Human health risk assessment and analysis involves evaluating the effect of toxins, contaminants and other environmental hazards on human health. This requires evaluation of both how humans might be exposed to the hazards (i.e., the environmental pathways through which they are exposed), as well as the health impact once they are exposed.
Predicting the behavior of environmental and biological systems is inherently complex and uncertain, since they involve analyzing systems made up of many component parts that are interrelated, the components interact in complex ways with numerous feedback mechanisms, and in many cases, the systems are poorly characterized or understood. In addition, such systems are often controlled by stochastic variables (i.e., precipitation, temperature) and involve uncertain processes, parameters, and events.
The challenge when evaluating such systems is to find an approach that can incorporate all the knowledge available to engineers and scientists into a quantitative framework that can be used to predict the potential risks associated with a product or project. To be effective, the framework needs to be both flexible (so that it can accurately represent the systems) and transparent (so the models can be easily explained to decision-makers and stakeholders).
By combining the flexibility of a general-purpose and highly-graphical probabilistic simulation framework with a specialized module to support mass transport modeling, GoldSim allows you to create realistic models of complex, real-world multi-media environmental systems. Using Monte Carlo simulation, you can explicitly represent the uncertainty inherent is these systems in order to carry out both exposure analysis and risk analysis. GoldSim has the power and flexibility to build ‘total system” models of many kinds of environmental biological systems, ranging from individuals to populations. In addition, GoldSim supports two-dimensional (nested) Monte Carlo simulation, allowing you to explicitly separate uncertainty and variability in your analyses.
