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Nach einer kurzen wissenschaftstheoretischen Einführung wendet sich der Beitrag der (schlechten) Datenqualität in der Coronavirus-Pandemie zu. Michael Krawczak beschreibt die Krise nicht zuletzt auch als Datenkrise. Zudem widmet sich der Autor den Zusammenhängen zwischen Epidemiologie, klinischer Forschung und Krankenversorgung. ; After a short introduction on the theory of science, the article turns to the (poor) data quality in the coronavirus pandemic. Michael Krawczak describes the crisis not least as a data crisis. In addition, the author addresses the interrelationships between epidemiology, clinical research, and patient care.

AbstractCommentary on Cherkas et al. (2004). Genetic Influences on Female Infidelity and Number of Sexual Partners in Humans: A Linkage and Association Study on the Role of the Vasopressin Receptor Gene (AVPR1A). Twin Research, 7, 649–658.

A database of the frequency of human inherited disorders is being established for use in a clinical context, in medical research, for epidemiological studies, and in the planning of genetic services. Each entry includes the disease name categorized by organ system, an Online Mendelian Inheritance in Man (OMIM) number, the mode of inheritance, the population origin, a prevalence and/or incidence rate and a literature reference. The Frequency of Inherited Disorders Database (FIDD) currently contains 1,580 entries relating to 280 different Mendelian disorders. FIDD will be prospectively maintained and can be accessed at http://www.uwcm.ac.uk/uwcm/mg/fidd/. A more refined and systematic literature search that will serve to expand the size, scope and scale of the database is currently in progress. The coverage of neurological and neuromuscular disorders is however considered to be nearly complete. In this first description of FIDD, Huntington disease was used to illustrate the structure and scope of the database as well as its potential scientific utility. A total of 100 published articles on the prevalence of Huntington disease were appraised. Prevalence and incidence rates varied between different ethnic groups and between different countries. Possible reasons for this variation are discussed.

<i>Objective:</i> Patient samples used for mapping complex human disease genes are unlikely to be representative of the phenotype spectrum of the respective population as a whole. On the other hand, most ongoing prospective studies are probably too small for evaluating polygenic disease markers. <i>Design:</i> Precise estimates of population-specific genotypic risks can be obtained efficiently through the complete ascertainment of patients in a geographically confined area. The PopGen project uses the most northern part of Germany as a target region for such a pursuit. <i>Results:</i> PopGen currently pursues recruitment, sampling and processing activities in close collaboration with a multitude of clinical partners, covering cardiovascular, neuropsychiatric and environmental diseases. <i>Conclusion:</i> PopGen has successfully established itself as a large-scale genetic epidemiological project of international recognition.