Relative Health Indicator
Chad Seidel, CU
Research Approach
This activity will develop and apply a relative risk-based index, Relative Health Indicator, in order to comprehensively evaluate risk reduction, reliability, and resilience that can be achieved by treatment technologies for small drinking water systems. While new technologies routinely emerge touting low-cost and effective solutions, small and large water systems alike can benefit from a tool that evaluates the risk posed by contaminants and associated treatment solutions and assists in choosing appropriate and maximized risk reduction schemes. Such a tool can provide a simple, visual methodology of viewing risk from individual contaminants, the total summation of risk for all contaminants present, and comparisons of different treatment approaches in terms of achievable risk reduction.
Numerous methodologies are available for cumulative risk assessment (CRA), and these methodologies are used to assess community or population risks from exposure to multiple environmental sources, stressors, effects, and pathways (USEPA 1997, Sexton 2012, Williams et al., 2012). Depending on the objective of the analyses, and the CRA methodology used, differing levels of dis-aggregation of health impacts can be achieved, ranging from keeping impacts separated by nature of effect (e.g. cancer versus non-cancer) and/or expressed as probabilities or frequencies of effect, to placing all impacts on a common metric such as Quality Adjusted Life Years (QALYs) or Disability Adjusted Life Years (DALYs). The resulting risk metric can correspondingly range from primarily subjective to primarily quantitative.
In Water Research Foundation (WaterRF) Project # 4310, “Identifying Meaningful Opportunities for Drinking Water Health Risk Reduction in the United States” (Seidel et al., 2013), the researchers concluded that the aggregated and primarily quantitative approaches for estimating drinking water risks have the advantage of being able to make significantly improved decisions on the relative public health impact and cost-effectiveness of proposed control measures, as well allowing for comparability of public health implications of different water sources and systems. However, the quantitative approaches also have greater data requirements and information needs, and the introduction of public health metrics such as QALYs and DALYs makes the resulting metric partially subjective, allowing room for debate and/or disagreement.
The aggregated and primarily quantitative approaches were used in the Seidel et al. WaterRF # 4310 project to develop a summary metric of relative cumulative health impact resulting from drinking water. Termed “Relative Health Indicator” or RHI, this metric allows for the cross- comparison of health indicators of multiple contaminants across “cups of water,” thereby facilitating comparisons of the overall public health benefit provided by different small system water treatment technologies. The RHI is made up three primary components: (1) non-cancer, (2) cancer,and (3) microbial. The cancer RHI is similarly calculated using cancer toxicity and severity factors and exposure estimates. Last, the microbial RHI incorporates overall risks based upon Total Coliform Rule monitoring; source water risks based upon E. coli results; treatment risks and avoidance following the Partnership for Safe Water Phase IV criteria; and distribution system risks based upon disinfectant residual and pipe breaks per mile of distribution system. In this effort, the RHI approach will be further developed to compare and contrast risk impacts of installing drinking water treatment systems. The approach will be expanded beyond the current framework that assumes steady state operation of newly installed treatment systems to also incorporate reliability and resiliency within small system operational constraints. Emerging treatment technologies typically differ from current technologies in their design and operational requirements and, as such, may be more or less operationally reliable and resilient. We will quantify the treatment performance of innovative treatment technologies developed by the Center to inform the RHI approach, and expand the approach to quantify the certainty of those RHI outcomes given differences in reliability and resiliency.