A new study used state-of-the-art actuarial science to examine excess deaths in Germany. The study set out to estimate covid deaths. There were no excess deaths in 2020 but “something must have happened in spring 2021 that led to a sudden and sustained increase in mortality,” the study said. A similar mortality pattern was observed for stillbirths.
The study also explored factors which could explain these mortality patterns one of which was to compare mortality patterns to covid vaccination campaigns. It found that during the months with a high number of vaccinations, there was also a high number of excess deaths.
Given this relationship, the study authors noted: “It seems surprising that a respective safety signal has not been detected in the pharmacovigilance by the Paul-Ehrlich-Institut (PEI).” And so, the study included a brief investigation into PEI’s safety analysis which they found to be flawed.
The German Federal Statistical Office fails to account for the effects of changes in the size and age profile of the population in its estimation of excess deaths. And the World Health Organisation also fails to take into account the effects of historical trends in mortality rates. “The estimations provided by the WHO not only ignore long-term trends but also changes in population,” the study authors noted.
To account for these effects, the study used a state-of-the-art method of actuarial science – based on population tables, life tables and longevity trends – to estimate the expected number of all-cause deaths from 2020 to 2022 as if there had been no pandemic. This expected number of all-cause deaths was then compared to the reported number of all-cause deaths to calculate the excess mortality.
“The results show that the observed number of deaths in 2020 was close to the expected number with respect to the empirical standard deviation … By contrast, in 2021, the observed number of deaths was two empirical standard deviations above the expected number and even more than four times the empirical standard deviation in 2022,” the study said.
The empirical rule, also called the “three-sigma rule” or the “68-95-99.7 rule,” is a statistical rule that states that, for normally distributed data, almost all the data points will fall within three standard deviations on either side of the mean (average value) – 68% of data within 1 standard deviation; 95% of data within 2 standard deviations; and 99.7% of data within 3 standard deviations. Higher standard deviation (sigma) values mean that the discovery is less and less likely to be accidentally a mistake, “random chance” or a result of random variations.
In other words, the 2021 three standard deviation (3-sigma) observed is on the outer limits of what is expected but the 2022 four standard deviation (4-sigma) falls outside the normal distribution. If the distribution of a dataset is normal, 4-sigma is rarely seen.
