By Ted Belman and Peloni
I recently posted
The latest figures published by the new UK Health Security Agency on Covid-19 cases, hospitalisations and deaths show that the vaccinated population still accounted for 4 in every 5 Covid-19 deaths over the past four weeks even though those who are deemed to be the most vulnerable to Covid-19 received their “booster” jab in September and October.
Then in a day or two, regretted having done so. Nothing in the article supports the conclusions in the title or the first paragraph.
Its is wrong to compare the deaths among the vaccinated to the deaths among the non vaccinated. The only question is did the vaccinations reduce the number of deaths among the group vaccinated. He begs this issue. He omits to say that the vaccinated people are the most vulnerable to begin with.
In effect we learn nothing about their value.
Focusing on the non vaccinated group, if their death rates is so low without vaccination, why bother.
My daughter posed the right question:
What is the rate of death of unvaccinated vs fully vaccinated 80 year olds.
But that is not the only question that should underline policy. Assuming the vaccinations and other policies reduces the number of deaths, is the reduction worth all the policies implemented to achieve it. There must be a cost/ benefit analysis. The benefit would be the saved lives. The cost would be the diminution of rights, the adverse effects of the vaccines long term and the cost to the country in dollars to achieve it. That’s for the people to decide by a vote. It is not for the elite to decide.
I asked Peloni, our most prolific, knowledgeable and intelligent reader to comment on my comment. He essentially agreed.
Regarding the Expose author’s claim, their analysis and observations are completely useless.
Raw data is not useful for anything. I thought we should be well past such games. As I alluded to somewhere on this thread, you have to categorize data by age, normalized per 100K and for population growth to make a comparison relevant. Beyond their partisan statements of advocacy against the vaccine, the entire article is falsely based and useless to discuss. Such tribal advocacy is not beneficial to anyone. Indeed, such echo-chamber clatter should be expunged from this debate, altogether. These are serious matters which require a serious consideration of all sides of reality and we should always be wary of trusting our source without looking at the data they base their findings upon. As we move forward thru this maze of data and science, much of which is a new realm of knowledge to many, we have to be savvy enough and nimble of mind enough to recognize and parse reality from theatre. I highly applaud your efforts and those of your daughter to recognize and describe this article as you have and to keep this conversation an honest one.
With this in mind, let us draw our attention to the data itself. You have to trust the data for any calculations derived from it. So, should we find a flaw, a serious systematic overwhelming flaw, built within the data, it might cause us to understand why what we are seeing is not responsive to the conclusions of research based on such data.
Over the past couple of weeks, I have shared, a report(https://www.researchgate.net/publication/356756711_Latest_statistics_on_England_mortality_data_suggest_systematic_mis-categorisation_of_vaccine_status_and_uncertain_effectiveness_of_Covid-19_vaccination) on the ONS data and its revelations are quite concerning. The authors are taking a great risk to their careers by signing their names to it. Indeed, it is stated clearly that many who aided in preparing this report refused to sign their names to it for this very reason.
The authors received a copy of the ONS data newly separated into categories of 0-59, 60-69, 70-79 and 80+ with the intent of analyzing the data. The 0-59 category is too broad to be useful, though they have some details shared in the report on this group. So let us look at what they discovered.
Historically, including in 2020, mortality has been seen to peak at consistent time intervals thru the year. The vaccine rollout seems to have changed this. We know of the vaccine safety issues, and the elderly have a disproportionate number of vaccine adverse effects, so this is not surprising. Supporting this conclusion, when analyzing the data, they found that the increases in death actually occurred in a staggered pattern associated with the vaccine rollout in 2021. The peak in deaths, however, were occurring in the unvaccinated, coincident with the vaccine rollout in each age group. Restated, the unvaccinated were exhibiting alarming increases in deaths as the vaccines were administered to their coevalists. This defies reason, but it is worse than this.
The different age groups between 60-69, 70-79, 80+ were exibing this phenomena at different times, as the vaccines were administered. Hence it is not a natural occurrence occurring simultaneously which would strike people regardless of their age at a single or multiple intervals, rather than as coordinated with the vaccines being applied to the respectively different age groups.
Additionally, when compared to the lifetables of expected deaths, it is clearly evident that the vaccinated have a lower than expected level of death while the vaccinated have a double the expected level of death, for each age set. To exacerbate this finding, this unbelievable protection by the vaccines seems to hold true among the non-Covid all cause mortality. As the authors note:
By simple comparison with lifetable values, the vaccinated appear to suffer less mortality than we would expect them to (and this is during a period of expected higher seasonal mortality) and vice versa for the unvaccinated. This is very odd.
All of this makes sense if the vaccinated deaths are mis-categorized as unvaccinated. Perhaps there is another reason for both these and other anomalies in the data, but the data is clearly not consistent with reason unless the vaccine are providing a regenerative effect to their recipients. What we do know is that, as the authors close with, :
In, any event the ONS data provide no reliable evidence that the vaccine reduces all-cause mortality.
The analysis is much more rewarding than this very brief summary in which I have ignored a great deal of detail which they provide and explain in easy language, clearly intelligible and intended for the general public.
This is the data on which the studies your daughter shared is based. The data, for whatever reason, is “unreliable and misleading” as McNeil and associates state. So, this is the reason I have come to re-qualify the input of the English data, with which I had, til recently, been quite impressed with the level of detail they offered.
It would be truly amazing given the anomalies in the data if any study based on this data could do anything other than provide a certainty of vaccine efficacy. I strongly suggest everyone read this report who finds merit in the data. We are being lied to, for whatever reason, or perhaps there is no intent complicit in this managed stagecraft supporting the govt narrative when the govt is collecting, preparing and reporting the data.
In either case, you can’t base good conclusions on bad, seriously flawed data. Otherwise, you wind up basing conclusions on things as badly flawed as this Expose report.
@Adam
This was an overstatement and forgive the absolute nature of the comment. It is true that raw data is not useful for anything when comparing two populations sets as it was being imployed, and this is what should have been stated.
It is not uninformative to look at the full breadth of the raw data. As I stated some months ago, no one should be dying from a vaccine due to safety and no one should be dying from a vaccine if it is 95% effective, not by the hundreds, not by the thousands, and certainly not by the tens of thousands. So in this context, considering the numbers of thousands dying following vaccination, from the vaccine and the virus both, it is a fair line of conversation and analysis. This is a valid purpose for raw data.
However, when you look at two populations, say Texas and New Jersey, you will see that Texas has 75,494 deaths as compared to New Jersey which has 28,730 deaths. These raw numbers reveal a real disparity. These numbers are not remotely equivalent or close to equivalent. Yet, New Jersey holds one of the highest death rates of any single state and only 8 nations in the world hold a higher death rate. There are many tricks of data collection and data analysis that can be used to mislead people, even informed people, towards making false conclusions based on false assumptions. This doesn’t even require an intent of malice, as such mistakes are rather easy pot-holes in which to fall. This is one of the key purposes for the use of peer review of all scientific literature, to weed out such mistakes.
For instance, Texas has 75,494 deaths, but only 2,604/million, while New Jersey has 28,730 deaths, but 3,235/million. It is not improper to look at the raw data and I do not suggest it should be hidden from view, or knowledge, or discussion. It just can’t be used to compare as relavent between populations where the size of the two populations being compared vary in size. The disadvantage drawn between this sort of comparison will grow as the distinction between the population sizes increases.
I do appreciate your reluctance to trust data manipulation as hiding significant realities, but you have to make comparisons based on normalization, otherwise the path you choose will be just as likely to be towards New Jersey as towards Texas. Trust me, nobody wants to wind up like New Jersey.
You have to relate things on a even playing field so that a fair assessment can be reached. The cases/100K was listed in a later table from the same source the author found Table 8. I do not know who wrote this article or their background or understanding on these matters, but this is a common mistake made to show how ineffective the vaccines are, which they are, but comparing raw numbers did not prove anything other than the fact that, well, the author was standing in a pothole when he chose to make a comparison between the two populations.
The vaccines have failed in every way possible to protect the world from this disease and they have caused a great deal of suffering and death by themselves. But words of protestation based on flawed comparisons generate a straw man that only disadvantages the author’s argument instead of pursuing better grounds for his arguments than those he chose. There are good arguments to be made. He just didn’t make them.
I find nothing “incendiary” or “misleading” about the Expose report. And I don’t agree with Peloni that “raw data” is “misleading.”
“Raw data” gives us genuine facts, while “adjusted” data gives us the interpretation of those facts by someone with an agenda. I would prefer to see the “raw” facts rather than someone’s interpretation of what they “really” mean.
If Expose’s facts are accurate that within a certain time period of time, most deaths in England attributed to Covid were in “fully vaccinated” people, there is nothing “incendiary” about reporting this fact. Repressive governments always argue that revealing the facts that tend to discredit government policies are “incendiary.” They do not want people to know that thir policies have failed or that the their results have been other than what the government promised they would be. So they attributed these inconvenient facts to “incendiary” rabble-rousers.
If it is true that within a recent period of time, the majority of people who died of Covid19-2 in England were fully vaccinated, that is evidence, although perhaps not absolute proof, that the vaccinations have failed as a means of protecting the public from this disease.
In Vietnam, after 4 children died following vaccination and 120 children were hospitalized, the vaccines involved were seen to have had their expiration date “extended”. The deaths have been reported by the National Health Ministry to be related to an “overreaction to the vaccines… not linked to the quality of the vaccine process”. The official newspaper referred to these side effects as being due to hysteria These “extended” batches of vaccines were placed in a freezer to be used on adults at a later date(what??). The official narrative claims that the children were undergoing a chain reaction of hysteria at seeing other children faint following injection. This narrative does not explain why 2 children were transferred from a regional hospital to a provintial hospital due to convulsive symptoms. Meanwhile the official claim is that the vaccines are not halted but it has been reported that child vaccination has actually been “paused”.
There is an article in the Wall Street Journal that everyone concerned about the Covid19 epidemic should read. It is titled “Covid’s Secret Toll: Other Patients.” Author Anna Wilde Mathews. Begins on front page and then continues in a full two-page spread inside. A long read, but a very important one. It describes the experiences of a primary care physician named Christine Hancock in treating her huge number of patients (0ver 1,900) in a medium size city in the state of Washington.
But Dr. Hancock actually had to treat few cases of Covid. Instead,what she experienced was a marked increase in non-Covid but serious illnesses in her patients, Her city, Bellingham, was one of the first to report in the nationthat the epidemic was spreading rapidly through the population. The press in Washington state gave a lot of attention to the epidemic, and public officials expressed great alarm.
But Dr. Hancock’s total case load was much higher than in 2020 or in previous years. Most of the illnesses, she traced to the physical effects of severe panic and anxiety created by the massive scare stories about Covid circulated by the U.S. government and the press-not by the virus itself.
Among her patients, there was a marked increase in substance abuse, including but not limited to heroin addiction. Dr. Hancock believes that this massive increase in substance abuse was caused mainly by the terror that so many people, especially the elderly and the critically ill. People could not cope with the severe anxiety and depression created by the Covid hysteria, and turned to “self-medicating.” This caused a rapid decline in their health.
A lockdown forced many people to remain in their homes for long periods of time. Especially among elderly people who lived alone, this isolation and the terrible loneliness it generated, made many people very depressed, which harmed their health.
There was a major increase not only in substance abuse but in heart disease, which Dr. Handcock attributed to severe, prolonged anxiety and depression, which can affect the heart.
And there was an increase in people suffering from severe pschiatric illnesses requiring hospitalization, such as schizophrenia. The condition of people who had been suffering from severe mental illness before the Covid panic got worse, and more acute. Many reacted by stopping the use of their medications. which had previously controlled their illnesses. But when Dr. Hancock tried to have some of these patients hospitalized, she was told that the psychiatric wards of hospitals were overwhelmed with patients, and had no beds for her patients. So they remained in their homes or roamed the streets aimlessly.
Another source of the increase in non-Covid illnesses was the orders given to doctors, including Dr. Hancock, not to see patients in person, but only by telehealth. This meant that many illnesses that require physical examination to be detected went undiagnosed. It also meant that many patients were forced to miss “routine” blood tests and other medical tests that were needed to screen for serious illnesses or monitor their pre-existing conditions. This lack of screening and regular check-ups caused many people with chronic illnesses to become dangerously ill and even near death.
Bcause of the Covid crisis, many hospitals and clinics declined to perform so-called “elective” surgeries of months. But some of these sugerical procedures were not “elective,” but rather were procedures that were urgently needed to save the patient.
Many of the doctors and nurses in Dr. Hancock’s city of Bellingham quit, citing “burn-out” caused by the Covid crisis. Dr. Hancock’s clinic became seriously understaffed, placing an added burden of the few remaining providers, such as Dr. Hancock.
Th closure of schools meant that many mothers were forced to home-school their children and remain at home most of the time, which caused many to suffer depression and its adverse health impacts. The children, denied mental stimulation, recreation and contact with other children, also frequently became extremely depressed and engaged in “acting out” behavior, or even suffered from psychiatric illnesses.
In order to finance Covid treatments, the government severely cut back funding for psychiatric and psychological illnesses. Many clinics were forced to discharge their psychiatric social workers and psychiatrists, which denied people access to counseling when they most needed it.
Dr. Hancock lost only three patients among the 1,900 plus that she treated in 2020. None died of Covid. In 2021, she lost nine patients, again none of them suffering from Covid. This was a “threefold increase” in deaths. Still, given her huge number of patients, this suggests that the over-all death rate in her city was very low, and the death rate from Covid lower still.
If Bellingham in Washington state is representative of effects of the alleged Covid pandemic in most communities throughout the “developed” world. which I believe to be very possible, than the “pandemic” is essentially a cruel hoax. It may well be that few people have died of Covid19-2, but vast numbers of people have died from stress-related illnesses caused by the government-generated Covid hysteria.