Machine learning to attribute the source of Campylobacter infections in the United States: A retrospective analysis of national surveillance data.

Journal: The Journal of infection
PMID:

Abstract

OBJECTIVES: Integrating pathogen genomic surveillance with bioinformatics can enhance public health responses by identifying risk and guiding interventions. This study focusses on the two predominant Campylobacter species, which are commonly found in the gut of birds and mammals and often infect humans via contaminated food. Rising incidence and antimicrobial resistance (AMR) are a global concern, and there is an urgent need to quantify the main routes to human infection.

Authors

  • Ben Pascoe
    Ineos Oxford Institute for Antimicrobial Research, Department of Biology, University of Oxford, Oxford, United Kingdom.
  • Georgina Futcher
    The Milner Centre for Evolution, Department of Biology and Biochemistry, University of Bath, Claverton Down, Bath, United Kingdom.
  • Johan Pensar
    Department of Mathematics, University of Oslo, Oslo, Norway.
  • Sion C Bayliss
    Bristol Veterinary School, University of Bristol, Langford, Bristol, United Kingdom.
  • Evangelos Mourkas
    Ineos Oxford Institute for Antimicrobial Research, Department of Biology, University of Oxford, Oxford, United Kingdom; Zoonosis Science Centre, Department of Medical Sciences, Uppsala University, Uppsala, Sweden.
  • Jessica K Calland
    Oslo University Hospital, Oslo Centre for Biostatistics and Epidemiology, Oslo, Norway.
  • Matthew D Hitchings
    Swansea University Medical School, Swansea University, Swansea, United Kingdom.
  • Lavin A Joseph
    Division of Foodborne, Waterborne, and Environmental Diseases, Centers for Disease Control and Prevention, Atlanta, GA, USA.
  • Charlotte G Lane
    Division of Foodborne, Waterborne, and Environmental Diseases, Centers for Disease Control and Prevention, Atlanta, GA, USA.
  • Tiffany Greenlee
    Center for Food Safety and Applied Nutrition, Food and Drug Administration, College Park, MD, USA.
  • Nicolas Arning
    Big Data Institute, Oxford Population Health, University of Oxford, Li Ka Shing Centre for Health Information and Discovery, Old Road Campus, Oxford, United Kingdom.
  • Daniel J Wilson
    Nuffield Department of Medicine, University of Oxford, Oxford, OX3 7BN, UK.
  • Keith A Jolley
    Department of Biology, University of Oxford, Oxford, United Kingdom.
  • Jukka Corander
    Department of Mathematics and Statistics, University of Helsinki, Helsinki, Finland.
  • Martin C J Maiden
    Department of Biology, University of Oxford, Oxford, United Kingdom.
  • Craig T Parker
    Produce Safety and Microbiology Research Unit, Agricultural Research Service, US Department of Agriculture, Albany, CA, USA.
  • Kerry K Cooper
    School of Animal and Comparative Biomedical Sciences, University of Arizona, Tucson, AZ, USA.
  • Erica B Rose
    Division of Foodborne, Waterborne, and Environmental Diseases, Centers for Disease Control and Prevention, Atlanta, GA, USA.
  • Kelli Hiett
    Center for Food Safety and Applied Nutrition, Food and Drug Administration, Laurel, MD, USA.
  • Beau B Bruce
    From the Department of Ophthalmology (V.B., M.Y.L., B.B.B., N.J.N.), Emory University School of Medicine, Atlanta, Georgia, USA; Department of Neurology (V.B., B.B.B., N.J.N.), Emory University School of Medicine, Atlanta, Georgia, USA; Rollins School of Public Health (B.B.B.), Emory University School of Medicine, Atlanta, Georgia, USA.
  • Samuel K Sheppard
    Department of Biology, Ineos Oxford Institute, University of Oxford, Oxford, UK.