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Domènech-Montoliu S, Pac-Sa MR, Sala-Trull D, Del Rio-González A, Sanchéz-Urbano M, Satorres-Martinez P, Blasco-Gari R, Casanova-Suarez J, Gil-Fortuño M, López-Diago L, Notari-Rodríguez C, Pérez-Olaso Ó, Romeu-Garcia MA, Ruiz-Puig R, Aleixandre-Gorriz I, Domènech-León C, Arnedo-Pena A. Underreporting of Cases in the COVID-19 Outbreak of Borriana (Spain) during Mass Gathering Events in March 2020: A Cross-Sectional Study. EPIDEMIOLOGIA 2024; 5:499-510. [PMID: 39189253 PMCID: PMC11348374 DOI: 10.3390/epidemiologia5030034] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/25/2024] [Revised: 08/02/2024] [Accepted: 08/06/2024] [Indexed: 08/28/2024] Open
Abstract
Determining the number of cases of an epidemic is the first function of epidemiological surveillance. An important underreporting of cases was observed in many locations during the first wave of the COVID-19 pandemic. To estimate this underreporting in the COVID-19 outbreak of Borriana (Valencia Community, Spain) in March 2020, a cross-sectional study was performed in June 2020 querying the public health register. Logistic regression models were used. Of a total of 468 symptomatic COVID-19 cases diagnosed in the outbreak through anti-SARS-CoV-2 serology, 36 cases were reported (7.7%), resulting in an underreporting proportion of 92.3% (95% confidence interval [CI], 89.5-94.6%), with 13 unreported cases for every reported case. Only positive SARS-CoV-2 polymerase chain reaction cases were predominantly reported due to a limited testing capacity and following a national protocol. Significant factors associated with underreporting included no medical assistance for COVID-19 disease, with an adjusted odds ratio [aOR] of 10.83 (95% CI 2.49-47.11); no chronic illness, aOR = 2.81 (95% CI 1.28-6.17); middle and lower social classes, aOR = 3.12 (95% CI 1.42-6.85); younger age, aOR = 0.97 (95% CI 0.94-0.99); and a shorter duration of illness, aOR = 0.98 (95% CI 0.97-0.99). To improve the surveillance of future epidemics, new approaches are recommended.
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Affiliation(s)
| | - Maria Rosario Pac-Sa
- Public Health Center, 12003 Castelló de la Plana, Spain; (M.R.P.-S.); (M.A.R.-G.)
| | - Diego Sala-Trull
- Emergency Service University Hospital de la Plana, 12540 Vila-Real, Spain; (D.S.-T.); (M.S.-U.); (P.S.-M.); (R.B.-G.); (C.N.-R.); (R.R.-P.)
| | | | - Manuel Sanchéz-Urbano
- Emergency Service University Hospital de la Plana, 12540 Vila-Real, Spain; (D.S.-T.); (M.S.-U.); (P.S.-M.); (R.B.-G.); (C.N.-R.); (R.R.-P.)
| | - Paloma Satorres-Martinez
- Emergency Service University Hospital de la Plana, 12540 Vila-Real, Spain; (D.S.-T.); (M.S.-U.); (P.S.-M.); (R.B.-G.); (C.N.-R.); (R.R.-P.)
| | - Roser Blasco-Gari
- Emergency Service University Hospital de la Plana, 12540 Vila-Real, Spain; (D.S.-T.); (M.S.-U.); (P.S.-M.); (R.B.-G.); (C.N.-R.); (R.R.-P.)
| | | | - Maria Gil-Fortuño
- Microbiology Service University Hospital de la Plana, 12540 Vila-Real, Spain; (M.G.-F.); (Ó.P.-O.)
| | - Laura López-Diago
- Clinical Analysis Service University Hospital de la Plana, 12540 Vila-Real, Spain; (L.L.-D.); (I.A.-G.)
| | - Cristina Notari-Rodríguez
- Emergency Service University Hospital de la Plana, 12540 Vila-Real, Spain; (D.S.-T.); (M.S.-U.); (P.S.-M.); (R.B.-G.); (C.N.-R.); (R.R.-P.)
| | - Óscar Pérez-Olaso
- Microbiology Service University Hospital de la Plana, 12540 Vila-Real, Spain; (M.G.-F.); (Ó.P.-O.)
| | | | - Raquel Ruiz-Puig
- Emergency Service University Hospital de la Plana, 12540 Vila-Real, Spain; (D.S.-T.); (M.S.-U.); (P.S.-M.); (R.B.-G.); (C.N.-R.); (R.R.-P.)
| | - Isabel Aleixandre-Gorriz
- Clinical Analysis Service University Hospital de la Plana, 12540 Vila-Real, Spain; (L.L.-D.); (I.A.-G.)
| | - Carmen Domènech-León
- Department of Medicine, University CEU Cardenal Herrera, 12006 Castelló de la Plana, Spain;
| | - Alberto Arnedo-Pena
- Public Health Center, 12003 Castelló de la Plana, Spain; (M.R.P.-S.); (M.A.R.-G.)
- Department of Health Science, Public University Navarra, 31006 Pamplona, Spain
- Epidemiology and Public Health (CIBERESP), 28029 Madrid, Spain
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2
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Ahmed MI, Einhauser S, Peiter C, Senninger A, Baranov O, Eser TM, Huth M, Olbrich L, Castelletti N, Rubio-Acero R, Carnell G, Heeney J, Kroidl I, Held K, Wieser A, Janke C, Hoelscher M, Hasenauer J, Wagner R, Geldmacher C. Evolution of protective SARS-CoV-2-specific B and T cell responses upon vaccination and Omicron breakthrough infection. iScience 2024; 27:110138. [PMID: 38974469 PMCID: PMC11225850 DOI: 10.1016/j.isci.2024.110138] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/06/2023] [Revised: 03/21/2024] [Accepted: 05/27/2024] [Indexed: 07/09/2024] Open
Abstract
Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) Omicron breakthrough infection (BTI) induced better protection than triple vaccination. To address the underlying immunological mechanisms, we studied antibody and T cell response dynamics during vaccination and after BTI. Each vaccination significantly increased peak neutralization titers with simultaneous increases in circulating spike-specific T cell frequencies. Neutralization titers significantly associated with a reduced hazard rate for SARS-CoV-2 infection. Yet, 97% of triple vaccinees became SARS-CoV-2 infected. BTI further boosted neutralization magnitude and breadth, broadened virus-specific T cell responses to non-vaccine-encoded antigens, and protected with an efficiency of 88% from further infections by December 2022. This effect was then assessed by utilizing mathematical modeling, which accounted for time-dependent infection risk, the antibody, and T cell concentration at any time point after BTI. Our findings suggest that cross-variant protective hybrid immunity induced by vaccination and BTI was an important contributor to the reduced virus transmission observed in Bavaria in late 2022 and thereafter.
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Affiliation(s)
- Mohamed I.M. Ahmed
- Division of Infectious Diseases and Tropical Medicine, University Hospital, LMU Munich, 80799 Munich, Germany
- German Centre for Infection Research (DZIF), Partner Site Munich, Munich, Germany
| | - Sebastian Einhauser
- Institute for Medical Microbiology and Hygiene, University of Regensburg, 93053 Regensburg, Germany
| | - Clemens Peiter
- Faculty of Mathematics and Natural Sciences, University of Bonn, 53113 Bonn, Germany
| | - Antonia Senninger
- Institute for Medical Microbiology and Hygiene, University of Regensburg, 93053 Regensburg, Germany
| | - Olga Baranov
- Division of Infectious Diseases and Tropical Medicine, University Hospital, LMU Munich, 80799 Munich, Germany
- German Centre for Infection Research (DZIF), Partner Site Munich, Munich, Germany
| | - Tabea M. Eser
- Division of Infectious Diseases and Tropical Medicine, University Hospital, LMU Munich, 80799 Munich, Germany
- German Centre for Infection Research (DZIF), Partner Site Munich, Munich, Germany
- Fraunhofer Institute for Translational Medicine and Pharmacology ITMP, Immunology, Infection and Pandemic Research, 80799 Munich, Germany
| | - Manuel Huth
- Faculty of Mathematics and Natural Sciences, University of Bonn, 53113 Bonn, Germany
- Institute of Computational Biology, Helmholtz Zentrum München – German Research Center for Environmental Health, 85764 Neuherberg, Germany
| | - Laura Olbrich
- Division of Infectious Diseases and Tropical Medicine, University Hospital, LMU Munich, 80799 Munich, Germany
- German Centre for Infection Research (DZIF), Partner Site Munich, Munich, Germany
| | - Noemi Castelletti
- Division of Infectious Diseases and Tropical Medicine, University Hospital, LMU Munich, 80799 Munich, Germany
| | - Raquel Rubio-Acero
- Division of Infectious Diseases and Tropical Medicine, University Hospital, LMU Munich, 80799 Munich, Germany
| | - George Carnell
- Lab of Viral Zoonotics, Department of Veterinary Medicine, University of Cambridge, Cambridge, UK
| | - Jonathan Heeney
- Lab of Viral Zoonotics, Department of Veterinary Medicine, University of Cambridge, Cambridge, UK
| | - Inge Kroidl
- Division of Infectious Diseases and Tropical Medicine, University Hospital, LMU Munich, 80799 Munich, Germany
- German Centre for Infection Research (DZIF), Partner Site Munich, Munich, Germany
| | - Kathrin Held
- Division of Infectious Diseases and Tropical Medicine, University Hospital, LMU Munich, 80799 Munich, Germany
- German Centre for Infection Research (DZIF), Partner Site Munich, Munich, Germany
| | - Andreas Wieser
- Division of Infectious Diseases and Tropical Medicine, University Hospital, LMU Munich, 80799 Munich, Germany
- German Centre for Infection Research (DZIF), Partner Site Munich, Munich, Germany
- Fraunhofer Institute for Translational Medicine and Pharmacology ITMP, Immunology, Infection and Pandemic Research, 80799 Munich, Germany
| | - Christian Janke
- Division of Infectious Diseases and Tropical Medicine, University Hospital, LMU Munich, 80799 Munich, Germany
| | - Michael Hoelscher
- Division of Infectious Diseases and Tropical Medicine, University Hospital, LMU Munich, 80799 Munich, Germany
- German Centre for Infection Research (DZIF), Partner Site Munich, Munich, Germany
- Fraunhofer Institute for Translational Medicine and Pharmacology ITMP, Immunology, Infection and Pandemic Research, 80799 Munich, Germany
- Unit Global Health, Helmholtz Zentrum München, German Research Center for Environmental Health (HMGU), 85764 Neuherberg, Germany
| | - Jan Hasenauer
- Faculty of Mathematics and Natural Sciences, University of Bonn, 53113 Bonn, Germany
- Institute of Computational Biology, Helmholtz Zentrum München – German Research Center for Environmental Health, 85764 Neuherberg, Germany
- Center for Mathematics, Technische Universität München, 85748 Garching, Germany
| | - Ralf Wagner
- Institute for Medical Microbiology and Hygiene, University of Regensburg, 93053 Regensburg, Germany
- Institute of Clinical Microbiology and Hygiene, University Hospital Regensburg, 93053 Regensburg, Germany
| | - Christof Geldmacher
- Division of Infectious Diseases and Tropical Medicine, University Hospital, LMU Munich, 80799 Munich, Germany
- German Centre for Infection Research (DZIF), Partner Site Munich, Munich, Germany
- Fraunhofer Institute for Translational Medicine and Pharmacology ITMP, Immunology, Infection and Pandemic Research, 80799 Munich, Germany
| | - on behalf of the KoCo19/ORCHESTRA working group
- Division of Infectious Diseases and Tropical Medicine, University Hospital, LMU Munich, 80799 Munich, Germany
- German Centre for Infection Research (DZIF), Partner Site Munich, Munich, Germany
- Institute for Medical Microbiology and Hygiene, University of Regensburg, 93053 Regensburg, Germany
- Faculty of Mathematics and Natural Sciences, University of Bonn, 53113 Bonn, Germany
- Fraunhofer Institute for Translational Medicine and Pharmacology ITMP, Immunology, Infection and Pandemic Research, 80799 Munich, Germany
- Institute of Computational Biology, Helmholtz Zentrum München – German Research Center for Environmental Health, 85764 Neuherberg, Germany
- Lab of Viral Zoonotics, Department of Veterinary Medicine, University of Cambridge, Cambridge, UK
- Unit Global Health, Helmholtz Zentrum München, German Research Center for Environmental Health (HMGU), 85764 Neuherberg, Germany
- Center for Mathematics, Technische Universität München, 85748 Garching, Germany
- Institute of Clinical Microbiology and Hygiene, University Hospital Regensburg, 93053 Regensburg, Germany
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Sbierski-Kind J, Schlickeiser S, Feldmann S, Ober V, Grüner E, Pleimelding C, Gilberg L, Brand I, Weigl N, Ahmed MIM, Ibarra G, Ruzicka M, Benesch C, Pernpruner A, Valdinoci E, Hoelscher M, Adorjan K, Stubbe HC, Pritsch M, Seybold U, Roider J. Persistent immune abnormalities discriminate post-COVID syndrome from convalescence. Infection 2024; 52:1087-1097. [PMID: 38326527 PMCID: PMC11142964 DOI: 10.1007/s15010-023-02164-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/13/2023] [Accepted: 12/19/2023] [Indexed: 02/09/2024]
Abstract
BACKGROUND Innate lymphoid cells (ILCs) are key organizers of tissue immune responses and regulate tissue development, repair, and pathology. Persistent clinical sequelae beyond 12 weeks following acute COVID-19 disease, named post-COVID syndrome (PCS), are increasingly recognized in convalescent individuals. ILCs have been associated with the severity of COVID-19 symptoms but their role in the development of PCS remains poorly defined. METHODS AND RESULTS Here, we used multiparametric immune phenotyping, finding expanded circulating ILC precursors (ILCPs) and concurrent decreased group 2 innate lymphoid cells (ILC2s) in PCS patients compared to well-matched convalescent control groups at > 3 months after infection or healthy controls. Patients with PCS showed elevated expression of chemokines and cytokines associated with trafficking of immune cells (CCL19/MIP-3b, FLT3-ligand), endothelial inflammation and repair (CXCL1, EGF, RANTES, IL-1RA, PDGF-AA). CONCLUSION These results define immunological parameters associated with PCS and might help find biomarkers and disease-relevant therapeutic strategies.
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Affiliation(s)
- Julia Sbierski-Kind
- Department of Medicine IV, University Hospital, Ludwig-Maximilians-Universität München, Munich, Germany
- Department of Internal Medicine IV, Division of Diabetology, Endocrinology and Nephrology, University Hospital, Eberhard-Karls-Universität Tübingen, Tübingen, Germany
- The M3 Research Center, University Clinic Tübingen (UKT), Medical Faculty, Otfried-Müllerstr. 37, Tübingen, Germany
| | - Stephan Schlickeiser
- Charité, Universitätsmedizin Berlin, Freie Universität Berlin and Humboldt- Universität Zu Berlin, Institute of Medical Immunology, Augustenburger Platz 1, 13353, Berlin, Germany
- Berlin Institute of Health (BIH) at Charité, Universitätsmedizin Berlin, BIH Center for Regenerative Therapies (BCRT), Charitéplatz 1, 10117, Berlin, Germany
| | - Svenja Feldmann
- Department of Infectious Diseases, Department of Medicine IV, University Hospital, Ludwig-Maximilians-Universität München, Munich, Germany
| | - Veronica Ober
- Department of Infectious Diseases, Department of Medicine IV, University Hospital, Ludwig-Maximilians-Universität München, Munich, Germany
| | - Eva Grüner
- Department of Infectious Diseases, Department of Medicine IV, University Hospital, Ludwig-Maximilians-Universität München, Munich, Germany
| | - Claire Pleimelding
- Department of Infectious Diseases, Department of Medicine IV, University Hospital, Ludwig-Maximilians-Universität München, Munich, Germany
| | - Leonard Gilberg
- Department of Infectious Diseases, Department of Medicine IV, University Hospital, Ludwig-Maximilians-Universität München, Munich, Germany
| | - Isabel Brand
- German Center for Infection Research (DZIF), Partner Site Munich, Munich, Germany
| | - Nikolas Weigl
- Department of Medicine IV, Division of Clinical Pharmacology, University Hospital, Ludwig-Maximilians-Universität München, Munich, Germany
| | - Mohamed I M Ahmed
- German Center for Infection Research (DZIF), Partner Site Munich, Munich, Germany
- Division of Infectious Diseases and Tropical Medicine, University Hospital, Ludwig-Maximilians-Universität München, Munich, Germany
| | - Gerardo Ibarra
- The M3 Research Center, University Clinic Tübingen (UKT), Medical Faculty, Otfried-Müllerstr. 37, Tübingen, Germany
- COVID-19 Registry of the LMU Munich (CORKUM), University Hospital, Ludwig-Maximilians-Universität München, Munich, Germany
| | - Michael Ruzicka
- COVID-19 Registry of the LMU Munich (CORKUM), University Hospital, Ludwig-Maximilians-Universität München, Munich, Germany
- Department of Medicine III, LMU University Hospital, LMU Munich, Munich, Germany
| | - Christopher Benesch
- COVID-19 Registry of the LMU Munich (CORKUM), University Hospital, Ludwig-Maximilians-Universität München, Munich, Germany
- Department of Medicine II, University Hospital, Ludwig-Maximilians-Universität München, Munich, Germany
| | - Anna Pernpruner
- COVID-19 Registry of the LMU Munich (CORKUM), University Hospital, Ludwig-Maximilians-Universität München, Munich, Germany
- Department of Medicine II, University Hospital, Ludwig-Maximilians-Universität München, Munich, Germany
| | - Elisabeth Valdinoci
- COVID-19 Registry of the LMU Munich (CORKUM), University Hospital, Ludwig-Maximilians-Universität München, Munich, Germany
- Department of Medicine II, University Hospital, Ludwig-Maximilians-Universität München, Munich, Germany
| | - Michael Hoelscher
- German Center for Infection Research (DZIF), Partner Site Munich, Munich, Germany
- Division of Infectious Diseases and Tropical Medicine, University Hospital, Ludwig-Maximilians-Universität München, Munich, Germany
| | - Kristina Adorjan
- COVID-19 Registry of the LMU Munich (CORKUM), University Hospital, Ludwig-Maximilians-Universität München, Munich, Germany
- Department of Psychiatry and Psychotherapy, University Hospital, Ludwig-Maximilians-Universität München, Munich, Germany
| | - Hans Christian Stubbe
- German Center for Infection Research (DZIF), Partner Site Munich, Munich, Germany
- COVID-19 Registry of the LMU Munich (CORKUM), University Hospital, Ludwig-Maximilians-Universität München, Munich, Germany
- Department of Medicine II, University Hospital, Ludwig-Maximilians-Universität München, Munich, Germany
| | - Michael Pritsch
- German Center for Infection Research (DZIF), Partner Site Munich, Munich, Germany
- Division of Infectious Diseases and Tropical Medicine, University Hospital, Ludwig-Maximilians-Universität München, Munich, Germany
| | - Ulrich Seybold
- Department of Infectious Diseases, Department of Medicine IV, University Hospital, Ludwig-Maximilians-Universität München, Munich, Germany
| | - Julia Roider
- Department of Infectious Diseases, Department of Medicine IV, University Hospital, Ludwig-Maximilians-Universität München, Munich, Germany.
- German Center for Infection Research (DZIF), Partner Site Munich, Munich, Germany.
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4
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Kulmala I, Taipale A, Sanmark E, Lastovets N, Sormunen P, Nuorti P, Saari S, Luoto A, Säämänen A. Estimated relative potential for airborne SARS-CoV-2 transmission in a day care centre. Heliyon 2024; 10:e30724. [PMID: 38756615 PMCID: PMC11096945 DOI: 10.1016/j.heliyon.2024.e30724] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/20/2023] [Revised: 05/01/2024] [Accepted: 05/02/2024] [Indexed: 05/18/2024] Open
Abstract
We estimated the hourly probability of airborne severe acute respiratory coronavirus 2 (SARS-CoV-2) transmission and further the estimated number of persons at transmission risk in a day care centre by calculating the inhaled dose for airborne pathogens based on their concentration, exposure time and activity. Information about the occupancy and activity of the rooms was collected from day care centre personnel and building characteristics were obtained from the design values. The generation rate of pathogens was calculated as a product of viral load of the respiratory fluids and the emission of the exhaled airborne particles, considering the prevalence of the disease and the activity of the individuals. A well-mixed model was used in the estimation of the concentration of pathogens in the air. The Wells-Riley model was used for infection probability. The approach presented in this study was utilised in the identification of hot spots and critical events in the day care centre. Large variation in the infection probabilities and estimated number of persons at transmission risk was observed when modelling a normal day at the centre. The estimated hourly infection probabilities between the worst hour in the worst room and the best hour in the best room varied in the ratio of 100:1. Similarly, the number of persons at transmission risk between the worst and best cases varied in the ratio 1000:1. Although there are uncertainties in the input values affecting the absolute risk estimates the model proved to be useful in ranking and identifying the hot spots and events in the building and implementing effective control measures.
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Affiliation(s)
- Ilpo Kulmala
- VTT Smart Energy and Built Environment, Visiokatu 4, PO Box 1300, FI-33101, Tampere, Finland
| | - Aimo Taipale
- VTT Smart Energy and Built Environment, Visiokatu 4, PO Box 1300, FI-33101, Tampere, Finland
| | - Enni Sanmark
- Helsinki University Hospital, Department of Otorhinolaryngology and Phoniatrics – Head and Neck Surgery, Helsinki, Finland
- University of Helsinki, Helsinki, Finland
| | - Natalia Lastovets
- Tampere University, Faculty of Built Environment, Civil Engineering Unit, Korkeakoulunkatu 5D, FI-33720, Tampere, Finland
| | - Piia Sormunen
- Tampere University, Faculty of Built Environment, Civil Engineering Unit, Korkeakoulunkatu 5D, FI-33720, Tampere, Finland
| | - Pekka Nuorti
- Tampere University, Faculty of Social Sciences, Health Sciences Unit, Arvo Ylpön Katu 34, 33520, Tampere, Finland
| | - Sampo Saari
- Tampere University of Applied Sciences, Kuntokatu 3, 33520, Tampere, Finland
| | - Anni Luoto
- Granlund Oy, Malminkaari 21, 00700, Helsinki, Finland
| | - Arto Säämänen
- VTT Smart Energy and Built Environment, Visiokatu 4, PO Box 1300, FI-33101, Tampere, Finland
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5
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Castelletti N, Paunovic I, Rubio-Acero R, Beyerl J, Plank M, Reinkemeyer C, Kroidl I, Noreña I, Winter S, Olbrich L, Janke C, Hoelscher M, Wieser A. A Dried Blood Spot protocol for high-throughput quantitative analysis of SARS-CoV-2 RBD serology based on the Roche Elecsys system. Microbiol Spectr 2024; 12:e0288523. [PMID: 38426747 PMCID: PMC10986497 DOI: 10.1128/spectrum.02885-23] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/18/2023] [Accepted: 11/15/2023] [Indexed: 03/02/2024] Open
Abstract
SARS-CoV-2 spreads pandemically since 2020; in 2021, effective vaccinations became available and vaccination campaigns commenced. Still, it is hard to track the spread of the infection or to assess vaccination success in the broader population. Measuring specific anti-SARS-CoV-2 antibodies is the most effective tool to track the spread of the infection or successful vaccinations. The need for venous-blood sampling however poses a significant barrier for large studies. Dried-blood-spots on filter-cards (DBS) have been used for SARS-CoV-2 serology in our laboratory, but so far not to follow quantitative SARS-CoV-2 anti-spike reactivity in a longitudinal cohort. We developed a semi-automated protocol or quantitative SARS-CoV-2 anti-spike serology from self-sampled DBS, validating it in a cohort of matched DBS and venous-blood samples (n = 825). We investigated chromatographic effects, reproducibility, and carry-over effects and calculated a positivity threshold as well as a conversion formula to determine the quantitative binding units in the DBS with confidence intervals. Sensitivity and specificity reached 96.63% and 97.81%, respectively, compared to the same test performed in paired venous samples. Between a signal of 0.018 and 250 U/mL, we calculated a correction formula. Measuring longitudinal samples during vaccinations, we demonstrated relative changes in titers over time in several individuals and in a longitudinal cohort over four follow-ups. DBS sampling has proven itself for anti-nucleocapsid serosurveys in our laboratory. Similarly, anti-spike high-throughput DBS serology is feasible as a complementary assay. Quantitative measurements are accurate enough to follow titer dynamics in populations also after vaccination campaigns. This work was supported by the Bavarian State Ministry of Science and the Arts; LMU University Hospital, LMU Munich; Helmholtz Center Munich; University of Bonn; University of Bielefeld; German Ministry for Education and Research (proj. nr.: 01KI20271 and others) and the Medical Biodefense Research Program of the Bundeswehr Medical Service. Roche Diagnostics provided kits and machines for analyses at discounted rates. The project is funded also by the European-wide Consortium ORCHESTRA. The ORCHESTRA project has received funding from the European Union's Horizon 2020 research and innovation program under grant agreement No 101016167. The views expressed in this publication are the sole responsibility of the author, and the Commission is not responsible for any use that may be made of the information it contains.IMPORTANCESARS-CoV-2 has been spreading globally as a pandemic since 2020. To determine the prevalence of SARS-CoV-2 antibodies among populations, the most effective public health tool is measuring specific anti-SARS-CoV-2 antibodies induced by infection or vaccination. However, conducting large-scale studies that involve venous-blood sampling is challenging due to the associated feasibility and cost issues. A more cost-efficient and less invasive method for SARS-CoV-2 serological testing is using Dried-Blood-Spots on filter cards (DBS). In this paper, we have developed a semi-automated protocol for quantifying SARS-CoV-2 anti-spike antibodies from self-collected DBS. Our laboratory has previously successfully used DBS sampling for anti-nucleocapsid antibody surveys. Likewise, conducting high-throughput DBS serology for anti-spike antibodies is feasible as an additional test that can be performed using the same sample preparation as the anti-nucleocapsid analysis. The quantitative measurements obtained are accurate enough to track the dynamics of antibody levels in populations, even after vaccination campaigns.
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Affiliation(s)
- Noemi Castelletti
- Division of Infectious Diseases and Tropical Medicine, LMU University Hospital, LMU Munich, Munich, Germany
- Institute of Radiation Medicine, Helmholtz Zentrum München, Neuherberg, Germany
- Fraunhofer Institute for Translational Medicine and Pharmacology ITMP, Immunology, Infection and Pandemic Research, Munich, Germany
| | - Ivana Paunovic
- Division of Infectious Diseases and Tropical Medicine, LMU University Hospital, LMU Munich, Munich, Germany
- Fraunhofer Institute for Translational Medicine and Pharmacology ITMP, Immunology, Infection and Pandemic Research, Munich, Germany
- Max-von-Pettenkofer Institute, LMU Munich, Munich, Germany
| | - Raquel Rubio-Acero
- Division of Infectious Diseases and Tropical Medicine, LMU University Hospital, LMU Munich, Munich, Germany
| | - Jessica Beyerl
- Division of Infectious Diseases and Tropical Medicine, LMU University Hospital, LMU Munich, Munich, Germany
- Fraunhofer Institute for Translational Medicine and Pharmacology ITMP, Immunology, Infection and Pandemic Research, Munich, Germany
- Max-von-Pettenkofer Institute, LMU Munich, Munich, Germany
| | - Michael Plank
- Division of Infectious Diseases and Tropical Medicine, LMU University Hospital, LMU Munich, Munich, Germany
| | - Christina Reinkemeyer
- Division of Infectious Diseases and Tropical Medicine, LMU University Hospital, LMU Munich, Munich, Germany
| | - Inge Kroidl
- Division of Infectious Diseases and Tropical Medicine, LMU University Hospital, LMU Munich, Munich, Germany
- German Center for Infection Research (DZIF), partner site Munich, Munich, Germany
| | - Ivan Noreña
- Division of Infectious Diseases and Tropical Medicine, LMU University Hospital, LMU Munich, Munich, Germany
| | - Simon Winter
- Division of Infectious Diseases and Tropical Medicine, LMU University Hospital, LMU Munich, Munich, Germany
- Fraunhofer Institute for Translational Medicine and Pharmacology ITMP, Immunology, Infection and Pandemic Research, Munich, Germany
| | - Laura Olbrich
- Division of Infectious Diseases and Tropical Medicine, LMU University Hospital, LMU Munich, Munich, Germany
- Fraunhofer Institute for Translational Medicine and Pharmacology ITMP, Immunology, Infection and Pandemic Research, Munich, Germany
- German Center for Infection Research (DZIF), partner site Munich, Munich, Germany
| | - Christian Janke
- Division of Infectious Diseases and Tropical Medicine, LMU University Hospital, LMU Munich, Munich, Germany
| | - Michael Hoelscher
- Division of Infectious Diseases and Tropical Medicine, LMU University Hospital, LMU Munich, Munich, Germany
- Fraunhofer Institute for Translational Medicine and Pharmacology ITMP, Immunology, Infection and Pandemic Research, Munich, Germany
- German Center for Infection Research (DZIF), partner site Munich, Munich, Germany
- Center for International Health (CIH), University Hospital, LMU Munich, Munich, Germany
| | - Andreas Wieser
- Division of Infectious Diseases and Tropical Medicine, LMU University Hospital, LMU Munich, Munich, Germany
- Fraunhofer Institute for Translational Medicine and Pharmacology ITMP, Immunology, Infection and Pandemic Research, Munich, Germany
- Max-von-Pettenkofer Institute, LMU Munich, Munich, Germany
- German Center for Infection Research (DZIF), partner site Munich, Munich, Germany
| | - on behalf of the KoCo19/ORCHESTRA Working group
- Division of Infectious Diseases and Tropical Medicine, LMU University Hospital, LMU Munich, Munich, Germany
- Institute of Radiation Medicine, Helmholtz Zentrum München, Neuherberg, Germany
- Fraunhofer Institute for Translational Medicine and Pharmacology ITMP, Immunology, Infection and Pandemic Research, Munich, Germany
- Max-von-Pettenkofer Institute, LMU Munich, Munich, Germany
- German Center for Infection Research (DZIF), partner site Munich, Munich, Germany
- Center for International Health (CIH), University Hospital, LMU Munich, Munich, Germany
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6
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Reinkemeyer C, Khazaei Y, Weigert M, Hannes M, Le Gleut R, Plank M, Winter S, Noreña I, Meier T, Xu L, Rubio-Acero R, Wiegrebe S, Le Thi TG, Fuchs C, Radon K, Paunovic I, Janke C, Wieser A, Küchenhoff H, Hoelscher M, Castelletti N. The Prospective COVID-19 Post-Immunization Serological Cohort in Munich (KoCo-Impf): Risk Factors and Determinants of Immune Response in Healthcare Workers. Viruses 2023; 15:1574. [PMID: 37515259 PMCID: PMC10383736 DOI: 10.3390/v15071574] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/14/2023] [Revised: 07/11/2023] [Accepted: 07/15/2023] [Indexed: 07/30/2023] Open
Abstract
Antibody studies analyze immune responses to SARS-CoV-2 vaccination and infection, which is crucial for selecting vaccination strategies. In the KoCo-Impf study, conducted between 16 June and 16 December 2021, 6088 participants aged 18 and above from Munich were recruited to monitor antibodies, particularly in healthcare workers (HCWs) at higher risk of infection. Roche Elecsys® Anti-SARS-CoV-2 assays on dried blood spots were used to detect prior infections (anti-Nucleocapsid antibodies) and to indicate combinations of vaccinations/infections (anti-Spike antibodies). The anti-Spike seroprevalence was 94.7%, whereas, for anti-Nucleocapsid, it was only 6.9%. HCW status and contact with SARS-CoV-2-positive individuals were identified as infection risk factors, while vaccination and current smoking were associated with reduced risk. Older age correlated with higher anti-Nucleocapsid antibody levels, while vaccination and current smoking decreased the response. Vaccination alone or combined with infection led to higher anti-Spike antibody levels. Increasing time since the second vaccination, advancing age, and current smoking reduced the anti-Spike response. The cumulative number of cases in Munich affected the anti-Spike response over time but had no impact on anti-Nucleocapsid antibody development/seropositivity. Due to the significantly higher infection risk faced by HCWs and the limited number of significant risk factors, it is suggested that all HCWs require protection regardless of individual traits.
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Affiliation(s)
- Christina Reinkemeyer
- Division of Infectious Diseases and Tropical Medicine, LMU University Hospital, LMU Munich, 80802 Munich, Germany
| | - Yeganeh Khazaei
- Statistical Consulting Unit StaBLab, Department of Statistics, LMU Munich, Ludwigstraße 33, 80539 Munich, Germany
| | - Maximilian Weigert
- Statistical Consulting Unit StaBLab, Department of Statistics, LMU Munich, Ludwigstraße 33, 80539 Munich, Germany
- Munich Center for Machine Learning (MCML), 80539 Munich, Germany
| | - Marlene Hannes
- Division of Infectious Diseases and Tropical Medicine, LMU University Hospital, LMU Munich, 80802 Munich, Germany
| | - Ronan Le Gleut
- Institute of Computational Biology, Helmholtz Munich, 85764 Neuherberg, Germany
- Core Facility Statistical Consulting, Helmholtz Munich, 85764 Neuherberg, Germany
| | - Michael Plank
- Division of Infectious Diseases and Tropical Medicine, LMU University Hospital, LMU Munich, 80802 Munich, Germany
| | - Simon Winter
- Division of Infectious Diseases and Tropical Medicine, LMU University Hospital, LMU Munich, 80802 Munich, Germany
| | - Ivan Noreña
- Division of Infectious Diseases and Tropical Medicine, LMU University Hospital, LMU Munich, 80802 Munich, Germany
| | - Theresa Meier
- Statistical Consulting Unit StaBLab, Department of Statistics, LMU Munich, Ludwigstraße 33, 80539 Munich, Germany
| | - Lisa Xu
- Statistical Consulting Unit StaBLab, Department of Statistics, LMU Munich, Ludwigstraße 33, 80539 Munich, Germany
| | - Raquel Rubio-Acero
- Division of Infectious Diseases and Tropical Medicine, LMU University Hospital, LMU Munich, 80802 Munich, Germany
| | - Simon Wiegrebe
- Statistical Consulting Unit StaBLab, Department of Statistics, LMU Munich, Ludwigstraße 33, 80539 Munich, Germany
- Department of Genetic Epidemiology, University of Regensburg, 93053 Regensburg, Germany
| | - Thu Giang Le Thi
- Department of Pediatrics, Dr. von Hauner Children's Hospital, University Hospital, LMU Munich, Lindwurmstrasse 4, 80337 Munich, Germany
| | - Christiane Fuchs
- Institute of Computational Biology, Helmholtz Munich, 85764 Neuherberg, Germany
- Core Facility Statistical Consulting, Helmholtz Munich, 85764 Neuherberg, Germany
- Faculty of Business Administration and Economics, Bielefeld University, 33615 Bielefeld, Germany
- Center for Mathematics, Technische Universität München, 85748 Garching, Germany
| | - Katja Radon
- Institute and Outpatient Clinic for Occupational, Social and Environmental Medicine, University Hospital, LMU Munich, 80336 Munich, Germany
- Center for International Health (CIH), University Hospital, LMU Munich, 80336 Munich, Germany
- Comprehensive Pneumology Center (CPC) Munich, German Center for Lung Research (DZL), 89337 Munich, Germany
| | - Ivana Paunovic
- Division of Infectious Diseases and Tropical Medicine, LMU University Hospital, LMU Munich, 80802 Munich, Germany
| | - Christian Janke
- Division of Infectious Diseases and Tropical Medicine, LMU University Hospital, LMU Munich, 80802 Munich, Germany
| | - Andreas Wieser
- Division of Infectious Diseases and Tropical Medicine, LMU University Hospital, LMU Munich, 80802 Munich, Germany
- German Center for Infection Research (DZIF), Partner Site Munich, 80802 Munich, Germany
- Fraunhofer Institute for Translational Medicine and Pharmacology ITMP, Immunology, Infection and Pandemic Research, 80799 Munich, Germany
- Max von Pettenkofer Institute, Faculty of Medicine, LMU Munich, 80336 Munich, Germany
| | - Helmut Küchenhoff
- Statistical Consulting Unit StaBLab, Department of Statistics, LMU Munich, Ludwigstraße 33, 80539 Munich, Germany
| | - Michael Hoelscher
- Division of Infectious Diseases and Tropical Medicine, LMU University Hospital, LMU Munich, 80802 Munich, Germany
- Center for International Health (CIH), University Hospital, LMU Munich, 80336 Munich, Germany
- German Center for Infection Research (DZIF), Partner Site Munich, 80802 Munich, Germany
- Fraunhofer Institute for Translational Medicine and Pharmacology ITMP, Immunology, Infection and Pandemic Research, 80799 Munich, Germany
| | - Noemi Castelletti
- Division of Infectious Diseases and Tropical Medicine, LMU University Hospital, LMU Munich, 80802 Munich, Germany
- Fraunhofer Institute for Translational Medicine and Pharmacology ITMP, Immunology, Infection and Pandemic Research, 80799 Munich, Germany
- Institute of Radiation Medicine, Helmholtz Zentrum München, 85764 Neuherberg, Germany
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Le Gleut R, Plank M, Pütz P, Radon K, Bakuli A, Rubio-Acero R, Paunovic I, Rieß F, Winter S, Reinkemeyer C, Schälte Y, Olbrich L, Hannes M, Kroidl I, Noreña I, Janke C, Wieser A, Hoelscher M, Fuchs C, Castelletti N. The representative COVID-19 cohort Munich (KoCo19): from the beginning of the pandemic to the Delta virus variant. BMC Infect Dis 2023; 23:466. [PMID: 37442952 DOI: 10.1186/s12879-023-08435-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/08/2023] [Accepted: 06/30/2023] [Indexed: 07/15/2023] Open
Abstract
BACKGROUND Population-based serological studies allow to estimate prevalence of SARS-CoV-2 infections despite a substantial number of mild or asymptomatic disease courses. This became even more relevant for decision making after vaccination started. The KoCo19 cohort tracks the pandemic progress in the Munich general population for over two years, setting it apart in Europe. METHODS Recruitment occurred during the initial pandemic wave, including 5313 participants above 13 years from private households in Munich. Four follow-ups were held at crucial times of the pandemic, with response rates of at least 70%. Participants filled questionnaires on socio-demographics and potential risk factors of infection. From Follow-up 2, information on SARS-CoV-2 vaccination was added. SARS-CoV-2 antibody status was measured using the Roche Elecsys® Anti-SARS-CoV-2 anti-N assay (indicating previous infection) and the Roche Elecsys® Anti-SARS-CoV-2 anti-S assay (indicating previous infection and/or vaccination). This allowed us to distinguish between sources of acquired antibodies. RESULTS The SARS-CoV-2 estimated cumulative sero-prevalence increased from 1.6% (1.1-2.1%) in May 2020 to 14.5% (12.7-16.2%) in November 2021. Underreporting with respect to official numbers fluctuated with testing policies and capacities, becoming a factor of more than two during the second half of 2021. Simultaneously, the vaccination campaign against the SARS-CoV-2 virus increased the percentage of the Munich population having antibodies, with 86.8% (85.5-87.9%) having developed anti-S and/or anti-N in November 2021. Incidence rates for infections after (BTI) and without previous vaccination (INS) differed (ratio INS/BTI of 2.1, 0.7-3.6). However, the prevalence of infections was higher in the non-vaccinated population than in the vaccinated one. Considering the whole follow-up time, being born outside Germany, working in a high-risk job and living area per inhabitant were identified as risk factors for infection, while other socio-demographic and health-related variables were not. Although we obtained significant within-household clustering of SARS-CoV-2 cases, no further geospatial clustering was found. CONCLUSIONS Vaccination increased the coverage of the Munich population presenting SARS-CoV-2 antibodies, but breakthrough infections contribute to community spread. As underreporting stays relevant over time, infections can go undetected, so non-pharmaceutical measures are crucial, particularly for highly contagious strains like Omicron.
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Affiliation(s)
- Ronan Le Gleut
- Institute of Computational Biology, Helmholtz Munich, German Research Centre for Environmental Health, 85764, Neuherberg, Germany
- Core Facility Statistical Consulting, Helmholtz Munich, German Research Centre for Environmental Health, 85764, Neuherberg, Germany
| | - Michael Plank
- Division of Infectious Diseases and Tropical Medicine, University Hospital, LMU Munich, 80802, Munich, Germany
| | - Peter Pütz
- Robert Koch Institute, Nordufer 20, 13353, Berlin, Germany
| | - Katja Radon
- Institute and Outpatient Clinic for Occupational, Social and Environmental Medicine, University Hospital, LMU Munich, 80336, Munich, Germany
- Centre for International Health (CIH), University Hospital, LMU Munich, 80336, Munich, Germany
- Comprehensive Pneumology Centre (CPC) Munich, German Centre for Lung Research (DZL), 89337, Munich, Germany
| | - Abhishek Bakuli
- Division of Infectious Diseases and Tropical Medicine, University Hospital, LMU Munich, 80802, Munich, Germany
| | - Raquel Rubio-Acero
- Division of Infectious Diseases and Tropical Medicine, University Hospital, LMU Munich, 80802, Munich, Germany
| | - Ivana Paunovic
- Division of Infectious Diseases and Tropical Medicine, University Hospital, LMU Munich, 80802, Munich, Germany
| | - Friedrich Rieß
- Division of Infectious Diseases and Tropical Medicine, University Hospital, LMU Munich, 80802, Munich, Germany
| | - Simon Winter
- Division of Infectious Diseases and Tropical Medicine, University Hospital, LMU Munich, 80802, Munich, Germany
| | - Christina Reinkemeyer
- Division of Infectious Diseases and Tropical Medicine, University Hospital, LMU Munich, 80802, Munich, Germany
| | - Yannik Schälte
- Institute of Computational Biology, Helmholtz Munich, German Research Centre for Environmental Health, 85764, Neuherberg, Germany
- Centre for Mathematics, Technische Universität München, 85748, Garching, Germany
- Life and Medical Sciences Institute, University of Bonn, 53115, Bonn, Germany
| | - Laura Olbrich
- Division of Infectious Diseases and Tropical Medicine, University Hospital, LMU Munich, 80802, Munich, Germany
| | - Marlene Hannes
- Division of Infectious Diseases and Tropical Medicine, University Hospital, LMU Munich, 80802, Munich, Germany
| | - Inge Kroidl
- Division of Infectious Diseases and Tropical Medicine, University Hospital, LMU Munich, 80802, Munich, Germany
| | - Ivan Noreña
- Division of Infectious Diseases and Tropical Medicine, University Hospital, LMU Munich, 80802, Munich, Germany
| | - Christian Janke
- Division of Infectious Diseases and Tropical Medicine, University Hospital, LMU Munich, 80802, Munich, Germany
| | - Andreas Wieser
- Division of Infectious Diseases and Tropical Medicine, University Hospital, LMU Munich, 80802, Munich, Germany
- German Centre for Infection Research (DZIF), Partner Site, Munich, Germany
- Fraunhofer Institute for Translational Medicine and Pharmacology ITMP, Immunology, Infection and Pandemic Research, 80799, Munich, Germany
- Max Von Pettenkofer Institute, Faculty of Medicine, LMU Munich, 80336, Munich, Germany
| | - Michael Hoelscher
- Division of Infectious Diseases and Tropical Medicine, University Hospital, LMU Munich, 80802, Munich, Germany
- Centre for International Health (CIH), University Hospital, LMU Munich, 80336, Munich, Germany
- German Centre for Infection Research (DZIF), Partner Site, Munich, Germany
- Fraunhofer Institute for Translational Medicine and Pharmacology ITMP, Immunology, Infection and Pandemic Research, 80799, Munich, Germany
| | - Christiane Fuchs
- Institute of Computational Biology, Helmholtz Munich, German Research Centre for Environmental Health, 85764, Neuherberg, Germany
- Core Facility Statistical Consulting, Helmholtz Munich, German Research Centre for Environmental Health, 85764, Neuherberg, Germany
- Centre for Mathematics, Technische Universität München, 85748, Garching, Germany
- Faculty of Business Administration and Economics, Bielefeld University, 33615, Bielefeld, Germany
| | - Noemi Castelletti
- Division of Infectious Diseases and Tropical Medicine, University Hospital, LMU Munich, 80802, Munich, Germany.
- Fraunhofer Institute for Translational Medicine and Pharmacology ITMP, Immunology, Infection and Pandemic Research, 80799, Munich, Germany.
- Institute of Radiation Medicine, Helmholtz Munich, German Research Centre for Environmental Health, 85764, Neuherberg, Germany.
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8
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Contento L, Castelletti N, Raimúndez E, Le Gleut R, Schälte Y, Stapor P, Hinske LC, Hoelscher M, Wieser A, Radon K, Fuchs C, Hasenauer J. Integrative modelling of reported case numbers and seroprevalence reveals time-dependent test efficiency and infectious contacts. Epidemics 2023; 43:100681. [PMID: 36931114 PMCID: PMC10008049 DOI: 10.1016/j.epidem.2023.100681] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/06/2021] [Revised: 02/28/2023] [Accepted: 03/08/2023] [Indexed: 03/16/2023] Open
Abstract
Mathematical models have been widely used during the ongoing SARS-CoV-2 pandemic for data interpretation, forecasting, and policy making. However, most models are based on officially reported case numbers, which depend on test availability and test strategies. The time dependence of these factors renders interpretation difficult and might even result in estimation biases. Here, we present a computational modelling framework that allows for the integration of reported case numbers with seroprevalence estimates obtained from representative population cohorts. To account for the time dependence of infection and testing rates, we embed flexible splines in an epidemiological model. The parameters of these splines are estimated, along with the other parameters, from the available data using a Bayesian approach. The application of this approach to the official case numbers reported for Munich (Germany) and the seroprevalence reported by the prospective COVID-19 Cohort Munich (KoCo19) provides first estimates for the time dependence of the under-reporting factor. Furthermore, we estimate how the effectiveness of non-pharmaceutical interventions and of the testing strategy evolves over time. Overall, our results show that the integration of temporally highly resolved and representative data is beneficial for accurate epidemiological analyses.
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Affiliation(s)
- Lorenzo Contento
- Faculty of Mathematics and Natural Sciences, University of Bonn, Bonn, Germany.
| | - Noemi Castelletti
- Division of Infectious Diseases and Tropical Medicine, University Hospital, LMU Munich, Munich, Germany
| | - Elba Raimúndez
- Faculty of Mathematics and Natural Sciences, University of Bonn, Bonn, Germany; Center for Mathematics, Technische Universität München, Garching, Germany
| | - Ronan Le Gleut
- Institute of Computational Biology, Helmholtz Zentrum München - German Research Center for Environmental Health, Neuherberg, Germany; Core Facility Statistical Consulting, Helmholtz Zentrum München - German Research Center for Environmental Health, Neuherberg, Germany
| | - Yannik Schälte
- Institute of Computational Biology, Helmholtz Zentrum München - German Research Center for Environmental Health, Neuherberg, Germany; Center for Mathematics, Technische Universität München, Garching, Germany
| | - Paul Stapor
- Institute of Computational Biology, Helmholtz Zentrum München - German Research Center for Environmental Health, Neuherberg, Germany; Center for Mathematics, Technische Universität München, Garching, Germany
| | - Ludwig Christian Hinske
- Institut für medizinische Informationsverarbeitung, Biometrie und Epidemiologie, Munich, Germany
| | - Michael Hoelscher
- Division of Infectious Diseases and Tropical Medicine, University Hospital, LMU Munich, Munich, Germany; Center for International Health (CIH), University Hospital, LMU Munich, Munich, Germany; German Center for Infection Research (DZIF), partner site Munich, Germany
| | - Andreas Wieser
- Division of Infectious Diseases and Tropical Medicine, University Hospital, LMU Munich, Munich, Germany; German Center for Infection Research (DZIF), partner site Munich, Germany
| | - Katja Radon
- German Center for Infection Research (DZIF), partner site Munich, Germany; Institute and Outpatient Clinic for Occupational, Social and Environmental Medicine, University Hospital, LMU Munich, Munich, Germany; Comprehensive Pneumology Center (CPC) Munich, German Center for Lung Research (DZL), Munich, Germany
| | - Christiane Fuchs
- Institute of Computational Biology, Helmholtz Zentrum München - German Research Center for Environmental Health, Neuherberg, Germany; Core Facility Statistical Consulting, Helmholtz Zentrum München - German Research Center for Environmental Health, Neuherberg, Germany; Center for Mathematics, Technische Universität München, Garching, Germany; Faculty of Business Administration and Economics, Bielefeld University, Bielefeld, Germany
| | - Jan Hasenauer
- Faculty of Mathematics and Natural Sciences, University of Bonn, Bonn, Germany; Institute of Computational Biology, Helmholtz Zentrum München - German Research Center for Environmental Health, Neuherberg, Germany; Center for Mathematics, Technische Universität München, Garching, Germany
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9
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Eser TM, Baranov O, Huth M, Ahmed MIM, Deák F, Held K, Lin L, Pekayvaz K, Leunig A, Nicolai L, Pollakis G, Buggert M, Price DA, Rubio-Acero R, Reich J, Falk P, Markgraf A, Puchinger K, Castelletti N, Olbrich L, Vanshylla K, Klein F, Wieser A, Hasenauer J, Kroidl I, Hoelscher M, Geldmacher C. Nucleocapsid-specific T cell responses associate with control of SARS-CoV-2 in the upper airways before seroconversion. Nat Commun 2023; 14:2952. [PMID: 37225706 DOI: 10.1038/s41467-023-38020-8] [Citation(s) in RCA: 12] [Impact Index Per Article: 12.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/21/2022] [Accepted: 04/12/2023] [Indexed: 05/26/2023] Open
Abstract
Despite intensive research since the emergence of SARS-CoV-2, it has remained unclear precisely which components of the early immune response protect against the development of severe COVID-19. Here, we perform a comprehensive immunogenetic and virologic analysis of nasopharyngeal and peripheral blood samples obtained during the acute phase of infection with SARS-CoV-2. We find that soluble and transcriptional markers of systemic inflammation peak during the first week after symptom onset and correlate directly with upper airways viral loads (UA-VLs), whereas the contemporaneous frequencies of circulating viral nucleocapsid (NC)-specific CD4+ and CD8+ T cells correlate inversely with various inflammatory markers and UA-VLs. In addition, we show that high frequencies of activated CD4+ and CD8+ T cells are present in acutely infected nasopharyngeal tissue, many of which express genes encoding various effector molecules, such as cytotoxic proteins and IFN-γ. The presence of IFNG mRNA-expressing CD4+ and CD8+ T cells in the infected epithelium is further linked with common patterns of gene expression among virus-susceptible target cells and better local control of SARS-CoV-2. Collectively, these results identify an immune correlate of protection against SARS-CoV-2, which could inform the development of more effective vaccines to combat the acute and chronic illnesses attributable to COVID-19.
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Affiliation(s)
- Tabea M Eser
- Division of Infectious Diseases and Tropical Medicine, University Hospital, LMU Munich, 81377, Munich, Germany
- German Center for Infection Research (DZIF), Partner Site Munich, 81377, Munich, Germany
| | - Olga Baranov
- Division of Infectious Diseases and Tropical Medicine, University Hospital, LMU Munich, 81377, Munich, Germany
- German Center for Infection Research (DZIF), Partner Site Munich, 81377, Munich, Germany
| | - Manuel Huth
- Institute of Computational Biology, Helmholtz Zentrum München, 85764, Neuherberg, Germany
- Center for Mathematics, Technische Universität München, 85748, Garching, Germany
| | - Mohammed I M Ahmed
- Division of Infectious Diseases and Tropical Medicine, University Hospital, LMU Munich, 81377, Munich, Germany
- German Center for Infection Research (DZIF), Partner Site Munich, 81377, Munich, Germany
| | - Flora Deák
- Division of Infectious Diseases and Tropical Medicine, University Hospital, LMU Munich, 81377, Munich, Germany
- German Center for Infection Research (DZIF), Partner Site Munich, 81377, Munich, Germany
| | - Kathrin Held
- Division of Infectious Diseases and Tropical Medicine, University Hospital, LMU Munich, 81377, Munich, Germany
- German Center for Infection Research (DZIF), Partner Site Munich, 81377, Munich, Germany
| | - Luming Lin
- Division of Infectious Diseases and Tropical Medicine, University Hospital, LMU Munich, 81377, Munich, Germany
- German Center for Infection Research (DZIF), Partner Site Munich, 81377, Munich, Germany
| | - Kami Pekayvaz
- Department of Medicine I, University Hospital, LMU Munich, 81377, Munich, Germany
- German Center for Cardiovascular Research (DZHK), Partner Site Munich Heart Alliance, 81377, Munich, Germany
| | - Alexander Leunig
- Department of Medicine I, University Hospital, LMU Munich, 81377, Munich, Germany
- German Center for Cardiovascular Research (DZHK), Partner Site Munich Heart Alliance, 81377, Munich, Germany
| | - Leo Nicolai
- Department of Medicine I, University Hospital, LMU Munich, 81377, Munich, Germany
- German Center for Cardiovascular Research (DZHK), Partner Site Munich Heart Alliance, 81377, Munich, Germany
| | - Georgios Pollakis
- Institute of Infection and Global Health, University of Liverpool, Liverpool, L69 2BE, UK
| | - Marcus Buggert
- Center for Infectious Medicine, Department of Medicine Huddinge, Karolinska Institutet, Karolinska University Hospital Huddinge, 141 86, Stockholm, Sweden
| | - David A Price
- Division of Infection and Immunity, Cardiff University School of Medicine, University Hospital, Heath Park, Cardiff, CF14 4XN, UK
- Systems Immunity Research Institute, Cardiff University School of Medicine, University Hospital, Heath Park, Cardiff, CF14 4XN, UK
| | - Raquel Rubio-Acero
- Division of Infectious Diseases and Tropical Medicine, University Hospital, LMU Munich, 81377, Munich, Germany
| | - Jakob Reich
- Division of Infectious Diseases and Tropical Medicine, University Hospital, LMU Munich, 81377, Munich, Germany
| | - Philine Falk
- Division of Infectious Diseases and Tropical Medicine, University Hospital, LMU Munich, 81377, Munich, Germany
| | - Alissa Markgraf
- Division of Infectious Diseases and Tropical Medicine, University Hospital, LMU Munich, 81377, Munich, Germany
| | - Kerstin Puchinger
- Division of Infectious Diseases and Tropical Medicine, University Hospital, LMU Munich, 81377, Munich, Germany
| | - Noemi Castelletti
- Division of Infectious Diseases and Tropical Medicine, University Hospital, LMU Munich, 81377, Munich, Germany
- German Center for Infection Research (DZIF), Partner Site Munich, 81377, Munich, Germany
| | - Laura Olbrich
- Division of Infectious Diseases and Tropical Medicine, University Hospital, LMU Munich, 81377, Munich, Germany
- German Center for Infection Research (DZIF), Partner Site Munich, 81377, Munich, Germany
| | - Kanika Vanshylla
- Laboratory of Experimental Immunology, Institute of Virology, Faculty of Medicine and University Hospital Cologne, University of Cologne, 50931, Cologne, Germany
| | - Florian Klein
- Laboratory of Experimental Immunology, Institute of Virology, Faculty of Medicine and University Hospital Cologne, University of Cologne, 50931, Cologne, Germany
- German Center for Infection Research (DZIF), Partner Site Bonn-Cologne, 50937, Cologne, Germany
- Center for Molecular Medicine Cologne (CMMC), University of Cologne, 50931, Cologne, Germany
| | - Andreas Wieser
- Division of Infectious Diseases and Tropical Medicine, University Hospital, LMU Munich, 81377, Munich, Germany
- German Center for Infection Research (DZIF), Partner Site Munich, 81377, Munich, Germany
- Max von Pettenkofer Institute for Hygiene and Medical Microbiology, LMU Munich, 81377, Munich, Germany
| | - Jan Hasenauer
- Institute of Computational Biology, Helmholtz Zentrum München, 85764, Neuherberg, Germany
- Center for Mathematics, Technische Universität München, 85748, Garching, Germany
- Faculty of Mathematics and Natural Sciences, University of Bonn, 53113, Bonn, Germany
| | - Inge Kroidl
- Division of Infectious Diseases and Tropical Medicine, University Hospital, LMU Munich, 81377, Munich, Germany
- German Center for Infection Research (DZIF), Partner Site Munich, 81377, Munich, Germany
| | - Michael Hoelscher
- Division of Infectious Diseases and Tropical Medicine, University Hospital, LMU Munich, 81377, Munich, Germany
- German Center for Infection Research (DZIF), Partner Site Munich, 81377, Munich, Germany
| | - Christof Geldmacher
- Division of Infectious Diseases and Tropical Medicine, University Hospital, LMU Munich, 81377, Munich, Germany.
- German Center for Infection Research (DZIF), Partner Site Munich, 81377, Munich, Germany.
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Wasnik RN, Vincze F, Földvári A, Pálinkás A, Sándor J. Effectiveness of and Inequalities in COVID-19 Epidemic Control Strategies in Hungary: A Nationwide Cross-Sectional Study. Healthcare (Basel) 2023; 11:healthcare11091220. [PMID: 37174762 PMCID: PMC10178097 DOI: 10.3390/healthcare11091220] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/24/2023] [Revised: 04/21/2023] [Accepted: 04/23/2023] [Indexed: 05/15/2023] Open
Abstract
INTRODUCTION Before the mass vaccination, epidemiological control measures were the only means of containing the COVID-19 epidemic. Their effectiveness determined the consequences of the COVID-19 epidemic. Our study evaluated the impact of sociodemographic, lifestyle, and clinical factors on patient-reported epidemiological control measures. METHODS A nationwide representative sample of 1008 randomly selected adults were interviewed in person between 15 March and 30 May 2021. The prevalence of test-confirmed SARS-CoV-2 infection was 12.1%, of testing was 33.7%, and of contact tracing among test-confirmed infected subjects was 67.9%. The vaccination coverage was 52.4%. RESULTS According to the multivariable logistic regression models, the occurrence of infection was not influenced by sociodemographic and lifestyle factors or by the presence of chronic disease. Testing was more frequent among middle-aged adults (aOR = 1.53, 95% CI 1.10-2.13) and employed adults (aOR = 2.06, 95% CI 1.42-3.00), and was more frequent among adults with a higher education (aORsecondary = 1.93, 95% CI 1.20-3.13; aORtertiary = 3.19, 95% CI 1.81-5.63). Contact tracing was more frequently implemented among middle-aged (aOR41-7y = 3.33, 95% CI 1.17-9.45) and employed (aOR = 4.58, 95% CI 1.38-15.22), and those with chronic diseases (aOR = 5.92, 95% CI 1.56-22.47). Positive correlation was observed between age groups and vaccination frequency (aOR41-70y = 2.94, 95% CI 2.09-4.15; aOR71+y = 14.52, 95% CI 7.33-28.77). Higher than primary education (aORsecondary = 1.69, 95% CI 1.08-2.63; aORtertiary = 4.36, 95% CI 2.46-7.73) and the presence of a chronic disease (aOR = 2.58, 95% CI 1.75-3.80) positively impacted vaccination. Regular smoking was inversely correlated with vaccination (aOR = 0.60; 95% CI 0.44-0.83). CONCLUSIONS The survey indicated that testing, contact tracing, and vaccination were seriously influenced by socioeconomic position; less so by chronic disease prevalence and very minimally by lifestyle. The etiological role of socioeconomic inequalities in epidemic measure implementation likely generated socioeconomic inequality in COVID-19-related complication and death rates.
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Affiliation(s)
- Rahul Naresh Wasnik
- Department of Public Health and Epidemiology, Faculty of Medicine, University of Debrecen, H-4002 Debrecen, Hungary
- Doctoral School of Health Sciences, University of Debrecen, H-4002 Debrecen, Hungary
| | - Ferenc Vincze
- Department of Public Health and Epidemiology, Faculty of Medicine, University of Debrecen, H-4002 Debrecen, Hungary
| | - Anett Földvári
- Doctoral School of Health Sciences, University of Debrecen, H-4002 Debrecen, Hungary
| | - Anita Pálinkás
- ELKH-DE Public Health Research Group, Department of Public Health and Epidemiology, Faculty of Medicine, University of Debrecen, H-4002 Debrecen, Hungary
| | - János Sándor
- Department of Public Health and Epidemiology, Faculty of Medicine, University of Debrecen, H-4002 Debrecen, Hungary
- ELKH-DE Public Health Research Group, Department of Public Health and Epidemiology, Faculty of Medicine, University of Debrecen, H-4002 Debrecen, Hungary
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11
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Metzger C, Leroy T, Bochnakian A, Jeulin H, Gegout-Petit A, Legrand K, Schvoerer E, Guillemin F. Seroprevalence and SARS-CoV-2 invasion in general populations: A scoping review over the first year of the pandemic. PLoS One 2023; 18:e0269104. [PMID: 37075077 PMCID: PMC10118383 DOI: 10.1371/journal.pone.0269104] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/25/2021] [Accepted: 05/13/2022] [Indexed: 04/20/2023] Open
Abstract
Since the beginning of the COVID-19 pandemic, counting infected people has underestimated asymptomatic cases. This literature scoping review assessed the seroprevalence progression in general populations worldwide over the first year of the pandemic. Seroprevalence studies were searched in PubMed, Web of Science and medRxiv databases up to early April 2021. Inclusion criteria were a general population of all ages or blood donors as a proxy. All articles were screened for the title and abstract by two readers, and data were extracted from selected articles. Discrepancies were resolved with a third reader. From 139 articles (including 6 reviews), the seroprevalence estimated in 41 countries ranged from 0 to 69%, with a heterogenous increase over time and continents, unevenly distributed among countries (differences up to 69%) and sometimes among regions within a country (up to 10%). The seroprevalence of asymptomatic cases ranged from 0% to 31.5%. Seropositivity risk factors included low income, low education, low smoking frequency, deprived area residency, high number of children, densely populated centres, and presence of a case in a household. This review of seroprevalence studies over the first year of the pandemic documented the progression of this virus across the world in time and space and the risk factors that influenced its spread.
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Affiliation(s)
- Clémentine Metzger
- CHRU -Nancy, INSERM, Université de Lorraine, CIC Epidémiologie clinique,
F-54000, Nancy, France
| | - Taylor Leroy
- CHRU -Nancy, INSERM, Université de Lorraine, CIC Epidémiologie clinique,
F-54000, Nancy, France
| | - Agathe Bochnakian
- CHRU -Nancy, INSERM, Université de Lorraine, CIC Epidémiologie clinique,
F-54000, Nancy, France
| | - Hélène Jeulin
- Université de Lorraine, CNRS, LCPME, F‐54000, Nancy,
France
- Laboratoire de Virologie, CHRU de Nancy Brabois, F‐54500, Nancy,
France
| | | | - Karine Legrand
- CHRU -Nancy, INSERM, Université de Lorraine, CIC Epidémiologie clinique,
F-54000, Nancy, France
| | - Evelyne Schvoerer
- Université de Lorraine, CNRS, LCPME, F‐54000, Nancy,
France
- Laboratoire de Virologie, CHRU de Nancy Brabois, F‐54500, Nancy,
France
| | - Francis Guillemin
- CHRU -Nancy, INSERM, Université de Lorraine, CIC Epidémiologie clinique,
F-54000, Nancy, France
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12
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Offergeld R, Preußel K, Zeiler T, Aurich K, Baumann-Baretti BI, Ciesek S, Corman VM, Dienst V, Drosten C, Görg S, Greinacher A, Grossegesse M, Haller S, Heuft HG, Hofmann N, Horn PA, Houareau C, Gülec I, Jiménez Klingberg CL, Juhl D, Lindemann M, Martin S, Neuhauser HK, Nitsche A, Ohme J, Peine S, Sachs UJ, Schaade L, Schäfer R, Scheiblauer H, Schlaud M, Schmidt M, Umhau M, Vollmer T, Wagner FF, Wieler LH, Wilking H, Ziemann M, Zimmermann M, der Heiden MA. Monitoring the SARS-CoV-2 Pandemic: Prevalence of Antibodies in a Large, Repetitive Cross-Sectional Study of Blood Donors in Germany—Results from the SeBluCo Study 2020–2022. Pathogens 2023; 12:pathogens12040551. [PMID: 37111436 PMCID: PMC10144823 DOI: 10.3390/pathogens12040551] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/28/2023] [Revised: 03/17/2023] [Accepted: 03/27/2023] [Indexed: 04/05/2023] Open
Abstract
SARS-CoV-2 serosurveillance is important to adapt infection control measures and estimate the degree of underreporting. Blood donor samples can be used as a proxy for the healthy adult population. In a repeated cross-sectional study from April 2020 to April 2021, September 2021, and April/May 2022, 13 blood establishments collected 134,510 anonymised specimens from blood donors in 28 study regions across Germany. These were tested for antibodies against the SARS-CoV-2 spike protein and nucleocapsid, including neutralising capacity. Seroprevalence was adjusted for test performance and sampling and weighted for demographic differences between the sample and the general population. Seroprevalence estimates were compared to notified COVID-19 cases. The overall adjusted SARS-CoV-2 seroprevalence remained below 2% until December 2020 and increased to 18.1% in April 2021, 89.4% in September 2021, and to 100% in April/May 2022. Neutralising capacity was found in 74% of all positive specimens until April 2021 and in 98% in April/May 2022. Our serosurveillance allowed for repeated estimations of underreporting from the early stage of the pandemic onwards. Underreporting ranged between factors 5.1 and 1.1 in the first two waves of the pandemic and remained well below 2 afterwards, indicating an adequate test strategy and notification system in Germany.
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Affiliation(s)
- Ruth Offergeld
- Robert Koch Institute, Nordufer 20, 13353 Berlin, Germany
| | - Karina Preußel
- Robert Koch Institute, Nordufer 20, 13353 Berlin, Germany
| | - Thomas Zeiler
- German Red Cross Blood Service West, 58097 Hagen, Germany
| | - Konstanze Aurich
- Institute for Immunology and Transfusion Medicine, University Medicine Greifswald, Sauerbruchstrasse, 17475 Greifswald, Germany
| | | | - Sandra Ciesek
- Institute for Medical Virology, German Centre for Infection Research, External Partner Site Frankfurt, University Hospital, Goethe University Frankfurt am Main, 39120 Frankfurt am Main, Germany
| | - Victor M. Corman
- Institute of Virology, German National Reference Laboratory for Coronavirus, Charité—University Medicine Berlin, 10117 Berlin, Germany
| | | | - Christian Drosten
- Institute of Virology, German National Reference Laboratory for Coronavirus, Charité—University Medicine Berlin, 10117 Berlin, Germany
| | - Siegfried Görg
- Institute of Transfusion Medicine, University Hospital of Schleswig-Holstein, Lübeck/Kiel, Ratzeburger Allee 160, 23538 Lübeck, Germany
| | - Andreas Greinacher
- Institute for Immunology and Transfusion Medicine, University Medicine Greifswald, Sauerbruchstrasse, 17475 Greifswald, Germany
| | | | | | - Hans-Gert Heuft
- Institute of Transfusion Medicine and Immunohaematology/Blood Bank, University Hospital Magdeburg, Leipziger Str. 44, 39120 Magdeburg, Germany
| | | | - Peter A. Horn
- Institute for Transfusion Medicine, University Hospital Essen, Hufelandstraße 55, 45147 Essen, Germany
| | | | - Ilay Gülec
- Institute of Transfusion Medicine and Immunohematology, German Red Cross Blood Transfusion Service Baden-Württemberg—Hessen, Sandhofstraße 1, 60528 Frankfurt am Main, Germany
| | | | - David Juhl
- Institute of Transfusion Medicine, University Hospital of Schleswig-Holstein, Lübeck/Kiel, Ratzeburger Allee 160, 23538 Lübeck, Germany
| | - Monika Lindemann
- Institute for Transfusion Medicine, University Hospital Essen, Hufelandstraße 55, 45147 Essen, Germany
| | - Silke Martin
- Bavarian Red Cross Blood Service, Herzog-Heinrich-Str. 2, 80336 München, Germany
| | | | | | - Julia Ohme
- German Red Cross Blood Service NSTOB, Eldagsener Straße 38, 31832 Springe, Germany
| | - Sven Peine
- Institute of Transfusion Medicine, University Medical Center Hamburg-Eppendorf, 20251 Hamburg, Germany
| | - Ulrich J. Sachs
- Center for Transfusion Medicine and Haemotherapy, University Hospital Giessen and Marburg, Langhansstr. 7, 35392 Giessen, Germany
| | - Lars Schaade
- Robert Koch Institute, Nordufer 20, 13353 Berlin, Germany
| | - Richard Schäfer
- Institute for Transfusion Medicine and Gene Therapy, Faculty of Medicine, Medical Center—University of Freiburg, Hugstetter Str. 55, 79106 Freiburg, Germany
| | | | - Martin Schlaud
- Robert Koch Institute, Nordufer 20, 13353 Berlin, Germany
| | - Michael Schmidt
- Institute of Transfusion Medicine and Immunohematology, German Red Cross Blood Transfusion Service Baden-Württemberg—Hessen, Sandhofstraße 1, 60528 Frankfurt am Main, Germany
| | - Markus Umhau
- Institute for Transfusion Medicine and Gene Therapy, Faculty of Medicine, Medical Center—University of Freiburg, Hugstetter Str. 55, 79106 Freiburg, Germany
| | - Tanja Vollmer
- Heart and Diabetes Centre NRW, Institute for Laboratory and Transfusion Medicine, Ruhr-University Bochum, 32545 Bad Oeynhausen, Germany
| | - Franz F. Wagner
- German Red Cross Blood Service NSTOB, Eldagsener Straße 38, 31832 Springe, Germany
| | | | | | - Malte Ziemann
- Institute of Transfusion Medicine, University Hospital of Schleswig-Holstein, Lübeck/Kiel, Ratzeburger Allee 160, 23538 Lübeck, Germany
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13
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Oberste M, Schnörch N, Shah-Hosseini K, Asenova T, Dewald F, Lehmann C, Buess M, Fätkenheuer G, Klein F, Rosenberger KD, Kossow A, Neuhann F, Hellmich M. Results of the Cologne Corona Surveillance (CoCoS) study - a cross-sectional study: survey data on risk factors of SARS-CoV-2 infection in adults. BMC Public Health 2023; 23:260. [PMID: 36747171 PMCID: PMC9902063 DOI: 10.1186/s12889-023-15047-6] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/08/2022] [Accepted: 01/13/2023] [Indexed: 02/08/2023] Open
Abstract
BACKGROUND The personal, environmental, and behavioral risk factors that play an important role in the spread of SARS-CoV-2 are still largely unclear. At the same time, there is limited evidence on the effectiveness of specific countermeasures for SARS-CoV-2. As a first approach to these questions, we use data from the Cologne Corona Surveillance (CoCoS) study, a large cross-sectional study conducted in Cologne, Germany, in June 2021. METHODS This study was conducted in Cologne, Germany. Six thousand randomly selected Cologne residents who were 18 years of age or older were invited to participate in this study. Participant information was obtained via an online survey. Previous SARS-CoV-2 infections were recorded using self-reports. Sociodemographic and environmental information such as age, sex, living situation were collected. Potential SARS-CoV-2 risk behaviors were captured (workplace situation, adherence to hygiene regulations, and regular use of public transportation). Adherence to hygiene regulations was surveyed by determining the compliance with the 'AHA'-rules (German acronym that stands for keeping a distance of 1.5 m from fellow citizens, hand disinfection, and wearing a face mask). Binary logistic regression analysis was used to identify risk factors for SARS-CoV-2 infection. RESULTS A sample of 2,433 study participants provided information. Comparison of the sample with the general population showed representativeness for most sociodemographic characteristics with a preference for higher level of education in the study sample. Younger age, as well as living with minor children (under 18 years) in the same household were associated with a higher number of self-reported SARS-CoV-2 infections. Adherence to hygiene regulations was associated with fewer self-reported SARS-CoV-2 infections in adults. Gender, size of living space per person, workplace situation (work from home versus working with contact to colleagues/customers), and regular use of public transportation showed no significant association with self-reported SARS-CoV-2 infections in multivariable analysis. CONCLUSION The presented results provide initial indications of which sociodemographic and behavioral factors may be associated with SARS-CoV-2 infection. However, the fact that these factors were recorded without exact dates and could have changed accordingly during the pandemic or after infection limits the strength of the results. TRIAL REGISTRATION DRKS.de, German Clinical Trials Register (DRKS), Identifier: DRKS00024046, Registered on 25 February 2021.
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Affiliation(s)
- Max Oberste
- grid.6190.e0000 0000 8580 3777Institute 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
- grid.6190.e0000 0000 8580 3777Institute 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
- grid.6190.e0000 0000 8580 3777Institute 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
- grid.6190.e0000 0000 8580 3777Institute of Medical Statistics and Computational Biology, Medical Faculty and University Hospital of Cologne, University of Cologne, Robert-Koch-Straße 10, 50931 Cologne, Germany
| | - Felix Dewald
- grid.6190.e0000 0000 8580 3777Institute of Virology, Medical Faculty and University Hospital of Cologne, University of Cologne, Fürst-Pückler-Straße 56, 50935 Cologne, Germany
| | - Clara Lehmann
- grid.6190.e0000 0000 8580 3777Department of Internal Medicine, Medical Faculty and University Hospital of Cologne, University of Cologne, Kerpener Str. 62, 50931 Cologne, Germany
| | | | - Gerd Fätkenheuer
- grid.6190.e0000 0000 8580 3777Department of Internal Medicine, Medical Faculty and University Hospital of Cologne, University of Cologne, Kerpener Str. 62, 50931 Cologne, Germany
| | - Florian Klein
- grid.6190.e0000 0000 8580 3777Institute of Virology, Medical Faculty and University Hospital of Cologne, University of Cologne, Fürst-Pückler-Straße 56, 50935 Cologne, Germany
| | - Kerstin Daniela Rosenberger
- grid.6190.e0000 0000 8580 3777Institute 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
- Cologne Health Authority, Cologne, Germany ,grid.16149.3b0000 0004 0551 4246Institute of Hygiene, University Hospital of Muenster, University Muenster, Robert-Koch-Straße 49, 48149 Muenster, Germany
| | - Florian Neuhann
- Cologne Health Authority, Cologne, Germany ,grid.7700.00000 0001 2190 4373Heidelberg Institute of Global Health, University, Heidelberg, Germany ,grid.513520.00000 0004 9286 1317School of Medicine and Clinical Sciences, Levy Mwanawasa Medical University, Lusaka, Zambia
| | - Martin Hellmich
- Institute of Medical Statistics and Computational Biology, Medical Faculty and University Hospital of Cologne, University of Cologne, Robert-Koch-Straße 10, 50931, Cologne, Germany.
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14
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Seiler LK, Stolpe S, Stanislawski N, Stahl F, Witt M, Jonczyk R, Heiden S, Blume H, Kowall B, Blume C. Low impact of regular PCR testing on presence at work site during the COVID-19 pandemic: experiences during an open observational study in Lower Saxony 2020-21. BMC Public Health 2023; 23:240. [PMID: 36737718 PMCID: PMC9897879 DOI: 10.1186/s12889-023-15036-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/04/2022] [Accepted: 01/12/2023] [Indexed: 02/05/2023] Open
Abstract
BACKGROUND Since social distancing during the COVID-19-pandemic had a profound impact on professional life, this study investigated the effect of PCR testing on on-site work. METHODS PCR screening, antibody testing, and questionnaires offered to 4,890 working adults in Lower Saxony were accompanied by data collection on demographics, family status, comorbidities, social situation, health-related behavior, and the number of work-related contacts. Relative risks (RR) with 95 % confidence intervals were estimated for the associations between regular PCR testing and other work and health-related variables, respectively, and working on-site. Analyses were stratified by the suitability of work tasks for mobile office. RESULTS Between April 2020 and February 2021, 1,643 employees underwent PCR testing. Whether mobile working was possible strongly influenced the work behavior. Persons whose work was suitable for mobile office (mobile workers) had a lower probability of working on-site than persons whose work was not suitable for mobile office (RR = 0.09 (95 % CI: 0.07 - 0.12)). In mobile workers, regular PCR-testing was slightly associated with working on-site (RR = 1.19 (0.66; 2.14)). In those whose working place was unsuitable for mobile office, the corresponding RR was 0.94 (0.80; 1.09). Compared to persons without chronic diseases, chronically ill persons worked less often on-site if their workplace was suitable for mobile office (RR = 0.73 (0.40; 1.33)), but even more often if their workplace was not suitable for mobile office (RR = 1.17 (1.04; 1.33)). CONCLUSION If work was suitable for mobile office, regular PCR-testing did not have a strong effect on presence at the work site. TRIAL REGISTRATION An ethics vote of the responsible medical association (Lower Saxony, Germany) retrospectively approved the evaluation of the collected subject data in a pseudonymized form in the context of medical studies (No. Bo/30/2020; Bo/31/2020; Bo/32/2020).
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Affiliation(s)
- Lisa K Seiler
- Institute of Technical Chemistry, Leibniz University Hannover, Hanover, Germany
| | - Susanne Stolpe
- Institute for Clinical Epidemiology, University Hospital Essen, Essen, Germany
| | - Nils Stanislawski
- Institute of Microelectronic Systems, Leibniz University Hannover, Hanover, Germany
| | - Frank Stahl
- Institute of Technical Chemistry, Leibniz University Hannover, Hanover, Germany
| | - Martin Witt
- Institute of Technical Chemistry, Leibniz University Hannover, Hanover, Germany
| | - Rebecca Jonczyk
- Institute of Technical Chemistry, Leibniz University Hannover, Hanover, Germany
| | - Stefanie Heiden
- Institute of Innovation Research, Technology Management & Entrepreneurship, Leibniz University Hannover, Hanover, Germany
| | - Holger Blume
- Institute of Technical Chemistry, Leibniz University Hannover, Hanover, Germany
| | - Bernd Kowall
- Institute for Clinical Epidemiology, University Hospital Essen, Essen, Germany
| | - Cornelia Blume
- Institute of Technical Chemistry, Leibniz University Hannover, Hanover, Germany.
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15
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Riesenhuber M, Nitsche C, Binder CJ, Schernhammer ES, Stamm T, Jakse F, Anwari E, Hamidi F, Haslacher H, Perkmann T, Hengstenberg C, Zelniker TA. Comparison of the prevalence of SARS-CoV-2 nucleoprotein antibodies in healthcare workers and an unselected adult and paediatric all-comer patient population: insights from a longitudinal study of healthcare workers and concurrent serial cross-sectional studies of patients at an academic medical centre in Austria. BMJ Open 2023; 13:e063760. [PMID: 36657754 PMCID: PMC9852740 DOI: 10.1136/bmjopen-2022-063760] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/13/2022] [Accepted: 12/27/2022] [Indexed: 01/20/2023] Open
Abstract
OBJECTIVES This study aimed to estimate and compare the prevalence of the virus-specific antibodies against the SARS-CoV-2 nucleoprotein antigen (anti-SARS-CoV-2 N) in healthcare workers and an all-comer paediatric and adult patient population. DESIGN, SETTING AND PARTICIPANTS A longitudinal study enrolling healthcare professionals and concurrent serial cross-sectional studies of unselected all-comer patients were conducted at an Austrian academic medical centre. Healthcare workers were tested at enrolment and after 1, 2, 3, 6 and 12 months. The cross-sectional studies in patients were conducted at three time periods, which roughly coincided with the times after the first, second and third wave of SARS-CoV-2 in Austria (ie, 24 August-7 September 2020; 8-22 February 2021 and 9-23 November 2021). Anti-SARS-CoV-2 N antibodies were measured using a sandwich electrochemiluminescence assay (Roche). RESULTS In total, 2735 and 9275 samples were measured in 812 healthcare workers (median age: 40 years, 78% female) and 8451 patients (median age: 55 years, 52% female), respectively. Over the entire study period, anti-SARS-CoV-2 N antibodies were detected in 98 of 812 healthcare workers, resulting in a seroprevalence of 12.1% (95% CI 10.0% to 14.5%), which did not differ significantly (p=0.63) from that of the all-comer patient population at the end of the study period (407/3184; 12.8%, 95% CI 11.7% to 14.0%). The seroprevalence between healthcare workers and patients did not differ significantly at any time and was 1.5-fold to 2-fold higher than the number of confirmed cases in Austria throughout the pandemic. In particular, there was no significant difference in the seroprevalence between paediatric and adult patients at any of the tested time periods. CONCLUSION Throughout the pandemic, healthcare staff and an adult and paediatric all-comer patient population had similar exposure to SARS-CoV-2. TRIAL REGISTRATION NUMBER ClinicalTrials.gov Identifier: NCT04407429.
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Affiliation(s)
- Martin Riesenhuber
- Department of Internal Medicine II, Division of Cardiology, Medical University of Vienna, Wien, Austria
| | - Christian Nitsche
- Department of Internal Medicine II, Division of Cardiology, Medical University of Vienna, Wien, Austria
| | - Christoph J Binder
- Department of Laboratory Medicine, Medical University of Vienna, Wien, Austria
| | - Eva S Schernhammer
- Department of Epidemiology, Center for Public Health, Medical University of Vienna, Wien, Austria
| | - Tanja Stamm
- Institute for Outcomes Research, Center for Medical Data Science, Medical University of Vienna, Vienna, Austria
| | - Friedrich Jakse
- Department of Internal Medicine II, Division of Cardiology, Medical University of Vienna, Wien, Austria
| | - Elaaha Anwari
- Department of Internal Medicine II, Division of Cardiology, Medical University of Vienna, Wien, Austria
| | - Fardin Hamidi
- Department of Internal Medicine II, Division of Cardiology, Medical University of Vienna, Wien, Austria
| | - Helmuth Haslacher
- Department of Laboratory Medicine, Medical University of Vienna, Wien, Austria
| | - Thomas Perkmann
- Department of Laboratory Medicine, Medical University of Vienna, Wien, Austria
| | - Christian Hengstenberg
- Department of Internal Medicine II, Division of Cardiology, Medical University of Vienna, Wien, Austria
| | - Thomas A Zelniker
- Department of Internal Medicine II, Division of Cardiology, Medical University of Vienna, Wien, Austria
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16
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Neuhauser H, Rosario AS, Butschalowsky H, Haller S, Hoebel J, Michel J, Nitsche A, Poethko-Müller C, Prütz F, Schlaud M, Steinhauer HW, Wilking H, Wieler LH, Schaade L, Liebig S, Gößwald A, Grabka MM, Zinn S, Ziese T. Nationally representative results on SARS-CoV-2 seroprevalence and testing in Germany at the end of 2020. Sci Rep 2022; 12:19492. [PMID: 36376417 PMCID: PMC9662125 DOI: 10.1038/s41598-022-23821-6] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/01/2021] [Accepted: 11/07/2022] [Indexed: 11/16/2022] Open
Abstract
Pre-vaccine SARS-CoV-2 seroprevalence data from Germany are scarce outside hotspots, and socioeconomic disparities remained largely unexplored. The nationwide representative RKI-SOEP study (15,122 participants, 18-99 years, 54% women) investigated seroprevalence and testing in a supplementary wave of the Socio-Economic-Panel conducted predominantly in October-November 2020. Self-collected oral-nasal swabs were PCR-positive in 0.4% and Euroimmun anti-SARS-CoV-2-S1-IgG ELISA from dry-capillary-blood antibody-positive in 1.3% (95% CI 0.9-1.7%, population-weighted, corrected for sensitivity = 0.811, specificity = 0.997). Seroprevalence was 1.7% (95% CI 1.2-2.3%) when additionally correcting for antibody decay. Overall infection prevalence including self-reports was 2.1%. We estimate 45% (95% CI 21-60%) undetected cases and lower detection in socioeconomically deprived districts. Prior SARS-CoV-2 testing was reported by 18% from the lower educational group vs. 25% and 26% from the medium and high educational group (p < 0.001, global test over three categories). Symptom-triggered test frequency was similar across educational groups. Routine testing was more common in low-educated adults, whereas travel-related testing and testing after contact with infected persons was more common in highly educated groups. This countrywide very low pre-vaccine seroprevalence in Germany at the end of 2020 can serve to evaluate the containment strategy. Our findings on social disparities indicate improvement potential in pandemic planning for people in socially disadvantaged circumstances.
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Affiliation(s)
- Hannelore Neuhauser
- Robert Koch Institute, Berlin, Germany.
- Department of Epidemiology and Health Monitoring, Robert Koch Institute, General-Pape-Str. 62-66, 12101, Berlin, Germany.
| | | | | | | | | | | | | | | | | | | | - Hans W Steinhauer
- Socio-Economic Panel, German Institute for Economic Research, Berlin, Germany
| | | | | | | | - Stefan Liebig
- Socio-Economic Panel, German Institute for Economic Research, Berlin, Germany
- SOEP & Department of Political and Social Sciences, Free University, Berlin, Germany
| | | | - Markus M Grabka
- Socio-Economic Panel, German Institute for Economic Research, Berlin, Germany
| | - Sabine Zinn
- Socio-Economic Panel, German Institute for Economic Research, Berlin, Germany
- SOEP & Department of Social Sciences, Humboldt University, Berlin, Germany
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17
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Waggershauser CH, Tillack-Schreiber C, Weyh P, Alt E, Siegmund T, Berchthold-Benchieb C, Szokodi D, Schnitzler F, Ochsenkühn T. Impact of Immunotherapies on SARS-CoV-2-Infections and Other Respiratory Tract Infections during the COVID-19 Winter Season in IBD Patients. Can J Gastroenterol Hepatol 2022; 2022:3469789. [PMID: 36060521 PMCID: PMC9433291 DOI: 10.1155/2022/3469789] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/29/2022] [Revised: 06/18/2022] [Accepted: 06/21/2022] [Indexed: 11/17/2022] Open
Abstract
Background COVID-19 represents one of the most significant medical problems of our time. Aims This study is focused on the question whether patients with inflammatory bowel disease (IBD) who receive immunotherapies are more vulnerable to respiratory tract infections and SARS-CoV-2 infections in comparison to medical staff, as a cohort with an increased infection risk, and to the general population in a COVID-19 hotspot. Methods We analysed data regarding respiratory tract infections that were collected in our IBD registry and compared them with corresponding data from medical employees in our associated Isarklinikum hospital and from the healthy general population in Munich, Germany, over the same time frame in April and June 2020. Patients were tested for SARS-CoV-2 immunoglobulins (Ig). Results Symptoms of respiratory tract infections occurred equally frequent in IBD patients with immunotherapies as compared to those without. Older age (>49 years), TNF-inhibitor, and ustekinumab treatment showed a significantly protective role in preventing respiratory tract symptomatic COVID-19 infections that occurred in 0.45% of all our 1.091 IBD patients. Of those, 1.8% were positive for SARS-CoV-2 Ig, identically to the general population of Munich with also 1.8% positivity. Whilst more than 3% of all COVID-19 subjects of the general population died during the first wave, none of our IBD patients died or needed referral to the ICU or oxygen treatment. Conclusions In our study, IBD patients are as susceptible to respiratory tract infections or SARS-CoV-2 as the normal population. There is no evidence of an association between IBD therapies and increased risk of COVID-19. Interestingly, a reduced rate of COVID-19 deaths in IBD patients, the majority on immunomodulator therapy, was observed, compared to the general population. Therefore, no evidence was found to suggest that IBD medication should be withheld, and adherence should be encouraged to prevent flares. In addition to older age (>49 years), TNF inhibitors and ustekinumab show a protective role in preventing respiratory tract infections. In addition, these results add to the growing evidence that supports further investigation of TNF inhibitors as a possible treatment in the early course of severe COVID-19.
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Affiliation(s)
| | | | - Paul Weyh
- Synesis Research, Sonnenstraße 29, 80331 Munich, Germany
| | - Eckard Alt
- Isarklinikum, Sonnenstraße 24-26, 81244 Munich, Germany
| | | | | | - Daniel Szokodi
- IBD Center Munich, Sonnenstraße 29, 80331 Munich, Germany
| | - Fabian Schnitzler
- Synesis Research, Sonnenstraße 29, 80331 Munich, Germany
- Ludwig-Maximilians-University of Munich, Marchioninistraße 15, 81377 Munich, Germany
| | - Thomas Ochsenkühn
- IBD Center Munich, Sonnenstraße 29, 80331 Munich, Germany
- Isarklinikum, Sonnenstraße 24-26, 81244 Munich, Germany
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18
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Oberste M, Pusch LM, Roth R, Shah-Hosseini K, Schmitz J, Heger E, Dewald F, Müller C, von Goltzheim LS, Lehmann C, Buess M, Wolff A, Fätkenheuer G, Wiesmüller G, Klein F, Rosenberger KD, Neuhann F, Hellmich M. Results of the Cologne Corona surveillance (CoCoS) study - a prospective population-based cohort study: incidence data and potential underestimation of new SARS-CoV-2 adult infections by health authorities. BMC Public Health 2022; 22:1379. [PMID: 35854283 PMCID: PMC9294849 DOI: 10.1186/s12889-022-13745-1] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/22/2021] [Accepted: 06/28/2022] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND Current incidence estimates of SARS-CoV-2 in Germany rely to a large extent on case notifications. However, the large number of mild or asymptomatic infections is likely to result in underestimation. Population-based studies can provide valid estimates of the SARS-CoV-2 incidence and thus support health authorities to monitor the epidemiological situation and to initiate, maintain, strengthen or relax effective countermeasures. METHODS This study was conducted in Cologne, Germany. Six-thousand randomly drawn Cologne residents, 18 years of age or older, were contacted by mail in March 2021. Study envelopes contained a kit for self-administered saliva sample and access details to a questionnaire on sociodemographic characteristics, previous positive SARS-CoV-2 RT-qPCR and completed COVID-19 vaccinations. Participants were again invited for a second round in June 2021, while those who declined participation were replaced by additional randomly drawn Cologne residents in order to reach a total of 6000 potential participants again. The saliva samples were sent to the laboratory by mail and tested for SARS-CoV-2 using RT-qPCR. The incidence estimates were adjusted for sensitivity and specificity of the test procedure and compared with the official numbers of new SARS-CoV-2 cases in the adult Cologne population. RESULTS The first surveillance round in March 2021 (response rate: 34.08%, N = 2045) showed a SARS-CoV-2 seven-day incidence of 85 cases per 100,000 adult Cologne residents (95% CI: 9 to 319). In the same period, the officially registered cases were 125 per 100,000. The second surveillance round in June 2021 (response rate: 36.53%, N = 2192) showed a seven-day incidence of 27 per 100,000 adult Cologne residents (95% CI: 1 to 142), while the official figures for newly registered SARS-CoV-2 cases in the same period were 15 per 100,000. CONCLUSIONS The incidence estimates do not indicate relevant underestimation of new SARS-CoV-2 infections based on case notification. Regular use of the surveillance method developed here may nevertheless complement the efforts of the health authorities to assess the epidemiological situation. TRIAL REGISTRATION DRKS.de, German Clinical Trials Register (DRKS), Identifier: DRKS00024046 , Registered on 25 February 2021.
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Affiliation(s)
- Max Oberste
- Institute of Medical Statistics and Computational Biology, Medical Faculty and University Hospital Cologne, University of Cologne, Robert-Koch-Straße 10, 50931, Cologne, Germany
| | - Lynn-Marie Pusch
- Institute of Medical Statistics and Computational Biology, Medical Faculty and University Hospital Cologne, University of Cologne, Robert-Koch-Straße 10, 50931, Cologne, Germany
| | - Rebecca Roth
- Institute of Medical Statistics and Computational Biology, Medical Faculty and University Hospital Cologne, University of Cologne, Robert-Koch-Straße 10, 50931, Cologne, Germany
| | - Kija Shah-Hosseini
- Institute of Medical Statistics and Computational Biology, Medical Faculty and University Hospital Cologne, University of Cologne, Robert-Koch-Straße 10, 50931, Cologne, Germany
| | - Jana Schmitz
- Institute of Virology, Medical Faculty and University Hospital Cologne, University of Cologne, Fürst-Pückler-Straße 56, 50935, Cologne, Germany
| | - Eva Heger
- Institute of Virology, Medical Faculty and University Hospital Cologne, University of Cologne, Fürst-Pückler-Straße 56, 50935, Cologne, Germany
| | - Felix Dewald
- Institute of Virology, Medical Faculty and University Hospital Cologne, University of Cologne, Fürst-Pückler-Straße 56, 50935, Cologne, Germany
| | - Claudia Müller
- Institute of Virology, Medical Faculty and University Hospital Cologne, University of Cologne, Fürst-Pückler-Straße 56, 50935, Cologne, Germany
| | - Luise Stach von Goltzheim
- Institute of Medical Statistics and Computational Biology, Medical Faculty and University Hospital Cologne, University of Cologne, Robert-Koch-Straße 10, 50931, Cologne, Germany
| | - Clara Lehmann
- Department of Internal Medicine, Medical Faculty and University Hospital Cologne, University of Cologne, Kerpener Str. 62, 50931, Cologne, Germany
| | | | - Anna Wolff
- Cologne Health Authority, Cologne, Germany
| | - Gerd Fätkenheuer
- Department of Internal Medicine, Medical Faculty and University Hospital Cologne, University of Cologne, Kerpener Str. 62, 50931, Cologne, Germany
| | | | - Florian Klein
- Institute of Virology, Medical Faculty and University Hospital Cologne, University of Cologne, Fürst-Pückler-Straße 56, 50935, Cologne, Germany
| | - Kerstin Daniela Rosenberger
- Institute of Medical Statistics and Computational Biology, Medical Faculty and University Hospital Cologne, University of Cologne, Robert-Koch-Straße 10, 50931, Cologne, Germany
| | - Florian Neuhann
- 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
- Institute of Medical Statistics and Computational Biology, Medical Faculty and University Hospital Cologne, University of Cologne, Robert-Koch-Straße 10, 50931, Cologne, Germany.
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19
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Balck A, Föh B, Borsche M, Rahmöller J, Vollstedt EJ, Waldeck F, Käding N, Twesten C, Mischnik A, Gillessen-Kaesbach G, Ehlers M, Sina C, Taube S, Busch H, Rupp J, Katalinic A, Klein C. Protocol of the Luebeck longitudinal investigation of SARS-CoV-2 infection (ELISA) study - a prospective population-based cohort study. BMC Public Health 2022; 22:1305. [PMID: 35799167 PMCID: PMC9261226 DOI: 10.1186/s12889-022-13666-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/05/2022] [Accepted: 06/03/2022] [Indexed: 11/23/2022] Open
Abstract
Background Considering the insufficiently controlled spread of new SARS-CoV-2 variants, partially low vaccination rates, and increased risk of a post-COVID syndrome, well-functioning, targeted intervention measures at local and national levels are urgently needed to contain the SARS-CoV-2 pandemic. Surveillance concepts (cross-sectional, cohorts, clusters) need to be carefully selected to monitor and assess incidence and prevalence at the population level. A critical methodological gap for identifying specific risks/dynamics for SARS-Cov-2 transmission and post-COVID-19-syndrome includes repetitive testing for past or present infection of a defined cohort with simultaneous assessment of symptoms, behavior, risk, and protective factors, as well as quality of life. Methods The ELISA-Study is a longitudinal, prospective surveillance study with a cohort approach launched in Luebeck in April 2020. The first part comprised regular PCR testing, antibody measurements, and a recurrent App-based questionnaire for a population-based cohort of 3000 inhabitants of Luebeck. The follow-up study protocol includes self-testing for antibodies and PCR testing for a subset of the participants, focusing on studying immunity after vaccination and/or infection and post-COVID-19 symptoms. Discussion The ELISA cohort and our follow-up study protocol will enable us to study the effects of a sharp increase of SARS-CoV-2 infections on seroprevalence of Anti-SARS-CoV-2 antibodies, post-COVID-19-symptoms, and possible medical, occupational, and behavioral risk factors. We will be able to monitor the pandemic continuously and discover potential sequelae of an infection long-term. Further examinations can be readily set up on an ad-hoc basis in the future. Our study protocol can be adapted to other regions and settings and is transferable to other infectious diseases. Trial registration DRKS.de, German Clinical Trials Register (DRKS), Identifier: DRKS00023418, Registered on 28 October 2020. Supplementary Information The online version contains supplementary material available at 10.1186/s12889-022-13666-z.
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Affiliation(s)
- Alexander Balck
- Institute of Neurogenetics, University of Lübeck and University Hospital Schleswig-Holstein, Lübeck, Germany.,Department of Neurology, University of Lübeck and University Hospital Schleswig-Holstein, Lübeck, Germany
| | - Bandik Föh
- Institute of Nutritional Medicine, University of Lübeck, Lübeck, Germany.,Department of Medicine I, University Hospital Schleswig-Holstein, Lübeck, Germany
| | - Max Borsche
- Institute of Neurogenetics, University of Lübeck and University Hospital Schleswig-Holstein, Lübeck, Germany.,Department of Neurology, University of Lübeck and University Hospital Schleswig-Holstein, Lübeck, Germany
| | - Johann Rahmöller
- Institute of Nutritional Medicine, University of Lübeck, Lübeck, Germany.,Department of Anesthesiology and Intensive Care, University of Lübeck and University Hospital Schleswig-Holstein, Lübeck, Germany
| | - Eva-Juliane Vollstedt
- Institute of Neurogenetics, University of Lübeck and University Hospital Schleswig-Holstein, Lübeck, Germany
| | - Frederike Waldeck
- Department of Infectious Diseases and Microbiology, University of Lübeck and University Hospital Schleswig-Holstein, Campus Lübeck, Lübeck, Germany
| | - Nadja Käding
- Department of Infectious Diseases and Microbiology, University of Lübeck and University Hospital Schleswig-Holstein, Campus Lübeck, Lübeck, Germany
| | | | | | | | - Marc Ehlers
- Institute of Nutritional Medicine, University of Lübeck, Lübeck, Germany
| | - Christian Sina
- Institute of Nutritional Medicine, University of Lübeck, Lübeck, Germany
| | - Stefan Taube
- Institute of Virology and Cell Biology, University of Lübeck, Lübeck, Germany
| | - Hauke Busch
- Lübeck Institute of Experimental Dermatology (LIED), University of Lübeck, Lübeck, Germany
| | - Jan Rupp
- Department of Infectious Diseases and Microbiology, University of Lübeck and University Hospital Schleswig-Holstein, Campus Lübeck, Lübeck, Germany
| | - Alexander Katalinic
- Institute of Social Medicine and Epidemiology, University of Lübeck, Lübeck, Germany
| | - Christine Klein
- Institute of Neurogenetics, University of Lübeck and University Hospital Schleswig-Holstein, Lübeck, Germany.
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20
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Determinants of SARS-CoV-2 Infection in the Older Adult Population: Data from the LOST in Lombardia Study. Vaccines (Basel) 2022; 10:vaccines10070989. [PMID: 35891155 PMCID: PMC9324825 DOI: 10.3390/vaccines10070989] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/25/2022] [Revised: 06/14/2022] [Accepted: 06/20/2022] [Indexed: 11/17/2022] Open
Abstract
Most COVID-19 fatalities have occurred among older adults; however, evidence regarding the determinants of SARS-CoV-2 infection in this population is limited. Telephone interviews were conducted in November 2020 with a representative sample of 4400 Italians aged ≥65 years from the Lombardy region. We determined the prevalence of a history of SARS-CoV-2 infection. Through unconditional multiple logistic regression models, we estimated the odds ratios (ORs) of infection and the corresponding 95% confidence intervals (CIs). We further evaluated whether infection was related to a reduction in mental wellbeing. Of the participants, 4.9% reported a previous infection. No significant relationship between sex and infection was observed. Prior infection was less frequently reported in subjects aged ≥70 (OR = 0.55; 95% CI: 0.41–0.74) compared to 65–69 years, with no trend after 70 years of age. Those with at least one chronic condition reported a lower infection rate compared to healthy subjects (OR = 0.68; 95% CI: 0.49–0.93). Participants who lived alone more frequently reported infection than those who cohabited (OR = 2.33; 95% CI: 1.29–4.20). Prior infection was related to increased depressive symptoms (OR = 1.57; 95% CI: 1.17–2.10). This representative study of people aged ≥65 years suggests that in Italy, the oldest subjects and chronic patients less frequently exposed themselves to SARS-CoV-2 infection.
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21
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Einhauser S, Peterhoff D, Beileke S, Günther F, Niller HH, Steininger P, Knöll A, Korn K, Berr M, Schütz A, Wiegrebe S, Stark KJ, Gessner A, Burkhardt R, Kabesch M, Schedl H, Küchenhoff H, Pfahlberg AB, Heid IM, Gefeller O, Überla K, Wagner R. Time Trend in SARS-CoV-2 Seropositivity, Surveillance Detection- and Infection Fatality Ratio until Spring 2021 in the Tirschenreuth County-Results from a Population-Based Longitudinal Study in Germany. Viruses 2022; 14:v14061168. [PMID: 35746640 PMCID: PMC9228731 DOI: 10.3390/v14061168] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/29/2022] [Revised: 05/20/2022] [Accepted: 05/24/2022] [Indexed: 12/02/2022] Open
Abstract
Herein, we provide results from a prospective population-based longitudinal follow-up (FU) SARS-CoV-2 serosurveillance study in Tirschenreuth, the county which was hit hardest in Germany in spring 2020 and early 2021. Of 4203 individuals aged 14 years or older enrolled at baseline (BL, June 2020), 3546 participated at FU1 (November 2020) and 3391 at FU2 (April 2021). Key metrics comprising standardized seroprevalence, surveillance detection ratio (SDR), infection fatality ratio (IFR) and success of the vaccination campaign were derived using the Roche N- and S-Elecsys anti-SARS-CoV-2 test together with a self-administered questionnaire. N-seropositivity at BL was 9.2% (1st wave). While we observed a low new seropositivity between BL and FU1 (0.9%), the combined 2nd and 3rd wave accounted for 6.1% new N-seropositives between FU1 and FU2 (ever seropositives at FU2: 15.4%). The SDR decreased from 5.4 (BL) to 1.1 (FU2) highlighting the success of massively increased testing in the population. The IFR based on a combination of serology and registration data resulted in 3.3% between November 2020 and April 2021 compared to 2.3% until June 2020. Although IFRs were consistently higher at FU2 compared to BL across age-groups, highest among individuals aged 70+ (18.3% versus 10.7%, respectively), observed differences were within statistical uncertainty bounds. While municipalities with senior care homes showed a higher IFR at BL (3.0% with senior care home vs. 0.7% w/o), this effect diminished at FU2 (3.4% vs. 2.9%). In April 2021 (FU2), vaccination rate in the elderly was high (>77.4%, age-group 80+).
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Affiliation(s)
- Sebastian Einhauser
- Institute of Medical Microbiology and Hygiene, Molecular Microbiology (Virology), University of Regensburg, Franz-Josef-Strauß-Allee 11, 93053 Regensburg, Germany; (S.E.); (D.P.); (H.-H.N.); (M.B.); (A.S.); (A.G.)
| | - David Peterhoff
- Institute of Medical Microbiology and Hygiene, Molecular Microbiology (Virology), University of Regensburg, Franz-Josef-Strauß-Allee 11, 93053 Regensburg, Germany; (S.E.); (D.P.); (H.-H.N.); (M.B.); (A.S.); (A.G.)
- Institute of Clinical Microbiology and Hygiene, University Hospital Regensburg, Franz-Josef-Strauß-Allee 11, 93053 Regensburg, Germany
| | - Stephanie Beileke
- Institute of Clinical and Molecular Virology, University Hospital Erlangen, Friedrich-Alexander Universität Erlangen-Nürnberg, Schlossgarten 4, 91054 Erlangen, Germany; (S.B.); (P.S.); (A.K.); (K.K.)
| | - Felix Günther
- Department of Mathematics, Stockholm University, Kräftriket 6, 106 91 Stockholm, Sweden;
- Department of Genetic Epidemiology, University of Regensburg, Franz-Josef-Strauß-Allee 11, 93053 Regensburg, Germany; (S.W.); (K.J.S.); (I.M.H.)
| | - Hans-Helmut Niller
- Institute of Medical Microbiology and Hygiene, Molecular Microbiology (Virology), University of Regensburg, Franz-Josef-Strauß-Allee 11, 93053 Regensburg, Germany; (S.E.); (D.P.); (H.-H.N.); (M.B.); (A.S.); (A.G.)
| | - Philipp Steininger
- Institute of Clinical and Molecular Virology, University Hospital Erlangen, Friedrich-Alexander Universität Erlangen-Nürnberg, Schlossgarten 4, 91054 Erlangen, Germany; (S.B.); (P.S.); (A.K.); (K.K.)
| | - Antje Knöll
- Institute of Clinical and Molecular Virology, University Hospital Erlangen, Friedrich-Alexander Universität Erlangen-Nürnberg, Schlossgarten 4, 91054 Erlangen, Germany; (S.B.); (P.S.); (A.K.); (K.K.)
| | - Klaus Korn
- Institute of Clinical and Molecular Virology, University Hospital Erlangen, Friedrich-Alexander Universität Erlangen-Nürnberg, Schlossgarten 4, 91054 Erlangen, Germany; (S.B.); (P.S.); (A.K.); (K.K.)
| | - Melanie Berr
- Institute of Medical Microbiology and Hygiene, Molecular Microbiology (Virology), University of Regensburg, Franz-Josef-Strauß-Allee 11, 93053 Regensburg, Germany; (S.E.); (D.P.); (H.-H.N.); (M.B.); (A.S.); (A.G.)
| | - Anja Schütz
- Institute of Medical Microbiology and Hygiene, Molecular Microbiology (Virology), University of Regensburg, Franz-Josef-Strauß-Allee 11, 93053 Regensburg, Germany; (S.E.); (D.P.); (H.-H.N.); (M.B.); (A.S.); (A.G.)
| | - Simon Wiegrebe
- Department of Genetic Epidemiology, University of Regensburg, Franz-Josef-Strauß-Allee 11, 93053 Regensburg, Germany; (S.W.); (K.J.S.); (I.M.H.)
| | - Klaus J. Stark
- Department of Genetic Epidemiology, University of Regensburg, Franz-Josef-Strauß-Allee 11, 93053 Regensburg, Germany; (S.W.); (K.J.S.); (I.M.H.)
| | - André Gessner
- Institute of Medical Microbiology and Hygiene, Molecular Microbiology (Virology), University of Regensburg, Franz-Josef-Strauß-Allee 11, 93053 Regensburg, Germany; (S.E.); (D.P.); (H.-H.N.); (M.B.); (A.S.); (A.G.)
- Institute of Clinical Microbiology and Hygiene, University Hospital Regensburg, Franz-Josef-Strauß-Allee 11, 93053 Regensburg, Germany
| | - Ralph Burkhardt
- Institute of Clinical Chemistry and Laboratory Medicine, University Hospital Regensburg, Franz-Josef-Strauß-Allee 11, 93053 Regensburg, Germany;
| | - Michael Kabesch
- University Children’s Hospital Regensburg (KUNO) at the Hospital St. Hedwig of the Order of St. John, University of Regensburg, Steinmetzstraße 1-3, 93049 Regensburg, Germany;
| | - Holger Schedl
- Bayerisches Rotes Kreuz, Kreisverband Tirschenreuth, Egerstraße 21, 95643 Tirschenreuth, Germany;
| | - Helmut Küchenhoff
- Statistical Consulting Unit StaBLab, Department of Statistics, LMU Munich, Geschwister-Scholl-Platz 1, 80539 Munich, Germany;
| | - Annette B. Pfahlberg
- Department of Medical Informatics, Biometry and Epidemiology, Friedrich-Alexander Universität Erlangen-Nürnberg (FAU), Waldstr. 6, 91054 Erlangen, Germany; (A.B.P.); (O.G.)
| | - Iris M. Heid
- Department of Genetic Epidemiology, University of Regensburg, Franz-Josef-Strauß-Allee 11, 93053 Regensburg, Germany; (S.W.); (K.J.S.); (I.M.H.)
| | - Olaf Gefeller
- Department of Medical Informatics, Biometry and Epidemiology, Friedrich-Alexander Universität Erlangen-Nürnberg (FAU), Waldstr. 6, 91054 Erlangen, Germany; (A.B.P.); (O.G.)
| | - Klaus Überla
- Institute of Clinical and Molecular Virology, University Hospital Erlangen, Friedrich-Alexander Universität Erlangen-Nürnberg, Schlossgarten 4, 91054 Erlangen, Germany; (S.B.); (P.S.); (A.K.); (K.K.)
- Correspondence: (K.Ü.); (R.W.); Tel.: +49-9131-85-23563 (K.Ü.); +49-941-944-6452 (R.W.)
| | - Ralf Wagner
- Institute of Medical Microbiology and Hygiene, Molecular Microbiology (Virology), University of Regensburg, Franz-Josef-Strauß-Allee 11, 93053 Regensburg, Germany; (S.E.); (D.P.); (H.-H.N.); (M.B.); (A.S.); (A.G.)
- Institute of Clinical Microbiology and Hygiene, University Hospital Regensburg, Franz-Josef-Strauß-Allee 11, 93053 Regensburg, Germany
- Correspondence: (K.Ü.); (R.W.); Tel.: +49-9131-85-23563 (K.Ü.); +49-941-944-6452 (R.W.)
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22
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Lohse S, Sternjakob-Marthaler A, Lagemann P, Schöpe J, Rissland J, Seiwert N, Pfuhl T, Müllendorff A, Kiefer LS, Vogelgesang M, Vella L, Denk K, Vicari J, Zwick A, Lang I, Weber G, Geisel J, Rech J, Schnabel B, Hauptmann G, Holleczek B, Scheiblauer H, Wagenpfeil S, Smola S. German federal-state-wide seroprevalence study of 1 st SARS-CoV-2 pandemic wave shows importance of long-term antibody test performance. COMMUNICATIONS MEDICINE 2022; 2:52. [PMID: 35603305 PMCID: PMC9117207 DOI: 10.1038/s43856-022-00100-z] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/05/2021] [Accepted: 03/09/2022] [Indexed: 12/12/2022] Open
Abstract
Background Reliable data on the adult SARS-CoV-2 infection fatality rate in Germany are still scarce. We performed a federal state-wide cross-sectional seroprevalence study named SaarCoPS, that is representative for the adult population including elderly individuals and nursing home residents in the Saarland. Methods Serum was collected from 2940 adults via stationary or mobile teams during the 1st pandemic wave steady state period. We selected an antibody test system with maximal specificity, also excluding seroreversion effects due to a high longitudinal test performance. For the calculations of infection and fatality rates, we accounted for the delays of seroconversion and death after infection. Results Using a highly specific total antibody test detecting anti-SARS-CoV-2 responses over more than 180 days, we estimate an adult infection rate of 1.02% (95% CI: [0.64; 1.44]), an underreporting rate of 2.68-fold (95% CI: [1.68; 3.79]) and infection fatality rates of 2.09% (95% CI: (1.48; 3.32]) or 0.36% (95% CI: [0.25; 0.59]) in all adults including elderly individuals, or adults younger than 70 years, respectively. Conclusion The study highlights the importance of study design and test performance for seroprevalence studies, particularly when seroprevalences are low. Our results provide a valuable baseline for evaluation of future pandemic dynamics and impact of public health measures on virus spread and human health in comparison to neighbouring countries such as Luxembourg or France.
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Affiliation(s)
- Stefan Lohse
- Institute of Virology, Saarland University Medical Center, 66421 Homburg, Germany
| | | | - Paul Lagemann
- Institute of Virology, Saarland University Medical Center, 66421 Homburg, Germany
| | - Jakob Schöpe
- Institute for Medical Biometry, Epidemiology and Medical Informatics, Saarland University Medical Center, 66421 Homburg, Germany
| | - Jürgen Rissland
- Institute of Virology, Saarland University Medical Center, 66421 Homburg, Germany
| | - Nastasja Seiwert
- Institute of Virology, Saarland University Medical Center, 66421 Homburg, Germany
| | - Thorsten Pfuhl
- Institute of Virology, Saarland University Medical Center, 66421 Homburg, Germany
| | - Alana Müllendorff
- Institute of Virology, Saarland University Medical Center, 66421 Homburg, Germany
| | - Laurent S Kiefer
- Institute of Virology, Saarland University Medical Center, 66421 Homburg, Germany
| | - Markus Vogelgesang
- Institute of Virology, Saarland University Medical Center, 66421 Homburg, Germany
| | - Luca Vella
- Institute of Virology, Saarland University Medical Center, 66421 Homburg, Germany
| | - Katharina Denk
- Institute of Virology, Saarland University Medical Center, 66421 Homburg, Germany
| | - Julia Vicari
- Institute of Virology, Saarland University Medical Center, 66421 Homburg, Germany
| | - Anabel Zwick
- Institute of Virology, Saarland University Medical Center, 66421 Homburg, Germany
| | - Isabelle Lang
- Institute of Virology, Saarland University Medical Center, 66421 Homburg, Germany
| | - Gero Weber
- Physical Geography and Environmental Research, Saarland University, 66125 Saarbrücken, Germany
| | - Jürgen Geisel
- Central Laboratory, Saarland University Hospital, 66421 Homburg, Germany
| | - Jörg Rech
- Ministry of Health, Social Affairs, Women and the Family, 66119 Saarbrücken, Germany
| | - Bernd Schnabel
- Ministry of Health, Social Affairs, Women and the Family, 66119 Saarbrücken, Germany
| | - Gunter Hauptmann
- Kassenärztliche Vereinigung Saarland, 66113 Saarbrücken, Germany
| | - Bernd Holleczek
- Ministry of Health, Social Affairs, Women and the Family, 66119 Saarbrücken, Germany.,Saarland Cancer Registry, 66117 Saarbrücken, Germany
| | | | - Stefan Wagenpfeil
- Institute for Medical Biometry, Epidemiology and Medical Informatics, Saarland University Medical Center, 66421 Homburg, Germany
| | - Sigrun Smola
- Institute of Virology, Saarland University Medical Center, 66421 Homburg, Germany.,Helmholtz Institute for Pharmaceutical Research Saarland (HIPS), Helmholtz Centre for Infection Research (HZI), Saarland University Campus, 66123 Saarbrücken, Germany
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23
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Klein C, Borsche M, Balck A, Föh B, Rahmöller J, Peters E, Knickmann J, Lane M, Vollstedt EJ, Elsner SA, Käding N, Hauswaldt S, Lange T, Hundt JE, Lehrian S, Giese J, Mischnik A, Niemann S, Maurer F, Homolka S, Paulowski L, Kramer J, Twesten C, Sina C, Gillessen-Kaesbach G, Busch H, Ehlers M, Taube S, Rupp J, Katalinic A. One-year surveillance of SARS-CoV-2 transmission of the ELISA cohort: A model for population-based monitoring of infection risk. SCIENCE ADVANCES 2022; 8:eabm5016. [PMID: 35427158 PMCID: PMC9012459 DOI: 10.1126/sciadv.abm5016] [Citation(s) in RCA: 12] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/07/2023]
Abstract
With newly rising coronavirus disease 2019 (COVID-19) cases, important data gaps remain on (i) long-term dynamics of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection rates in fixed cohorts (ii) identification of risk factors, and (iii) establishment of effective surveillance strategies. By polymerase chain reaction and antibody testing of 1% of the local population and >90,000 app-based datasets, the present study surveilled a catchment area of 300,000 inhabitants from March 2020 to February 2021. Cohort (56% female; mean age, 45.6 years) retention was 75 to 98%. Increased risk for seropositivity was detected in several high-exposure groups, especially nurses. Unreported infections dropped from 92 to 29% during the study. "Contact to COVID-19-affected" was the strongest risk factor, whereas public transportation, having children in school, or tourism did not affect infection rates. With the first SARS-CoV-2 cohort study, we provide a transferable model for effective surveillance, enabling monitoring of reinfection rates and increased preparedness for future pandemics.
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Affiliation(s)
- Christine Klein
- Institute of Neurogenetics, University of Lübeck and University Hospital Schleswig-Holstein, Campus Lübeck, Lübeck, Germany
- Corresponding author.
| | - Max Borsche
- Institute of Neurogenetics, University of Lübeck and University Hospital Schleswig-Holstein, Campus Lübeck, Lübeck, Germany
| | - Alexander Balck
- Institute of Neurogenetics, University of Lübeck and University Hospital Schleswig-Holstein, Campus Lübeck, Lübeck, Germany
- Department of Neurology, University of Lübeckand and University Hospital Schleswig-Holstein, Campus Lübeck, Lübeck, Germany
| | - Bandik Föh
- Institute of Nutritional Medicine, University of Lübeck, Lübeck, Germany
- Department of Medicine I, University Hospital Schleswig-Holstein, Lübeck, Germany
| | - Johann Rahmöller
- Institute of Nutritional Medicine, University of Lübeck, Lübeck, Germany
- Department of Anesthesiology and Intensive Care, University Hospital Schleswig-Holstein, Lübeck, Germany
| | - Elke Peters
- Institute of Social Medicine and Epidemiology, University of Lübeck, Lübeck, Germany
| | - Jan Knickmann
- Institute of Virology and Cell Biology, University of Lübeck, Lübeck, Germany
| | - Miranda Lane
- Institute of Virology and Cell Biology, University of Lübeck, Lübeck, Germany
| | - Eva-Juliane Vollstedt
- Institute of Neurogenetics, University of Lübeck and University Hospital Schleswig-Holstein, Campus Lübeck, Lübeck, Germany
| | - Susanne A. Elsner
- Institute of Social Medicine and Epidemiology, University of Lübeck, Lübeck, Germany
| | - Nadja Käding
- Department of Infectious Diseases and Microbiology, University of Lübeck and University Hospital Schleswig-Holstein, Campus Lübeck, Lübeck, Germany
| | - Susanne Hauswaldt
- Department of Infectious Diseases and Microbiology, University of Lübeck and University Hospital Schleswig-Holstein, Campus Lübeck, Lübeck, Germany
| | - Tanja Lange
- Department of Rheumatology and Clinical Immunology, University of Lübeck and University Hospital Schleswig-Holstein, Campus Lübeck, Lübeck, Germany
| | - Jennifer E. Hundt
- Lübeck Institute of Experimental Dermatology (LIED), University of Lübeck, Lübeck, Germany
| | - Selina Lehrian
- Institute of Nutritional Medicine, University of Lübeck, Lübeck, Germany
| | - Julia Giese
- Institute of Nutritional Medicine, University of Lübeck, Lübeck, Germany
| | | | - Stefan Niemann
- Research Center Borstel, Leibniz Lung Center, Borstel, Germany
- German Center for Infection Research (DZIF), Partner site Hamburg-Lübeck-Borstel-Riems, Borstel, Germany
| | - Florian Maurer
- Research Center Borstel, Leibniz Lung Center, Borstel, Germany
| | - Susanne Homolka
- Research Center Borstel, Leibniz Lung Center, Borstel, Germany
| | - Laura Paulowski
- Research Center Borstel, Leibniz Lung Center, Borstel, Germany
| | - Jan Kramer
- Institute of Virology and Cell Biology, University of Lübeck, Lübeck, Germany
- LADR Laboratory Group Dr. Kramer & Colleagues, Geesthacht, Germany
| | | | - Christian Sina
- Institute of Nutritional Medicine, University of Lübeck, Lübeck, Germany
| | | | - Hauke Busch
- Lübeck Institute of Experimental Dermatology (LIED), University of Lübeck, Lübeck, Germany
| | - Marc Ehlers
- Institute of Nutritional Medicine, University of Lübeck, Lübeck, Germany
| | - Stefan Taube
- Institute of Virology and Cell Biology, University of Lübeck, Lübeck, Germany
| | - Jan Rupp
- Department of Infectious Diseases and Microbiology, University of Lübeck and University Hospital Schleswig-Holstein, Campus Lübeck, Lübeck, Germany
| | - Alexander Katalinic
- Institute of Social Medicine and Epidemiology, University of Lübeck, Lübeck, Germany
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24
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Hohl HT, Heumann C, Rothe C, Hoelscher M, Janke C, Froeschl G. COVID-19 Testing Unit Munich: Impact of Public Health and Safety Measures on Patient Characteristics and Test Results, January to September 2020. Front Public Health 2022; 10:856189. [PMID: 35392481 PMCID: PMC8980425 DOI: 10.3389/fpubh.2022.856189] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/16/2022] [Accepted: 02/25/2022] [Indexed: 11/13/2022] Open
Abstract
To assess the course of the COVID-19 pandemic and the impact of non-pharmaceutical interventions, the number of reported positive test results is frequently used as an estimate of the true number of population-wide infections. We conducted a retrospective observational analysis of patient data of the Corona Testing Unit (CTU) in Munich, Bavaria, Germany between January 27th, and September 30th, 2020. We analyzed the course of daily patient numbers over time by fitting a negative binomial model with multiple breakpoints. Additionally, we investigated possible influencing factors on patient numbers and characteristics by literature review of policy papers and key informant interviews with individuals involved in the set-up of the CTU. The 3,963 patients included were mostly young (median age: 34, interquartile range: 27–48), female (66.2%), and working in the healthcare sector (77%). For these, 5,314 real-time RT-PCR tests were conducted with 157 (2.94%) positive results. The overall curve of daily tests and positive results fits the re-ported state-wide incidence in large parts but shows multiple breakpoints with considerable trend changes. These can be most fittingly attributed to testing capacities and -strategies and individual risk behavior, rather than public health measures. With the large impact on patient numbers and pre-test probabilities of various strategic and operational factors, we consider the derived re-ported incidence as a poor measurement to base policy decisions on. Testing units should be prepared to encounter these fluctuations with a quickly adaptable structure.
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Affiliation(s)
- Hannah Tuulikki Hohl
- Division of Infectious Diseases and Tropical Medicine, University Hospital, LMU Munich, Munich, Germany
| | - Christian Heumann
- Department of Statistics, Faculty of Mathematics, Informatics and Statistics, University of Munich, Ludwig-Maximilians-Universität (LMU), Munich, Germany
| | - Camilla Rothe
- Division of Infectious Diseases and Tropical Medicine, University Hospital, LMU Munich, Munich, Germany
| | - Michael Hoelscher
- Division of Infectious Diseases and Tropical Medicine, University Hospital, LMU Munich, Munich, Germany.,German Center for Infection Research (DZIF), Partner Site Munich, Braunschweig, Germany
| | - Christian Janke
- Division of Infectious Diseases and Tropical Medicine, University Hospital, LMU Munich, Munich, Germany
| | - Guenter Froeschl
- Division of Infectious Diseases and Tropical Medicine, University Hospital, LMU Munich, Munich, Germany.,German Center for Infection Research (DZIF), Partner Site Munich, Braunschweig, Germany
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25
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Puchinger K, Castelletti N, Rubio-Acero R, Geldmacher C, Eser TM, Deák F, Paunovic I, Bakuli A, Saathoff E, von Meyer A, Markgraf A, Falk P, Reich J, Riess F, Girl P, Müller K, Radon K, Guggenbuehl Noller JM, Wölfel R, Hoelscher M, Kroidl I, Wieser A, Olbrich L. The interplay of viral loads, clinical presentation, and serological responses in SARS-CoV-2 - Results from a prospective cohort of outpatient COVID-19 cases. Virology 2022; 569:37-43. [PMID: 35245784 PMCID: PMC8855229 DOI: 10.1016/j.virol.2022.02.002] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/27/2021] [Revised: 02/15/2022] [Accepted: 02/15/2022] [Indexed: 11/24/2022]
Abstract
Risk factors for disease progression and severity of SARS-CoV-2 infections require an understanding of acute and long-term virological and immunological dynamics. Fifty-one RT-PCR positive COVID-19 outpatients were recruited between May and December 2020 in Munich, Germany, and followed up at multiple defined timepoints for up to one year. RT-PCR and viral culture were performed and seroresponses measured. Participants were classified applying the WHO clinical progression scale. Short symptom to test time (median 5.0 days; p = 0.0016) and high viral loads (VL; median maximum VL: 3∙108 copies/mL; p = 0.0015) were indicative for viral culture positivity. Participants with WHO grade 3 at baseline had significantly higher VLs compared to those with WHO 1 and 2 (p = 0.01). VLs dropped fast within 1 week of symptom onset. Maximum VLs were positively correlated with the magnitude of Ro-N-Ig seroresponse (p = 0.022). Our results describe the dynamics of VLs and antibodies to SARS-CoV-2 in mild to moderate cases that can support public health measures during the ongoing global pandemic.
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Affiliation(s)
- Kerstin Puchinger
- Division of Infectious Diseases and Tropical Medicine, University Hospital, LMU Munich, 80802, Munich, Germany
| | - Noemi Castelletti
- Division of Infectious Diseases and Tropical Medicine, University Hospital, LMU Munich, 80802, Munich, Germany; Institute of Radiation Medicine, Helmholtz Zentrum München, 85764, Neuherberg, Germany.
| | - Raquel Rubio-Acero
- Division of Infectious Diseases and Tropical Medicine, University Hospital, LMU Munich, 80802, Munich, Germany
| | - Christof Geldmacher
- Division of Infectious Diseases and Tropical Medicine, University Hospital, LMU Munich, 80802, Munich, Germany; German Center for Infection Research (DZIF), Partner Site Munich, Germany
| | - Tabea M Eser
- Division of Infectious Diseases and Tropical Medicine, University Hospital, LMU Munich, 80802, Munich, Germany; German Center for Infection Research (DZIF), Partner Site Munich, Germany
| | - Flora Deák
- Division of Infectious Diseases and Tropical Medicine, University Hospital, LMU Munich, 80802, Munich, Germany; German Center for Infection Research (DZIF), Partner Site Munich, Germany
| | - Ivana Paunovic
- Division of Infectious Diseases and Tropical Medicine, University Hospital, LMU Munich, 80802, Munich, Germany
| | - Abhishek Bakuli
- Division of Infectious Diseases and Tropical Medicine, University Hospital, LMU Munich, 80802, Munich, Germany
| | - Elmar Saathoff
- Division of Infectious Diseases and Tropical Medicine, University Hospital, LMU Munich, 80802, Munich, Germany; German Center for Infection Research (DZIF), Partner Site Munich, Germany
| | - Alexander von Meyer
- Institute for Laboratory Medicine, Medical Microbiology and Technical Hygienics, Munich Municipal Hospital Group, 81675, Munich, Germany
| | - Alisa Markgraf
- Division of Infectious Diseases and Tropical Medicine, University Hospital, LMU Munich, 80802, Munich, Germany
| | - Philine Falk
- Division of Infectious Diseases and Tropical Medicine, University Hospital, LMU Munich, 80802, Munich, Germany
| | - Jakob Reich
- Division of Infectious Diseases and Tropical Medicine, University Hospital, LMU Munich, 80802, Munich, Germany
| | - Friedrich Riess
- Division of Infectious Diseases and Tropical Medicine, University Hospital, LMU Munich, 80802, Munich, Germany; German Center for Infection Research (DZIF), Partner Site Munich, Germany
| | - Philipp Girl
- German Center for Infection Research (DZIF), Partner Site Munich, Germany; Bundeswehr Institute of Microbiology, 80937, Munich, Germany
| | - Katharina Müller
- German Center for Infection Research (DZIF), Partner Site Munich, Germany; Bundeswehr Institute of Microbiology, 80937, Munich, Germany
| | - Katja Radon
- Center for International Health, Institute and Outpatient Clinic for Occupational, Social and Environmental Medicine, University Hospital Munich (LMU), Ziemssenstr. 1, 80336, Munich, Germany
| | | | - Roman Wölfel
- German Center for Infection Research (DZIF), Partner Site Munich, Germany; Bundeswehr Institute of Microbiology, 80937, Munich, Germany
| | - Michael Hoelscher
- Division of Infectious Diseases and Tropical Medicine, University Hospital, LMU Munich, 80802, Munich, Germany; German Center for Infection Research (DZIF), Partner Site Munich, Germany
| | - Inge Kroidl
- Division of Infectious Diseases and Tropical Medicine, University Hospital, LMU Munich, 80802, Munich, Germany; German Center for Infection Research (DZIF), Partner Site Munich, Germany
| | - Andreas Wieser
- Division of Infectious Diseases and Tropical Medicine, University Hospital, LMU Munich, 80802, Munich, Germany; German Center for Infection Research (DZIF), Partner Site Munich, Germany
| | - Laura Olbrich
- Division of Infectious Diseases and Tropical Medicine, University Hospital, LMU Munich, 80802, Munich, Germany; German Center for Infection Research (DZIF), Partner Site Munich, Germany; Oxford Vaccine Group, Department of Paediatrics, And the NIHR Oxford Biomedical Research Centre, University of Oxford, OX1 2JD, Oxford, UK
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26
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Erber J, Kappler V, Haller B, Mijočević H, Galhoz A, Prazeres da Costa C, Gebhardt F, Graf N, Hoffmann D, Thaler M, Lorenz E, Roggendorf H, Kohlmayer F, Henkel A, Menden MP, Ruland J, Spinner CD, Protzer U, Knolle P, Lingor P. Infection Control Measures and Prevalence of SARS-CoV-2 IgG among 4,554 University Hospital Employees, Munich, Germany. Emerg Infect Dis 2022; 28:572-581. [PMID: 35195515 PMCID: PMC8888242 DOI: 10.3201/eid2803.204436] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/24/2022] Open
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27
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Piler P, Thon V, Andrýsková L, Doležel K, Kostka D, Pavlík T, Dušek L, Pikhart H, Bobák M, Matic S, Klánová J. Nationwide increases in anti-SARS-CoV-2 IgG antibodies between October 2020 and March 2021 in the unvaccinated Czech population. COMMUNICATIONS MEDICINE 2022; 2:19. [PMID: 35603283 PMCID: PMC9053194 DOI: 10.1038/s43856-022-00080-0] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/03/2021] [Accepted: 01/24/2022] [Indexed: 01/13/2023] Open
Abstract
Background The aim of the nationwide prospective seroconversion (PROSECO) study was to investigate the dynamics of anti-SARS-CoV-2 IgG antibodies in the Czech population. Here we report on baseline prevalence from that study. Methods The study included the first 30,054 persons who provided a blood sample between October 2020 and March 2021. Seroprevalence was compared between calendar periods, previous RT-PCR results and other factors. Results The data show a large increase in seropositivity over time, from 28% in October/November 2020 to 43% in December 2020/January 2021 to 51% in February/March 2021. These trends were consistent with government data on cumulative viral antigenic prevalence in the population captured by PCR testing - although the seroprevalence rates established in this study were considerably higher. There were only minor differences in seropositivity between sexes, age groups and BMI categories, and results were similar between test providing laboratories. Seropositivity was substantially higher among persons with history of symptoms (76% vs. 34%). At least one third of all seropositive participants had no history of symptoms, and 28% of participants with antibodies against SARS-CoV-2 never underwent PCR testing. Conclusions Our data confirm the rapidly increasing prevalence in the Czech population during the rising pandemic wave prior to the beginning of vaccination. The difference between our results on seroprevalence and PCR testing suggests that antibody response provides a better marker of past infection than the routine testing program.
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Affiliation(s)
- Pavel Piler
- grid.10267.320000 0001 2194 0956RECETOX, Faculty of Science, Masaryk University, Kotlarska 2, 611 37 Brno, Czech Republic
| | - Vojtěch Thon
- grid.10267.320000 0001 2194 0956RECETOX, Faculty of Science, Masaryk University, Kotlarska 2, 611 37 Brno, Czech Republic
| | - Lenka Andrýsková
- grid.10267.320000 0001 2194 0956RECETOX, Faculty of Science, Masaryk University, Kotlarska 2, 611 37 Brno, Czech Republic
| | - Kamil Doležel
- QualityLab Association, Evropská 846/176a, Prague, Czech Republic
| | - David Kostka
- grid.436106.6Health Insurance Company of the Ministry of the Interior of the Czech Republic, Vinohradská 2577/178, 130 00 Prague, Czech Republic
| | - Tomáš Pavlík
- grid.10267.320000 0001 2194 0956Institute of Biostatistics and Analyses, Faculty of Medicine, Masaryk University, Kamenice 3, 625 00 Brno, Czech Republic ,grid.486651.80000 0001 2231 0366Institute of Health Information and Statistics of the Czech Republic, Palackého náměstí 4, 128 01 Prague, Czech Republic
| | - Ladislav Dušek
- grid.10267.320000 0001 2194 0956Institute of Biostatistics and Analyses, Faculty of Medicine, Masaryk University, Kamenice 3, 625 00 Brno, Czech Republic ,grid.486651.80000 0001 2231 0366Institute of Health Information and Statistics of the Czech Republic, Palackého náměstí 4, 128 01 Prague, Czech Republic
| | - Hynek Pikhart
- grid.10267.320000 0001 2194 0956RECETOX, Faculty of Science, Masaryk University, Kotlarska 2, 611 37 Brno, Czech Republic ,grid.83440.3b0000000121901201Department of Epidemiology & Public Health, University College London, 1 – 19 Torrington Place, London, WC1E 6BT UK
| | - Martin Bobák
- grid.10267.320000 0001 2194 0956RECETOX, Faculty of Science, Masaryk University, Kotlarska 2, 611 37 Brno, Czech Republic ,grid.83440.3b0000000121901201Department of Epidemiology & Public Health, University College London, 1 – 19 Torrington Place, London, WC1E 6BT UK
| | - Srdan Matic
- World Health Organization (WHO), Country Office in the Czech Republic, Rytířská 31, 110 00 Prague, Czech Republic
| | - Jana Klánová
- grid.10267.320000 0001 2194 0956RECETOX, Faculty of Science, Masaryk University, Kotlarska 2, 611 37 Brno, Czech Republic
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28
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Speierer A, Chocano-Bedoya PO, Anker D, Schmid A, Keidel D, Vermes T, Imboden M, Levati S, Franscella G, Corna L, Amati R, Harju E, Luedi C, Michel G, Veys-Takeuchi C, Zuppinger C, Nusslé SG, D’Acremont V, Tall I, Salberg É, Baysson H, Lorthe E, Pennacchio F, Frei A, Kaufmann M, Geigges M, West EA, Schwab N, Cullati S, Chiolero A, Kahlert C, Stringhini S, Vollrath F, Probst-Hensch N, Rodondi N, Puhan MA, von Wyl V. The Corona Immunitas Digital Follow-Up eCohort to Monitor Impacts of the SARS-CoV-2 Pandemic in Switzerland: Study Protocol and First Results. Int J Public Health 2022; 67:1604506. [PMID: 35295967 PMCID: PMC8919370 DOI: 10.3389/ijph.2022.1604506] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/04/2021] [Accepted: 01/20/2022] [Indexed: 01/22/2023] Open
Abstract
Objectives: To describe the rationale, organization, and procedures of the Corona Immunitas Digital Follow-Up (CI-DFU) eCohort and to characterize participants at baseline. Methods: Participants of Corona Immunitas, a population-based nationwide SARS-CoV-2 seroprevalence study in Switzerland, were invited to join the CI-DFU eCohort in 11 study centres. Weekly online questonnaires cover health status changes, prevention measures adherence, and social impacts. Monthly questionnaires cover additional prevention adherence, contact tracing apps use, vaccination and vaccine hesitancy, and socio-economic changes. Results: We report data from the 5 centres that enrolled in the CI-DFU between June and October 2020 (covering Basel City/Land, Fribourg, Neuchâtel, Ticino, Zurich). As of February 2021, 4636 participants were enrolled and 85,693 weekly and 27,817 monthly questionnaires were collected. Design-based oversampling led to overrepresentation of individuals aged 65+ years. People with higher education and income were more likely to enroll and be retained. Conclusion: Broad enrolment and robust retention of participants enables scientifically sound monitoring of pandemic impacts, prevention, and vaccination progress. The CI-DFU eCohort demonstrates proof-of-principle for large-scale, federated eCohort study designs based on jointly agreed principles and transparent governance.
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Affiliation(s)
- Alexandre Speierer
- Institute of Primary Health Care (BIHAM), University of Bern, Bern, Switzerland
- Department of General Internal Medicine, Inselspital, Bern University Hospital, University of Bern, Bern, Switzerland
| | - Patricia O. Chocano-Bedoya
- Institute of Primary Health Care (BIHAM), University of Bern, Bern, Switzerland
- Population Health Laboratory (#PopHealthLab), University of Fribourg, Fribourg, Switzerland
| | - Daniela Anker
- Population Health Laboratory (#PopHealthLab), University of Fribourg, Fribourg, Switzerland
| | - Alexia Schmid
- Institute of Family Medicine, University of Fribourg, Fribourg, Switzerland
| | - Dirk Keidel
- Department of Epidemiology and Public Health, Swiss Tropical and Public Health Institute, Basel, Switzerland
- University of Basel, Basel, Switzerland
| | - Thomas Vermes
- Department of Epidemiology and Public Health, Swiss Tropical and Public Health Institute, Basel, Switzerland
- University of Basel, Basel, Switzerland
| | - Medea Imboden
- Department of Epidemiology and Public Health, Swiss Tropical and Public Health Institute, Basel, Switzerland
- University of Basel, Basel, Switzerland
| | - Sara Levati
- Department of Business Economics, Health and Social Care, University of Applied Sciences and Arts of Southern Switzerland, Lugano, Switzerland
| | - Giovanni Franscella
- Institute of Public Health, Faculty of BioMedicine, Università Della Svizzera Italiana, Lugano, Switzerland
| | - Laurie Corna
- Institute of Public Health, Faculty of BioMedicine, Università Della Svizzera Italiana, Lugano, Switzerland
| | - Rebecca Amati
- Institute of Public Health, Faculty of BioMedicine, Università Della Svizzera Italiana, Lugano, Switzerland
| | - Erika Harju
- Department of Health Sciences and Medicine, University of Luzern, Luzern, Switzerland
| | - Chantal Luedi
- Department of Health Sciences and Medicine, University of Luzern, Luzern, Switzerland
| | - Gisela Michel
- Department of Health Sciences and Medicine, University of Luzern, Luzern, Switzerland
| | - Caroline Veys-Takeuchi
- Department of Epidemiology and Health Systems, Center for Primary Care and Public Health (Unisanté), Lausanne University, Lausanne, Switzerland
| | - Claire Zuppinger
- Department of Epidemiology and Health Systems, Center for Primary Care and Public Health (Unisanté), Lausanne University, Lausanne, Switzerland
| | - Semira Gonseth Nusslé
- Department of Epidemiology and Health Systems, Center for Primary Care and Public Health (Unisanté), Lausanne University, Lausanne, Switzerland
| | - Valérie D’Acremont
- Department of Research and Innovation, Center for Primary Care and Public Health (Unisanté), Lausanne University, Lausanne, Switzerland
| | - Ismaël Tall
- Cantonal Public Health Service, Neuchâtel, Switzerland
| | - Éric Salberg
- Cantonal Public Health Service, Neuchâtel, Switzerland
| | - Hélène Baysson
- Department of Health and Community Medicine, Faculty of Medicine, University of Geneva, Geneva, Switzerland
- Unit of Population Epidemiology, Division of Primary Care Medicine, Geneva University Hospitals, Geneva, Switzerland
| | - Elsa Lorthe
- Unit of Population Epidemiology, Division of Primary Care Medicine, Geneva University Hospitals, Geneva, Switzerland
| | - Francesco Pennacchio
- Unit of Population Epidemiology, Division of Primary Care Medicine, Geneva University Hospitals, Geneva, Switzerland
| | - Anja Frei
- Epidemiology, Biostatistics and Prevention Institute, Zurich, Switzerland
| | - Marco Kaufmann
- Epidemiology, Biostatistics and Prevention Institute, Zurich, Switzerland
| | - Marco Geigges
- Epidemiology, Biostatistics and Prevention Institute, Zurich, Switzerland
| | - Erin Ashley West
- Epidemiology, Biostatistics and Prevention Institute, Zurich, Switzerland
| | - Nathalie Schwab
- Institute of Primary Health Care (BIHAM), University of Bern, Bern, Switzerland
- Department of General Internal Medicine, Inselspital, Bern University Hospital, University of Bern, Bern, Switzerland
| | - Stéphane Cullati
- Population Health Laboratory (#PopHealthLab), University of Fribourg, Fribourg, Switzerland
- Department of Readaptation and Geriatrics, University of Geneva, Geneva, Switzerland
| | - Arnaud Chiolero
- Population Health Laboratory (#PopHealthLab), University of Fribourg, Fribourg, Switzerland
- School of Population and Global Health, McGill University, Montreal, QC, Canada
| | - Christian Kahlert
- Department of Infectious Diseases and Hospital Epidemiology, Cantonal Hospital St. Gallen, St. Gallen, Switzerland
- Infectious Diseases and Hospital Epidemiology, Children’s Hospital of Eastern Switzerland, St. Gallen, Switzerland
| | - Silvia Stringhini
- Department of Health and Community Medicine, Faculty of Medicine, University of Geneva, Geneva, Switzerland
- Unit of Population Epidemiology, Division of Primary Care Medicine, Geneva University Hospitals, Geneva, Switzerland
- University Center for General Medicine and Public Health, University of Lausanne, Lausanne, Switzerland
| | - Fabian Vollrath
- Corona Immunitas Program Management Group, Swiss School of Public Health, Zurich, Switzerland
| | - Nicole Probst-Hensch
- Department of Epidemiology and Public Health, Swiss Tropical and Public Health Institute, Basel, Switzerland
- University of Basel, Basel, Switzerland
| | - Nicolas Rodondi
- Institute of Primary Health Care (BIHAM), University of Bern, Bern, Switzerland
- Department of General Internal Medicine, Inselspital, Bern University Hospital, University of Bern, Bern, Switzerland
| | - Milo A. Puhan
- Epidemiology, Biostatistics and Prevention Institute, Zurich, Switzerland
| | - Viktor von Wyl
- Institute for Implementation Science in Health Care, University of Zurich, Zurich, Switzerland
- *Correspondence: Viktor von Wyl,
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29
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Pengid S, Peltzer K, de Moura Villela EF, Fodjo JNS, Siau CS, Chen WS, Bono SA, Jayasvasti I, Hasan MT, Wanyenze RK, Hosseinipour MC, Dolo H, Sessou P, Ditekemena JD, Colebunders R. Using Andersen's model of health care utilization to assess factors associated with COVID-19 testing among adults in nine low-and middle-income countries: an online survey. BMC Health Serv Res 2022; 22:265. [PMID: 35227263 PMCID: PMC8882718 DOI: 10.1186/s12913-022-07661-8] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/08/2021] [Accepted: 02/21/2022] [Indexed: 12/23/2022] Open
Abstract
Background This study aimed to investigate, using Andersen’s model of health care utilization, factors associated with COVID-19 testing among adults in nine low- and middle- income countries. Methods In between 10 December 2020 and 9 February 2021, an online survey was organized in nine low- and middle-income countries. In total 10,183 adults (median age 45 years, interquartile range 33–57 years, range 18–93 years), including 6470 from Brazil, 1738 Malaysia, 1124 Thailand, 230 Bangladesh, 219 DR Congo, 159 Benin, 107 Uganda, 81 Malawi and 55 from Mali participated in the study. COVID-19 testing/infection status was assessed by self-report. Results Of the 10,183 participants, 40.3% had ever tested for COVID-19, 7.3% tested positive, and 33.0% tested negative. In an adjusted logistic regression model, predisposing factors (residing in Brazil, postgraduate education), enabling/disabling factors (urban residence, higher perceived economic status, being a student or worker in the health care sector, and moderate or severe psychological distress), and need factors (having at least one chronic condition) increased the odds of COVID-19 testing. Among those who were tested, participants residing in Bangladesh, those who had moderate to severe psychological distress were positively associated with COVID-19 positive diagnosis. Participants who are residing in Malaysia and Thailand, and those who had higher education were negatively associated with a COVID-19 positive diagnosis. Considering all participants, higher perceived economic status, being a student or worker in the health sector, and moderate or severe psychological distress were positively associated with a COVID-19 positive diagnosis, and residing in Malaysia, Thailand or five African countries was negatively associated with a COVID-19 positive diagnosis. Conclusion A high rate of COVID-19 testing among adults was reported in nine low-and middle-income countries. However, access to testing needs to be increased in Africa. Moreover, COVID-19 testing programmes need to target persons of lower economic status and education level who are less tested but most at risk for COVID-19 infection.
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Affiliation(s)
- Supa Pengid
- Department of Health Education and Behavioral Sciences, Faculty of Public Health, Mahidol University, Bangkok, 10400, Thailand.,Department of Research Administration and Development, University of Limpopo, Polokwane, South Africa
| | - Karl Peltzer
- Department of Research Administration and Development, University of Limpopo, Polokwane, South Africa. .,Department of Psychology, College of Medical and Health Science, Asia University, Taichung, Taiwan.
| | - Edlaine Faria de Moura Villela
- Disease Control Coordination, São Paulo State Health Department, São Paulo, 01246-000, Brazil.,Institute of Tropical Pathology and Public Health, Federal University of Goiás, Goiânia, 74690-900, Brazil
| | | | - Ching Sin Siau
- Centre for Community Health Studies (ReaCH), Faculty of Health Sciences, Universiti Kebangsaan Malaysia, 50300, Kuala Lumpur, Malaysia
| | - Won Sun Chen
- Department of Health Science and Biostatistics, Faculty of Health, Arts and Design, Swinburne University of Technology, Hawthorn, VIC, 3122, Australia
| | - Suzanna A Bono
- School of Social Science, Universiti Sains Malaysia, 11800, Gelugor, Malaysia
| | | | - M Tasdik Hasan
- Jeeon Bangladesh Ltd., Dhaka, Bangladesh.,Department of Public Health, State University of Bangladesh (SUB), Dhaka, Bangladesh.,Department of Primary Care & Mental Health, University of Liverpool, Liverpool, L69 3BX, UK
| | - Rhoda K Wanyenze
- School of Public Health, College of Health Sciences, Makerere University, Kampala, Uganda
| | | | - Housseini Dolo
- International Center of Excellence in Research, Faculty of Medicine and OdontoStomatology, Bamako, Mali.,Lymphatic Filariasis Research Unit/International Center of Excellence in Research, Bamako, Mali
| | - Philippe Sessou
- Research Unit on Communicable Diseases, Polytechnic School of Abomey-Calavi, University of Abomey-Calavi, Cotonou 01, BP, 526, Benin
| | - John D Ditekemena
- Kinshasa School of Public Health, University of Kinshasa, Kinshasa, 7948, Democratic Republic of the Congo
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Protective immune trajectories in early viral containment of non-pneumonic SARS-CoV-2 infection. Nat Commun 2022; 13:1018. [PMID: 35197461 PMCID: PMC8866527 DOI: 10.1038/s41467-022-28508-0] [Citation(s) in RCA: 12] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/21/2021] [Accepted: 01/28/2022] [Indexed: 02/07/2023] Open
Abstract
The antiviral immune response to SARS-CoV-2 infection can limit viral spread and prevent development of pneumonic COVID-19. However, the protective immunological response associated with successful viral containment in the upper airways remains unclear. Here, we combine a multi-omics approach with longitudinal sampling to reveal temporally resolved protective immune signatures in non-pneumonic and ambulatory SARS-CoV-2 infected patients and associate specific immune trajectories with upper airway viral containment. We see a distinct systemic rather than local immune state associated with viral containment, characterized by interferon stimulated gene (ISG) upregulation across circulating immune cell subsets in non-pneumonic SARS-CoV2 infection. We report reduced cytotoxic potential of Natural Killer (NK) and T cells, and an immune-modulatory monocyte phenotype associated with protective immunity in COVID-19. Together, we show protective immune trajectories in SARS-CoV2 infection, which have important implications for patient prognosis and the development of immunomodulatory therapies. Infection with SARS-COV-2 can result in self-limited upper airway infection or progress to a more systemic inflammatory condition including pneumonic COVID-19. Here the authors utilise a multi-omics approach to interrogate the immune response of patients with self-limiting upper respiratory SARS-CoV-2 infection and reveal a temporal immune trajectory they associate with viral containment and restriction from pneumonic progressive disease.
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Piler P, Thon V, Andrýsková L, Doležel K, Kostka D, Pavlík T, Dušek L, Pikhart H, Bobák M, Matic S, Klánová J. Nationwide increases in anti-SARS-CoV-2 IgG antibodies between October 2020 and March 2021 in the unvaccinated Czech population. COMMUNICATIONS MEDICINE 2022. [PMID: 35603283 DOI: 10.1038/s43856-022-00080-0.pmid:35603283] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 05/04/2023] Open
Abstract
BACKGROUND The aim of the nationwide prospective seroconversion (PROSECO) study was to investigate the dynamics of anti-SARS-CoV-2 IgG antibodies in the Czech population. Here we report on baseline prevalence from that study. METHODS The study included the first 30,054 persons who provided a blood sample between October 2020 and March 2021. Seroprevalence was compared between calendar periods, previous RT-PCR results and other factors. RESULTS The data show a large increase in seropositivity over time, from 28% in October/November 2020 to 43% in December 2020/January 2021 to 51% in February/March 2021. These trends were consistent with government data on cumulative viral antigenic prevalence in the population captured by PCR testing - although the seroprevalence rates established in this study were considerably higher. There were only minor differences in seropositivity between sexes, age groups and BMI categories, and results were similar between test providing laboratories. Seropositivity was substantially higher among persons with history of symptoms (76% vs. 34%). At least one third of all seropositive participants had no history of symptoms, and 28% of participants with antibodies against SARS-CoV-2 never underwent PCR testing. CONCLUSIONS Our data confirm the rapidly increasing prevalence in the Czech population during the rising pandemic wave prior to the beginning of vaccination. The difference between our results on seroprevalence and PCR testing suggests that antibody response provides a better marker of past infection than the routine testing program.
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Affiliation(s)
- Pavel Piler
- RECETOX, Faculty of Science, Masaryk University, Kotlarska 2, 611 37 Brno, Czech Republic
| | - Vojtěch Thon
- RECETOX, Faculty of Science, Masaryk University, Kotlarska 2, 611 37 Brno, Czech Republic
| | - Lenka Andrýsková
- RECETOX, Faculty of Science, Masaryk University, Kotlarska 2, 611 37 Brno, Czech Republic
| | - Kamil Doležel
- QualityLab Association, Evropská 846/176a, Prague, Czech Republic
| | - David Kostka
- Health Insurance Company of the Ministry of the Interior of the Czech Republic, Vinohradská 2577/178, 130 00 Prague, Czech Republic
| | - Tomáš Pavlík
- Institute of Biostatistics and Analyses, Faculty of Medicine, Masaryk University, Kamenice 3, 625 00 Brno, Czech Republic
- Institute of Health Information and Statistics of the Czech Republic, Palackého náměstí 4, 128 01 Prague, Czech Republic
| | - Ladislav Dušek
- Institute of Biostatistics and Analyses, Faculty of Medicine, Masaryk University, Kamenice 3, 625 00 Brno, Czech Republic
- Institute of Health Information and Statistics of the Czech Republic, Palackého náměstí 4, 128 01 Prague, Czech Republic
| | - Hynek Pikhart
- RECETOX, Faculty of Science, Masaryk University, Kotlarska 2, 611 37 Brno, Czech Republic
- Department of Epidemiology & Public Health, University College London, 1 - 19 Torrington Place, London, WC1E 6BT UK
| | - Martin Bobák
- RECETOX, Faculty of Science, Masaryk University, Kotlarska 2, 611 37 Brno, Czech Republic
- Department of Epidemiology & Public Health, University College London, 1 - 19 Torrington Place, London, WC1E 6BT UK
| | - Srdan Matic
- World Health Organization (WHO), Country Office in the Czech Republic, Rytířská 31, 110 00 Prague, Czech Republic
| | - Jana Klánová
- RECETOX, Faculty of Science, Masaryk University, Kotlarska 2, 611 37 Brno, Czech Republic
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Gornyk D, Harries M, Glöckner S, Strengert M, Kerrinnes T, Heise JK, Maaß H, Ortmann J, Kessel B, Kemmling Y, Lange B, Krause G. SARS-CoV-2 Seroprevalence in Germany. DEUTSCHES ARZTEBLATT INTERNATIONAL 2021; 118:824-831. [PMID: 35191825 PMCID: PMC8888869 DOI: 10.3238/arztebl.m2021.0364] [Citation(s) in RCA: 20] [Impact Index Per Article: 6.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/10/2021] [Revised: 05/10/2021] [Accepted: 10/08/2021] [Indexed: 01/25/2023]
Abstract
BACKGROUND Until now, information on the spread of SARS-CoV-2 infections in Germany has been based mainly on data from the public health offices. It may be assumed that these data do not include many cases of asymptomatic and mild infection. METHODS We determined seroprevalence over the course of the pandemic in a sequential, multilocal seroprevalence study (MuSPAD). Study participants were recruited at random in seven administrative districts (Kreise) in Germany from July 2020 onward; each participant was tested at two different times 3-5 months apart. Test findings on blood samples were used to determine the missed-case rate of reported infections, the infection fatality rate (IFR), and the association between seropositivity and demographic, socio-economic, and health-related factors, as well as to evaluate the self-reported results of PCR and antigenic tests. The registration number of this study is DRKS00022335. RESULTS Among non-vaccinated persons, the seroprevalence from July to December 2020 was 1.3-2.8% and rose between February and May 2021 to 4.1-13.1%. In July 2021, 35% of tested persons in Chemnitz were not vaccinated, and the seroprevalence among these persons was 32.4% (07/2021). The surveillance detection ratio (SDR), i.e., the ratio between the true number of infections estimated from seroprevalence and the actual number or reported infections, varied among the districts included in the study from 2.2 to 5.1 up to December 2020 and from 1.3 to 2.9 up to June 2021, and subsequently declined. The IFR was in the range of 0.8% to 2.4% in all regions except Magdeburg, where a value of 0.3% was calculated for November 2020. A lower educational level was associated with a higher seropositivity rate, smoking with a lower seropositivity rate. On average, 1 person was infected for every 8.5 persons in quarantine. CONCLUSION Seroprevalence was low after the first wave of the pandemic but rose markedly during the second and third waves. The missed-case rate trended downward over the course of the pandemic.
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Affiliation(s)
- Daniela Gornyk
- Department of Epidemiology, Helmholtz Center for Infection Research, Braunschweig; RNA Biology of Bacterial Infections, Helmholtz Institute for RNA-Based Infection Research, Würzburg; TI Bioresources, Biodata, and Digital Health (TI BBD), German Center for Infection Research (DZIF), Braunschweig; TWINCORE, Center for Experimental and Clinical Infection Research, Hanover
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Pang KW, Tham SL, Ng LS. Exploring the Clinical Utility of Gustatory Dysfunction (GD) as a Triage Symptom Prior to Reverse Transcription Polymerase Chain Reaction (RT-PCR) in the Diagnosis of COVID-19: A Meta-Analysis and Systematic Review. Life (Basel) 2021; 11:1315. [PMID: 34947846 PMCID: PMC8706269 DOI: 10.3390/life11121315] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/24/2021] [Revised: 11/25/2021] [Accepted: 11/25/2021] [Indexed: 12/14/2022] Open
Abstract
BACKGROUND The diagnosis of COVID-19 is made using reverse transcription polymerase chain reaction (RT-PCR) but its sensitivity varies from 20 to 100%. The presence of gustatory dysfunction (GD) in a patient with upper respiratory tract symptoms might increase the clinical suspicion of COVID-19. AIMS To perform a systematic review and meta-analysis to determine the pooled sensitivity, specificity, positive likelihood ratio (LR+), negative likelihood ratio (LR-) and diagnostic odds ratio (DOR) of using GD as a triage symptom prior to RT-PCR. METHODS PubMed and Embase were searched up to 20 June 2021. Studies published in English were included if they compared the frequency of GD in COVID-19 adult patients (proven by RT-PCR) to COVID-19 negative controls in case control or cross-sectional studies. The Newcastle-Ottawa scale was used to assess the methodological quality of the included studies. RESULTS 21,272 COVID-19 patients and 52,298 COVID-19 negative patients were included across 44 studies from 21 countries. All studies were of moderate to high risk of bias. Patients with GD were more likely to test positive for COVID-19: DOR 6.39 (4.86-8.40), LR+ 3.84 (3.04-4.84), LR- 0.67 (0.64-0.70), pooled sensitivity 0.37 (0.29-0.47) and pooled specificity 0.92 (0.89-0.94). While history/questionnaire-based assessments were predictive of RT-PCR positivity (DOR 6.62 (4.95-8.85)), gustatory testing was not (DOR 3.53 (0.98-12.7)). There was significant heterogeneity among the 44 studies (I2 = 92%, p < 0.01). CONCLUSIONS GD is useful as a symptom to determine if a patient should undergo further testing, especially in resource-poor regions where COVID-19 testing is scarce. Patients with GD may be advised to quarantine while repeated testing is performed if the initial RT-PCR is negative. FUNDING None.
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Affiliation(s)
- Khang Wen Pang
- Department of Otolaryngology-Head and Neck Surgery, National University Hospital, Singapore 119228, Singapore; (S.-L.T.); (L.S.N.)
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Rubio-Acero R, Beyerl J, Muenchhoff M, Roth MS, Castelletti N, Paunovic I, Radon K, Springer B, Nagel C, Boehm B, Böhmer MM, Graf A, Blum H, Krebs S, Keppler OT, Osterman A, Khan ZN, Hoelscher M, Wieser A. Spatially resolved qualified sewage spot sampling to track SARS-CoV-2 dynamics in Munich - One year of experience. THE SCIENCE OF THE TOTAL ENVIRONMENT 2021; 797:149031. [PMID: 34346361 PMCID: PMC8294104 DOI: 10.1016/j.scitotenv.2021.149031] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 04/30/2021] [Revised: 06/23/2021] [Accepted: 07/09/2021] [Indexed: 05/03/2023]
Abstract
Wastewater-based epidemiology (WBE) is a tool now increasingly proposed to monitor the SARS-CoV-2 burden in populations without the need for individual mass testing. It is especially interesting in metropolitan areas where spread can be very fast, and proper sewage systems are available for sampling with short flow times and thus little decay of the virus. We started in March 2020 to set up a once-a-week qualified spot sampling protocol in six different locations in Munich carefully chosen to contain primarily wastewater of permanent residential areas, rather than industry or hospitals. We used RT-PCR and sequencing to track the spread of SARS-CoV-2 in the Munich population with temporo-spatial resolution. The study became fully operational in mid-April 2020 and has been tracking SARS-CoV-2 RNA load weekly for one year. Sequencing of the isolated viral RNA was performed to obtain information about the presence and abundance of variants of concern in the Munich area over time. We demonstrate that the evolution of SARS-CoV-2 RNA loads (between <7.5 and 3874/ml) in these different areas within Munich correlates well with official seven day incidence notification data (between 0.0 and 327 per 100,000) obtained from the authorities within the respective region. Wastewater viral loads predicted the dynamic of SARS-CoV-2 local incidence about 3 weeks in advance of data based on respiratory swab analyses. Aligning with multiple different point-mutations characteristic for certain variants of concern, we could demonstrate the gradual increase of variant of concern B.1.1.7 in the Munich population beginning in January 2021, weeks before it became apparent in sequencing results of swabs samples taken from patients living in Munich. Overall, the study highlights the potential of WBE to monitor the SARS-CoV-2 pandemic, including the introduction of variants of concern in a local population.
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Affiliation(s)
- Raquel Rubio-Acero
- Division of Infectious Diseases and Tropical Medicine, University Hospital, Ludwig-Maximilians-Universität (LMU) Munich, 80802 Munich, Germany.
| | - Jessica Beyerl
- Division of Infectious Diseases and Tropical Medicine, University Hospital, Ludwig-Maximilians-Universität (LMU) Munich, 80802 Munich, Germany.
| | - Maximilian Muenchhoff
- Max von Pettenkofer Institute & Gene Center, Virology, National Reference Center for Retroviruses, LMU Munich, 80336 Munich, Germany; German Center for Infection Research (DZIF), partner site Munich, Germany.
| | | | - Noemi Castelletti
- Division of Infectious Diseases and Tropical Medicine, University Hospital, Ludwig-Maximilians-Universität (LMU) Munich, 80802 Munich, Germany.
| | - Ivana Paunovic
- Division of Infectious Diseases and Tropical Medicine, University Hospital, Ludwig-Maximilians-Universität (LMU) Munich, 80802 Munich, Germany.
| | - Katja Radon
- Institute and Outpatient Clinic for Occupational, Social and Environmental Medicine, University Hospital, LMU Munich, 80336 Munich, Germany; Center for International Health, Ludwig-Maximilians-University, Munich, Germany.
| | - Bernd Springer
- Fire Department, Disaster Control, City of Munich, Germany.
| | | | | | - Merle M Böhmer
- Taskforce Infectiology, Department for Infectious Disease Epidemiology (TFI 2), Bavarian Health and Food Safety Authority, Oberschleissheim, Germany; Institute of Social Medicine and Health Systems Research, Otto-von-Guericke-University Magdeburg, Magdeburg, Germany.
| | - Alexander Graf
- Laboratory for Functional Genome Analysis, Gene Center, Ludwig Maximilians University of Munich, Munich, Germany.
| | - Helmut Blum
- Laboratory for Functional Genome Analysis, Gene Center, Ludwig Maximilians University of Munich, Munich, Germany.
| | - Stefan Krebs
- Laboratory for Functional Genome Analysis, Gene Center, Ludwig Maximilians University of Munich, Munich, Germany.
| | - Oliver T Keppler
- German Center for Infection Research (DZIF), partner site Munich, Germany; Max von Pettenkofer Institute & Gene Center, Virology, National Reference Center for Retroviruses, LMU Munich, 80336 Munich, Germany.
| | - Andreas Osterman
- German Center for Infection Research (DZIF), partner site Munich, Germany; Max von Pettenkofer Institute & Gene Center, Virology, National Reference Center for Retroviruses, LMU Munich, 80336 Munich, Germany.
| | - Zohaib Nisar Khan
- Division of Infectious Diseases and Tropical Medicine, University Hospital, Ludwig-Maximilians-Universität (LMU) Munich, 80802 Munich, Germany.
| | - Michael Hoelscher
- Division of Infectious Diseases and Tropical Medicine, University Hospital, Ludwig-Maximilians-Universität (LMU) Munich, 80802 Munich, Germany; Center for International Health, Ludwig-Maximilians-University, Munich, Germany; German Center for Infection Research (DZIF), partner site Munich, Germany.
| | - Andreas Wieser
- Division of Infectious Diseases and Tropical Medicine, University Hospital, Ludwig-Maximilians-Universität (LMU) Munich, 80802 Munich, Germany; German Center for Infection Research (DZIF), partner site Munich, Germany.
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SARS-CoV-2 antibody seroprevalence in a large neuroimmunological patient cohort. J Neurol 2021; 269:1133-1137. [PMID: 34609601 PMCID: PMC8491170 DOI: 10.1007/s00415-021-10818-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/02/2021] [Revised: 09/22/2021] [Accepted: 09/22/2021] [Indexed: 11/20/2022]
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Radev ST, Graw F, Chen S, Mutters NT, Eichel VM, Bärnighausen T, Köthe U. OutbreakFlow: Model-based Bayesian inference of disease outbreak dynamics with invertible neural networks and its application to the COVID-19 pandemics in Germany. PLoS Comput Biol 2021; 17:e1009472. [PMID: 34695111 PMCID: PMC8584772 DOI: 10.1371/journal.pcbi.1009472] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/13/2021] [Revised: 11/11/2021] [Accepted: 09/23/2021] [Indexed: 01/08/2023] Open
Abstract
Mathematical models in epidemiology are an indispensable tool to determine the dynamics and important characteristics of infectious diseases. Apart from their scientific merit, these models are often used to inform political decisions and interventional measures during an ongoing outbreak. However, reliably inferring the epidemical dynamics by connecting complex models to real data is still hard and requires either laborious manual parameter fitting or expensive optimization methods which have to be repeated from scratch for every application of a given model. In this work, we address this problem with a novel combination of epidemiological modeling with specialized neural networks. Our approach entails two computational phases: In an initial training phase, a mathematical model describing the epidemic is used as a coach for a neural network, which acquires global knowledge about the full range of possible disease dynamics. In the subsequent inference phase, the trained neural network processes the observed data of an actual outbreak and infers the parameters of the model in order to realistically reproduce the observed dynamics and reliably predict future progression. With its flexible framework, our simulation-based approach is applicable to a variety of epidemiological models. Moreover, since our method is fully Bayesian, it is designed to incorporate all available prior knowledge about plausible parameter values and returns complete joint posterior distributions over these parameters. Application of our method to the early Covid-19 outbreak phase in Germany demonstrates that we are able to obtain reliable probabilistic estimates for important disease characteristics, such as generation time, fraction of undetected infections, likelihood of transmission before symptom onset, and reporting delays using a very moderate amount of real-world observations.
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Affiliation(s)
- Stefan T. Radev
- Institute of Psychology, Heidelberg University, Heidelberg, Germany
| | - Frederik Graw
- BioQuant - Center for Quantitative Biology, Heidelberg University, Heidelberg, Germany
| | - Simiao Chen
- Heidelberg Institute of Global Health, Heidelberg, Germany
- Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Nico T. Mutters
- Institute for Hygiene and Public Health, University Hospital Bonn, Bonn, Germany
| | - Vanessa M. Eichel
- Center of Infectious Diseases, University Hospital Heidelberg, Heidelberg, Germany
| | - Till Bärnighausen
- Heidelberg Institute of Global Health, Heidelberg, Germany
- Harvard T.H. Chan School of Public Health, Boston, Massachusetts, United States of America
- Africa Health Research Institute, Durban, South Africa
| | - Ullrich Köthe
- Computer Vision and Learning Lab, Heidelberg University, Heidelberg, Germany
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Olbrich L, Castelletti N, Schälte Y, Garí M, Pütz P, Bakuli A, Pritsch M, Kroidl I, Saathoff E, Guggenbuehl Noller JM, Fingerle V, Le Gleut R, Gilberg L, Brand I, Falk P, Markgraf A, Deák F, Riess F, Diefenbach M, Eser T, Weinauer F, Martin S, Quenzel EM, Becker M, Durner J, Girl P, Müller K, Radon K, Fuchs C, Wölfel R, Hasenauer J, Hoelscher M, Wieser A. Head-to-head evaluation of seven different seroassays including direct viral neutralisation in a representative cohort for SARS-CoV-2. J Gen Virol 2021; 102:001653. [PMID: 34623233 PMCID: PMC8604188 DOI: 10.1099/jgv.0.001653] [Citation(s) in RCA: 19] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/23/2021] [Accepted: 07/20/2021] [Indexed: 12/21/2022] Open
Abstract
A number of seroassays are available for SARS-CoV-2 testing; yet, head-to-head evaluations of different testing principles are limited, especially using raw values rather than categorical data. In addition, identifying correlates of protection is of utmost importance, and comparisons of available testing systems with functional assays, such as direct viral neutralisation, are needed.We analysed 6658 samples consisting of true-positives (n=193), true-negatives (n=1091), and specimens of unknown status (n=5374). For primary testing, we used Euroimmun-Anti-SARS-CoV-2-ELISA-IgA/IgG and Roche-Elecsys-Anti-SARS-CoV-2. Subsequently virus-neutralisation, GeneScriptcPass, VIRAMED-SARS-CoV-2-ViraChip, and Mikrogen-recomLine-SARS-CoV-2-IgG were applied for confirmatory testing. Statistical modelling generated optimised assay cut-off thresholds. Sensitivity of Euroimmun-anti-S1-IgA was 64.8%, specificity 93.3% (manufacturer's cut-off); for Euroimmun-anti-S1-IgG, sensitivity was 77.2/79.8% (manufacturer's/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 Euroimmun-anti-S1-IgA and -IgG titres decreased 30/90 days after RT-PCR-positivity, Roche-anti-N titres decreased significantly later. Virus-neutralisation was 80.6% sensitive, 100.0% specific (≥1:5 dilution). Neutralisation surrogate tests (GeneScriptcPass, Mikrogen-recomLine-RBD) were >94.9% sensitive and >98.1% specific. Optimised cut-offs improved test performances of several tests. Confirmatory testing with virus-neutralisation might be complemented with GeneScriptcPassTM or recomLine-RBD for certain applications. Head-to-head comparisons given here aim to contribute to the refinement of testing strategies for individual and public health use.
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Affiliation(s)
- Laura Olbrich
- Division of Infectious Diseases and Tropical Medicine, University Hospital, LMU Munich, 80802 Munich, Germany
- German Center for Infection Research (DZIF), Partner site Munich, Germany
| | - Noemi Castelletti
- Division of Infectious Diseases and Tropical Medicine, University Hospital, LMU Munich, 80802 Munich, Germany
- Institute of Radiation Medicine, Helmholtz Zentrum München, 85764 Neuherberg, Germany
| | - Yannik Schälte
- Institute of Computational Biology, Helmholtz Zentrum München, 85764 Neuherberg, Germany
- Center for Mathematics, Technische Universität München, 85748 Garching, Germany
| | - Mercè Garí
- Institute of Computational Biology, Helmholtz Zentrum München, 85764 Neuherberg, Germany
| | - Peter Pütz
- Institute of Computational Biology, Helmholtz Zentrum München, 85764 Neuherberg, Germany
- Department of Business Administration and Economics, Bielefeld University, 33615 Bielefeld, Germany
| | - Abhishek Bakuli
- Division of Infectious Diseases and Tropical Medicine, University Hospital, LMU Munich, 80802 Munich, Germany
| | - Michael Pritsch
- Division of Infectious Diseases and Tropical Medicine, University Hospital, LMU Munich, 80802 Munich, Germany
| | - Inge Kroidl
- Division of Infectious Diseases and Tropical Medicine, University Hospital, LMU Munich, 80802 Munich, Germany
- German Center for Infection Research (DZIF), Partner site Munich, Germany
| | - Elmar Saathoff
- Division of Infectious Diseases and Tropical Medicine, University Hospital, LMU Munich, 80802 Munich, Germany
- German Center for Infection Research (DZIF), Partner site Munich, Germany
| | | | - Volker Fingerle
- German Center for Infection Research (DZIF), Partner site Munich, Germany
- Bavarian Health and Food Safety Authority (LGL), Germany
| | - Ronan Le Gleut
- Institute of Computational Biology, Helmholtz Zentrum München, 85764 Neuherberg, Germany
- Core Facility Statistical Consulting, Helmholtz Zentrum München, 85764 Neuherberg, Germany
| | - Leonard Gilberg
- Division of Infectious Diseases and Tropical Medicine, University Hospital, LMU Munich, 80802 Munich, Germany
| | - Isabel Brand
- Division of Infectious Diseases and Tropical Medicine, University Hospital, LMU Munich, 80802 Munich, Germany
| | - Philine Falk
- Division of Infectious Diseases and Tropical Medicine, University Hospital, LMU Munich, 80802 Munich, Germany
| | - Alisa Markgraf
- Division of Infectious Diseases and Tropical Medicine, University Hospital, LMU Munich, 80802 Munich, Germany
| | - Flora Deák
- Division of Infectious Diseases and Tropical Medicine, University Hospital, LMU Munich, 80802 Munich, Germany
| | - Friedrich Riess
- Division of Infectious Diseases and Tropical Medicine, University Hospital, LMU Munich, 80802 Munich, Germany
| | - Max Diefenbach
- Division of Infectious Diseases and Tropical Medicine, University Hospital, LMU Munich, 80802 Munich, Germany
| | - Tabea Eser
- Division of Infectious Diseases and Tropical Medicine, University Hospital, LMU Munich, 80802 Munich, Germany
| | | | | | | | - Marc Becker
- Department of Conservative Dentistry and Periodontology, University Hospital, LMU Munich Ludwig-Maximilians-University of Munich, Goethestr. 70, 80336 Munich, Germany
- Laboratory Becker and colleagues, Führichstr. 70, 81671 München, Germany
| | - Jürgen Durner
- Department of Conservative Dentistry and Periodontology, University Hospital, LMU Munich Ludwig-Maximilians-University of Munich, Goethestr. 70, 80336 Munich, Germany
- Laboratory Becker and colleagues, Führichstr. 70, 81671 München, Germany
| | - Philipp Girl
- German Center for Infection Research (DZIF), Partner site Munich, Germany
- Bundeswehr Institute of Microbiology, 80937 Munich, Germany
| | - Katharina Müller
- German Center for Infection Research (DZIF), Partner site Munich, Germany
- Bundeswehr Institute of Microbiology, 80937 Munich, Germany
| | - Katja Radon
- Institute and Outpatient Clinic for Occupational, Social and Environmental Medicine, University Hospital, LMU Munich, 80336 Munich, Germany
- Center for International Health (CIH), University Hospital, LMU Munich, 80336 Munich, Germany
- Comprehensive Pneumology Center (CPC) Munich, German Center for Lung Research (DZL), 80337 Munich, Germany
| | - Christiane Fuchs
- Institute of Computational Biology, Helmholtz Zentrum München, 85764 Neuherberg, Germany
- Center for Mathematics, Technische Universität München, 85748 Garching, Germany
- Department of Business Administration and Economics, Bielefeld University, 33615 Bielefeld, Germany
- Core Facility Statistical Consulting, Helmholtz Zentrum München, 85764 Neuherberg, Germany
| | - Roman Wölfel
- German Center for Infection Research (DZIF), Partner site Munich, Germany
- Bundeswehr Institute of Microbiology, 80937 Munich, Germany
| | - Jan Hasenauer
- Institute of Computational Biology, Helmholtz Zentrum München, 85764 Neuherberg, Germany
- Center for Mathematics, Technische Universität München, 85748 Garching, Germany
- Faculty of Mathematics and Natural Sciences, University of Bonn, 53113 Bonn, Germany
| | - Michael Hoelscher
- Division of Infectious Diseases and Tropical Medicine, University Hospital, LMU Munich, 80802 Munich, Germany
- German Center for Infection Research (DZIF), Partner site Munich, Germany
- Center for International Health (CIH), University Hospital, LMU Munich, 80336 Munich, Germany
| | - Andreas Wieser
- Division of Infectious Diseases and Tropical Medicine, University Hospital, LMU Munich, 80802 Munich, Germany
- German Center for Infection Research (DZIF), Partner site Munich, Germany
| | - on behalf of the KoCo19-Study Group
- Division of Infectious Diseases and Tropical Medicine, University Hospital, LMU Munich, 80802 Munich, Germany
- German Center for Infection Research (DZIF), Partner site Munich, Germany
- Institute of Radiation Medicine, Helmholtz Zentrum München, 85764 Neuherberg, Germany
- Institute of Computational Biology, Helmholtz Zentrum München, 85764 Neuherberg, Germany
- Center for Mathematics, Technische Universität München, 85748 Garching, Germany
- Department of Business Administration and Economics, Bielefeld University, 33615 Bielefeld, Germany
- Bavarian Health and Food Safety Authority (LGL), Germany
- Core Facility Statistical Consulting, Helmholtz Zentrum München, 85764 Neuherberg, Germany
- BRK-Blutspendedienst, 80336 Munich, Germany
- Department of Conservative Dentistry and Periodontology, University Hospital, LMU Munich Ludwig-Maximilians-University of Munich, Goethestr. 70, 80336 Munich, Germany
- Laboratory Becker and colleagues, Führichstr. 70, 81671 München, Germany
- Bundeswehr Institute of Microbiology, 80937 Munich, Germany
- Institute and Outpatient Clinic for Occupational, Social and Environmental Medicine, University Hospital, LMU Munich, 80336 Munich, Germany
- Center for International Health (CIH), University Hospital, LMU Munich, 80336 Munich, Germany
- Comprehensive Pneumology Center (CPC) Munich, German Center for Lung Research (DZL), 80337 Munich, Germany
- Faculty of Mathematics and Natural Sciences, University of Bonn, 53113 Bonn, Germany
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Koletzko L, Klucker E, Le Thi TG, Breiteneicher S, Rubio-Acero R, Neuhaus L, Stark RG, Standl M, Wieser A, Török H, Koletzko S, Schwerd T. Following Pediatric and Adult IBD Patients through the COVID-19 Pandemic: Changes in Psychosocial Burden and Perception of Infection Risk and Harm over Time. J Clin Med 2021; 10:4124. [PMID: 34575235 PMCID: PMC8464949 DOI: 10.3390/jcm10184124] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/10/2021] [Revised: 09/06/2021] [Accepted: 09/07/2021] [Indexed: 12/04/2022] Open
Abstract
BACKGROUND COVID-19-associated restrictions impact societies. We investigated the impact in a large cohort of inflammatory bowel disease (IBD) patients. METHODS Pediatric (pIBD) and adult patients and pIBD parents completed validated questionnaires for self-perceived stress (Perceived Stress Questionnaire, PSQ) and quality of life from July to October 2020 (1st survey) and March to April 2021 (2nd survey). Analyses were stratified by age groups (6-20, >20-40, >40-60, >60 years). Perceived risk of infection and harm from COVID-19 were rated on a 1-7 scale. An index for severe outcome (SIRSCO) was calculated. Multivariable logistic regression analysis was performed. RESULTS Of 820 invited patients, 504 (62%, 6-85 years) patients and 86 pIBD parents completed the 1st, thereof 403 (80.4%) the 2nd survey. COVID-19 restrictions resulted in cancelled doctoral appointments (26.7%), decreased physical activity, increased food intake, unintended weight gain and sleep disturbance. PSQ increased with disease activity. Elderly males rated lower compared to females or younger adults. PSQ in pIBD mothers were comparable to moderate/severe IBD adults. Infection risk and harm were perceived high in 36% and 75.4%. Multivariable logistic models revealed associations of higher perceived risk with >3 household members, job conditions and female gender, and of perceived harm with higher SIRSCO, unintended weight change, but not with gender or age. Cancelled clinic-visits were associated with both. SARS-CoV-2 antibodies prior 2nd infection wave were positive in 2/472 (0.4%). CONCLUSIONS IBD patients report a high degree of stress and self-perceived risk of complications from COVID-19 with major differences related to gender and age. Low seroprevalence may indicate altered immune response.
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Affiliation(s)
- Leandra Koletzko
- Department of Medicine II, LMU Klinikum, 81377 Munich, Germany; (L.K.); (S.B.); (L.N.); (H.T.)
| | - Elisabeth Klucker
- Department of Pediatrics, Dr von Hauner Kinderspital, LMU Klinikum, 80337 Munich, Germany; (E.K.); (T.G.L.T.); (T.S.)
| | - Thu Giang Le Thi
- Department of Pediatrics, Dr von Hauner Kinderspital, LMU Klinikum, 80337 Munich, Germany; (E.K.); (T.G.L.T.); (T.S.)
| | - Simone Breiteneicher
- Department of Medicine II, LMU Klinikum, 81377 Munich, Germany; (L.K.); (S.B.); (L.N.); (H.T.)
| | - Raquel Rubio-Acero
- Division of Infectious Diseases and Tropical Medicine, LMU Klinikum, 80802 Munich, Germany; (R.R.-A.); (A.W.)
| | - Lukas Neuhaus
- Department of Medicine II, LMU Klinikum, 81377 Munich, Germany; (L.K.); (S.B.); (L.N.); (H.T.)
| | - Reneé G. Stark
- Institute of Health Economics and Healthcare Management, Helmholtz Zentrum München, 85764 Neuherberg, Germany;
| | - Marie Standl
- Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, 85764 Neuherberg, Germany;
| | - Andreas Wieser
- Division of Infectious Diseases and Tropical Medicine, LMU Klinikum, 80802 Munich, Germany; (R.R.-A.); (A.W.)
| | - Helga Török
- Department of Medicine II, LMU Klinikum, 81377 Munich, Germany; (L.K.); (S.B.); (L.N.); (H.T.)
| | - Sibylle Koletzko
- Department of Pediatrics, Dr von Hauner Kinderspital, LMU Klinikum, 80337 Munich, Germany; (E.K.); (T.G.L.T.); (T.S.)
- Department of Pediatrics, Gastroenterology and Nutrition, School of Medicine Collegium Medicum University of Warmia and Mazury, 10-719 Olsztyn, Poland
| | - Tobias Schwerd
- Department of Pediatrics, Dr von Hauner Kinderspital, LMU Klinikum, 80337 Munich, Germany; (E.K.); (T.G.L.T.); (T.S.)
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39
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Radon K, Bakuli A, Pütz P, Le Gleut R, Guggenbuehl Noller JM, Olbrich L, Saathoff E, Garí M, Schälte Y, Frahnow T, Wölfel R, Pritsch M, Rothe C, Pletschette M, Rubio-Acero R, Beyerl J, Metaxa D, Forster F, Thiel V, Castelletti N, Rieß F, Diefenbach MN, Fröschl G, Bruger J, Winter S, Frese J, Puchinger K, Brand I, Kroidl I, Wieser A, Hoelscher M, Hasenauer J, Fuchs C. From first to second wave: follow-up of the prospective COVID-19 cohort (KoCo19) in Munich (Germany). BMC Infect Dis 2021; 21:925. [PMID: 34493217 PMCID: PMC8423599 DOI: 10.1186/s12879-021-06589-4] [Citation(s) in RCA: 16] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/16/2021] [Accepted: 08/19/2021] [Indexed: 02/06/2023] Open
Abstract
BACKGROUND In 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. METHODS The 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 4433 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® 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. RESULTS Weighted 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 2020 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. CONCLUSION The 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 SARS-CoV-2 sero-positive 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.
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Affiliation(s)
- Katja Radon
- Institute and Outpatient Clinic for Occupational, Social and Environmental Medicine, University Hospital, LMU Munich, 80336, Munich, Germany.
- Center for International Health (CIH), University Hospital, LMU Munich, 80336, Munich, Germany.
- Comprehensive Pneumology Center (CPC) Munich, German Center for Lung Research (DZL), 89337, Munich, Germany.
| | - Abhishek Bakuli
- Division of Infectious Diseases and Tropical Medicine, University Hospital, LMU Munich, 80802, Munich, Germany
| | - Peter Pütz
- Institute of Computational Biology, Helmholtz Zentrum München-German Research Center for Environmental Health, 85764, Neuherberg, Germany
- Faculty of Business Administration and Economics, Bielefeld University, 33615, Bielefeld, Germany
| | - Ronan Le Gleut
- Institute of Computational Biology, Helmholtz Zentrum München-German Research Center for Environmental Health, 85764, Neuherberg, Germany
- Core Facility Statistical Consulting, Helmholtz Zentrum München-German Research Center for Environmental Health, 85764, Neuherberg, Germany
| | | | - Laura Olbrich
- Division of Infectious Diseases and Tropical Medicine, University Hospital, LMU Munich, 80802, Munich, Germany
- German Center for Infection Research (DZIF), partner site, Munich, Germany
| | - Elmar Saathoff
- Division of Infectious Diseases and Tropical Medicine, University Hospital, LMU Munich, 80802, Munich, Germany
- German Center for Infection Research (DZIF), partner site, Munich, Germany
| | - Mercè Garí
- Institute of Computational Biology, Helmholtz Zentrum München-German Research Center for Environmental Health, 85764, Neuherberg, Germany
| | - Yannik Schälte
- Institute of Computational Biology, Helmholtz Zentrum München-German Research Center for Environmental Health, 85764, Neuherberg, Germany
- Center for Mathematics, Technische Universität München, 85748, Garching, Germany
| | - Turid Frahnow
- Institute of Computational Biology, Helmholtz Zentrum München-German Research Center for Environmental Health, 85764, Neuherberg, Germany
- Faculty of Business Administration and Economics, Bielefeld University, 33615, Bielefeld, Germany
| | - Roman Wölfel
- German Center for Infection Research (DZIF), partner site, Munich, Germany
- Bundeswehr Institute of Microbiology, 80937, Munich, Germany
| | - Michael Pritsch
- Division of Infectious Diseases and Tropical Medicine, University Hospital, LMU Munich, 80802, Munich, Germany
- German Center for Infection Research (DZIF), partner site, Munich, Germany
| | - Camilla Rothe
- Division of Infectious Diseases and Tropical Medicine, University Hospital, LMU Munich, 80802, Munich, Germany
| | - Michel Pletschette
- Division of Infectious Diseases and Tropical Medicine, University Hospital, LMU Munich, 80802, Munich, Germany
| | - Raquel Rubio-Acero
- Division of Infectious Diseases and Tropical Medicine, University Hospital, LMU Munich, 80802, Munich, Germany
| | - Jessica Beyerl
- Division of Infectious Diseases and Tropical Medicine, University Hospital, LMU Munich, 80802, Munich, Germany
| | - Dafni Metaxa
- Division of Infectious Diseases and Tropical Medicine, University Hospital, LMU Munich, 80802, Munich, Germany
| | - Felix Forster
- Institute and Outpatient Clinic for Occupational, Social and Environmental Medicine, University Hospital, LMU Munich, 80336, Munich, Germany
- Comprehensive Pneumology Center (CPC) Munich, German Center for Lung Research (DZL), 89337, Munich, Germany
| | - Verena Thiel
- Division of Infectious Diseases and Tropical Medicine, University Hospital, LMU Munich, 80802, Munich, Germany
| | - Noemi Castelletti
- Division of Infectious Diseases and Tropical Medicine, University Hospital, LMU Munich, 80802, Munich, Germany
| | - Friedrich Rieß
- Division of Infectious Diseases and Tropical Medicine, University Hospital, LMU Munich, 80802, Munich, Germany
- German Center for Infection Research (DZIF), partner site, Munich, Germany
| | - Maximilian N Diefenbach
- Division of Infectious Diseases and Tropical Medicine, University Hospital, LMU Munich, 80802, Munich, Germany
| | - Günter Fröschl
- Center for International Health (CIH), University Hospital, LMU Munich, 80336, Munich, Germany
- Division of Infectious Diseases and Tropical Medicine, University Hospital, LMU Munich, 80802, Munich, Germany
| | - Jan Bruger
- Division of Infectious Diseases and Tropical Medicine, University Hospital, LMU Munich, 80802, Munich, Germany
| | - Simon Winter
- Division of Infectious Diseases and Tropical Medicine, University Hospital, LMU Munich, 80802, Munich, Germany
| | - Jonathan Frese
- Division of Infectious Diseases and Tropical Medicine, University Hospital, LMU Munich, 80802, Munich, Germany
| | - Kerstin Puchinger
- Division of Infectious Diseases and Tropical Medicine, University Hospital, LMU Munich, 80802, Munich, Germany
| | - Isabel Brand
- Division of Infectious Diseases and Tropical Medicine, University Hospital, LMU Munich, 80802, Munich, Germany
| | - Inge Kroidl
- Division of Infectious Diseases and Tropical Medicine, University Hospital, LMU Munich, 80802, Munich, Germany
- German Center for Infection Research (DZIF), partner site, Munich, Germany
| | - Andreas Wieser
- Division of Infectious Diseases and Tropical Medicine, University Hospital, LMU Munich, 80802, Munich, Germany
- German Center for Infection Research (DZIF), partner site, Munich, Germany
| | - Michael Hoelscher
- Center for International Health (CIH), University Hospital, LMU Munich, 80336, Munich, Germany
- Division of Infectious Diseases and Tropical Medicine, University Hospital, LMU Munich, 80802, Munich, Germany
- German Center for Infection Research (DZIF), partner site, Munich, Germany
| | - Jan Hasenauer
- Institute of Computational Biology, Helmholtz Zentrum München-German Research Center for Environmental Health, 85764, Neuherberg, Germany
- Center for Mathematics, Technische Universität München, 85748, Garching, Germany
- Interdisciplinary Research Unit Mathematics and Life Sciences, University of Bonn, 53113, Bonn, Germany
| | - Christiane Fuchs
- Institute of Computational Biology, Helmholtz Zentrum München-German Research Center for Environmental Health, 85764, Neuherberg, Germany
- Faculty of Business Administration and Economics, Bielefeld University, 33615, Bielefeld, Germany
- Core Facility Statistical Consulting, Helmholtz Zentrum München-German Research Center for Environmental Health, 85764, Neuherberg, Germany
- Center for Mathematics, Technische Universität München, 85748, Garching, Germany
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Wratil PR, Schmacke NA, Osterman A, Weinberger T, Rech J, Karakoc B, Zeilberger M, Steffen J, Mueller TT, Spaeth PM, Stern M, Albanese M, Thun H, Reinbold J, Sandmeyer B, Kressirer P, Grabein B, Falkai P, Adorjan K, Hornung V, Kaderali L, Klein M, Keppler OT. In-depth profiling of COVID-19 risk factors and preventive measures in healthcare workers. Infection 2021; 50:381-394. [PMID: 34379308 PMCID: PMC8354838 DOI: 10.1007/s15010-021-01672-z] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/22/2021] [Accepted: 07/17/2021] [Indexed: 12/12/2022]
Abstract
Purpose To determine risk factors for coronavirus disease 2019 (COVID-19) in healthcare workers (HCWs), characterize symptoms, and evaluate preventive measures against SARS-CoV-2 spread in hospitals. Methods In a cross-sectional study conducted between May 27 and August 12, 2020, after the first wave of the COVID-19 pandemic, we obtained serological, epidemiological, occupational as well as COVID-19-related data at a quaternary care, multicenter hospital in Munich, Germany. Results 7554 HCWs participated, 2.2% of whom tested positive for anti-SARS-CoV-2 antibodies. Multivariate analysis revealed increased COVID-19 risk for nurses (3.1% seropositivity, 95% CI 2.5–3.9%, p = 0.012), staff working on COVID-19 units (4.6% seropositivity, 95% CI 3.2–6.5%, p = 0.032), males (2.4% seropositivity, 95% CI 1.8–3.2%, p = 0.019), and HCWs reporting high-risk exposures to infected patients (5.5% seropositivity, 95% CI 4.0–7.5%, p = 0.0022) or outside of work (12.0% seropositivity, 95% CI 8.0–17.4%, p < 0.0001). Smoking was a protective factor (1.1% seropositivity, 95% CI 0.7–1.8% p = 0.00018) and the symptom taste disorder was strongly associated with COVID-19 (29.8% seropositivity, 95% CI 24.3–35.8%, p < 0.0001). An unbiased decision tree identified subgroups with different risk profiles. Working from home as a preventive measure did not protect against SARS-CoV-2 infection. A PCR-testing strategy focused on symptoms and high-risk exposures detected all larger COVID-19 outbreaks. Conclusion Awareness of the identified COVID-19 risk factors and successful surveillance strategies are key to protecting HCWs against SARS-CoV-2, especially in settings with limited vaccination capacities or reduced vaccine efficacy. Supplementary Information The online version contains supplementary material available at 10.1007/s15010-021-01672-z.
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Affiliation(s)
- Paul R Wratil
- Faculty of Medicine, National Reference Center for Retroviruses, Max Von Pettenkofer Institute and Gene Center, Virology, LMU München, Munich, Germany.
- German Center for Infection Research (DZIF), Partner site, Munich, Germany.
| | - Niklas A Schmacke
- Department of Biochemistry and Gene Center, LMU München, Munich, Germany
| | - Andreas Osterman
- Faculty of Medicine, National Reference Center for Retroviruses, Max Von Pettenkofer Institute and Gene Center, Virology, LMU München, Munich, Germany
| | - Tobias Weinberger
- Department of Medicine I, University Hospital, LMU München, Munich, Germany
- DZHK (German Centre for Cardiovascular Research), Partner Site Munich Heart Alliance, Munich, Germany
| | - Jochen Rech
- Department of Biochemistry and Gene Center, LMU München, Munich, Germany
| | - Burak Karakoc
- Faculty of Medicine, National Reference Center for Retroviruses, Max Von Pettenkofer Institute and Gene Center, Virology, LMU München, Munich, Germany
| | - Mira Zeilberger
- Department of Medicine IV, University Hospital, LMU München, Munich, Germany
| | - Julius Steffen
- Department of Medicine I, University Hospital, LMU München, Munich, Germany
- DZHK (German Centre for Cardiovascular Research), Partner Site Munich Heart Alliance, Munich, Germany
| | - Tonina T Mueller
- Department of Medicine I, University Hospital, LMU München, Munich, Germany
| | - Patricia M Spaeth
- Faculty of Medicine, National Reference Center for Retroviruses, Max Von Pettenkofer Institute and Gene Center, Virology, LMU München, Munich, Germany
| | - Marcel Stern
- Faculty of Medicine, National Reference Center for Retroviruses, Max Von Pettenkofer Institute and Gene Center, Virology, LMU München, Munich, Germany
| | - Manuel Albanese
- Faculty of Medicine, National Reference Center for Retroviruses, Max Von Pettenkofer Institute and Gene Center, Virology, LMU München, Munich, Germany
| | - Hella Thun
- Department of Communication and Media, University Hospital, LMU München, Munich, Germany
| | - Julia Reinbold
- Department of Communication and Media, University Hospital, LMU München, Munich, Germany
| | - Benedikt Sandmeyer
- Institute of Emergency Medicine and Management in Medicine, University Hospital, LMU Munich, Munich, Germany
| | - Philipp Kressirer
- Department of Communication and Media, University Hospital, LMU München, Munich, Germany
| | - Béatrice Grabein
- Department for Clinical Microbiology and Hospital Hygiene, University Hospital, LMU München, Munich, Germany
| | - Peter Falkai
- Department of Psychiatry and Psychotherapy, University Hospital, LMU München, Munich, Germany
| | - Kristina Adorjan
- Department of Psychiatry and Psychotherapy, University Hospital, LMU München, Munich, Germany
| | - Veit Hornung
- Department of Biochemistry and Gene Center, LMU München, Munich, Germany
| | - Lars Kaderali
- Institute of Bioinformatics, University Medicine Greifswald, Greifswald, Germany
| | - Matthias Klein
- Emergency Department and Department of Neurology, University Hospital, LMU München, Munich, Germany
| | - Oliver T Keppler
- Faculty of Medicine, National Reference Center for Retroviruses, Max Von Pettenkofer Institute and Gene Center, Virology, LMU München, Munich, Germany.
- German Center for Infection Research (DZIF), Partner site, Munich, Germany.
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Rubio-Acero R, Castelletti N, Fingerle V, Olbrich L, Bakuli A, Wölfel R, Girl P, Müller K, Jochum S, Strobl M, Hoelscher M, Wieser A. In Search of the SARS-CoV-2 Protection Correlate: Head-to-Head Comparison of Two Quantitative S1 Assays in Pre-characterized Oligo-/Asymptomatic Patients. Infect Dis Ther 2021; 10:1-14. [PMID: 34155471 PMCID: PMC8208377 DOI: 10.1007/s40121-021-00475-x] [Citation(s) in RCA: 50] [Impact Index Per Article: 16.7] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/25/2021] [Accepted: 05/28/2021] [Indexed: 12/31/2022] Open
Abstract
BACKGROUND Quantitative serological assays detecting response to SARS-CoV-2 are needed to quantify immunity. This study analyzed the performance and correlation of two quantitative anti-S1 assays in oligo-/asymptomatic individuals from a population-based cohort. METHODS In total, 362 plasma samples (108 with reverse transcription-polymerase chain reaction [RT-PCR]-positive pharyngeal swabs, 111 negative controls, and 143 with positive serology without confirmation by RT-PCR) were tested with quantitative assays (Euroimmun Anti-SARS-CoV-2 QuantiVac enzyme-linked immunosorbent assay [EI-S1-IgG-quant]) and Roche Elecsys® Anti-SARS-CoV-2 S [Ro-RBD-Ig-quant]), which were compared with each other and confirmatory tests, including wild-type virus micro-neutralization (NT) and GenScript®cPass™. Square roots R of coefficients of determination were calculated for continuous variables and non-parametric tests were used for paired comparisons. RESULTS Quantitative anti-S1 serology correlated well with each other (true positives, 96%; true negatives, 97%). Antibody titers decreased over time (< 30 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 distinct separation between positives and negatives, and less non-specific reactivity versus EI-S1-IgG-quant. Raw values (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 NT > 1:5 in 95% of cases. CONCLUSIONS Our findings suggest both quantitative anti-S1 assays (EI-S1-IgG-quant and Ro-RBD-Ig-quant) may replace direct neutralization assays in quantitative measurement of immune protection against SARS-CoV-2 in certain circumstances. However, although the mean antibody titers for both assays tended to decrease over time, a higher proportion of Ro-RBD-Ig-quant values remained positive after 240 days. SUPPLEMENTARY INFORMATION The online version contains supplementary material available at 10.1007/s40121-021-00475-x.
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Affiliation(s)
- Raquel Rubio-Acero
- Division of Infectious Diseases and Tropical Medicine, University Hospital, Ludwig-Maximilians-Universität (LMU) Munich, Leopoldstr. 5, 80802 Munich, Germany
| | - Noemi Castelletti
- Division of Infectious Diseases and Tropical Medicine, University Hospital, Ludwig-Maximilians-Universität (LMU) Munich, Leopoldstr. 5, 80802 Munich, Germany
- Institute of Radiation Medicine, Helmholtz Zentrum München, 85764 Neuherberg, Germany
| | - Volker Fingerle
- German Center for Infection Research (DZIF), Partner Site, Munich, Germany
- Bavarian Health and Food Safety Authority (LGL), Oberschleissheim, Germany
| | - Laura Olbrich
- Division of Infectious Diseases and Tropical Medicine, University Hospital, Ludwig-Maximilians-Universität (LMU) Munich, Leopoldstr. 5, 80802 Munich, Germany
- German Center for Infection Research (DZIF), Partner Site, Munich, Germany
| | - Abhishek Bakuli
- Division of Infectious Diseases and Tropical Medicine, University Hospital, Ludwig-Maximilians-Universität (LMU) Munich, Leopoldstr. 5, 80802 Munich, Germany
| | - Roman Wölfel
- German Center for Infection Research (DZIF), Partner Site, Munich, Germany
- Bundeswehr Institute of Microbiology, 80937 Munich, Germany
| | - Philipp Girl
- German Center for Infection Research (DZIF), Partner Site, Munich, Germany
- Bundeswehr Institute of Microbiology, 80937 Munich, Germany
| | - Katharina Müller
- German Center for Infection Research (DZIF), Partner Site, Munich, Germany
- Bundeswehr Institute of Microbiology, 80937 Munich, Germany
| | | | | | - Michael Hoelscher
- Division of Infectious Diseases and Tropical Medicine, University Hospital, Ludwig-Maximilians-Universität (LMU) Munich, Leopoldstr. 5, 80802 Munich, Germany
- German Center for Infection Research (DZIF), Partner Site, Munich, Germany
- Center for International Health (CIH), University Hospital, LMU Munich, 80336 Munich, Germany
| | - Andreas Wieser
- Division of Infectious Diseases and Tropical Medicine, University Hospital, Ludwig-Maximilians-Universität (LMU) Munich, Leopoldstr. 5, 80802 Munich, Germany
- German Center for Infection Research (DZIF), Partner Site, Munich, Germany
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Brand I, Gilberg L, Bruger J, Garí M, Wieser A, Eser TM, Frese J, Ahmed MIM, Rubio-Acero R, Guggenbuehl Noller JM, Castelletti N, Diekmannshemke J, Thiesbrummel S, Huynh D, Winter S, Kroidl I, Fuchs C, Hoelscher M, Roider J, Kobold S, Pritsch M, Geldmacher C. Broad T Cell Targeting of Structural Proteins After SARS-CoV-2 Infection: High Throughput Assessment of T Cell Reactivity Using an Automated Interferon Gamma Release Assay. Front Immunol 2021; 12:688436. [PMID: 34093595 PMCID: PMC8173205 DOI: 10.3389/fimmu.2021.688436] [Citation(s) in RCA: 22] [Impact Index Per Article: 7.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/30/2021] [Accepted: 04/30/2021] [Indexed: 11/13/2022] Open
Abstract
Background Adaptive immune responses to structural proteins of the virion play a crucial role in protection against coronavirus disease 2019 (COVID-19). We therefore studied T cell responses against multiple SARS-CoV-2 structural proteins in a large cohort using a simple, fast, and high-throughput approach. Methods An automated interferon gamma release assay (IGRA) for the Nucleocapsid (NC)-, Membrane (M)-, Spike-C-terminus (SCT)-, and N-terminus-protein (SNT)-specific T cell responses was performed using fresh whole blood from study subjects with convalescent, confirmed COVID-19 (n = 177, more than 200 days post infection), exposed household members (n = 145), and unexposed controls (n = 85). SARS-CoV-2-specific antibodies were assessed using Elecsys® Anti-SARS-CoV-2 (Ro-N-Ig) and Anti-SARS-CoV-2-ELISA (IgG) (EI-S1-IgG). Results 156 of 177 (88%) previously PCR confirmed cases were still positive by Ro-N-Ig more than 200 days after infection. In T cells, most frequently the M-protein was targeted by 88% seropositive, PCR confirmed cases, followed by SCT (85%), NC (82%), and SNT (73%), whereas each of these antigens was recognized by less than 14% of non-exposed control subjects. Broad targeting of these structural virion proteins was characteristic of convalescent SARS-CoV-2 infection; 68% of all seropositive individuals targeted all four tested antigens. Indeed, anti-NC antibody titer correlated loosely, but significantly with the magnitude and breadth of the SARS-CoV-2-specific T cell response. Age, sex, and body mass index were comparable between the different groups. Conclusion SARS-CoV-2 seropositivity correlates with broad T cell reactivity of the structural virus proteins at 200 days after infection and beyond. The SARS-CoV-2-IGRA can facilitate large scale determination of SARS-CoV-2-specific T cell responses with high accuracy against multiple targets.
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Affiliation(s)
- Isabel Brand
- Division of Infectious Diseases and Tropical Medicine, University Hospital, Ludwig-Maximilians-Universität (LMU) Munich, Munich, Germany
- Division of Clinical Pharmacology, Department of Medicine IV, University Hospital, LMU Munich, Munich, Germany
| | - Leonard Gilberg
- Division of Infectious Diseases and Tropical Medicine, University Hospital, Ludwig-Maximilians-Universität (LMU) Munich, Munich, Germany
- Department of Infectious Diseases, University Hospital, LMU Munich, Munich, Germany
| | - Jan Bruger
- Division of Infectious Diseases and Tropical Medicine, University Hospital, Ludwig-Maximilians-Universität (LMU) Munich, Munich, Germany
| | - Mercè Garí
- Institute of Computational Biology, Helmholtz Zentrum München – German Research Center for Environmental Health (HMGU), Neuherberg, Germany
| | - Andreas Wieser
- Division of Infectious Diseases and Tropical Medicine, University Hospital, Ludwig-Maximilians-Universität (LMU) Munich, Munich, Germany
- German Center for Infection Research (DZIF), Partner Site Munich, Munich, Germany
| | - Tabea M. Eser
- Division of Infectious Diseases and Tropical Medicine, University Hospital, Ludwig-Maximilians-Universität (LMU) Munich, Munich, Germany
- German Center for Infection Research (DZIF), Partner Site Munich, Munich, Germany
| | - Jonathan Frese
- Division of Infectious Diseases and Tropical Medicine, University Hospital, Ludwig-Maximilians-Universität (LMU) Munich, Munich, Germany
| | - Mohamed I. M. Ahmed
- Division of Infectious Diseases and Tropical Medicine, University Hospital, Ludwig-Maximilians-Universität (LMU) Munich, Munich, Germany
- German Center for Infection Research (DZIF), Partner Site Munich, Munich, Germany
| | - Raquel Rubio-Acero
- Division of Infectious Diseases and Tropical Medicine, University Hospital, Ludwig-Maximilians-Universität (LMU) Munich, Munich, Germany
| | - Jessica M. Guggenbuehl Noller
- Division of Infectious Diseases and Tropical Medicine, University Hospital, Ludwig-Maximilians-Universität (LMU) Munich, Munich, Germany
| | - Noemi Castelletti
- Division of Infectious Diseases and Tropical Medicine, University Hospital, Ludwig-Maximilians-Universität (LMU) Munich, Munich, Germany
| | - Jana Diekmannshemke
- Institute of Computational Biology, Helmholtz Zentrum München – German Research Center for Environmental Health (HMGU), Neuherberg, Germany
- Faculty of Business Administration and Economics, Bielefeld University, Bielefeld, Germany
| | - Sophie Thiesbrummel
- Institute of Computational Biology, Helmholtz Zentrum München – German Research Center for Environmental Health (HMGU), Neuherberg, Germany
- Faculty of Business Administration and Economics, Bielefeld University, Bielefeld, Germany
| | - Duc Huynh
- Division of Clinical Pharmacology, Department of Medicine IV, University Hospital, LMU Munich, Munich, Germany
| | - Simon Winter
- Division of Infectious Diseases and Tropical Medicine, University Hospital, Ludwig-Maximilians-Universität (LMU) Munich, Munich, Germany
| | - Inge Kroidl
- Division of Infectious Diseases and Tropical Medicine, University Hospital, Ludwig-Maximilians-Universität (LMU) Munich, Munich, Germany
- German Center for Infection Research (DZIF), Partner Site Munich, Munich, Germany
| | - Christiane Fuchs
- Institute of Computational Biology, Helmholtz Zentrum München – German Research Center for Environmental Health (HMGU), Neuherberg, Germany
- Faculty of Business Administration and Economics, Bielefeld University, Bielefeld, Germany
- Center for Mathematics, Technische Universität München, Garching, Germany
| | - Michael Hoelscher
- Division of Infectious Diseases and Tropical Medicine, University Hospital, Ludwig-Maximilians-Universität (LMU) Munich, Munich, Germany
- German Center for Infection Research (DZIF), Partner Site Munich, Munich, Germany
- Center for International Health (CIH), University Hospital, LMU Munich, Munich, Germany
| | - Julia Roider
- Department of Infectious Diseases, University Hospital, LMU Munich, Munich, Germany
- German Center for Infection Research (DZIF), Partner Site Munich, Munich, Germany
| | - Sebastian Kobold
- Division of Clinical Pharmacology, Department of Medicine IV, University Hospital, LMU Munich, Munich, Germany
- German Center for Translational Cancer Research (DKTK), Partner Site Munich, Munich, Germany
- Unit for Clinical Pharmacology (EKLiP), Helmholtz Zentrum München – German Research Center for Environmental Health (HMGU), Neuherberg, Germany
| | - Michael Pritsch
- Division of Infectious Diseases and Tropical Medicine, University Hospital, Ludwig-Maximilians-Universität (LMU) Munich, Munich, Germany
- German Center for Infection Research (DZIF), Partner Site Munich, Munich, Germany
| | - Christof Geldmacher
- Division of Infectious Diseases and Tropical Medicine, University Hospital, Ludwig-Maximilians-Universität (LMU) Munich, Munich, Germany
- German Center for Infection Research (DZIF), Partner Site Munich, Munich, Germany
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