The 14-Day Illusion: How a Statistical Trick Distorted the Vaccine Narrative

New study proves statistical manipulation of vaccinated vs unvaccinated data requiring a bottom up review of all statistical data from the Covid pandemic.

When Autoimmunity published Classification bias and impact of COVID-19 vaccination on all-cause mortality: the case of the Italian region Emilia-Romagna (Alessandria et al., 2025), it confirmed what independent researchers had been warning since the start of the pandemic. The public data on vaccine effectiveness and safety were shaped by statistical manipulations that reversed reality.

The paper exposes what it calls the “case-counting window bias” – the practice of classifying newly vaccinated individuals as “unvaccinated” for the first 14 to 21 days after injection. Any deaths or serious events during this window were therefore recorded against the unvaccinated group. This alone inflated mortality among the unvaccinated while producing an illusion of safety for the vaccinated.

In effect, those who died soon after vaccination were simply entered under the wrong category of the dataset.

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The new evidence

Using daily mortality and vaccination records for the entire Emilia-Romagna region during 2021, the researchers showed that each surge in first-dose administration was followed almost immediately by a spike in all-cause deaths among those still labelled unvaccinated. Statistical testing showed strong significance, with the 70-79 age group displaying the highest correlation.

Even when COVID-19 deaths – only around 9 per cent of total Italian mortality that year – were removed, the pattern persisted. The bias alone explained much of the apparent mortality gap between vaccinated and unvaccinated populations.

The same 14- to 21-day rule was used by UK and EU public-health bodies, meaning that this distortion affected the majority of global vaccine-efficacy claims.

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How the data were skewed

From early 2021 onwards, analyses documented how this bias formed part of a much wider pattern of distortion. We recognised this early and were networking the data in 2021. Few were reporting these data accurately, however, and those that were were effectively removed from the public narrative, banned on social media and classed as misinformationists. Some, were amongst the most respected medics and scientists in the world. The mainstream media repeatedly reported actual misinformation as factual, and upheld a fiction that is still being unravelled. To put it simply, we were right - from the start - and we tried to warn the population, whilst most of the population simply believed the lies that were coming from official sources.

The statistics available to us for analysis today mainly consist of unreliable and massively skewed official datasets that repeatedly misclassified and distorted the numbers from the outset. What should have amounted to a collective dataset worthy of further analysis to reveal the truth, appears designed from the beginning to prevent the truth ever becoming known. Sleight of hand tactics, bizarre classification parameters, and radically irrational data collection policies were in place from the outset. For example:

1. PCR manipulation – People were labelled “COVID-positive” on the basis of PCR tests run at unreported, often excessive, cycle thresholds, identifying trace fragments rather than active infection.

2. Cause-of-death distortion – Anyone dying within 28 days of a positive test was officially counted as a COVID death, regardless of actual cause. This is patently insane, yet it was reported seriously nightly by the media, and the masses appeared to believe it was reasonable. If there is one element in this whole sorry tale that shows how hypnotised and mass mind controlled the majority have become, it is surely this!

3. Vaccination-status distortion – Those who died within 14-21 days of vaccination were recorded as unvaccinated, inflating unvaccinated mortality and concealing post-vaccine events. This also a clear manipulation of the data by those who think the masses are so hypnotised, stupid or scared that the above point 2 was a successful message. If a majority of people can fall for that, then anything else is child’s play!

These mechanisms formed a self-confirming loop. The official statistics always reinforced the same narrative – that infection was universal, vaccination was salvation, and refusal placed others at risk. The data themselves became instruments of persuasion.

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The misuse of all-cause mortality

Later analysts, such as Denis Rancourt, used all-cause mortality trends to claim that there was no clear pandemic in 2020 but that mortality rose sharply after mass vaccination. The later rise is evident, but early data cannot be trusted either way. The statistical scaffolding was already compromised by PCR exaggeration, cause-of-death reclassification, and the vaccination-window bias.

No conclusion can be reliable until the methods creating those numbers are exposed and corrected. The Autoimmunity study demonstrates exactly how such correction must be approached.

Of course, nothing in this new analysis will surprise the many of us who have been following the data since 2021 and commenting on how the official statistics have skewed the reality to such extremes that they have become near to useless. History may yet show that the reality was antithetical to the propaganda, and only such studies will prove that. Otherwise, the history books will continue to state untruths such as the vaccinated fared better than the unvaccinated forevermore. The Covid pandemic thus has proved again, that those of us who follow the data and understand it are mislabelled and condemned as heretics, whilst the perpetrators of harms are embraced by the consensus viewpoint. This is par for the course. We live in a Huxwelled world.

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Manufactured consensus

These biases did not arise by accident. They served an explicit behavioural and political strategy aimed at increasing vaccination compliance. By generating the illusion that the unvaccinated were dying in greater numbers, public-health authorities and their pharmaceutical advisers created the statistical justification for mandates, censorship, and coercion.

Professionals who upheld evidence-based ethics were dismissed for non-compliance. The unvaccinated were portrayed as a social threat, while emerging evidence shows that early post-vaccination mortality was the very signal hidden from view.

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Conclusion

The study by Alessandria and colleagues stands as the first peer-reviewed confirmation of what independent researchers had already mapped in detail. The case-counting window bias explains the illusion of vaccine advantage and exposes the foundation of the official pandemic narrative as a construct of method rather than fact.

Correcting this bias is not an academic exercise. It is the prerequisite for rebuilding trust in public data and recognising the psychological operations that replaced science with compliance. Until that happens, the statistical record of the COVID era will remain a monument to manipulation, not measurement.

Further reading:

This paper will SHOCK the world: Unveiling hidden biases that inflated COVID-19 vaccine effectiveness and safety