Probabilistic transmission models incorporating sequencing data for healthcare-associated Clostridioides difficile outperform heuristic rules and identify strain-specific differences in transmission

• David W. Eyre ,

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

  * E-mail: david.eyre@bdi.ox.ac.uk

  Affiliations Big Data Institute, Nuffield Department of Population Health, University of Oxford, United Kingdom, Nuffield Department of Medicine, University of Oxford, United Kingdom, Health Protection Research Unit in Healthcare Associated Infections and Antimicrobial Resistance, University of Oxford, United Kingdom

  https://orcid.org/0000-0001-5095-6367

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• Mirjam Laager,

  Roles Investigation, Writing – review & editing

  Affiliation Nuffield Department of Medicine, University of Oxford, United Kingdom

  https://orcid.org/0000-0002-7146-0544

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• A. Sarah Walker,

  Roles Conceptualization, Supervision

  Affiliations Nuffield Department of Medicine, University of Oxford, United Kingdom, Health Protection Research Unit in Healthcare Associated Infections and Antimicrobial Resistance, University of Oxford, United Kingdom

  https://orcid.org/0000-0002-0412-8509

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• Ben S. Cooper,

  Roles Supervision, Writing – review & editing

  Affiliation Nuffield Department of Medicine, University of Oxford, United Kingdom

  https://orcid.org/0000-0002-9445-7217

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• Daniel J. Wilson,

  Roles Conceptualization, Methodology, Supervision, Writing – review & editing

  Affiliation Big Data Institute, Nuffield Department of Population Health, University of Oxford, United Kingdom

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• on behalf of the CDC Modeling Infectious Diseases in Healthcare Program (MInD-Healthcare)