How Big Data and algorithms are slashing the cost of fixing Flint’s water crisis

The water crisis in Flint highlights a number of serious problems: a public health outbreak, inadequate urban infrastructure, environmental injustice and political failures. But when it comes to recovery, the central challenge, and one that has received relatively little attention, is the lack of useful information and understanding.

Who is most at risk? Where are the harmful sources of lead? Where should resources be allocated? Using modern big-data tools, professors from the U-M can answer these questions and help inform the response to this crisis.

With the support of a student team at U-M, they have aggregated a trove of available data around Flint’s water issues, including water test results, records of the service lines that deliver water to homes, information on parcels of land and water usage. Leveraging new algorithmic and statistical tools, they are able to produce a significantly more complete picture of the risks and challenges in Flint.

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