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Enhanced molecular-based (MLST/whole genome) surveillance and source attribution of campylobacter infections in the UK


"The information from this project will be used to provide quantitative attribution of human campylobacter infections to probable reservoir/sources (food, non-human animal or environmental) and monitoring the contribution that these different sources make to the burden of disease from campylobacter. In addition, this research will allow evaluation of changes between years and seasonality as well as subpopulation comparisons (children and adults; rural and urban). Identified clusters from single clone outbreaks will be utilised by public health authorities to support public health investigations. This characterisation and attribution of isolates should therefore provide feedback on whether the FSA’s campylobacter risk management programme is having an impact on the proportion of poultry meat associated campylobacter infections in humans relative to other sources.

This project will confirm current scientific evidence that the chicken reservoir and particularly chicken meat are the main sources of human cases of campylobacter infection in the UK, and verify that the interventions implemented by the poultry industry across the poultry chain are having an effect in reducing human cases attributable to chicken meat. If a reduction in human cases is not observed, this research would still provide information on potential shifts in the origin of human infection in relation to different food reservoirs (ie poultry, bovine, ovine).

The objectives for this project are:

Establish a laboratory and epidemiological sentinel sampling frame representative of urban and rural England (a two site sampling frame with defined urban and rural catchment areas).
Undertake genome sequencing on human isolates with extraction of MLST profile.
Obtain basic epidemiology including travel history from cases.
Establish a broad food animal and other source reference MLST dataset from existing data.
Implement rolling attribution of human infection to sources based on existing seven locus MLST approaches.
Genome sequence isolates from animals and foods to develop a whole genome sequence. reference database from important sources of human infection – complementing other ongoing work.
Develop a whole genome attribution dataset using the data from collaborative projects and publicly available genome data.
Maintain accessible virtual and physical archives of isolates from the project.
Develop and evaluate attribution methods based on whole genome data.
Implement rolling attribution of human infection to sources using whole genome data on isolates from this project."

University of Oxford
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