Individual exposure model

Wu J, Lurmann F, Winer A, Lu R, Turco R, Funk T (2005) Development of an individual exposure model for application to the Southern California children s health study. Atmos Environ 39 259-273... 

Thus, tlie focus of tliis subsection is on qualitative/semiquantitative approaches tliat can yield useful information to decision-makers for a limited resource investment. There are several categories of uncertainties associated with site risk assessments. One is tlie initial selection of substances used to characterize exposures and risk on tlie basis of the sampling data and available toxicity information. Oilier sources of uncertainty are inlierent in tlie toxicity values for each substance used to characterize risk. Additional micertainties are inlierent in tlie exposure assessment for individual substances and individual exposures. These uncertainties are usually driven by uncertainty in tlie chemical monitoring data and tlie models used to estimate exposure concentrations in tlie absence of monitoring data, but can also be driven by population intake parameters. As described earlier, additional micertainties are incorporated in tlie risk assessment when exposures to several substances across multiple patliways are suimned. 

Fate and exposure analyses. The multimedia transport and transformation model is a dynamic model that can be used to assess time-varying concentrations of contaminants that are placed in soil layers at a time-zero concentration or contaminants released continuously to air, soil, or water. This model is used for determining the distribution of a chemical in the environmental compartments. An overview of the partitioning among the liquid, solid and/or gas phases of individual compartments is presented in Fig. 7. The exposure model encompasses... 

The fact that the application of exposure models for the evaluation of sources of phthalate exposures yielded variable results means that the extent of exposure via different pathways depends on the individual phthalate, the geographic area, the age, and the lifestyle of the consumers [121]. 

Careful construction of the conceptual model diagram, and the use of a tabular approach such as Table 2.1, should help to avoid these problems. The diagram should show clearly the point at which individual exposure is used to predict individual effects and the process by which individual effects are aggregated to generate the risk estimate. In addition, it should be remembered that the risk estimate may be combined quantitatively or qualitatively with other lines of evidence to address the assessment endpoint. 

Recently, metapopulation models have been successfully applied to assess the risks of contaminants to aquatic populations. A metapopulation model to extrapolate responses of the aquatic isopod Asellus aquaticus as observed in insecticide-stressed mesocosms to assess its recovery potential in drainage ditches, streams, and ponds is provided by van den Brink et al. (2007). They estimated realistic pyrethroid concentrations in these different types of aquatic ecosystems by means of exposure models used in the European legislation procedure for pesticides. It appeared that the rate of recovery of Asellus in pyrethroid-stressed drainage ditches was faster in the field than in the isolated mesocosms. However, the rate of recovery in drainage ditches was calculated to be lower than that in streams and ponds (van den Brink et al. 2007). In another study, the effects of flounder foraging behavior and habitat preferences on exposure to polychlorinated biphenyls in sediments were assessed by Linkov et al. (2002) using a tractable individual-based metapopulation model. In this study, the use of a spatially and temporally explicit model reduced the estimate of risk by an order of magnitude as compared with a nonspatial model (Linkov et al. 2002). 

Deterministic models use a single value for input variables and provide a point estimate of exposure or dose. Probabilistic models take into account the fact that most input variables will have a distribution of values. These models use probability distributions to develop a range of plausible exposures for the population of concern. Understanding exposure distributions will allow understanding of the range of exposures as well as prediction of risk for the entire population. It will also allow prediction of risk for the most highly exposed individuals. Sophisticated models can be used to develop distributions for different pathways and populations. They can also be used to develop information on interindividual variability and uncertainty in the estimated distributions and to predict the variables that are most important for both exposure and dose. 

Exposure models use available information on concentrations of chemicals in exposure media along with information about when, where, and how individuals might contact the exposure media to estimate exposure. For population assessments, distributional data on exposure factors and environmental concentrations are used to estimate exposure distributions for a population. Examples of various exposure models are summarized in Table 6. 

The individual tolerance concept has some unrealistic properties (Kooijman 1996 Newman and McCloskey 2000). Most importantly, if there is a distribution in sensitivities, this would imply that the survivors from an experiment are the less sensitive individuals. Experiments with sequential exposure show that this prediction fails (at least as the dominant mechanism) (Newman and McCloskey 2000 Zhao and Newman 2007). There is sufficient reason to conclude that the individual threshold model is not sufficient to explain the observed dose-response relationships, and that mortality is a stochastic process at the level of the individual... 

By brainstorming about potential disaster scenarios and the scope of resources anticipated to be needed under each scenario, the intensity and duration of the mental health response can also be anticipated. The U.S. Department of Health and Human Services (2004) has developed a population exposure model that planners can use to estimate the psychological impact of mass violence and terrorism and, therefore, the resources that might he needed. The model s underlying principle is that individuals who are most personally, physically, and psychologically exposed to trauma and the disaster scene are likely to he affected the most (Figure 5.1). 

Each of the models defines individuals exposures as a series of separate events. These events are defined in a way that allows the calculation of the dose received during the event. An event may consist of eating a specific food (an apple, a slice of pizza, or a fish from a contaminated river) or a specific act (mowing a lawn, applying a pesticide, or refueling a car). 

By repeating this process for different types of individuals, the models create a picture of the exposure histories of a representative population of individuals. The variation of exposures in such a... 

Freshman, J.S. and C.A. Menzie. 1996. Two wildlife exposure models to assess impacts at the individual and population levels and the efficacy of remedial actions. Hum. Health Ecol. Risk Assess. 2(3) 481-498. 

When modeling real data, an important first step is to carefully consider and specify the intended use of the model to be developed. With this in hand, an appropriate strategy and analysis plan can be crafted to ensure the appropriateness of the model (15). For the purposes of this chapter, a simulated data set is used to mimic a typical Phase 2 trial of a novel compound where an endpoint measurement is collected at each study visit. In this case, the endpoint of interest is the presence or absence of a particular adverse event. Various demographic variables are available for possible correlation with the endpoint in addition to a calculated measure of individual exposure to the drug. 

Once all available and relevant information has been assembled, it can be critically analyzed for missing data elements or significant data gaps. The exposure assessor must determine where existing exposure measurements can be used directly and where other techniques must be applied to extrapolate or estimate the exposures of interest. Key types of data gaps that may need to be addressed include insufficient existing exposure data, inadequate information to characterize exposure scenarios for individual job tasks or titles, limited inputs for exposure models, or a lack of certainty regarding appropriate exposure classification. 

Several researchers have attempted to correlate levels of lead-210 in bone with cumulative radon daughter exposure. Eisenbud et al. (1969) employed in vivo techniques to measure lead-210 in the skull of nonoccupationally exposed and occupationally exposed individuals. Exposure for miners was derived from mine records and compared to that estimated from a model. Their results showed that the amount of lead-210 deposited, regardless of temporal considerations, will be within a factor of... 

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