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Corona Monitoring Nationwide (RKI-SOEP-2): Seroepidemiological Study on the Spread of SARS-CoV-2 Across Germany

Author

Listed:
  • Bartig Susanne
  • Butschalowsky Hans
  • Gößwald Antje
  • Hey Isabell
  • Hoebel Jens
  • Jordan Susanne
  • Kubisch Ulrike
  • Poethko-Mueller Christina
  • Schaffrath Rosario Angelika
  • Schlaud Martin
  • Stahlberg Silke
  • Wernitz Jörg

    (Department of Epidemiology and Health Monitoring, Robert Koch Institute, Berlin, Germany)

  • Brücker Herbert
  • Goßner Laura
  • Trübswetter Parvati

    (Institute for Employment Research (IAB) of the Federal Employment Agency (BA), Nuremberg, Germany)

  • Danne Christian
  • Priem Maximilian

    (DIW Econ, Berlin, Germany)

  • Grabka Markus M.
  • Steinhauer Hans W.
  • Zinn Sabine

    (Socio-Economic Panel, German Institute for Economic Research, Berlin, Germany)

  • Haller Sebastian
  • Wilking Hendrik

    (Department of Infectious Disease Epidemiology, Robert Koch Institute, Berlin, Germany)

  • Hess Doris
  • Torregroza Sabrina

    (infas Institute for Applied Social Sciences, Bonn, Germany)

  • Niehues Wenke
  • Rother Nina
  • Siegert Manuel
  • Tanis Kerstin

    (Research Center of the Federal Office for Migration and Refugees, Nuremberg, Germany)

  • Schaade Lars

    (Centre for Biological Threats and Special Pathogens, Robert Koch Institute, Berlin, Germany)

  • Wieler Lothar H.

    (Institute Leadership, Robert Koch Institute, Berlin, Germany)

Abstract

SARS-CoV-2, the coronavirus, spread across Germany within just a short period of time. Seroepidemiological studies are able to estimate the proportion of the population with antibodies against SARS-CoV-2 infection (seroprevalence) as well as the level of undetected infections, which are not captured in official figures. In the seroepidemiological study Corona Monitoring Nationwide (RKI-SOEP-2), biospecimens and interview data were collected in a nationwide population-based subsample of the Socio-Economic Panel (SOEP). By using laboratory-analyzed blood samples to detect antibodies to the SARS-CoV-2 virus, we were able to identify a history of vaccination or infection in study participants. By combining these results with survey data, we were able to identify groups within the population that are at increased risk of infection. By linking the RKI-SOEP-2 survey data with data from other waves of the SOEP survey, we will be able to examine the medium- to long-term impacts of the COVID-19 pandemic, including effects of long COVID, in diverse areas of life. Furthermore, the data provide insight into the population’s willingness to be vaccinated as well as related attitudes and conditions. In sum, the RKI-SOEP-2 survey data offer a better understanding of the scope of the epidemic in Germany and can help in identifying target groups for infection control in the present and future pandemics.

Suggested Citation

  • Bartig Susanne & Butschalowsky Hans & Gößwald Antje & Hey Isabell & Hoebel Jens & Jordan Susanne & Kubisch Ulrike & Poethko-Mueller Christina & Schaffrath Rosario Angelika & Schlaud Martin & Stahlberg, 2023. "Corona Monitoring Nationwide (RKI-SOEP-2): Seroepidemiological Study on the Spread of SARS-CoV-2 Across Germany," Journal of Economics and Statistics (Jahrbuecher fuer Nationaloekonomie und Statistik), De Gruyter, vol. 243(3-4), pages 431-449, June.
    • Handle: RePEc:jns:jbstat:v:243:y:2023:i:3-4:p:431-449:n:10
    DOI: 10.1515/jbnst-2022-0047
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    References listed on IDEAS

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    1. Jia Wei & Philippa C. Matthews & Nicole Stoesser & Thomas Maddox & Luke Lorenzi & Ruth Studley & John I. Bell & John N. Newton & Jeremy Farrar & Ian Diamond & Emma Rourke & Alison Howarth & Brian D. M, 2021. "Anti-spike antibody response to natural SARS-CoV-2 infection in the general population," Nature Communications, Nature, vol. 12(1), pages 1-12, December.
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    More about this item

    Keywords

    SARS-CoV-2; COVID-19; seroepidemiological study; seroprevalence; vaccine status; willingness for vaccination; SOEP;
    All these keywords.

    JEL classification:

    • I12 - Health, Education, and Welfare - - Health - - - Health Behavior
    • I19 - Health, Education, and Welfare - - Health - - - Other
    • C89 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Other

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