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Preprint in English | medRxiv | ID: ppmedrxiv-21256133


BackgroundIn the 2nd year of the Covid-19 pandemic, knowledge about the dynamics of the infection in the general population is still limited. Such information is essential for health planners, as many of those infected show no or only mild symptoms and thus, escape the surveillance system. We therefore aimed to describe the course of the pandemic in the Munich general population living in private households from April 2020 to January 2021. MethodsThe KoCo19 baseline study took place from April to June 2020 including 5313 participants (age 14 years and above). From November 2020 to January 2021, we could again measure SARS-CoV-2 antibody status in 4,433 of the baseline participants (response 83%). Participants were offered a self-sampling kit to take a capillary blood sample (dry blood spot; DBS). Blood was analysed using the Elecsys(R) Anti-SARS-CoV-2 assay (Roche). Questionnaire information on socio-demographics and potential risk factors assessed at baseline was available for all participants. In addition, follow-up information on health-risk taking behaviour and number of personal contacts outside the household (N=2768) as well as leisure time activities (N=1263) were collected in summer 2020. ResultsWeighted and adjusted (for specificity and sensitivity) SARS-CoV-2 sero-prevalence at follow-up was 3.6% (95% CI 2.9-4.3%) as compared to 1.8% (95% CI 1.3-3.4%) at baseline. 91% of those tested positive at baseline were also antibody-positive at follow-up. While sero-prevalence increased from early November 2021 to January 2021, no indication of geospatial clustering across the city of Munich was found, although cases clustered within households. Taking baseline result and time to follow-up into account, men and participants in the age group 20-34 years were at the highest risk of sero-positivity. In the sensitivity analyses, differences in health-risk taking behaviour, number of personal contacts and leisure time activities partly explained these differences. ConclusionThe number of citizens in Munich with SARS-CoV-2 antibodies was still below 5% during the 2nd wave of the pandemic. Antibodies remained present in the majority of baseline participants. Besides age and sex, potentially confounded by differences in behaviour, no major risk factors could be identified. Non-pharmaceutical public health measures are thus still important.

Preprint in English | medRxiv | ID: ppmedrxiv-21252080


BackgroundQuantitative serological assays detecting response to SARS-CoV-2 infection are urgently needed to quantify immunity. This study analyzed the performance and correlation of two independent quantitative anti-S1 assays in oligo-/asymptomatic individuals from a previously characterized population-based cohort. MethodsA total of 362 samples included 108 from individuals who had viral RNA detected in pharyngeal swabs, 111 negative controls and 143 samples with positive serology but not confirmed by RT-PCR. Blood plasma was tested with quantitative assays Euroimmun Anti-SARS-CoV-2 QuantiVac ELISA (IgG) (EI-S1-IgG-quant) and Roche Elecsys(R) Anti-SARS-CoV-2 CoV-2 S (Ro-RBD-Ig-quant), which were compared with each other and with confirmatory tests, including wild-type virus micro-neutralization (NT) and GenScript(R)cPass. Results were analyzed using square roots R of coefficients of determination for association among continuous variables and non-parametric tests for paired comparisons. ResultsQuantitative anti-S1 serology correlated well with each other (96%/97% for true-positives and true-negatives, respectively). Antibody titers decreased over time (from <30 days to >240 days after initial positive RT-PCR). Agreement with GenScript-cPass was 96%/99% for true-positives and true-negatives, respectively, for Ro-RBD-Ig-quant and 93%/97% for EI-S1-IgG-quant. Ro-RBD-Ig-quant allowed a distinct separation between positive and negative values, and less non-specific reactivity compared with EI-S1-IgG-quant. Raw values (with 95% CI) [≥]28.7 U/mL (22.6-36.4) for Ro-RBD-Ig-quant and [≥]49.8 U/mL (43.4-57.1) for EI-S1-IgG-quant predicted virus neutralization >1:5 in 95% of cases. ConclusionsBoth quantitative anti-S1 assays, Ro-RBD-Ig-quant and EI-S1-IgG-quant, may replace direct neutralization assays in quantitative measurement of immune protection against SARS-CoV-2 in certain circumstances in the future. Key pointsTwo quantitative anti-S1 assays showed similar performance and a high level of agreement with direct virus neutralization and surrogate neutralization tests, arguing for their utility in quantifying immune protection against SARS-CoV-2.

Preprint in English | medRxiv | ID: ppmedrxiv-21249735


BackgroundSerosurveys are essential to understand SARS-CoV-2 exposure and enable population-level surveillance, but currently available tests need further in-depth evaluation. We aimed to identify testing-strategies by comparing seven seroassays in a population-based cohort. MethodsWe analysed 6,658 samples consisting of true-positives (n=193), true-negatives (n=1,091), and specimens of unknown status (n=5,374). For primary testing, we used Euroimmun-Anti-SARS-CoV-2-ELISA-IgA/IgG and Roche-Elecsys-Anti-SARS-CoV-2; and virus-neutralisation, GeneScript(R)cPass, VIRAMED-SARS-CoV-2-ViraChip(R), and Mikrogen-recomLine-SARS-CoV-2-IgG, including common-cold CoVs, for confirmatory testing. Statistical modelling generated optimised assay cut-off-thresholds. FindingsSensitivity of Euroimmun-anti-S1-IgA was 64.8%, specificity 93.3%; for Euroimmun-anti-S1-IgG, sensitivity was 77.2/79.8% (manufacturers/optimised cut-offs), specificity 98.0/97.8%; Roche-anti-N sensitivity was 85.5/88.6%, specificity 99.8/99.7%. In true-positives, mean and median titres remained stable for at least 90-120 days after RT-PCR-positivity. Of true-positives with positive RT-PCR (<30 days), 6.7% did not mount detectable seroresponses. Virus-neutralisation was 73.8% sensitive, 100.0% specific (1:10 dilution). Neutralisation surrogate tests (GeneScript(R)cPass, Mikrogen-recomLine-RBD) were >94.9% sensitive, >98.1% specific. Seasonality had limited effects; cross-reactivity with common-cold CoVs 229E and NL63 in SARS-CoV-2 true-positives was significant. ConclusionOptimised cut-offs improved test performances of several tests. Non-reactive serology in true-positives was uncommon. For epidemiological purposes, confirmatory testing with virus-neutralisation may be replaced with GeneScript(R)cPass or recomLine-RBD. Head-to-head comparisons given here aim to contribute to the refinement of testing-strategies for individual and public health use.

Preprint in English | medRxiv | ID: ppmedrxiv-20069955


The novel coronavirus (SARS-CoV-2), identified in China at the end of December 2019 and causing the disease COVID-19, has meanwhile led to outbreaks all over the globe with about 2.2 million confirmed cases and more than 150,000 deaths as of April 17, 2020 [37]. In view of most recent information on testing activity [32], we present here an update of our initial work [4]. In this work, mathematical models have been developed to study the spread of COVID-19 among the population in Germany and to asses the impact of non-pharmaceutical interventions. Systems of differential equations of SEIR type are extended here to account for undetected infections, as well as for stages of infections and age groups. The models are calibrated on data until April 5, data from April 6 to 14 are used for model validation. We simulate different possible strategies for the mitigation of the current outbreak, slowing down the spread of the virus and thus reducing the peak in daily diagnosed cases, the demand for hospitalization or intensive care units admissions, and eventually the number of fatalities. Our results suggest that a partial (and gradual) lifting of introduced control measures could soon be possible if accompanied by further increased testing activity, strict isolation of detected cases and reduced contact to risk groups.

Preprint in English | medRxiv | ID: ppmedrxiv-20056630


The novel coronavirus (SARS-CoV-2), identified in China at the end of December 2019 and causing the disease COVID-19, has meanwhile led to outbreaks all over the globe, with about 571,700 confirmed cases and about 26,500 deaths as of March 28th, 2020. We present here the preliminary results of a mathematical study directed at informing on the possible application or lifting of control measures in Germany. The developed mathematical models allow to study the spread of COVID-19 among the population in Germany and to asses the impact of non-pharmaceutical interventions.