+ relationships between fecal indicator bacteria prevalence in private water supplies and...
TRANSCRIPT
+Relationships Between Fecal Indicator Bacteria Prevalence in Private Water Supplies and Demographic Data in Virginia
Tamara Smith, E.I.M.S. Candidate, Virginia Tech
2012 Water and Health Conference Chapel Hill, NC31 October 2012
+Presentation Outline
Introduction-What are Private Drinking Water Systems?
Research Objectives- What Do We Hope To Accomplish?
Methods- How It Happens
Initial Results- What Have We Done So Far?
Conclusions-What Did We Learn?
Future Work-What’s Next?
+What are Private Drinking Water Systems? Serves < 25 persons and
has < 15 connections
Types: Drilled, dug, and bored
wells Springs Cisterns
Depend on groundwater
If properly maintained, these systems can provide potable drinking water.
+Potential Problems
23 and 45 million Americans rely on private water supply systems for drinking water.
Not regulated by the Safe Drinking Water Act (SWDA) for two main reasons: Private property rights Dispersion of private water systems nationwide
Over the past 30 years, the proportion of Centers of Disease Control (CDC) annual reported outbreaks associated with private water supplies has increased.1
1. Craun et al. (2010)
+Potential Problems Cont’d
Previous studies have attempted to correlate well construction and local geology with observations of water quality. Aquifer composition(such as limestone and fractured rock) can
increase contaminant exposure. 2
Poor construction and proximity to potential sources of contamination (e.g. septic tank) can lead increased contaminant exposure.3
Although inadequate water and sanitation is often linked to poverty, there have been no studies linking private system water quality and demographic data.
2. Brunkard et al. (2011) 3. Swistock and Sharpe (2005)
+Private Drinking Water Systems in Virginia: A Particular Concern Over 1.7 million households rely on
private water systems for drinking water.4
The majority of households in 60 out of 95 counties rely on private water systems.5
In 52 counties, the number of households being served by private water supplies is increasing at a rate greater the households currently being joined to municipal systems.5
4. Gatseyer and Vaswani (2004) 5. US Census Bureau (1990)
Scientific Investigations Report (2009)
+Overall Goal and Objectives
Identify relationships between the prevalence of fecal indicator bacteria from privately supplied water systems and demographic data with the following objectives:
1) Quantification of total coliform (TC) bacteria and E. coli (EC) prevalence in water samples from private systems collected from the point-of-use;
2) Identification of possible correlations between demographic data and fecal indicator bacteria;
3) Applying a chemical source tracking technique (i.e. fluorometry) to identify possible human contamination (i.e. sewage intrusion).
+Virginia Household Water Quality Program (VAHWQP)
VAHWQP’s objective is to improve the water quality and health of Virginians using private water supplies.
A program a part of Virginia Cooperative Extension.
Currently partnering with the Southeast Rural Community Project (SERCAP).
+VAHWQP-Drinking Water Clinics
1. Kickoff Meeting
4. Interpretation Meeting
2. Sample Collection
3. Analysis
+Sample Collection
Survey in kits contains: Homeowner perception of
water quality Homeowner-supplied
demographic data
+Sample Collection and Analysis
Household Samples (Four
Bottles)
2 Bottles (Bacterial Analysis)
100 mL- TC/EC Presence &
Quantification
250 mL- ST
2 Bottles (Other Analysis)
pH, Conductivity, Heavy Metals,
etc.
+TC/EC Detection & Quantification
Presence- Colilert (IDEXX) defined substrate technology
Quantification-Quanti-tray/2000 (MPN)
~24h incubation
~35°C±0.5°C
+Chemical Source Tracking
Source Tracking is used to determine the source of fecal bacteria. Usually a specific marker is used that is linked to a specific source of fecal contamination.
Typically used for for surface waters, but are starting to become used for drinking water.
Fluorometry analyzes fluorescence in a sample. Optical brighteners are likely indicative of fecal contamination via septic sewage.
+Primary and Secondary Maximum Contaminant Levels Maximum Contaminant Levels (MCL)
refer to the highest that is allowed in drinking water by the US EPA.
Primary MCLs are standards that are health-based. These include Total Coliforms, E. coli, and Nitrate.
Secondary MCLS are non-enforceable guidelines based on a contaminants’ cosmetic and aesthetic effects.
Although not applied to private systems can be used as a guideline
Some MCLs of Concern4
Contaminant MCL
Total Coliforms No more than 5% positive samples in one month.
Fecal Coliforms/E. coli
Any sample tested positive from a repeat of total coliform or the reverse is true, then is in violation of MCL.
Nitrate 10 mg/L
4. US EPA (2011)
+Objective 1: Overall Prevalence of Fecal Indicator Bacteria Positive Samples2012 Drinking Water Clinics (n=543)
Counties Participating
28
Percent Positive for TC
38%
Average TC Concentration
~118 MPN/ 100 mL
Percent Positive for EC
6%
Average EC Concentration
~11 MPN/ 100 mL
Nitrate Below MCL
Average Nitrate Concentration
0.80 mg/L
Although these bacteria prevalences seem high, it coincides with previous studies in private water supplies5,6,7,8,9,10,11
5. Sandhu et al. (1979) 6. Lamka et al. (1980) 7. Sworobuk et al.( 1987) 8. Bauder et al. (1991) 9. Kross et al. (1993) 10. Gosselin et al. (1997) 11. Borchardt et al. (2003)
+Objective 1: Cumulative Distribution for Total Coliform Concentrations
Non-zero samples around 61st percentile.
13 samples above detection limit
0.6 0.65 0.7 0.75 0.8 0.85 0.9 0.95 10
500
1000
1500
2000
2500
0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 10
500
1000
1500
2000
2500
Percentile
TC
MP
N/
100 m
L
+Objective 1: Cumulative Distribution for E. coli Concentrations
0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 10
500
1000
1500
2000
2500
Percentile
EC
MP
N/
100 m
L
Non-zero samples around 94th percentile.
1 sample above detection limit
0.9 0.92 0.94 0.96 0.98 10
500
1000
1500
2000
2500
+Objective 2. Total Coliform Presence by Income Level
<$10K $11K-$24K $25K-$40K $41K-$64K >$65K0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100% n=476
Income Level
Perc
en
t P
osit
ive f
or
Each
Cate
gory
n=15 n=252
n=88
n=86
n=35
+Objective 2. E. coli Presence by Income Level
<$10K $11K-$24K $25K-$40K $41K-$64K >$65K0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100% n=476
Income Level
Perc
en
t P
osit
ive f
or
Each
Cate
gory
n=15n=252
n=88n=86
n=35
+
0%20%40%60%80%
100% n=516
Education Level
Perc
en
t P
osit
ive f
or
Each
Cate
gory
Objective 2. Total Coliform Presence by Education Level
n=7
n=81
n=17
n=146
n=149
n=116
+Objective 2. E. coli Presence by Education Level
0%20%40%60%80%
100% n=516
Education Level
Perc
en
t P
osit
ive f
or
Each
Cate
gory
n=7n=81n=17 n=146n=149
n=116
+Objective 2. Correlations Between Bacteria Prevalence and Demographics
Chi-squared Test were used to determine differences in categorical distributions between TC/EC Presence and Income
Level TC/EC Presence and
Education Level
Alpha= 0.05
For TC Presence P-value
Income Level 0.0025
Education Level 0.0516
For EC Presence P-value
Income Level 0.0119
Education Level 0.0730
+Objective 3. Application of Chemical Source Tracking Technique
11/543 were tested positive for optical brighteners
45.5% positive for TC; 36.4% positive for EC
Average TC concentration: 503.1 MPN/100 mL
Average EC concentration: 249.6 MPN/100 mL
27% of systems have some type of treatment (i.e. chlorination, filtering, etc.)
18.2% of systems 100 ft or less to septic system drain field
County Location: 27.3% Lancaster, 27.3% Northumberland, 18.2% Tazewell, 18.2% Charlotte
72.7% households <$65K; 18.2% >$65k
+Conclusions
There is presence of total coliform and E. coli bacteria in private drinking water supplies.
TC and EC presence are statistically different between income levels, but not necessarily for education levels.
Fluorometry positive samples have some similarities in location and income level, but not all tested positive for E. coli contamination.
+Future Work
Continuing analysis of 2012 Drinking Water Clinic Data
Analysis of E. coli-positive samples for Bacteroides human marker (BacHum) via qPCR
Further explore relationships between fluorometry positive samples
Statistical correlations between E. coli incidence and self-reported illness
+Acknowledgements Dr. Leigh-Anne Krometis
All the members of my research committee: Dr. Brian Benham, Dr. Charles Hagedorn III, and Susan Marmagas
VAHWQP & The Krometis Research Group
Sponsor: USDA-NIFA Rural Health Education Program Competitive Grant No. 2011-46100-31115