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Researchers Prof. Dr. Rolf Steyer and Dr. Gregor Kappler conducted an analysis examining excess mortality in all 16 German states during weeks 36 to 40. The analysis compared states with higher vaccination rates versus those with lower vaccination rates. The analysis showed: the higher the vaccination rate, the higher the excess mortality.
Prof. Steyer is professor emeritus of Friedrich Schiller University with a research interest is in the theory of causality and the theory of latent variables. Dr. Kappler is a Multivariate Statistical Methods lecturer, senior data scientist and software developer.
Dr. Ute Berner, an experimental physicist and Member of Thüringen State Parliament, commissioned the two statisticians, Prof. Steyer and Dr. Kappler, to investigate whether there was a connection between the vaccination rate and excess mortality across Germany.
The analysis was based on data from the Federal Office for Statistics and Germany’s Public Health Robert Koch Institute (“RKI”). The authors wrote (translated into English):
“The correlation is + .31, is amazingly high and especially in an unexpected direction. Actually, it should be negative, so that one could say: The higher the vaccination rate, the lower the excess mortality. However, the opposite is the case and this urgently needs to be clarified. Excess mortality can be observed in all 16 [states]. The number of Covid deaths reported by the RKI in the period under consideration consistently represents only a relatively small part of mortality and, above all, cannot explain the critical facts:”
On 17 November 2021, Dr. Bergner presented the analysis she had commissioned to the State Minister of Health, Heike Werner. “2G is excluding and discriminatory,” she said. In Germany, people who are vaccinated against Covid (geimpft) or have recovered from Covid (genesen) are designated as “2G.” The so-called “2G rule” is, for example, when only 2G have access to restaurants, cinemas, theatres, museums or galleries and unvaccinated people are barred from entry. By 18 November a number of states had brought in the 2G rule.
According to Our World in Data during the period 2 February to 22 November 2020 Germany’s all-cause deaths were lower compared to previous years. From 29 November 2020 there were 2,916 excess deaths and by 14 November 2021 Germany had a cumulative 61,920 excess deaths.
Excepting for a few isolated places, the Covid injection roll-out started on 27 December 2020. By 17 June 2021 50% of Germany’s population had received at least one Covid injection dose and by 14 November that had risen to 69%.
Our World in Data shows that in the “year of the pandemic” there were no excess deaths while in the “year of the vaccination” there are excess deaths, almost 37,500 occurring post-vaccination roll-out.
Prof. Steyer and Dr. Kappler proved a correlation between excess deaths and increased vaccination rates. Instead of investigating, and in spite of this information, on 2 December the outgoing German chancellor, Angela Merkel, announced a national lockdown for those who refuse the Covid injection and backed plans by the incoming government to make vaccination mandatory.
Further resources:
- German study: The higher the vaccination rate, the more excess mortality, America’s Frontline Doctors
- Federal states with a high vaccination rate have the highest excess mortality (German to English Google translate)
- New study from Germany confirms higher vax coverage – higher excess mortality, Steve Kirsch
- German states with a high vaccination rate have the highest excess mortality, Free West Media, 20 November 2021
- The higher the vaccination rate, the higher the excess mortality, Prof. Dr. Rolf Steyer and Dr. Gregor Kappler, 16 November 2021
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Categories: Breaking News, World News
Why Hide What Happens In The First Two Weeks After Vaccination?
December 6, 2021
There have been numerous papers published showing how well the vaccines protect people after the second dose. Some of this effect is an illusion. The effect happens as a result of inaccurate measuring and a phenomenon called survivorship bias.
Survivorship bias happens when a group is compared at two time points, but the members of the group change between the time points. It would be like assessing the quality of a swimming school which favours the technique of throwing people into the middle of the ocean, leaving them for a couple of hours and claiming credit for how well the remaining students can swim. After two hours, the only people left would be the ones who could already swim and possibly a few who learnt to swim the hard way! The poor souls who drowned in the interim don’t even make the count. Attributing the remaining people’s swimming ability to the coach who turned up 2 hours later would obviously give a very misleading picture. Pointing out that no-one drowned in later lessons would be equally misleading in determining the success of the ‘teaching technique’.
With covid vaccination there is a two week period after vaccination that is not included in the data. The rationale given for this is that vaccines take a while to induce antibodies and therefore the first two weeks’ data are not relevant. Obviously this is flawed. What if the vaccines have deleterious effects that are visible straightaway, that have nothing to do with antibody production? An example is the high rate of shingles seen after covid vaccination, suggesting there is a problem with viral reactivation. This may explain why Sars-CoV-2 infection rates are actually higher in the vaccinated than in the unvaccinated in the first two weeks after vaccination.
The effect of eliminating the first two weeks is a misleading data bias. If people become infected and are dying during that period, this needs to be included. The possibility that the vaccine itself may exert an effect on infection rate cannot be overlooked and the entire dataset needs to be included in order to accurately assess effectiveness. By only measuring the period after the higher risk of infection (0-14 days) it is possible to be deceived. Any signal would be missed.
Aside from it being nonsensical in terms of individual risk to remove this period of time, there will also be an impact on the wider community. If the vaccine in fact causes a spike in infections during the first two weeks, this will inevitably increase spread and will lead to an increased number of infections in that community during that time. Therefore, the assessment of the impact of the vaccination programme must include not only the effect on the individual, but the impact on the wider community.
This point is of particular relevance for close-knit communities where many are being vaccinated at the same time, such as schools and in particular communities with a high number of vulnerable people such as care homes and hospitals. What we are effectively doing is ‘speeding up’ the wave of infections (and deaths). Ultimately at the end of the viral season, the same number of people died. Because of excluding the earlier deaths (1-14 days), we are misled into thinking that the vaccines were more effective than they actually were. By only looking at the later period and seeing fewer deaths during that time, the illusion was created that lives were saved. This is evident in data from many countries following vaccine roll-out. The graph below showing the UK versus Europe illustrates this point, as the UK was the fastest to roll out the vaccine. The total number of deaths, represented by the area under the curve, was similar to other countries, but is just compressed into a shorter time period.
Figure 1: Covid Deaths in winter in UK and the European Union
Let’s now examine some specific examples, e.g. this study of nursing home residents in the United States. The results show that over the course of the study 6.8% of the vaccinated population were infected and 6.8% of the unvaccinated population were infected. However, by deciding that the first 14 days after vaccination should be excluded, the grey area for the vaccinated group is compared to the black and grey area combined for the unvaccinated. Doing so could lead to the claim of 66% vaccine efficacy against infection. The authors of this study were honest enough to share the raw data and did not claim 66% efficacy.
Figure 2: Data from US paper showing the percentage of the nursing home population to be infected by time after the clinic came to their home and by vaccination status
However, numerous studies have relied on this trick to make claims of vaccine efficacy. The most obvious examples of this are the original Pfizer trial study and the AstraZeneca trial.
Figure 3: Graph from AstraZeneca trial showing censorship of early period (‘Exclusion Period’)
To take a second example, a Danish paper measured infection numbers in healthcare workers and care home residents. Prior to the beginning of the vaccination programme 4.8% of the healthcare workers had been infected and 3.8% of the care home residents had been. The study ended at the end of the Danish winter wave after 95% of the care home residents had been vaccinated and 28% of the healthcare workers had been. Given the worse position at the start and the lower vaccination rate in healthcare workers you might expect that they were worse off overall. However, the percentage infected by the end of the wave was 7.0% among healthcare workers but 7.7% among care home residents.
Figure 4: Data from Danish paper showing percentage of population infected among care home residents and healthcare workers
How much of the vaccine efficacy reported in covid research is really a measure of survivorship bias coupled with naturally acquired immunity? This is a critical question. No claim of vaccine efficacy should be made without first addressing this.
Report originally published by Health Advisory and Recovery Team. HART is a group of highly qualified UK doctors, scientists, economists, psychologists and other academic experts.
GreatGameIndia
Probably, the above scientists did not take these above figures into account either – well, at this rate the Germans, after starting World War One and Two won’t be starting World War 3 because there won’t be enough of them left to do that!!
THIS IS NOTHING TO DO WITH HEALTH STOPING THE LIFES OF THE UN JABB MOST PEOPLE WANT TO DIE WHEN ITS TIME TO GO NOT WHEN THE GOVERNMENT DECIDES THIS HATRED TO PEOPLE WHO DO NOT WONT THERE CRAP IN ARM LET THEM START EXPLAINING THE DAMAGE THERE WONDER DRUG HAS DONE THIS WILL CREAP IN TO EVERY COUNTRY ONE BY ONE THIS IS A WAR WITHOUT BOMBS
Here is the answer, why this is happening, why they are so pushy with the vax and passport – a must watch video.
THANK YOU GUNDEIP MOST WELCOME EVIL BEYOND WORDS
Inded it does appear to be, but why? Is it because they don’t practice due diligence and actually investigate the word of the cherished corporate thinking they will do no wrong or is it some other agenda such as population control for climate change? which is another made up bombshell for the sake of grants and money. Money really does seem to earn reputation as evil here.
[…] Analysis of German Data Shows the Higher the Vaccination Rate, the Higher the Excess Mortality […]
[…] December 6, 2021Analysis of German Data Shows the Higher the Vaccination Rate, the Higher the Excess Mortality […]
[…] The Expose – Prof. Steyer is professor emeritus of Friedrich Schiller University with a research interest is in the theory of causality and the theory of latent variables. Dr. Kappler is a Multivariate Statistical Methods lecturer, senior data scientist and software developer. […]
Vaxxed people emit radio frequencies and wifi signals and amplifying them because of the graphene oxide in their blood stream and organs. When one person exposed too much electiricity or radio signals his/her blood vessels shape changes from perfect circles to abrupt shapes. It has also been proven that electiricity and radio frequencies cause FLU/COVID like symptoms since electiricity come in to our lives. Covid as a virus may not exist however threat is real. Vaxxed people emit and broadcast signals. Try getting an old Android device and search for bluetooth near crowded places. Then go somewhere quiet like nature. You will see unidentified MAC addresses when searching for nearby devices. In one instance, I was able to see 50+ unidentified devices when I searched in a crowded place. There cannot be this much electronic devices, it is simply unnatural. Ivermectin is safe and proven medicine and it cures these FLU/COVID like symptoms. Do not get the poison jab.
Get Ivermectin while you still can! ivmpharmacy.com
Ah yes, but they have made damned certain that you cannot get your hands on it. Vit D3, zinc, and Quercetin that allows the protective zinc to the cell also works. I take it 2 days out of three just to ensure.Better keep it secret in case they ban it.
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[…] December 6, 2021Analysis of German Data Shows the Higher the Vaccination Rate, the Higher the Excess Mortality […]
When the authorities speak to their professional consultants, do they ever take into account that the consultant may be being paid on the board of the product under question or being reported upon for negative effects so why are they not pointing this out? As far as I can tell they are complicit int he murders of children under their own guidance. They should be jailed.
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[…] Rhoda Wilson on December 6, 2021 […]
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[…] Analysis of German Data Shows the Higher the Vaccination Rate, the Higher the Excess Mortality […]