Visualizing and Communicating the Water Pipe Replacement Program in Flint, Michigan

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Presented by OmniSci

An analytics platform that gives users the ability to exercise unbounded curiosity when exploring data visually.

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In this session, we’ll discuss how a predictive algorithm helped the City of Flint focus their service line (water pipe) investigations in the areas at highest risk for having lead or galvanized steel service lines. We’ll discuss our work (in progress) to create a public map using best visual data and public health communication practices that, when completed, will allow Flint residents to visualize the predictive model outcomes and the pipe replacement progress in the city.

Jared Webb

Jared Webb has worked since 2016 as a member of the University of Michigan research team that used machine learning to locate Flint’s lead service

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