Over 1.7 million Virginians rely on private water systems to supply household water. The heaviest reliance on these systems occurs in rural areas, which are often underserved in terms of financial resources and access to environmental health education. As the Safe Drinking Water Act (SDWA) does not regulate private water systems, it is the sole responsibility of the homeowner to maintain and monitor these systems.

Previous limited studies indicate that microbial contamination of drinking water from private wells and springs is far from uncommon, ranging from 10% to 68%, depending on type of organism and geological region. With the exception of one thirty-year old government study on rural water supplies, there have been no documented investigations of links between private system water contamination and household demographic characteristics, making the design of effective public health interventions, very difficult.

The goal of the present study is to identify potential associations between concentrations of fecal indicator bacteria (e.g. coliforms, E. coli) in 831 samples collected at the point-of-use in homes with private water supply systems and homeowner-provided demographic data (e.g. homeowner age, household income, education, water quality perception). Household income and the education of the perceived head of household were determined to have an association with bacteria concentrations. However, when a model was developed to evaluate strong associations between total coliform presence and potential predictors, no demographic parameters were deemed significant enough to be included in the final model. Of the 831 samples tested, 349 (42%) of samples tested positive for total coliform and 55 (6.6%) tested positive for E. coli contamination. Chemical and microbial source tracking efforts using fluorometry and qPCR suggested possible E. coli contamination from human septage in 21 cases.  The findings of this research can ultimately aid in determining effective strategies for public health intervention and gain a better understanding of interactions between demographic data and private system water quality.