Society For Risk Analysis Annual Meeting 2017

Session Schedule & Abstracts


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Common abbreviations

M2-H
Listeria in the Food Supply Chain: Incidence and Control Measures

Room: Salon J   10:30 am–12:00 pm

Chair(s): Moez Sanaa, Amir Mokhtari   moez.sanaa@anses.fr

Sponsored by Microbial Risk Analysis Specialty Group



M2-H.1  10:30 am  Listeria monocytogenes in ready-to-eat (RTE) foods and the risk for human health in the European Union (EU). Sanaa M*; Anses   moez.sanaa@anses.fr

Abstract: In order to address the identified factors/hypothesis explaining the increase of human listeriosis incidence in the EU/EEA a quantitative risk assessment model was developed based on the available data in EU. The model predicts consumer exposure based on the initial contamination level at retail of a variety of RTE foods, and the potential growth before consumption. The consumer probability of being infected and getting listeriosis is then predicted by applying a dose-response (DR) relation model. Fourteen subpopulations defined by age and gender were considered when assessing exposure and DR models. A suitable model structure integrating exposure and DR models were applied in order to assess the impact of different factors on the public health risks from consumption of various RTE food categories contaminated with L. monocytogenes. The model include variability and uncertainty. It was built in such a way that it avoids the recurring problem of convergence when Monte Carlo techniques are used.

M2-H.2  10:50 am  Listeria incidence and exposure: Assessing the impacts of changing US population demographics and differing consumption patterns among groups at higher risk for listeriosis. Pohl AM*, Gaveleck AY, Spungen JH, Pouillot R, Van Doren JM; US Food and Drug Administration   aurelie.pohl@fda.hhs.gov

Abstract: Listeriosis is an important foodborne illness with incidence rates that vary significantly among US population subgroups with pregnant women, older adults, and the Hispanic population having increased relative risks. Using FoodNet data, we evaluated the predicted number of cases and incidence rates of listeriosis over time, as the proportions of elderly and Hispanic individuals increase. If the incidence rate per subpopulation is held constant, the overall US population listeriosis incidence rate would increase from 0.25 per 100,000 (95%CI: 0.19-0.34) in 2010, to 0.28 (95%CI: 0.22-0.38) in 2020 and 0.32 (95%CI: 0.25-0.43) in 2030, because of the expected changes in the population structure. Likewise, the pregnancy-associated incidence rate would increase from 4.0 per 100,000 pregnant women (95%CI: 2.5-6.5) in 2010, to 4.1 (95%CI: 2.6-6.7) in 2020 and 4.4 (95%CI: 2.7-7.2) in 2030 as the proportion of Hispanic pregnant women increases. An important question is why incidence rates differ between the Hispanic and non-Hispanic populations. One possible explanation is differing exposure due to consumption patterns among these groups. Data on consumption patterns among the higher and lower risk sub-populations was obtained from the National Health and Nutrition Examination Survey (NHANES) for the years 2003-2014 and compared for selected food categories that have been associated with listeriosis. Comparisons were made among the Hispanic and non-Hispanic subpopulations including pregnant and non-pregnant women of childbearing age (20-44 years). Consumption by older adults (60-69, 70-79 and 80+ years) was also compared with that of younger adults. A number of significant differences (p-value <0.05) in consumption frequency were identified among these sub-groups. For example, among dairy products, significant differences in consumption frequency were found for fluid milk, yogurt, fresh soft cheese, ripened soft cheese and hard cheese among some of these subgroups.

M2-H.3  11:10 am  A novel agent-based model of Listeria spp. dynamics in a food processing facility for assessment of environmental monitoring programs. Zoellner C*, Jennings R, Wiedmann M, Ivanek R; Cornell University   cez23@cornell.edu

Abstract: To reduce the risk of foodborne listeriosis, food manufacturers conduct routine sampling of equipment, personnel and facilities as part of environmental monitoring (EM) and corrective action programs. Our objective was to model the hourly dynamics of Listeria in a cold-smoked salmon slicing room as an example of a food processing facility implementing EM strategies. Using agent-based modeling, the 3D environment of the slicing room was discretized into 625-cm^2 patches with spatially explicit autonomous entities (objects, employees and equipment) defined by rules and attributes central to the behavior of Listeria. Cleanability of equipment, presence of water, traffic patterns and introduction events to the slicing room were modeled. Relationships between entities based on physical proximity or interactions created the network upon which Listeria spread. Expert elicitation and extensive literature review methods were used in parameter estimation. Preliminary modeling results illustrated that without EM, the median prevalence of Listeria on food (FCS) and non-food contact surfaces (NFCS) would be 8.9% (5th and 95th percentile: 8.5-9.5) and 3.2% (3.0-3.3), respectively, with most FCS and NFCS (98% and 99%, resp.) containing ≤ 10 CFU/cm^2. The median prevalence of Listeria on the floor was 1.9% (1.7-2.1). The median prevalence of Listeria in smoked salmon fillets entering the slicing room was 0.10% (0.09-0.11). FCS and NCFS prevalence were strongly correlated with cross-contamination events and employee contacts with FCS (p < 0.001). FCS prevalence was also correlated with contaminated smoked salmon fillet prevalence (p < 0.05). Eliminating incoming fillet contamination to the slicing room reduced FCS and NFCS median prevalence to 3.6% (2.7-4.9) and 1.8% (1.4-2.3), respectively. Methods and results presented are intended to be useful in customizing models to food production facilities for evaluation of different EM schemes and interventions on prevalence of Listeria.

M2-H.4  11:30 am  Interagency Listeria monocytogenes Market Basket Survey – results and critical considerations for developing surveys to support quantitative risk assessments. Chen Y*, Pouillot R, Luchansky JB, Porto-Fett ACS, Catlin M, Kause J, Gallagher D, Van Doren JM, Lindsay JA, Dennis S; FDA Center for Food Safety and Applied Nutrition, USDA Agricultural Research Service, Virginia Polytechnic Institute and State University, and USDA Food Safety and Inspection Service   yuhuan.chen@fda.hhs.gov

Abstract: An interagency Listeria monocytogenes Market Basket Survey (Lm MBS) was conducted 2010-2013 for 16 categories of ready-to-eat foods purchased at retail in four U.S. FoodNet states. The study collection and microbial analysis protocols were designed to maximize their utility to assess the current status and potential changes in L. monocytogenes prevalence and levels in the selected foods that could have resulted from regulatory and industry interventions over the previous decade. Published L. monocytogenes surveys often focused on the proportion of positive samples, but few reported metadata or how metadata were considered in analyzing results. The Lm MBS took a structured pragmatic approach based on stratification by predictors with the greatest anticipated impact on reducing uncertainty, and collection of multiple samples per food category from the same store for efficiency (total 27,389 samples from 1042 stores). This approach required planning and recording appropriate metadata, such as the food types within each category, the FoodNet sites, the retail store identification number, the type of store (e.g., national chain vs. independent), and packaging location (prepackaged vs. deli-packaged). The target number of samples required careful review of historical data. Analytical sample size, which varies from study to study (e.g., 25g and 125g), was also considered to allow comparison of results from different surveys. With the metadata and microbial testing data from the Lm MBS, generalized linear mixed models, with consideration of sampling stratification and potential clustering effects with regard to stores and states, determined that prevalence ranged from 0.11% [95%CI:0.03,0.34] for sprouts (pre-packaged) to 1.01% [95%CI:0.58,1.74] for raw cut vegetables (pre-packaged). Developing, documenting, and analyzing survey data in this way allows direct comparison to other studies, even when the study design is different, as long as the design has been specified.



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