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Concerns about adequate protection of children's health from chemicals in the environment have created a need for research to identify how children's risks differ from adults'. A systematic review of factors that affect child sensitivity throughout development may be useful for research and practice in this area. We summarized available literature and other peer-reviewed information on factors that affect pharmacokinetics and exposure in an age-based developmental framework. Biological processes related to chemical absorption (gastrointestinal, dermal, and pulmonary), distribution, metabolism, and excretion were considered, along with reference to behaviors and other factors associated with child-specific exposures. The available information was summarized in a timeline of maturation for biological processes. It indicates variability in the duration and timing of maturation for each biological function. Possible implications for understanding pediatric sensitivity to environmental chemicals are discussed in light of factors affecting exposure through development. Themes that emerge from the evidence are presented as hypothesis-generating conclusions. This approach may be useful for evaluating developmental trends of susceptibility, and for identifying time periods and/or chemical classes of particular concern and thus important to consider in risk assessment.

An interdisciplinary workshop was convened by the George Washington University in June 2001 to discuss how to incorporate new knowledge about susceptibility to microbial pathogens into risk assessment and management strategies. Experts from government, academic, and private sector organizations discussed definitions, methods, data needs, and issues related to susceptibility in microbial risk assessment. The participants agreed that modeling approaches need to account for the highly specific nature of host-pathogen relationships, and the wide variability of infectivity, immunity, disease transmission, and outcome rates within microbial species and strains. Concerns were raised about distinguishing between exposure and dose more clearly, interpreting experimental and outbreak data correctly, and using thresholds and possibly linearity at low doses. Recommendations were made to advance microbial risk assessment by defining specific terms and concepts more precisely, designing explicit conceptual frameworks to guide development of more complex models and data collection, addressing susceptibility in all steps of the model, measuring components of immunity to characterize susceptibility, reexamining underlying assumptions, applying default methods appropriately, obtaining more mechanistic data to improve default methods, and developing more biologically relevant and continuous risk estimators. The interrelated impacts of selecting specific subpopulations and health outcomes, and of increasing model complexity and data demands, were considered in the contexts of public policy goals and resources required. The participants stated that zero risk is unattainable, so targeted and effective risk reduction and communication strategies are essential not only to raise pubic awareness about water quality but also to protect the most susceptible members of the population.

Regional estimates of cryptosporidiosis risks from drinking water exposure were developed and validated, accounting for AIDS status and age. We constructed a model with probability distributions and point estimates representing Cryptosporidium in tap water, tap water consumed per day (exposure characterization); dose response, illness given infection, prolonged illness given illness; and three conditional probabilities describing the likelihood of case detection by active surveillance (health effects characterization). The model predictions were combined with population data to derive expected case numbers and incidence rates per 100,000 population, by age and AIDS status, borough specific and for New York City overall in 2000 (risk characterization). They were compared with same-year surveillance data to evaluate predictive ability, assumed to represent true incidence of waterborne cryptosporidiosis. The predicted mean risks, similar to previously published estimates for this region, overpredicted observed incidence-most extensively when accounting for AIDS status. The results suggest that overprediction may be due to conservative parameters applied to both non-AIDS and AIDS populations, and that biological differences for children need to be incorporated. Interpretations are limited by the unknown accuracy of available surveillance data, in addition to variability and uncertainty of model predictions. The model appears sensitive to geographical differences in AIDS prevalence. The use of surveillance data for validation and model parameters pertinent to susceptibility are discussed.

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