Open Access

Peer-reviewed

A Bayesian model for repeated cross-sectional epidemic prevalence survey data

• Nicholas Steyn ,

  Roles Conceptualization, Data curation, Formal analysis, Investigation, Methodology, Resources, Software, Validation, Visualization, Writing – original draft, Writing – review & editing

  * E-mail: nicholas.steyn@univ.ox.ac.uk

  Affiliation Department of Statistics, University of Oxford, Oxford, United Kingdom

  ORCID logo https://orcid.org/0000-0001-8904-2941

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• Marc Chadeau-Hyam,

  Roles Conceptualization, Data curation, Formal analysis, Funding acquisition, Investigation, Methodology, Project administration, Resources, Supervision, Validation, Visualization, Writing – original draft, Writing – review & editing

  Affiliations MRC Centre for Environment and Health, School of Public Health, Imperial College London, London, United Kingdom, Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, United Kingdom

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• Paul Elliott,

  Roles Data curation, Funding acquisition, Project administration, Writing – review & editing

  Affiliations MRC Centre for Environment and Health, School of Public Health, Imperial College London, London, United Kingdom, Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, United Kingdom

  ORCID logo https://orcid.org/0000-0002-7511-5684

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• Christl A. Donnelly

  Roles Conceptualization, Data curation, Formal analysis, Funding acquisition, Investigation, Methodology, Project administration, Resources, Supervision, Validation, Visualization, Writing – original draft, Writing – review & editing

  Affiliations Department of Statistics, University of Oxford, Oxford, United Kingdom, Pandemic Sciences Institute, University of Oxford, Oxford, United Kingdom

  ORCID logo https://orcid.org/0000-0002-0195-2463

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