Program Schedule

Improving Detection and Investigation of Listeriosis Outbreaks Using Real-Time Whole-Genome Sequencing

Session: Oral Abstract Session: Epidemiology and Prevention of Infectious Diseases
Saturday, October 11, 2014: 10:45 AM
Room: The Pennsylvania Convention Center: 111-AB
Background: Listeriosis is estimated to be the third leading cause of death from foodborne illness in the United States. Despite intensive efforts, the incidence has not declined since 2001. Solved outbreaks identify food safety gaps. Since September 2013, we used real-time whole-genome sequencing (WGS) of US clinical, food, and environmental Listeria monocytogenes isolates to enhance surveillance.

Methods: Beginning September 1, 2013, CDC, state and local public health laboratories, FDA, and USDA in collaboration with NIH performed WGS on all human isolates received through public health surveillance and available food and environmental isolates of L. monocytogenes, including those detected through routine sampling of ready-to-eat foods. Clusters were detected through PulseNet, the national molecular subtyping network for foodborne bacterial disease surveillance, using pulsed-field gel electrophoresis (PFGE) patterns and through WGS analysis. State and local health departments collected food exposure data from patients. We compared the number of listeriosis clusters detected and solved from September 1, 2012–April 1, 2013 (pre-WGS period) with the number of clusters detected and solved from September 1, 2013–April 1, 2014 (WGS pilot period).

Results: Seven listeriosis clusters were detected (median size 6 cases) and none were solved during the pre-WGS period compared with 12 clusters detected (median size 5) and 1 solved in the WGS pilot period; the solved outbreak resulted in a recall of contaminated food. In the pilot period, 1 cluster was identified by PFGE only, 4 by WGS only, and 7 by both; when isolates in the cluster identified by PFGE only were found to not be highly related by WGS, investigation stopped. Two-thirds of cases lacked food exposure data at the time of cluster identification, limiting investigations.

Conclusion: This project represents the first use of real-time WGS-enhanced surveillance; it increased the number of listeriosis clusters detected and detected smaller clusters. The discriminatory power of WGS resulted in discontinuation of a cluster investigation, saving public health resources. WGS is a promising tool for surveillance; more complete and timely epidemiologic data are needed to complement this advanced technique.

Brendan Jackson, MD, MPH1, Kelly Jackson, MPH1, Cheryl Tarr, PhD1, Peter Evans, PhD, MPH2, William Klimke, PhD3, Kristy Kubota, MPH4, Zuzana Kucerova, MD, PhD1, Lee Katz, PhD1, Eija Trees, PhD, DVM1, Heather Carleton, PhD1, Steven Stroika, BS1, Amanda Conrad, MPH1, John Besser, PhD1, Peter Gerner-Smidt, MD, PhD1 and Rajal Mody, MD, MPH1, (1)Centers for Disease Control and Prevention, Atlanta, GA, (2)Food and Drug Administration, College Park, MD, (3)National Institutes of Health, Bethesda, MD, (4)Association of Public Health Laboratories, Silver Spring, MD


B. Jackson, None

K. Jackson, None

C. Tarr, None

P. Evans, None

W. Klimke, None

K. Kubota, None

Z. Kucerova, None

L. Katz, None

E. Trees, None

H. Carleton, None

S. Stroika, None

A. Conrad, None

J. Besser, None

P. Gerner-Smidt, None

R. Mody, None

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