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. 2021 Jun 10;13(6):1118.
doi: 10.3390/v13061118.

Estimates and Determinants of SARS-Cov-2 Seroprevalence and Infection Fatality Ratio Using Latent Class Analysis: The Population-Based Tirschenreuth Study in the Hardest-Hit German County in Spring 2020

Ralf Wagner  1   2 , David Peterhoff  1 , Stephanie Beileke  3 , Felix Günther  4   5 , Melanie Berr  1 , Sebastian Einhauser  1 , Anja Schütz  1 , Hans Helmut Niller  1 , Philipp Steininger  3 , Antje Knöll  3 , Matthias Tenbusch  3 , Clara Maier  3 , Klaus Korn  3 , Klaus J Stark  5 , André Gessner  1   2 , Ralph Burkhardt  6 , Michael Kabesch  7 , Holger Schedl  8 , Helmut Küchenhoff  4 , Annette B Pfahlberg  9 , Iris M Heid  5 , Olaf Gefeller  9 , Klaus Überla  3
Affiliations

Estimates and Determinants of SARS-Cov-2 Seroprevalence and Infection Fatality Ratio Using Latent Class Analysis: The Population-Based Tirschenreuth Study in the Hardest-Hit German County in Spring 2020

Ralf Wagner et al. Viruses. .

Abstract

SARS-CoV-2 infection fatality ratios (IFR) remain controversially discussed with implications for political measures. The German county of Tirschenreuth suffered a severe SARS-CoV-2 outbreak in spring 2020, with particularly high case fatality ratio (CFR). To estimate seroprevalence, underreported infections, and IFR for the Tirschenreuth population aged ≥14 years in June/July 2020, we conducted a population-based study including home visits for the elderly, and analyzed 4203 participants for SARS-CoV-2 antibodies via three antibody tests. Latent class analysis yielded 8.6% standardized county-wide seroprevalence, a factor of underreported infections of 5.0, and 2.5% overall IFR. Seroprevalence was two-fold higher among medical workers and one third among current smokers with similar proportions of registered infections. While seroprevalence did not show an age-trend, the factor of underreported infections was 12.2 in the young versus 1.7 for ≥85-year-old. Age-specific IFRs were <0.5% below 60 years of age, 1.0% for age 60-69, and 13.2% for age 70+. Senior care homes accounted for 45% of COVID-19-related deaths, reflected by an IFR of 7.5% among individuals aged 70+ and an overall IFR of 1.4% when excluding senior care home residents from our computation. Our data underscore senior care home infections as key determinant of IFR additionally to age, insufficient targeted testing in the young, and the need for further investigations on behavioral or molecular causes of the fewer infections among current smokers.

Keywords: CLIA; ELISA; SARS-CoV-2; antibodies; infection fatality ratio; latent class analysis; senior care homes; seroprevalence; smoking; underreported infections.

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Conflict of interest statement

The authors declare that no competing interests or conflicts of interest exist. The authors have no financial or proprietary interests in any material discussed in this article.

Figures

Figure 1
Figure 1
Summary of the TiCoKo study design. The strategy and numbers (n) underlying the random sampling and recruitment of study participants, the collection of information via a self-reporting questionnaire as well as the testing strategy to determine the true serostatus of the participants via three independent test formats (Roche-Cobas, in-house ELISA and YHLO) are shown. Measures to minimize and understand non-response are indicated (dashed line), reasons for drop-outs of participants, numbers of returned questionnaires, and successful blood samples are given (grey line). Figure was designed using PowerPoint 365 for Windows, Microsoft, Redmond Washington, DC, USA, www.microsoft.com.
Figure 2
Figure 2
Seroprevalence, factor of underreported infections, and infection fatality ratios overall and by age groups. Standardized seroprevalence (%), dark figure factor and infection fatality ratio (%) in the overall county population (a–c) and the indicated age groups (d–f). Error bars represent 95% confidence intervals (95%-CI), respectively. Figure was designed using GraphPad Prism version 8.4.3 for Windows, GraphPad Software, La Jolla, CA, USA, www.graphpad.com.
Figure 3
Figure 3
Seroprevalence, factor of underreported infections, and infection fatality ratios by municipalities with and without senior care homes. (a) Standardized seroprevalence (%) determined for inhabitants of the local municipalities in county Tirschenreuth. (b–d) Standardized seroprevalence (b), factor of underreported infections (c) and infection fatality ratio (d) in the overall county population, in the population of local municipalities without senior care homes (w/o SCH) and with senior care homes (with SCH). The 95% confidence intervals (95%-CI) are indicated, respectively. Red squares indicate the location of the study test centers, black squares highlight the municipality association of senior care homes. Figure was designed using GraphPad Prism version 8.4.3 for Windows, GraphPad Software, La Jolla, CA, USA, www.graphpad.com, and GIMP 2.10.22 for Windows, The GIMP Development Team, California, USA, www.gimp.org.
Figure 4
Figure 4
Symptoms. Percent individuals of the indicated categories, who developed one or several of the indicated symptoms. Odds ratios, OR, as well as 95%-CI [CI] testing serostatus positive versus serostatus negative (unadjusted) are depicted. Figure was designed using GraphPad Prism version 8.4.3 for Windows, GraphPad Software, La Jolla, CA, USA, www.graphpad.com.
Figure 5
Figure 5
Association of demographic and life style factors with seropositivity. Odds ratios including the 95%-CI are indicated, respectively. p < 0.001 (***). Analysis was conducted in R (R Core Team (2020). R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. URL http://www.R-project.org/). This figure was produced using the package ggplot2 (Wickham, H. (2009) ggplot2: elegant graphics for data analysis. Springer New York).
See this image and copyright information in PMC

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