Robert L. Buchanan

Use of Epidemiologic and Food Survey Data To Estimate a Purposefully Conservative Dose-Response Relationship for Listeria monocytogenes Levels and Incidence of Listeriosis†

The development of effective quantitative microbial risk-assessment models for foodborne pathogens depends on the availability of data on the consumers exposure to a biological agent and the dose-response relationship that relates levels of the biological agent ingested with frequency of infection or disease. Information on the latter has historically been acquired from human volunteer feeding studies. However, such studies are not feasible for pathogens that either have a significant risk of being life threatening or for which morbidity is primarily associated with high-risk populations (i.e., immunocompromised persons). For these pathogens, it is proposed that purposefully conservative dose-response relationships can be estimated on the basis of combining available epidemiologic data with food-survey data for a ready-to-eat product. As an example, data on the incidence of listeriosis in Germany were combined with data on the levels of Listeria monocytogenes in smoked fish to generate a dose-response curve for this foodborne pathogen.

The key events dose-response framework: its potential for application to foodborne pathogenic microorganisms.

The Key Events Dose-Response Framework (KEDRF) is an analytical approach that facilitates the use of currently available data to gain insight regarding dose-response relationships. The use of the KEDRF also helps identify critical knowledge gaps that once filled, will reduce reliance on assumptions. The present study considers how the KEDRF might be applied to pathogenic microorganisms, using fetal listeriosis resulting from maternal ingestion of food contaminated with L. monocytogenes as an initial example. Major biological events along the pathway between food ingestion and the endpoint of concern are systematically considered with regard to dose (i.e., number of organisms), pathogen factors (e.g., virulence), and protective host mechanisms (e.g., immune response or other homeostatic mechanisms). It is concluded that the KEDRF provides a useful structure for systematically evaluating the complex array of host and pathogen factors that influence the dose-response relationship. In particular, the KEDRF supports efforts to specify and quantify the sources of variability, a prerequisite to strengthening the scientific basis for food safety decision making.

Assessment of region, farming system, irrigation source and sampling time as food safety risk factors for tomatoes

In the mid-Atlantic region of the United States, small- and medium-sized farmers use varied farm management methods and water sources to produce tomatoes. It is unclear whether these practices affect the food safety risk for tomatoes. This study was conducted to determine the prevalence, and assess risk factors for Salmonella enterica, Shiga toxin-producing Escherichia coli (STEC) and bacterial indicators in pre-harvest tomatoes and their production areas. A total of 24 organic and conventional, small- to medium-sized farms were sampled for six weeks in Maryland (MD), Delaware (DE) and New Jersey (NJ) between July and September 2012, and analyzed for indicator bacteria, Salmonella and STEC. A total of 422 samples--tomato fruit, irrigation water, compost, field soil and pond sediment samples--were collected, 259 of which were tomato samples. A low level of Salmonella-specific invA and Shiga toxin genes (stx1 or stx2) were detected, but no Salmonella or STEC isolates were recovered. Of the 422 samples analyzed, 9.5% were positive for generic E. coli, found in 5.4% (n=259) of tomato fruits, 22.5% (n=102) of irrigation water, 8.9% (n=45) of soil, 3/9 of pond sediment and 0/7 of compost samples. For tomato fruit, farming system (organic versus conventional) was not a significant factor for levels of indicator bacteria. However, the total number of organic tomato samples positive for generic E. coli (1.6%; 2/129) was significantly lower than for conventional tomatoes (6.9% (9/130); (χ(2) (1)=4.60, p=0.032)). Region was a significant factor for levels of Total Coliforms (TC) (p=0.046), although differences were marginal, with western MD having the highest TC counts (2.6 log CFU/g) and NJ having the lowest (2.0 log CFU/g). Tomatoes touching the ground or plastic mulch harbored significantly higher levels of TC compared to vine tomatoes, signaling a potential risk factor. Source of irrigation water was a significant factor for all indicator bacteria (p<0.0001), and groundwater had lower bacterial levels than surface water. End of line surface water samples were not significantly different from source water samples, but end of line groundwater samples had significantly higher bacterial counts than source (p<0.0001), suggesting that Good Agricultural Practices that focus on irrigation line maintenance might be beneficial. In general, local effects other than cropping practices, including topography, land use and adjacent industries, might be important factors contributing to microbiological inputs on small- and medium-sized farms in the mid-Atlantic region.

The Growing Season, but Not the Farming System, Is a Food Safety Risk Determinant for Leafy Greens in the Mid-Atlantic Region of the United States

ABSTRACT Small- and medium-size farms in the mid-Atlantic region of the United States use varied agricultural practices to produce leafy greens during spring and fall, but the impact of preharvest practices on food safety risk remains unclear. To assess farm-level risk factors, bacterial indicators, Salmonella enterica, and Shiga toxin-producing Escherichia coli (STEC) from 32 organic and conventional farms were analyzed. A total of 577 leafy greens, irrigation water, compost, field soil, and pond sediment samples were collected. Salmonella was recovered from 2.2% of leafy greens (n = 369) and 7.7% of sediment (n = 13) samples. There was an association between Salmonella recovery and growing season (fall versus spring) (P = 0.006) but not farming system (organic or conventional) (P = 0.920) or region (P = 0.991). No STEC was isolated. In all, 10% of samples were positive for E. coli: 6% of leafy greens, 18% of irrigation water, 10% of soil, 38% of sediment, and 27% of compost samples. Farming system was not a significant factor for levels of E. coli or aerobic mesophiles on leafy greens but was a significant factor for total coliforms (TC) (P < 0.001), with higher counts from organic farm samples. Growing season was a factor for aerobic mesophiles on leafy greens (P = 0.004), with higher levels in fall than in spring. Water source was a factor for all indicator bacteria (P < 0.001), and end-of-line groundwater had marginally higher TC counts than source samples (P = 0.059). Overall, the data suggest that seasonal events, weather conditions, and proximity of compost piles might be important factors contributing to microbial contamination on farms growing leafy greens.

Quantitative assessment of human and pet exposure to Salmonella associated with dry pet foods.

Recent Salmonella outbreaks associated with dry pet foods and treats highlight the importance of these foods as previously overlooked exposure vehicles for both pets and humans. In the last decade efforts have been made to raise the safety of this class of products, for instance by upgrading production equipment, cleaning protocols, and finished product testing. However, no comprehensive or quantitative risk profile is available for pet foods, thus limiting the ability to establish safety standards and assess the effectiveness of current and proposed Salmonella control measures. This study sought to develop an ingredients-to-consumer quantitative microbial exposure assessment model to: 1) estimate pet and human exposure to Salmonella via dry pet food, and 2) assess the impact of industry and household-level mitigation strategies on exposure. Data on prevalence and concentration of Salmonella in pet food ingredients, production process parameters, bacterial ecology, and contact transfer in the household were obtained through literature review, industry data, and targeted research. A probabilistic Monte Carlo modeling framework was developed to simulate the production process and basic household exposure routes. Under the range of assumptions adopted in this model, human exposure due to handling pet food is null to minimal if contamination occurs exclusively before extrusion. Exposure increases considerably if recontamination occurs post-extrusion during coating with fat, although mean ingested doses remain modest even at high fat contamination levels, due to the low percent of fat in the finished product. Exposure is highly variable, with the distribution of doses ingested by adult pet owners spanning 3Log CFU per exposure event. Child exposure due to ingestion of 1g of pet food leads to significantly higher doses than adult doses associated with handling the food. Recontamination after extrusion and coating, e.g., via dust or equipment surfaces, may also lead to exposure due to the absence of pathogen reduction steps after extrusion or at consumer households. Exposure is potentially highest when Salmonella is transferred to human food that is left at growth-promoting conditions. This model can be applied to evaluate the impact of alternative Salmonella control measures during production, risk communication to consumers, and regulatory standards.

A System Model for Understanding the Role of Animal Feces as a Route of Contamination of Leafy Greens before Harvest

ABSTRACT The majority of foodborne outbreaks in the United States associated with the consumption of leafy greens contaminated with Escherichia coli O157:H7 have been reported during the period of July to November. A dynamic system model consisting of subsystems and inputs to the system (soil, irrigation, cattle, wild pig, and rainfall) simulating a hypothetical farm was developed. The model assumed two crops of lettuce in a year and simulated planting, irrigation, harvesting, ground preparation for the new crop, contamination of soil and plants, and survival of E. coli O157:H7. As predicted by the baseline model for crops harvested in different months from conventional fields, an estimated 13 out of 257 (5.05%) first crops harvested in July would have at least one plant with at least 1 CFU of E. coli O157:H7. Predictions indicate that no first crops would be contaminated with at least 1 CFU of E. coli O157:H7 for other months (April to June). The maximum E. coli O157:H7 concentration in a plant was higher in the second crop (27.10 CFU) than in the first crop (9.82 CFU). For the second crop, the probabilities of having at least one plant with at least 1 CFU of E. coli O157:H7 in a crop were predicted as 15/228 (6.6%), 5/333 (1.5%), 14/324 (4.3%), and 6/115 (5.2%) in August, September, October, and November, respectively. For organic fields, the probabilities of having at least one plant with ≥1 CFU of E. coli O157:H7 in a crop (3.45%) were predicted to be higher than those for the conventional fields (2.15%). IMPORTANCE This study is the first attempt toward developing a mathematical system model to understand the pathway of E. coli O157:H7 in the production of leafy greens. Results of the presented system model indicate that the seasonality of outbreaks of E. coli O157:H7-associated contamination of leafy greens was in good agreement with the prevalence of this pathogen in cattle and wild pig feces in a major leafy greens-producing region in California. On the basis of comparisons among the results of different scenarios, it can be recommended that the concentration of E. coli O157:H7 in leafy greens can be reduced considerably if contamination of soil with wild pig and cattle feces is mitigated.

Development of Dose-Response Models to Predict the Relationship for Human Toxoplasma gondii Infection Associated with Meat Consumption.

Toxoplasma gondii is a protozoan parasite that is responsible for approximately 24% of deaths attributed to foodborne pathogens in the United States. It is thought that a substantial portion of human T. gondii infections is acquired through the consumption of meats. The dose-response relationship for human exposures to T. gondii-infected meat is unknown because no human data are available. The goal of this study was to develop and validate dose-response models based on animal studies, and to compute scaling factors so that animal-derived models can predict T. gondii infection in humans. Relevant studies in literature were collected and appropriate studies were selected based on animal species, stage, genotype of T. gondii, and route of infection. Data were pooled and fitted to four sigmoidal-shaped mathematical models, and model parameters were estimated using maximum likelihood estimation. Data from a mouse study were selected to develop the dose-response relationship. Exponential and beta-Poisson models, which predicted similar responses, were selected as reasonable dose-response models based on their simplicity, biological plausibility, and goodness fit. A confidence interval of the parameter was determined by constructing 10,000 bootstrap samples. Scaling factors were computed by matching the predicted infection cases with the epidemiological data. Mouse-derived models were validated against data for the dose-infection relationship in rats. A human dose-response model was developed as P (d) = 1-exp (-0.0015 × 0.005 × d) or P (d) = 1-(1 + d × 0.003 / 582.414)(-1.479) . Both models predict the human response after consuming T. gondii-infected meats, and provide an enhanced risk characterization in a quantitative microbial risk assessment model for this pathogen.

Transmission of Bacterial Zoonotic Pathogens between Pets and Humans: The Role of Pet Food

Recent Salmonella outbreaks associated with dry pet food and treats raised the level of concern for these products as vehicle of pathogen exposure for both pets and their owners. The need to characterize the microbiological and risk profiles of this class of products is currently not supported by sufficient specific data. This systematic review summarizes existing data on the main variables needed to support an ingredients-to-consumer quantitative risk model to (1) describe the microbial ecology of bacterial pathogens in the dry pet food production chain, (2) estimate pet exposure to pathogens through dry food consumption, and (3) assess human exposure and illness incidence due to contact with pet food and pets in the household. Risk models populated with the data here summarized will provide a tool to quantitatively address the emerging public health concerns associated with pet food and the effectiveness of mitigation measures. Results of such models can provide a basis for improvements in production processes, risk communication to consumers, and regulatory action.

Modeling the long-term kinetics of Salmonella survival on dry pet food.

Due to multiple outbreaks and large-scale product recalls, Salmonella has emerged as a priority pathogen in dry pet food and treats. However, little data are available to quantify risks posed by these classes of products to both pets and their owners. Specifically, the kinetics of Salmonella survival on complex pet food matrices are not available. This study measured the long-term kinetics of Salmonella survival on a dry pet food under storage conditions commonly encountered during production, retail, and in households (awxa0<xa00.60, 23xa0°C). A Salmonella enterica cocktail of 12 strains isolated from dry pet foods and treats was used to inoculate commercial dry dog food. Salmonella was enumerated on non-selective (BHI) and selective (XLD and BS) media. Results at 570 days indicated an initial relatively rapid decline (up to 54 days), followed by a much slower extended decline phase. The Weibull model provided a satisfactory fit for time series of Log-transformed Salmonella counts from all three media (δ: mean 4.65 day/Log (CFU/g); p: mean 0.364 on BHI). This study provides a survival model that can be applied in quantitative risk assessment models.

Impact of mulches and growing season on indicator bacteria survival during lettuce cultivation

In fresh produce production, the use of mulches as ground cover to retain moisture and control weeds is a common agricultural practice, but the influence that various mulches have on enteric pathogen survival and dispersal is unknown. The goal of this study was to assess the impact of different mulching methods on the survival of soil and epiphytic fecal indicator bacteria on organically grown lettuce during different growing seasons. Organically managed lettuce, cultivated with various ground covers--polyethylene plastic, corn-based biodegradable plastic, paper and straw mulch--and bare ground as a no-mulch control, was overhead inoculated with manure-contaminated water containing known levels of generic Escherichia coli and Enterococcus spp. Leaves and soil samples were collected at intervals over a two week period on days 0, 1, 3, 5, 7, 10 and 14, and quantitatively assessed for E. coli, fecal coliforms and Enterococcus spp. Data were analyzed using mixed models with repeated measures and an exponential decline with asymptote survival model. Indicator bacterial concentrations in the lettuce phyllosphere decreased over time under all treatments, with more rapid E. coli declines in the fall than in the spring (p<0.01). Persistence of E. coli in spring was correlated with higher maximum and minimum temperatures in this season, and more regular rainfall. The survival model gave very good fits for the progression of E. coli concentrations in the phyllosphere over time (R(2)=0.88 ± 0.12). In the spring season, decline rates of E. coli counts were faster (2013 p=0.18; 2014 p<0.005) for the bare ground-cultivated lettuce compared to mulches. In fall 2014, the E. coli decline rate on paper mulch-grown lettuce was higher (p<0.005). Bacteria fluctuated more, and persisted longer, in soil compared to lettuce phyllosphere, and mulch type was a factor for fecal coliform levels (p<0.05), with higher counts retrieved under plastic mulches in all trials, and higher enterococci levels under straw in fall 2014 (p<0.05). This study demonstrates that mulches used in lettuce production may impact the fate of enteric bacteria in soil or on lettuce, most likely in relation to soil moisture retention, and other weather-related factors, such as temperature and rainfall. The data suggest that the time between exposure to a source of enteric bacteria and harvesting of the crop is season dependent, which has implications for determining best harvest times.