Society For Risk Analysis Annual Meeting 2017

Session Schedule & Abstracts


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Common abbreviations

M3-H
Evaluating the Impact of Risk Factors and Control Measures: From Drinking Water to Produce and Nuts

Room: Salon J   1:30 pm–3:00 pm

Chair(s): Jane Van Doren, Hao Pang   Jane.VanDoren@fda.hhs.gov

Sponsored by Microbial Risk Analysis Specialty Group



M3-H.1  1:30 pm  Risk of Pre-Harvest Microbiological Contamination in Tomatoes: Effects of Meteorological, Farm Management, and Environmental Factors. Pang H*, Pradhan AK; University of Maryland   panghhao@gmail.com

Abstract: Tomatoes have been linked to several foodborne disease outbreaks in recent years and the source of contamination has been traced back to tomato farms. This study sought to identify and evaluate meteorological, environmental, and farm management factors affecting microbial contamination risk in tomato fruits and in tomato production environments at the pre-harvest level. Tomato (n = 259), irrigation water (n = 72), and field soil (n = 45) samples were collected from 24 farms located in Maryland, Delaware, and New Jersey. Local meteorological information (temperature and precipitation) during the study period were collected from National Climatic Data Center. Farm level environmental factors and management practices were acquired through questionnaires answered by farmers. These factors were evaluated for their association with aerobic plate count (APC), total coliform (TC) count, and presence of generic E. coli in tomato, irrigation water, and field soil samples. For tomato samples, prevalence of E. coli was significantly reduced by the use of potable water for cleaning, chemical application, and hand washing; however, prevalence of E. coli increased with increasing of precipitation on sampling day. In addition, higher TC counts occurred in tomatoes from farms exposed to higher average temperature and higher average precipitation over the previous 10 days before sampling. In irrigation water samples, presence of E. coli increased with increasing average temperature over the previous 25 days before sampling day. In addition, increasing precipitation over the previous 30 days before sampling increased the count of APC and TC in irrigation water samples. These results indicate that microbial contamination at tomato pre-harvest level can be influenced by certain meteorological conditions, environmental factors, and farm management practices. Our study provides information that will assist growers in evaluating farm management and preventive measures to reduce the risk of pre-harvest contamination in tomatoes.

M3-H.2  1:50 pm  The impact of a microbial reduction treatment on the risk of human salmonellosis from the consumption of almonds and pecans in the United States: A comparison. Santillana Farakos SM*, Pouillot R, Davidson GR, Johnson R, Spungen J, Son I, Anderson NA, Van Doren J; Food and Drug Administration   sofia.santillanafarakos@fda.hhs.gov

Abstract: We developed quantitative risk assessments to assess the risk of human salmonellosis arising from the consumption of almonds and, separately, pecans, after the application of a microbial reduction treatment level (1-5 log CFU). These include exposure models evaluating contamination at harvest and including various steps in tree nut processing such as pre-treatment storage, post-treatment partitioning, and post-treatment and retail storage. Steps specific to each tree nut, such as pecan processing immersion in water, drying, conditioning, and cracking were included. U.S. consumption data and the WHO/FAO Salmonella dose-response model were used to assess the risk per serving and per year, quantifying variability and uncertainty separately. The model predicted a mean risk of salmonellosis from consumption of almonds and almond products (>80% almond) in the U.S. with no microbial reduction treatment and no further cooking by the consumer as 1,697 cases/year (95% CI: 1,162– 3,501 cases). For pecans and pecan products (>80% pecan), the mean estimated number of cases/year under a cold conditioning process with no microbial reduction treatment and no further consumer cooking was estimated as 529 cases (95%CI: 213 – 2,295 cases). Assuming 77% of shelled pecans sold at retail receive hot conditioning (industry estimate), the mean estimated cases/year from consumption of in-shell and shelled pecans uncooked at home combined is 203 cases (95%CI: 81 - 882 cases) when no additional microbial reduction treatment is applied. In spite of differences in initial contamination, survival, processing steps, and consumption, the models for both almonds and pecans estimate that a minimum 4 log reduction treatment results in a mean risk of illness below one case/year in the U.S., including uncertainty, assuming typical conditions. Atypical situations that may occur post-treatment (e.g., cross contamination) could result in higher risk estimates that are not impacted by treatment level.

M3-H.3  2:10 pm  An Advanced Legionellosis Risk Model Incorporating Epidemiological Evidence of Disease Burden. Weir MH*, Mraz AL, Mitchell J; The Ohio State University   weirmarkh@gmail.com

Abstract: The overall disease burden of Legionellosis in the United States has been increasing in the past decade. This increase in national disease burden has made Legionella pneumophila (L. pneumophila) the leading waterborne etiological agent in the United States. Legionellosis is a disease outcome that incorporates two specific diseases, first is Pontiac Fever, a self-limiting febrile illness, and Legionnaire’s Disease, a potential lethal pulmonary disease. This research desired to account for more realistic water use patterns in showering, effects of flow rate on aerosol size, breathing rates of the population, and rates of disease incidence in the United States. The incorporation of these factors has developed a microbial risk model with the potential for higher accuracy and resolution to the population. Additionally, as the disease burden data were reported using age, sex and racial demographics, these demographics were modeled as well. The risks were modeled as daily risk of infection and illness, annual risk of infection and illness, moderate illness DALY, severe illness DALY and post-acute illness DALY. This research postulates three methods. First, that the method of incorporating incidence rate to model probability of illness given infection allows for a means of modeling this probability of illness given infection for specific populations. Second, that higher disease risk estimate resolution can be provided to use moderate DALY for Pontiac Fever, severe DALY for Legionnaire’s Disease and post-acute DALY for consequences of illness later in life. Third, a more accurate model of L. pneumophila exposure and pathogenesis develops a more accurate risk model. This model allows for the first steps in a deeper understanding of the population level risk of Legionellosis in the United States’ drinking water systems.

M3-H.4  2:30 pm  Development of a mathematical model for the influence of relative humidity on the survival of Salmonella on cucumbers. Jung J*, Schaffner DW; Rutgers University   jiin.jung@rutgers.edu

Abstract: Fresh cucumbers have recently been recognized as a vehicle in foodborne disease outbreaks, but little is known about the environmental factors that influence the survival of Salmonella on cucumbers. The objective of this study was to develop and validate a mathematical model that predicts the survival of Salmonella on cucumbers at different relative humidity conditions. Fresh cucumbers were spot inoculated with a four-strain cocktail of Salmonella enterica. Inoculated cucumbers were dried for two hours and placed in desiccators containing saturated salt (lithium chloride, potassium carbonate, and potassium sulfate) used to create controlled RH environments (~15, 50, 100 % RH) at 21 °C. Samples were enumerated at appropriate time intervals ranging from 0 to 72 h. Cucumber weights were recorded, and the percentage weight loss was calculated. DMfit was used to model the survival of Salmonella from experimental observations fitting the data to the Baranyi model. Predictive models for the survival of Salmonella on cucumbers under different RH conditions were developed using Baranyi and Roberts models as a primary model. The R2 values for the primary models ranged from 0.70 to 0.85 indicating relatively good fit. Salmonella populations on cucumbers decreased by approximately 0.88, 0.41, and 0.33 log CFU/cucumber after 72h at 15, 50, and 100 % RH, respectively. Overall visual quality of cucumber declined over time and weight loss from cucumbers increased. Weight loss of cucumbers was significantly highest at 15 (15.3 %), followed by 50 (11.5 %) and 100 % RH (2.8 %) at the end of 72h (p < 0.001). Although further research is needed to develop secondary models for survival of microorganism on cucumbers under varying storage time, temperature, and relative humidity, the models in this study will be useful for future microbial risk assessments to develop accurate risk analysis for food borne outbreaks related to fresh produce.



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