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Detecting the circaseptan pattern in COVID-19 infections and deaths for quality management of health-related data assets

Leading article: 2020. August (MIAU No. 264.)
(Previous article: MIAU No. 263.)

Keywords: circaseptan, COVID-19, data asset management, quality management, risk management, similarity analysis

Abstract: Objectives: Biological rhythms are controlling a lot of aspects of the human body. Nowadays, we already know about the existence and importance of the circaseptan (7-day) patterns in humans. It is well-known, that these biological rhythms influence a lot of aspects of the human life – but endemic/pandemic patterns could still not be described. This paper tries to derive, that circaseptan characteristics can be identified behind COVID19 processes. Study design: The ECDC data-asset can be downloaded with daily updates where the daily numbers of infections and deaths can be interpreted for countries. The analyses focus on a Wednesday-oriented pattern and show which frequency this pattern can be realized in case of countries. Methods: The time series for each country have a length of 11 weeks. It was derived whether a Wednesday has the higher number of infections and/or deaths than Tuesday and/or Thursday. Results: The Wednesday-pattern (it means: the (volume of) dominance of Wednesday, the lengths of Wednesday-dominated weeks) can be identified in case of deaths in a more characteristic way than in case of infections (as expected). Conclusions: The interpretation potential of health-related data asset are limited based on different factors: the cause of a death can not be derived in a trivial way – because there can be parallel causes. The detection accuracy of being infected is not error-free. The human timestamps are specific – it means: the time is depending on the rotation of the Earth – therefore, the phenomenon of Wednesday is a kind of arbitrary category. The production of health-related data assets can be influenced by the human working rhythms (e.g. weekend-factor – where some data from the previous week(end) will be processed in the next week). The official documentation of the deaths is stronger than the documentation of infections. Identified patterns are capable of evaluating the quality of the data asset management as such. It can be assumed that countries with a higher pattern-quality (pattern-pureness) should have a better data asset management system than countries with foggy/confuse patterns. The fuzziness of the Wednesday-pattern-layers can be aggregated into an index value based on artificial intelligence for automated term-creation (called similarity analysis) where an anti-discriminative principle will be optimized. It means whether each country can have the same fuzziness-index-value based on the statistical layers of the Wednesday-pattern-analyses. More (DOC) *** More (PDF)


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