JJ Wedgworth, MS, PhD Candidate University of Alabama Department of Biological Sciences

Our Team Joe Brown PhD PE, London School of Tropical Medicine and Hygiene, Principal Investigator Pauline Johnson PhD, UA CCEE, Principle Investigator Julie Olson PhD, UA Biological Sciences (co-PI) Christine Stauber PhD, GSU Environmental Health (co- PI) Mark Elliott PhD, UA CCEE JJ Wedgworth, PhD candidate, UA Biological Sciences Phillip Grammer MS, PhD student, UA CCEE Rick Forehand MS, UA CCEE alumnus Daniel Bunei MS, UA CCEE alumnus

Outline Background and context: Alabama’s Black Belt Pilot data and hypothesis generation Goals Methods overview Preliminary data Next steps

Alabama’s Black Belt Common Demographic and Socio-economic Characteristics High Poverty High Unemployment Decreasing Population High Percentage of Minorities Common Themes Decaying infrastructure Poor access to basic services and health care High percentage of vulnerable people (the young, elderly and infirm)

2010 Black Belt in Comparison County 1County 2County 3AlabamaUS Population15,42113,47811,4824,802,740311,591,917 Population Change -2.2%-2.1%-1.6%0.5%0.9% Population Density/ mi Living in Poverty 24.6%34.8%38.5%17.1%13.8% Median Income$29,299$25,338$23,491$42,081$51,914 Public Water81.5%91.4%61.7%89%86% On-site Septic60.3%55.4%53.7%43.6%24.1% “non-perc” soils77%74%83%NA

PWS Violations Alabama > 8x 197x L Talebi > 40x

Small Rural System Challenges 1. More than 94 percent of the nation’s 156,000 public water systems serve fewer than 3,300 persons (EPA 2009). This results in wide service areas with disperse populations. 2. Small-scale, decentralized, or rural systems may be particularly susceptible to problems as infrastructure ages (ADPH 2009). Aging infrastructure leads to an increase in operation and maintenance challenges. 3. All of these issues combined make it increasingly more difficult for systems to meet the regulatory requirements.

– Water Quality and Wastewater survey in 3 Counties: 14 water systems, 900 households, 18 months 1. Assess public health impacts associated with small, rural water supply system performance and water quality. 2. Conduct microbial risk assessments to identify sources of microbial contamination. Propose risk reduction strategies for rural systems. 3. Identify possible transmission pathways for waterborne pathogens. 4. Identify low-cost, practicable, sustainable risk mitigation strategies to protect public health. EPA-STAR

Household level Health Data surveys POU Water Quality Flamed/Un-flamed samples System level Water distribution: System attributes, upgrades, O&M OSS Wastewater system evaluation Data Collection

Field and Lab Quality Testing Project Components Physical Tests Chemical Tests Operator Surveys and Water System l Membrane Tests Household WASH Surveys Biological Tests Water is tested for: pH Free and total chlorine Water is tested for: Total coliform E. coli Positives: DNA source tracking : human/animal origin Project Components Physical Tests Chemical Tests Operator Surveys and Water System l Membrane Tests Household WASH Surveys Biological Tests Water is tested for: pH Free and total chlorine Water is tested for: Total coliform E. coli Positives: DNA source tracking : human/animal origin Project Components Physical Tests Chemical Tests Operator Surveys and Water System l Membrane Tests Household WASH Surveys Biological Tests Water is tested for: pH Free and total chlorine Water is tested for: Total coliform E. coli Positives: DNA source tracking : human/animal origin Parameters Physical Turbidity, Pressure Chemical Free & Total Cl, pH Dead End Ultrafiltration for Identification of Pathogens System Performance Data Microbial source tracking

Not in the Job Description

Household Level Water Sampling A total of 900 households were visited and samples were taken from faucets (grab samples) and from outdoor taps (flamed samples) 16.7% of all flamed samples were + for total coliforms 12.2 % of all grab samples were + for total coliforms < 1% of either type of samples were positive for E. coli FIB contamination was not associated with any reported symptom of gastrointestinal illness (diarrhea, vomiting, nausea or abdominal cramping)

Low Pressure, Intermittent Service and GI Symptoms Reports of low water pressure were associated with any symptoms of GI illness, reported watery diarrhea and vomiting. Reported intermittent service was also associated with reported symptoms of GI illness, watery diarrhea and vomiting.

Measured vs Reported Water Pressure

Summary Relatively high percentage of samples positive for TC, lower than expected number of E. coli positives. Significant health associations emerging with some water quality measures including reported low pressure and intermittent service. No association with reported sanitation conditions. Data collection and analysis are ongoing System-level samples are of central importance to study questions At-risk areas emerging when merging household and system data

Next Steps System Level Samples 10 sample points for each system chosen based on location within the system and areas of vulnerability 100 liter sample taken at each sample point 4 time points Sample analyzed for: pH, turbidity, pressure, free and total chlorine Total coliform, E. coli, and Enterococci by IDEXX Coliphage by Single Agar Layer-EPA 1602 Heteroptrophic Plate Count Cryptosporidium, Giardia, norovirus, adenovirus, and potentially others

Acknowledgments All Project Staff and Students CDC Emory University University of Alabama Georgia State University LSTMH Local Water System Operators Community Partner Household participants Funding Department of Biological Sciences Center for Community Based Partnerships (CCBP) EPA STAR ***DISCLAIMER: Although the research described in the article has been funded wholly or in part by the United States Environmental Protection Agency through grant R to the University of Alabama and Georgia State University, it has not been subject to the Agency’s required peer and policy review and therefore does not necessarily reflect the views of the Agency and no official endorsement should be inferred.

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