Monitoring the aftermath of Flint drinking water contamination crisis: Another case of sampling bias?

Abstract

The delay in reporting high levels of lead in Flint drinking water, following the city’s switch to the Flint River as its water supply, was partially caused by the biased selection of sampling sites away from the lead pipe network. Since Flint returned to its pre-crisis source of drinking water, the State has been monitoring water lead levels (WLL) at selected “sentinel” sites. In a first phase that lasted two months, 739 residences were sampled, most of them bi-weekly, to determine the general health of the distribution system and to track temporal changes in lead levels. During the same period, water samples were also collected through a voluntary program whereby concerned citizens received free testing kits and conducted sampling on their own. State officials relied on the former data to demonstrate the steady improvement in water quality. A recent analysis of data collected by voluntary sampling revealed, however, an opposite trend with lead levels increasing over time. This paper looks at potential sampling bias to explain such differences. Although houses with higher WLL were more likely to be sampled repeatedly, voluntary sampling turned out to reproduce fairly well the main characteristics (i.e. presence of lead service lines (LSL), construction year) of Flint housing stock. State-controlled sampling was less representative; e.g., sentinel sites with LSL were mostly built between 1935 and 1950 in lower poverty areas, which might hamper our ability to disentangle the effects of LSL and premise plumbing (lead fixtures and pipes present within old houses) on WLL. Also, there was no sentinel site with LSL in two of the most impoverished wards, including where the percentage of children with elevated blood lead levels tripled following the switch in water supply. Correcting for sampling bias narrowed the gap between sampling programs, yet overall temporal trends are still opposite.

How geostatistics can help you find lead and galvanized water service lines: The case of Flint, MI

“…Interestingly, only 5% and 11.3% of lines inspected in these two census units were classified as lead and galvanized, respectively. At the same time, these two block groups had a poverty level of 44.8%, much lower than the average for the City of Flint (66.3%) and Ward 7 (57.6%), which confirms the socio-economic bias mentioned in recent studies (Goovaerts, 2017a, b). …”

“…Kernel smoothing introduced in Goovaerts (2017b) was used to explore how the relative frequency of LSLs, GSLs, and copper lines changes with built year. Every year between 1895 and 2010, frequencies of occurrence of the three types of SL material were computed from all houses built within an 11-year window (e.g., 1916–1926 for year 1921).…”

“…(2016), and iii) environmental justice considerations, specifically lead paint indicators, minority population, and low income derived from EPA Environmental Justice Mapping and Screening Tool known as EJSCREEN (US EPA, 2016b). As the MDEQ campaign progressed and houses built from the late 30s to the late 40s turned out to be the main housing segment with LSLs, the sampling started targeting specifically houses built during that period (Bryce Feighner, personal communication, March 2, 2017), which explains the preferential sampling noticed in earlier studies (Goovaerts 2017a,b). …”

Flint Drinking Water Crisis: A First Attempt to Model Geostatistically the Space-Time Distribution of Water Lead Levels

“…presence of houses with lead-based paint, minority population, and lower socio-economic households). This initial set evolved between sampling rounds as some residents stopped participating, while others asked to be included in the network (Goovaerts 2017b), which explains the fluctuation in the number of sampled sites during the first five rounds S1-S5: 607-621 (Table 14.1). Fewer sites (149-178) were then part of the "Extended Sentinel Site Program".…”

A Data Science Approach to Understanding Residential Water Contamination in Flint

“…In addition, [4] provides an overview of the water crisis and discusses strategies for risk management in Flint. Further, there is some work analyzing some similar trends that we observe in lead levels over time [8,9]. But to the best of our knowledge, we are the rst to apply predictive modeling techniques to help with the Flint Water Crisis.…”