Marcel Barz: Covid 19 in raw data

19.08.2022 | www.kla.tv/23381

Marcel Barz, 46, business information scientist, former officer of the German Federal Armed Forces, lets numbers speak for themselves. Kla.TV recently broadcasted an unabridged version of his lecture: “The Pandemic in Raw Data”. Since the lecture is very detailed and long, Kla.TV is showing an abridged version with the most important facts today. At the beginning when the pandemic was proclaimed, Marcel Barz, like many of us, was initially very frightened. The threatening worldwide reports and images in the media made him afraid - afraid of illness, afraid of dying, afraid for his family, afraid for his children. In his circle of friends there was someone who saw the pandemic somewhat differently. Barz, who has always enjoyed working with numbers, wanted to prove to his friend that he was barking up the wrong tree and began to do some research. As a “bean counter”, as he calls himself, he determined and analyzed actual deaths, Intensive Care Unit bed occupancy and Corona-infected patients from 2020. Summary of the analysis on deaths: According to official statistics, there were higher numbers of deaths in 2020 than in 2019, which were attributed to Corona. First, Barz noted that when these figures were calculated, they did not take into account that 2020 was a leap year and that there was a demographic increase from 80 to 83 million citizens. After he added these important facts to the calculations and also took into account the different age groups, a different result emerged. Compared to earlier years, there was no increase in the number of deaths in any age group! Conclusion: The mortality figures for 2020 on the German federal government's website were clearly misrepresented. Summary of the analysis on Intensive Care Unit bed occupancy: In the next step, he reviewed the actual occupancy of intensive care beds by Covid patients. The German Interdisciplinary Association for Intensive Care and Emergency Medicine, or DIVI for short, publishes daily figures on available beds and their occupancy in hospitals. There, free beds, occupied beds, covid patients, deceased patients and departures are shown in daily rates and time series. Barz imported all these figures together into a table, taking into account other relevant data, e.g. municipality codes, in order to be able to present everything more clearly [Graph 33:13-46]. So the utilization in the intensive care units is on the rise or increases over the entire course of the pandemic. So, and that was the first – the first thought for me was, “Aha, here’s the pandemic.” But you know, in thinking through, we’re going to start with quality control, so we’re going to go in there now. So again, the question: how does a pea come into being and whether all the peas are in the pot or whether there might not be some rotten peas in there. In the process, he noticed contradictions. What is communicated to the public by the DIVI are not, as expected, the reports of the hospitals, but summaries based on charts. Here are two examples from his presentation: [Graph 35:14-53] So here, for example, I now have the deaths: Each day is a bar and the red, these are the total deaths in Germany. And the blue are the deaths reported by the intensive care units from the DIVI register. And there I see that some blue bars are chasing far beyond the red ones and that’s just not plausible. So there can’t have been more deaths in ICU than the total in Germany on that day. And above all, I then see correction reports that go into the negative. Or, second example, where Barz superimposed charts on reports and found inconsistencies in the Covid reports: [Graph 36:20-57] So the red curve, these are the Covid patients in the intensive care unit, which are therefore taken from the DIVI, and the blue are the Covid patients who are in the hospital – who are reported to the RKI. And the red curve is always subset of the blue curve, yes, because blue curve are all in hospital and red only those who are in ICU with Covid-19. And from the 16 calendar week, you can see this here: So the blue curve intersects the red curve and that’s just not plausible for the pea counter. So there can’t be more in ICU than there are in the hospital. These data are not plausible to him. In summary, Barz shows from his analyses that Covid patients did not burden ICUs more. Even DIVI staff were stunned when they were informed of this. Thus, the number of intensive care beds was unchanged and constantly low at 4 % in the last 15 months regarding Corona. It was noticeable, however, that from November 2020 onwards, many hospitals suddenly reported a higher occupancy rate. However, this was not due to more Covid patients, but to the fact that beds were reduced in the hospitals. But other circumstances also caused a falsified result, for example reports of multiple occupancy of patients who were transferred more often. Or patients who were admitted with completely different illnesses and then counted as Covid patients because of a positive Corona test. The conclusion for Barz as a "bean counter" is: “As good as the data from the DIVI intensive care register are, I cannot represent a pandemic here! So, I could, for example, by putting the percentage utilization at the top, show my friend Hartmut: Look here, how this has increased! But if I honestly look at the data with the toolbox I have as a “bean counter”, I have to say: These data do not help me to give evidence of a pandemic.” Summary of the analysis on Corona infected persons: What does the “bean counter” Barz now say about the infected figures or the incidence figures? As you have already guessed, the statistics do not provide valid [valid = legally valid] data here either. This is because it is not the people who are actually infected who are counted, but the people who test positive with the PCR test. As confirmed by the WHO and experts, a PCR test cannot provide reliable results. The test does not detect viable virus, so in the case of positive PCR tests it is not possible to determine whether an infection is actually present. Consequently, "incidence values" are not meaningful, as they do not show the percentage of positive and negative tests in the total number. The more Covid tests are performed, the more positive values are obtained [= higher incidence value]. Conclusion: Poor data from infected and non-infected persons cannot prove a pandemic. In all three of the cases mentioned, Barz was thus able to prove that the figures were either wrong, manipulated or not meaningful. His conclusion: he would never have imagined this result. If he had not felt compelled to do his own research by his dissenting friend, whom he had to agree with in the end, he would not have ended with a chandelier full of light but would continue being frightened in the dim glow of foggy candles. Through Barz’s correct and analytical understanding in dealing with numbers, frightening information, as steered by the political Corona agenda and propagated by the media, can be put into perspective and even dissolved. If you want to know more about the development of his investigations, including his experiences with the German Bundeswehr in the Kosovo war, where he draws parallels to today’s situation, you can find his entire lecture here on Kla.TV. [kla.tv/19889] (in German).

from wou/avr

Sources/Links: Presentation by Marcel Barz: "Pandemic in the Raw Data". https://www.youtube.com/watch?v=nEPiOEkkWzg
www.kla.tv/19889