Streuspanne – Statistics and Its Curiosities

In our podcast, we have already talked about how vaccine effectiveness is calculated. We mainly referred to the registration studies. Now millions of people have been vaccinated and we have a lot of new data. Shouldn't we know better now how effective vaccination is?

The probability calculus was invented in the 16th century in the first place only so that noblemen would do better at gambling. What is left of it today? Do statisticians have an advantage in Lotto, roulette and the like and win more often?

Having dealt with apparent contradictions between statistical measures in the last blog post, we now delve deeper into how local incidences are determined. There have been occasional criticisms in the German media that the incidences reported by the RKI are too low in some counties. We want to address the question: How large is this effect and how comparable are incidences in different regions?

Just in time for the end of 2020, we were surprised to learn that a mutation of the Corona virus is circulating in England. It is not said to be more deadly, but more contagious. Directly, neighboring countries have expressed concern that the mutation could also reach them. So let's ask ourselves today: can we tell from the reported infection numbers if something like this has happened?

The blog Streuspanne has been around for over two years now. Time for an interim balance right at the beginning of the year. In this interview, our bloggers Sascha Feth and Jochen Fiedler look back, talk about developments, goals, the motivation behind it, and the statistical future.

Here in the blog we have recently dealt with the dark figure of corona infections and the statistical characteristics of the tests. This time we ask ourselves the question: If we take measures today, will they affect all age groups at the same time?

Recently, we looked at the extent to which incomplete infection figures in the Corona pandemic can be compared with warranty data for vehicle components. Today, we use statistical quality control to reject some conspiracy theories surrounding Covid-19.

In the last post we presented a simple approach that can be used to statistically estimate the dark figure of corona infections (with regard to SARS-CoV-2). We originally developed the approach to explain at least a large part of the very different mortality rates between Italy and Germany (and less to estimate the number of unreported cases as precisely as possible). At the same time, the approach has aroused great interest among many readers and colleagues. We have therefore decided to develop the approach further so that it can estimate the dark figure even better.

On 2 April, Germany reported 73,000 corona infections and 867 deaths. Italy counts 100,000 infections and 12,000 deaths. Based on these figures, the case mortality rate in Italy is more than 10 times higher than in Germany. Experts are clear: this difference is less an expression of a different health care system or a different population structure, but rather an expression of unknown dark figures.