The NOS reported on Friday: "In November 3500 more people died than normal". The actual scope could have been "6,000 dead, what did they die of?". Or for the Telegraph "Mysterious death wave plagues the Netherlands". However, at the NOS it was another attempt to blame the excess mortality fact-free on covid or unvaccinated people. In the end, of course, that does not match the total accounting. In the Netherlands, however, they don't calculate that far, so the NOS gets away with it for a while. Abroad they can calculate better, as we will see in a moment.
With the addition 'partly due to the coronavirus', NOS indicates that it has not bothered to subtract the number of corona deaths from the excess mortality. These are figures that they take from RIVM in their news every day, you would say that they not only have them but also trust and find them important.
It is also suggestive: "During previous corona waves, increased mortality was largely caused by Covid-19." The unsuspecting reader understands from this that this will now be the case again. That Corona anyway, what a terrible disease.
One sentence in the article gave me an idea: "Relatively speaking, excess mortality was highest in Limburg. […] in Friesland, excess mortality was relatively lowest.”
I did check whether that corresponded to the vaccination rate. Limburg has a vaccination rate of 83%, Friesland 80% (depending on the source, this varies slightly). It is, of course, a wafer-thin observation. 3% difference is too small to see these kinds of effects. On the other hand, the vaccination rate will and must increase a few percent with draconian coercive measures... Why then if it matters so little? Is it perhaps a threshold value above which all the virus suddenly disappears? Well no, that virus keeps going around. There are certainly many other factors in this specific case: the aging of Limburg will play a major role and perhaps also the average BMI or the number of inhabitants who live close together or have a close social life, who knows.
Link between vaccination coverage and Covid admissions
It did give me the idea to look at how mortality relates to vaccination coverage in each city. After all, those figures are available and the dataset is larger. This is another detour to find out something you could determine in an afternoon if the crucial data were shared: age-stratified data on vaccination status (incl. date), date of death and cause of death. Unfortunately, we are not allowed to know them in detail, while they could still exonerate the vaccines from the hefty excess mortality in one fell swoop.
De eerste exercitie was om te kijken wat de vaccinatiegraad voor invloed had op de ziekenhuisopnames. We zien dat de ziekenhuisopnames inderdaad dalen (hoog->laag) met het stijgen van de vaccinatiegraad (links->rechts).
We also see (even though there are few cities lower than 75%) that COVID hospitalizations are halved from 70% to 85% vaccination coverage. A higher degree than 85% no longer makes a significant difference. So it is a waste of energy and unnecessary polarization to want to achieve a vaccination rate higher than 85% under duress. There are also not that many municipalities below 80%, so it doesn't help nationally either.
Link between vaccination coverage and mortality
Then the vaccination rate compared to the mortality rates. Of course, mortality is highly dependent on, for example, the composition of the population. A rich small village with an abundance of retirees will have a high mortality rate (and a high vaccination rate). So actually nothing can be read from this graph. It could have been that there would have been a convincingly lower mortality rate with higher vaccination. However, for that you need a serious disease, which causes significant differences in mortality. That disease does not appear to exist.
The trend line is rising slightly: more vaccination goes hand in hand with slightly higher mortality. (When choosing a different type of trend line, this effect disappears). Correcting for the average age per city did not bring satisfactory solace either, strangely enough. Excess mortality per city would be a better parameter, but we couldn't find out.
With some better data, you could think this through in much more detail. We could take the data from Belgium, or from the UK. Studies have just been published in which something like this has happened.
European Journal of Epidemiology
In the States have compared countries and states and on a better level than the exploratory beer mat above. The main finding of this statistical analysis is:
Increases in COVID-19 infections are not related to vaccination rates
S. V. Subramanian&Akhil Kumar, European Journal of Epidemiology(2021)
From their interpretation after comparing 68 countries and 2947 counties in the US, I quote the paragraph in which they refer to the scientific "Umfeld" in which their observation fits:
Growing scientific evidence on the effectiveness of the vaccines in the real world:
For example, a report by the Ministry of Health in Israel reported that the effectiveness of 2 doses of the BNT162b2 (Pfizer-BioNTech) vaccine against preventing COVID-19 infection was 39%, significantly lower than the trial efficacy of 96%. It also emerges that the immunity derived from the Pfizer-BioNTech vaccine may not be as strong as the immunity obtained from recovery from the COVID-19 virus [8]. A substantial decrease in immunity from mRNA vaccines 6 months after immunization has also been reported. Although vaccinations protect individuals from severe hospitalization and death, the CDC reported a increase from 0.01 to 9% and 0 to 15.1% respectively (between January and May 2021) in the number of hospitalisations and deaths among the fully vaccinated.
Uncertain effectiveness of Covid-19 vaccination
(University of London)
The UK data is also used for calculations. This study (pre-print, looks credible) has been released in the UK. Two data analysts from the University of London come to staggering conclusions when they comb through the data. And actually, my graphs and findings above fit in wonderfully with that, no matter how clumsy.
Their summary and conclusions are recognizable and very worthwhile:
The accuracy of any data demonstrating the effectiveness or safety of the vaccine against a disease depends to a large extent on the accurate measurements of:
- people classified as suffering from the disease;
- vaccination status;
- death notification;
- the population of vaccinated and unvaccinated people (the so-called 'denominators').
If any of these points contain errors, claims of effectiveness or safety cannot be considered reliable.
The risk/benefit of Covid vaccines is best – and easiest – measured by the all-cause mortality of vaccinated against unvaccinated persons, because it avoids the thorny issue of what constitutes a Covid case/infection. In principle, the data in the ONS vaccine mortality surveillance reports should provide us with the necessary information to track this crucial comparison over time. However, until the most recent report [7], no data in age ranges was provided, meaning that all comparisons based on age were confused (older people are both disproportionately more likely to be vaccinated than younger people and disproportionately more likely to die).
The latest ONS report does provide some relevant data based on age categories. Specifically, it includes separate data for the 60-69, 70-79 and 80+ age groups, but there is only one group of data for the 10-59 age group.
At first glance, the data suggest that in each of the older age groups, all-cause mortality is lower in the vaccinated than in the unvaccinated. […]
Despite this apparent evidence to support the efficacy of the vaccine – at least for the older age groups – a closer look at these data calls into question this conclusion. That's because we've shown a series of fundamental inconsistencies and flaws in the data. specific:
- In each group, the non-Covid death rates in the three different categories of vaccinated people fluctuate in a volatile but consistent manner, far from the expected historical mortality rates.
- While the non-Covid death rate for the unvaccinated must be consistent with historical death rates (it may be slightly lower than the vaccinated non-Covid death rate), it is not only higher than the vaccinated death rate, but much higher than the historical mortality rate.
- In previous years, each of the groups 60-69, 70-79 and 80+ had death peaks at the same time during the year (including 2020 when they all experienced the Covid peak in April at the same time). Still, in 2021, every age group non-Covid mortality peaks for unvaccinated at a different time, namely the moment that vaccination programmes for those cohorts are reaching a peak.
- The spikes in Covid mortality data for the unvaccinated do not match the actual Covid wave.
Whatever the explanations for the observed data, it is clear that they are both unreliable and misleading. We considered the socio-demographic and behavioral differences between vaccinated and unvaccinated that have been proposed as possible explanations for the data anomalies, but found no evidence supporting any of these explanations. According to the occam razor The most likely explanations are:
- Systematic miscategorization of deaths between the different groups of unvaccinated and vaccinated.
- Deferred or non-notification of vaccinations.
- Systematic underestimation of the proportion of unvaccinated people.
- Improper population selection for Covid deaths.
With these considerations in mind, we have made adjustments to the ONS data and have shown that they lead to the conclusion that the vaccines not reduce all-cause mortality, but rather cause real spikes in mortality from all causes shortly after vaccination.
[...]
We believe that it is up to those who offer competing explanations for the data to explain how and why the data is the way it is. We explained that it is very unlikely that different social and ethnic factors can explain these strange differences in the ONS dataset. In the absence of another better explanation, Occam's razor would support our conclusions. In any case, the ONS data provide no reliable evidence that the vaccine reduces all-cause mortality.
In short: The vaccines are failing, the data look unreliable (at least in the UK but in the Netherlands RIVM does not excel in this either and we are simply not allowed to see them), there is no link between mortality and vaccination coverage and other research actually says so too.
Am I cherry picking? That could be, but statistical studies should never be able to produce such results, no matter how you look at it, should it? It's like someone sold you a container of boullion and when you taste a spoonful out of it, it tastes like sugar water. That should not be possible. That requires further research. The desired effect of the vaccines should be abundantly clear, especially in the face of such a risky action as the hastily developing and omonkable injection of a novelty, intended exclusively for use in emergency conditions, at the enormous cost that has been invested in it. The capital of government promises that has now been built up is asking for a collapse.
If the vaccinations have an effect at all, it seems that there is not so much less but in any case it does other people are dying. A meager harvest for so many pretensions.
The Eucalyptic Society is continued with the analysis where I stopped (they are biters, especially for those Akkermans you have to keep an eye on), with graphs that also show how the big cities distinguish themselves from the "countryside". Click on the chart to go to that article.
