Results of the Cologne Corona Surveillance (CoCoS) project- a cross-sectional study: survey data on risk factors of SARS-CoV-2 infection, and moderate-to-severe course in primarily immunized adults.

Age Booster vaccination Chronic lung disease Female sex Infection severity Moderate-to-severe breakthrough infection Smoking

Journal

BMC public health
ISSN: 1471-2458
Titre abrégé: BMC Public Health
Pays: England
ID NLM: 100968562

Informations de publication

Date de publication:
21 Feb 2024
Historique:
received: 31 03 2023
accepted: 01 02 2024
medline: 22 2 2024
pubmed: 22 2 2024
entrez: 21 2 2024
Statut: epublish

Résumé

Amidst the COVID-19 pandemic, vaccination has been a crucial strategy for mitigating transmission and disease severity. However, vaccine-effectiveness may be influenced by various factors, including booster vaccination, as well as personal factors such as age, sex, BMI, smoking, and comorbidities. To investigate the potential effects of these factors on SARS-CoV-2 infection and disease severity, we analyzed data from the third round of the Cologne Corona Surveillance (CoCoS) project, a large cross-sectional survey. The study was conducted mid-February to mid-March 2022 in Cologne, Germany. A random sample of 10,000 residents aged 18 years and older were invited to participate in an online survey. Information on participants' demographics (age, sex), SARS-CoV-2 infections, vaccination status, smoking, and preexisting medical conditions were collected. The outcomes of the study were: (1) the occurrence of SARS-CoV-2 infection despite vaccination (breakthrough infection) and (2) the occurrence of moderate-to-severe disease as a result of a breakthrough infection. Cox proportional-hazards regression was used to investigate possible associations between the presence/absence of booster vaccination, personal factors and the occurrence of SARS-CoV-2 infection. Associations with moderate-to-severe infection were analyzed using the Fine and Gray subdistribution hazard model. A sample of 2,991 residents responded to the questionnaire. A total of 2,623 primary immunized participants were included in the analysis of breakthrough infection and 2,618 in the analysis of SARS-CoV-2 infection severity after exclusions due to incomplete data. The multivariable results show that booster vaccination (HR = 0.613, 95%CI 0.415-0.823) and older age (HR = 0.974, 95%CI 0.966-0.981) were associated with a reduced hazard of breakthrough infection. Regarding the severity of breakthrough infection, older age was associated with a lower risk of moderate-to-severe breakthrough infection (HR = 0.962, 95%CI0.949-0.977). Female sex (HR = 2.570, 95%CI1.435-4.603), smoking (HR = 1.965, 95%CI1.147-3.367) and the presence of chronic lung disease (HR = 2.826, 95%CI1.465-5.450) were associated with an increased hazard of moderate-to-severe breakthrough infection. The results provide a first indication of which factors may be associated with SARS-CoV-2 breakthrough infection and moderate-to-severe course of infection despite vaccination. However, the retrospective nature of the study and risk of bias in the reporting of breakthrough infection severity limit the strength of the results. DRKS.de, German Clinical Trials Register (DRKS), Identifier: DRKS00024046, Registered on 25 February 2021.

Sections du résumé

BACKGROUND BACKGROUND
Amidst the COVID-19 pandemic, vaccination has been a crucial strategy for mitigating transmission and disease severity. However, vaccine-effectiveness may be influenced by various factors, including booster vaccination, as well as personal factors such as age, sex, BMI, smoking, and comorbidities. To investigate the potential effects of these factors on SARS-CoV-2 infection and disease severity, we analyzed data from the third round of the Cologne Corona Surveillance (CoCoS) project, a large cross-sectional survey.
METHODS METHODS
The study was conducted mid-February to mid-March 2022 in Cologne, Germany. A random sample of 10,000 residents aged 18 years and older were invited to participate in an online survey. Information on participants' demographics (age, sex), SARS-CoV-2 infections, vaccination status, smoking, and preexisting medical conditions were collected. The outcomes of the study were: (1) the occurrence of SARS-CoV-2 infection despite vaccination (breakthrough infection) and (2) the occurrence of moderate-to-severe disease as a result of a breakthrough infection. Cox proportional-hazards regression was used to investigate possible associations between the presence/absence of booster vaccination, personal factors and the occurrence of SARS-CoV-2 infection. Associations with moderate-to-severe infection were analyzed using the Fine and Gray subdistribution hazard model.
RESULTS RESULTS
A sample of 2,991 residents responded to the questionnaire. A total of 2,623 primary immunized participants were included in the analysis of breakthrough infection and 2,618 in the analysis of SARS-CoV-2 infection severity after exclusions due to incomplete data. The multivariable results show that booster vaccination (HR = 0.613, 95%CI 0.415-0.823) and older age (HR = 0.974, 95%CI 0.966-0.981) were associated with a reduced hazard of breakthrough infection. Regarding the severity of breakthrough infection, older age was associated with a lower risk of moderate-to-severe breakthrough infection (HR = 0.962, 95%CI0.949-0.977). Female sex (HR = 2.570, 95%CI1.435-4.603), smoking (HR = 1.965, 95%CI1.147-3.367) and the presence of chronic lung disease (HR = 2.826, 95%CI1.465-5.450) were associated with an increased hazard of moderate-to-severe breakthrough infection.
CONCLUSION CONCLUSIONS
The results provide a first indication of which factors may be associated with SARS-CoV-2 breakthrough infection and moderate-to-severe course of infection despite vaccination. However, the retrospective nature of the study and risk of bias in the reporting of breakthrough infection severity limit the strength of the results.
TRIAL REGISTRATION BACKGROUND
DRKS.de, German Clinical Trials Register (DRKS), Identifier: DRKS00024046, Registered on 25 February 2021.

Identifiants

pubmed: 38383381
doi: 10.1186/s12889-024-17958-4
pii: 10.1186/s12889-024-17958-4
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

548

Informations de copyright

© 2024. The Author(s).

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Auteurs

Max Oberste (M)

Institute of Medical Statistics and Computational Biology, Medical Faculty and University Hospital of Cologne, University of Cologne, Robert-Koch-Straße 10, 50931, Cologne, Germany.

Teodora Asenova (T)

Institute of Medical Statistics and Computational Biology, Medical Faculty and University Hospital of Cologne, University of Cologne, Robert-Koch-Straße 10, 50931, Cologne, Germany.

Angela Ernst (A)

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-Hosseini (K)

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 (N)

Institute of Medical Statistics and Computational Biology, Medical Faculty and University Hospital of Cologne, University of Cologne, Robert-Koch-Straße 10, 50931, Cologne, Germany.

Michael Buess (M)

Cologne Health Authority, Cologne, Germany.

Kerstin Daniela Rosenberger (KD)

Institute of Medical Statistics and Computational Biology, Medical Faculty and University Hospital of Cologne, University of Cologne, Robert-Koch-Straße 10, 50931, Cologne, Germany.

Annelene Kossow (A)

Cologne Health Authority, Cologne, Germany.
Institute of Hygiene, University Hospital of Muenster, University Muenster, Robert-Koch-Straße 49, 48149, Muenster, Germany.

Felix Dewald (F)

Institute of Virology, Medical Faculty and University Hospital of Cologne, University of Cologne, Fürst-Pückler-Straße 56, 50935, Cologne, Germany.

Florian Neuhann (F)

Cologne Health Authority, Cologne, Germany.
Heidelberg Institute of Global Health, University Heidelberg, Heidelberg, Germany.
School of Medicine and Clinical Sciences, Levy Mwanawasa Medical University, Lusaka, Zambia.

Martin Hellmich (M)

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.

Classifications MeSH