We propose a computationally efficient probabilistic modeling, methodology to estimate the adverse effects on humans of exposure to contaminated groundwater. Our work is aligned with the standard suggested by the regulatory agencies and allows to propagate uncertainty from hydrogeological, toxicological and behavioral parameters to the final health risk endpoint. The problem under consideration consists of a contaminated aquifer supplying water to a population. Contamination stems from a continuous source that feeds a steady plume which constitutes the hazard source. This scenario is particularly suited for NAPL pollutants. The erratic displacement of the contaminant plume in groundwater, due to the spatial variability of hydraulic conductivity, is characterized within the Lagrangian stochastic framework which enables the complete probabilistic characterization of the contaminant concentration at an environmentally sensitive location. Following the probabilistic characterization of flow and transport, we quantify the adverse health effects on humans. The dose response assessment involves the estimation of the uncertain effects of the exposure to a given contaminant while accounting for the exposed individual's metabolism. The model integrates groundwater transport, exposure and human metabolism in a comprehensive probabilistic framework which allows the assessment of the risk probability through a novel simple analytical solution. Aside from its computational efficiency, the analytical features of the framework allows the assessment of uncertainty arising from the hydrogeological parameters. (C) 2016 Elsevier B.V. All rights reserved.