Evidence map›Paper›PMID 33691815›Full record

ArticleEpidemiology and infection2021

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

Helmut Küchenhoff, Felix Günther, Michael Höhle, Andreas Bender

Abstract read
In one paragraph

Article in Epidemiology and infection, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

8 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Stringency of containment and closures on the growth of SARS-CoV-2 in Canada prior to accelerated vaccine roll-out.International journal of infectious diseases : IJID : official publication of the International Society for Infectious Diseases · 2022
    Article
  5. Article
  6. Article
  7. On the role of data, statistics and decisions in a pandemic.Advances in statistical analysis : AStA : a journal of the German Statistical Society · 2022
    Article
  8. Influence of transportation network on transmission heterogeneity of COVID-19 in China.Transportation research. Part C, Emerging technologies · 2021
    Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Helmut KüchenhoffStatistical Consulting Unit StaBLab, LMU Munich, Germany.ORCID 0000-0002-6372-2487
Felix GüntherStatistical Consulting Unit StaBLab, LMU Munich, Germany.ORCID 0000-0001-6582-1174
Michael HöhleDepartment of Mathematics, Stockholm University, Sweden.ORCID 0000-0002-0423-6702
Andreas BenderStatistical Consulting Unit StaBLab, LMU Munich, Germany.ORCID 0000-0001-5628-8611

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

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.

Indexed as

AgedAged, 80 and overAge DistributionBayes TheoremCOVID-19FemaleGermanyHumansMaleRegression AnalysisSARS-CoV-2Change pointCOVID-19epidemiology

Identifiers

PMID33691815
PMCPMC7985895

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.