ArticleACS ES&T engineering2022
Improved Decision-Making: A Sociotechnical Utility-Based Framework for Drinking Water Investment.
Article in ACS ES&T engineering, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Authors and funding
6 authors.
Funding
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Abstract
To achieve the goals of the Safe Drinking Water Act, state and local water authorities need to make decisions about where to direct limited funding for infrastructure improvements and currently do so in the absence of adequate evaluative metrics. We developed a framework grounded in utility theory that compares trade-offs explicitly and broadens the factors considered in prioritizing resource allocations. Relevant existing indices were reviewed to identify data applicable to drinking water decision-making. A utility-theory-based decision analysis framework was developed and applied to evaluate how different objectives affect funding decisions for lead service line replacement (LSLR) programs in Pennsylvania and Michigan, United States. The decision framework incorporates drinking water quality characteristics with community and environmental quality attributes. We compare additive and multiplicative model structures, different weights, and spatial scales. Our decision framework showed that the inclusion of additional data beyond what is usually considered in LSLR decisions could change the top 10 counties or public water systems prioritized. Further, the counties or water systems in the top 10 were influenced by the model structure and weights. Prioritization changed based on which data were included, and has implications for the use of evaluative metrics beyond traditional water system data.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.