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Analysis of the early COVID-19 epidemic curve in Germany by regression models with change points
Stockholms universitet, Naturvetenskapliga fakulteten, Matematiska institutionen.ORCID-id: 0000-0002-0423-6702
Antal upphovsmän: 42021 (Engelska)Ingår i: Epidemiology and Infection, ISSN 0950-2688, E-ISSN 1469-4409, Vol. 149, s. 1-7, artikel-id e68Artikel i tidskrift (Refereegranskat) Published
Abstract [en]

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.

Ort, förlag, år, upplaga, sidor
2021. Vol. 149, s. 1-7, artikel-id e68
Nyckelord [en]
Change point, COVID-19, epidemiology
Nationell ämneskategori
Folkhälsovetenskap, global hälsa och socialmedicin
Identifikatorer
URN: urn:nbn:se:su:diva-193218DOI: 10.1017/S0950268821000558ISI: 000629562500001PubMedID: 33691815OAI: oai:DiVA.org:su-193218DiVA, id: diva2:1555095
Tillgänglig från: 2021-05-17 Skapad: 2021-05-17 Senast uppdaterad: 2025-02-20Bibliografiskt granskad

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Günther, FelixHöhle, MichaelBender, Andreas

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Epidemiology and Infection
Folkhälsovetenskap, global hälsa och socialmedicin

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