Maximizing the Potential of Whole Genome Sequencing in Listeriosis Outbreak Investigations

Key Objectives:

1. Review the use and interpretation of whole genome sequencing (WGS) data in recent listeriosis investigations
2. Discuss the evolving role of epidemiology in the era of WGS-based surveillance
3. Discuss experiences with Listeria WGS from state, territorial, and local epidemiology and environmental health perspectives
4. Discuss preferred means for epidemiologists to access Listeria WGS data
5. Identify training needs for epidemiologists to understand and use Listeria WGS data

Brief Summary:
The incidence of Listeria monocytogenes infections, the third leading cause of death from foodborne illness in the United States, has not declined in over a decade. Whole genome sequencing (WGS), which provides far greater resolution than pulsed-field gel electrophoresis, is a powerful technology that has the potential to transform enteric disease surveillance and help reduce the burden of listeriosis. Since September 2013, all L. monocytogenesstrains isolated from clinical, food, and environmental sources have been sequenced in as close to real time as possible. WGS improves cluster detection and investigation by refining case definitions, helping to exclude less-related isolates that are indistinguishable by pulsed-field gel electrophoresis (PFGE) and to include related isolates that differ by PFGE. Since September 2013, WGS data helped solve five multistate listeriosis outbreaks and link one sporadic illness to a contaminated food. Linking illnesses to food sources helps identify important food safety gaps. By reducing misclassification (ie, helping to exclude some isolates and include others), WGS increases the significance of small disease clusters and increases the importance of food or environmental isolates for generating hypotheses. During 2014, the median cluster size was only 4 cases at time of detection. WGS of isolates from recalled products and human specimens helped suggest linkages in three instances that were later supported by exposure information. However, the quality of exposure data continues to be a limiting step for investigations, especially for smaller disease clusters and those clusters without WGS-linked food or environmental information. As WGS-based laboratory surveillance expands beyond L. monocytogenes to other pathogens, epidemiologists must be able to readily access and interpret WGS data. Feedback to CDC from state, territorial, and local epidemiologists regarding successes, challenges, and barriers regarding use of WGS data is needed to make the most of this technology.