Infection fatality rate of SARS-CoV2 in a super-spreading event in Germany

  1. Hendrik Streeck
  2. Bianca Schulte
  3. Beate M. Kümmerer
  4. Enrico Richter
  5. Tobias Höller
  6. Christine Fuhrmann
  7. Eva Bartok
  8. Ramona Dolscheid-Pommerich
  9. Moritz Berger
  10. Lukas Wessendorf
  11. Monika Eschbach-Bludau
  12. Angelika Kellings
  13. Astrid Schwaiger
  14. Martin Coenen
  15. Per Hoffmann
  16. Birgit Stoffel-Wagner
  17. Markus M. Nöthen
  18. Anna M. Eis-Hübinger
  19. Martin Exner
  20. Ricarda Maria Schmithausen
  21. Matthias Schmid
  22. Gunther Hartmann

Reviewed by

Read the full article

Discuss this preprint

Start a discussion What are Sciety discussions?

Listed in

Log in to save this article

Abstract

A SARS-CoV2 super-spreading event occurred during carnival in a small town in Germany. Due to the rapidly imposed lockdown and its relatively closed community, this town was seen as an ideal model to investigate the infection fatality rate (IFR). Here, a 7-day seroepidemiological observational study was performed to collect information and biomaterials from a random, household-based study population. The number of infections was determined by IgG analyses and PCR testing. We found that of the 919 individuals with evaluable infection status, 15.5% (95% CI:[12.3%; 19.0%]) were infected. This is a fivefold higher rate than the reported cases for this community (3.1%). 22.2% of all infected individuals were asymptomatic. The estimated IFR was 0.36% (95% CI:[0.29%; 0.45%]) for the community and 0.35% [0.28%; 0.45%] when age-standardized to the population of the community. Participation in carnival increased both infection rate (21.3% versus 9.5%, p  < 0.001) and number of symptoms (estimated relative mean increase 1.6, p  = 0.007). While the infection rate here is not representative for Germany, the IFR is useful to estimate the consequences of the pandemic in places with similar healthcare systems and population characteristics. Whether the super-spreading event not only increases the infection rate but also affects the IFR requires further investigation.

Article activity feed

  1. ScreenIT

    SciScore for 10.1101/2020.05.04.20090076: (What is this?)

    Please note, not all rigor criteria are appropriate for all manuscripts.

    Table 1: Rigor

    Institutional Review Board StatementConsent: All study participants provided written and informed consent before enrolment.
    IRB: The study was approved by the Ethics Committee of the Medical Faculty of the University of Bonn (approval number 085/20) and has been registered at the German Clinical Trials Register (https://www.drks.de, identification number DRKS00021306).
    RandomizationSampling was done randomly under the side condition that all 600 persons had different surnames, as it was assumed that different surnames were likely to indicate different households.
    Blindingnot detected.
    Power Analysisnot detected.
    Sex as a biological variablenot detected.
    Cell Line Authenticationnot detected.

    Table 2: Resources

    Antibodies
    SentencesResources
    The data sheet (April 7, 2020) reports cross-reactivities with anti-SARS-CoV-1-IgG-antibodies, but not with MERS-CoV-, HCoV-229E-, HCoV-NL63-, HCoV-HKU1- or HCoV-OC43-IgG antibodies.
    HCoV-OC43-IgG
    suggested: None
    Experimental Models: Cell Lines
    SentencesResources
    After incubation of 1 h at 37°C, 200 μl of each mixture were added to wells of a 24 well plate seated the day before with 1.5×105 Vero E6 cells/well.
    Vero E6
    suggested: RRID:CVCL_XD71)
    Software and Algorithms
    SentencesResources
    Study data were collected and managed using REDCap electronic data capture tools hosted at Institute for Medical Biometry, Informatics and Epidemiology13, 14. REDCap (Research Electronic Data Capture) is a secure, web-based software platform designed to support data capture for research studies, providing 1) an intuitive interface for validated data capture; 2) audit trails for tracking data manipulation and export procedures; 3) automated export procedures for seamless data downloads to common statistical packages; and 4) procedures for data integration and interoperability with external sources.
    REDCap
    suggested: (REDCap, RRID:SCR_003445)
    R Foundation for Statistical Computing, Vienna, Austria) and version 9.4 of the SAS System for Windows (copyright © 2002-2012 by SAS Institute Inc., Cary, NC, USA).
    SAS Institute
    suggested: (Statistical Analysis System, RRID:SCR_008567)

    Results from OddPub: We did not detect open data. We also did not detect open code. Researchers are encouraged to share open data when possible (see Nature blog).

    Results from LimitationRecognizer: We detected the following sentences addressing limitations in the study:
    However, with the limitations discussed above, the IFR calculated here remains a useful metric for other regions with higher or lower infection rates. If in a theoretical model the here calculated IFR is applied to Germany with currently approximately 6,575 SARS-CoV-2 associated deaths (May 2nd, 2020, RKI), the estimated number of infected in Germany would be higher than 1.8 Mio (i.e. 2.2% of the German population). It will be very important to determine the true average IFR for Germany. However, because of the currently low infection rate of approximately 2% (estimated based on IFR), an ELISA with 99% specificity will not provide reliable data. Therefore, under the current non-superspreading conditions, it is more reasonable to determine the IFR in high prevalence hotspots such as Heinsberg county. The data of the study reported here will serve as baseline for follow up studies on the delta of infections and deaths to identify the corresponding IFR under those changed conditions.

    Results from TrialIdentifier: No clinical trial numbers were referenced.

    Results from Barzooka: We found bar graphs of continuous data. We recommend replacing bar graphs with more informative graphics, as many different datasets can lead to the same bar graph. The actual data may suggest different conclusions from the summary statistics. For more information, please see Weissgerber et al (2015).

    Results from JetFighter: We did not find any issues relating to colormaps.

    Results from rtransparent:
    • Thank you for including a conflict of interest statement. Authors are encouraged to include this statement when submitting to a journal.
    • Thank you for including a funding statement. Authors are encouraged to include this statement when submitting to a journal.
    • No protocol registration statement was detected.

    About SciScore

    SciScore is an automated tool that is designed to assist expert reviewers by finding and presenting formulaic information scattered throughout a paper in a standard, easy to digest format. SciScore checks for the presence and correctness of RRIDs (research resource identifiers), and for rigor criteria such as sex and investigator blinding. For details on the theoretical underpinning of rigor criteria and the tools shown here, including references cited, please follow this link.

  2. Version published to 10.1038/s41467-020-19509-y
  3. ScreenIT

    SciScore for 10.1101/2020.05.04.20090076: (What is this?)

    Please note, not all rigor criteria are appropriate for all manuscripts.

    Table 1: Rigor

    Institutional Review Board StatementAll study participants provided written and informed consent before enrolment.RandomizationSampling was done randomly under the side condition that all 600 persons had different surnames, as it was assumed that different surnames were likely to indicate different households.Blindingnot detected.Power Analysisnot detected.Sex as a biological variablenot detected.Cell Line Authenticationnot detected.

    Table 2: Resources

    Antibodies
    SentencesResources
    Here we combined virus RT-PCR testing and assessment for SARS-CoV2 antibodies to determine the total number of individuals with SARS-CoV-2 infections in a given population.
    SARS-CoV2
    suggested: (Abcam Cat# ab273074, AB_2847846)
    The data sheet (April 7, 2020) reports cross-reactivities with anti-SARS-CoV-1-IgG-antibodies, but not with MERS-CoV-, HCoV-229E-, HCoV-NL63-, HCoV-HKU1- or HCoV-OC43-IgG antibodies.
    HCoV-OC43-IgG
    suggested: None
    Experimental Models: Cell Lines
    SentencesResources
    After incubation for 1 h at 37°C, 2x104 Vero E6 cells were added to each well and the plates were incubated at 37°C for 2 days in 5% CO2 before evaluating the cytopathic effect (CPE) via microscopy.
    Vero E6
    suggested: None
    Software and Algorithms
    SentencesResources
    Study data were collected and managed using REDCap electronic data capture tools hosted at Institute for Medical Biometry, Informatics and Epidemiology13, 14. REDCap (Research Electronic Data Capture) is a secure, web-based software platform designed to support data capture for research studies, providing 1) an intuitive interface for validated data capture; 2) audit trails for tracking data manipulation and export procedures; 3) automated export procedures for seamless data downloads to common statistical packages; and 4) procedures for data integration and interoperability with external sources.
    REDCap
    suggested: (REDCap, SCR_003445)
    R Foundation for Statistical Computing, Vienna, Austria) and version 9.4 of the SAS System for Windows (copyright © 2002-2012 by SAS Institute Inc., Cary, NC, USA).
    SAS Institute
    suggested: (Statistical Analysis System, SCR_008567)

    Results from Barzooka: We also found bar graphs of continuous data. We recommend replacing bar graphs with more informative graphics, as many different datasets can lead to the same bar graph. The actual data may suggest different conclusions from the summary statistics. For more information, please see Weissgerber et al (2015).

    Results from OddPub: We did not find a statement about open data. We also did not find a statement about open code. Researchers are encouraged to share open data when possible (see Nature blog).

    About SciScore

    SciScore is an automated tool that is designed to assist expert reviewers by finding and presenting formulaic information scattered throughout a paper in a standard, easy to digest format. SciScore is not a substitute for expert review. SciScore checks for the presence and correctness of RRIDs (research resource identifiers) in the manuscript, and detects sentences that appear to be missing RRIDs. SciScore also checks to make sure that rigor criteria are addressed by authors. It does this by detecting sentences that discuss criteria such as blinding or power analysis. SciScore does not guarantee that the rigor criteria that it detects are appropriate for the particular study. Instead it assists authors, editors, and reviewers by drawing attention to sections of the manuscript that contain or should contain various rigor criteria and key resources. For details on the results shown here, including references cited, please follow this link.

  4. Version published to 10.1101/2020.05.04.20090076 on medRxiv