As more and more questions are being asked by more and more scientists, health professionals and journalists, the narrative of “safe and effective” Covid-19 vaccines is crumbling by the day, and scientific truth is slowly beginning to impose itself.
It is not surprising that all those who promoted them are now desperately trying to cling on to their story. How? Well, let’s publish some models, as we have done since the inception of the whole Covid propaganda and hysteria. Who needs hard clinical data?
Another modeling study, comparable in its basic assumptions, algorithms and results to the one published in The Lancet a few weeks ago, is now claiming that the Covid vaccines have saved millions of people from death and hospitalization. This time it is in the US alone that – over roughly a two-year period (December 2020 to November 2022) – 3.2 million people would have died and 18.5 million would have needed in-patient treatment, had it not been for the Covid jabs.
Given that the annual death rate in the US was around 3.4 million in both 2020 and 2021, the model pretends to demonstrate that total mortality would have risen by around 50 percent without the vaccines. Five million people would have died in both 2021 and 2022, 2 million would have been counted as “Corona-deaths” (a rise of more than 500 percent compared to the “pandemic year” 2020), and Covid-19 would thus have become the absolutely predominant cause of death in the United States of America.
Which is to say that Covid-19 would by now have to be the absolutely predominant cause of death in the unvaccinated part of the population – and in countries with low vaccination rates.
Perhaps our distinguished modelers are so detached from clinical reality that they actually believe in this output, as absurd as it is.
Brownstone’s scientific and medical writers are not “anti-vaxxers.” We all recognize the historical and current benefits of immunization. Some of us still believe that there may be a place for Covid vaccines in the at-risk population.
Nor are we opposed to scientific progress – on the contrary. Most of us agree that mRNA technology holds great therapeutic promise. During my time at Merck & Co., I visited BioNTech in Mainz several times and then tried to convince my headquarter scientists of the interest of the company’s cancer vaccine programmes.
However, we all claim the right to think freely, and to ask for clinical evidence. We do not concede to the argument: “How can you assume that the FDA, the EMA, the peer-reviewed journals, the politicians, and the media all got it wrong?” We take the liberty to analyze the data, and to draw our rational conclusions. And we all remain open to any rational discussion of these conclusions.
One of my conclusions is that the Covid deaths are part of normal and inevitable population mortality which cannot be prevented by an immunization against one particular respiratory virus. If the vaccine clinical trials had demonstrated a mortality benefit, I would have been swayed in this conclusion – and Fitzpatrick et al. would have had a credible fundamental input for their population model.
However, the endpoints in all the clinical Covid-19 vaccine trials were common cold and flu symptoms, plus a positive test.
My conclusions from the available trial data (as per the publications and FDA submissions documents) are the following:
- The observed reductions in test-positivity for the SARS-CoV-2 virus (the “95 percent efficacy”) in people presenting with a common cold or flu are an interesting biological result – if they are real (The numbers are small, and clinical reality appears to not confirm this result).
- Clinically, people were much sicker (altogether more common cold and flu symptoms) in the vaccine than in the placebo groups.
- No conclusions can be drawn for severe forms of pneumonia and mortality.
- As Covid-19 is a disease with non-specific symptoms, the pivotal trial endpoint would have to be all-cause pneumonias and all-cause mortality, in order to gauge any intervention’s clinical benefit (or harm).
Any public health model needs good and credible clinical and epidemiological data for its input and algorithms. For the Covid-19 vaccines, good and credible data demonstrating a prevention of severe pneumonia, hospitalization, and death do not exist. My conclusion from the clinic and the epidemiology is that they cannot exist.
It is therefore not surprising that published models yield absurd results. Unfortunately, it is no longer surprising either that these absurd results are being swallowed and regurgitated by medical journals and the media, by politicians and agencies.
It may be a long struggle, but the scientific truth will prevail in the end.