COVID-19 VACCINES: A STATISTICAL ILLUSION THEIR EFFECTIVENESS! LET'S SEE WHY.
After all we are seeing today what is happening ...
We had already talked about statistical bias in the studies on anticovid-19 vaccines and specifically about the difference between relative and absolute value of mRNA vaccines in this article:
Today we see some other tricks of the "science" to pass the FDA-EMA-AIFA (paid in turn by the pharmaceutical companies themselves) for some experimental drugs.
Is vaccine efficacy a statistical illusion?
To assess the risk / benefit of a vaccine for treating a disease, such as covid-19, we can periodically compare the all-cause mortality rate of vaccinated versus unvaccinated people. If the death rate for vaccinated is consistently lower than for unvaccinated, then we could conclude that the vaccine must be beneficial.
Meanwhile, in 2021, the year in which 7 billion doses of experimental vaccines were administered at the time of writing, throughout the Western world we are witnessing a clearly out of scale and "inexplicable" dying of the population over 14 years ...
Vaccination with placebo (reasoning by absurdity that in mathematics it is a way to prove that the opposite of what we want to prove is true)
Imagine a placebo rather than a vaccine being rapidly distributed to a population of one million people of similar age and health. Suppose the weekly death rate NOT attributed to COVID-19 disease for this population is 15 deaths per 100.000 (100k), so we would expect around 150 in a million individuals to die in any given week. Since placebo doesn't change anything by definition, mortality rates for both vaccinated and unvaccinated would average the same all-cause mortality - 15 per 100k, week-to-week. So, on average, what we should observe - while the "vaccination" schedule extends to the majority of the population - is shown in the Table below. Note that the “placebo” vaccine launch program is being implemented at an increasing rate and the cumulative percentage of the “vaccinated” population rises to 98% within 12 weeks.
Table 1 Distribution of the placebo "vaccine". No observed difference in mortality rates (no population growth and total population each week reduced from the previous week's deaths)
Cumulative vaccinated in percent
|Dead||Population||Mortality rate||Dead||Population||Mortality rates|
Now suppose there is a one week delay in reporting deaths. Such delays are routine in statistical reporting of mortality and vaccine data. So the data reported by the authorities are different from reality, let's report them in Table 2, which is the same as Table 1 but where the total deaths are simply "shifted" by one week.
TABLE 2: Report of deaths delayed by one week
|Week||Population||Cumulative vaccinated in percent||Dead||Population||Mortality rate||Dead||Population||mortality rate|
GENTLEMEN, NO TRICKS NO DECEPTION!
Now suppose we want to examine and compare the mortality rates of the unvaccinated and vaccinated cohorts based on the data in Table 2 and not Table 1 as would be correct. Figure 1 shows this comparison and we can see that the mortality rate is consistently lower for vaccinated than for unvaccinated during the roll out of the vaccination schedule and decreases as vaccination approaches population saturation close to 100%.
WHICH IS EXACTLY WHAT (NOT LINEARLY LIKE IN THE EXAMPLE) HAS HAPPENED IN ITALY AND IN THE WORLD, MAKING EXTRAORDINARY POLITICIANS AND COMMISSIONERS EXULT AS WELL AS THE VIROLOGISTS FROM THE SALON AND EVEN EJACULATE THE JOURNALISTS OF THE UNIFIED TELEVISION NETWORKS AND THE NEWSPAPERS ...
Doesn't it look like one of those graphs that show you on TV? Yet it is purely theoretical and think if the data recording shift were larger ... In our naivety we could conclude that the unvaccinated seem to suffer from much higher mortality levels than the vaccinated. The delay in reporting therefore creates a completely artificial impression that the vaccine is highly effective. Indeed, it looks like a miracle magic drug "Cure everything"! Even stupidity!
The fact that the death rate of the unvaccinated peaks when the percentage of vaccinated reaches the inflection of the curve should sound like a wake-up call and let any statistician know that something strange is going on (unless there are independent evidence that the disease is peaking at the same time).
ONS data on Covid-19 vaccination
While the placebo vaccine example was purely hypothetical, Figure 2 shows vaccinated mortality versus unvaccinated mortality using data from the latest ONS England Mortality Report by Covid-19 vaccination status (weeks 1 to 38) , supplemented by data from the NIMS vaccination survey (up to week 27 only). I show non-covid mortality to remove disease influence. I use the English data because I believe the Italian data manipulated as in total contrast with other countries (at least until a few days ago, today is November 16, 2021).
Note that we see the same IDENTICAL characteristics of the graph in Figure 1. In other words, a perfectly reasonable explanation for what is observed could be that there is no difference in mortality rates between vaccinated and unvaccinated and the differences in mortality are simply a result of a delay in registration of death. Furthermore, since we have removed the deaths from covid (which were only a small percentage of deaths from all causes in the data reported, in mathematics they are referred to as infinitesimal of lower order) we obtain an almost identical result for non-covid mortality to what it would turn out if the vaccine were a placebo! Therefore, it appears that we have created a statistical illusion of the vaccine's effectiveness that we could sell as "science".
If this is not a statistical illusion, how is it possible for the unvaccinated to die from non-covid causes at a higher rate than the vaccinated? Furthermore, how is it possible that, by the time vaccination rates have increased to nearly 100% of the population, the unvaccinated die from non-covid deaths at nearly double the rates of those who are vaccinated?
These same patterns are also observable in the 70-79 and 80+ age groups (with peaks in mortality for the unvaccinated appearing at different weeks because these age groups received vaccinations before the 60-69 age group between November and December. 2020). This strongly suggests that what we are seeing is a genuine statistical illusion inexplicable by any real impact of the vaccine on mortality rates. There could, of course, be reasons other than simple delays in reporting deaths or misclassification. For example, any systematic underestimation of the actual percentage of those who remain unvaccinated would lead to a higher mortality rate for the unvaccinated than for the vaccinated, even if the mortality rates were the same in each category.
LET'S SIMULATE NOW THAT THE PLACEBO VACCINE MAY HAVE SIDE EFFECTS ...
Let's see and shiver ...
It is also important to note that even if the actual death rate for the vaccinated were higher than for the unvaccinated, where the vaccine was causing death as a side effect, we would likely observe the same illusion.
To see this effect, let's revisit our placebo vaccine example and make a small modification to Table 1 where instead of a 15 per 100k death rate for the vaccinated, let's assume it's 17 per 100k (an increase in mortality of about 13k). %). Thus, the placebo vaccine is killing an additional two in every 100.000 people and has no mortality benefit. In this scenario the reported mortality rate for the "deadly placebo" is compared with the first "placebo" scenario, in Figure 3. Here too we see the illusion that the death rate for vaccinated is lower than for unvaccinated . Both scenarios are the opposite of reality and both seem interchangeable. This means that the ability to detect a vaccine side effect signal is nearly impossible and instead creates the illusion of vaccine efficacy.
COMPARISON FIGURE 1 (HYPOTHESIS OF ZERO SIDE EFFECTS) AND FIGURE 4 (HYPOTHESIS OF HEAVY SIDE EFFECTS OF PLACEBUS)
The illusion of a decrease in the effectiveness of the vaccine
Finally, it is important to note that the same statistical illusion applies to all vaccine efficacy measures, be they cases, hospitalizations or deaths. Indeed, replacing the number of deaths in Table 1 with the number of cases, with a reporting delay of one week, would result in vaccine efficacy rates as shown in Figure 5.
This occurs when the actual efficacy of the placebo vaccine for cases is zero. This, however, "coincidentally" corresponds to the 4-6 months of effectiveness that today the living room virologists tell us on all the state TVs with unified networks, pushing the population to a (evidently) more than probable USELESS BOOSTER
This reporting bias is a type of bias that could be called "Reporting lag censoring", a phenomenon whereby structural or process factors systematically interfere with the management and reporting of data with the consequent effect that they are then misinterpreted, leading to erroneous conclusions.
ORIGINAL ANONYMOUS REFERENCE: https://probabilityandlaw.blogspot.com/2021/11/is-vaccine-efficacy-statistical-illusion.html