Evidence map›Paper›PMID 36747171›Full record

ArticleBMC public health2023

Results of the Cologne Corona Surveillance (CoCoS) study - a cross-sectional study: survey data on risk factors of SARS-CoV-2 infection in adults.

Max Oberste, Nadja Schnörch, Kija Shah-Hosseini, Teodora Asenova, Felix Dewald, Clara Lehmann, Michael Buess, Gerd Fätkenheuer, Florian Klein, Kerstin Daniela Rosenberger and 3 more

Open access · goldAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in BMC public health, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
1.6field-weighted citation impact, top 19% of its field
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

4 citing papers in PubMed, 5 citations in OpenAlex.

  1. Review
  2. Article
  3. Observational
  4. 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

13 authors at 4 institutions in 2 countries.

Max Oberste *Institute of Medical Statistics and Computational Biology, Medical Faculty and University Hospital of Cologne, University of Cologne, Robert-Koch-Straße 10, 50931, Cologne, Germany.
Nadja Schnörch *Institute of Medical Statistics and Computational Biology, Medical Faculty and University Hospital of Cologne, University of Cologne, Robert-Koch-Straße 10, 50931, Cologne, Germany.
Kija Shah-HosseiniInstitute of Medical Statistics and Computational Biology, Medical Faculty and University Hospital of Cologne, University of Cologne, Robert-Koch-Straße 10, 50931, Cologne, Germany.
Teodora AsenovaInstitute of Medical Statistics and Computational Biology, Medical Faculty and University Hospital of Cologne, University of Cologne, Robert-Koch-Straße 10, 50931, Cologne, Germany.
Felix DewaldInstitute of Virology, Medical Faculty and University Hospital of Cologne, University of Cologne, Fürst-Pückler-Straße 56, 50935, Cologne, Germany.
Clara LehmannDepartment of Internal Medicine, Medical Faculty and University Hospital of Cologne, University of Cologne, Kerpener Str. 62, 50931, Cologne, Germany.
Michael BuessCologne Health Authority, Cologne, Germany.
Gerd FätkenheuerDepartment of Internal Medicine, Medical Faculty and University Hospital of Cologne, University of Cologne, Kerpener Str. 62, 50931, Cologne, Germany.
Florian KleinInstitute of Virology, Medical Faculty and University Hospital of Cologne, University of Cologne, Fürst-Pückler-Straße 56, 50935, Cologne, Germany.
Kerstin Daniela RosenbergerInstitute of Medical Statistics and Computational Biology, Medical Faculty and University Hospital of Cologne, University of Cologne, Robert-Koch-Straße 10, 50931, Cologne, Germany.
Annelene KossowCologne Health Authority, Cologne, Germany.
Florian Neuhann *Cologne Health Authority, Cologne, Germany.
Martin Hellmich *Institute of Medical Statistics and Computational Biology, Medical Faculty and University Hospital of Cologne, University of Cologne, Robert-Koch-Straße 10, 50931, Cologne, Germany. martin.hellmich@uni-koeln.de.
University Hospital Cologne · DEUniversity of Cologne · DEHeidelberg University · DEUniversity Hospital Münster · DE

Funding

German Federal Ministry of Education and Research ("Nationales Netzwerk Universitätsmedizin" ) 01KX2021
6 · The paper itself

Abstract

backgroundThe personal, environmental, and behavioral risk factors that play an important role in the spread of SARS-CoV-2 are still largely unclear. At the same time, there is limited evidence on the effectiveness of specific countermeasures for SARS-CoV-2. As a first approach to these questions, we use data from the Cologne Corona Surveillance (CoCoS) study, a large cross-sectional study conducted in Cologne, Germany, in June 2021.

methodsThis study was conducted in Cologne, Germany. Six thousand randomly selected Cologne residents who were 18 years of age or older were invited to participate in this study. Participant information was obtained via an online survey. Previous SARS-CoV-2 infections were recorded using self-reports. Sociodemographic and environmental information such as age, sex, living situation were collected. Potential SARS-CoV-2 risk behaviors were captured (workplace situation, adherence to hygiene regulations, and regular use of public transportation). Adherence to hygiene regulations was surveyed by determining the compliance with the 'AHA'-rules (German acronym that stands for keeping a distance of 1.5 m from fellow citizens, hand disinfection, and wearing a face mask). Binary logistic regression analysis was used to identify risk factors for SARS-CoV-2 infection.

resultsA sample of 2,433 study participants provided information. Comparison of the sample with the general population showed representativeness for most sociodemographic characteristics with a preference for higher level of education in the study sample. Younger age, as well as living with minor children (under 18 years) in the same household were associated with a higher number of self-reported SARS-CoV-2 infections. Adherence to hygiene regulations was associated with fewer self-reported SARS-CoV-2 infections in adults. Gender, size of living space per person, workplace situation (work from home versus working with contact to colleagues/customers), and regular use of public transportation showed no significant association with self-reported SARS-CoV-2 infections in multivariable analysis.

conclusionThe presented results provide initial indications of which sociodemographic and behavioral factors may be associated with SARS-CoV-2 infection. However, the fact that these factors were recorded without exact dates and could have changed accordingly during the pandemic or after infection limits the strength of the results.

trial registrationDRKS.de, German Clinical Trials Register (DRKS), Identifier: DRKS00024046, Registered on 25 February 2021.

Indexed as

COVID-19AdolescentAdultChildCross-Sectional StudiesHumansRisk FactorsSARS-CoV-2AgeCompliance to countermeasuresRisk associationSelf-reported infectionSocial factors

Identifiers

PMID36747171
PMCPMC9902063
OpenAlexW4319301674

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.