FDA-iRISK® 4.0

Glossary and Abbreviations

Glossary
TermDescription
Acute ExposureExposure to a microbial or chemical hazard in food, that is limited to a single eating occasion after which illness can ensue.
Chance DistributionA probability distribution defined using a series of discrete probability-‘x-value’ pairs, where x can be the level of hazard in a food, or the amount of food consumed per day, for example. The only constraint is that each probability value is between 0 and 1, and that they sum to 1. See also Variability Distribution.
Chronic ExposureRepeated exposure (over the lifespan) to a chemical that may occur in food in levels too low to pose an immediate risk of illness, but that can cause illness after a long period of regular exposure at these low levels. Compare to Acute Exposure.
Colony-forming Unit (cfu)An individual microbe, capable of multiplying and forming a colony under favorable conditions. One of the options for the numerator of the unit of microbial contamination of food. The choice of numerator is for the convenience of the user and has no impact on calculation of risk.
Consumption ModelA specification of the amount of a food consumed by an individual on a daily (for chronic exposure), or on a per eating occasion (for acute exposure) basis.
Convergence CriterionThe user-specified percentage change in the simulation result deemed to represent adequate stability (i.e. a sufficient number of simulations have been run to achieve a stable result). In FDA-iRISK the user can choose to test the risk or the exposure of the variability simulation, and the mean, median, or an interval of the uncertainty simulation. See Simulation Settings.
Conversion RateThe relationship between the concentration of a microbial hazard in a food, and the concentration of a chemical hazard associated with it. This must be defined when a microbial upstream process model is linked with a chemical downstream process model, and is useful to model toxigenic bacteria.
Cost per IllnessThe economic cost associated with one case of a particular health condition. See Cost-of-Illness.
Cost-of-Illness (COI)The economic cost associated with a particular health condition, that may include such things as lost productivity in addition to medical treatment.
Cumulative Empirical DistributionA probability distribution defined using a series of successively increasing cumulative probability-‘x value’ pairs, where x can be the level of hazard in a food, or the amount of food consumed per day, for example. The constraint is that the first cumulative probability value must be 0, the last must be 1, and that intervening values are strictly increasing. The user can select linear or cubic interpolation between successively defined points. See also Variability Distribution.
DecreaseSee “Glossary of Process Types” in the tool.
Decrease by Inactivation ModelSee “Glossary of Process Types” in the tool.
DietA user-defined set of previously-defined foods, intended to permit estimation of consumer exposure to one or more hazards or nutrients. The diet should include the major sources of exposure to the relevant hazard or nutrient.
Diet ShiftA set of factor increases or decreases to be applied to a previously-defined diet, and intended to represent a systematic change in exposure to one or more hazards or nutrients via a change in consumption of food sources.
Disability-Adjusted Life Years (DALYs)A metric that combines morbidity and mortality by scaling duration of a health endpoint by severity (0 would be perfect health while 1 is death), in order to describe the burden of illness, typically of a population.
Dose Response ModelA function that computes the probability of illness for a given distribution of exposure (dose) to a hazard or nutrient. In FDA-iRISK the distribution of exposure (dose) is calculated from the process model and consumption model.
Downstream ModelIn linked process models, a process model which forgoes the definition of initial conditions in favor of specifying an upstream process model. The final state of the upstream model then defines the initial conditions of the downstream model. The downstream model consists of one or more process stages and must end at the point of consumption. See also Linked Process Models, and Upstream Model.
Eating Occasion (eo)A unit of consumption, used to describe acute exposure, and representing the consumption of a food at a single “sitting”. The underlying assumption is that the amount of hazard present in that amount of food determines the probability of acute illness according to the applied dose response model.
Evaporation/DilutionSee “Glossary of Process Types” in the tool.
Exposure TypeTerm referring to either acute or chronic exposure to a hazard.
Growth model (Predictive Model)A specification of the dynamics and expected extent of growth of a microbial hazard under certain environmental conditions, based on parameters associated with the microbe. It can be called from a process stage to predict growth under the conditions specified for that stage. See also Predictive Model, Primary Model, Secondary Model.
Health EndpointA single health condition associated with a case of illness resulting from exposure to a hazard. For example, exposure to Salmonella spp. may result in pain, fever, and/or diarrhea: each is considered a health endpoint. It is convenient to describe illness in terms of health endpoints for which disability weights are available in the literature.
Health MetricA quantitative means of describing a state of health, typically of a population. FDA-iRISK provides an option for using DALY, QALY loss or COI as a health metric.
Inactivation model (Predictive Model)A specification of the dynamics and expected extent of inactivation of a microbial hazard under certain environmental conditions, based on parameters associated with the microbe. It can be called from a Process Stage to predict inactivation under the conditions specified for that stage. See also Predictive Model, Primary Model, Secondary Model.
Increase by AdditionSee “Glossary of Process Types” in the tool.
Increase by Cross Contamination (Amount or Concentration)See “Glossary of Process Types” in the tool.
Initial Concentration/ Initial ContaminationA component of the process model definition, specifying the level of the hazard of concern in the food at the stage of food production or processing chosen by the user to be the start of the process model. In FDA-iRISK, this description of concentration applies to contaminated units of food only (uncontaminated units are accounted for using the prevalence).
Initial PrevalenceA component of the process model definition, specifying the prevalence of the hazard of concern among units of the food at the stage of food production or processing chosen by the user to be the start of the process model. The value must be determined based on units having the initial unit size specified, unless the value is 0 or 1.
Initial Unit SizeA component of the process model definition, specifying the unit size (mass or volume) of the food at the stage of food production or processing chosen by the user to be the start of the process model. The unit size must be that for which the specified initial prevalence was determined (unless the initial prevalence is 0 or 1).
Lag model (Predictive Model)A specification of the expected delay to onset of growth of a microbe under certain environmental conditions, based on parameters associated with the microbe. It can be called from a process stage to predict lag duration under the conditions specified for that stage. Alternatively, the option of specifying a lag phase directly is offered. See also Predictive Model, Secondary Model.
Life StageA user-specified age category describing individuals assumed to share a consumption pattern (in units of g/d or g/kg-d where kg is the body weight) for the food in question. In aggregate the (mutually exclusive) life stages represent the duration of chronic exposure.
Lifetime Average Daily Dose (LADD)In chronic exposure, the amount of the chemical hazard consumed daily by an individual consumer, attributable to the food or foods in question, averaged over the lifetime (sum of durations of life stages). The amount associated with each life stage is weighted by the relative duration of the life stage when obtaining the average.
Linked Process ModelA Process Model composed of a previously-defined process model (“Upstream Process Model”) to which additional process stages (as the “Downstream Process Model”) can be appended. The term can also refer to either of the linked models. Linking facilitates the description of process models describing a variety of further processing techniques of a single, partially processed ingredient, for example. Linking can also be used to describe the behavior of a toxigenic microbe, by using an upstream microbial process model to compute a cell population in the food, and a downstream chemical process model to represent the toxin, up to the point of consumption (see “Conversion Rate”). See also Downstream Model, and Upstream Model.
Log and Non-Log DistributionsVariability distributions or uncertainty distributions in which the value on the x-axis is in log or non-log form, respectively. Log distributions are not explicitly available for defining microbial concentration as the user can select log units when defining the hazard itself. See also Variability Distribution, and Uncertainty Distribution.
Maximum Population Density (MPD)A concentration value used to impose a limit on microbial growth. In a processing step that allows growth, a predicted final concentration that exceeds the MPD is replaced by the MPD.
Monotonically decreasing functionA function between ordered sets that reverses the given order. In FDA-iRISK, OC curves (for probability of acceptance), and dose response models for nutrient deficiency are monotonically decreasing functions. This can be used to evaluate a nutrient with beneficial health effects.
Monotonically increasing functionA function between ordered sets that preserves the given order. In FDA-iRISK, cumulative empirical distributions, OC curves (for probability of rejection), and dose response models for hazards with negative health outcomes, are monotonically increasing functions.
Monte Carlo SimulationMonte Carlo simulation is a computerized mathematical technique that allows variability in inputs to be reflected in the resulting output, which takes the form of a distribution of values from which means and percentiles can be obtained. The simulation consists of a large number of individual iterations, each utilizing a value randomly sampled from each input variability distribution to arrive at the result. See also Second-Order Monte Carlo Simulation.
No ChangeSee “Glossary of Process Types” in the tool.
Operating Characteristic (OC) CurveA curve representing the probability of lot rejection (or alternately: lot acceptance) as a function of the concentration of hazard in a sampling of that lot. The sampling process type requires the definition of a OC curve.
Parallel Process ModelA process model, available for microbial hazards only, that consists of more than one variation of a single set of process stages. This facilitates the description of a situation in which a food is produced at different facilities each implementing a variation of a shared process model. The process stages must be the same in all variations, however the specific parameter values may differ across parameter sets.
PartitioningSee “Glossary of Process Types” in the tool.
PlaceholderSee “Glossary of Process Types” in the tool.
PoolingSee “Glossary of Process Types” in the tool.
Population GroupA user-specified segment of a population describing individuals assumed to share a consumption pattern (in units of g per eating occasion) for the food in question. In aggregate (mutually exclusive) population groups represent all the consumers at risk of acute exposure to the hazard during one year.
Predictive ModelFor a particular microbial hazard, specification of a set of parameter values permitting the estimation of behaviour (lag phase, growth, or inactivation) of the microbe under certain environmental conditions (such as time, temperature, pH and water activity). See also Growth model, Inactivation model, Lag model, and Process Stage.
PrevalenceThe proportion of food units that are contaminated with the hazard in question, expressed as a unitless value from 0 to 1. The prevalence value specified in each process model must be the proportion of contaminated food units for the unit size specified. For example, if the unit size is for a head of lettuce, the prevalence must be the proportion of heads of lettuce that are contaminated and not the proportion of fields or shipping crates that are contaminated.
Primary (predictive) ModelA type of function in which microbial population is predicted as a function of time. FDA-iRISK permits the user to define primary growth models and primary inactivation models. See Predictive Models; compare to Secondary (predictive) Model.
Process ModelA description of the stages of production/processing/handling for a food to predict the final level and prevalence of the hazard at the point of consumption (and the unit size of the food at the end of processing), given specified initial conditions (for unit size of the food, and prevalence and level of the hazard). See also Process Stage, and Process Type.
Process StageOne of a series of processing steps for a food, defined by a process type and associated quantitative parameters such that the effect of the stage on the level and prevalence of the hazard can be estimated. Appropriate predictive models can be called from within a process stage definition. A process model consists of specification of initial conditions followed by zero or more process stages until the point of consumption is reached. See also Process Model, Process Type, and Predictive Model.
Process TypeAn option for specifying the effect of a processing stage on the concentration or prevalence of the hazard, or on the unit mass of the food. Process types available in FDA-iRISK include growth, decrease, evaporation, and pooling (for a complete list see the FDA-iRISK® 4.0 Technical Document) and definitions are available from within the tool. See also Process Model, and Process Stage.
Quality-Adjusted Life Years (QALYs)A metric that expresses health-related quality of life by applying a scaling factor (0 is death and 1 is full health) to duration in years. In contrast to DALYs, scaling factors are not developed for specific diseases or disorders, but instead tend to represent well-being with or without a particular medical treatment, for example. QALY loss is an option for health metric in FDA-iRISK.
Redistribution (Partial or Total)See “Glossary of Process Types” in the tool.
RepositoryA virtual location for storing and managing a collection of risk models belonging to the user. Each user can create multiple repositories and share read-only access to one or more repositories with other users.
Risk ScenarioA risk model consisting of data and information for seven elements (the hazard, the food, process model, consumption pattern, dose-response and health metric) sufficient to estimate the risk to population health from a particular food-hazard combination. See also: Computed Scenario and Specified Risk Scenario.
Risk Scenario, Exposure OnlyA risk scenario that combines information from previously-defined risk models (process model, consumption model), to compute the exposure of a population to a hazard. No dose response model or health metric is required.
Risk Scenario, Multi-foodA risk scenario that computes the risk to population health from a single previously-defined hazard in a selection of previously-defined foods, that can be useful, for example, in evaluating the risk from chronic exposure to a chemical hazard occurring in several foods within the diet. If the chemical is a nutrient this type of risk scenario can be used to evaluate the risk of deficiency of the nutrient across the diet.
Risk Scenario, Multi-food, multi-hazardA risk scenario that computes the risk to population health for a selection of previously-defined hazards in a selection of previously-defined foods. This type of risk scenario is used to evaluate dietary risk from chronic exposure to several chemical hazards that may include nutrients.
Risk Scenario, Single foodA risk scenario that computes the risk to population health from a single previously-defined food and single previously-defined hazard. It can also be used to evaluate risk from acute or chronic exposure.
Sampling (OC Curve)See “Glossary of Process Types” in the tool.
Sampling (Simple Poisson)See “Glossary of Process Types” in the tool.
Scenario GroupA group of scenarios, defined as such at the time of creating a report, in which each scenario contributes to the risk being evaluated.
Scenario WeightA fraction between 0 and 1 representing the relative contribution of a single scenario to the overall risk represented by a group of scenarios. See Scenario Group.
Secondary (predictive) ModelA type of function in which the rate of growth, or of inactivation, of a microbe is predicted as a function of the conditions the food and the microbe are in (such as temperature pH, water activity, etc.). See Predictive Models; compare to Primary (predictive) Model.
Second-Order Monte Carlo SimulationA method for incorporating both uncertainty and variability of parameter values when evaluating a risk scenario, by nesting Monte Carlo simulations sampling from input variability distributions, within Monte Carlo simulations sampling from input uncertainty distributions. See also Simulation Settings.
Sensitivity AnalysisAn option available when defining a risk scenario, in which alternate values can be specified for selected parameters. This option permits the user to evaluate the sensitivity of the risk to that parameter by comparing the result using the sensitivity analysis to the original result, and can, for example, help identify important data gaps.
Set Maximum Population DensitySee “Glossary of Process Types” in the tool.
Simulation SettingsA set of parameters specifying the dimensions and convergence criterion of a Second-Order Monte-Carlo simulation. The user can specify the desired value of each parameter before running a risk scenario.
Uncertainty DistributionA means of representing uncertainty in the value of a particular parameter being defined. When a parameter value has an uncertainty distribution associated with it, FDA-iRISK uses Second-Order Monte Carlo simulation to compute any downstream results. See also Cumulative Empirical Distributions, Chance Distributions, and Log and Non-Log Distributions.
Upstream ModelIn linked process models, the process model which defines the earlier set of conditions, up until the point of food processing at which the downstream model applies. The upstream model consists of initial conditions and zero or more process stages. See also Linked Process Models, and Downstream Model.
Variability DistributionA means of representing variation in the value of a particular parameter being defined. When a parameter value is defined using a variability distribution, FDA-iRISK uses Monte Carlo simulation to compute any downstream results. See also Cumulative Empirical Distributions, Chance Distributions, and Log and Non-Log Distributions.
Abbreviations
TermDescription
cfuColony Forming Unit
DALYDisability-Adjusted Life Year
eoEating Occasion
LADDLifetime Average Daily Dose
MPDMaximum Population Density
pfuPlaque Forming Unit
sdStandard Deviation
yrYear