No abstract

The Monte Carlo computational system for stochastic modelling of dietary exposure to food chemicals and nutrients is presented. This system was developed through a European Commission-funded research project. It is accessible as a Web-based application service. The system allows and supports very significant complexity in the data sets used as the model input, but provides a simple, general purpose, linear kernel for model evaluation. Specific features of the system include the ability to enter (arbitrarily) complex mathematical or probabilistic expressions at each and every input data field, automatic bootstrapping on subjects and on subject food intake diaries, and custom kernels to apply brand information such as market share and loyalty to the calculation of food and chemical intake.

Current microbial exposure models assume that microbial exchange follows a concentration gradient during hand-to-surface contacts. Our objectives were to evaluate this assumption using transfer efficiency experiments and to evaluate a model's ability to explain concentration changes using approximate Bayesian computation (ABC) on these experimental data. Experiments were conducted with two phages (MS2, Φ X174) simultaneously to study bidirectional transfer. Concentrations on the fingertip and surface were quantified before and after fingertip-to-surface contacts. Prior distributions for surface and fingertip swabbing efficiencies and transfer efficiency were used to estimate concentrations on the fingertip and surface post contact. To inform posterior distributions, Euclidean distances were calculated for predicted detectable concentrations (log 10 PFU cm −2 ) on the fingertip and surface post contact in comparison with experimental values. To demonstrate the usefulness of posterior distributions in calibrated model applications, posterior transfer efficiencies were used to estimate rotavirus infection risks for a fingertip-to-surface and subsequent fingertip-to-mouth contact. Experimental findings supported the transfer gradient assumption. Through ABC, the model explained concentration changes more consistently when concentrations on the fingertip and surface were similar. Future studies evaluating microbial transfer should consider accounting for differing fingertip-to-surface and surface-to-fingertip transfer efficiencies and extend this work for other microbial types.

The quality of irrigation water drawn from surface water sources varies greatly. This is particularly true for waters that are subject to intermittent contamination events such as runoff from rainfall or direct entry of livestock upstream of use. Such pollution in irrigation systems increases the risk of food crop contamination and require adoption of best monitoring practices. Therefore, this study aimed to define optimal strategies for monitoring irrigation water quality. Following the analysis of 1,357 irrigation water samples for Escherichia coli, total coliforms, and physical and chemical parameters, the following key irrigation water collection approaches are suggested: 1) explore up to 950 m upstream to ensure no major contamination or outfalls exists; 2) collect samples before 12:00 PM local time; 3) collect samples at the surface of the water at any point across the canal where safe access is available; and 4) composite five samples and perform a single E. coli assay. These recommendations comprehensively consider the results as well as sampling costs, personnel effort, and current scientific knowledge of water quality characterization. These strategies will help to better characterize risks from microbial pathogen contamination in irrigation waters in the Southwest United States and aid in risk reduction practices for agricultural water use in regions with similar water quality, climate, and canal construction. HIGHLIGHTS • Microbial testing practices must be based on irrigation water-specific research. • Assaying sample composites is the most cost-effective best representation of microbial content. • Contamination events have 2-log10 reductions 950 m downstream. • Microbial concentrations are highest before noon. • Microbial concentrations are homogenous throughout the canal water column.

Results suggest firefighters' hands were the main vehicles of microbial transfer. Current practices were not consistently applied or standardized and minimally reduced prevalence and quantity of microbial contamination on EMS surfaces. Although use of a consistent protocol of H2O2 wipes significantly reduced percent prevalence and concentration of viruses, training and promotion of surface disinfection should be provided.