Evidence map›Paper›PMID 28694792›Full record

ArticleFrontiers in microbiology2017

Context Is Everything: Harmonization of Critical Food Microbiology Descriptors and Metadata for Improved Food Safety and Surveillance.

Emma Griffiths, Damion Dooley, Morag Graham, Gary Van Domselaar, Fiona S L Brinkman, William W L Hsiao

Abstract read
In one paragraph

Article in Frontiers in microbiology, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.

0numbers the graph read from it
0cells of the map it votes in
17citing 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

17 citing papers in PubMed.

  1. Review
  2. Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. Antibiotic Resistance: One Health One World Outlook.Frontiers in cellular and infection microbiology · 2021
    Review
  9. Quantifying the transmission of antimicrobial resistance at the human and livestock interface with genomics.Clinical microbiology and infection : the official publication of the European Society of Clinical Microbiology and Infectious Diseases · 2020
    Review
  10. Performance and Accuracy of Four Open-Source Tools forApplied and environmental microbiology · 2020
    Article
  11. Article
  12. Article
  13. Article
  14. Review
  15. Article
  16. Article
  17. 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

6 authors.

Emma GriffithsDepartment of Molecular Biology and Biochemistry, Simon Fraser University, VancouverBC, Canada.
Damion DooleyDepartment of Pathology and Laboratory Medicine, University of British Columbia, VancouverBC, Canada.
Morag GrahamNational Microbiology Laboratory, Public Health Agency of Canada, WinnipegMB, Canada.
Gary Van DomselaarNational Microbiology Laboratory, Public Health Agency of Canada, WinnipegMB, Canada.
Fiona S L BrinkmanDepartment of Molecular Biology and Biochemistry, Simon Fraser University, VancouverBC, Canada.
William W L HsiaoDepartment of Pathology and Laboratory Medicine, University of British Columbia, VancouverBC, Canada.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Globalization of food networks increases opportunities for the spread of foodborne pathogens beyond borders and jurisdictions. High resolution whole-genome sequencing (WGS) subtyping of pathogens promises to vastly improve our ability to track and control foodborne disease, but to do so it must be combined with epidemiological, clinical, laboratory and other health care data (called "contextual data") to be meaningfully interpreted for regulatory and health interventions, outbreak investigation, and risk assessment. However, current multi-jurisdictional pathogen surveillance and investigation efforts are complicated by time-consuming data re-entry, curation and integration of contextual information owing to a lack of interoperable standards and inconsistent reporting. A solution to these challenges is the use of 'ontologies' - hierarchies of well-defined and standardized vocabularies interconnected by logical relationships. Terms are specified by universal IDs enabling integration into highly regulated areas and multi-sector sharing (e.g., food and water microbiology with the veterinary sector). Institution-specific terms can be mapped to a given standard at different levels of granularity, maximizing comparability of contextual information according to jurisdictional policies. Fit-for-purpose ontologies provide contextual information with the auditability required for food safety laboratory accreditation. Our research efforts include the development of a Genomic Epidemiology Ontology (GenEpiO), and Food Ontology (FoodOn) that harmonize important laboratory, clinical and epidemiological data fields, as well as existing food resources. These efforts are supported by a global consortium of researchers and stakeholders worldwide. Since foodborne diseases do not respect international borders, uptake of such vocabularies will be crucial for multi-jurisdictional interpretation of WGS results and data sharing.

Indexed as

contextual metadatafoodborne pathogen surveillancegenomic epidemiologyontologyoutbreak investigations

Identifiers

PMID28694792
PMCPMC5483436

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.