Towards an integrated food safety surveillance system: a simulation study to explore the potential of combining genomic and epidemiological metadata.

ABSTRACT: Foodborne infection is a result of exposure to complex, dynamic food systems. The efficiency of foodborne infection is driven by ongoing shifts in genetic machinery. Next-generation sequencing technologies can provide high-fidelity data about the genetics of a pathogen. However, food safety surveillance systems do not currently provide similar high-fidelity epidemiological metadata to associate with genetic data. As a consequence, it is rarely possible to transform genetic data into actionable knowledge that can be used to genuinely inform risk assessment or prevent outbreaks. Big data approaches are touted as a revolution in decision support, and pose a potentially attractive method for closing the gap between the fidelity of genetic and epidemiological metadata for food safety surveillan

SUBMITTER: Hill AA 

PROVIDER: S-EPMC5383817 | biostudies-literature | 2017 Mar

REPOSITORIES: biostudies-literature