Updates to the food categorization scheme and new methods for assigning implicated foods to specific food categories can help increase the number of outbreaks attributed to a single food category. The increased specificity of food categories in this scheme may help improve source attribution analyses, eventually leading to improved foodborne illness source attribution estimates and enhanced food safety and regulatory efforts.

The U.S. Food and Drug Administration (FDA) created the GenomeTrakr Whole Genome Sequencing (WGS) Network in 2013, as a tool to improve food safety. This study presents an analysis of Whole Genome source tracking implementation on potential food contamination and related illnesses through theoretical, empirical, and cost benefit analyses. We conduct empirical tests using data from FDA regulated food commodity outbreaks garnering FDA response from 1999 through 2019 and examine the effect of the National Center for Biotechnology Information (NCBI) Pathogen detection program of source tracking WGS isolates collected in the U.S. on outbreak illnesses for three pilot pathogens (E. coli, Listeria, and Salmonella). Empirical results are consistent with the theoretical model and suggest that each additional 1,000 WGS isolates added to the public NCBI database is associated with a reduction of approximately 6 illnesses per WGS pathogen, per year. Empirical results are connected to existing literature for a Monte Carlo analysis to estimate benefits and costs. By 2019, annual health benefits are estimated at nearly $500 million, compared to an approximately $22 million investment by public health agencies. Even under conservative assumptions, the program likely broke even in its second year of implementation and could produce increasing public health benefits as the GenomeTrakr network matures.

This multi-agency report developed under the Interagency Collaboration for Genomics for Food and Feed Safety (Gen-FS) provides an overview of the use of and transition to Whole-Genome Sequencing (WGS) technology to detect and characterize pathogens transmitted commonly by food and identify their sources. We describe foodborne pathogen analysis, investigation, and harmonization efforts among federal agencies, including the National Institutes of Health (NIH); the Department of Health and Human Services’ Centers for Disease Control and Prevention (CDC) and the Food and Drug Administration (FDA); and the U.S. Department of Agriculture’s Food Safety and Inspection Service (FSIS), Agricultural Research Service (ARS), and Animal and Plant Health Inspection Service (APHIS). We describe single nucleotide polymorphism (SNP), core-genome (cg) and whole-genome multi-locus sequence typing (wgMLST) data analysis methods as used in CDC’s PulseNet and FDA’s GenomeTrakr networks, underscoring the complementary nature of the results for linking genetically related foodborne pathogens during outbreak investigations while allowing flexibility to meet the specific needs of Gen-FS agency partners. We highlight how we apply WGS to pathogen characterization (virulence and antimicrobial resistance profiles), source attribution efforts, and increasing transparency by making the sequences and other data publicly available through the National Center for Biotechnology Information (NCBI). Finally, we highlight the impact of current trends in the use of culture-independent diagnostics tests (CIDT) for human diagnostic testing on analytical approaches related to food safety. Lastly, we highlight what is next for WGS in food safety.