DiSCoVer: Discovering the sources of Salmonella, Campylobacter, VTEC and antimicrobial resistance
This project brought together experts from different disciplines (microbiology, bioinformatics and epidemiology) and sectors (veterinary science, food safety, public health and environmental health) from 19 institutions in 13 European countries into a unique consortium to address the challenges of source attribution in an interdisciplinary manner. As there is no gold standard for source attribution, we took a comprehensive approach to applying several different methodologies and models in a comparative fashion.
The project has mapped the existing knowledge gaps. The work started by mapping existing data and establishing a joint data-sharing platform for the project partners. Data was included from a broad range of reservoirs and sources, including those that are not traditionally part of existing monitoring and surveillance activities, e.g. pets (incl. reptiles), wildlife, and environmental sources.
The work also focused on cataloging, evaluating and advancing existing methods for source attribution and developing methods for the critical assessment of source attribution models. Novel approaches for source attribution were explored, developed and assessed. Investigation of existing approaches included microbial subtyping, meta-analysis of case-control studies and outbreak data, and risk-assessment-based methods. The source attribution estimates focused on three pathogens (Salmonella, Campylobacter, and STEC) and AMR.
Project Outputs and Outcomes
DiSCoVeR project has collected comprehensive and standardised datasets for the target pathogens (Salmonella (n=145,000 isolates; s=4,185 sequences), Campylobacter (n=5,361 isolates/sequences), STEC (n=7,552 isolates; s=3,418), and ESBL (n=10,674 isolates)) and made the phenotypic and metadata open accessible through Zenodo. The sequence data (WGS) will be available at ENA through an umbrella project. We believe that these multi-country datasets compiled of isolate data and sequences from humans and various animal and food sources are quite unique and could be analysed by other methods and by other researchers to provide novel insights to the epidemiology of foodborne hazards in EU MS.
DiSCoVeR project has made a critical and systematic assessment of existing source attribution models and developed new phenotypic and genomic-based attribution models for pathogen and antimicrobial resistance.
Based on the results, DiSCoVeR project has provided recommendations on the translation of results from source attribution models in to actions, emphasising that Salmonella in pigs and pork and Campylobacter in broilers and chicken meat stand out as areas, where targeted future control and intervention could be implemented to reduce the burden of human infections significantly. The project has also evaluated current surveillance and control activities in a One Health context and made recommendations for improvement by seeking out (further) collaboration and identifying possible surveillance synergies within the environmental/ecosystem pillar of One Health, as surveillance and research focus currently is very much oriented towards human health and food-producing animals. Most of these recommendations are considered relevant for risk managers/decision makers such as ECDC and EFSA, national food, veterinary, and environmental authorities, and farmer and consumer organisations. These recommendations have been presented to and discussed with stakeholders, including ECDC, EFSA, EURLs, and the EC.
Finally, DiSCoVeR project has evaluated transfer of the source attribution approaches as an opportunity to strengthen the institutional capacity building for One Health by promoting increased network-collaboration and training within integrated surveillance, source attribution approaches, burden of disease methodologies, risk assessment, and system thinking.
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