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Responsive population-based cohorts as platforms for characterising pathogen- and population-level infection dynamics for epidemic prevention, preparedness and response
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Ivonne Morales1,2
, Van Kính Nguyen2,3
, Mirna Abd El Aziz1 , Ayten Sultani1,4 , Till Bärnighausen2,5,6
, Heiko Becher2
, Sandra Ciesek7,8,9
, Beate Kampmann10,11
, Berit Lange12,13
, Jan Rupp14,15
, Simone Scheithauer16
, Helen Ward3,17,18,19
, André Karch20
, Claudia M Denkinger1,21
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View Affiliations Hide AffiliationsAffiliations: 1 Department of Infectious Disease and Tropical Medicine, Center for Infectious Diseases, Heidelberg University Hospital, Heidelberg, Germany 2 Heidelberg Institute for Global Health (HIGH), Heidelberg University Hospital, Heidelberg, Germany 3 School of Public Health, Imperial College London, London, United Kingdom 4 Institute of Tropical Medicine, Travel Medicine, and Human Parasitology, University Hospital Tübingen, Tübingen, Germany 5 Department of Global Health and Population, Harvard TH Chan School of Public Health, Harvard University, Boston, United States 6 Africa Health Research Institute, KwaZulu-Natal, South Africa 7 Institute for Medical Virology, University Hospital Frankfurt, Goethe University Frankfurt, Frankfurt am Main, Frankfurt, Germany 8 German Center for Infection Research (DZIF), Frankfurt am Main, Frankfurt, Germany 9 Fraunhofer Institute for Translational Medicine and Pharmacology ITMP, Frankfurt am Main, Frankfurt, Germany 10 The Vaccine Centre, Faculty of Infectious and Tropical Diseases, London School of Hygiene and Tropical Medicine, London, United Kingdom 11 Medical Research Council Unit The Gambia, London School of Hygiene and Tropical Medicine, Fajara, The Gambia 12 Department of Epidemiology, Helmholtz Centre for Infection Research (HZI), Braunschweig, Germany 13 German Center for Infection Research (DZIF), Braunschweig, Germany 14 Department of Infectious Diseases and Microbiology, University Hospital Schleswig-Holstein, Campus Lübeck, Lübeck, Germany 15 German Center for Infection Research (DZIF), Partner Hamburg-Lübeck-Borstel-Riems, Germany 16 Department of Infection Control and Infectious Diseases, University Medical Center Göttingen (UMG), Georg-August University Göttingen, Göttingen, Germany 17 Imperial College Healthcare NHS Trust, London, United Kingdom 18 National Institute for Health Research Imperial Biomedical Research Centre, London, United Kingdom 19 MRC Centre for Global Infectious Disease Analysis and Abdul Latif Jameel Institute for Disease and Emergency Analytics, Imperial College London, London, United Kingdom 20 Institute of Epidemiology and Social Medicine, University of Münster, Albert-Schweitzer-Campus 1, Münster, Germany 21 German Center for Infection Research (DZIF), Partner Heidelberg, Heidelberg, GermanyIvonne Moralesivonne.morales uni-heidelberg.de
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Citation style for this article: Morales Ivonne, Nguyen Van Kính, Abd El Aziz Mirna, Sultani Ayten, Bärnighausen Till, Becher Heiko, Ciesek Sandra, Kampmann Beate, Lange Berit, Rupp Jan, Scheithauer Simone, Ward Helen, Karch André, Denkinger Claudia M. Responsive population-based cohorts as platforms for characterising pathogen- and population-level infection dynamics for epidemic prevention, preparedness and response. Euro Surveill. 2025;30(25):pii=2400255. https://doi.org/10.2807/1560-7917.ES.2025.30.25.2400255 Received: 25 Apr 2024; Accepted: 13 Feb 2025
Abstract
Establishing population-based cohorts is indispensable for effective epidemic prevention, preparedness and response. Existing passive surveillance systems face limitations in their capacity to promptly provide representative data for estimating disease burden and modelling disease transmission. This perspective paper introduces a framework for establishing a dynamic and responsive nationally representative population-based cohort, with Germany as an example country. We emphasise the need for comprehensive demographic representation, innovative strategies to address participant attrition, efficient data collection and testing using digital tools, as well as novel data integration and analysis methods. Financial considerations and cost estimates for cohort establishment are discussed, highlighting potential cost savings through integration with existing research infrastructures and digital approaches. The framework outlined for creating, operating and integrating the cohort within the broader epidemiological landscape illustrates the potential of a population-based cohort to offer timely, evidence-based insights for robust public health interventions during both epidemics and pandemics, as well as during inter-epidemic periods.

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