A quantitative risk assessment model was built based on potential prevalence and concentration distribution data coming off the farm and then using cross-contamination, survival, and intervention rates as key variables that would affect the outcome of the model.The mathematical structure of the exposure assessment model was translated into a friendly-user web-based tool which is released as a Beta version in English and Spanish. The application incorporates a module for growth predictions in different vegetable matrices and microorganisms as well as a module which allows user designing and simulating exposure models to estimate the final concentration at the moment of consumption. To access this tool, you must register a username and password by clicking the "Register here" button in the lower right-hand corner. Once registered, you will need to wait for an email from the administrator of the tool before you have access. 

An exposure model was developed to relate seafood consumption to levels of methylmercury (reported as mercury) in blood and hair in the U.S. population, and two subpopulations defined as children aged 2–5 and women aged 18–45. 

To describe the transmission dynamics of a pathogen over a food pathway in quantitative microbiological risk assessment (QMRA), several types of processes need to be modelled. Next to microbial processes like bacterial growth and inactivation, four food handling processes can be identified. Among these are partitioning and mixing of the food product.  

Some examples show the effect of more realistic modelling on the prevalence and the probability distribution of the number of pathogens per unit of food product. In general, cell clustering will result in lower prevalences, but higher levels of contamination in contaminated food units. With the methods presented, these effects can be quantified. Difficulties in estimating the model parameters and the impact of implementation of the proposed methods on risk estimates in QMRA are discussed.

The WHO/IPCS Risk Assessment Toolkit (RA Toolkit) project aims to make the international tools on chemical risk assessment more readily accessible, especially to relevant stakeholders in developing countries and countries with economies in transition.

This website includes records of the meeting introducing the pilot phase of the draft WHO Risk Assessment Toolkit in Thailand, Malaysia and China (Bangkok meeting, July 2009).

The RA Toolkit is organized into sections that provide:

-An overview of chemical RA, including the RA framework and uses of RA;

-Generic road maps for how to conduct RA;

-Listing of international resources that are useful for conducting RAs; and

-Examples of how that information can be applied to a RA question, including case-specific roadmaps.

The aims of this report included (i) the relative likelihood of New Zealanders becoming ill from Salmonella transmitted via food compared with Salmonella being transmitted via other pathways such as direct contact with animals and overseas travel and (ii) Changes in relative likelihood of foodborne salmonellosis that may eventuate from importation of poultry products from overseas according to specific import scenarios.

A stochastic simulation modelling approach was taken to determine the extent of Escherichia coli O157:H7 contamination in fresh-cut bagged lettuce leaving the processing plant. A probabilistic model was constructed in Excel to account for E. coli O157:H7 cross contamination when contaminated lettuce enters the processing line.

In this study, a variance-based global sensitivity analysis method was first applied to a contamination assessment model of Listeria monocytogenes in cold smoked vacuum packed salmon at consumption. The impact of the choice of the modeling approach (populational or cellular) of the primary and econdary models as well as the effect of their associated input factors on the final contamination level was investigated.

In this study, transfer of L. monocytogenes from one contact surface to another for Ready-to-Eat deli meats with a delicatessen or restaurant type slicer was investigated. The objectives were to achieve the surface transfer model development and to predict the cross-contamination for the slicing operation. Two cross-contamination routes were studied for model development: (1) L. monocytogenes–contaminated blade to ham (Case I), and (2) L. monocytogenes–contaminated ham to blade and then to uncontaminated ham (Case II).

This report details a mathematical simulation model describing cross contamination pathways for L. monocytogenes. A smoked fish processing plant was used for the model. The report concludes that 10.7% of foods in a lot are contaminated, and that the most significant contributors to contamination were the frequency in which employees' gloves touched food and food surfaces, and the frequency of changing gloves. Access to the full report requires purchase.

This study uses Monte Carlo simulation techniques to quantitatively describe the cross-contamination of Listeria monocytogenes. Two models are presented. The first model describes the number and prevalence for four different strains while the second model describes the number and prevalence for only one strain. The purpose of these models is to provide a mathematical framework for future predictive models with the ultimate goal of understanding and controlling L. monocytogenes in food-processing plants.

This document presents exposure scenarios for different exposure pathways and demonstrates the application of data from the Exposure Factors Handbook in estimating exposures. For each scenario, an exposure algorithm, exposure factor inputs, calculations, and exposure characterization and uncertainties are presented. Ingestion pathways described include contaminated homegrown vegetables, homegrown tomatoes, beef, dairy products, drinking water, fish, and breastmilk

Computer simulation model for estimating the way that changes in food handling practices at the retail, foodservice, or household level may affect the incidence of food-borne illness in the US. Downloadable files for the model, a user's guide, backgrounder, and final report are available

Model and database system for estimating dietary exposure to chemical residues. Data is included from government-sponsored national food intake surveys and chemical residue monitoring programs. The user can add additional foods or chemicals and associated data, and the user can import food diaries for exposure analysis. There is also an option to include exposure from tap water

One report from the SSC Task Force Report on Harmonisation of Risk Assessment Procedures. It discusses methodology for quantitative exposure assessment. Topics discussed include the role of the exposure assessment in the overall process of risk analysis, model development, modeling the food chain, data sources, exposure estimates, and model validation and review. There are also several examples of exposure modeling exercises

Software program for conducting probabilistic microbial risk assessment. The program was developed by Exponent together with the Food and Drug Administration, and consists of a Contamination and Growth Module and an Exposure Module. Data from the U.S. Department of Agriculture's Continuing Survey of Food Intakes by Individuals (CSFII) 1994-96, 98 are included in the program. A users manual, containing both installation and use guidelines, is provided

This report presents models on the uptake of contaminants from the soil by plants. Most of the study data is based on agricultural crop plants. Contaminants studied include arsenic, cadmium, copper, lead, mercury, nickel, selenium, and zinc