The City of Philadelphia requires landlords to disclose to tenants the presence of any known lead service lines and provide a pamphlet outlining ways to reduce the risk of lead exposure.

The Area Deprivation Index includes factors like income, education, employment, and housing quality to generate rankings of neighborhoods by socioeconomic disadvantage at the state or national level.

Milwaukee uses an Area Deprivation Index to prioritize neighborhoods for LSLR.

Greater Cincinnati Water Works collaborated with the University of Cincinnati to develop a Prioritization model.

DC Water uses a model to prioritize LSLR in disadvantaged communities that are already marginalized, underserved, and overburdened by pollution.

The City of Detroit has leveraged predictive modeling to achieve a 75% decrease in its proposed project schedule, assess communities most at risk, and reduce the estimated number of lead service lines from 120,000 to 80,000.

BlueConduit delivers rigorously designed, predictive and decision modeling tools that empower water system leaders to make informed decisions on behalf of the communities they serve.

leadCAST Predict helps you accelerate the classification of unknown service lines and prioritize field verifications through advanced service line material predictions powered by machine learning. leadCAST Predict is an additional feature of leadCAST LCRR compliance management solution.

This report found that lead pipe replacement programs in Washington, DC disproportionately benefited wealthier, predominantly white neighborhoods, leaving low-income and minority communities at greater risk of lead exposure due to the financial burden of replacing private service lines.