Society For Risk Analysis Annual Meeting 2017

Session Schedule & Abstracts


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Common abbreviations

T3-H
Modeling Transmission of Microbial Contaminants in Poultry, Meat and Beyond

Room: Salon J   1:30 pm–3:00 pm

Chair(s): Moez Sanaa, Abhinav Mishra   moez.sanaa@anses.fr

Sponsored by Microbial Risk Analysis Specialty Group



T3-H.1  1:30 pm  Cross-contamination of Broiler Chickens with Campylobacter During Transport. Otten A*, Ernst N, Ng V, Smith B.A, Fazil A; Public Health Agency of Canada   ainsley.otten@phac-aspc.gc.ca

Abstract: Campylobacter frequently colonizes the intestines of broiler chickens on farm. Cross-contamination to the exterior of birds creates risk to consumers, as the cells of Campylobacter can persist through processing and are routinely present on retail products. Ingestion of Campylobacter by consumers can cause gastroenteritis and potentially serious sequelae. The role of cross-contamination during broiler transport has not been extensively modelled, and due to complexities of the system is often not included in QMRAs concerning Campylobacter on poultry. An agent-based model was developed with AnyLogic software to study how broiler chicken Campylobacter contamination may change during transport from farm to slaughterhouse. Contamination may be present or introduced in the truck from: a) transport crates which were not properly sanitized prior to loading; b) the exterior of incoming birds; and c) colonized birds who defecate during transport. Each bird is represented as an individual agent within the model and the colonization status and exterior contamination level is simulated and recorded. Contamination may be passed within and among crates through bird and fomite contact. Additionally, colonized chickens may soil broilers below or beside them with fecal material. Outputs include the final number of birds with exterior contamination and the respective concentration of Campylobacter. Scenario analysis allows transport interventions such as limited inter-crate transfer, logistic loading and reduced transport time to be evaluated. Results will be implemented in a Canadian farm-to-fork QMRA of Campylobacter in chicken products sold at retail to examine mitigation strategies that can be employed to reduce the risk of campylobacteriosis in Canada.

T3-H.2  1:50 pm  Ordinal QMRA to prioritize pork products that may contribute to foodborne hepatitis E virus transmission. Bouwknegt M*, van 't Hooft BJ, Koppen K, Rietveld H, Straatsma G, Heres L; Vion, Boxtel, the Netherlands; Stegeman, Deventer, the Netherlands; Dutch Meat Products Association, Zoetermeer, the Netherlands; Zwanenberg, Almelo, the Netherlands; Sonac, Son, the Netherlands   martijn.bouwknegt@vionfood.com

Abstract: Hepatitis E virus (HEV) is an opportunistic zoonotic virus that can cause liver inflammation especially in transplant recipients, immunocompromised people and those with underlying disease. The majority of exposed individuals develop no clinical symptoms. Reported case numbers rose in several European countries recently. Domestic pigs, wild boar and deer are local reservoirs for HEV and suspected transmission routes to humans include environmental, direct contact and foodborne transmission. We, as meat industry, therefore initiated a prioritization of food groups for the contribution to foodborne HEV transmission, to develop intervention measures when needed. Seven food groups were considered: fresh meat, porcine liver (whole), liver sausage, raw meat products, cooked meat products, fermented products and blood sausage. A quantitative microbiological risk assessment model was developed to compare exposure doses among food groups. As data scarcity made characterization of parameter distributions and the generation of absolute risk estimates impossible, parameters were quantified as ordinal, order-of-magnitude levels, analogous to a multi-criteria decision analysis approach. Preliminary results showed that of the two sources of HEV-introduction in meat, i.e. blood and liver, the contribution of blood was negligible. The model is now being completed for the remaining parameters and the full prioritization will be completed in the summer of 2017. The results will be presented to the members of the Dutch Meat Products Association, comprising the major companies in meat production, in September. The effectivity of feasible intervention measures will be estimated with the model and proposed to the industry. Furthermore, results will be compared to other ongoing studies to estimate which part of all human cases can be attributed to meat in comparison to other possible transmission routes and other food products.

T3-H.3  2:10 pm  Risk Assessment for Transfusion Transmission of Dengue. Huang Y*, Lane C, Rios M, Fares-Gusmao R, Chancey C, Forshee R, Yang H; Food and Drug Administration   Yin.Huang@fda.hhs.gov

Abstract: Dengue viruses (DENVs) are known to be transmitted from person to person through the bite of an infected mosquito. Cases of dengue after receipt of blood products or donor organs or tissue have been also reported. We developed a quantitative risk assessment model to estimate the dengue risk from pre-clinical (during incubation period) and subclinical (infected but never showing symptoms) blood donors. We derived predictive coefficients from model simulations for predicting the risk outcomes such as monthly infectious blood units and transfusion-transmitted dengue (TT-DENV) cases based on the rate of reported clinical cases. The model was validated with a previous study where donor blood samples from the 2012 dengue transmission season in Rio de Janeiro, Brazil were tested for DENV RNA by a transcription-mediated amplification (TMA) assay. In that study about 69.4% donations were tested by the TMA assay and 78 samples were found positive during March, April and May, the peak period of the outbreak, indicating that 112 DENV RNA-positive donations would have been detected if testing screening had been performed on all donations. Our model estimated a mean of 93 (2.5th%ile-97.5th%ile: 47 - 186) infected units among the donations, which was consistent with the reported numbers. We applied the model to estimate the risk in the US. For year 2013, 2014, 2015 and 2016, based on the annual reported dengue cases of 543, 470, 751 and 764, respectively, a mean of 2, 1, 2 and 2 annual TT-DENV infections were estimated.

T3-H.4  2:30 pm  Assessing the impact of different microbiological criteria for Salmonella in raw poultry products. Lambertini E*, Kowalcyk BB, Ruzante JM; RTI International   elambertini@rti.org

Abstract: Contamination of not-ready-to-eat poultry products with Salmonella has been responsible for numerous foodborne illness outbreaks and recalls. In the U.S., despite initiatives to improve the safety of poultry products, progress has stalled and public health agencies have reported little to no improvement in recent years. Currently, poultry products performance standards for Salmonella and Campylobacter are implemented to identify and incrementally correct contamination issues at production plant level, thus reducing the risk of consumer exposure. Such standards are based on presence/absence pathogen detection. Different strategies have been discussed to identify and classify contamination at lot and plant level, based on detection methods ranging from qualitative to fully quantitative. However, production and public health impacts of such strategies have not been evaluated. This study sought to: 1) quantitatively assess the product management and public health impacts of a range of microbiological criteria to determine lot acceptability, in association with a hypothetical “test and divert” Salmonella control strategy in chicken parts, 2) compare the impact of a microbial criterion on different chicken part products, and 3) compare “test and divert” risk reduction strategies to non-divert strategies based on “continuous improvement” feedback driven by microbial criteria testing results. A probabilistic quantitative risk model was developed to describe relevant portions of a typical U.S. production chain for chicken parts, including consumer handling. Distributions of model variables and parameters were derived from microbial surveys, federal inspection data, and published literature. Model outcomes were expressed in terms of product contamination, percent of lots not meeting a criterion, and public health burden. Outcomes are expected to inform industry practices and provide a basis for future standard updates.



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