate the causal factor as much as possible from its usual complexity to see what it does on its own, but this might not always be practically possible. RCTs are one way to do this, the idea being that if there is a difference in outcome between the two situations, it is because of the controlled factor. Only if the cause can be isolated or controlled in this way, can we say to have “observed” its causal contribution.
Without such isolation, we cannot know if some other factor was present that produced the effect instead. This is called the problem of overdetermination and is a problem for studying causation in its natural complexity (Collins, Hall, & Paul, 2004). From an empiricist point of view, we thus see that causal complexity becomes a challenge for establishing what exactly the causal contribution of each factor is, which means that separation and isolation are necessary steps of the scientific procedure.”
The authors further acknowledge that individual factors must be distinguished from confounders if we are to determine whether they actually contribute to the outcome. This is one of the basic difficulties of establishing causation.
Natural systems are complex, and unless the variable being examined can be isolated, we cannot simply assume that the observed outcome was caused by that variable rather than something else.
This provides a straightforward standard for determining whether causation has actually been demonstrated. Observing an outcome and associating it with a proposed cause is not enough. The cause must be identified and isolated, and shown to produce the outcome without relying on other possible explanations.
The Inversion of Logic
It is upon applying this scientific standard to “infectious” disease research that an important question is raised: does virology follow the basic rules of experimental science? Specifically, do researchers isolate and test the independent variable before observing its alleged effects? This is where the fatal methodological flaws arise in virology.
While there is an observed phenomenon—illness and its apparent “spread”—and a clearly definable dependent variable in the form of symptoms, the corresponding independent variable is not established in a direct and controlled manner.
Examining the historical literature reveals that the concept of a “virus” did not arise as a discovered entity, but as a theoretical construct, a late 19th century placeholder explanation for disease processes that bacteria could not explain.
Unlike a lightning strike, which can be directly observed and tested independently of the fire it causes, the “virus” was inferred from the very effects it was proposed to explain. Because the independent variable was not independently established and characterized apart from the effect it was claimed to produce, the foundational requirement for a true cause-and-effect demonstration was bypassed from the very start.
Instead, the effect—disease or cellular changes—is reproduced under artificial laboratory conditions using complex, unpurified materials such as fluids, tissues, or swabs. These materials are, by definition, a collection of confounding variables containing countless proteins, extracellular vesicles, cellular debris, and unknown factors.
When these are introduced into animals or cell cultures through unnatural routes of exposure, any observed effect cannot reliably be traced to a single, isolated variable. The cause is inferred from the effect rather than demonstrated as a distinct and manipulable variable capable of producing the effect on its own.
The requirement for a purified agent to prove causation is not some arbitrary requirement—it dates back to the mid-19th century. Yet throughout the birth of the field, researchers routinely acknowledged their inability to achieve full purification free of confounding factors.
While defenders of virology argue that strict physical isolation is unnecessary or unreflective of biological research standards, evaluating that claim requires examining the record itself: the standards established at the birth of the field, the admissions made across decades of literature, and where the methodology stands today.
You may be surprised to learn that, despite unprecedented technological advances, virology still operates without this critical missing variable required to truly demonstrate causation. The fatal flaw remains unresolved.
What follows is an intensive examination of this problem, broken into six parts within this article.
Each part builds upon the last, tracing the historical development of the methodology, the attempts to establish the “virus” as an independent causal agent, and the problems that remain unsettled today.
It is a lengthy investigation, but one that requires time to fully examine and digest the evidence. By the end, you will be asking: where is the missing variable?
What follows is an extensive essay which would take up too much space, so you can read it here substack.com
Header image: CNRS News
Tom
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Knowing the true variable would mean an end to the fakeness of virology. The charade must go on. It’s that way for all of the modern stone age medical mafia. It is built upon lies, propaganda and FEAR.
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