Evidence map›Paper›PMID 39245152›Full record

ArticleThe Journal of infection2024

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

Ben Pascoe, Georgina Futcher, Johan Pensar, Sion C Bayliss, Evangelos Mourkas, Jessica K Calland, Matthew D Hitchings, Lavin A Joseph, Charlotte G Lane, Tiffany Greenlee and 11 more

Abstract read
In one paragraph

Article in The Journal of infection, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers.

0numbers the graph read from it
0cells of the map it votes in
21citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

21 citing papers in PubMed.

  1. Article
  2. AcceleratingProceedings of the National Academy of Sciences of the United States of America · 2026
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  3. Article
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  7. Genomic epidemiology ofProceedings of the National Academy of Sciences of the United States of America · 2026
    Article
  8. Detection ofEuro surveillance : bulletin Europeen sur les maladies transmissibles = European communicable disease bulletin · 2026
    Article
  9. Article
  10. Article
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  12. Article
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  14. Article
  15. Article
  16. Review
  17. Phenotypic characterization and antimicrobial resistance ofJournal of advanced veterinary and animal research · 2025
    Article
  18. FliO is an evolutionarily conserved yet diversified core component of the bacterial flagellar type III secretion system.Proceedings of the National Academy of Sciences of the United States of America · 2025
    Article
  19. Article
  20. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

21 authors.

Ben PascoeIneos Oxford Institute for Antimicrobial Research, Department of Biology, University of Oxford, Oxford, United Kingdom.
Georgina FutcherThe Milner Centre for Evolution, Department of Biology and Biochemistry, University of Bath, Claverton Down, Bath, United Kingdom.
Johan PensarDepartment of Mathematics, University of Oslo, Oslo, Norway.
Sion C BaylissBristol Veterinary School, University of Bristol, Langford, Bristol, United Kingdom.
Evangelos MourkasIneos 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 CallandOslo University Hospital, Oslo Centre for Biostatistics and Epidemiology, Oslo, Norway.
Matthew D HitchingsSwansea University Medical School, Swansea University, Swansea, United Kingdom.
Lavin A JosephDivision of Foodborne, Waterborne, and Environmental Diseases, Centers for Disease Control and Prevention, Atlanta, GA, USA.
Charlotte G LaneDivision of Foodborne, Waterborne, and Environmental Diseases, Centers for Disease Control and Prevention, Atlanta, GA, USA.
Tiffany GreenleeCenter for Food Safety and Applied Nutrition, Food and Drug Administration, College Park, MD, USA.
Nicolas ArningBig 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 WilsonBig Data Institute, Oxford Population Health, University of Oxford, Li Ka Shing Centre for Health Information and Discovery, Old Road Campus, Oxford, United Kingdom; Department for Continuing Education, University of Oxford, United Kingdom.
Keith A JolleyDepartment of Biology, University of Oxford, Oxford, United Kingdom.
Jukka CoranderOslo University Hospital, Oslo Centre for Biostatistics and Epidemiology, Oslo, Norway; Department of Mathematics and Statistics, University of Helsinki, Helsinki, Finland; Parasites and Microbes, Wellcome Sanger Institute, Cambridge, United Kingdom.
Martin C J MaidenDepartment of Biology, University of Oxford, Oxford, United Kingdom.
Craig T ParkerProduce Safety and Microbiology Research Unit, Agricultural Research Service, US Department of Agriculture, Albany, CA, USA.
Kerry K CooperSchool of Animal and Comparative Biomedical Sciences, University of Arizona, Tucson, AZ, USA.
Erica B RoseDivision of Foodborne, Waterborne, and Environmental Diseases, Centers for Disease Control and Prevention, Atlanta, GA, USA.
Kelli HiettCenter for Food Safety and Applied Nutrition, Food and Drug Administration, Laurel, MD, USA.
Beau B BruceDivision of Foodborne, Waterborne, and Environmental Diseases, Centers for Disease Control and Prevention, Atlanta, GA, USA.
Samuel K SheppardIneos Oxford Institute for Antimicrobial Research, Department of Biology, University of Oxford, Oxford, United Kingdom. Electronic address: samuel.sheppard@biology.ox.ac.uk.

Funding

Medical Research Council MR/V001213/1Medical Research Council MR/V001213/2Wellcome Trust 088786Wellcome Trust 310742
6 · The paper itself

Abstract

objectivesIntegrating 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.

methodsDuring routine US national surveillance (2009-2019), 8856 Campylobacter genomes from human infections and 16,703 from possible sources were sequenced. Using machine learning and probabilistic models, we target genetic variation associated with host adaptation to attribute the source of human infections and estimate the importance of different disease reservoirs.

resultsPoultry was identified as the primary source of human infections, responsible for an estimated 68% of cases, followed by cattle (28%), and only a small contribution from wild birds (3%) and pork sources (1%). There was also evidence of an increase in multidrug resistance, particularly among isolates attributed to chickens.

conclusionsNational surveillance and source attribution can guide policy, and our study suggests that interventions targeting poultry will yield the greatest reductions in campylobacteriosis and spread of AMR in the US. DATA AVAILABILITY: All sequence reads were uploaded and shared on NCBI's Sequence Read Archive (SRA) associated with BioProjects; PRJNA239251 (CDC / PulseNet surveillance), PRJNA287430 (FSIS surveillance), PRJNA292668 & PRJNA292664 (NARMS) and PRJNA258022 (FDA surveillance). Publicly available genomes, including reference genomes and isolates sampled worldwide from wild birds are associated with BioProject accessions: PRJNA176480, PRJNA177352, PRJNA342755, PRJNA345429, PRJNA312235, PRJNA415188, PRJNA524300, PRJNA528879, PRJNA529798, PRJNA575343, PRJNA524315 and PRJNA689604. Contiguous assemblies of all genome sequences compared are available at Mendeley data (assembled C. coli genomes doi: 10.17632/gxswjvxyh3.1; assembled C. jejuni genomes doi: 10.17632/6ngsz3dtbd.1) and individual project and accession numbers can be found in Supplementary tables S1 and S2, which also includes pubMLST identifiers for assembled genomes. Figshare (10.6084/m9.figshare.20279928). Interactive phylogenies are hosted on microreact separately for C. jejuni (https://microreact.org/project/pascoe-us-cjejuni) and C. coli (https://microreact.org/project/pascoe-us-ccoli).

Indexed as

CampylobacterCampylobacter InfectionsMachine LearningAnimalsCattleChickensEpidemiological MonitoringGenome, BacterialHumansPoultryRetrospective StudiesSwineUnited StatesCampylobacteriosisChicken consumptionGastroenteritisMachine learningSource attribution

Identifiers

PMID39245152
PMCPMC7617841

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.