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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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