Radermacher Walter J
Ludwig-Maximilians-Universitat München Fakultät für Mathematik Informatik und Statistik, Munich, Germany.
Adv Stat Anal. 2022;106(3):391-397. doi: 10.1007/s10182-022-00447-7. Epub 2022 May 21.
In the Corona pandemic, it became clear with burning clarity how much good quality statistics are needed, and at the same time how unsuccessful we are at providing such statistics despite the existing technical and methodological possibilities and diverse data sources. It is therefore more than overdue to get to the bottom of the causes of these issues and to learn from the findings. This defines a high aspiration, namely that firstly a diagnosis is carried out in which the causes of the deficiencies with their interactions are identified as broadly as possible. Secondly, such a broad diagnosis should result in a therapy that includes a coherent strategy that can be generalised, i.e. that goes beyond the Corona pandemic.
在新冠疫情期间,我们清楚地认识到优质统计数据是多么必要,同时也清楚地看到,尽管有现有的技术和方法可能性以及多样的数据来源,但我们在提供此类统计数据方面却多么不成功。因此,深入探究这些问题的原因并从研究结果中吸取教训早就应该进行了。这确定了一个很高的目标,即首先要进行诊断,尽可能广泛地确定缺陷的原因及其相互作用。其次,这样广泛的诊断应该产生一种治疗方法,其中包括一种连贯的、可推广的策略,也就是说,这种策略要超越新冠疫情。