title: The drinking water contamination crisis in Flint: Modeling temporal trends of lead level since returning to Detroit water system.
abstract: Since Flint returned to its pre-crisis source of drinking water close to 25,000 water samples have been collected and tested for lead and copper in >10,000 residences. This paper presents the first analysis and time trend modeling of lead data, providing new insights about the impact of this intervention. The analysis started with geocoding all water lead levels (WLL) measured during an 11-month period following the return to the Detroit water supply. Each data was allocated to the corresponding tax parcel unit and linked to secondary datasets, such as the composition of service lines, year built, or census tract poverty level. Only data collected on residential parcels within the City limits were used in the analysis. One key feature of Flint data is their collection through two different sampling initiatives: (i) voluntary or homeowner-driven sampling whereby concerned citizens decided to acquire a testing kit and conduct sampling on their own (non-sentinel sites), and (ii) State-controlled sampling where data were collected bi-weekly at selected sites after training of residents by technical teams (sentinel sites). Temporal trends modeled from these two datasets were found to be statistically different with fewer sentinel data exceeding WLL thresholds ranging from 10 to 50μg/L. Even after adjusting for housing characteristics the odds ratio (OR) of measuring WLL above 15μg/L at non-sentinel sites is significantly >1 (OR=1.480) and it increases with the threshold (OR=2.055 for 50μg/L). Joinpoint regression showed that the city-wide percentage of WLL data above 15μg/L displayed four successive trends since the return to Detroit Water System. Despite the recent improvement in water quality, the culprit for differences between sampling programs needs to be identified as it impacts exposure assessment and might influence whether there is compliance or not with the Lead and Copper Rule.
authors.affiliation: BioMedware Inc., PO Box 1577, Ann Arbor, MI 48106, USA. Electronic address: goovaerts@biomedware.com.
authors.forename: Pierre
authors.initials: P
authors.lastname: Goovaerts
mesh_terms: D002947:Cities; D003300:Copper / Q000032:analysis; D060766:Drinking Water / Q000032:analysis*; D007854:Lead / Q000032:analysis; D008824:Michigan; D014874:Water Pollutants, Chemical / Q000032:analysis*; D014876:Water Pollution; D014881:Water Supply
chemical_list: D060766:Drinking Water; D014874:Water Pollutants, Chemical; D007854:Lead; D003300:Copper
keywords: Generalized estimating equations; Joinpoint regression; Lead and copper rule; Lead service lines; Sampling