An economic evaluation of the Whole Genome Sequencing source tracking program in the U.S.

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.

A Series of Papaya-Associated Salmonella Illness Outbreak Investigations in 2017 and 2019: A Focus on Traceback, Laboratory, and Collaborative Efforts.

ABSTRACT: In 2017 and 2019, five outbreaks of infections from multiple strains of Salmonella linked to the consumption of whole, fresh Maradol papayas were reported in the United States, resulting in 325 ill persons. Traceback, laboratory, and epidemiologic evidence indicated papayas as the likely vehicle for each of these outbreaks and identified the source of papayas. State and U.S. Food and Drug Administration (FDA) laboratories recovered Salmonella from papaya samples from various points of distribution, including at import entry, and conducted serotyping, pulsed-field gel electrophoresis, and phylogenetic analyses of whole genome sequencing data. Federal and state partners led traceback investigations to determine the source of papayas. Four different suppliers of papayas were linked by traceback and laboratory results to five separate outbreaks of Salmonella infections associated with papayas. In 2017, multiple states tested papaya samples collected at retail, and Maryland and Virginia investigators recovered strains of Salmonella associated with one outbreak. FDA collected 183 papaya samples in 2017, and 11 samples yielded 62 isolates of Salmonella. Eleven serotypes of Salmonella were recovered from FDA papaya samples, and nine serotypes were closely related genetically by pulsed-field gel electrophoresis and whole genome sequencing to clinical isolates of four outbreaks, including the outbreak associated with positive state sample results. Four farms in Mexico were identified, and their names were released to the general public, retailers, and foreign authorities. In 2019, FDA collected 119 papaya samples, three of which yielded Salmonella; none yielded the 2019 outbreak strain. Investigators determined that papayas of interest had been sourced from a single farm in Campeche, Mexico, through traceback. This information was used to protect public health through public guidance, recalls, and import alerts and helped FDA collaborate with Mexican regulatory partners to enhance the food safety requirements for papayas imported from Mexico.

Whole Genome and Core Genome Multilocus Sequence Typing and Single Nucleotide Polymorphism Analyses of Listeria monocytogenes Isolates Associated with an Outbreak Linked to Cheese, United States, 2013.

Epidemiological findings of a listeriosis outbreak in 2013 implicated Hispanic-style cheese produced by company A, and pulsed-field gel electrophoresis (PFGE) and whole genome sequencing (WGS) were performed on clinical isolates and representative isolates collected from company A cheese and environmental samples during the investigation. The results strengthened the evidence for cheese as the vehicle. Surveillance sampling and WGS 3 months later revealed that the equipment purchased by company B from company A yielded an environmental isolate highly similar to all outbreak isolates. The whole genome and core genome multilocus sequence typing and single nucleotide polymorphism (SNP) analyses results were compared to demonstrate the maximum discriminatory power obtained by using multiple analyses, which were needed to differentiate outbreak-associated isolates from a PFGE-indistinguishable isolate collected in a nonimplicated food source in 2012. This unrelated isolate differed from the outbreak isolates by only 7 to 14 SNPs, and as a result, the minimum spanning tree from the whole genome analyses and certain variant calling approach and phylogenetic algorithm for core genome-based analyses could not provide differentiation between unrelated isolates. Our data also suggest that SNP/allele counts should always be combined with WGS clustering analysis generated by phylogenetically meaningful algorithms on a sufficient number of isolates, and the SNP/allele threshold alone does not provide sufficient evidence to delineate an outbreak. The putative prophages were conserved across all the outbreak isolates. All outbreak isolates belonged to clonal complex 5 and serotype 1/2b and had an identical inlA sequence which did not have premature stop codons.IMPORTANCE In this outbreak, multiple analytical approaches were used for maximum discriminatory power. A PFGE-matched, epidemiologically unrelated isolate had high genetic similarity to the outbreak-associated isolates, with as few as 7 SNP differences. Therefore, the SNP/allele threshold should not be used as the only evidence to define the scope of an outbreak. It is critical that the SNP/allele counts be complemented by WGS clustering analysis generated by phylogenetically meaningful algorithms to distinguish outbreak-associated isolates from epidemiologically unrelated isolates. Careful selection of a variant calling approach and phylogenetic algorithm is critical for core-genome-based analyses. The whole-genome-based analyses were able to construct the highly resolved phylogeny needed to support the findings of the outbreak investigation. Ultimately, epidemiologic evidence and multiple WGS analyses should be combined to increase confidence levels during outbreak investigations.