Cross-sectoral genomic surveillance reveals a lack of insight in sources of human infections with Shiga toxin-producing Escherichia coli, the Netherlands, 2017 to 2023
Eurosurveillance·
- DOI
- 10.2807/1560-7917.es.2024.29.49.2400264
- PMID
- —
- PMCID
- —
- OpenAlex
- W4405116373
- Study type
- Genomic study
- Publisher
- European Centre for Disease Control and Prevention (ECDC)
- Article type
- journal-article
- Integrity
- current
Why this research matters now
The findings highlight gaps in identifying sources of human STEC infections despite existing monitoring programs. The decision to begin national-level STEC isolation aims to improve surveillance, source attribution, and guidance for monitoring and outbreak investigation.
Structured evidence summary
Research question
The study examined phylogenetic clustering of Shiga toxin-producing Escherichia coli strains across human, animal, and food sectors in the Netherlands to understand reservoirs and sources of human STEC infections.
Study design
Cross-sectoral genomic surveillance analysis of STEC strains from animals, food, and human cases in the Dutch surveillance system from 2017 to 2023.
Population and setting
STEC strains collected from human cases, animals, and food sources in the Netherlands over a seven-year period (2017-2023).
Main findings
Phylogenetic clustering of STEC strains from animals, food, and human cases was low. International travel and person-to-person transmission contributed substantially to STEC epidemiology. Some STEC strains causing human disease may originate from human reservoirs, and certain animal and food products may be under-recognized as sources of infection.
Public-health relevance
The findings highlight gaps in identifying sources of human STEC infections despite existing monitoring programs. The decision to begin national-level STEC isolation aims to improve surveillance, source attribution, and guidance for monitoring and outbreak investigation.
Important limitations
This summary relies on the supplied single-article abstract and metadata. A full assessment of study limitations, including sampling methods, genomic resolution, and completeness of cross-sectoral data, requires review of the original paper.
GIDS interpretation
The GIDS classifier linked this article to topics including genomic epidemiology, surveillance, One Health, and travel medicine, reflecting its cross-sectoral approach and exploration of STEC transmission pathways. These links aid discoverability for users monitoring zoonotic pathogens and source attribution methods.
Related GIDS surveillance
Literature context does not validate, explain, or change a surveillance signal. Exact and contextual relationships are shown separately.
Evidence relationships
This article has 10 auditable classifier relationships to diseases, places, topics, and study design.