Out mortality is with vaccinates!

A further analysis of the death rates after vaccination brings a remarkable conclusion: the overdirts are precisely with the vaccinates. Whether there is subsequent "left" for unvaccinated people is uncertain.

TheNivel published a research report on 2 September 2024About the cause of excess mortality during the COVID-19 Pandemie, which contains an opposite and controversial conclusion:

Under-mortality among COVID-19 vaccinated and excess mortality among unvaccinated people

Nivel signals remarkable figures. In the first 3 months after vaccination, there would be up to 45% less death and up to 10 times higher mortality among the unsaved parties. Remarkable. The study ends 12 months after the first vaccination. The excess after that time was not investigated. We will show that the excess with vaccinates 71-81 years old is around 15% since the second half of 2022. We use the same CIMS data!

The Nivel Study is still cited in Politics The Hague as "evidence" for the safety of the vaccines. But what does Pfizer say about that?

What Pfizer says

Many studies have been done into the safety of the vaccines, but none of them showed that non-vaccination was accompanied by an increased risk for unvaccinated people to die due to non-vaccination. It would also have been a strange conclusion of that research: the placebo group wouldsuddenlyDie much more often than the treated group.

Onestudy of pfizerShowed that 17 unvaccinals died within the randomized group and 21 vaccinates (all causes). Enciddees therefore died almost 25% more often than unnumptions, but that difference was too small to be significant. So there was no reason to expect a difference in death in follow-up studies, certainly not if it were about a higher risk of death after non-vaccination.

What Nivel says

Nivel, on the other hand, states in her report that the mortality among unvaccinated people in the first 3 months after vaccination was up to 10 times as high as among vaccinates. See this table that plays a central role in this. For example, look at the group 76 to 80 years. In the "vaccinated" column we see 0.55% death for the first 3 months and with "unaccinated" that is 5.03%. So that is more than 9 times as high. At 81+ it is even more than 10 times as high.

After criticizing the report and improving calculation errors (signaled by, among others.Maurice de Hond) The figures were adjusted, but the conclusions remained intact. Despite the findings of Pfizer itself.

How does this research work?

About 12 million Dutch people have been vaccinated, of which around 700,000 vaccinates were followed within this study. Each vaccinated was administratively linked to a similar person whonothas vaccinated. Subsequently, it was counted how often a vaccine person died in comparison to an unvaccinated person. Intermediate counts were done after 3 and 12 months and formed the basis for the conclusion: overdiction only for unvaccinated people.

The question then is whether the group that was not vaccinated is comparable to the group that was vaccinated. NIVEL states that although there may be a difference in composition, this will have had little influence on the final conclusion: overdolution for unvaccinated people, underpainted by vaccinates. Remarkable, because Pfizer noted that there would be no significant difference in the risk of death. Vaccinated people would have a higher risk of death, although the difference was too small to be significant.

Master and Jacobs

Master & Jacobshave done its own research based on the mortality and vaccination figures ofallDutch. The basic principle was the same as with NIVEL: an vaccinated person was administratively linked to an unvaccinated person and the deaths were analyzed. The required data came from the same source: the CIMS database. The numerical findings should therefore be comparable and that appears to be the case.

A big difference, however, there were only 2 reference moments (3 and 12 months) with Nivel, while the research of Master analyzed the deaths per day. This creates a much more detailed image and gives more insight. Here we will suffice with a single graph as an example, which is central to this study: the Kaplan-Meier graph.

Here we see the chance of survival for vaccinates (Orange) and unvaccinated (blue) for the age group that was born between 1940 and 1950 (71-81 years). According to this graph, the unsaved parties would have a clearly lower chance of survival than vaccinates. In the first few weeks even an extremely lower chance: the blue line runs steeply down.

In the graph we read that after 1000 days fewer than 80% of the unsvacaged people are still alive, against more than 90% of the vaccinates. Although this is difficult to read from this graph, the numerical findings are comparable to those from the NIVEL study: after 90 days, 99.5% of the vaccinates still live against only 89% of the unsaved parties. That's beautiful! Two studies that confirm each other's findings more or less numerically. But why does this clash with the findings of Pfizer itself?

The statement

The investigations provide a different explanation for this. Master's report keeps itself "politically neutral" and speaks of "data pollution," but states two likely causes: theHVEandincomplete registration. There is therefore a hefty over -representation in the unvaccinated group, creating a false protection. NIVEL sees this evidence that the vaccines are safe and even causes over mortality for unvaccinates.

The statistics, including Kaplan-Meijer Graphics, is in our articleNivel for dummiesexplained. It remains a difficult graph, from which it is not easy to draw quantitative conclusions. That is why we have recalculated the figures as an opportunity to die on a certain day. We can then compare them with the (seasonal) to be expectednorm mortality. We then get this graph:

The green line is the risk of death for vaccinates. This is counted from the day they were vaccinated and coupled to an unvaccinated person. The orange line is the expected death chance per day for this group. What is of course immediately noticeable is that no one died on the first days after vaccination. It is still about all the causes together and that is already strange: the vaccineseemsdeath to prevent completely.

If we go further in time, we see that a stable chance is achieved after 28 days, but it remains a piece below the expected death. Your chance to die has become 22.3% smaller on average from that day. This is the elixir of the vaccines claimed by RIVM: vaccination apparently reduces your chance to die in the first 3 months (regardless of the cause of death) by 22.3%.

The unsavory

On the other hand, if we look at the risk of death among unvaccinated people, it was 0.008% per day for vaccination. On the day you were linked to an vaccinated person, it suddenly rose to no less than 1.59%. That is a 200 times as large chance of death, only by linking this unvaccinated to a just vaccinated person. See this graph (graph 2) in which the Y-axis is a factor of 10. The line still does not fit within the graph.

It is clear that this towering unvaccinated death chance is impossible. A serious researcher would look for an explanation for this impossible phenomenon. For Nivel, it is precisely the clear evidence that the excess mortality is among the unsvacaged people.

Data pollution

The cause for this phenomenon is the "data pollution" when registering the vaccination data. In the first few weeks, the backlog in the registration in CIMS seems to be the big culprit. In case you have just been vaccinated and shortly thereafter die, your data is not yet included in CIMS. Legislation (Staatscourant November 19, 2020.) prevents this from being done after the death.

From day 28 it isHVEdominant. Too sick people can no longer be vaccinated. As a result, the group of unvaccinated people is expanded with likely and certain deaths of people who would otherwise be vaccinated. If there are ten times as many vaccinates as unavoidable people, then every percent of vaccinates who are being transferred in this way counts for 10% higher mortality in the unvaccinated people. The number of deaths in the unvaccinated group is therefore going to rise proportionally. For that reason, the vaccinated group alone seems to have 22.3% less mortality than expected.

Because of this data pollution, we are unable to make reliable statements in this period about differences in the risk of death for well-being and non-vaccinated people. But then the image becomes sharper ...

The sequel

Nivel in particular looks at the first 12 months, but we look further. If we compare the weekly mortality with the standard mortality (the statistically expected death) then we see that it has reached the level of standard mortality after six months. After that, there is excess with the vaccinates, despite the data pollution! After 8 months (day 252), the excess with the vaccinees rose to 15%.

The second year

If we look at the second year specifically (Nivel stopped their analysis here), then we see a continuation of the image. Because everyone has become a year older, the baseline shifts slightly up, but the excess remains around 14%. The HvE is extinguished in the long term and the registration arrears were made up in the spring of 2022 according to RIVM. That is around day 500, counted from the first shot.

In this graph, the unsaved parties are no longer depicted, because there is now a very large uncertainty in the figures. There will still be any HVE and we also know that 1% is still missing. Small differences that give very large shifts and therefore no longer have any relevance. It is certain that the CBS figures show that there was an excess of around 10% among the entire population and therefore there is little or no space left for overdolution for unvaccinated people.

Conclusions

We show that the NIVEL report, which claims lower mortality and higher mortality among unvaccinals in the first three months after vaccination, is misleading due to data problems. The most important problems are the "Healthy Vaccinee Effect" (HvE), in which sick people were vaccinated less often, and incomplete registration in the CIMS database, as a result of which some vaccinates who died shortly after vaccination were registered as unaccinated. These biases create a distorted image of vaccine protection.

Our calculations show a overdolution of 10-15% for vaccinates of 71–81 years from the second half of 2021. The use of defective data in policy discussions should be prevented, because this may conceal the actual mortality patterns.