1.Our research team have now analysed the ONS England November mortality data. We conclude that despite seeming evidence to support vaccine effectiveness this conclusion is doubtful because of a range of serious inconsistencies and anomalies.
2.The data appear to show lower non-Covid mortality for the vaccinated compared to the unvaccinated. Odd. Also unvaccinated mortality rates peak at the same time as the vaccine rollout peaks for the age group, then falls and closes in on the vaccinated. This is not natural
3. Consider what we are witnessing here. We have a vaccine whose recipients are suffering fewer non-covid deaths and hence are benefitting from improved mortality. And the mortality rates look to differ significantly from historical norms, as evidenced in mortality lifetables.
4.Correlating unvaccinated mortality with vaccine roll out we see curious patterns (dotted line the proportion of people getting first and second doses). Why are the unvaccinated dying after NOT getting the 1st dose? Why are the single dosed dying after NOT getting the 2nd dose?
5.Plenty of evidence that the vaccinated who die within 14 days of vaccination may be categorized as unvaccinated. Then someone who dies within 14 days of first dose is miscategorised as unvaccinated and a similar thing could occur post second dose.
6. Miscategorization might explain odd phenomena in ONS mortality. To correct the error we can take the difference between the expected mortality for the unvaccinated and the data, and re-allocate this unexpected excess mortality to the vaccinated to get new ADJUSTED estimates.
7. The early spikes in mortality that appear to occur soon after vaccination may be caused by the infirm, moribund, and severely ill receiving vaccination in priority order and thus simply appearing to hasten deaths that might otherwise have occurred later in the year.
8.Turning to Covid mortality, at face value, there appears to be clear evidence of vaccine effectiveness. But……..
9.After vaccination people endure weakened immune response for a period of up to 28 days and may be in danger of infection from Covid or other infectious agent at any time in that period. It therefore makes sense to examine infection date rather than date of death registration.
10.We adjust for this using a temporal offset and see a large spike in mortality for all age groups during the early weeks, when covid prevalence was high, and when the first dose vaccination rollout peaked.
11.After our offset adjustment we observe no significant benefit of the vaccines in the short term. They appear to expose people to an increased mortality, in line with what we know about immune exposure or pre-infection risks,
12.Whatever the explanations for the observed data, it is clear that the ONS data is both unreliable and misleading.
Absent any better explanation Occam’s razor would support our conclusions. The ONS data provide no reliable evidence that the vaccines reduce all-cause mortality.
Y axis is mortality = deaths per 100,000 of population.
This is the latest of numerous attempt to decode ONS hieroglyphs, but now we may have stumbled upon a rosetta stone to help solve the puzzle.
1/ A friend asked me what I thought about the new AI system called Perplexity. I was eager to test it out
- Would it tell the truth about the Covid-19 event?
- Would it use credible sources?
- Would it stick to the narrative or cite other causal explanations?
.@perplexity_ai
2/ So, I thought I should try it out, just to see how misinformed I could become using this new AI. I started off with some simple, yet probing, questions about the covid-19 event.
3/ It's answers were incredibly accurate, and more importantly it is ‘aware’ of what actually happened. It also isn’t shy about finding and using sources that support honest explanations.
A thorough review of the available evidence suggests that the emergence of a novel engineered virus is the least likely explanation for the event known as the ‘covid pandemic’.
1 / The discovery of ‘novel’ viruses is a function of how determined we are to find them. The attribution of novelty to a virus is as much the result of a politicised process rather than something based on an objective analysis of its properties.
2 / The features of SARS-CoV-2 do not appear to be as ‘special’ or ‘unique’ as claimed.
There is no good evidence that the many and complex hurdles in front of deliberately engineering viruses to become more pathogenic or transmissible in humans have been overcome.
1. Without PCR testing data mortality and morbidity would not be attributable to the novel virus and if this attribution is false there must therefore be other explanations for the ‘pandemic’.
.@Jikkyleaks .@Kevin_McKernan
2. Whilst scandals about PCR testing are well known a materially important aspect of PCR testing has been given scant attention and that is cross reactivity (or crosstalk). This is where other viruses, such as common colds or flus etc., trigger a false positive PCR result.
3. We analysed the very few studies that used blind samples of colds or flu viruses to undertake ‘mystery shopper’ testing of laboratories using PCR.
In these studies, we found strong evidence for up to 25% cross reactivity between other competing viruses and the PCR tests.
1. How did antibiotics use change during the Covid-19 'pandemic'?
And what happened to the stockpiles of antibiotics Fauci said were needed?
In our latest article we pulled together material on policy changes on antibiotic use during the 'pandemic'.
2. Antibiotics are essential in a pandemic. This view is motivated by the fact that in his 2008 article in the Journal of Infectious Diseases (which reported on autopsies of well-preserved victims of the Spanish Flu pandemic), Anthony Fauci concluded that:
3. Despite this UK NICE guidance NG165, on managing suspected or confirmed pneumonia, explicitly forbade the use of antibiotics in Covid-19 cases:
1. Did flu vanish or was there a failure to search for it?
There has been a collective and systemic failure in flu surveillance and flu death reporting systems in the UK during 2020 and into 2021.
2. The UK FluDetector system, which uses machine learning to track flu using Google Trends data, reported that flu disappeared in 2020/21. This is contradicted by Google’s own data and UKHSA reports, both of which report a clear signal for flu in the UK in 2020/21.
3. The UK FluSurvey system tracked flu incidence only until week 20 of 2020 and never updated this data. They then abandoned flu tracking until January 2021 when they announced that the flu season had now restarted, after supposedly witnessing the near eradication of flu.
Quarantines were sold as measures to reduce spread of SARS-CoV-2 and are claimed to have prevented the spread of flu.
But what if there is another explanation.......
1. Flu tests are recommended to be administered within 4 days of symptom onset. If they are administered after 4 days, they would likely produce a false negative result for someone with flu (flu tests are rarely administered routinely anyway).
2. Mandatory Covid-19 tests, run at high cycle thresholds and suffering from cross-reactivity with other pathogens (amongst other operational issues), may well have resulted in false positives for Covid-19, when in fact the pathogen causing symptoms may have been flu.