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Analysis of the early COVID-19 epidemic curve in Germany by regression models with change points.

Helmut KüchenhoffFelix GuentherMichael HöhleAndreas Bender
Published in: Epidemiology and infection (2021)
We analysed the coronavirus disease 2019 epidemic curve from March to the end of April 2020 in Germany. We use statistical models to estimate the number of cases with disease onset on a given day and use back-projection techniques to obtain the number of new infections per day. The respective time series are analysed by a trend regression model with change points. The change points are estimated directly from the data. We carry out the analysis for the whole of Germany and the federal state of Bavaria, where we have more detailed data. Both analyses show a major change between 9 and 13 March for the time series of infections: from a strong increase to a decrease. Another change was found between 25 March and 29 March, where the decline intensified. Furthermore, we perform an analysis stratified by age. A main result is a delayed course of the pandemic for the age group 80 + resulting in a turning point at the end of March. Our results differ from those by other authors as we take into account the reporting delay, which turned out to be time dependent and therefore changes the structure of the epidemic curve compared to the curve of newly reported cases.
Keyphrases
  • coronavirus disease
  • sars cov
  • electronic health record
  • respiratory syndrome coronavirus
  • machine learning
  • adverse drug
  • data analysis
  • contrast enhanced