Evidence map›Paper›PMID 35392481›Full record

ArticleFrontiers in public health2022

COVID-19 Testing Unit Munich: Impact of Public Health and Safety Measures on Patient Characteristics and Test Results, January to September 2020.

Hannah Tuulikki Hohl, Christian Heumann, Camilla Rothe, Michael Hoelscher, Christian Janke, Guenter Froeschl

Abstract read
In one paragraph

Article in Frontiers in public health, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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

6 authors.

Hannah Tuulikki HohlDivision of Infectious Diseases and Tropical Medicine, University Hospital, LMU Munich, Munich, Germany.
Christian HeumannDepartment of Statistics, Faculty of Mathematics, Informatics and Statistics, University of Munich, Ludwig-Maximilians-Universität (LMU), Munich, Germany.
Camilla RotheDivision of Infectious Diseases and Tropical Medicine, University Hospital, LMU Munich, Munich, Germany.
Michael HoelscherDivision of Infectious Diseases and Tropical Medicine, University Hospital, LMU Munich, Munich, Germany.
Christian JankeDivision of Infectious Diseases and Tropical Medicine, University Hospital, LMU Munich, Munich, Germany.
Guenter FroeschlDivision of Infectious Diseases and Tropical Medicine, University Hospital, LMU Munich, Munich, Germany.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

To assess the course of the COVID-19 pandemic and the impact of non-pharmaceutical interventions, the number of reported positive test results is frequently used as an estimate of the true number of population-wide infections. We conducted a retrospective observational analysis of patient data of the Corona Testing Unit (CTU) in Munich, Bavaria, Germany between January 27th, and September 30th, 2020. We analyzed the course of daily patient numbers over time by fitting a negative binomial model with multiple breakpoints. Additionally, we investigated possible influencing factors on patient numbers and characteristics by literature review of policy papers and key informant interviews with individuals involved in the set-up of the CTU. The 3,963 patients included were mostly young (median age: 34, interquartile range: 27-48), female (66.2%), and working in the healthcare sector (77%). For these, 5,314 real-time RT-PCR tests were conducted with 157 (2.94%) positive results. The overall curve of daily tests and positive results fits the re-ported state-wide incidence in large parts but shows multiple breakpoints with considerable trend changes. These can be most fittingly attributed to testing capacities and -strategies and individual risk behavior, rather than public health measures. With the large impact on patient numbers and pre-test probabilities of various strategic and operational factors, we consider the derived re-ported incidence as a poor measurement to base policy decisions on. Testing units should be prepared to encounter these fluctuations with a quickly adaptable structure.

Indexed as

COVID-19PandemicsAdultCOVID-19 TestingFemaleHumansMaleMiddle AgedPublic HealthRetrospective StudiesSARS-CoV-2COVID-19epidemiologyGermanyMunichpublic healthSARS-CoV-2testing unit

Identifiers

PMID35392481
PMCPMC8980425

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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.