H0SARS-CoV-2 was nasty, but not unusually so, and certainly not particularly novel. The cure was worse than the disease. It is difficult to bottle up truths forever, and it will be instructive to see whether this hypothesis is still in the running when it comes to writing the definitive history of the Covid epoch.
The disappointment from Covidean doom-mongers about the recent – and entirely expected – downtick in cases of respiratory disease has been palpable, presumably because this has happened without recourse to ‘clever’ public health interventions.
Risk is notoriously difficult to communicate effectively. It is especially hard when referring to an emotive subject like the risk of dying as the emotional response prevents rational interpretation of complex numbers. To simplify understanding of the benefits of interventions the number of people who need to be treated to prevent a death can be measured, the number needed to treat (or “NNT”). The same
Authorities continue to claim that vaccination provides 80% protection from covid death. The data that these calculations are based on are measured in sample populations subject to different biases.
Covid and influenza appear to have a reciprocal relationship. When a covid wave occurs influenza disappears and when covid recedes influenza returns. The fear of having to cope with covid and influenza at the same time over winter as warned in a report from Imperial this time last year, was not valid.
The ONS have released the latest update on their data for deaths by vaccination status. Superficially it appears to show residual protection against death in the vaccinated but only a little digging reveals that there is likely hidden information that could turn that observation on its head.
Imperial College has produced a new fantasy number to test people’s gullibility. This time they are claiming that 19.8 million lives have been saved by vaccination.
Imperial College now have a global reputation for making provable wrong claims based on modelling and they appear to want to bolster that reputation.
Whether this is Omicron or cross reactivity with previously endemic coronaviruses is uncertain. What is clear from the Ct values in the ONS Infection Survey is that neither “non-pharmaceutical interventions” or vaccines have had any impact on waves of infectious SARS-CoV-2 carriers and that neither economically destructive lockdowns or mandating experimental vaccines should ever have been attempted.
The ONS have published their survey data on the number of working aged people who are economically inactive. The levels are higher than in the past and many commentators were quick to blame the rise on long covid. It is worth looking a little more closely before jumping to that conclusion.
Last week we published Part 2 of our evidence updates, focusing on ethics, masks and elderly care. This week, we take another detailed look at the collateral damage caused by lockdowns and rather topically have reworked the piece on covid vaccines for children.
In December 2021 Norman Fenton, Martin Neil, Clare Craig, Josh Geutzkow, Joel Smalley, Scott McLachlan and Jonathan Engler published an article casting doubt on the vaccine efficacy implied by the UK’s official mortality statistics as they related to vaccination status, raising miscategorisation of vaccinated deaths soon after injection as unvaccinated as a possible significant factor.
It is over two years since the first lockdown and now more than a year since HART published its paper COVID-19: an overview of the evidence. We asked all the original authors to go back and review their article and update with relevant publications, revising their conclusions as appropriate.
There have been marked differences between the covid trajectories in Eastern and Western Europe; in particular Spring 2020, Spring 2021 and Autumn 2021 showed markedly different death rates (from covid).
This paper, published in the “peer-reviewed” Canadian Medical Association Journal, quite simply represents an amoral, unethical and utterly transparent attempt to use pseudoscientific modelling to fabricate a false narrative.