Economic Analysis for the 

Final Ground Water Rule 
 

Office of Water (4606-M) EPA 815-R-06-014 October 2006 www.epa.gov/safewater
Economic Analysis for the i October 2006

Final Ground Water Rule

Contents

Appendices ........................................................................ vii

Exhibits ............................................................................ vi

Acronyms ......................................................................... xiii

Health Risk Reduction and Cost Analysis ............................................... xvi

Executive Summary

ES.1 Need for the Rule . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ES-1

ES.2 Consideration of Regulatory Alternatives . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ES-2

ES.3 Summary of the Final GWR Requirements . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ES-2

ES.4 Systems Subject to the GWR . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ES-6

ES.5 National Benefits and Costs of the GWR . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ES-8

ES.5.1 Derivation of Benefits . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ES-9

ES.5.2 Derivation of Costs . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ES-14

ES.6 Projected Impacts on Household Costs . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ES-15

ES.7 Comparison of Benefits and Costs, and of Regulatory Alternatives of the GWR . . ES-16

ES.8 Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ES-19

1. Introduction

1.1 Summary of the Ground Water Rule . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1-1

1.2 Document Organization . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1-2

1.3 Calculations and Citations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1-2

2. Statement of Need for the Rule

2.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2-1

2.1.1 Description of the Issue . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2-1

2.2 Public Health Concerns to Be Addressed . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2-2

2.2.1 Contaminants and Their Health Effects . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2-2

2.2.2 Sources of Contaminants . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2-5

2.2.2.1 Ground Water Contamination through the Subsurface . . . . . . . . . . . . 2-6

2.2.2.2 Ground Water Contamination through the Wellhead . . . . . . . . . . . . . 2-6

2.2.2.3 Contamination of Drinking Water in Distribution Systems . . . . . . . . . 2-7

2.3 Statutory Authority for Promulgating the Rule . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2-8

2.4 Regulatory History . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2-8

2.4.1 1979 Total Trihalomethane Rule . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2-9

2.4.2 1989 Total Coliform Rule . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2-9

2.4.3 1996 Information Collection Rule . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2-9

2.4.4 1998 Stage 1 Disinfectants and Disinfection Byproducts Rule . . . . . . . . . . . 2-10

2.4.5 2001 Arsenic Rule . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2-10

2.4.6 2006 Stage 2 Disinfectants and Disinfection Byproducts Rule . . . . . . . . . . . 2-10

2.4.7 Underground Injection Control Program . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2-11

2.5 Economic Rationale . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2-12
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3. Consideration of Regulatory Alternatives

3.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3-1

3.2 Process for Development of Regulatory Alternatives . . . . . . . . . . . . . . . . . . . . . . . . . . 3-1

3.3 Regulatory Alternatives Considered . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3-2

3.4 Final Rule Requirements . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3-3

3.4.1 Mandatory Rule Components . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3-6

3.4.2 Optional Provision . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3-11

3.5 Other Changes Since Proposal . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3-11

4. Baseline Conditions

4.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4-1

4.2 Industry Profile . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4-1

4.2.1 Data Sources . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4-2

4.2.2 Water System Characterization . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4-2

4.2.3 Baseline Number of Systems, Entry Points, and Population . . . . . . . . . . . . . . 4-4

4.2.4 Water Treatment Plant Design and Average Daily Flows . . . . . . . . . . . . . . . 4-15

4.2.5 Treatment Practices Baseline . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4-17

4.2.6 Number of Households Served . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4-17

4.2.7 Triggered Monitoring Baseline . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4-18

4.3 Water Quality Baseline . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4-23

4.3.1 Background . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4-24

4.3.1.1 Representative Pathogens . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4-24

4.3.2 Enterovirus and E. coli Occurrence in PWS Well Source Ground Water . . . 4-25

4.3.2.1 Lieberman et al. 2002 Study . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4-27

4.3.2.2 Abbaszadegan et al. 2003 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4-29

4.3.2.3 Pennsylvania Noncommunity Wells (Lindsey et al., 2002) . . . . . . . 4-31

4.3.2.4 Southeast Michigan (Francy et al., 2004) . . . . . . . . . . . . . . . . . . . . 4-32

4.3.2.5 New Jersey (Atherholt et al., 2003) . . . . . . . . . . . . . . . . . . . . . . . . . 4-33

4.3.2.6 Missouri Ozark Plateau #1 (Davis and Witt, 2000) . . . . . . . . . . . . . 4-34

4.3.2.7 Missouri Ozark Plateau #2 (Femmer, 2000) . . . . . . . . . . . . . . . . . . 4-35

4.3.2.8 Wisconsin Migrant Worker Camp (USEPA et al., 1998) . . . . . . . . 4-35

4.3.2.9 New England (Doherty et al., 1998) . . . . . . . . . . . . . . . . . . . . . . . . 4-36

4.3.2.10 Three-State Study: (Wisconsin-Battigelli, 1999) . . . . . . . . . . . . . . . 4-37

4.3.2.11 Three-State Study: (Maryland-Banks et al, 2001) . . . . . . . . . . . . . . 4-37

4.3.2.12 Three-State Study: (Maryland-Banks and Battigelli, 2002) . . . . . . 4-38

4.3.2.13 Three-State Study: (Minnesota-Banks and Battigelli, 2002) . . . . . . 4-38

4.3.2.14 EPA Vulnerability Study (USEPA, 1998c) . . . . . . . . . . . . . . . . . . . 4-39

4.3.2.15 Montana Study . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4-39

4.3.2.16 Summary of New Data . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4-40

4.3.3 Well Vulnerability . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4-46

4.3.3.1 Background . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4-46

4.3.3.2 Estimating percent wells in vulnerability categories . . . . . . . . . . . . . 4-47

4.3.4 Occurrence Analyses . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4-49

4.3.4.1 Viral and Fecal Indicator Hit Rates . . . . . . . . . . . . . . . . . . . . . . . . . . 4-50

4.3.4.2 Pathogen Concentration Analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . 4-64

4.4 Outbreak Baseline and Causes of Contamination . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4-68

4.5 Summary of Uncertainties in Development of GWR Baselines . . . . . . . . . . . . . . . . . 4-70
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Final Ground Water Rule

5. Benefits Analysis

5.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5-1

5.1.1 Quantified Benefits . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5-2

5.1.2 Nonquantified Benefits . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5-4

5.2 Quantified Health Benefits from Reduction in Exposure to Viruses . . . . . . . . . . . . . . . 5-4

5.2.1 Overview of Risk Assessment Methodology . . . . . . . . . . . . . . . . . . . . . . . . . . 5-5

5.2.2 Hazard Identification . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5-7

5.2.2.1 Health Effects of Viral Infections . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5-7

5.2.2.2 Sensitive Subgroups . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5-8

5.2.3 Exposure Assessment . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5-11

5.2.3.1 Source Water Viral Occurrence and Concentration . . . . . . . . . . . . . . 5-12

5.2.3.2 Finished Water Concentrations in Disinfecting 

Ground Water Systems . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5-12

5.2.3.3 Size of Exposed Population . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5-13

5.2.3.4 Drinking Water Consumption Factors . . . . . . . . . . . . . . . . . . . . . . . . 5-13

5.2.4 Probability of Infection, Illness, and Mortality . . . . . . . . . . . . . . . . . . . . . . . . 5-17

5.2.4.1 Infectivity from Dose response Modeling of Human 

Challenge Study Data . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5-17

5.2.4.2 Morbidity and Mortality Data Sources and Uncertainty . . . . . . . . . . 5-21

5.2.4.3 Quantified GWR Benefits (Predictions of Illnesses and Deaths)–

Model Input Values . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5-26

5.2.5 Risk Characterization . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5-34

5.2.5.1 Risk Assessment Methodology for Baseline (Pre-GWR) 

Risk Calculations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5-34

5.2.5.2 Results of the Baseline Risk Calculations . . . . . . . . . . . . . . . . . . . . . 5-42

5.2.5.3 Baseline Illnesses and Deaths in Sensitive Subgroups . . . . . . . . . . . 5-43

5.2.5.4 Baseline Risk to a Highly Exposed Individual . . . . . . . . . . . . . . . . . 5-44

5.2.5.5 Sensitivity of Baseline Estimates to Quantified Uncertainty Inputs . 5-45

5.2.5.6 Methodology for Estimating Risk Reductions . . . . . . . . . . . . . . . . . . 5-48

5.2.5.7 Results for Risk Reduction for the Final GWR . . . . . . . . . . . . . . . . . 5-54

5.2.5.8 Results for Reduction in Individual Risks for the Final GWR . . . . . 5-56

5.2.5.9 Potential Increases in Health Risks . . . . . . . . . . . . . . . . . . . . . . . . . . 5-60

5.3 Monetized Benefits from Reduction in Exposure to Waterborne Pathogens . . . . . . . . 5-61

5.3.1 Value of Reduction in Type A and Type B Virus Cases . . . . . . . . . . . . . . . . 5-61

5.3.1.1 Value of Viral Illnesses Avoided . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5-61

5.3.1.2 Value of Mortality Avoided . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5-76

5.3.1.3 Measuring Benefits Over the GWR Implementation Schedule . . . . . 5-76

5.3.1.4 Adjustments for Income Elasticity . . . . . . . . . . . . . . . . . . . . . . . . . . . 5-76

5.3.1.5 Present Value of Future Benefits . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5-78

5.3.2 Summary of Quantified Benefits of GWR . . . . . . . . . . . . . . . . . . . . . . . . . . . 5-78

5.3.3 Quantified Benefits to Sensitive Subpopulations . . . . . . . . . . . . . . . . . . . . . . 5-81

 5.4 Nonquantified Benefits of GWR Provisions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5-82

5.4.1 Decreased Incidence of Illness Caused by Other Type A Viruses . . . . . . . . . 5-82

5.4.1.1 Norovirus . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5-82

5.4.1.2 Other Type A viruses . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5-86

5.4.2 Decreased Incidence of Other Illness Caused by Type B Viruses . . . . . . . . . 5-88

5.4.3 Decreased Incidence of Bacterial Illness and Death . . . . . . . . . . . . . . . . . . . . 5-92

5.4.3.1 Bacterial Pathogen Occurrence . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5-92
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5.4.3.2 Estimate of Potentially Avoided Bacterial Caused Deaths 

by GWR . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5-95

5.4.3.3 Estimate of a Hospitalization Rate for Waterborne Bacterial 

Illness . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5-98

5.4.4 Other Chronic and Acute Illness Potentially Avoided . . . . . . . . . . . . . . . . . 5-100

5.4.5 Reduction in Outbreak Risk and Response Costs . . . . . . . . . . . . . . . . . . . . . 5-102

5.4.6 Reduced Disinfection Treatment Failure Rates and Associated 

Waterborne Disease . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5-103

5.4.7 Distribution System Contamination . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5-104

5.4.8 Benefits From the Reduction of Co-Occurring and Emerging 

Contaminants . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5-104

5.4.9 Reduced Uncertainty/Costs to Households to Avert Infection . . . . . . . . . . . 5-105

5.4.10 Summary of Nonquantified Benefits . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5-105

5.5 Alternative Analyses . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5-107

5.5.1 Alternative Viral Concentration Baseline . . . . . . . . . . . . . . . . . . . . . . . . . . . 5-107

5.5.2 Alternative Type A Dose response . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5-107

5.5.3 Alternative Type B Dose Response . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5-108

5.5.4 Alternative Occurrence (Peer Review) Data . . . . . . . . . . . . . . . . . . . . . . . . . 5-108

5.6 Summary of Uncertainty . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5-109

5.7 Regulatory Alternatives . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5-112

6. Cost Analysis

6.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6-1

6.2 General Costing Assumptions and Methodology . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6-2

6.2.1 Labor Rates . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6-2

6.2.2 Laboratory Fees . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6-4

6.2.3 Technology Unit Costs and Compliance Forecasts . . . . . . . . . . . . . . . . . . . . . 6-5

6.2.4 Cost Model . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6-6

6.2.5 Modeled Variability and Uncertainty in National Costs . . . . . . . . . . . . . . . . . . 6-6

6.3 Projecting and Discounting National Costs . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6-6

6.4 Derivation of Costs for Systems and States . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6-8

6.4.1 Rule Implementation and Annual Administration . . . . . . . . . . . . . . . . . . . . . 6-11

6.4.2 Sanitary Surveys . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6-16

6.4.3 Triggered Source Water Monitoring . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6-25

6.4.4 Corrective Actions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6-32

6.4.4.1 Sanitary Survey Corrective Actions . . . . . . . . . . . . . . . . . . . . . . . . . . 6-32

6.4.4.2 Source Water Contamination Corrective Actions . . . . . . . . . . . . . . . 6-36

6.4.5 Compliance Monitoring . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6-44

6.4.6 Total Capital and One-Time Costs . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6-53

6.4.7 Uncertainty in Unit Costs . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6-53

6.4.8 Alternative Cost Analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6-54

6.5 Household Costs . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6-54

6.6 Nonquantified Costs . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6-56

6.7 Uncertainty Analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6-57

6.8 Total Annualized Cost for Final GWR Regulatory Alternative . . . . . . . . . . . . . . . . . . 6-61

6.9 Comparison of Regulatory Alternatives . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6-62
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7. Economic Impact Analysis

7.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7-1

7.2 Regulatory Flexibility Act and Small Business Regulatory Enforcement Fairness Act 7-1

7.3 Small Drinking Water System Variances . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7-4

7.4 Feasible Treatment Technologies for All Systems . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7-4

7.5 Effect of Compliance with the GWR on the Technical, Financial, and 

Managerial Capacity of Public Water Systems . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7-4

7.5.1 Requirements of the Final GWR . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7-5

7.5.2 Systems Subject to the GWR . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7-6

7.5.3 Impact of the GWR on System Capacity . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7-6

7.5.4 Derivation of GWR Scores . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7-9

7.5.4.1 Small Water Systems (Those Serving 10,000 or Fewer People) . . . . . 7-9

7.5.4.2 Large Water Systems (Those Serving at Least 10,000 People) . . . . . 7-10

7.6 Paperwork Reduction Act . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7-10

7.7 Unfunded Mandates Reform Act . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7-12

7.7.1 Social Benefits and Costs . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7-13

7.7.2 Disproportionate Budgetary Effects . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7-15

7.7.3 Macroeconomic Effects . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7-17

7.7.4 Consultation with Small Governments . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7-18

7.7.5 Consultation with State, Local, and Tribal Governments . . . . . . . . . . . . . . . . 7-18

7.7.6 Regulatory Alternatives Considered . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7-19

7.7.7 Impacts on Small Governments . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7-19

7.8 Indian Tribal Governments . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7-19

7.9 Impacts on Sensitive Subpopulations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7-22

7.9.1 Protection of Children from Environmental Health Risks and Safety Risks . 7-23

7.10 Environmental Justice . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7-23

7.11 Federalism . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7-24

7.12 Actions Concerning Regulations That Significantly Affect Energy Supply, 

Distribution, or Use . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7-25

8. Comparison of Benefits and Costs of the LT2ESWTR

8.1 National Quantified Benefits and Costs of the GWR . . . . . . . . . . . . . . . . . . . . . . . . . . 8-1

8.1.1 National Quantified Benefits Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8-1

8.1.2 National Cost Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8-6

8.1.3 Comparison of National Quantified Benefits and Costs . . . . . . . . . . . . . . . . . . 8-6

8.2 Effect of Uncertainties and Nonquantified Benefit/Cost Estimates on the 

Estimation of Net National Benefits . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8-8

8.3 Breakeven Analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8-9

8.4 Comparison of Regulatory Alternatives . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8-10

8.4.1 Comparison of Benefits and Costs . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8-11

8.4.2 Cost-Effectiveness Measures . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8-14

8.5 Summary of Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8-19

9. References
Economic Analysis for the vi October 2006

Final Ground Water Rule

Appendices

Appendix A: Calculations Supporting the Cost of Illness (COI) Analysis

Appendix B: Detail of Benefits Valuation Inputs

Appendix C: Benefits Detail

Appendix D: Costs Details

Appendix E: Potential Implications of Population Dynamics and Secondary Transmission of Infection

on the Benefits of the Groundwater Rule

Appendix F: Infectivity Dose Response Relationships: Description of Analysis Conducted to Select

Model Forms and Estimate Model Parameters

Appendix G: Summary Flowcharts for Baseline Risk and Benefits Model

Appendix H: Cost Effectiveness Analysis Using a Quality-Adjusted Life Years Approach

Appendix I: Analysis of Total Coliform Hit Rates in Drinking Water Systems With Ground Water

Sources

Appendix J: Changes in GWR Economic Analysis from Proposal to Final

Appendix K: Cost Details for Alternatives 1, 3, and 4

Appendix L: Summary Flow Charts for GWR Cost Model
Economic Analysis for the vii October 2006

Final Ground Water Rule

Exhibits 

Executive Summary

Exhibit ES.1 Flowchart of Compliance with GWR Requirements for Systems . . . . . . . . . . . . . . . . ES-4

Exhibit ES.2 Implementation Timeline for the GWR . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ES-5

Exhibit ES.3 Summary of Rule Implications . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ES-7

Exhibit ES.4 Summary of Annual Avoided Viral Illnesses and Deaths by System Type . . . . . . . . ES-10

Exhibit ES.5 Summary of Annualized Present Value Quantified Benefits ($Millions, 2003$) . . . ES-11

Exhibit ES.6 Summary of Benefits of the GWR . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ES-13

Exhibit ES.7 Total Initial Capital and One-Time Costs ($Millions, 2003$) . . . . . . . . . . . . . . . . . . ES-15

Exhibit ES.8 Total Annualized Present Value Costs of the GWR ($Millions, 2003$) . . . . . . . . . . ES-15

Exhibit ES.9 Summary of Annual Per-Household Costs for the GWR (2003$Year) . . . . . . . . . . . ES-16

Exhibit ES.10 Estimated Annualized National Benefits and Costs for the GWR 

($Millions, 2003$) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ES-17

1. Introduction

2. Statement of Need for the Rule

Exhibit 2.1 Examples of Illnesses Caused by Known or Suspected Waterborne Fecal Viral 

Pathogens . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2-4

Exhibit 2.2 Examples of Illnesses Caused by Common Waterborne Bacterial Pathogens . . . . . . . . 2-4

Exhibit 2.3 Etiology of Waterborne Outbreaks in Ground Water Systems,

1991-2000 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2-5

3. Consideration of Regulatory Alternatives

Exhibit 3.1 Flowchart of Mandatory PWS Ground Water Rule Requirements . . . . . . . . . . . . . . . . 3-5

4. Baseline Conditions

Exhibit 4.1 Ground Water Rule System Baseline . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4-6

Exhibit 4.2 Ground Water Rule System Baseline: Disinfecting and Nondisinfecting 

Systems . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4-8

Exhibit 4.3 Ground Water Rule Entry Point Baseline . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4-10

Exhibit 4.4 Ground Water Rule System Population Baseline . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4-12

Exhibit 4.5 Ground Water Rule Entry Point Population Baseline . . . . . . . . . . . . . . . . . . . . . . . . . 4-13

Exhibit 4.6 Design Flows and Average Daily Flows per Plant (MGD) . . . . . . . . . . . . . . . . . . . . . 4-16

Exhibit 4.7 Disinfection Treatment Practices for Disinfecting Ground Water Systems . . . . . . . . . 4-18

Exhibit 4.8 Ground Water Rule CWS Household Baseline . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4-18

Exhibit 4.9 Total Coliform Positive Hit Rates . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4-21

Exhibit 4.10 Estimated Number of Routine Total Coliform Samples 

Taken Per System, Per Year, by Type and Size of System . . . . . . . . . . . . . . . . . . . . . 4-22

Exhibit 4.11 Estimated Number of TC+ Samples Per System, Per Year, 

by System Size and System Type . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4-22

Exhibit 4.12 Results of the Abbaszadegan et al. 2003 Study . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4-30

Exhibit 4.13a New Data Available since publication of the Proposed GWR . . . . . . . . . . . . . . . . . . 4-42
Economic Analysis for the viii October 2006

Final Ground Water Rule

Exhibit 4.13b Virus Assays and Positives for 1,253 Wells Assayed for Viruses . . . . . . . . . . . . . . . . 4-45

Exhibit 4.13c E.coli Assays and Positives for 687 Wells Assayed for E.coli . . . . . . . . . . . . . . . . . . 4-45

Exhibit 4.13d Number of Virus and E.coli Assays . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4-46

Exhibit 4.14 Mean Percent of Systems with Acute or Monthly MCL Violations

by System Type and System Size . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4-48

Exhibit 4.15 Number and Percent of Systems Disinfecting, By Type of System . . . . . . . . . . . . . . 4-48

Exhibit 4.16 Categories of Indicator and Viral Classification Among PWS Wells in U.S. . . . . . . . 4-51

Exhibit 4.17 Median of 10,000 Estimates of P1, P2, P3, and P4

(with error bars showing the 5th and 95th percentiles) . . . . . . . . . . . . . . . . . . . . . . . . 4-55

Exhibit 4.18 Median of 10,000 Estimates of Pwell for Virus and Indicator

(with error bars showing the 5th and 95th percentiles) . . . . . . . . . . . . . . . . . . . . . . . . 4-56

Exhibit 4.19 Scatter Plot of Pwell Pairs for Indicators and Viruses . . . . . . . . . . . . . . . . . . . . . . . . . . 4-57

Exhibit 4.20 Density Function Shapes of Psample for Viruses . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4-58

Exhibit 4.21 Cumulative Distributions of Psample for Viruses . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4-58

Exhibit 4.22 Median of 10,000 Estimates of Psample for Virus and Indicator

(with error bars showing the 5th and 95th percentiles) . . . . . . . . . . . . . . . . . . . . . . . 4-59

Exhibit 4.23 Scatter Plot of Means of Psample Pairs for Indicators and Viruses . . . . . . . . . . . . . . . . . 4-60

Exhibit 4.24 Mean of Psample Versus Pwell for Viruses

(1,000 Pairs from Occurrence Model) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4-61

Exhibit 4.25 Mean of Psample Versus Pwell for Indicators

(1,000 Pairs from Occurrence Model) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4-61

Exhibit 4.26 Cumulative Probability of an Indicator Positive as a 

Function of Assay Number -- All Wells (used for cost analysis) . . . . . . . . . . . . . . . . 4-63

Exhibit 4.27 Cumulative Probability of an Indicator Positive as a Function of

Assay Number -- Virus Positive Wells (used for risk reduction analysis) . . . . . . . . . . 4-64

Exhibit 4.28 Summary of Virus Concentrations Observed

 in the Lieberman et al. 2002 Study . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4-66

Exhibit 4.29 Summary of Virus Concentrations Observed

 in the Abbaszadegan et al. 2003 Study . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4-67

Exhibit 4.30 Summary of Virus Concentrations Observed

 in the Pennsylvania Noncommunity Study . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4-68

Exhibit 4.31 Summary of Waterborne Disease Outbreaks Attributable to PWSs Served by 

Wells using Ground Water: 1991-2000* . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4-71

Exhibit 4.32 Summary of Uncertainties Affecting GWR Baseline Estimates . . . . . . . . . . . . . . . . . 4-73

5. Benefits Analysis

Exhibit 5.1 Overview of Quantified and Nonquantified GWR Benefits . . . . . . . . . . . . . . . . . . . . . 5-1

Exhibit 5.2 Overview of Viral Pathogen Risk Assessment and Benefits Valuation Procedure 

for Quantified Benefits (Main Analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5-3

Exhibit 5.3 Health Risk Assessment Framework . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5-6

Exhibit 5.4 Sensitive Populations in the United States . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5-9

Exhibit 5.5 Distribution of Individual Daily Drinking Water Consumptionby Age Group 

(L/person/day) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5-14

Exhibit 5.6 Derivation of Transient Noncommunity Water System Consumption Factor . . . . . . . 5-16

Exhibit 5.7 Estimated Exposure Days by System Type . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5-17

Exhibit 5.8 Rotavirus Dose-Response Data . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5-19

Exhibit 5.9 Echovirus Dose-Response Data . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5-19

Exhibit 5.10 Dose Response Assumptions of Viral Pathogens for the GWR Risk Assessment . . . 5-26
Economic Analysis for the ix October 2006

Final Ground Water Rule

Exhibit 5.11 Summary of Virus Watch Morbidity Data . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5-30

Exhibit 5.12 Summary Table of Risk Calculation Factors, Distribution Category (Variability,

Uncertainty, Constant) and Distribution Type) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5-37

Exhibit 5.13 Estimates of Annual Baseline Viral Illness and Death1 . . . . . . . . . . . . . . . . . . . . . . . . 5-43

Exhibit 5.14 Baseline Illnesses and Deaths in Sensitive Subgroups . . . . . . . . . . . . . . . . . . . . . . . . 5-44

Exhibit 5.15a Summary of Pearson Correlation Coefficients for Uncertain Inputs, Virus Type A . 5-47

Exhibit 5.15b Summary of Pearson Correlation Coefficients for Uncertain Inputs, Virus Type B . 5-48

Exhibit 5.16 Example of Baseline Cases, Cases Remaining, and Cases Avoided

at the Well Level . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5-50

Exhibit 5.17 Annual Viral Illnesses and Deaths Avoided for the GWR by System Size and Type . 5-55

Exhibit 5.18 Summary of Annual Viral Illnesses and Deaths Avoided for the GWR . . . . . . . . . . . 5-56

Exhibit 5.19 Viral Illnesses and Deaths Avoided in the 25th Year 

after Implementation of the GWR . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5-56

Exhibit 5.20a Comparison of Average Annual Individual Infectivity Risk Distributions for 

Baseline and Rule Alternatives for Type A Viruses . . . . . . . . . . . . . . . . . . . . . . . . . . 5-58

Exhibit 5.20b Comparison of Average Annual Individual Infectivity Risk Distributions for 

Baseline and Rule Alternatives for Type B Viruses . . . . . . . . . . . . . . . . . . . . . . . . . . 5-59

Exhibit 5.21a Estimates for Average Cost and Average Cost per Healthy Patient of Type A 

Illness, by Age (Enhanced COI) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5-65

Exhibit 5.21b Estimates for Average Cost and Average Cost per

Immunocompromised Patient of Type A Illness, by Age (Enhanced COI) . . . . . . . . . 5-66

Exhibit 5.21c: Estimates for Average Cost and Average Cost per Case of Type B Illness 

Requiring No Medical Care, by Age (Enhanced COI) . . . . . . . . . . . . . . . . . . . . . . . . 5-67

Exhibit 5.21d Estimates for Average Cost and Average Cost per Case of Type B Illness 

Requiring Outpatient Care, by Age (Enhanced COI) . . . . . . . . . . . . . . . . . . . . . . . . . 5-68

Exhibit 5.21e Estimates for Average Cost and Average Cost per Case of Type B Illness 

Requiring Inpatient Care, by Age (Enhanced COI) . . . . . . . . . . . . . . . . . . . . . . . . . . . 5-69

Exhibit 5.22a Estimates for Average Cost and Average Cost per Healthy Patient of Type A 

Illness, by Age (Traditional COI) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5-70

Exhibit 5.22b Estimates for Average Cost and Average Cost per

Immunocompromised Patient of Type A Illness, by Age (Traditional COI) . . . . . . . . 5-71

Exhibit 5.22c Estimates for Average Cost and Average Cost per Case of Type B Illness 

Requiring No Medical Care, by Age (Traditional COI) . . . . . . . . . . . . . . . . . . . . . . . 5-72

Exhibit 5.22d Estimates for Average Cost and Average Cost per Case of Type B Illness 

Requiring Outpatient Care, by Age (Traditional COI) . . . . . . . . . . . . . . . . . . . . . . . . 5-73

Exhibit 5.22e Estimates for Average Cost and Average Cost per Case of Type B Illness 

Requiring Inpatient Care, by Age (Traditional COI) . . . . . . . . . . . . . . . . . . . . . . . . . . 5-74

Exhibit 5.23a Annualized Quantified Benefits of Illnesses and Deaths Avoided, Final Rule, 

Enhanced COI, All Systems by System Size and Type ($Millions, 2003) . . . . . . . . . 5-79

Exhibit 5.23b Annualized Quantified Benefits of Illnesses and Deaths Avoided, Final Rule, 

Traditional COI, All Systems, by System Size and Type ($Millions, 2003) . . . . . . . . 5-80

Exhibit 5.24 Annual Illnesses and Deaths Avoided at Full Implementation, and Quantified 

Benefits of the GWR in Sensitive Populations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5-81

Exhibit 5.25 Estimated Bacterial Illnesses and Deaths Avoided . . . . . . . . . . . . . . . . . . . . . . . . . . . 5-97

Exhibit 5.26 Waterborne Bacterial Illness Hospitalization Rates . . . . . . . . . . . . . . . . . . . . . . . . . . . 5-99

Exhibit 5.27 Results of Alternative Analyses . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5-109

Exhibit 5.28 Summary of Uncertainties Affecting GWR Estimates . . . . . . . . . . . . . . . . . . . . . . . 5-110
Economic Analysis for the x October 2006

Final Ground Water Rule

Exhibit 5.29 Remaining Number of Annual Viral Illnesses and Deaths for Each 

Regulatory Alternative . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5-113

Exhibit 5.30 Comparison of Number of Annual Viral Illnesses and Deaths Avoided for 

Regulatory Alternatives . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5-113

Exhibit 5.31 Annualized Value of Viral Illnesses and Deaths Avoided for 

Regulatory Alternatives . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5-113

6. Cost Analysis

Exhibit 6.1 Wage Rates by System Size . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6-3

Exhibit 6.2 State Labor Rates . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6-4

Exhibit 6.3 Source Water Monitoring Costs per Sample . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6-5

Exhibit 6.4 Discount Rates for Private and Public Systems . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6-7

Exhibit 6.5a GWR Baselines: Number of Systems, Entry Points, and Wells . . . . . . . . . . . . . . . . . . 6-9

Exhibit 6.5b Summary of Rule Implications . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6-10

Exhibit 6.5c Annualized Costs for Meeting Each of the GWR Provisions to Systems and 

States ($Millions, 2003$) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6-11

Exhibit 6.6 PWS Unit Burden and Cost Estimates for Implementation Activities . . . . . . . . . . . . . 6-13

Exhibit 6.7a State Burden and Cost Estimates for Implementation Activities . . . . . . . . . . . . . . . . . 6-15

Exhibit 6.7b State Burden and Cost Estimates for Annual Administration . . . . . . . . . . . . . . . . . . . 6-15

Exhibit 6.8 PWS and State Cost Estimates for Implementation and Annual 

Administration Activities ($Millions, 2003$) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6-16

Exhibit 6.9 Schematic of Sanitary Survey Process . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6-18

Exhibit 6.10 Number of Full and Incremental Sanitary Surveys for Systems . . . . . . . . . . . . . . . . . 6-20

Exhibit 6.11a PWS Unit Burden and Cost Estimates for Performing Full and Incremental 

Sanitary Surveys (Treatment) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6-21

Exhibit 6.11b PWS Unit Burden and Cost Estimates for Performing Full and Incremental 

Sanitary Surveys (No Treatment) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6-22

Exhibit 6.12a State Unit Burden and Cost Estimates for Performing Full and Incremental 

Sanitary Surveys (Treatment) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6-23

Exhibit 6.12b State Unit Burden and Cost Estimates for Performing Full and Incremental 

Sanitary Surveys (No Treatment) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6-24

Exhibit 6.13 PWS and State Cost Estimates for Sanitary Survey Performance 

($Millions, 2003$) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6-25

Exhibit 6.14 Schematic of Triggered Monitoring Process . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6-26

Exhibit 6.15 Estimated Number of Triggered Samples Per Year Per Entry Point . . . . . . . . . . . . . . 6-27

Exhibit 6.16 PWS Unit Costs for Triggered Monitoring . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6-30

Exhibit 6.17 PWS and State Cost Estimates for Performing Triggered Monitoring 

($Millions, 2003$) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6-31

Exhibit 6.18 Estimated Distribution of Significant Deficiency Corrective Actions . . . . . . . . . . . . . 6-33

Exhibit 6.19 Estimated Unit Costs of Significant Deficiency Corrective Actions . . . . . . . . . . . . . . 6-34

Exhibit 6.20a PWS and State Unit Costs for Corrective Action Plans . . . . . . . . . . . . . . . . . . . . . . . . 6-35

Exhibit 6.20b PWS and State Cost Estimates for Sanitary Survey Corrective Action 

Activities ($Millions, 2003$) ............................................ 6–36

Exhibit 6.21a Summary Flow Chart Estimated Distribution of Source Water Contamination 

Corrective Actions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6-39

Exhibit 6.21b Estimated Distribution of Source Water Contamination Corrective Actions . . . . . . . 6-40

Exhibit 6.22a Estimated Unit Costs of Nontreatment Corrective Actions

for Source Water Contamination . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6-42
Economic Analysis for the xi October 2006

Final Ground Water Rule

Exhibit 6.22b Estimated Unit Costs of Treatment Corrective Actions for Source

Water Contamination . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6-43

Exhibit 6.23 PWS and State Cost Estimates for Triggered Monitoring Corrective 

Action Activities ($Millions, 2003$) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6-44

Exhibit 6.24 Schematic of Compliance Monitoring Process . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6-45

Exhibit 6.25 Assumptions for Entry Points Subject to Compliance Monitoring . . . . . . . . . . . . . . . 6-47

Exhibit 6.26 PWS Unit Costs for Compliance Monitoring for Initial State Notification and 

Disinfection Failure Reports . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6-49

Exhibit 6.27a PWS Compliance Monitoring Unit Costs for Systems Serving 3,300 or 

Fewer People . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6-50

Exhibit 6.27b PWS Compliance Monitoring Capital Unit and O&M Costs for Systems 

Serving More than 3,300 People . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6-51

Exhibit 6.28 State Unit Costs for Compliance Monitoring . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6-52

Exhibit 6.29 PWS and State Cost Estimates for Compliance Monitoring Activities 

($Millions, 2003$) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6-52

Exhibit 6.30 Total Initial Capital and One-Time Costs ($Millions, 2003$) . . . . . . . . . . . . . . . . . . . 6-53

Exhibit 6.31 Summary of Annual Per-Household Costs for the GWR (2003$/Year) . . . . . . . . . . . 6-55

Exhibit 6.32 Cost Uncertainty Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6-60

Exhibit 6.33 Total Annualized Present Value Costs ($Millions, 2003$) . . . . . . . . . . . . . . . . . . . . . 6-61

Exhibit 6.34 Total Annualized Costs to Systems by System Size and Type ($Millions, 2003$) . . . 6-62

Exhibit 6.35 Comparison of National Annual Costs by Regulatory Alternative 

($Millions, 2003$) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6-63

7. Economic Impact Analysis

Exhibit 7.1a Estimated Impact of the GWR on Small System’s Technical, Managerial, and 

Financial Capacity . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7-7

Exhibit 7.1b Estimated Impact of the GWR on Large System’s Technical, Managerial, and 

Financial Capacity . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7-8

Exhibit 7.2 Average Annual Burden Hours and Costs for the GWR Information Collection 

Request 3-Year Approval Period . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7-11

Exhibit 7.3 Ground Water System, State, and Tribal Estimated . . . . . . . . . . . . . . . . . . . . . . . . . . 7-13

Exhibit 7.4 Mean Total Annualized Benefits and Costs of Regulatory Alternatives 

($Millions, 2003$) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7-14

Exhibit 7.5 Annualized Compliance Costs by Type of Ground Water System . . . . . . . . . . . . . . . 7-16

Exhibit 7.6 Mean Annualized Compliance Cost per Ground Water System by 

System Size and Type . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7-17

Exhibit 7.7 Annual Cost of Compliance for Tribal Systems by System Type and Size 

(Annualized at 3 Percent) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7-21

Exhibit 7.8 Total Increased Annual National Energy Usage Attributable to the GWR . . . . . . . . . 7-27

Exhibit 7.9 Sample Calculation for Determining Increase in Energy Usage: Chlorine 

Dioxide (ClO2 Dose = 1.25 mg/L) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7-28

8. Comparison of Benefits and Costs of the LT2ESWTR

Exhibit 8.1 Summary of Annual Avoided Viral Illnesses and Deaths by System Type . . . . . . . . . . 8-2

Exhibit 8.2 Summary of Annualized Present Value Quantified Benefits ($Millions, 2003$) . . . . . 8-4

Exhibit 8.3 Summary of Benefits of the GWR . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8-5
Economic Analysis for the xii October 2006

Final Ground Water Rule

Exhibit 8.4 Summary of Quantified Costs, Final Rule ($Millions, 2003$) . . . . . . . . . . . . . . . . . . . 8-6

Exhibit 8.5a Estimated Annualized National Benefits and Costs for the GWR 

($Millions, 2003$) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8-7

Exhibit 8.5b Estimated Net Benefits Including Annual Bacterial Illness and Death 

Avoidance Estimate ($Millions 2003$) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8-8

Exhibit 8.6 Estimated Breakeven Points . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8-10

Exhibit 8.7 Annualized Costs, by Regulatory Alternative ($Millions, 2003$) . . . . . . . . . . . . . . . 8-11

Exhibit 8.8 Number of Annual Quantified Viral Illnesses and Deaths Avoided 

by Regulatory Alternatives . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8-11

Exhibit 8.9 Annualized Value of Quantified Viral Illnesses and Deaths Avoided, 

by Regulatory Alternative ($Millions, 2003$) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8-12

Exhibit 8.10a Annualized Net Benefits by Regulatory Alternative ($Millions, 2003$) . . . . . . . . . . 8-13

Exhibit 8.10b Annualized Mean Net Benefits for Final Rule Including Estimates for 

Nonquantified Benefits ($Millions, 2003$) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8-13

Exhibit 8.11a Mean Annualized Costs at Mean Benefit Level, Enhanced COI, 

by Regulatory Alternative . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8-15

Exhibit 8.11b Mean Annualized Costs at Mean Benefit Level, Traditional COI,

by Regulatory Alternative . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8-16

Exhibit 8.12 Cost Per Viral Illness or Death Avoided by Regulatory Alternative (2003$) . . . . . . . 8-17

Exhibit 8.13a Incremental Net Quantified Benefits by Rule Alternative - Enhanced COI 

(Annualized Present Value Mean, $Millions, 2003$) . . . . . . . . . . . . . . . . . . . . . . . . . 8-18

Exhibit 8.13b Incremental Net Quantified Benefits by Rule Alternative - Traditional COI 

(Annualized Present Value Mean, $Millions, 2003$) . . . . . . . . . . . . . . . . . . . . . . . . . 8-19

9. References
Economic Analysis for the xiii October 2006

Final Ground Water Rule

List of Acronyms

ADA American Diabetes Association

AIDS Acquired Immune Deficiency Syndrome

ASDWA Association of State Drinking Water Administrators

AWWA American Water Works Association

AWWARF American Water Works Association Research Foundation

AWWSCo American Water Works Service Company

BLS Bureau of Labor Statistics

BMP Best Management Practice

BGM Buffalo Green Monkey

CCR Consumer Confidence Report

CDC Centers for Disease Control and Prevention

CFR Combined Federal Register

Cl chlorine

ClO2 chlorine dioxide

COI Cost of Illness

CDBG Community Development Block Grant 

CPI Consumer Price Index

CT product of the residual disinfectant concentration (C) & the disinfectant contact time (T)

CWS Community Water System 

CWSS Community Water System Survey

DBP Disinfection Byproduct

DBPR Disinfectants and Disinfection Byproducts Rule

DOE Department of Energy

DWSRF Drinking Water State Revolving Fund

E Income Elasticity

EA Economic Analysis

EIA Economic Impact Analysis

EPA United States Environmental Protection Agency

FBRR Filter Backwash Recycling Rule

FDA Food and Drug Administration

FSIS Federalism summary impact statement

FR Federal Register

FTE Full time equivalent

GDP Gross Domestic Product

gpd gallons per day

gpm gallons per minute

GWR Ground Water Rule

GWSS Ground Water Supply Survey

GWUDI Ground Water Under Direct Influence of Surface Water

HAA Haloacetic Acid

HAA5 Sum of 5 Haloacetic Acids

HAV hepatitis A virus

HCUP Hospital Cost and Utilization Project

HSA Hydrogeologic Sensitivity Analysis

I Income

ICR Information Collection Rule

IESWTR Interim Enhanced Surface Water Treatment Rule
Economic Analysis for the xiv October 2006

Final Ground Water Rule

IDDM Insulin-dependent diabetes mellitus

IDSE Initial Distribution System Evaluation

ICD International Class of Diseases

kgal kilogallons

kgpd kilogallons per day

kW kilowatt

kWh kilowatt hour

kWh/y kilowatt hour per year

L liter

LRAA locational running annual average

LT1ESWTR Long Term 1 Enhanced Surface Water Treatment Rule

MCL Maximum Contaminant Level

MCLGs Maximum Contaminant Level Goal

MF Microfiltration

mgd million gallons per day

mg/L milligrams per liter

μg/L microgram per liter

MPN Most probable number

MPNIU Most probable number of infectious units

MRDL Maximum residual disinfectant level

MRDLG Maximum residual disinfectant level goal

NCHS National Center for Health Statistics

NHLBI National Health, Lung and Blood Institute

NCWS Noncommunity Water System

NDWAC National Drinking Water Advisory Committee

NFID National Foundation for Infectious Diseases

NRC National Research Council

NWRI National Water Research Institute

NF Nanofiltration

nm nanometers

NPDES National Pollutant Discharge Elimination System

NPDWR National Primary Drinking Water Regulations

NRC National Research Council

NTNCWS Nontransient Noncommunity Water System

O&M Operation and Maintenance

OGWDW Office of Ground Water and Drinking Water

OMB Office of Management and Budget

POE Point-of-Entry

PCR Polymerase Chain Reaction

POTW Publicly Owned Treatment Works

POU Point-of-Use

PPI Producer Price Index

ppm parts per million

PWS Public Water System

PWSS Public Water Systems Supervision

PV Present Value

RAA Running Annual Average

RFA Regulatory Flexibility Act

RNA Ribonucleic acid
Economic Analysis for the xv October 2006

Final Ground Water Rule

RO Reverse Osmosis

RTI Research Triangle Institute

RT-PCR Reverse Transcription-Polymerase Chain Reaction

RUS Rural Utility Service

SAB Science Advisory Board

SBA Small Business Administration

SBAR Small Business Advocacy Review 

SBREFA Small Business Regulatory Enforcement Fairness Act

SDWA Safe Drinking Water Act

SDWIS Safe Drinking Water Information System

SER Small entity representative

SIC Standard Industrial Classification

SOC Standard Occupational Classification

SRSV Small round, structured viruses

SRMD Standards and Risk Management Division

SWAPP Source Water Assessment and Protection Program

SWTR Surface Water Treatment Rule

T&C Technology and Cost

TC Total Coliform

TCR Total Coliform Rule

TMF Technical, managerial, and financial

THM Trihalomethane

TNCWS Transient Noncommunity Water System

TTHM Total Trihalomethanes

UIC Underground Injection Control

UF Ultrafiltration

UMRA Unfunded Mandates Reform Act

USDA United States Department of Agriculture

UV Ultraviolet

VSL Value of a Statistical Life

WTP Willingness to Pay
Economic Analysis for the xvi October 2006

Final Ground Water Rule

Health Risk Reduction and Cost Analysis

Under the Safe Drinking Water Act (SDWA) Amendments of 1996, when proposing a national

primary drinking water regulation that includes an maximum contaminant level (MCL), the U.S.

Environmental Protection Agency (EPA or the Agency) must conduct a health risk reduction and cost

analysis (HRRCA). A HRRCA addresses seven requirements, all of which are addressed in this Economic

Analysis (EA) for the Ground Water Rule (GWR).

HRRCA Crosswalk Summary

HRRCA Requirement Addressed in Economic Analysis

Quantifiable and nonquantifiable health risk

reduction benefits

Chapter 5 (All sections and exhibits)

Chapter 7 (Section 7.7.1; Exhibit 7.4)

Chapter 8 (Sections 8.1; Exhibits 8.1–8.3, 8.5)

Quantifiable and nonquantifiable health risk

reduction benefits from co-occurring contaminants

Chapter 5 (Section 5.4)

Quantifiable and nonquantifiable costs Chapter 6 (All sections and exhibits)

Chapter 7 (Sections 7.2–7.8; Exhibits 7.1–7.7)

Chapter 8 (Sections 8.1, 8.3; Exhibit 8.4, 8.6)

Incremental costs and benefits associated with

regulatory alternatives

Chapter 5 (Section 5.7; Exhibit 5.31)

Chapter 6 (Sections 6.9; Exhibit 6.35)

Chapter 8 (Section 8.4; Exhibits 8.7 - 8.13)

Effects of the contaminants on the general

population and sensitive subpopulations

Chapter 5 (Sections 5.2.2.2, 5.2.5.3, and 5.3.3)

Chapter 7 (Section 7.9)

Increased health risk that may occur as a result of

compliance

Chapter 5 (Section 5.2.5.9)

Other relevant factors (quality and uncertainty of

information)

Chapter 4 (Section 4.6; Exhibit 4.32)

Chapter 5 (Section 5.6; Exhibit 5.28)

Chapter 6 (Sections 6.2 - 6.4, Section 6.7; Exhibit

6.32)

Chapter 8 (Section 8.2)
Economic Analysis for the ES-1 October 2006

Final Ground Water Rule

Executive Summary

This Economic Analysis (EA) presents the evaluation of the benefits and costs of the Ground

Water Rule (GWR). The analysis is performed in compliance with Executive Order 12866, Regulatory

Planning and Review (58 FR 51735, September 1993), which requires the United States Environmental

Protection Agency (EPA or Agency) to estimate the economic impact of rules that have an annual effect

on the economy of over $100 million and make that analysis available to the public in conjunction with

publication of the final rule. Although EPA's analysis of the GWR has determined that its annual costs

are most likely below this threshold, EPA has chosen to publish a complete EA for this rule. Earlier, EPA

had prepared an EA (formerly known as the Regulatory Impact Analysis) to accompany the May 2000

proposed GWR.

EPA developed the GWR in collaboration with States and other interested stakeholders. The

primary goal of the GWR is to improve public health by identifying public ground water systems (GWSs)

that are susceptible to fecal contamination and to ensure that they take adequate measures to remove or

inactivate pathogens in drinking water they provide to the public.

ES.1 Need for the Rule

An estimated 147,330 public water systems (PWSs) in the United States, serving over 114 million

people, use ground water as their primary water source. EPA is concerned about any potential adverse

health risks that may be associated with ground water sources and, in particular, the risks associated with

fecal contamination. Fecal contamination includes all of the bacteria and viruses—both pathogenic

(disease-causing) and non-pathogenic—found in feces. Under certain circumstances, these

microorganisms can make their way into ground water sources. Unlike for surface water sources, no

federal regulations currently require filtration or disinfection of ground water sources to remove microbial

contaminants. Currently for GWSs, there are only requirements for distribution system monitoring of

total coliforms, periodic sanitary surveys of small GWSs, and a maximum contaminant level (MCL) for

total coliforms.

The GWR will address the human risks of illness and death due to fecal contamination of ground

water and improve upon the protection provided by existing sanitary survey requirements for GWSs. The

reduction in risk will be accomplished through implementation of the GWR’s risk-targeted approach. 

Because of the difficulties involved in monitoring for the wide range of specific pathogenic bacteria and

viruses that could occur in ground water, one of the key provisions of the risk-targeted approach is

monitoring for a more easily measured bacterial or viral fecal indicator microorganism. Based on source

water sampling results, as well as sanitary survey results, PWSs will be required to take action to

minimize the possible presence of pathogenic bacteria and viruses that pose threats to human health.
1

 Modifications to Alternatives 2 and 3 since proposal are described in further detail in Chapter 3.

Economic Analysis for the ES-2 October 2006

Final Ground Water Rule

ES.2 Consideration of Regulatory Alternatives

EPA considered several regulatory alternatives when the GWR was proposed on May 10, 2000

(65 FR 30194). The proposed GWR and accompanying EA evaluated four regulatory alternatives, the

multi-barrier approach (Alternative 3) was the preferred alternative. 

After the proposal, EPA considered comments and revised the occurrence analysis underlying the

cost-benefit analysis for the rule (as discussed in Chapter 4 of this EA) and made modifications to

Alternatives 2 and 3. This resulted in the choice of a different rule alternative, Alternative 2, termed the

risk-targeted approach, for the final GWR. .1

 The four alternatives considered for the final GWR and

analyzed in this EA are as follows:

Alternative 1 - Sanitary surveys and corrective action.

Alternative 2 - Risk-targeted approach: sanitary surveys, triggered monitoring, optional

assessment monitoring, corrective action, and compliance monitoring.

Alternative 3 - Multi-barrier approach: sanitary surveys, triggered monitoring, optional

hydrogeologic sensitivity assessment (HSA), assessment monitoring (a derivation of the proposed

routine monitoring), corrective action, and compliance monitoring.

Alternative 4 - Across-the-board disinfection.

As shown in Chapter 8, the risk-targeted approach is cost-effective (using either the Enhanced or the

Traditional cost-of-illness approach) and, considering the nonquantified benefits, the benefits justify the

costs. The final rule provides public health benefits while apportioning costs in a more flexible targeted

manner. 

ES.3 Summary of the Final GWR Requirements

The GWR applies to all community and noncommunity PWSs that use ground water as a water

source. The final GWR targets GWSs that are susceptible to fecal contamination. A flowchart that

illustrates the compliance steps for systems is illustrated in Exhibit ES.1. The components of the risktargeted strategy are used to identify source contamination and significant deficiencies that may lead to

source contamination. Each component is described below. Exhibit ES.2 presents the schedule for these

activities.

Sanitary Surveys

The final GWR requires regular (every three years for CWSs and every five years for NCWSs)

comprehensive sanitary surveys of 8 critical components: (1) source; (2) treatment; (3) distribution

system; (4) finished water storage; (5) pumps, pump facilities, and controls; (6) monitoring and reporting,

and data verification; (7) system management and operation; and (8) operator compliance with State

requirements. The State may reduce the frequency of sanitary surveys for CWSs to at least once every

five years if the water system has an outstanding performance record as determined by the State (e.g., no

significant deficiencies documented in previous assessments and no history of total coliform MCL or
Economic Analysis for the ES-3 October 2006

Final Ground Water Rule

monitoring violations under the TCR or the system maintains 4-log treatment of viruses using

inactivation, removal, or State-approved combination of virus inactivation and removal). If a significant

deficiency is identified, corrective action is required or a treatment technique violation is incurred. 

Source Water Monitoring

In the final GWR, systems not achieving 4-log treatment of viruses (using inactivation, removal,

or a State-approved combination of these technologies) must conduct triggered source water monitoring

for the presence of at least one of the following State-specified fecal indicators: E. coli, enterococci, or

somatic coliphage. The triggered monitoring requirements apply to systems that are notified that a Total

Coliform Rule (TCR) routine sample is total coliform-positive. Within 24 hours of receiving the total

coliform-positive notice, GWSs must collect a source water sample and test it for the presence of the

State-specified fecal indicator.

If the State does not require corrective action (see Corrective Action section below) for the initial

fecal indicator-positive source water sample immediately, the system must collect five additional source

water samples within 24 hours of being notified of the initial fecal indicator-positive source water sample.

The GWR provides States with the option to require systems to conduct assessment source water

monitoring as needed and require systems to take corrective action. The purpose of this optional

assessment source water monitoring requirement is to target source water monitoring to systems that the

State determines are at higher risk for fecal contamination. 

Corrective Action

The GWR requires a system with a significant deficiency or source water fecal contamination to

fix the problem by implementing a corrective action. The system must implement at least one of the

following corrective actions: correct all significant deficiencies; provide an alternate source of water;

eliminate the source of contamination; or provide treatment that reliably achieves at least 4-log treatment

of viruses. Furthermore, the system is required to notify the public served by the water system of any

uncorrected significant deficiencies and/or source water contamination. (The State may also require

notification of corrected significant deficiencies).

Compliance Monitoring

Compliance monitoring requirements are the final defense against microbial contaminants

provided by the final GWR. All GWSs that provide at least 4-log treatment of viruses using chemical

disinfection, membrane filtration, or a State-approved alternative treatment technology must conduct

compliance monitoring to demonstrate continual treatment effectiveness.
Economic Analysis for the ES-4 October 2006

Final Ground Water Rule

All ground water PWSs (1) Sanitary surveys for all 

ground water PWSs

Does system 

provide 

treatment >4 

logs? (2)

Did survey 

find 

deficiencies?

NO

Must correct deficiencies (4)

YES

Compliance monitoring

YES

Conduct TCR routine 

monitoring

NO

Is TCR routine 

sample TC-positive? NO

Conduct triggered 

monitoring (3)

YES

Fecal Coliform

Indicator Positive?

Per State’s direction, take 

corrective action or take 

5 additional samples(4)

YES

Did system 

install 

treatment as 

corrective 

action? (2)

YES

Take non-treatment 

corrective actions

NO

Continue GWR 

compliance: sanitary 

surveys, compliance 

monitoring, TCR 

compliance

(1) Includes mixed systems with ground water entry points

(2) Treatment using inactivation, removal, or State-approved 

combination of these technologies.

(3) For those systems that do not receive a triggered monitoring 

waiver from the State

(4) The State may determine that the source of contamination has 

been eliminated..

Continue GWR 

compliance: sanitary 

surveys, triggered 

monitoring, TCR 

compliance

Systems are not required 

to take corrective action 

if all 5 repeat samples are 

fecal negative.

NO

All ground water PWSs (1) Sanitary surveys for all 

ground water PWSs

Does system 

provide 

treatment >4 

logs? (2)

Did survey 

find 

deficiencies?

NO

Must correct deficiencies (4)

YES

Compliance monitoring

YES

Conduct TCR routine 

monitoring

NO

Is TCR routine 

sample TC-positive? NO

Conduct triggered 

monitoring (3)

YES

Fecal Coliform

Indicator Positive?

Per State’s direction, take 

corrective action or take 

5 additional samples(4)

YES

Did system 

install 

treatment as 

corrective 

action? (2)

YES

Take non-treatment 

corrective actions

NO

Continue GWR 

compliance: sanitary 

surveys, compliance 

monitoring, TCR 

compliance

(1) Includes mixed systems with ground water entry points

(2) Treatment using inactivation, removal, or State-approved 

combination of these technologies.

(3) For those systems that do not receive a triggered monitoring 

waiver from the State

(4) The State may determine that the source of contamination has 

been eliminated..

Continue GWR 

compliance: sanitary 

surveys, triggered 

monitoring, TCR 

compliance

Systems are not required 

to take corrective action 

if all 5 repeat samples are 

fecal negative.

NO

Exhibit ES.1 Flowchart of Compliance with GWR Requirements for Systems
Economic Analysis for the ES-5 

Final Ground Water Rule

Final GWR publication date (2006); final rule takes effect 3 years after published in Federal Register

NCWSs

CWSs

State

Year 1 Year 2 Year 3 Year 4 Year 5 Year 6 Year 7 Year 8 Year 9 Y

Implementation

Conduct Sanitary Surveys

Review Triggered Source Water Monitoring

Review & Approve Corrective Action

Review Compliance Monitoring

ImplementationImplementation

Triggered Source Water MonitoringTriggered Source Water Monitoring

Perform Corrective Action

Perform Compliance Monitoring

1st round Sanitary Surveys

2nd round S

Perform Corrective Action

Perform Compliance Monitoring

1st round Sanitary Surveys

2nd round Sanitary Surveys

Primacy Application

Possible Extension for Primacy

3

S

Final GWR publication date (2006); final rule takes effect 3 years after published in Federal Register

NCWSs

CWSs

State

Year 1 Year 2 Year 3 Year 4 Year 5 Year 6 Year 7 Year 8 Year 9 Y

Implementation

Conduct Sanitary Surveys

Review Triggered Source Water Monitoring

Review & Approve Corrective Action

Review Compliance Monitoring

ImplementationImplementation

Triggered Source Water MonitoringTriggered Source Water Monitoring

Perform Corrective Action

Perform Compliance Monitoring

1st round Sanitary Surveys

2nd round S

Perform Corrective Action

Perform Compliance Monitoring

1st round Sanitary Surveys

2nd round Sanitary Surveys

Primacy Application

Possible Extension for Primacy

3

S

Exhibit ES.2 Implementation Timeline for the GWR
2

 SDWIS-Federal Version (SDWIS/FED) is a database created by EPA containing data submitted by States

and regions regarding compliance with SDWA. 

3

 The column G figures pertain only to entry points with newly installed treatment to achieve 4-log viral

inactivation or removal. The number of entry points performing non-treatment corrective actions can be calculated

by subtracting Column G figures from those presented in column F.

Economic Analysis for the ES-6 October 2006

Final Ground Water Rule

ES.4 Systems Subject to the GWR

Exhibit ES.3 shows the baseline number of systems and entry points subject to the rule and the

estimated number that will perform or undergo various rule activities (implementation, sanitary surveys,

triggered monitoring, corrective actions, and compliance monitoring). This baseline is derived from

EPA’s Safe Drinking Water Information System (SDWIS) inventory, 4th quarter 2003 data.2

 The systems

are subdivided by type [community water systems (CWS), nontransient noncommunity water systems

(NTNCWS), and transient noncommunity water systems (TNCWS)], and size (nine size categories).

All GWSs will undergo sanitary surveys (column A). EPA estimates that all GWSs will also

have to perform implementation activities (reading and understanding the rule, training, etc.) which is

also represented by column A. Column B presents the number of systems estimated to find and be

required to correct a significant deficiency based on conducting a sanitary survey. The remaining

activities are evaluated at the entry point into the distribution system. Column C indicates that all entry

points that do not achieve 4-log treatment of viruses will perform triggered source water monitoring for

the GWR. Corrective actions predicted as a result of triggered monitoring are presented in column D,

with estimates (cumulative) of the different levels of disinfection (i.e., increased disinfection or

installation of new disinfection) resulting from those corrective actions presented in columns E and F. 

Finally, column G shows the number of entry points incurring costs for additional compliance monitoring

to ensure the effectiveness and reliability of treatment.3
Economic Analysis for the ES-7 

Final Ground Water Rule

System Size

Systems Receiving Sanitary Survey

Systems with Corrective Actions for Significant Deficiencies

Entry Points with Triggered Monitoring

Entry Points with Corrective Actions for Triggered Monitoring

Entry Points with Viral Disinfection Increased from less than 4 logs to 4 logs

Previously Nondisinfecting EntPoints Taking Corrective Actio

AB C D E F 

Community Water Systems (CWSs) <100 12,843 2,181 12,797 1,249 358 

 

101-500 14,358 2,444 14,819 1,625 917 

 

501-1,000 4,649 789 5,578 608 360 

 

1,001-3,300 5,910 1,001 8,910 712 396 

 

3,301-10K 2,884 492 5,638 617 353 

 

10,001-50K 1,444 245 4,357 655 548 

 

50,001-100K 167 28 1,295 226 93 

 

100,001-1 Million 103 18 749 136 94 

 

> 1 Million 3 - - - - 

 

Nontransient Noncommunity Water Systems (NTNCWSs)<100 9,456 1,608 8,609 687 150 

 

101-500 6,758 1,148 6,149 533 119 

 

501-1,000 1,894 322 1,724 149 33 

 

1,001-3,300 715 121 651 86 19 

 

3,301-10K 73 12 66 10 2 

 

10,001-50K 10 2 9 2 0 

 

50,001-100K 1 0 1 0 0 

 

100,001-1 Million 1 0 1 0 0 

 

> 1 Million - - - - - 

 

Transient Noncommunity Water Systems (TNCWSs)<100 64,448 10,990 63,295 6,915 1,143 

 

101-500 18,993 3,234 18,648 2,026 337 

 

501-1,000 1,940 329 1,905 208 35 

 

1,001-3,300 585 99 574 76 12 

 

3,301-10K 74 13 73 12 2 

 

10,001-50K 19 3 19 3 1 

 

50,001-100K 1 0 1 0 0 

 

100,001-1 Million 1 0 1 0 0 

 

> 1 Million - - - - - 

 

Sources: Exhibit 6.5bNotes:(G) indicates number of entry points with treatment corrective actions.(F) - (G) indicates non treatment corrective actions.

Exhibit ES.3 Summary of Rule Implications
4

 There is much discussion among economists of the proper social discount rate to use for policy analysis. 

For GWR cost analyses, calculations are made using two social discount rates (3 and 7 percent) thought to best

represent current policy evaluation methodologies. Historically, the use of 3 percent is based on rates of return on

relatively risk-free investments, as described in the Guidelines for Preparing Economic Analyses (USEPA, 2000j). 

The rate of 7 percent is a recommendation of the Office of Management and Budget (OMB) as an estimate of

“before-tax rate of return to incremental private investment” (USEPA, 1996b). 

Economic Analysis for the ES-8 October 2006

Final Ground Water Rule

ES.5 National Benefits and Costs of the GWR

EPA has determined from its analysis of the available human exposure and epidemiological

studies that the GWR will result in benefits in terms of reduced incidence of illnesses and deaths

associated with fecal contamination of ground water. There are substantial benefits attributable to the

GWR that are not quantified within this EA as part of the main analyses because of data limitations. 

Beneficial aspects of the rule not quantified are characterized as either health benefits or non-health

benefits. Nonquantified health-related benefits include reducing other acute viral illness (other than those

caused by rotavirus and enterovirus), endemic acute bacterial illnesses and deaths, epidemic bacterial and

viral acute illness and death (associated with outbreaks, disinfection failures, and distribution system

contamination). Chronic illnesses, both bacterial and viral, are also not quantified. The rule will also

result in many non-health benefits such as reduced costs for responding to outbreaks, costs for averting

behavior, and reduced uncertainly regarding drinking water safety. Chapter 5, Section 5.4.3.2 presents a

discussion of nonquantified benefits and estimates a portion of their value, based only on bacterial

illnesses avoided, at four times the primary analysis benefits (resulting in total benefits that are five times

the primary benefits). This includes consideration of the value of deaths and hospitalization costs avoided

for waterborne cases of bacterial illness prevented by the rule. This does not include indirect (nonmedical) costs associated with waterborne bacterial illness or the value of avoiding other chronic or viral

illnesses.

Sections ES.5.1 and ES.5.2 summarize the methods used to derive the benefits and costs of the

rule. These sections describe the analyses of the total number of illnesses and deaths avoided, the

monetized benefits resulting from those cases and deaths avoided, a summary of nonquantified benefits,

and the total national costs (both one-time and annualized) for the GWR. The cases and monetized

benefits are based on reductions in microbial contamination that result from corrective actions. EPA’s

national cost estimate includes rule implementation, sanitary surveys, triggered monitoring, corrective

actions (which account for more than half of the national costs), and compliance monitoring. Note that

two estimates for national costs and monetized benefits are presented depending upon the discount rate

used for present value calculations and annualizing costs.4

 Benefits are also further divided into two

additional estimates based on different methodologies for estimating cost of illness (COI) attributed to

illnesses avoided. Chapters 4 through 6 and the appendices provide a more complete discussion of all the

analyses discussed in the sections below.

The GWR EA does not include estimates of costs and benefits of assessment source water

monitoring because it is an optional requirement. EPA does not know the extent to which States will use

the option or the manner in which they will implement it. This provision could potentially increase both

benefits and costs. 
Economic Analysis for the ES-9 October 2006

Final Ground Water Rule

ES.5.1 Derivation of Benefits

The GWR is expected to reduce the current incidence of acute and chronic illness caused by a

wide variety of viral and bacterial pathogens that are associated with fecal contamination of ground water. 

Determining the economic value of the health benefits involves a sequential two-step process. First, a

risk assessment is prepared to quantify a health endpoint. Following this is the valuation of benefits. 

Chapter 5 of this EA presents a complete discussion of these steps. Additional benefits accrue but are not

quantified.

EPA developed a risk assessment model to quantify a subset of the total number of predicted

illnesses and deaths avoided. Medical research has not isolated all waterborne pathogens, nor has it

thoroughly characterized the ability of these organisms to infect humans and cause illness and death. 

Risk from bacterial pathogens was not characterized in the risk model because occurrence data for

bacterial pathogens in drinking water are limited (however, the discussion of nonquantified benefits

assesses the potential impact). For the risk assessment, EPA has selected two well-characterized viral

pathogens having different infectivity, morbidity, and mortality rates to represent a wide range of

waterborne viral pathogens to estimate the number of acute illnesses and deaths avoided by implementing

the GWR. The selected representative viruses are rotavirus and enteric viruses represented by echovirus

data.

Rotavirus is a highly infectious virus, but generally does not result in life-threatening illness. It is

similar to a large group of viruses that cause widespread, but usually not very serious, cases of

gastroenteritis. This large group includes noroviruses (i.e., Norwalk-like viruses), sapoviruses,

adenovirus, astrovirus and others. Echovirus is an enterovirus that is not highly infectious, but can cause

severe health effects if illness occurs (e.g., encephalitis or myocarditis). This economic analysis identifies

these two representative types as Type A and Type B viruses, respectively. EPA used these two viruses

to represent the range of possible acute illness risk that could result from all viruses.

The Agency, having identified representative viruses for modeling purposes, used probability of

virus occurrence in wells and samples along with estimated concentrations of enteric viruses to estimate

the population’s exposure to Type A and Type B viruses. Combining these occurrence and concentration

data with daily drinking water intake data from the 1994–1996 USDA, Continuing Survey of Food Intakes

by Individuals (USEPA, 2000) yields estimates of risk of pathogen exposure. EPA combines these data

with viral dose-response functions and health effects data to estimate infections, morbidity, and mortality

to derive the baseline number of viral illnesses and deaths.

The baseline viral illnesses (185,186) and deaths (3.2) reflect conditions prior to the

implementation of the GWR. To determine the number of viral illnesses and deaths avoided by the final

GWR, EPA estimates the percentage reduction in viral occurrence as a result of systems implementing

changes to meet all rule requirements. The estimated numbers of avoided viral illnesses and deaths are

shown in Exhibit ES.4, and include the confidence bounds, reflecting uncertainty in those estimates. 
Economic Analysis for the ES-10 October 2006

Final Ground Water Rule

90% Confidence Bounds 90%Confidence Bounds

5th 95th 5th 95th

CWSs 32,031 8,704 68,994 0.62 0.07 1.81

NTNCWSs 2,094 533 4,308 0.03 0.00 0.09

TNCWSs 7,743 1,037 14,738 0.09 0.01 0.21

Total 41,868 10,274 88,039 0.74 0.08 2.11

Source: Exhibit 8.1

Note: Detail may not add due to independent forecasting. Values presented are average annual illnesses and 

deaths avoided over the 25 year period of analysis following rule promulgation. 

Annual Illnesses Avoided Annual Deaths Avoided

Mean Mean 

Exhibit ES.4 Summary of Annual Avoided Viral Illnesses and Deaths

by System Type

The final step in the benefit calculation is to monetize the estimated reduction in cases by

applying economic values for avoided viral illness and deaths. The value of avoiding cases of viral

illness is based on estimates of the direct and indirect costs of becoming ill. Due to lack of adequate data

on the willingness-to-pay (WTP) to avoid becoming ill, EPA uses a COI estimate. EPA has chosen to

present two different estimates of COI, referred to in this EA as Enhanced and Traditional. Both

approaches include the value of the direct medical costs and of lost work time, but differ in the

assessment of value of lost nonmarket work time. The Enhanced COI values nonmarket work time based

on opportunity costs. The other approach, the Traditional COI, includes nonmarket (unpaid) work time

based on replacement costs. In addition, the Enhanced COI also includes the value of lost leisure time

and lost productivity—the reduced utility (or sense of well-being) associated with decreased enjoyment of

time spent in both market and nonmarket activities. For deaths due to viral infection, the Value of a

Statistical Life (VSL) is used to capture the value of benefits. The VSL represents an estimate of the

monetary value of reducing risks of premature death. The VSL, therefore, is not an estimate of the value

of saving a particular individual’s life. Rather, the value of a “statistical” life represents the sum of the

values placed on small individual risk reductions across an exposed population. Other economic factors

are taken into consideration when calculating benefits over time, such as income growth, income

elasticity of demand, and social discount rates.

EPA estimates the quantified benefits of avoided illnesses and deaths from the GWR to be $8.6

million to $19.7 million depending on the discount rate and COI value used. These figures are presented

by system type in Exhibit ES.5.
Economic Analysis for the ES-11 October 2006

Final Ground Water Rule

5th 95th 5th 95th

CWSs 16.0 $ 5.4 $ 37.0 $ 13.7 $ 4.6 $ 31.6 $ 

NTNCWSs 0.9 $ 0.3 $ 2.2 $ 0.8 $ 0.2 $ 1.8 $ 

TNCWSs 2.7 $ 0.8 $ 6.2 $ 2.3 $ 0.7 $ 5.1 $ 

Total 19.7 $ 6.5 $ 45.4 $ 16.8 $ 5.5 $ 38.6 $ 

CWSs 8.2 $ 1.9 $ 22.3 $ 7.1 $ 1.6 $ 19.1 $ 

NTNCWSs 0.5 $ 0.1 $ 1.3 $ 0.4 $ 0.1 $ 1.0 $ 

TNCWSs 1.3 $ 0.3 $ 3.4 $ 1.1 $ 0.2 $ 2.8 $ 

Total 10.0 $ 2.2 $ 27.0 $ 8.6 $ 1.9 $ 22.9 $ 

Source: Exhibit 5.23a, 5.23b 

Notes: Detail may not add due to independent rounding. The Traditional COI only includes valuation for medical costs and 

lost work time (including some portion of unpaid household production). The Enhanced COI also factors in valuations for 

lost personal time (non-work time) such as childcare and homemaking (to the extent not covered by the Traditional COI), 

time with family, and recreation, and lost productivity at work on days when workers are ill but go to work anyway. 

The figures presented in this exhibit represent only the quantifiable benefits of the GWR. The unquantified benefits are 

expected to comprise a significant portion of the overall benefits of the Rule and are presented in Section 5.4 of Ch. 5 of the

EA.

Enhanced COI

Traditional COI

System Type

Annualized Benefits

at 3% Discount Rate

Annualized Benefits

at 7% Discount Rate

Mean Mean 

90% Confidence Bounds 90%Confidence Bounds

Exhibit ES.5 Summary of Annualized Present Value Quantified Benefits

($Millions, 2003$)

As mentioned above, there are substantial benefits attributable to the GWR that are not quantified

within this EA as part of the main analyses. These nonquantified benefits are shown in relation to

quantified benefits as part of the total benefits of the GWR in Exhibit ES.6. The nonquantified benefits

result from multiple factors. First, the quantified benefits are based on limited, well-defined data and key

assumptions that restrict the input parameters in the quantified benefit calculation. Typically, these

assumptions resulted in low mean values and narrow uncertainty ranges in the benefit analysis. This EA,

where applicable, discusses alternative assumptions. For example, the enterovirus morbidity fractions

are, by assumption, not determined using coxsackievirus (an enterovirus) data although the enterovirus

severity data use all enterovirus data. If coxsackievirus data were available, the mean morbidity values

would be greater. Choosing alternative values and ranges and differing key assumptions, which might

also be deemed reasonable, would increase the quantified benefits in this EA.

Second, the quantified benefits are based on data and assumptions that pertain to only partial

representation of Type A and Type B viruses potentially found in PWS wells with fecal contamination. 

Due to limited available data, only rotavirus and some enterovirus data were used to calculate the

quantified benefits. As is more completely discussed in Section 5.4. other viruses as well as pathogenic

bacteria may contribute to the disease burden, both acute and chronic, associated with PWS wells with

fecal contamination. Most importantly, bacterial illnesses can result in more frequent and lengthier

hospitalization and more frequently have fatal outcomes. If bacterial diseases were considered in the

quantified benefits, the monetized benefits could be substantially greater because bacterial disease can be

more severe and can result in higher mortality rates.
Economic Analysis for the ES-12 October 2006

Final Ground Water Rule

Third, the quantified benefits are based on data and assumptions that limit the characterization of

acute disease. For rotavirus, only acute gastroenteritis illness and fatal dehydration associated with that

illness are monetized. Norovirus disease is not considered. For the enteroviruses, all acute disease

endpoints are considered, but the prevalence of severe endemic cases may be substantially diluted by the

large number of hand, foot, and mouth disease cases that are not likely to be waterborne. Thus, the

proportion of severe cases in the quantitative benefits is likely to be underestimated. As is discussed more

completely in Section 5.4, in neither instance, either for rotavirus or the enteroviruses, are chronic

diseases identified or monetized in the quantitative benefits calculation.

Fourth, the quantified benefits are based explicitly on what has been directly measured in PWS

wells, yet there is great difficulty in identifying and counting all infectious viral pathogens in dilute

drinking water samples. Indeed, some viral pathogens like infectious norovirus can never be identified in

any sample. Section 4.3.2 discusses these difficulties in more detail. Standard fecal indicator data such

as total coliforms and E. coli, commonly used to identify water treatment deficiencies and potential

human health hazards, are explicitly not used to determine human exposure for the purposes of

quantifying the benefits in this EA.

Fifth, the quantified benefits are assumed to be based only on one contamination scenario, fecal

contamination of source water. Other contamination scenarios are thoroughly documented in the ground

water contamination and outbreak scientific literature. However, these scenarios, such as inadequate

disinfection, are not explicitly considered in calculating the quantified benefits in this EA.

Sixth, the quantified benefits are assumed to be based only on avoidance of endemic disease. The

GWR will likely also decrease the incidence of epidemic disease (outbreaks). If epidemic illnesses and

the avoided non-health-related costs of ground waterborne disease outbreaks were included, the

quantified benefits would increase.

In summary, this EA quantifies a subset of the total health and non-health related benefits. In a

sample calculation, discussed in Section 5.4.3.2, EPA estimated that the total benefits could increase by a

factor of five by only accounting for additional deaths and hospitalizations caused by bacterial illness

being avoided. While EPA recognizes that this estimate includes substantial uncertainty, given all the

other nonquantified factors described above, EPA believes that the total benefits from the GWR are likely

to be more than five times those which have been quantified.
Economic Analysis for the ES-13 October 2006

Final Ground Water Rule

Exhibit ES.6 Summary of Benefits of the GWR

Benefit

Category

Total Benefits GWR EA Quantified Benefits

Health Benefits

Reduction in

endemic illness

incidence

• viral exposure risk reduction (morbidity

and mortality)

• bacterial exposure risk reduction

(morbidity and mortality)

• chronic sequelae reduction

• reduction in secondary transmission of

viral or bacterial illness from

symptomatic and asymptomatic

individuals

• acute rotavirus (Type A) illnesses and

deaths avoided

• acute enterovirus (Type B) illnesses

and deaths avoided

• reduction in secondary transmission of

viral illness from symptomatic

individuals

Reduction in epidemic (outbreak)

illness incidence

• viral exposure risk reduction (morbidity

and mortality)

• bacterial exposure risk reduction

(morbidity and mortality)

• chronic sequelae reduction

• reduction in secondary transmission of

viral or bacterial illness to susceptible

populations

Not quantified

Reduction in

treatment failures

• Decreased illness through minimizing

treatment failures or fewer episodes

with inadequate treatment

Not quantified

Non-Health Benefits

Outbreak

responses avoided 

• Avoided costs to affected water

systems, local governments (provision

of alternate water, issuing warnings

and alerts), and community (decreased

tourism due to bad press). 

Not quantified

Avoided costs of

averting behavior

• reduced need or perceived need to

use bottled water, point-of-use

devices, etc. (includes time and

material costs)

• less time spent on averting behavior:

hauling/boiling water, etc.

Not quantified

Increased

confidence

• Perceived reduction in risk associated

with perceived improvement in drinking

water quality

Not quantified
Economic Analysis for the ES-14 October 2006

Final Ground Water Rule

ES.5.2 Derivation of Costs

To estimate the total national costs of the GWR, EPA calculated the costs to be incurred by PWSs

and States for the rule activities. Cost analyses for PWSs include estimating the costs to implement the

rule, assist with sanitary surveys, perform triggered source water monitoring, undergo corrective actions,

and perform compliance monitoring. State cost analyses include estimates of the labor burdens that States

would face for implementation and other annual administrative tasks (e.g., recordkeeping), conducting

sanitary surveys, responding to PWS reports for source water and compliance monitoring, and reviewing

corrective action plans. The methodology for estimating corrective action and noncorrective actionrelated costs for systems is discussed in the next several paragraphs, followed by a discussion of

uncertainties. A complete discussion of the cost analysis is provided in Chapter 6.

Noncorrective action costs for implementation, sanitary surveys, triggered monitoring, and

compliance monitoring are based on estimates of labor hours for performing these activities and on

additional laboratory costs. Some systems also incur capital costs for compliance monitoring. For all

noncorrective action cost calculations, EPA used the appropriate baseline (for systems or entry points)

shown in Exhibit ES.3.

Corrective action costs are based on unit cost estimates for a number of treatment technologies. 

Technology unit cost estimates are in the form of “dollars per entry point” for initial capital and yearly

operations and maintenance (O&M) activities. Derivation of unit costs for a wide range of plant sizes,

represented by different design and average daily flow rates, is described in detail in the document,

Technology and Cost Document for the Final Ground Water Rule (USEPA, 2006b). EPA uses mean

population per system for each of the nine system size categories (derived from SDWIS) combined with

regression equations and entry point per system estimates to estimate mean design and average daily

flows per entry point. Technology unit costs per entry point are calculated using these mean flow values

for each of the nine system size categories. The technology unit costs are then combined with the

predicted number of entry points assumed to select each technology to produce national treatment cost

estimates.

EPA recognizes that systems vary with respect to many of the input parameters to the GWR Cost

Model (e.g., entry points per system, population served, flow per population, and labor rates). In many

cases, there is insufficient information to characterize fully the variability on a national scale. EPA

believes that the mean values for the various input parameters are adequate to generate EPA’s best

estimate of national costs for the rule while still recognizing that impacts on specific systems may differ

substantially from these averages.

EPA also recognizes that there is uncertainty in the national cost estimates related to the national

average unit capital and O&M costs for the various technologies expected to be implemented in response

to the GWR. This uncertainty has been incorporated into the cost model using a Monte Carlo simulation. 

The national costs of the GWR summarized below in Exhibits ES.7 and ES.8 show both the expected

values and the 90 percent confidence bounds on the national cost estimates obtained from the cost model

reflecting this uncertainty. Further discussion of uncertainty analysis is presented in Section 6.7.

Although EPA has quantified the significant costs of the GWR, there are some costs that the Agency

did not quantify. Overall, EPA believes that these nonquantified costs are much smaller than the

nonquantified benefits. These nonquantified costs result from uncertainties surrounding rule assumptions

and from modeling assumptions. Detailed discussion of nonquantified costs is presented in Section 6.6.
Economic Analysis for the ES-15 October 2006

Final Ground Water Rule

PWSs Serving <10,000 PWSs Serving > 10,000 Total

Lower

(5th %ile)

Upper

(95th %ile)

Lower

(5th %ile)

Upper

(95th %ile)

Lower

(5th %ile)

Upper

(95th %ile)

$ 29 79 $ 158 $ 62 $ 24 $ 117 $ 141 $ 53 $ 275 $ 

$ 12 31 $ 60 $ 0 $ 0 $ 1 $ 31 $ 12 $ 61 $ 

$ 64 173 $ 339 $ 1 $ 0 $ 2 $ 174 $ 64 $ 341 $ 

$ 105 283 $ 556 $ 64 $ 24 $ 120 $ 346 $ 129 $ 676 $ 

CWS Start-Up Costs 5 $ 5 $ 5 $ 0 $ 0 $ 0 $ 5 $ 5 $ 5 $ 

NTNCWS Start-Up Costs 2 $ 2 $ 2 $ 0 $ 0 $ 0 $ 2 $ 2 $ 2 $ 

TNCWS Start-Up Costs 9 $ 9 $ 9 $ 0 $ 0 $ 0 $ 9 $ 9 $ 9 $ 

Total One-Time PWS Costs $ 16 16 $ 16 $ 0 $ 0 $ 0 $ 17 $ 17 $ 17 $ 

State Start-Up Cost $ 13 13 $ 13 $ 

Total State One-Time Costs $ 13 13 $ 13 $ 

Notes: Detail may not add to totals due to independent rounding.

Source: Exhibit 6.30

90 Percent

Confidence Bound

Mean

Value

90 Percent

Confidence Bound

Mean

Value

Total Initial PWS Capital Costs

Mean

Value

90 Percent

Confidence Bound

CWS Total Initial Capital

NTNCWS Total Initial Capital

TNCWS Total Initial Capital

Systems States Total

Lower

(5th %ile)

Upper

(95th %ile)

Lower

(5th %ile)

Upper

(95th %ile)

Lower

(5th %ile)

Upper

(95th %ile)

3 percent 50.0 $ 34.3 $ 68.8 $ 11.8 $ 10.9 $ 12.6 $ 61.8 $ 45.2 $ 81.4 $ 

7 percent 50.6 $ 35.2 $ 69.0 $ 11.7 $ 10.9 $ 12.6 $ 62.3 $ 46.1 $ 81.6 $ 

Notes: Detail may not add to totals due to independent rounding.

Source: Exhibit 6.33

Discount

Rate

Mean

Value

90 Percent

Confidence Bound

Mean

Value

90 Percent

Confidence Bound

Mean

Value

90 Percent

Confidence Bound

Exhibit ES.7 Total Initial Capital and One-Time Costs ($Millions, 2003$)

Exhibit ES.8 Total Annualized Present Value Costs of the GWR ($Millions, 2003$)

ES.6 Projected Impacts on Household Costs

The household cost analysis assumes that systems may pass some or all costs of a new regulation on

to their consumers in the form of rate increases. Exhibit ES.9 presents estimated annual household cost

increases. Only CWSs are included in this analysis because they are the only systems that serve

households directly. The top half of the exhibit shows summary statistics for all households affected by

the rule, including households that will incur minimal costs (e.g., those served by systems incurring only

implementation costs). The bottom half shows statistics only for households served by entry points

adding treatment technologies to comply with the rule (see Exhibit ES.3 for estimates of entry points

subject to corrective actions). Because treatment changes represent the majority of rule costs, this

provides insight into how the rule will affect the segment of the population most impacted by the rule.

As shown in Exhibit ES.9, mean annual household costs based on all GWSs (including those that do

not add treatment) range from $0.21 to $16.54, depending on system size. Mean household costs

reflecting the subset of GWSs that undertake corrective actions range from $0.45 to $52.38, depending on

system size. EPA estimates that, as a whole, households subject to the GWR face minimal increases in

their annual costs. Approximately 66 percent of the households potentially subject to the rule are served

by systems serving at least 10,000 people; these systems experience the lowest increases in costs due to
Economic Analysis for the ES-16 October 2006

Final Ground Water Rule

Households Mean Median

90th

Percentile

All Community Water Systems (CWSs) 

<100 289,222 16.54 $ 2.81 $ 9.31 $ 

101-500 1,303,890 3.51 $ 0.64 $ 6.11 $ 

501-1,000 1,278,081 0.97 $ 0.16 $ 1.70 $ 

1,001-3,300 4,196,105 0.37 $ 0.04 $ 0.61 $ 

3,301-10K 6,271,380 0.27 $ 0.03 $ 0.43 $ 

10,001-50K 11,468,813 0.21 $ 0.04 $ 0.49 $ 

50,001-100K 4,204,584 0.34 $ 0.10 $ 1.02 $ 

>100,000 9,755,817 0.21 $ 0.04 $ 0.62 $ 

Total 38,767,890 0.51 $ 0.09 $ 0.88 $ 

Corrective Action Community Water Systems (CWSs)

<100 70,563 52.38 $ 18.99 $ 82.21 $ 

101-500 312,484 12.00 $ 4.52 $ 25.76 $ 

501-1,000 302,557 3.23 $ 1.33 $ 6.56 $ 

1,001-3,300 919,133 1.33 $ 0.47 $ 2.59 $ 

3,301-10K 1,487,159 0.80 $ 0.25 $ 2.18 $ 

10,001-50K 2,871,250 0.45 $ 0.18 $ 1.18 $ 

50,001-100K 1,215,544 0.53 $ 0.26 $ 1.36 $ 

>100,000 2,283,144 0.68 $ 0.39 $ 1.65 $ 

Total 9,461,833 1.51 $ 0.60 $ 3.20 $ 

Source: GWR model output.

Systems Size

(Population 

Served)

significant economies of scale. Households served by small systems that undertake corrective actions

will face the greatest increases in annual costs.

Exhibit ES.9 Summary of Annual Per-Household Costs for the GWR (2003$Year)

ES.7 Comparison of Benefits and Costs, and of Regulatory Alternatives of the GWR

Exhibit ES.10 compares estimated quantified benefits with estimated costs. Based on the

comparison of these values, the estimated quantified benefits of the rule range from approximately 14% to

32% of the costs, depending on the discount rate and COI approach. The estimated quantified benefits for

the Enhanced COI approach are greater than the corresponding estimated benefits for the Traditional COI

approach. The quantified estimate of the benefits significantly understates the true benefit of the rule. As

discussed in Section ES.5.1 and Exhibit ES.6, the nonquantified health and non-health benefits far exceed

those that EPA was able to quantify.
Economic Analysis for the ES-17 October 2006

Final Ground Water Rule

5th 95th 5th 95th

Benefits 19.7 $ 6.5 $ 45.4 $ 16.8 $ 5.5 $ 38.6 $ 

Costs 61.8 $ 45.2 $ 81.4 $ 62.3 $ 46.1 $ 81.6 $ 

Net Benefits (42.1) $ Note 1 Note 1 (45.5) $ Note 1 Note 1

Benefits 10.0 $ 2.2 $ 27.0 $ 8.6 $ 1.9 $ 22.9 $ 

Costs 61.8 $ 45.2 $ 81.4 $ 62.3 $ 46.1 $ 81.6 $ 

Net Benefits (51.8) $ Note 1 Note 1 (53.7) $ Note 1 Note 1

Source: Exhibit 8.5a

Nonquantified 

Benefits

Nonquantified 

Costs

Decreased time spent on averting behavior

Avoided costs associated with outbreak response

Perceived improvement in drinking water quality and reduction in risk associated with ingestion

Benefits from optional Assessment Monitoring 

Decreased incidence of waterborne disease outbreaks and epidemic illness

Decreased illness through minimizing treatment failures or fewer episodes with inadequate treatment

Decreased incidence of other acute viral disease endpoints

Decreased incidence of bacterial illness and death

Decreased incidence of chronic bacterial and viral illness sequelae

Note 1: Because benefits and costs are calculated using different model modules, bounds are not calculated on net benefits. 

Notes: Detail may not add due to independent rounding. The Traditional COI only includes valuation for medical costs and lost work time (including 

some portion of unpaid household production). The Enhanced COI also factors in valuations for lost personal time (non-work time) such as childcare and 

homemaking (to the extent not covered by the Traditional COI), time with family, and recreation, and lost productivity at work on days when workers are ill 

but go to work anyway.

Benefits from correction of sanitary survey deficiencies identified in the distribution systems and treatment 

plant

Costs for optional Assessment Monitoring

Costs from correction of sanitary survey deficiencies identified in the distribution systems and

treatment plant

Some land costs depending on the treatment technology 

Costs for compliance monitoring for some systems that already disinfect

Cost for five repeat samples but this is small compared to the overestimate of cost for the initial

fecal-indicator sample that systems would take. 

Decreased use of bottle water and point-of-use devices (material costs)

Traditional COI

System Type

3% Discount Rate 7% Discount Rate

Mean

90% Confidence Bounds

Mean 

90%Confidence Bounds

Enhanced COI

Exhibit ES.10 Estimated Annualized National Benefits and Costs for the GWR

($Millions, 2003$)

The Agency also performed a number of other analyses related to the final rule. This process

included an analysis of net benefits, as well as cost effectiveness and efficiency analyses. In addition, the

Agency performed a number of comparisons among the four regulatory alternatives that are described in

more detail in Chapter 8. The following is a summary of these analyses. 
Economic Analysis for the ES-18 October 2006

Final Ground Water Rule

The GWR likely passes economic threshold criteria:

C The GWR has positive net benefits when both quantified and nonquantified benefits are

considered. For the Enhanced COI approach, the quantified benefits alone are approximately

27 to 32 percent of the costs of the GWR depending on the discount rate. For the Traditional

COI approach, the quantified benefits are approximately 14 to 16 percent of the costs of the

GWR. Considering that nonquantified benefits are expected to be significantly larger than

the quantified benefits, it appears likely that the final GWR would have positive net benefits

regardless of the discount rate or cost of illness approach used. Section 5.4.3.2 presents a

discussion of nonquantified benefits and estimates a portion of their value, based only on

bacterial illnesses avoided, at four times the primary analysis benefits (resulting in total

benefits that are five times the primary benefits). This includes consideration of the value of 

deaths and hospitalization costs avoided for ground water borne cases of bacterial illness

prevented by the rule. Including only these estimated bacterial illness and death benefits, the

total net benefits of the GWR would be positive using the Enhanced COI approach. Total net

benefits would still be slightly negative using the Traditional COI approach, however, other

nonquantified benefits such as indirect (non-medical) costs associated with waterborne

bacterial illness or the value of avoiding other chronic (either bacterial or viral) or other viral

illnesses (not accounted for in this analysis) would most likely make this value positive.

C The number of illnesses that must be avoided to break even with costs is well above the

estimated number of viral cases avoided, but is most likely within the bounds of cases

avoided once nonquantified cases (both bacterial and viral) are considered. The number of

deaths that must be avoided to break even, while outside the bounds of the quantitative

analysis, is small in absolute terms. Consideration of all nonquantified benefits is predicted

to result in favorable break even results. 

C The GWR is cost-effective (using either the Enhanced or the Traditional COI approach): no

other alternative achieves greater benefits at the same cost or the same benefits at lower cost.

Final GWR determinations:

C The economic analysis for this rule, considering quantified and nonquantified benefits,

supports the basis for selecting the final GWR over other alternatives. However, the

distinction between Alternative 2 and 3 on an economic basis, is not great. 

C EPA chose the final GWR because EPA believes it is more flexible, targeted, and costeffectively protective than Alternative 3. Optional assessment monitoring allows States to

most effectively target those systems at greatest risk and minimize unnecessary monitoring. 

EPA took the following considerations into account in making this judgment:

1) Under Alternative 3, some States may not be able to conduct HSAs and thereby require

systems in nonsensitive aquifers to conduct assessment monitoring unnecessarily. For

systems not at risk this additional monitoring would provide no benefit.

2) Systems with frequent TC positives in the distributions system (and subsequent frequent

triggered monitoring) would benefit little from assessment monitoring regardless if they

were located in sensitive aquifers or not because the source water would already be

thoroughly evaluated. Under Alternative 3, such systems in sensitive (or undetermined)

aquifers would be required to do assessment monitoring.
Economic Analysis for the ES-19 October 2006

Final Ground Water Rule

3) Systems identified as having significant risk factors pertaining to potential fecal

contamination at their source (e.g., aquifer condition, well characteristics, proximity to

sewage or septic), but infrequent triggered monitoring source water samples, would

benefit from assessment monitoring. States will be able to identify such systems on an

ongoing basis through a variety of tools and information readily available to them.

C The EPA believes that the final rule is a logical outgrowth of the proposed rule, that it is

supported by comments, and that it provides public health benefits while apportioning costs

in a more flexible targeted manner. 

ES.8 Conclusions

Pursuing its mandate to protect public health, EPA has promulgated the GWR to reduce the risk

that microbial contamination of ground water poses to consumers of drinking water. Over 114 million

people in the United States use ground water as a source of drinking water. It is, however, a largely

unprotected source, with considerable risk of fecal contamination. This contamination includes both viral

and bacterial pathogens causing illnesses of varying severity. EPA has determined that the final GWR

will provide important protection against illnesses and deaths attributable to ground water contamination.

EPA also believes that the GWR will provide this desired protection from ground water pathogen

contamination at a justifiable cost.
Economic Analysis for the 1-1 October 2006

Final Ground Water Rule

1. Introduction

This Economic Analysis (EA) presents the evaluation of the benefits and costs of the Ground

Water Rule (GWR). The analysis is performed in compliance with Executive Order 12866, Regulatory

Planning and Review (58 FR 51735), which requires the United States Environmental Protection Agency

(EPA or Agency) to estimate the economic impact of rules that have an annual effect on the economy of

over $100 million and make that analysis available to the public in conjunction with publication of the

final rule. Although EPA's analysis of the GWR has determined that its annual costs are most likely

below this threshold, EPA has chosen to publish a complete EA for this rule. EPA also prepared an EA

(formerly known as the Regulatory Impact Analysis) that accompanied the May 2000 proposed GWR.

EPA developed the GWR in collaboration with States and other interested stakeholders. The

primary goal of the GWR is to improve public health by identifying public ground water systems (GWSs)

that are susceptible to fecal contamination and to ensure that they take adequate measures to remove or

inactivate pathogens in drinking water they provide to the public.

This chapter provides a summary of the GWR in section 1.1. Section 1.2 outlines the

organization of this EA, and section 1.3 provides information regarding supporting calculations and

citations.

1.1 Summary of the Ground Water Rule

The GWR applies to all community and noncommunity public water systems (PWSs) that serve

ground water (referred to as GWSs in this document) as a water source, including mixed systems with any

ground water entry points to distribution systems. The GWR does not apply to ground water determined

by the State to be under the direct influence of surface water, nor does the rule apply to public water

systems that combine all of their ground water with surface water prior to treatment. These systems are

already regulated under surface water treatment rules.

The Risk-Targeted Approach of the final GWR targets ground water systems that are susceptible

to fecal contamination and requires corrective action. Key components of the strategy are:

1. Sanitary surveys and corrective action,

2. Triggered source water monitoring,

3. Corrective actions, and

4. Compliance monitoring.

In addition to the mandatory rule components listed above, the GWR provides a mechanism for

States to adopt an optional assessment source water monitoring provision, hereafter referred to as

assessment monitoring. See Chapter 3 (section 3.4.2) of this EA for details. 
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Final Ground Water Rule

1.2 Document Organization

The remainder of this EA is organized into the following chapters:

• Chapter 2 summarizes the technical, regulatory, and public health issues addressed by the rule

and provides an overview of National Primary Drinking Water Regulations (NPDWRs)

relevant to the GWR. It also explains the statutory authority for the GWR and the economic

rationale for the regulatory approach.

• Chapter 3 reviews alternative approaches EPA considered during the development of the rule

and presents the rationale for selecting the final rule requirements. 

• Chapter 4 characterizes conditions that exist (including system inventory, treatment, and

water quality data) before systems make changes to meet the GWR requirements.

• Chapter 5 presents a summary of the risk assessment performed to estimate the public health

benefits of the GWR. The economic benefits of the rule are also presented. The benefits of

other regulatory alternatives considered are compared.

• Chapter 6 presents an estimate of the costs of implementing the rule to industry, households,

and States. The costs of other regulatory alternatives considered are compared.

• Chapter 7 discusses distributional analyses performed to evaluate the effects of the rule on

different segments of the population, and considers various executive orders and

requirements, including the Regulatory Flexibility Act (RFA) and Unfunded Mandates

Reform Act (UMRA).

• Chapter 8 compares the rule’s benefits and costs to evaluate the potential net benefits and

cost-effectiveness of the rule. The results are discussed and compared to other regulatory

alternatives considered.

1.3 Calculations and Citations

This EA presents results from detailed and complex analyses. To help the reader track the

various calculations and analyses, the following are provided:

• A reference section.

• Appendices.

S Appendix A provides additional discussion of the derivation of the cost of illness values

used in the benefits model.

S Appendix B presents detailed cost of illness and value of statistical life estimates by

illness and year as used in the benefits model.

S Appendix C presents detailed benefits estimates by illness and system type.

S Appendix D presents detailed cost estimates by systems size and type.
Economic Analysis for the 1-3 October 2006

Final Ground Water Rule

S Appendix E discusses the potential implications of using a population dynamic modeling

to estimate secondary spread in the benefits model.

S Appendix F describes analyses conducted to select model forms and estimate model

parameters for infectivity dose response relationships.

S Appendix G provides summary flowcharts for the baseline risk and benefits models. 

S Appendix H presents the detailed cost effectiveness analysis of the rule alternatives using

a quality-adjusted life years approach.

S Appendix I provides detailed analysis of total coliform hit rates in ground water systems.

S Appendix J discusses changes in the cost and benefits modeling approaches between the

proposed and final rules.

S Appendix K discusses costing detail for regulatory alternatives not presented in the main

text.

S Appendix L provides summary flowcharts for the cost model. 

• Exhibits. Most tabular exhibits include a row that provides the formulas used to compute the

contents of each column.

• Sources for information used, but not calculated within the exhibits.

• Supporting electronic file outputs (i.e., GWR cost and benefits model outputs).

• Flowcharts that illustrate methodologies of analyses as well as rule requirements.
Economic Analysis for the 2-1 October 2006

Final Ground Water Rule

2. Need for the Rule

2.1 Introduction

The United States Environmental Protection Agency (EPA or Agency) is promulgating the

Ground Water Rule (GWR) to address microbial contamination of ground water-supplied drinking water

systems in accordance with the Safe Drinking Water Act (SDWA) of 1974, as amended in 1986 and again

in 1996. The 1986 SDWA Amendments directed EPA to establish National Primary Drinking Water

Regulations (NPDWRs) requiring disinfection for the inactivation of microbiological contaminants for all

public water systems (PWSs), including systems supplied by ground water sources. The 1996

Amendments included more specific language regarding ground water disinfection, specifying that the

Administrator must publish NPDWRs requiring disinfection as a treatment technique for all ground water

PWSs only “as necessary.”

This chapter summarizes the technical, regulatory, and public health issues addressed by the rule

and provides an overview of other NPDWRs relevant to the GWR. It also explains the statutory authority

for promulgating the GWR and the economic rationale for choosing a regulatory approach for

implementing the rule.

2.1.1 Description of the Issue

An estimated 147,330 PWSs in the United States, serving over 114 million people, use ground

water as their primary water source. EPA is concerned about any potential adverse health risks that may

be associated with ground water sources and, in particular, the risks associated with fecal contamination. 

Fecal contamination includes all of the bacteria and viruses—both pathogenic (disease-causing) and

nonpathogenic—found in feces. Under certain circumstances, these can make their way into ground

water sources. Unlike surface water sources, no federal regulations currently require filtration or

disinfection of ground water sources to remove microbial contaminants. There are, however, existing

requirements for distribution system monitoring and periodic inspection of ground water systems

(GWSs).

Monitoring for specific pathogenic bacteria and viruses is often difficult. Many methods for

monitoring pathogenic bacteria and viruses are not reliable or as sensitive as those for nonpathogenic

indicators of fecal contamination. Additionally, since pathogenic bacteria and viruses are shed in low

numbers by a few infected individuals and for a limited time, their numbers are low and difficult to detect

through periodic sampling compared to detection of nonpathogenic fecal microorganisms. Therefore,

because of their widespread presence in fecal material, nonpathogenic fecal organisms are often used as

indicators of fecal contamination. These indicators include strains of Escherichia coli (E. coli),

coliphage, coliform, and other bacteria. Coliphage are bacteriophages (viruses that infect bacteria) that

primarily infect E. coli. Coliforms include many bacteria that are free-living in the environment as well

as fecal coliform (bacteria more commonly found in human feces). Other bacteria that are used as

indicators of fecal contamination include fecal streptococci (enterococci) and Clostridium perfringens, a

spore-forming anaerobic organism that can persist for long periods of time in the environment.

The basic public health issue the GWR addresses is that people served by ground water sources

may face an increased risk of illness due to fecal contamination of those sources. EPA has evaluated data

on outbreaks and the occurrence of waterborne pathogens and indicators of fecal contamination in ground

water supplying PWS wells. These data indicate that there is a subset of GWSs that are susceptible to
Economic Analysis for the 2-2 October 2006

Final Ground Water Rule

fecal contamination where risk management strategies are needed to protect public health. Specifically,

the Centers for Disease Control and Prevention (CDC) reports that between 1991, the year in which the

TCR became effective, and 2000, GWSs were associated with 68 outbreaks that caused 10,926 illnesses

(Lee et al., 2002). These accounted for 51 percent of all waterborne disease outbreaks in the United

States. The major deficiencies identified by the CDC report were source water contamination and

inadequate treatment (or treatment failures). Distribution system deficiencies were also important. 

Studies of pathogen and/or fecal indicator occurrence in ground waters that supply PWSs show that a

subset of PWSs utilize contaminated wells. Using cell culture methods, one large national survey of 448

wells in 35 States found five percent of the wells positive for enteroviruses, 15 percent of the wells

positive for bacterial indicators, and 20 percent of the wells positive for viral indicators. Using another

method designed to detect viral DNA or RNA, this same study found over 30 percent of the wells positive

for viruses. 

Based on outbreak and occurrence data, inadequate sanitary surveys, difficulties in monitoring

directly for pathogenic bacteria and viruses, and uncorrected system deficiencies, EPA has concluded that

PWSs need to implement targeted risk management strategies to protect public health. Consequently,

EPA is promulgating requirements that provide a flexible, risk-based approach to achieve public health

protection. The final GWR builds on existing State programs – some which emphasize the importance of

monitoring and treatment and others which emphasize inspections and technical assistance – to identify

susceptible GWSs. PWSs will be required to take action to minimize the presence of pathogenic bacteria

and viruses, as necessary, based on the results of sampling or sanitary surveys. The GWR establishes

treatment technique requirements that allow multiple options to address significant deficiencies and fecal

contamination. Furthermore, the final GWR establishes compliance monitoring requirements to ensure

that treatment effectiveness is maintained.

2.2 Public Health Concerns to Be Addressed

EPA’s primary mission is to protect human health and the environment. The GWR requirements

are intended to achieve this mission with regard to fecal contamination of drinking water drawn from

ground water sources. This section describes the potential adverse health effects associated with

consuming fecally contaminated ground water.

2.2.1 Contaminants and Their Health Effects

Pathogenic enteric viral and bacterial microorganisms are excreted in the feces of infected

humans and animals. The word enteric (relating to the intestines or, more specifically, the human gut)

indicates that the natural habitat of these microorganisms is the intestinal tract of animals and humans. 

Enteric microorganisms, sometimes referred to as intestinal microflora, can survive in sewage and

leachate derived from septic tanks (septage). When sewage and septage are released into the

environment, they are sources of intestinal microflora and potential sources of viral and bacterial

pathogens. Once in the environment, fecal matter from infected humans or animals may make its way

into ground water sources. If an enteric pathogen is ingested, the likelihood of infection varies depending

on the number and pathogenicity of the organism. The likelihood and severity of symptomatic illness

also vary with the type of pathogen, the level of acquired immunity, and the general resistance of the

person who is exposed.

Examples of common fecal viral pathogens include enteroviruses (e.g., echoviruses and

coxsackieviruses), rotavirus, and hepatitis A virus (HAV). Viruses cannot reproduce outside of a host,
Economic Analysis for the 2-3 October 2006

Final Ground Water Rule

although they can survive and remain infectious. Also, with a few exceptions, viruses that can infect

human cells typically cannot infect the cells of other animals, and vice versa. Viruses that infect gut cells

become capable of reproducing when they infect humans. Once infected, humans shed viruses in stools,

typically for a period lasting between a few weeks to a few months. Thus, regardless of whether

individuals infected by the waterborne pathogen have actual symptoms of illness (such as diarrhea), they

still shed the virus, which may infect other people. This is called secondary spread, and it can result from

person-to-person contact or contact with contaminated surfaces. As a result, viral pathogens may infect

others via a variety of routes.

Some enteric viruses may infect cells in tissues outside the gut causing mild or serious secondary

effects (“sequelae”) such as myocarditis, conjunctivitis, meningitis, or hepatitis. There is also increasing

evidence that the human body reacts to foreign invasion by viruses in ways that may also be detrimental. 

For example, one hypothesis for the cause of adult onset (Type 2) diabetes is that the human body,

responding to coxsackie B5 virus infection, attacks both pathogenic cells and healthy pancreas cells in an

autoimmune reaction because of similarities between the two (Solimena and De Camilli, 1995).

Examples of illnesses caused by known or suspected waterborne fecal viral pathogens are shown

in Exhibit 2.1.

Examples of common fecal bacterial pathogens include E. coli, Salmonella, Shigella, and

Campylobacter jejuni. Some waterborne bacterial pathogens cause disease by rapid growth and

dissemination (e.g., Salmonella) while others primarily cause disease via toxin production (e.g., Shigella,

E. coli O157, Campylobacter jejuni). Campylobacter jejuni, E. coli, and Salmonella have a host range

that includes both animals and humans; Shigella is associated only with humans (Geldreich 1996). 

Unlike viruses, bacteria are able to reproduce outside of the host.

Most of the waterborne bacterial pathogens cause gastrointestinal illness, but some can cause

other severe illnesses as well. For example, Legionella causes Legionnaires Disease, a form of

pneumonia that has a fatality rate of about 15 percent. It can also cause Pontiac Fever, which is a milder

respiratory infection form of Legionnaires Disease. Several strains of E. coli can cause severe disease,

including kidney failure.

Some bacterial pathogens are opportunistic (i.e., they are only infectious in the presence of

another, preexisting condition or weakness). Opportunistic pathogens usually cause illness only in

immunocompromised persons or in other sensitive subpopulations, such as the very young or the elderly. 

Other pathogens, such as Salmonella, Shigella, and Campylobacter jejuni, are not entirely opportunistic

but result in certain diseases with greater frequency and severity in immunocompromised persons (Framm

and Soave, 1997).

Examples of illnesses caused by major waterborne bacterial pathogens are shown in Exhibit 2.2.
Economic Analysis for the 2-4 October 2006

Final Ground Water Rule

Exhibit 2.1 Examples of Illnesses Caused by Known or Suspected Waterborne

Fecal Viral Pathogens

Enteric Virus Illness

Poliovirus Paralysis

Coxsackievirus A Meningitis, fever, respiratory disease

Coxsackievirus B Myocarditis, meningitis, pleurodynia, eye

infections, congenital heart disease, rash, fever,

encephalitis, associated with diabetes

Echovirus Meningitis, rash, fever, gastroenteritis,

encephalitis, flaccid paralysis

Norovirus Gastroenteritis

Hepatitis A virus Hepatitis

Hepatitis E virus Hepatitis

Rotavirus Gastroenteritis

Enteric Adenovirus Eye infections, gastroenteritis, respiratory disease

Astrovirus Gastroenteritis

Note: Bold highlights indicate diseases directly caused by the enteric virus; other illnesses represent secondary

effects (“sequelae”).

Source: Adapted from Irving et al. 1996, Salvato 1992.

Exhibit 2.2 Examples of Illnesses Caused by Common Waterborne Bacterial

Pathogens

Bacterial Pathogen Illness

Campylobacter jejuni Gastroenteritis, meningitis, associated with

reactive arthritis and Guillain-Barre paralysis

Shigella species Gastroenteritis, dysentery, hemolytic uremic

syndrome, convulsions in young children,

associated with Reiters Disease (reactive

arthropathy)

Salmonella species Gastroenteritis, septicemia, anorexia, arthritis,

cholecystitis, meningitis, pericarditis, pneumonia,

typhoid fever

Vibrio cholerae Cholera (dehydration and kidney failure)

Escherichia coli (several species, including E. coli

O157:H7)

Gastroenteritis, hemolytic uremic syndrome

(kidney failure)

Yersinia enterocolitica Gastroenteritis, acute mesenteric lymphadenitis,

joint pain

Legionella species Legionnaires Disease, Pontiac Fever

Source: Adapted from Irving et al. 1996, Salvato 1992.
Economic Analysis for the 2-5 October 2006

Final Ground Water Rule

Outbreaks

Cases of 

Illness

Percent of 

Total 

Outbreaks Outbreaks

Cases of 

Illness

Percent of 

Total 

Outbreaks Outbreaks

Cases of 

Illness

Percent of 

Total 

Outbreaks

Protozoa 8 1,675 42.1% 3 576 6.1% 11 2,251 16.2%

 Giardia 136 5 26.3% 2 25 4.1% 7 161 10.3%

 Cryptosporidium 1,539 3 15.8% 1 551 2.0% 4 2,090 5.9%

Virus - - 0.0% 4 1,806 8.2% 4 1,806 5.9%

 Hepatitis A - - 0.0% - - 0.0% - - 0.0%

 Norwalk Virus - - 0.0% 4 1,806 8.2% 4 1,806 5.9%

Bacteria 6 1,037 31.6% 8 1,309 16.3% 14 2,346 20.6%

 Shigella 83 1 5.3% 4 473 8.2% 5 556 7.4%

 Campylobacter 172 1 5.3% 2 51 4.1% 3 223 4.4%

 Salmonella, non-typhoid 1 625 5.3% - - 0.0% 1 625 1.5%

 S. typhimurium 124 1 5.3% - - 0.0% 1 124 1.5%

 E. coli 22 1 5.3% 2 785 4.1% 3 807 4.4%

 Vibrio 11 1 5.3% - - 0.0% 1 11 1.5%

Undetermined 5 65 26.3% 34 4,458 69.4% 39 4,523 57.4%

Total 19 2,777 100.0% 49 8,149 100.0% 68 10,926 100.0%

NCWSs TOTAL

Causative Agent

CWSs

EPA and Centers for Disease Control and Prevention (CDC) data provide an indication of the

types of pathogens that have caused waterborne disease outbreaks. Exhibit 2.3 identifies the etiology of

bacterial and viral waterborne outbreaks in GWSs reported to the CDC from 1991 through 2000. Of the

68 outbreaks in GWSs, 14 (21 percent) were associated with specific bacterial pathogens. The fecal

bacterial pathogen, Shigella, caused more reported outbreaks (five-seven percent) than any other single

agent. Identified viral pathogens were associated with four (six percent) reported outbreaks. Etiologic

agents were not identified in 39 (57 percent) outbreaks; however, EPA suspects that many of these were

caused by viruses, given that it is generally more difficult to analyze for viral pathogens than bacterial

pathogens.

Exhibit 2.3 Etiology of Waterborne Outbreaks in Ground Water Systems,

1991-2000

Note: Detail may not add to totals due to independent rounding.

Sources: Compiled from CDC 1993, Kramer et al. 1996, Levy et al. 1998, Barwick et al. 2000, and Lee et al. 2002.

2.2.2 Sources of Contaminants

As discussed in section 2.2.1, water from ground water sources can contain microbial

contaminants. Fecal contamination of ground water can occur by several routes, including through the

subsurface, wellhead, or the distribution system. This section discusses these potential sources of viral

and bacterial fecal contamination of ground water supplies. Because pathogens are associated with

human and animal waste, the following sections discuss fecal contamination in general and not

necessarily the specific types of microbes associated with each source.
1

 For a more detailed discussion of the factors affecting bacterial and viral fate and transport, see the

Occurrence and Monitoring Document for the Final Ground Water Rule (USEPA, 2006b).

Economic Analysis for the 2-6 October 2006

Final Ground Water Rule

2.2.2.1 Ground Water Contamination through the Subsurface

Many factors control the fate and transport of viruses and bacteria in subsurface media. Because

these factors are often interrelated, defining the processes involved in the survival and migration of

viruses and bacteria is a complex task. Factors such as pH, hydrogeologic conditions, soil types,

inorganic ion content, organic matter content, microbial activity, moisture content, and type of pathogen

all affect pathogenic fate and transport. Other factors, such as climatic changes and agriculture and land

use practices, influence, and may alter, the complex soil environment. For example, wetter climatic

conditions may result in high water tables, thereby potentially reducing the distance and time required for

contaminants to enter the now-shallower aquifers. In addition, sewage and sludge application to land may

alter the physical and chemical properties of soils and affect their capacity to impact viral migration and

survival (Bitton and Gerba, 1984). These factors are likely to have a direct or indirect effect on pathogen

survival.1

Frequently, the subsurface conditions provide adequate natural attenuation of microbial

contaminants to ensure protection of the source water. However, certain hydrogeologic features make

aquifers more sensitive to microbial contamination. For example, karst, fractured bedrock, and gravel

aquifers are considered sensitive aquifers. In these hydrogeologic settings, contaminants that are

introduced into the environment are more likely to reach the drinking water production well than in

localities with greater natural attenuation capabilities (e.g., sand aquifers).

Given the right conditions, fecal contamination from a variety of sources can reach an aquifer. 

Normal septage and sewage practices release great amounts of human waste into the subsurface. Canter

and Knox (1984) estimated the volume of septic tank waste that is released into the subsurface in the

United States to be one trillion gallons per year. Contaminants from failed septic systems or sewage

lagoons, leaking sewer lines, and overflowing cesspools can enter ground water sources through the

subsurface. Other sources of fecal contamination include improperly treated wastewater used to recharge

ground water or to irrigate crop land and improper land application of raw septage or treated sewage. 

Solid wastes contaminated with human or animal bacteria and viruses may contaminate ground water

through individual waste disposal practices, open dumping practices, and landfills (Washington State

Department of Health, 1995). Improper land application of waste waters associated with food processing

or animal slaughter may also contribute to the contamination of ground water sources of drinking water. 

Microbial pathogens found in animal wastes may enter ground water from unlined or leaky manure

lagoons, spread manure, and concentrated animal feeding operations (USEPA, 1993; Washington State

Department of Health, 1995). Given the right subsurface conditions, contaminated water from any of

these sources may reach the aquifer and, possibly, the intake zone of a drinking water well.

2.2.2.2 Ground Water Contamination through the Wellhead

Conditions at or near wells may contribute to the occurrence of ground water contamination. 

Contamination may occur at the wellhead in several ways. The main causes are poor well location and/or

construction, improperly abandoned wells, and the presence of test holes or exploratory wells.
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Final Ground Water Rule

Well Location and/or Construction

Fecal contamination can enter inappropriately located or improperly constructed wells in several

ways. A well located in a low-lying area or within a well pit is susceptible to flooding. A well may be

particularly vulnerable to surface water contamination if it is not adequately cased and grouted. An

improperly constructed water-supply well may allow surface runoff or surface waters to enter through a

non-existent or broken well seal. Ground water contamination may also result from water infiltrating

through a contaminated gravelpack or the fill surrounding the intake point.

Many old wells were built before the institution of strict construction guidelines, sometimes in a

manner that could allow contamination. In some cases, newer wells, built after the institution of stricter

well construction guidelines, do not adhere to those guidelines. Such wells, if constructed in or near

potential sources of contamination, may be vulnerable to the contamination. Even wells that are built and

sited correctly may be exposed to contaminants through an improperly constructed well penetrating the

same aquifer as the properly constructed well.

Abandoned Wells

Historically, well abandonment and plugging have generally not been properly planned, designed,

and executed (USEPA, 1990; Canter et al., 1987). In many cases, the well casing was pulled out if it was

not too worn or corroded, thereby linking aquifers at different depths through the well shaft. Such wells

could then serve as conduits for contaminated ground water to spread more rapidly to other zones within

an aquifer or allow contaminants to enter adjacent aquifers at lower hydraulic pressures (USEPA, 1990). 

Other wells may not have been adequately plugged, providing a pathway for contamination from the

surface. Occasionally, abandoned wells have also been used as disposal sites for a variety of wastes,

resulting in the direct contamination of an aquifer.

Test Holes, Exploratory Wells, and Monitoring Wells

Many test holes and exploratory wells have been dug or drilled into the subsurface to search for

oil, gas, coal, minerals, and water. Other holes have been drilled for testing, including soil boreholes and

seismic shot holes. Monitoring wells are often drilled to sample ground water quality. When these holes

are not backfilled, or when the wells are not properly constructed or abandoned, they provide potential

conduits for contamination to enter ground water sources.

2.2.2.3 Contamination of Drinking Water in Distribution Systems

Even if the ground water source for a water system remains clean, contamination may occur

within the distribution system. Numerous contamination incidents in distribution systems have been

reported from systems using ground water sources. For example, if proper precautions are not taken,

water in the distribution system can become contaminated following routine maintenance or emergency

repairs (e.g., flushing or chlorination). Inadequately disinfected distribution systems, including storage

towers, can develop microbial mats or biofilms. Initially, biofilms may function as a filter, adsorbing

pathogens (Seunghyun and Corapcioglu, 1997), but the pathogens may ultimately be shed (sloughed)

from the system, potentially contaminating the drinking water at the tap.
Economic Analysis for the 2-8 October 2006

Final Ground Water Rule

2.3 Statutory Authority for Promulgating the Rule

EPA has the primary responsibility for regulating the quality of drinking water. The SDWA

establishes this responsibility and defines the mechanisms at the Agency’s disposal to protect public

health. EPA sets standards by identifying which contaminants should be regulated and by establishing

the maximum levels of the contaminants allowed in drinking water.

The 1986 Amendments to the Safe Drinking Water Act directed EPA to promulgate regulations

requiring disinfection at all public water systems using either surface water or ground water. The Surface

Water Treatment Rule (40 CFR Part 141 subpart H) implemented that requirement for surface water

systems (and systems using ground water under the direct influence of surface water), but when Congress

amended the Safe Drinking Water Act again in 1996, EPA had not promulgated regulations requiring

disinfection for systems that use ground water. In the legislative history of the 1996 Amendments to the

Safe Drinking Water Act, Congress identified several reasons for the delay, including the recognition that

not all GWSs are at risk of contamination and the high cost of across-the-board disinfection. In light of

this recognition, Section1412(b)(8) of the Safe Drinking Water Act, as amended on August 6, 1996,

requires EPA to promulgate national primary drinking water regulations (NPDWRS) requiring

disinfection as a treatment technique for all ground water systems only as necessary. In addition, Section

1412(b)(8) requires EPA to promulgate criteria as part of the regulations for determining whether

disinfection should be required as a treatment technique for any public water system served by ground

water.

Section 1413(a)(1) allows EPA to grant a State primary enforcement responsibility (primacy) for

NPDWRs when EPA has determined that the State has adopted regulations that are no less stringent than

EPA’s. To obtain primacy for the final GWR, States must adopt comparable regulations within two years

of EPA’s promulgation of the final rule, unless a two year extension is granted. State primacy requires,

among other things, adequate enforcement (including monitoring and inspections) and reporting. EPA

must approve or deny State primacy applications within 90 days of submission to EPA (section

1413(b)(2)). In some cases, a State submitting revisions to adopt an NPDWR has primacy enforcement

authority for the new regulation while EPA action on the revision is pending (section 1413(c)). Section

1445 authorizes the Administrator to establish monitoring, record keeping and reporting regulations to

assist the Administrator in determining compliance with the Safe Drinking Water Act and in advising the

public of the risks of unregulated contaminants. Section 1450 of the Safe Drinking Water Act authorizes

the Administrator to prescribe such regulations as are necessary or appropriate to carry out his functions

under the Act.

2.4 Regulatory History

The following sections summarize the development of NPDWRs and programs most relevant to

the GWR over the past 20 years. These include rules addressing microbial contaminants, rules addressing

disinfectants and disinfection byproducts (DBPs), and other rules that were considered (e.g., to determine

conflict or overlap of requirements) during the evaluation of GWR regulatory requirements. Drinking

water regulations that apply only to surface water systems, including the 1989 Surface Water treatment

Rule (SWTR), the 1998 Interim Enhanced Surface Water Treatment Rule (IESWTR), the 2001 Filter

Backwash Recycling Rule (FBRR), the 2002 Long Term 1 Enhanced Surface Water Treatment Rule

(LT1ESWTR), and the 2006 Long Term 2 Enhanced Surface Water Treatment Rule (LT2ESWTR), are

not summarized.
Economic Analysis for the 2-9 October 2006

Final Ground Water Rule

2.4.1 1979 Total Trihalomethane Rule

Under the Total Trihalomethane (TTHM) Rule (44 FR 68624, November 1979), EPA set an MCL

for TTHM, the sum of the concentrations of chloroform, bromoform, bromodichloromethane, and

dibromochloromethane, of 0.10 milligrams per liter (mg/L) as a running annual average (RAA) of

quarterly measurements. This standard applies to community water systems (CWSs) using surface or

ground water that serve at least 10,000 people and that add a disinfectant to the drinking water during any

part of the treatment process. This 1979 rule has been superceded by the 1998 Stage 1 DBPR (section

2.4.4). Compliance with the Stage 1 DBPR began in January 2002.

2.4.2 1989 Total Coliform Rule

The Total Coliform Rule (TCR) (54 FR 27544, June 1989) applies to all PWSs. Because

monitoring PWSs for every possible pathogenic organism is not feasible, coliform organisms are used as

indicators of possible system contamination. Coliforms are easily detected in water and are used to

indicate a water system’s vulnerability to pathogens. In the TCR, EPA set a Maximum Contaminant

Level Goal (MCLG) of zero for total coliforms. EPA also set a monthly MCL for total coliforms and

required testing of total coliform-positive cultures for the presence of E. coli or fecal coliforms. E. coli

and fecal coliforms indicate more immediate health risks from sewage or fecal contamination and are

used as a trigger of an acute MCL violation. Coliform monitoring frequency is determined by population

served, the type of system (community or noncommunity systems), and the type of source water (surface

water, ground water under the direct influence of surface water (GWUDI), or ground water). In addition,

the TCR required sanitary surveys every five years (ten years for noncommunity systems using

disinfected ground water) for systems that collect fewer than five total coliform samples per month (those

serving 4,100 people or fewer).

2.4.3 1996 Information Collection Rule

The Information Collection Rule (ICR) (61 FR 24354, May 1996) applied to PWSs serving at

least 100,000 people. A more limited set of ICR requirements cover GWSs serving 50,000 to 99,999

people. The ICR authorized EPA to collect occurrence and treatment information from water treatment

plants to help evaluate the possible need for changes to the current microbial requirements and existing

microbial treatment practices and to help evaluate the need for future regulation of disinfectants and

DBPs. The ICR provided EPA with information on the national occurrence of (1) chemical byproducts

that form when disinfectants used for microbial control react with naturally occurring compounds and

ions present in source water; and (2) disease-causing microorganisms including Cryptosporidium,

Giardia, viruses, and coliform bacteria. The ICR also mandated the collection of treatment train data on

how water systems currently control for contaminants. The ICR monthly sampling data provided 18

months of information on the quality of the influent and treated water, including pH, alkalinity, turbidity,

temperature, calcium, total hardness, total organic carbon, UV254 absorbency, bromide, ammonia, and

disinfectant residual. These data provide some indication of the “treatability” of the water, the occurrence

of contaminants, and the potential for DBP formation. The data collected under the ICR are continuing to

be analyzed to help develop current and future NPDWRs.
Economic Analysis for the 2-10 October 2006

Final Ground Water Rule

2.4.4 1998 Stage 1 Disinfectants and Disinfection Byproducts Rule

The Stage 1 DBPR (63 FR 69390, December 1998) applies to all CWSs and nontransient

noncommunity water systems (NTNCWSs) that add a chemical disinfectant to their water. Certain

requirements designed to provide protection against acute health effects from chlorine dioxide also apply

to transient noncommunity water systems (TNCWSs). Surface water and GWUDI systems serving at

least 10,000 people were required to begin compliance with the rule by January 2002. Surface water and

GWUDI systems serving fewer than 10,000 people and all GWSs must comply beginning January 2004.

The Stage 1 DBPR sets Maximum Disinfectant Residual Level Goals (MRDLGs) for chlorine (4

mg/L as Cl2), chloramines (4 mg/L as Cl2), and chlorine dioxide (0.8 mg/L as ClO2) and MCLGs for

bromodichloromethane (0 mg/L), bromoform (0 mg/L), dibromochloromethane (0.06 mg/L),

dichloroacetic acid (0 mg/L), trichloroacetic acid (0.3 mg/L), bromate (0 mg/L), and chlorite (0.8 mg/L). 

The rule sets Maximum Residual Disifectant Leevels (MRDLs) for chlorine (4.0 mg/L as Cl2),

chloramines (4.0 mg/L as Cl2), and chlorine dioxide (0.8 mg/L as ClO2) and MCLs for TTHM (0.080

mg/L), haloacetic acids [total of five] (HAA5) (0.060 mg/L), bromate (0.010 mg/L), and chlorite (1.0

mg/L). The MRDLs and MCLs, except those for chlorite and chlorine dioxide, are calculated as RAAs of

quarterly measurements. For surface water and GWUDI systems using conventional filtration treatment,

a treatment technique—enhanced coagulation/softening—is specified for the removal of DBP precursors.

2.4.5 2001 Arsenic Rule

The Arsenic Rule (66 FR 6976, January 2001) increases the level of public health protection

against exposure to arsenic in drinking water. The rule revises the MCL for arsenic in drinking water

from 0.05 mg/L to 0.010 mg/L and sets an MCLG of 0 mg/L for all CWSs and NTNCWSs. Clarification

on how compliance is demonstrated for many inorganic and organic contaminants in drinking water is

also given. All existing CWSs and NTNCWSs were required to comply with the Arsenic Rule by

January 23, 2006.

2.4.6 2006 Stage 2 Disinfectants and Disinfection Byproducts Rule

The Stage 2 DBPR tightens certain DBP compliance standards set by the Stage 1 DBPR. The

Stage 2 DBPR was promulgated concurrently with the LT2ESWTR and is designed to reduce DBP

occurrence peaks in the distribution system by changing compliance monitoring provisions. The

requirements in the Stage 2 DBPR apply to all CWSs and NTNCWSs that add a primary or residual

disinfectant other than ultraviolet light (UV) or that deliver water that has been treated with a disinfectant

other than UV.

For the Stage 2 DBPR, the MCLs will remain at the Stage 1 DBPR levels (0.080 mg/L for TTHM

and 0.060 mg/L for HAA5), but compliance will be measured based on locational running annual

averages (LRAAs) instead of the RAAs used in the Stage 1 DBPR. Most systems will also be required to

conduct Initial Distribution System Evaluations (IDSEs) to identify monitoring locations that represent

locations with the highest concentrations of TTHM and HAA5. In addition, the Stage 2 DBPR addresses

systems that are in full compliance with the Stage 2 DBPR LRAA MCLs but have individual DBP

measurements that exceed the MCLs. The rule provides a formula for determining averages for TTHM

and HAA5. If these averages exceed certain levels, the system must conduct an operational evaluation

and submit a written report or the operational evaluation to the State.
Economic Analysis for the 2-11 October 2006

Final Ground Water Rule

2.4.7 Underground Injection Control Program

The EPA’s Underground Injection Control (UIC) program was established to protect sources of

drinking water from underground injection of fluids through wells. Owners and operators of injection

wells are prohibited from operating their wells in a manner that causes the movement of fluid into

underground sources of drinking water if it may cause a violation of any primary drinking water

regulation or otherwise adversely affect human health. To prevent such fluid movement, EPA or the

appropriate State regulatory agency may require certain construction criteria, corrective action, operation,

monitoring, reporting, or plugging and abandonment. These regulations are designed to recognize

varying geologic, hydrological, or historical conditions among different States or areas within a State.

The regulations included in 40 CFR 144.6 define five classes of injection wells. These wells may

inject fluids that are associated with hazardous waste or radioactive waste sites, natural gas or oil

production, extraction of minerals, or other purposes. Class V wells are the most prevalent of the

injection well types and are most often associated with ground water contamination relevant to the GWR.

They include:

• Untreated sewage waste disposal wells

• Large-capacity cesspools

• Large-capacity septic systems (undifferentiated disposal method)

• Large-capacity septic systems (well disposal method)

• Large-capacity septic systems (drainfield disposal method)

• Domestic wastewater treatment plant effluent disposal wells

EPA regulates only multiple-dwelling, community, or regional septic systems, as opposed to individual or

single-family residential septic systems, as Class V wells (40 CFR 144.1(g)(1)(2)).

In November 1999, EPA finalized new UIC regulations that added requirements for two

categories of Class V wells (USEPA, 1999b). The regulation bans new large-capacity cesspools

nationwide and phases out existing large-capacity cesspools by April 2005. It also bans new motor

vehicle waste disposal wells nationwide. Operation of existing motor vehicle waste disposal wells in

ground water source water areas or other sensitive ground water areas is banned but with a provision that

owners and operators of such wells may seek a waiver from closing if they obtain a permit. The permit

conditions include requirements for meeting MCLs and other health-based standards at the point of

injection, injectate and sludge monitoring, and implementing best management practices. EPA expects to

achieve substantial protection of underground sources of drinking water by focusing the requirements on

these particular wells.
Economic Analysis for the 2-12 October 2006

Final Ground Water Rule

2.5 Economic Rationale

This section addresses the economic rationale for choosing a regulatory approach rather than nonregulatory alternatives. An economic rationale for the rule is required by Executive Order 12866,

Regulatory Planning and Review (58 FR 51735), which states:

“[E]ach agency shall identify the problem that it intends to address (including, where

applicable, the failures of the private markets or public institutions that warrant new

agency action) as well as assess the significance of that problem.” (Section 1, b(1))

In addition, Office of Management and Budget (OMB) guidance, dated January 11, 1996, states

that “in order to establish the need for the proposed action, the analysis should discuss whether the

problem constitutes a significant market failure” (USEPA, 1996a).

In a perfectly competitive market, prices and quantities are determined solely by the aggregated

decisions of buyers and sellers. Such a market occurs when many producers of a product are selling to

many buyers and where both producers and consumers have perfect information on the characteristics and

prices of each firm’s products. Barriers to entry in the industry cannot exist, and individual buyers and

sellers must be “price takers” (i.e., their individual decisions cannot affect the price). Several properties

of the public water supply do not satisfy the conditions for a perfectly competitive market and thus lead to

market failures that require regulation.

Many water systems are natural monopolies. A natural monopoly exists when it is impossible for

more than one firm in each area to recover the costs of production and survive. There are high fixed costs

associated with reservoirs and wells, transmission and distribution systems, treatment plants, and other

facilities. For other potential suppliers to enter the market, they would have to provide the same extensive

infrastructure to realize similar economies of scale and be competitive. A splitting of the market with

increased fixed costs (e.g., two supplier networks in a single market) usually makes this situation

unprofitable. The result is a market suitable for a single supplier and hostile to alternative suppliers. In

such natural monopolies, suppliers have fewer incentives for providing quality services or maintaining

competitive prices. In these situations, governments often intervene to help protect the public interest.

For example, because PWSs are legal, as well as natural, monopolies, they are often subject to

price controls, if not outright public ownership. While customers may demand improvements in water

quality, the regulatory structure may not facilitate the transmission of that demand to the water supplier or

allow the supplier to raise its price to recover the cost of the improvements. If consumers do not believe

that their drinking water is safe enough, they cannot simply switch to another water utility. Other options

for obtaining safe drinking water (e.g., buying bottled water or installing point of use filtration) most

often represent a higher water cost to consumers than the purchase from PWSs. Therefore, the water

supplier may have little incentive to improve water quality.

The public may also not understand the health and safety issues associated with poor drinking

water quality. Understanding the health risks posed by trace quantities of drinking water contaminants

involves analysis and synthesis of complex toxicological and health sciences data. Therefore, the public

may not be aware of the risks it faces. EPA has implemented a Consumer Confidence Report (CCR) Rule

(63 FR 44512, August 1998) that makes water quality information more easily available to consumers. 

This rule requires CWSs to publish an annual report on local drinking water quality. Consumers,

however, still have to analyze this information for its health risk implications. Furthermore, even if

informed consumers are able to engage water systems in a dialogue about health issues, the transaction
Economic Analysis for the 2-13 October 2006

Final Ground Water Rule

costs of such interaction (measured in personal time and monetary outlays) present another significant

impediment to consumer expression of risk reduction preferences.

SDWA regulations are intended to provide a level of protection from exposure to drinking water

contaminants. The regulations set minimum performance requirements to protect consumers from

exposure to contaminants. SDWA regulations are not intended to restructure market mechanisms or to

establish competition in supply; rather, they establish the level of service to be provided that best reflects

public preference for safety. The federal regulations reduce the high information and transaction costs by

acting on behalf of consumers in balancing risk reduction and the social costs of achieving this risk

reduction.
Economic Analysis for the 3-1 October 2006

Final Ground Water Rule

3. Consideration of Regulatory Alternatives

3.1 Introduction

The 1996 Amendments to the Safe Drinking Water Act (SDWA) require the United States

Environmental Protection Agency (EPA or Agency) to develop a national primary drinking water

regulation that requires disinfection as a treatment technique for all ground water PWSs only “as

necessary.” To address this mandate and the public health concerns presented in Chapter 2 of this EA,

EPA developed the Ground Water Rule (GWR). The Agency convened workgroups, held stakeholder

meetings, published a proposed rule, and evaluated public comments to develop a final regulation. This

chapter describes the process used to evaluate regulatory alternatives considered during the development

of the GWR and evaluated as part of this Economic Analysis (EA).

3.2 Process for Development of Regulatory Alternatives

In 1992, EPA circulated a draft proposal for review and comment, which began the process of

developing regulatory alternatives for addressing microbial contamination in ground water systems

(GWSs). In 1993, EPA published a preliminary draft of the Ground Water Disinfection Rule (later

renamed the Ground Water Rule). After review of the public comments, EPA recognized that additional

information needed to be gathered and, in 1995, convened a GWR regulatory workgroup. EPA used the

workgroup to obtain comments and additional information regarding the GWR. In 1996, EPA published

a report, Ground Water Disinfection and Protective Practices in the United States, on ground waterrelated statutes, regulations, guidance, and disinfection practices gathered from 50 State drinking water

programs (USEPA, 1996b). In 1997, EPA initiated another workgroup, including members from EPA,

other Federal agencies, and State agencies, to cooperate in the development of a proposed GWR.

In December 1997, EPA initiated stakeholder meetings. The Agency published public meeting

announcements in the Federal Register. EPA involved citizens, environmental groups, small businesses,

and water suppliers early in the rule development process and held public meetings in different regions

(Washington, DC; Portland, OR; Madison, WI; and Dallas, TX) to facilitate rule development and allow

stakeholders the opportunity to comment on the regulation.

In addition to the public meetings with stakeholders, EPA, as part of the consultation process

required by the Small Business Regulatory Enforcement Fairness Act (SBREFA), met with

representatives of small systems (i.e., those serving fewer than 10,000 people) in March and April 1998. 

EPA presented possible regulatory requirements and requested comments from the representatives during

these meetings.

In January 1999, EPA published a preliminary draft preamble for the GWR and solicited

comment. The preliminary draft preamble described regulatory alternatives and requested public

comment on a number of potential modifications. EPA received 80 comments on the preliminary draft

preamble.
Economic Analysis for the 3-2 October 2006

Final Ground Water Rule

3.3 Regulatory Alternatives Considered

EPA proposed four regulatory alternatives. The multi-barrier approach was the preferred

alternative in the proposed GWR. The primary elements of the multi-barrier approach were sanitary

surveys, triggered monitoring, HSAs, routine monitoring, corrective action, and compliance monitoring. 

After the proposal, EPA considered comments and chose a different final rule alternative, Alternative 2,

termed the risk-targeted approach. The primary elements of the risk-targeted approach include sanitary

surveys, triggered monitoring, optional assessment monitoring, corrective action, and compliance

monitoring.

The following discussion provides details of the four main regulatory alternatives considered. A

detailed comparison of the quantified benefits and costs of each of the four regulatory alternatives for the

GWR is found in Chapter 8 of this EA. 

Alternative 1: Sanitary survey and corrective action

Sanitary surveys are on-site assessments of the source water, treatment facilities, distribution

systems, finished water storage tanks, monitoring records, and the management and operation of a public

water system (PWS). This alternative requires sanitary surveys to be conducted by the State at least once

every 3 years for community water systems (CWSs) (with a provision that States may reduce frequency to

every five years for CWSs with outstanding performance and no TCR violations or that provide 4-log

treatment) and every 5 years for noncommunity water systems (NCWSs). Sanitary surveys must address

various elements set out in the EPA/State Joint Guidance on sanitary surveys. Operators would be

required to correct any significant deficiencies within 120 days of receiving the State sanitary survey

report or in accordance with a State-approved plan and schedule for correcting these deficiencies. All

systems that perform treatment (including those already achieving 4-log treatment of viruses before or at

the first customer) must perform compliance monitoring to ensure that the treatment is effective.

Alternative 2: Risk-Targeted Approach (Final Rule Alternative)

In addition to all the sanitary survey components of the first alternative, the Risk-Targeted

Approach includes a triggered source water microbial monitoring requirement for systems. Systems that

do not already achieve at least 4-log (99.99 percent) treatment of viruses (using inactivation, removal, or

State-approved combination of these technologies) before or at the first customer and that have a total

coliform (TC) positive result for any routine sample taken under the Total Coliform Rule (TCR) must

collect a ground water source sample. The ground water system must test the source water sample for a

fecal indicator (E. coli, enterococci, or coliphage) determined by the State or primacy agency. Unless the

State requires immediate corrective action for the initial fecal indicator-positive source water sample, the

system must collect and analyze five additional ground water source samples for the presence of a fecal

indicator. If any one of the five source water samples tests fecal indicator-positive, the system must take

correction action. Systems that are required to take corrective action must consult with the State within

30 days and complete the action within 120 days (or be in compliance with the State or primacy agency

approved plan and schedule) of receiving notice of the fecal indicator-positive sample in one of the five

additional samples or when the State determines a corrective action is necessary, whichever occurs first. 

The final GWR provides States with the option to require systems to conduct assessment monitoring any

time and require systems to take corrective actions. See section 3.4 for more details on this alternative.
Economic Analysis for the 3-3 October 2006

Final Ground Water Rule

Alternative 3: Multi-barrier Approach

The multi-barrier approach described in this EA includes modifications to two proposed

provisions: hydrogeologic sensitivity assessment and routine monitoring provisions. The changes made

to the multi-barrier approach stemmed from public comments received on the proposed GWR regulatory

alternative. 

The multi-barrier approach builds on the sanitary survey and triggered monitoring requirements

of the first two alternatives. This alternative includes an optional HSA provision for States rather than a

required HSA provision as proposed. An HSA is a tool used to identify those systems in aquifers where

water can move quickly through the subsurface, thereby increasing the possibility of fecal contamination. 

Under this alternative, each State has the option to complete the hydrogeologic sensitivity assessment

within six and eight years from the GWR publication date for CWSs and NCWSs, respectively. HSAs

would be conducted for all existing and new systems that do not maintain at least a 4-log treatment of

viruses (using inactivation, removal, or State-approved combination of these technologies) before or at

the first customer. If the State did not conduct an HSA to determined aquifer sensitivity, the system

would be required to conduct twelve months of assessment monitoring.

If an aquifer that a system uses as a source is identified as sensitive through an HSA or if the

State chooses not to conduct an HSA, the system would have to conduct assessment monitoring (a

derivation of routine monitoring in the proposed rule). The assessment monitoring provision involves the

system collecting a ground water source sample and testing it for the State-specified fecal indicator each

month that the system serves water to the public until a total of 12 ground water source samples is

collected. The proposed rule required a system to collect a source water sample each month that the

system serves water to the public, or otherwise specified by the State. Assessment monitoring is

performed in addition to any triggered source water monitoring samples that may be required. 

Under the multi-barrier approach, systems found to have source water contamination (either

through assessment or triggered monitoring) would be required to consult with the State within 30 days

and take corrective action within 120 days (or longer if the State or primacy agency approves a plan and

schedule) from the date the system receives notice of the fecal indicator-positive sample. 

Alternative 4: Across-the-Board Disinfection

This alternative requires all public ground water systems to install or operate disinfection

treatment processes capable of achieving a 4-log treatment of viruses (using inactivation, removal, or

State-approved combination of these technologies) before or at the first customer on a continuing basis. 

Systems treating to less than 4 logs would be required to upgrade their treatment. Unlike the other

alternatives, the across-the-board disinfection alternative does not consider the quality of a system’s

source water or potential for contamination. Similar to Alternatives 2 and 3, all systems (including those

already achieving 4-log treatment of viruses before or at the first customer) would have to conduct

compliance monitoring to ensure the treatment is effective. Also, States would be required to perform

sanitary surveys of ground water systems to ensure the treatment practices are being properly operated

and to evaluate the ground water system for potential source contamination. 

3.4 Final Rule Requirements

Following publication of the proposed GWR, EPA accepted public comments for 90 days. EPA

received approximately 3,300 comments from over 250 individuals and organizations representing a wide
Economic Analysis for the 3-4 October 2006

Final Ground Water Rule

range of stakeholders, including public water systems, States, Tribes, other organizations, and private

citizens. Each comment was read and considered as part of the process for selecting and, where

appropriate, modifying the final GWR regulatory alternative. A record of every comment received on the

proposal, as well as EPA’s response to each, can be found in the Public Comment and Response

Document for the Final Ground Water Rule (USEPA, 2006a). Copies of individual comments are also

available as part of the public record and can be accessed through EPA’s Water Docket.

Based on public comments, EPA reevaluated the regulatory alternatives, the assumptions, and

data underlying the GWR proposal. As stated in section 3.3, EPA selected Alternative 2 as the final

GWR alternative. Alternative 2, the risk-targeted approach, includes mandatory rule components and an

optional assessment monitoring provision. Exhibit 3.1 provides a flowchart of the mandatory rule

components.
Economic Analysis for the 3-5 October 2006

Final Ground Water Rule

All ground water PWSs (1) Sanitary surveys for all 

ground water PWSs

Does system 

provide 

treatment >4 

logs? (2)

Did survey 

find 

deficiencies?

NO

Must correct deficiencies (4)

YES

Compliance monitoring

YES

Conduct TCR routine 

monitoring

NO

Is TCR routine 

sample TC-positive? NO

Conduct triggered 

monitoring (3)

YES

Fecal Coliform

Indicator Positive?

Per State’s direction, take 

corrective action or take 

5 additional samples(4)

YES

Did system 

install 

treatment as 

corrective 

action? (2)

YES

Take non-treatment 

corrective actions

NO

Continue GWR 

compliance: sanitary 

surveys, compliance 

monitoring, TCR 

compliance

(1) Includes mixed systems with ground water entry points

(2) Treatment using inactivation, removal, or State-approved 

combination of these technologies.

(3) For those systems that do not receive a triggered monitoring 

waiver from the State

(4) The State may determine that the source of contamination has 

been eliminated..

Continue GWR 

compliance: sanitary 

surveys, triggered 

monitoring, TCR 

compliance

Systems are not required 

to take corrective action 

if all 5 repeat samples are 

fecal negative.

NO

All ground water PWSs (1) Sanitary surveys for all 

ground water PWSs

Does system 

provide 

treatment >4 

logs? (2)

Did survey 

find 

deficiencies?

NO

Must correct deficiencies (4)

YES

Compliance monitoring

YES

Conduct TCR routine 

monitoring

NO

Is TCR routine 

sample TC-positive? NO

Conduct triggered 

monitoring (3)

YES

Fecal Coliform

Indicator Positive?

Per State’s direction, take 

corrective action or take 

5 additional samples(4)

YES

Did system 

install 

treatment as 

corrective 

action? (2)

YES

Take non-treatment 

corrective actions

NO

Continue GWR 

compliance: sanitary 

surveys, compliance 

monitoring, TCR 

compliance

(1) Includes mixed systems with ground water entry points

(2) Treatment using inactivation, removal, or State-approved 

combination of these technologies.

(3) For those systems that do not receive a triggered monitoring 

waiver from the State

(4) The State may determine that the source of contamination has 

been eliminated..

Continue GWR 

compliance: sanitary 

surveys, triggered 

monitoring, TCR 

compliance

Systems are not required 

to take corrective action 

if all 5 repeat samples are 

fecal negative.

NO

Exhibit 3.1 Flowchart of Mandatory PWS Ground Water Rule Requirements
Economic Analysis for the 3-6 October 2006

Final Ground Water Rule

3.4.1 Mandatory Rule Components

The following subsections describe the GWR regulatory requirements with which ground water

systems and States must comply. Systems meeting certain criteria (i.e., 4-log disinfection or inactivation

of viruses) may not be required to implement all provisions.

Sanitary Surveys

The final GWR requires States to perform sanitary surveys for all GWSs. Ground water systems

must provide the State with any pertinent, existing information that will enable the State to perform the

sanitary survey. The final GWR goes beyond the existing definition of sanitary survey at 40 CFR 141.2,

explicitly references the use and relevance of source water assessments required under the 1996 SDWA

Amendments, and specifies in more detail the scope of a sanitary survey. Specifically, the final GWR

requires that States evaluate the eight components outlined in the EPA/State Joint Guidance as part of the

sanitary survey to the extent that they apply to an individual system: 

(1) source;

(2) treatment; 

(3) distribution system; 

(4) finished water storage; 

(5) pumps, pump facilities, and controls; 

(6) monitoring, reporting, and data verification; 

(7) system management and operation; and 

(8) operator compliance with State requirements. 

The final GWR requires States to conduct sanitary surveys of ground water CWSs every three

years (every five years for CWSs that meet performance criteria as described in the following paragraph)

and of ground water NCWSs every five years. States are required to complete the initial sanitary survey

cycle by December 31, 2012 for CWSs, except those that meet performance criteria (e.g., 4-log treatment

or outstanding performance and no TCR violations), and December 31, 2014 for all NCWSs and CWSs

that meet performance criteria. States may conduct more frequent sanitary survey cycles for any GWS as

appropriate.

The final GWR allows individual components of a sanitary survey to be conducted according to a

phased review process (e.g., as part of ongoing State assessment programs). While all applicable

components need not be evaluated at the same time, they must be evaluated within the required three- or

five-year frequency interval. Also, the final GWR allows the three-year CWS schedule to be extended to

a five-year frequency if the system meets performance criteria. 

Finally, the final GWR requires that GWSs correct any significant deficiencies identified in

sanitary surveys. Significant deficiencies, as determined by the State, include, but are not limited to,

defects in design, operation, or maintenance, or a failure or malfunction of the sources, treatment, storage,

or distribution system that the State determines to be causing, or have the potential for causing, the

introduction of contamination into the water delivered to consumers.

The State must provide the GWS with written notification, which describes any significant

deficiencies found, no later than 30 days after the State identifies the significant deficiency. The notice

may be sent to the PWS, or it may be provided on-site either at the time the sanitary survey is conducted

or the significant deficiency is identified. The State may specify appropriate follow-up corrective action

steps in the notice or may notify the GWS of appropriate corrective actions during the consultation
Economic Analysis for the 3-7 October 2006

Final Ground Water Rule

period. After receiving the written notification, the GWS has 30 days to consult with the State regarding

corrective actions. The GWS must correct the significant deficiency within 120 days or be on a

State-approved corrective action plan and schedule. States must confirm that the deficiencies have been

addressed within 30 days after the scheduled correction date. (See also the discussion of corrective

actions below.) 

Triggered Source Water Monitoring

A GWS must conduct triggered source water monitoring within 24 hours of receiving notification

that a sample collected in accordance with 40 CFR 141.21(a) (TCR) is total coliform-positive. A GWS

must collect at least one ground water source sample from each ground water source (e.g., a well or

spring) in use at the time the total coliform-positive sample was collected. Triggered source water

monitoring is required unless:

(1) the GWS provides at least 4-log treatment of viruses (using inactivation, removal, or a

State-approved combination of 4-log virus inactivation and removal) before or at the first

customer for each ground water source;

(2) the GWS is notified that a positive sample collected in accordance with 40 CFR

141.21(a) (TCR) has been invalidated under 40 CFR 141.21(c); or 

(3) the cause of the total coliform-positive collected under 40 CFR 141.21(a) directly relates

to the distribution system according to State criteria or a State determination. 

The State may extend the 24-hour limit on a case-by-case basis if the State determines that the system

cannot collect the ground water source water sample within 24 hours due to circumstances beyond its

control. In the case of an extension, the State must specify how much time the system has to collect the

sample. 

Systems are not required to conduct triggered source water monitoring if, according to State

criteria or a State determination, the cause of the total coliform-positive sample collected under 40 CFR

141.21(a) directly relates to the distribution system. If the decision is made according to State criteria, the

GWS must document the decision in writing; if the decision is made by the State, the State must

document the decision in writing. In the primacy application, the State must include criteria that will be

used to determine that the cause of a total coliform-positive sample collected under 40 CFR 141.21(a) is

directly related to the distribution system.

 

If the State approves the use of E. coli as a fecal indicator for triggered source water monitoring,

GWSs serving 1,000 people or fewer may use a TCR repeat sample collected from a ground water source

to simultaneously meet the requirements of 40 CFR 141.21(b) and satisfy the GWR's triggered source

water monitoring requirements for that ground water source only.

If approved by the State, GWSs with more than one ground water source may conduct triggered

source water monitoring at a representative ground water source or sources. The State may require

systems with more than one ground water source to submit for approval a triggered source water

monitoring plan that the system will use for representative sampling. A triggered source water

monitoring plan must identify ground water sources that are representative of each monitoring site in the

system's TCR sample siting plan. 
Economic Analysis for the 3-8 October 2006

Final Ground Water Rule

If any initial triggered source water sample is fecal indicator-positive, the system must collect five

additional source water samples within 24 hours at that site, unless the State requires immediate

corrective action to address contamination at that site. The samples must be tested for the same fecal

indicator for which the initial source water sample tested positive.

Ground water systems that purchase or sell finished drinking water (referred to as consecutive or

wholesale systems, respectively) must comply with triggered source water monitoring provisions for their

own sources.

 

Consecutive and wholesale systems must also comply with other triggered source water

monitoring requirements. A consecutive GWS that has a total coliform-positive sample collected under

40 CFR 141.21(a) (TCR) must notify the wholesale system(s) within 24 hours of being notified of the

total coliform-positive sample. If a wholesale GWS receives notice from a consecutive system it serves

that a sample collected under 40 CFR 141.21(a) (TCR) is total coliform-positive, the wholesale GWS

must conduct triggered source water monitoring. If the sample is fecal indicator-positive, in addition to

notifying its own customers, the wholesale GWS must notify all consecutive systems served by that

ground water source. The consecutive system is responsible for providing any required public notice to

the persons it serves.

Corrective Action

When a GWS has a significant deficiency, it must consult with the State regarding appropriate

corrective action within 30 days of receiving a written notice of the significant deficiency. When a GWS

receives a written notice from a laboratory indicating a fecal indicator positive result in one of the five

additional triggered source water monitoring samples, the GWS must consult with the State regarding

appropriate corrective action. When a GWS receives a written notice from a laboratory indicating a fecal

indicator positive result and the State has determined that corrective action is necessary, the GWS must

consult with the State regarding appropriate corrective action. Consultation must take place within 30

days. In any event, the State may specify corrective action without consultation. In the consultation

process, the State may approve and/or modify corrective actions and completion schedules proposed by

the system, or the State may specify alternatives. The State may also specify interim corrective action

measures. 

The final GWR rule requires that within 120 days (or earlier if directed by the State) of receiving

the notification from the State or laboratory described in the preceding paragraph, the GWS must either 

(i) complete appropriate corrective actions in accordance with applicable State plan review

processes or other State guidance or direction, or

(ii) be in compliance with a State-approved corrective action plan and schedule. 

If a GWS is unable to complete corrective action within 120 days or on the schedule specified by the

State, then the GWS is in violation of the treatment technique requirement. 

Systems must notify the State within 30 days of completing any State approved or specified

corrective action. As a condition of primacy, States must verify that the corrective action has been

completed within the next 30 days. States may verify that the corrective action has been completed and

has successfully addressed the significant deficiency and/or fecal contamination in the ground water

source either by a site visit or by written documentation from the system, which could consist of the

system's notification to the State.
Economic Analysis for the 3-9 October 2006

Final Ground Water Rule

Corrective Action Alternatives

When a system has a significant deficiency or a fecal indicator-positive ground water source

sample (either by the initial triggered sample, or positive additional sample, as determined by the State),

the GWS must implement one or more of the following corrective action options: 

(1) correct all significant deficiencies (e.g., repairs to well pads and sanitary seals, repairs to

piping tanks and treatment equipment, control of cross-connections);

(2) provide an alternate source of water (e.g., new well, connection to another PWS);

(3) eliminate the source of contamination (e.g., remove point sources, relocate pipelines and

waste disposal, redirect drainage or run-off, provide or fix existing fencing or housing of

the wellhead); or 

(4) provide treatment that reliably achieves at least 4-log treatment of viruses (using

inactivation, removal, or a State-approved combination of 4-log virus inactivation and

removal) before or at the first customer for each ground water source.

Compliance Monitoring for Systems Providing At Least 4-log Treatment of Viruses 

The final GWR also establishes compliance monitoring requirements for GWSs that provide at

least 4-log treatment of viruses as a corrective action. The final GWR also establishes compliance

monitoring requirements for those systems that have notified the State that they provide at least 4-log

treatment of viruses for their ground water sources before the first customer and are therefore not required

to meet the triggered source water monitoring requirement of this rule.

Treatment technologies capable of providing at least a 4-log treatment of viruses include the

following:

C Chemical Disinfection. Inactivation, with a sufficient disinfection concentration and

contact time, through disinfection with chlorine, chlorine dioxide, ozone, or through

anodic oxidation. Disinfectant concentration and contact time (CT) can be based on

existing CT tables (USEPA, 1991) or State-approved alternatives.

C Membrane Filtration. Removal with membrane technologies with an absolute molecular

weight cut-off (MWCO), or an alternate parameter that describes the exclusion

characteristics of the membrane, that can reliably achieve at least a 4-log removal of

viruses.

C Alternative Treatment. Inactivation, removal or combination of inactivation and removal

through alternative treatment technologies (e.g., ultraviolet radiation (UV)) approved by

the State, if the alternative treatment technology, alone or in combination (e.g., UV with

filtration, chlorination with filtration), can reliably provide at least 4-log treatment of

viruses.

Under the final GWR, GWSs providing 4-log treatment of viruses using chemical disinfection

must monitor for and must meet and maintain a State-determined residual disinfectant concentration (i.e.,

4-log inactivation of viruses based on CT tables) or State-approved alternatives every day the GWS

serves from the ground water source to the public. If the State has not approved compliance criteria for
Economic Analysis for the 3-10 October 2006

Final Ground Water Rule

the system to use to demonstrate 4-log treatment by the time that the system is required to conduct

compliance monitoring, the system must comply with ground water source monitoring in '141.402 until

the State approves compliance criteria for the system to use to demonstrate 4-log treatment.

Systems serving greater than 3,300 people and using chemical disinfection (e.g., chlorine) to

provide 4-log inactivation must continuously monitor the residual disinfectant concentration using

analytical methods specified in 40 CFR 141.74(a)(2) (Analytical and monitoring requirements) at a

location approved by the State, and record the lowest residual disinfectant level each day that the GWS

serves water from the ground water source to the public. The GWS must maintain the State-determined

residual disinfectant concentration every day the GWS serves from the ground water source.

Systems serving 3,300 people or fewer that use chemical disinfection must monitor the residual

disinfectant concentration using analytical methods specified in 40 CFR 141.74(a)(2) (Analytical and

monitoring requirements) at a location approved by the State either by taking at least one grab sample

every day the GWS serves water to the public or by continuously monitoring the disinfectant residual. 

Systems collecting grab samples must record the disinfectant residual level each day that the GWS serves

water from the ground water source to the public. The GWS must take a grab sample during the hour of

peak flow or at another time specified by the State. Systems serving 3,300 people or fewer that use

continuous residual monitoring equipment must record the lowest residual disinfectant level each day that

the GWS serves water from the ground water source to the public.

If a GWS taking grab samples has a sample measurement that falls below the State-specified

residual disinfectant concentration, then the system must take follow-up samples at least every four hours

until the State specified residual disinfectant level is restored. If a system using continuous monitoring

equipment fails to maintain the State specified disinfectant residual level necessary to achieve 4 log

inactivation of viruses, the system must restore the disinfectant residual level to the State specified level

within four hours. If continuous disinfectant monitoring equipment fails, the GWS must take a grab

sample at least every four hours until the equipment is back on-line. The system has 14 days to resume

continuous monitoring. Failure to restore the residual disinfectant level to that required for 4-log

inactivation of viruses within four hours, using either continuous monitoring or grab sampling, is a

treatment technique violation.

Ground water systems that use a membrane filtration treatment technology must maintain the

integrity of the membrane and monitor and operate the membrane filtration system in accordance with

State-specified monitoring and compliance requirements (e.g., membrane performance parameters and

integrity testing). If a system fails to meet these requirements or maintain the integrity of the membrane,

it must correct the problem within four hours or be in violation of the treatment technique requirement. 

Systems that use a State-approved alternative treatment technology must monitor and operate the

alternative treatment in accordance with all compliance requirements that the State determines to be

necessary to demonstrate that at least 4-log treatment of viruses is achieved. If the system does not

comply with these requirements, fails to maintain at least 4-log treatment of viruses, and does not restore

proper operation within four hours, the system is in violation of the treatment technique requirement.

GWSs providing at least 4-log treatment of viruses may discontinue treatment if the State

determines (e.g., based on source water monitoring or replacement of the source) and documents in

writing that the need for 4-log treatment of viruses no longer exists for that ground water source. GWSs

that discontinue treatment with State approval must comply with the triggered source water requirements

of this rule. GWSs that provide 4-log treatment of viruses and notify the State that they are not subject to

the source water monitoring requirements of this rule but subsequently discontinue 4-log treatment of
Economic Analysis for the 3-11 October 2006

Final Ground Water Rule

viruses must have State approval and must comply with the triggered source water requirements of the

final GWR. 

3.4.2 Optional Provision

The final GWR provides States with the option to require systems to conduct assessment source

water monitoring at any time and require systems to take corrective action. EPA believes that this

optional provision is an important tool that should be used by States to protect public health. States may

elect to require assessment source water monitoring on a case-by-case basis. EPA recommends that

States require GWSs that are most susceptible to fecal contamination to conduct assessment monitoring. 

States may use hydrogeologic sensitivity assessments (HSAs) as a tool to identify high risk systems for

assessment source water monitoring. States have other information available to them to target high risk

systems, such as source water assessments, wellhead protection plans, and historical monitoring data. 

Data on past indications of source water fecal contamination, particularly from TCR monitoring, in

combination with GWR triggered source water monitoring results, can be another important tool. 

EPA recommends that States require GWSs that are conducting assessment source water

monitoring to collect a total of 12 ground water source samples that represent each month the GWS

provides ground water to the public. For seasonal systems, EPA recommends equally distributing 12

samples or sampling during consecutive years. EPA recommends that States require corrective action for

sources that are fecally contaminated. 

3.5 Other Changes Since Proposal

In addition to modifications made to Alternative 2 since proposal, updates were made based on

comments to the assumptions, data, and analytical processes used to support the economic analysis of the

alternatives. Wherever possible, assumptions and data were updated to reflect the latest information on

the characteristics and number of entities affected, occurrence of contaminants, costs of items used as

modeling inputs, and public comment. In particular, extensive consideration was given to the appropriate

use of occurrence data to inform the benefits and cost analyses. EPA published a Notice of Data

Availability in the March 27, 2006 Federal Register to present additional occurrence studies the Agency

considered using in the final GWR economic analysis.

See Appendix J of this EA for a detailed discussion on changes in the GWR economic analysis

since proposal.
Economic Analysis for the 4-1 October 2006

Final Ground Water Rule

4. Baseline Analysis

4.1 Introduction

The baseline analysis is a characterization of the industry and its operations under the conditions

expected to exist before systems make changes to meet requirements of the GWR. The baseline allows a

consistent comparison of public health impacts (developed in Chapter 5) and the economic and financial

impacts (developed in Chapters 6 and 7) of the rule. Development of the GWR baseline consists of the

following processes:

C Compiling an industry profile—identifying and collecting information on the segment(s)

of the water supply industry subject to the GWR.

C Characterizing current disinfection practices of ground water systems—summarizing the

status of disinfection practices currently employed to ensure public health protection

from ground water contaminants.

C Characterizing current ground water quality—summarizing the relevant characteristics of

ground water sources.

Section 4.2 characterizes the water industry, including the baseline estimates of systems, entry

points, and population subject to the GWR. This section also includes an assessment of the current status

of disinfection practices among the systems potentially affected by the rule as well as estimates of annual

positive total coliform samples under the Total Coliform Rule (TCR). Source water quality is

summarized in section 4.3, and the recent history of outbreaks is presented in section 4.4. Lastly, section

4.5 itemizes and estimates the effects of significant uncertainties in the baseline analysis.

This chapter presents an analysis that is at a level of detail and precision appropriate to support

subsequent analyses and regulatory decisions under consideration for the GWR. Therefore, it does not

give an exhaustive review of the water supply industry, source waters, or industry practices.

4.2 Industry Profile

This section provides a water industry characterization that is used to derive costs and benefits for

the GWR. It is organized as follows:

Section 4.2.1 describes the data sources used to characterize the industry baseline.

Section 4.2.2 is a background section describing the various ways in which water systems can be

classified and identifies distinctions that are important for regulatory analysis.

Section 4.2.3 presents the baseline numbers of systems, entry points, and population according to

disinfection practices used for estimating treatment costs and subsequent benefits of the GWR.
1

 Data used are from the 4th quarter freeze of the 2003 database.

Economic Analysis for the 4-2 October 2006

Final Ground Water Rule

Section 4.2.4 presents the mean plant design and average daily flow for each of the nine system

size categories.

Section 4.2.5 presents the treatment practices baseline.

Section 4.2.6 estimates the total number of households in each of the nine size categories of

systems subject to the GWR.

Section 4.2.7 estimates the annual number of triggered monitoring samples that systems will have

to take as a result of positive total coliform samples taken under the Total Coliform Rule.

4.2.1 Data Sources

Several data sources were used to characterize the GWR baseline. Data from the Safe Drinking

Water Information System-Federal Version (SDWIS/FED or SDWIS) are used to create system and

population baselines (USEPA, 2003)1

. SDWIS is the United States Environmental Protection Agency’s

(EPA or Agency) national regulatory compliance database for the drinking water program. It includes

information on the nation’s 170,000 public water systems (PWSs) and on violations of drinking water

regulations. For more information on SDWIS, refer to EPA’s website

(http://www.epa.gov/safewater/sdwisfed/sdwis.htm). A second key source of data used to develop the

industry profile is the Third Edition of the Water Industry Baseline Handbook (Baseline Handbook)

(USEPA, 2001a) published in May 2001, which compiles data derived from the 1995 Community Water

System Survey (CWSS) and SDWIS. For certain analyses, CWSS raw data were used to develop

modeling inputs. The 1995 CWSS was a mail survey that covered ground and surface water systems of

all sizes (based on population served). The survey was based on a two-phase, stratified, random sample

design. Phase 1 was a telephone screening survey that provided a sampling frame for the main data

collection in Phase 2. The survey sample in Phase 2 was stratified according to water system size

(residential population served), ownership (public, private, or ancillary), and primary water source

(ground or surface). A total of 3,681 systems covering a range of source water types and system sizes

were selected to receive the main survey questionnaire. Of these, 1,980 systems responded. See the EPA

Report, “Community Water System Survey, Volume 2” (USEPA, 1997a), for more information on the

1995 CWSS sample design and data evaluation.

EPA also used the December 2000 document, “Geometries and Characteristics of Water Systems

Report” (Model Systems Report) (USEPA, 2000a). In this document, EPA analyzed 1995 CWSS data to

create equations relating flow and population, among other things.

4.2.2 Water System Characterization

Categorization of water systems is important because system size, ownership, and

consecutive/wholesale relationships affect the way in which costs and benefits are estimated. This section

explains the classifications of water systems, as defined by EPA’s National Primary Drinking Water

Regulations (NPDWRs) and describes further subdivisions according to water source, size (population

served), and ownership for regulatory analysis purposes.
Economic Analysis for the 4-3 October 2006

Final Ground Water Rule

PWS Type

NPDWRs apply to all PWSs. A PWS is defined as a system that provides water for human

consumption through pipes or other constructed conveyances if such a system has at least 15 service

connections or regularly serves an average of at least 25 individuals per day for at least 60 days per year.

PWSs are categorized as follows:

C Community Water Systems (CWSs) are PWSs that have at least 15 service connections

used by year-round residents or that regularly serve at least 25 year-round residents.

C Noncommunity Water Systems (NCWSs) are PWSs that are not classified as CWSs.

NCWSs are subdivided into two categories:

C Nontransient Noncommunity Water Systems (NTNCWSs) are NCWSs that regularly

serve at least 25 of the same people more than 6 months per year.

C Transient Noncommunity Water Systems (TNCWSs) are NCWSs that do not regularly

serve at least 25 of the same people more than 6 months per year.

Source Water Type

Systems are classified by the source from which they draw water. Systems that use either surface

water or ground water under the direct influence of surface water (GWUDI) are classified as surface

water systems. Ground water systems are, by default, systems that draw from ground water that are not

GWUDI.

Some systems may obtain water from both ground water and surface water and are referred to as

“mixed systems.” In SDWIS and the Baseline Handbook, a mixed system is categorized as a surface

water system because it gets some portion of its flow from surface water (i.e., all mixed systems are

considered surface water systems). Based on an analysis in the Geometries and Characteristics of Water

Systems Report (USEPA 2000a), it is estimated that 21 percent of systems classified as surface water

obtain some of their water from ground water sources. Furthermore approximately one-third of these, or

8 percent of all surface water systems in SDWIS and the Baseline Handbook, receive the majority of their

flow from ground water. The 1995 CWSS data are classified by primary source (i.e., if a system receives

more than 50 percent of its flow from ground water sources, it is considered a ground water system).

Population Served

Small systems are those serving fewer than 10,000 people. Systems are categorized in SDWIS

and the Baseline Handbook by retail population served (i.e., not including population of wholesale

customers). In the analyses that follow, nine size categories are most often used. System size is especially

important because smaller systems are expected to take different approaches to meet rule provisions than

large systems. Additionally, smaller systems are not able to achieve the same economies of scale as

larger systems for a given treatment technology. To account for these differences, both the compliance

decision tree and the unit costs for selected technologies use assumptions that are dependent on system

size. 
Economic Analysis for the 4-4 October 2006

Final Ground Water Rule

Ownership

Systems are categorized in SDWIS and in the Baseline Handbook according to three ownership

types: “private,” “public,” and “other.” Private systems are owned by private corporations or individuals. 

Public systems are owned by public entities such as municipalities, counties, or special districts. The

“other” category contains systems where ownership is not reported in SDWIS. Ownership distinctions

are important to the analysis because public systems have access to capital and other means of financing

that may not be available to private systems. This distinction becomes important in calculating household

costs (see Chapter 6) and in assessing the Unfunded Mandates Reform Act (UMRA) requirements (see

Chapter 7).

Consecutive and Wholesale System Types

Systems are categorized according to whether they treat water themselves or purchase treated

water from other systems. The GWR defines a consecutive system as a PWS that buys or otherwise

receives some or all of its finished water from one or more wholesale systems for at least 60 days per

year. A wholesale system is defined as a PWS that treats and then sells or otherwise delivers finished

water to another PWS at least 60 days per year. Treatment modifications are generally not made by

consecutive water systems, but are instead made by the associated wholesale systems. Costs of these

treatment modifications are typically passed on to the consecutive systems in the form of water rate

increases.

4.2.3 Baseline Number of Systems, Entry Points, and Population

The GWR applies to all PWSs, regardless of their size, that use ground water as a source. 

Further, because a person may need only ingest a small number of certain microbial pathogens (e.g.,

Shigella, enterovirus, rotavirus, norovirus) to become ill, this EA also considers the impact across all

types of ground water systems, including those noncommunity systems that provide drinking water only

part of the time or to a transient population. This section estimates the baseline number of systems, the

number of entry points, and, the size of the population subject to the GWR. These will be used to

estimate costs and benefits of the rule later in this EA.

Number of Systems

Estimates of the number of ground water PWSs subject to the GWR are presented in Exhibit 4.1. 

Most of these use ground water as their only source and reflect the SDWIS ground water system

inventory. In addition to the systems served solely by ground water, PWSs served by multiple sources

(i.e., those using both ground and surface water) may be subject to rule requirements. Entry points

delivering only ground water are often present in PWSs that are classified as surface water systems in

accordance with the SDWIS classification scheme (i.e., SDWIS classifies a system as surface water if any

portion of its source water comes from a surface source). These “mixed water” systems, and associated

ground water entry points and individuals served by them, would be excluded from the ground water

system baseline if only the SDWIS ground water inventory were used, resulting in a potential

underestimate of rule costs and benefits. To account for ground water entry points in mixed systems,

EPA derived an inventory of “primarily ground water” mixed systems that is added to the ground wateronly system inventory.
Economic Analysis for the 4-5 October 2006

Final Ground Water Rule

To derive the primarily ground water mixed system inventory, EPA identified surface water

CWSs that use primarily (more than 50 percent) ground water based on CWSS data, as presented in

Geometries and Characteristics of Public Water Systems (USEPA 2000a). NCWSs were not included in

the mixed system analysis due to lack of data on the existence of multiple sources within such systems. 

Because NTNCWSs and TNCWSs are typically a single building or located in a small area, a simplifying

assumption was made for this analysis that all NCWSs draw from a single source. The primarily ground

water mixed CWSs identified by this calculation (862 systems, as shown in Exhibit 4.1, column P) were

added to the ground water inventory to produce the baseline number of ground water systems used in this

EA (Exhibit 4.1, columns Q through U).

The resulting baseline number of ground water systems are all treated as ground water-only

systems throughout subsequent analyses. This methodology, treating mixed systems as ground wateronly systems, may overestimate costs and benefits (i.e., some surface water entry points are now counted

as ground water entry points). However, the ground water entry points in the excluded mixed surface

water inventory (those mixed systems using less than 50 percent ground water) are not included in the

analysis, potentially underestimating costs and benefits. The contrasting over- and under-accounting for

ground water entry points are expected to offset one another in the cost and benefit analyses. Data are not

available to quantify the direction or magnitude of the final effect on overall national cost estimates, but

the effect is expected to be minimal.

In addition to the baseline number of systems presented in Exhibit 4.1, the national cost model

requires system-by-system data. For ground water-only systems, systems and their associated attributes

are taken directly from SDWIS. System identity data (e.g., PWS Identification (ID) and address) are not

included in the attributes because the data are used for national level analysis and are not meant for

analysis of specific systems. To derive the system-by-system data for primarily ground water mixed

systems, a representative sample of systems was selected from the SDWIS surface water inventory. This

was done as follows:

C For each surface water system size category, all of the SDWIS systems were placed in

ascending order by population served.

C Within this ordered system list, systems were selected at equal intervals based on the

overall number of primarily ground water mixed systems. For example, the SDWIS

surface water inventory includes a total of 1,163 systems serving 100 or fewer people. 

Based on CWSS data, as presented in Geometries and Characteristics of Public Water

Systems (USEPA 2000a), 3.7 percent of these systems (43 systems) are primarily ground

water mixed systems. To select a representative sample of systems from the SDWIS

inventory for this size category, every 27th system (1,163/43) was selected from the

SDWIS surface water system list (ordered by population served) and assigned, along with

its attributes (minus system identity data), to the primarily ground water mixed system

data set.

Selection in this manner ensures that the systems chosen represent the full range of population served

within any given size category. The resulting system data were added to the SDWIS ground water data

for use in the cost model.
Economic Analysis for the 4-6 October 2006

Final Ground Water Rule

Number of Ground Water Only Systems Number of Surface Water Systems

Public Private Public Private

Purchased 

Systems

NonPurchased 

Systems

Purchased 

Systems

NonPurchased 

Systems

Purchased 

Systems

NonPurchased 

Systems

Purchased 

Systems

NonPurchased 

Systems

ABCDEFGH I J

CWSs

≤100 1,402 174 120 11,104 12,800 459 220 324 160 1,163 

101-500 604 4,284 252 9,022 14,162 848 357 607 226 2,038 

501-1,000 324 2,735 92 1,498 4,649 629 274 367 76 1,346 

1,001-3,300 325 4,135 81 1,224 5,765 1,169 864 301 128 2,462 

3,301-10,000 114 2,105 18 408 2,645 868 910 137 77 1,992 

10,001-50,000 33 1,032 6 201 1,272 708 823 92 98 1,721 

50,001-100,000 1 110 - 27 138 111 172 17 31 331 

100,001-1 Million 1 52 - 12 65 58 180 9 24 271 

> 1 Million - 3 - - 3 - 13 - 3 16 

National Total 15,858 1,576 569 23,496 41,499 4,850 3,813 1,854 823 11,340 

NTNCWSs

≤100 1,913 11 13 7,519 9,456 

101-500 18 3,076 14 3,650 6,758 

501-1,000 7 1,162 3 722 1,894 

1,001-3,300 8 374 1 332 715 

3,301-10,000 4 28 1 40 73 

10,001-50,000 3 5 - 2 10 

50,001-100,000 - 1 - - 1 

100,001-1 Million - - - 1 1 

> 1 Million - - - - - 

National Total 6,559 51 32 12,266 18,908 

TNCWSs

≤100 51,730 71 521 12,126 64,448 

101-500 33 3,773 45 15,142 18,993 

501-1,000 18 622 9 1,291 1,940 

1,001-3,300 9 268 5 303 585 

3,301-10,000 1 41 2 30 74 

10,001-50,000 1 9 1 8 19 

50,001-100,000 1 - - - 1 

100,001-1 Million - 1 - - 1 

> 1 Million - - - - - 

National Total 56,444 134 583 28,900 86,061 

Grand Total 78,861 1,761 1,184 64,662 146,468 4,850 3,813 1,854 823 11,340 

System Size 

(population served)

Total 

Ground 

Water Only 

Systems

Total 

Surface 

Water 

Systems

Exhibit 4.1 Ground Water Rule System Baseline (continued on next page)
Economic Analysis for the 4-7 October 2006

Final Ground Water Rule

Number of Primarily Ground Water Systems

Public Private Public Private

Purchased 

Systems

NonPurchased 

Systems

Purchased 

Systems

NonPurchased 

Systems

Purchased 

Systems

NonPurchased 

Systems

Purchased 

Systems

NonPurchased 

Systems

K L=F*K M=G*K N=H*K O=I*K P=J*K Q=A+L R=B+M S=C+N T=D+O U=E+P

CWSs

≤100 3.7% 17 8 12 6 43 191 1,410 132 11,110 12,843 

101-500 9.6% 81 34 58 22 196 685 4,318 310 9,044 14,358 

501-1,000 0.0% - - - - - 324 2,735 92 1,498 4,649 

1,001-3,300 5.9% 69 51 18 8 145 394 4,186 99 1,232 5,910 

3,301-10,000 12.0% 104 109 16 9 239 218 2,214 34 417 2,884 

10,001-50,000 10.0% 71 82 9 10 172 104 1,114 15 211 1,444 

50,001-100,000 8.9% 10 15 2 3 29 11 125 2 30 167 

100,001-1 Million 14.0% 8 25 1 3 38 9 77 1 15 103 

> 1 Million 0.0% - - - - - - 3 - - 3 

National Total 325 360 116 60 862 1,936 16,183 685 23,556 42,361 

NTNCWSs

≤100 1,913 11 13 7,519 9,456 

101-500 3,076 18 14 3,650 6,758 

501-1,000 1,162 7 3 722 1,894 

1,001-3,300 374 8 1 332 715 

3,301-10,000 28 4 1 40 73 

10,001-50,000 5 3 - 2 10 

50,001-100,000 1 - - - 1 

100,001-1 Million - - - 1 1 

> 1 Million - - - - - 

National Total 6,559 51 32 12,266 18,908 

TNCWSs

≤100 51,730 71 521 12,126 64,448 

101-500 3,773 33 45 15,142 18,993 

501-1,000 622 18 9 1,291 1,940 

1,001-3,300 268 9 5 303 585 

3,301-10,000 41 1 2 30 74 

10,001-50,000 9 1 1 8 19 

50,001-100,000 - 1 - - 1 

100,001-1 Million 1 - - - 1 

> 1 Million - - - - - 

National Total 56,444 134 583 28,900 86,061 

Grand Total 360 - 325 116 60 862 2,121 79,186 1,300 64,722 147,330 

Notes: Surface water systems include mixed systems. Detail may not add to totals due to independent rounding.

Ground Water System Baseline

Total 

Primarily 

Ground 

Water 

Systems

Total 

Number of 

Ground 

Water 

Systems

Percentage 

of SW that is 

Primarily 

(>50%) GW

Sources: (A-J) Ground water system inventories for CWSs, NTNCWSs, and TNCWSs: SDWIS (USEPA, 2003a).

(F-J) Surface water system inventory for CWSs: SDWIS (USEPA, 2003a).

(K) Percent of surface water CWSs served by more than 50% ground water from Geometries and Characteristics of Public Water Systems 

(USEPA 2000a), Exhibit 2.9.

System Size 

(population served)

Exhibit 4.1 Ground Water Rule System Baseline (continued)

Number of Disinfecting Systems

The system inventory presented in Exhibit 4.1 represents the baseline for rule activities that are

applicable to PWSs on a system level (i.e., rule implementation and performance of sanitary surveys),

regardless of any other factors. The applicability of other rule requirements (i.e., triggered source water

monitoring and compliance monitoring) are dependent upon whether a system (or entry point) achieves 4-

log treatment of viruses (using inactivation, removal, or State-approved combination of these

technologies) before or at the first customer. Exhibit 4.2 shows the system baseline stratified according to

disinfecting and nondisinfecting systems.
Economic Analysis for the 4-8 October 2006

Final Ground Water Rule

Number of DisinfectingGround Water Systems Number of Nondisinfecting Ground Water Systems

Public Private Public Private

Purchased 

Systems

NonPurchased 

Systems

Purchased 

Systems

NonPurchased 

Systems

Purchased 

Systems

NonPurchased 

Systems

Purchased 

Systems

NonPurchased 

Systems

A B=Sys*A C=Sys*A D=Sys*A E=Sys*A F=Sys*A

G=Sys*

(1-A) 

H=Sys*

(1-A) 

 I=Sys*

(1-A) 

 J=Sys*

(1-A) 

K=Sys*

(1-A) 

CWSs

≤100 52.8% 101 745 70 5,866 6,781 90 666 62 5,244 6,062 

101-500 77.9% 534 3,364 242 7,045 11,185 151 954 69 1,999 3,173 

501-1,000 84.0% 272 2,297 77 1,258 3,905 52 438 15 240 744 

1,001-3,300 79.7% 314 3,336 79 982 4,710 80 850 20 250 1,200 

3,301-10,000 86.8% 189 1,922 30 362 2,503 29 292 5 55 381 

10,001-50,000 96.5% 100 1,075 15 203 1,394 4 39 1 7 51 

50,001-100,000 86.3% 9 108 1 26 145 1 17 0 4 23 

100,001-1 Million 96.4% 9 74 1 15 99 0 3 0 1 4 

> 1 Million 100.0% - 3 - - 3 - - - - - 

National Totals 12,925 1,529 514 15,757 30,725 408 3,258 171 7,799 11,636 

NTNCWSs

≤100 29% 3 555 4 2,181 2,742 8 1,358 9 5,338 6,714 

101-500 29% 5 892 4 1,059 1,960 13 2,184 10 2,592 4,798 

501-1,000 29% 2 337 1 209 549 5 825 2 513 1,345 

1,001-3,300 29% 2 108 0 96 207 6 266 1 236 508 

3,301-10,000 29% 1 8 0 12 21 3 20 1 28 52 

10,001-50,000 29% 1 1 - 1 3 2 4 - 1 7 

50,001-100,000 29% - 0 - - 0 - 1 - - 1 

100,001-1 Million 29% - - - 0 0 - - - 1 1 

> 1 Million 29% - - - - - - - - - - 

National Totals 1,902 15 9 3,557 5,483 36 4,657 23 8,709 13,425 

TNCWSs

≤100 18% 13 9,311 94 2,183 11,601 58 42,419 427 9,943 52,847 

101-500 18% 6 679 8 2,726 3,419 27 3,094 37 12,416 15,574 

501-1,000 18% 3 112 2 232 349 15 510 7 1,059 1,591 

1,001-3,300 18% 2 48 1 55 105 7 220 4 248 480 

3,301-10,000 18% 0 7 0 5 13 1 34 2 25 61 

10,001-50,000 18% 0 2 0 1 3 1 7 1 7 16 

50,001-100,000 18% 0 - - - 0 1 - - - 1 

100,001-1 Million 18% - 0 - - 0 - 1 - - 1 

> 1 Million 18% - - - - - - - - - - 

National Totals 10,160 24 105 5,202 15,491 110 46,284 478 23,698 70,570 

Grand Totals 24,987 1,568 629 24,516 51,699 554 54,199 672 40,206 95,631 

(B-K) Sys = System inventory from Exhibit 4.1, columns Q-U.

Sources:(A) CWS percent disinfecting from Third Edition of the Baseline Handbook, Table B1.3.3, except for systems serving >1 million people. The three ground water 

systems serving >1 million people all perform disinfection. NTNCWS and TNCWS percent disinfecting derived from Ground Water Disinfection Practices in the United 

States (USEPA 1996b).

System Size 

(population 

served)

Percentage2 

of Systems 

Disinfecting Total Total

Notes: Detail may not add to totals due to independent rounding. 

Footnotes: 1) "Disinfection" refers to primary disinfection that is intended for microbial inactivation; 2) Percentages shown are weighted for item-level nonresponse, as 

indicated in Table 6.1 of “Geometries and Characteristics of Water Systems Report” (Model Systems Report) (USEPA, 2000a)."

Exhibit 4.2 Ground Water Rule System Baseline: Disinfecting1 and

Nondisinfecting Systems
Economic Analysis for the 4-9 October 2006

Final Ground Water Rule

Number of Entry Points

The GWR benefits and cost models use entry points as a metric for exposure potential and for

estimating the number of points of treatment and monitoring in response to GWR requirements. Ground

water systems can consist of one entry point supplying all water to the population, or multiple entry

points treating water, possibly from different sources.

As with the system baseline, the GWR requirements at the entry point level also depend on

whether disinfection is applied. In order to estimate baseline disinfection rates, EPA analyzed data from a 

survey of disinfection practices in CWSs serving fewer than 10,000 people (AWWA, 1998). In this

analysis, EPA used the data on the number of systems that apply disinfection prior to entry to the

distribution system, the flow rates, the volume of the distribution system prior to the first customer, and

the contact time (CT) value required for inactivation of Hepatitis A virus (HAV) at a temperature of 15

degrees C, and a pH of 6-9. EPA assumed that those systems providing insufficient information for the

CT calculation in the AWWA survey are not currently achieving 4-log virus inactivation. Where

additional assumptions were necessary, they were made to not overestimate the amount of 4-log treatment

in place (e.g., maximum flow rate), and any treatment provided prior to distribution was not accounted

for. Based on the evaluation, EPA found that 52 percent of small community ground water systems

applying disinfection met 4-log inactivation of viruses prior to the first customer. The number was also

applied to community ground water systems serving 10,000 or more people. 

Because the AWWA survey did not have any data on NCWSs, EPA used best professional

judgement to estimate the percent of NCWSs that achieved 4-log inactivation of viruses before the first

customer. Because of their small size and usually simple design as well as the transient nature of the

populations they serve, TNCWSs are believed to be the least likely systems to achieve 4-log inactivation.

Based on this characterization, EPA estimates that only 10 percent of TNCWSs that apply disinfection

(see Exhibit 4.3) achieve 4-log inactivation of viruses before the first customer. Many NTNCWSs are

relatively simple systems that share many characteristics with TNCWSs. However, many also share

characteristics more like CWSs (e.g., systems serving large institutions). Because of this dichotomy, EPA

estimated that the percentage of NTNCWSs that apply disinfection that are achieving 4-log inactivation

of viruses before the first customer falls between the percentages used for CWSs and TNCWSs, or 31

percent. Exhibit 4.3 shows the entry point baseline used for GWR analyses.

Population

System population characteristics are important to this analysis for several reasons. It is

important to know the total population served by ground water systems as well as the average population

served by each entry point so that the distribution of costs and benefits of the GWR can be assessed. 

Exhibit 4.4 presents the system-level population baseline and Exhibit 4.5 presents the entry point-level

baseline. 

As presented in Exhibit 4.4, ground water CWSs serve over 100 million people, while ground

water NCWSs serve about 14 million people. Overlaps do occur because individuals may be served by

both types of systems. For example, a person may be served by a surface water CWS at home and by a

ground water NCWS at work or at a restaurant. It should be noted that there does not appear to be a

consistent reporting standard for populations served by transient systems. In addition, some States may

report the total population served by a system over a year, while others may report the average population

served each day.
Economic Analysis for the 4-10 October 2006

Final Ground Water Rule

Number of Ground Water Entry Points Disinfecting to 4-Log

Public Private Public Private

Purchased Entry 

Points

Non-Purchased 

Entry Points

Purchased Entry 

Points

Non-Purchased 

Entry Points

Purchased 

Entry Points

Non-Purchased 

Entry Points

Purchased 

Entry Points

NonPurchased 

Entry Points

A B C D=Sys*A*B*C E=Sys*A*B*C F=Sys*A*B*C G=Sys*A*B*C H=Sys*A*B*C

I=Sys*

A*(1-B*C) 

 J=Sys*

A*(1-B*C) 

 K=Sys*

A*(1-B*C) 

L=Sys*

A*(1-B*C) 

M=Sys*

A*(1-B*C) 

CWSs

≤100 45.6% 52.0% 59 1.3 439 41 3,457 3,996 191 1,412 132 11,122 12,857 

101-500 1.6 72.9% 52.0% 424 2,669 192 5,589 8,873 694 4,371 314 9,155 14,534 

501-1,000 2.0 75.1% 52.0% 247 2,087 70 1,143 3,547 386 3,257 110 1,784 5,536 

1,001-3,300 2.4 72.1% 52.0% 358 3,809 90 1,121 5,378 598 6,350 150 1,868 8,966 

3,301-10,000 3.2 73.5% 52.0% 268 2,723 42 513 3,547 434 4,402 68 829 5,734 

10,001-50,000 5.6 91.4% 52.0% 277 2,975 41 563 3,856 306 3,285 45 621 4,257 

50,001-100,000 11.3 59.3% 52.0% 38 436 5 104 583 85 979 12 232 1,308 

100,001-1 Million 12.4 82.2% 52.0% 48 409 7 81 545 65 548 9 109 730 

> 1 Million 11.4 100.0% 100.0% - 34 - - 34 - - - - - 

National Totals 15,581 1,720 488 12,570 30,359 2,758 24,603 840 25,721 53,921 

NTNCWSs

≤100 1.0 29% 31% 1 172 1 676 850 10 1,741 12 6,843 8,606 

101-500 1.0 29% 31% 2 277 1 328 608 16 2,799 13 3,322 6,150 

501-1,000 1.0 29% 31% 1 104 0 65 170 6 1,058 3 657 1,724 

1,001-3,300 1.0 29% 31% 1 34 0 30 64 7 340 1 302 651 

3,301-10,000 1.0 29% 31% 0 3 0 4 7 4 25 1 36 66 

10,001-50,000 1.0 29% 31% 0 0 - 0 1 3 5 - 2 9 

50,001-100,000 1.0 29% 31% - 0 - - 0 - 1 - - 1 

100,001-1 Million 1.0 29% 31% - - - 0 0 - - - 1 1 

> 1 Million 1.0 29% 31% - - - - - - - - - - 

National Totals 590 5 3 1,103 1,700 46 5,969 29 11,163 17,208 

TNCWSs

≤100 1.0 18% 10% 1 931 9 218 1,160 70 50,799 512 11,908 63,288 

101-500 1.0 18% 10% 1 68 1 273 342 32 3,705 44 14,869 18,651 

501-1,000 1.0 18% 10% 0 11 0 23 35 18 611 9 1,268 1,905 

1,001-3,300 1.0 18% 10% 0 5 0 5 11 9 263 5 298 574 

3,301-10,000 1.0 18% 10% 0 1 0 1 1 1 40 2 29 73 

10,001-50,000 1.0 18% 10% 0 0 0 0 0 1 9 1 8 19 

50,001-100,000 1.0 18% 10% 0 - - - 0 1 - - - 1 

100,001-1 Million 1.0 18% 10% - 0 - - 0 - 1 - - 1 

> 1 Million 1.0 18% 10% - - - - - - - - - - 

National Totals 1,016 2 10 520 1,549 132 55,428 573 28,380 84,512 

Grand Totals 17,186 1,727 501 14,193 33,608 2,936 86,000 1,441 65,264 155,641 

Percentage of 

Disinfecting 

Entry Points 

Achieving

4-Log

Number of Ground Water Entry Points Not Disinfecting or

Disinfecting to <4-Log

System Size 

(population 

served)

Percentage 

of Entry 

Points 

Disinfecting Total Total

Entry 

Points 

per 

System

Exhibit 4.3 Ground Water Rule Entry Point Baseline (continued on next page)
Economic Analysis for the 4-11 October 2006

Final Ground Water Rule

Public Private Public Private

Purchased 

Entry Points

NonPurchased 

Entry Points

Purchased 

Entry Points

NonPurchased 

Entry Points

Purchased 

Entry Points

NonPurchased 

Entry Points

Purchased 

Entry Points

NonPurchased 

Entry Points

 N=Sys*

A*(1-B) 

 O=Sys*

A*(1-B) 

 P=Sys*

A*(1-B) 

 Q=Sys*

A*(1-B) 

R=Sys*

A*(1-B) S=I-N T=J-O U=K-P V=L-Q W=M-R 

 1,007 136 94 7,931 9,168 55 405 38 3,191 3,689 

 1,908 303 137 3,996 6,343 391 2,463 177 5,159 8,191 

 1,331 158 45 729 2,262 228 1,926 65 1,055 3,274 

 2,834 267 67 834 4,002 331 3,516 83 1,034 4,964 

 1,888 186 29 356 2,459 248 2,514 39 474 3,274 

 538 50 7 102 698 256 2,746 37 520 3,559 

 576 50 7 137 770 35 403 5 96 538 

 170 20 3 34 227 45 377 6 75 503 

 - - - - - - - - - - 

 10,252 1,170 389 14,117 25,929 1,588 14,351 450 11,604 27,992 

 1,358 8 9 5,338 6,714 2 383 3 1,505 1,892 

 2,184 13 10 2,592 4,798 4 616 3 730 1,352 

 825 5 2 513 1,345 1 233 1 144 379 

 266 6 1 236 508 2 75 0 66 143 

 20 3 1 28 52 1 6 0 8 15 

 4 2 - 1 7 1 1 - 0 2 

 1 - - - 1 - 0 - - 0 

 - - - 1 1 - - - 0 0 

 - - - - - - - - - - 

 4,657 36 23 8,709 13,425 10 1,312 6 2,454 3,783 

 42,419 58 427 9,943 52,847 12 8,380 84 1,964 10,441 

 3,094 27 37 12,416 15,574 5 611 7 2,453 3,077 

 510 15 7 1,059 1,591 3 101 1 209 314 

 220 7 4 248 480 1 43 1 49 95 

 34 1 2 25 61 0 7 0 5 12 

 7 1 1 7 16 0 1 0 1 3 

 - 1 - - 1 0 - - - 0 

 1 - - - 1 - 0 - - 0 

 - - - - - - - - - - 

 46,284 110 478 23,698 70,570 22 9,144 94 4,682 13,942 

 61,193 1,316 890 46,524 109,923 1,620 24,807 551 18,740 45,718 

Note: Detail may not add to totals due to independent rounding.

(C) Percentage of disinfecting entry points achieving 4 log derived from AWWA data (1998).

(D-R) Sys = System inventory from Exhibit 4.1, columns T-X.

Number of Ground Water Entry Points Not Disinfecting

Total

Number of Ground Water Entry Points Disinfecting to <4-Log

Total

Sources: (A) CWS entry points derived from Question 18 and 20 of the 1995 CWSS. NTNCWS and TNCWS entry points to system ratio assumed to be 1:1 

because these systems are most often housed in a single building or small area.

(B) CWS percent disinfecting from Third Edition of the Baseline Handbook, Table B1.3.5, except for systems serving >1 million people. Ground water systems 

serving >1 million people (3) all perform disinfection. NTNCWS and TNCWS percent disinfecting derived from Ground Water Disinfection Practices in the 

United States (USEPA 1996b).

Exhibit 4.3 Ground Water Rule Entry Point Baseline (continued)
Economic Analysis for the 4-12 October 2006

Final Ground Water Rule

Disinfecting Systems Population

Public Private Public Private

Purchased

NonPurchased PurchasedNonPurchased PurchasedNonPurchased PurchasedNonPurchased

A B=Sys*A C=Sys*A D=Sys*A E=Sys*A F=Sys*A G=Sys*A H=Sys*A I=Sys*A J=Sys*A K=Sys*A L=F+K

CWSs

≤100 5,882 58 43,427 4,065 342,143 395,517 5,258 38,821 3,634 305,855 353,568 749,084 

101-500 235 125,587 791,234 56,851 1,657,070 2,630,742 35,629 224,471 16,128 470,106 746,334 3,377,075 

501-1,000 712 193,786 1,635,819 55,026 895,962 2,780,593 36,912 311,585 10,481 170,659 529,637 3,310,229 

1,001-3,300 1,839 577,381 6,134,719 144,735 1,804,890 8,661,725 147,062 1,562,545 36,865 459,715 2,206,186 10,867,911 

3,301-10,000 5,632 1,066,489 10,824,258 168,362 2,039,704 14,098,814 162,185 1,646,085 25,603 310,185 2,144,059 16,242,873 

10,001-50,000 20,569 2,060,372 22,118,232 301,712 4,184,262 28,664,578 74,729 802,216 10,943 151,761 1,039,648 29,704,225 

50,001-100,000 65,030 610,540 7,032,405 84,911 1,670,104 9,397,959 96,922 1,116,384 13,479 265,127 1,491,912 10,889,872 

100,001-1 Million 207,247 1,822,052 15,423,507 251,731 3,068,718 20,566,008 68,043 575,982 9,401 114,599 768,025 21,334,033 

> 1 Million 1,311,178 - 3,933,533 - - 3,933,533 - - - - - 3,933,533 

National Totals 67,937,134 6,462,088 1,067,392 15,662,854 91,129,468 626,739 6,278,088 126,535 2,248,008 9,279,369 100,408,836 

NTNCWSs

≤100 161 50 27,985 190 109,993 138,329 394 68,514 466 269,294 338,668 476,998 

101-500 226 1,180 201,651 918 239,280 443,028 2,889 493,696 2,247 585,823 1,084,655 1,527,684 

501-1,000 673 1,366 226,696 585 140,856 369,502 3,343 555,013 1,433 344,853 904,643 1,274,145 

1,001-3,300 1,552 3,601 168,338 450 149,433 321,822 8,816 412,137 1,102 365,854 787,909 1,109,731 

3,301-10,000 5,153 5,978 41,845 1,494 59,779 109,096 14,636 102,449 3,659 146,355 267,098 376,195 

10,001-50,000 20,764 18,065 30,108 - 12,043 60,217 44,228 73,713 - 29,485 147,427 207,644 

50,001-100,000 66,000 - 19,140 - - 19,140 - 46,860 - - 46,860 66,000 

100,001-1 Million 110,000 - - - 31,900 31,900 - - - 78,100 78,100 110,000 

> 1 Million - - - - - - - - - - - - 

National Totals 715,762 30,350 3,638 743,285 1,493,035 74,306 1,752,383 8,906 1,819,766 3,655,361 5,148,396 

TNCWSs

≤100 488 38 355,608 3,582 83,358 443,036 2,223 1,619,993 16,316 379,742 2,018,274 2,461,310 

101-500 177 1,051 120,171 1,433 482,276 604,932 4,788 547,445 6,529 2,197,036 2,755,799 3,360,731 

501-1,000 641 2,076 71,722 1,038 148,864 223,700 9,455 326,736 4,728 678,160 1,019,079 1,242,779 

1,001-3,300 1,416 2,294 68,320 1,275 77,242 149,130 10,452 311,234 5,807 351,880 679,372 828,502 

3,301-10,000 5,017 903 37,029 1,806 27,094 66,832 4,114 168,687 8,229 123,429 304,459 371,291 

10,001-50,000 15,770 2,839 25,547 2,839 22,709 53,933 12,931 116,382 12,931 103,451 245,696 299,629 

50,001-100,000 51,850 9,333 - - - 9,333 42,517 - - - 42,517 51,850 

100,001-1 Million 125,000 - 22,500 - - 22,500 - 102,500 - - 102,500 125,000 

> 1 Million - - - - - - - - - - - - 

National Totals 700,897 18,984 11,972 841,543 1,573,397 86,482 3,192,977 54,539 3,833,698 7,167,696 8,741,092 

Grand Totals 69,353,793 6,511,422 1,083,002 17,247,682 94,195,899 787,526 11,223,447 189,980 7,901,471 20,102,425 114,298,324 

Note: Figures are derived using unrounded source data. Detail may not add to totals due to independent rounding.

Sources: (A) Derived from SDWIS (USEPA, 2003a).

(B-K) Sys = System inventory from Exhibit 4.2, columns B-K.

System Size

(population

served) Total

Total 

Total Population

Average 

Population

per System

Nondisinfecting Systems Population

Exhibit 4.4 Ground Water Rule System Population Baseline
Economic Analysis for the 4-13 October 2006

Final Ground Water Rule

Population of Entry Points Disinfecting to 4-Log

Public Private Public Private

Purchased

NonPurchased PurchasedNonPurchased PurchasedNonPurchased PurchasedNonPurchased

A B=EP*A C=EP*A D=EP*A E=EP*A F=EP*A G=EP*A H=EP*A I=EP*A J=EP*A K=EP*A 

CWSs

≤100 2,641 44 19,503 1,825 153,653 177,623 8,498 62,745 5,873 494,345 571,461 

101-500 144 61,114 385,033 27,665 806,370 1,280,182 100,102 630,671 45,314 1,320,806 2,096,894 

501-1,000 364 90,092 760,500 25,582 416,537 1,292,711 140,606 1,186,903 39,925 650,084 2,017,519 

1,001-3,300 758 271,608 2,885,858 68,086 849,046 4,074,597 452,834 4,811,406 113,515 1,415,559 6,793,314 

3,301-10,000 1,750 469,599 4,766,165 74,134 898,128 6,208,026 759,075 7,704,178 119,832 1,451,762 10,034,847 

10,001-50,000 3,662 1,014,771 10,893,630 148,598 2,060,825 14,117,824 1,120,330 12,026,817 164,056 2,275,198 15,586,401 

50,001-100,000 5,758 218,153 2,512,761 30,340 596,748 3,358,001 489,309 5,636,028 68,051 1,338,483 7,531,871 

100,001-1 Million 807,902 16,727 6,838,821 111,618 1,360,677 9,119,019 1,082,193 9,160,667 149,513 1,822,641 12,215,014 

> 1 Million 115,450 - 3,933,533 - - 3,933,533 - - - - - 

National Totals 32,995,805 2,935,880 487,848 7,141,984 43,561,516 4,152,947 41,219,417 706,079 10,768,878 56,847,321 

NTNCWSs

≤100 50 50 8,675 59 34,098 42,882 505 87,824 597 345,190 434,116 

101-500 226 366 62,512 285 74,177 137,339 3,703 632,835 2,880 750,926 1,390,345 

501-1,000 673 423 70,276 181 43,665 114,546 4,286 711,433 1,837 442,044 1,159,599 

1,001-3,300 1,552 1,116 52,185 140 46,324 99,765 11,300 528,290 1,413 468,963 1,009,966 

3,301-10,000 5,153 1,853 12,972 463 18,531 33,820 18,760 131,322 4,690 187,603 342,375 

10,001-50,000 20,764 5,600 9,334 - 3,733 18,667 56,693 94,488 - 37,795 188,976 

50,001-100,000 66,000 - 5,933 - - 5,933 - 60,067 - - 60,067 

100,001-1 Million - 110,000 - - 9,889 9,889 - - - 100,111 100,111 

> 1 Million - - - - - - - - - - - 

National Totals 221,886 9,409 1,128 230,418 462,841 95,247 2,246,259 11,416 2,332,632 4,685,555 

TNCWSs

≤100 49 38 35,561 358 8,336 44,304 2,663 1,940,041 19,539 454,764 2,417,006 

101-500 177 105 12,017 143 48,228 60,493 5,734 655,599 7,819 2,631,085 3,300,237 

501-1,000 641 208 7,172 104 14,886 22,370 11,323 391,286 5,662 812,138 1,220,409 

1,001-3,300 1,416 229 6,832 127 7,724 14,913 12,517 372,721 6,954 421,398 813,589 

3,301-10,000 5,017 90 3,703 181 2,709 6,683 4,927 202,013 9,854 147,814 364,608 

10,001-50,000 15,770 284 2,555 284 2,271 5,393 15,486 139,375 15,486 123,889 294,236 

50,001-100,000 51,850 933 - - - 933 50,917 - - - 50,917 

100,001-1 Million - 125,000 2,250 - - 2,250 - 122,750 - - 122,750 

> 1 Million - - - - - - - - - - - 

National Totals 70,090 1,898 1,197 84,154 157,340 103,567 3,823,784 65,314 4,591,087 8,583,753 

Grand Totals 33,287,781 2,947,187 490,172 7,456,556 44,181,696 4,351,761 47,289,460 782,810 17,692,597 70,116,628 

System Size

(population

served)

Total 

Disinfecting to 

4-log

Average 

Population 

per Entry 

Point

Total not 

Disinfecting 

to 4-log

Population of Entry Points Not Disinfecting or

Disinfecting to <4-Log

Exhibit 4.5 Ground Water Rule Entry Point Population Baseline

(continued on next page)
Economic Analysis for the 4-14 October 2006

Final Ground Water Rule

Population of Entry Points Not Disinfecting

Public Private Public Private

Purchased

NonPurchased PurchasedNonPurchased PurchasedNonPurchased PurchasedNonPurchased

L=EP*A M=EP*A N=EP*A O=EP*A P=EP*A Q=EP*A R=EP*A S=EP*A T=EP*A U=EP*A 

 44,743 6,060 4,188 352,511 407,502 2,438 18,002 1,685 141,834 163,960 

 275,256 43,689 19,777 576,465 915,187 56,413 355,415 25,537 744,341 1,181,706 

 484,903 57,444 16,311 265,589 824,247 83,162 702,000 23,614 384,496 1,193,271 

 2,147,537 202,119 50,666 631,825 3,032,147 250,715 2,663,869 62,848 783,734 3,761,167 

 3,304,641 325,599 51,401 622,721 4,304,361 433,476 4,399,537 68,431 829,041 5,730,486 

 1,971,158 183,619 26,888 372,898 2,554,563 936,711 10,055,659 137,168 1,902,300 13,031,838 

 3,316,557 287,937 40,045 787,639 4,432,178 201,372 2,319,471 28,006 550,844 3,099,693 

 2,847,909 336,437 46,481 566,631 3,797,458 745,756 6,312,758 103,032 1,256,010 8,417,556 

 - - - - - - - - - - 

 14,392,704 1,442,904 255,758 4,176,277 20,267,644 2,710,043 26,826,712 450,321 6,592,600 36,579,676 

 68,514 394 466 269,294 338,668 111 19,309 131 75,896 95,447 

 493,696 2,889 2,247 585,823 1,084,655 814 139,139 633 165,103 305,689 

 555,013 3,343 1,433 344,853 904,643 942 156,420 404 97,190 254,956 

 412,137 8,816 1,102 365,854 787,909 2,485 116,153 311 103,109 222,057 

 102,449 14,636 3,659 146,355 267,098 4,125 28,873 1,031 41,247 75,277 

 73,713 44,228 - 29,485 147,427 12,465 20,775 - 8,310 41,549 

 46,860 - - - 46,860 - 13,207 - - 13,207 

 - - - 78,100 78,100 - - - 22,011 22,011 

 - - - - - - - - - - 

 1,752,383 74,306 8,906 1,819,766 3,655,361 20,942 493,876 2,510 512,866 1,030,194 

 1,619,993 2,223 16,316 379,742 2,018,274 439 320,047 3,223 75,022 398,732 

 547,445 4,788 6,529 2,197,036 2,755,799 946 108,154 1,290 434,049 544,438 

 326,736 9,455 4,728 678,160 1,019,079 1,868 64,550 934 133,978 201,330 

 311,234 10,452 5,807 351,880 679,372 2,065 61,488 1,147 69,518 134,217 

 168,687 4,114 8,229 123,429 304,459 813 33,326 1,626 24,385 60,149 

 116,382 12,931 12,931 103,451 245,696 2,555 22,993 2,555 20,438 48,540 

 - 42,517 - - 42,517 8,400 - - - 8,400 

 102,500 - - - 102,500 - 20,250 - - 20,250 

 - - - - - - - - - - 

 3,192,977 86,482 54,539 3,833,698 7,167,696 17,085 630,808 10,775 757,389 1,416,057 

 19,338,064 1,603,691 319,204 9,829,741 31,090,701 2,748,070 27,951,396 463,606 7,862,856 39,025,927 

Note: Figures are derived using unrounded source data. Detail may not add to totals due to independent rounding.

Sources:

 (B-U) EP = Entry points per system from Exhibit 4.3, columns D-Y.

(A) Average population per system from Exhibit 4.4, column A divided by entry points per system from Exhibit 4.3, column A.

Population of Entry Points Disinfecting to <4-Log

Total Not 

Disinfecting

Total 

Disinfecting 

to <4-log

Exhibit 4.5 Ground Water Rule Entry Point Population Baseline

(continued)
Economic Analysis for the 4-15 October 2006

Final Ground Water Rule

Uncertainty in Baseline Input Data

Although EPA recognizes that there is uncertainty related to the various data sources used to

define the system inventory for the GWR, the uncertainty in the system inventory data inputs is not

quantified in this EA. However, a qualitative discussion of the identified uncertainties follows below.

As noted above, SDWIS and the 1995 CWSS are the sources of system inventory data. SDWIS

is EPA’s primary drinking water database, containing data for over 170,000 PWSs. SDWIS stores Statereported information on each water system, including name, ID number, population served, type of

system, and source of water (ground water or surface water), along with monitoring and violation

information. In 1998, EPA began a major effort to assess the quality of its drinking water data in SDWIS. 

The results of this effort, published in the report Data Reliability Analysis of the EPA SDWIS/FED, found

that the data quality of the required inventory data was high (USEPA 2000b). Thus, EPA believes that

uncertainty in the system inventory data from SDWIS with respect to numbers of systems, source

information, and size classification is low.

The 1995 CWSS was developed to gather data on water systems in the United States. A total of

3,681 systems covering a range of source water types and system sizes were selected statistically to

receive the main survey questionnaire. Of these, 1,980 systems responded. These responses were given a

weighting factor to maintain statistical representation of the total universe of CWSs. This weighting

factor was used in all evaluations of data. The EPA report, “Community Water System Survey” (USEPA

1997a) provides information on the 1995 CWSS survey design and data evaluation.

The 1995 CWSS was the primary data source used to estimate percentage of ground water

systems that disinfect, the number of entry points per system, and average and design flow based on

population served. Because the CWSS is a statistical sample, estimates based on the data will contain

uncertainty because of sampling and other errors. The resulting sampling error uncertainty in some of the

CWSS estimates were characterized in the published report by confidence bounds (95 percent) on the

means and proportions provided. While these confidence bounds were not directly used to quantify

uncertainty in the CWSS data elements used in this EA, most of the 95 percent confidence intervals for

CWSS data related to those used in this EA were with within +/- 10 percent of the best estimates

provided.

4.2.4 Water Treatment Plant Design and Average Daily Flows

Treatment technology costs are based on the volume of water treated per day. The cost analysis

described in Chapter 6 uses two types of treatment plant flow:

Design flow—the maximum capacity at which the plant was intended to operate, expressed in

millions of gallons per day (mgd).

Average daily flow—the flow produced by a treatment plant in one day, averaged over 365 days,

expressed in mgd.

Design flows are used to estimate the capital costs of the technology that will be installed to meet the

requirements of the GWR. Average daily flows are used to estimate the annual cost of continuing

operations and maintenance (O&M). 
Economic Analysis for the 4-16 October 2006

Final Ground Water Rule

System Size 

(population served)

Average Population 

Served per Entry Point

Design Flows (MGD)

Per Entry Point

Average Daily Flow (MGD) Per 

Entry Point

X Y = 0.39639 X 0.97708 / 1,000 Y = 0.06428 X 1.07652 / 1,000

≤ 100 0.016 44 0.004 

101-500 144 0.051 0.014 

501-1,000 364 0.126 0.037 

1,001-3,300 758 0.258 0.081 

3,301-10,000 1,750 0.585 0.199

10,001-50,000 3,662 1.203 0.441 

50,001-100,000 5,758 1.872 0.718 

100,001-1 Million 16,727 5.306 2.263

> 1 Million 115,450 35.034 18.107 

≤ 100 0.02 50 0.00 

101-500 226 0.08 0.02 

501-1,000 673 0.23 0.07 

1,001-3,300 1,552 0.52 0.18 

3,301-10,000 5,153 1.68 0.64

10,001-50,000 20,764 6.55 2.86 

50,001-100,000 66,000 20.29 9.92 

100,001-1 Million 110,000 33.42 17.19 

>1 Million - - - 

≤ 100 0.01 38 0.00 

101-500 177 0.06 0.02 

501-1,000 641 0.22 0.07 

1,001-3,300 1,416 0.48 0.16 

3,301-10,000 5,017 1.64 0.62

10,001-50,000 15,770 5.01 2.12 

50,001-100,000 51,850 16.03 7.65 

100,001-1 Million 125,000 37.86 19.72 

>1 Million - - - 

CWSs

Source: Equations relating mean population to flow are from the Baseline Handbook (USEPA, 2001a). 

Population per system (X) data are from Exhibit 4.5, column A.

Note: Flow rates are calculated from unrounded population data.

TNCWSs

NTNCWSs

To derive flow information for different sized systems, EPA developed the following regression

equations from the Baseline Handbook (USEPA 2001a) relating design and average daily flow (MGD)

for ground water systems to population served (X), using data from the 1995 CWSS: 

Design Flow (MGD) = (0.39639*X0.97708)/1,000

Average Daily Flow (MGD) = (0.06428*X1.07652)/1,000

The derivation of these equations is presented in detail in the Model Systems Report (USEPA, 2000a) and

summarized in the Baseline Handbook (USEPA, 2001a). The equations are used in this EA to estimate

mean flows per entry point for each size category, using the average population served per entry point. 

Exhibit 4.6 presents the average population per entry point and corresponding average daily and design

flows.

Exhibit 4.6 Design Flows and Average Daily Flows per Plant (MGD)
Economic Analysis for the 4-17 October 2006

Final Ground Water Rule

This EA uses a single regression equation to estimate flows for both publicly and privately owned

systems. There is, however, a slight difference in the flow characteristics for these two ownership types,

as discussed in the Model Systems Report (USEPA, 2000a). The use of different flow equations for

public and private systems would not affect total national costs, although per-household costs may be

slightly affected. EPA has evaluated the equations and believes that the differences are small and would

have a negligible effect on estimated household costs.

Comparable analyses relating average daily and design flow to population were not performed for

the NCWSs. Other drinking water rules have evaluated flows for NCWSs according to service categories

(e.g., schools, restaurants, hotels, and industry) instead of size. EPA considered using this method for

evaluating NTNCWSs for the GWR, but decided against it for the following reasons:

C Service category flows are based on mean population served for all systems in that

category, regardless of source water type. EPA expects that ground water sources would

be less prevalent in larger NCWSs, but has no basis for developing revised population

estimates for each service category by source.

C The prediction of technology selection in Chapter 6 is a function of population served

and does not directly apply to service categories that may include a wide range of water

system sizes and flows (e.g., schools can be very small local buildings or large

metropolitan high schools).

EPA, therefore, applied the CWS regression equations to NCWSs, recognizing that this may

over-estimate flows and, therefore, costs. This over-estimation is addressed as part of the uncertainties

summarized in section 4.5. Mean plant flows for CWSs and NCWSs may differ from each other because

of the difference in mean population per plant within each size category. 

4.2.5 Treatment Practices Baseline

To properly estimate the cost of compliance with the GWR, the EA takes into account the

percentage of systems presently employing certain types of disinfection. These percentages are used for

determining what additional treatment technologies will be installed to comply with the rule. The GWR

compliance forecast for treatment technology selection (see section 6.3.6.2) was developed based on the

assumption that systems would install technologies in approximately the same proportions as the

technologies that are currently employed. Exhibit 4.7 displays the percentage of systems using various

treatment technologies. Because some systems perform no treatment and some may perform more than

one type of treatment, percentages do not total to 100 percent of systems by system size.

4.2.6 Number of Households Served

Because CWS costs are often passed onto customers in the form of water rate increases, the GWR

also conducts analyses to assess the impact of the rule provisions at a household level. The number of

households served by CWSs expected to be subject to the GWR is estimated by dividing the population

for each system size category by the average number of people per household (2.59, according to the

2000 U.S. Census) (U.S. Bureau of the Census, 2001a). As shown in Exhibit 4.8, CWSs serve almost 39

million households.
Economic Analysis for the 4-18 October 2006

Final Ground Water Rule

Service Population Category (Population Served)

<100 101-500

501-

1,000

1,001-

3,300

3,301-

10,000

10,001-

50,000

50,001-

100,000 >100,000

64.2% 69.9% 56.7% 73.2% 60.6% 57.4% 36.2% 38.1%

1.3% 0.0% 0.0% 0.0% 0.0% 0.0% 3.1% 0.0%

0.0% 0.0% 0.0% 0.0% 0.0% 0.6% 1.4% 0.7%

0.0% 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% 0.6%

0.3% 0.5% 0.0% 0.7% 1.0% 2.6% 0.0% 0.0%

0.0% 0.7% 0.0% 0.6% 0.6% 0.2% 0.3% 0.0%

23.0% 23.4% 32.5% 28.3% 42.5% 41.9% 54.5% 65.8%

0.0% 1.0% 0.0% 0.0% 0.0% 0.6% 0.0% 0.0%

0.0% 0.0% 0.0% 0.0% 0.1% 1.1% 3.9% 4.3%

0.0% 0.0% 0.0% 0.0% 0.1% 0.1% 0.0% 0.0%

Notes: Represents treatment practices for plants treating water that comes entirely or partly from ground sources.

Percentages may not add to 100% because systems may perform more than one treatment.

Sources: Community Water System Survey (CWSS), 1997. Volume II, Table 1-23.

Chloramines

Ozone

Treatment Type

Chlorine

Chloramines

Post-disinfection

combinations

Pre-Disinfection

Pre-disinfection/

oxidation combinations

Filtration

Reverse Osmosis

Post-Disinfection

Chlorine/

Hypochlorination

Chlorine dioxide

Chlorine dioxide

Number of Household Served by Disinfecting Systems

Public Private Public Private

Purchased

NonPurchased PurchasedNonPurchased PurchasedNonPurchased PurchasedNonPurchased

<100 2,271 16,767 1,569 132,102 152,709 2,030 14,989 1,403 118,091 136,513 

101-500 48,489 305,496 21,950 639,795 1,015,730 13,756 86,668 6,227 181,508 288,160 

501-1,000 74,821 631,590 21,245 345,931 1,073,588 14,252 120,303 4,047 65,892 204,493 

1,001-3,300 222,927 2,368,617 55,882 696,869 3,344,295 56,781 603,299 14,234 177,496 851,809 

3,301-10,000 411,772 4,179,250 65,005 787,531 5,443,557 62,620 635,554 9,886 119,763 827,822 

10,001-50,000 795,510 8,539,858 116,491 1,615,545 11,067,404 28,853 309,736 4,225 58,595 401,408 

50,001-100,000 235,730 2,715,214 32,784 644,828 3,628,556 37,422 431,036 5,204 102,365 576,028 

100,001-1 Million 703,495 5,955,022 97,193 1,184,833 7,940,544 26,272 222,387 3,630 44,247 296,535 

> 1 Million - 1,518,739 - - 1,518,739 - - - - - 

National Totals 26,230,554 2,495,015 412,121 6,047,434 35,185,123 241,984 2,423,972 48,855 867,957 3,582,768 

Note: Detail may not add to totals due to independent rounding

Sources: System CWS population baseline (Exhibit 4.4) divided by 2.59 people per household (U.S. Bureau of the Census, 2001a).

System Size

(population

served) Total Total

Number of Households Served by Non-Disinfecting Systems

Exhibit 4.7 Disinfection Treatment Practices for Disinfecting

Ground Water Systems

Exhibit 4.8 Ground Water Rule CWS Household Baseline

4.2.7 Triggered Monitoring Baseline

The Ground Water Rule (GWR) requires specified systems to conduct triggered source water

monitoring with every sample that tests positive for total coliform (TC) collected in accordance with the

Total Coliform Rule (TCR) (40 CFR 141.21). An important variable used in the cost and benefits models

is the number of a system’s TCR samples that would test positive for total coliform each year. The
2

 X-log virus inactivation or removal means that only one of every 10x viruses survives treatment in such a

condition that it is capable of initiating infection in a human host. 10-x is the fraction that is neither inactivated nor

removed.

3

 System-years can be defined as the sum, across systems, of the number of years covered by their DV data. 

Almost every DV system produces 1 year of DV data, so system-years are approximately equal to the number of

systems.

Economic Analysis for the 4-19 October 2006

Final Ground Water Rule

average varies by system type (CWS, NTNCWS, and TNCWS) and by system size (eight size categories). 

This is an important variable because indicator monitoring is “triggered” by positive total coliform

(TC-positive) samples. Information from the Data Verification (DV) project were used as the primary

inputs for modeling the occurrence of TC-positive samples, while data from other sources were used for

weighting results. The following is a summary of the derivation of this baseline. More detailed

discussion and calculations are presented in Appendix I. 

Data Verification (DV)

The DV study involves the comparison of 1 year’s worth of PWS records in SDWIS/Fed with

State PWS records to identify any discrepancies between the two records. State files contain the water

systems’ reports on the numbers of total coliform samples taken to comply with the TCR and the numbers

of TC-positive samples. Using these data, EPA derived national estimates of the percent of all TCR

samples that test positive for total coliform, and the number of total coliform samples per year that test

positive for all systems in the eight categories.

Description of Method

Several steps were taken to compile the data and weight them appropriately for each system type

and size category.

1) Estimate the fraction of samples that are TC positive by type (CWS, NTNCWS, and

TNCWS) and size of system (those serving at most 1,000 people, and those serving more

than 1,000 people).

2) Estimate the number of routine TC samples taken by each system according to its type

and size category. (Monitoring requirements under the TCR are related to system size.)

3) Multiply the fraction positive by the number of TC samples taken to estimate the number

of TC samples that will test positive, per system and per year, for each of the three

system types and eight system sizes.

Step 1: The raw annual fractions positive were computed for systems in the DV sample by

dividing the total number of routine samples that tested positive for TC by the total number of TC

samples that were taken for each type and size of system. The DV data includes information on systems’

treatment processes, including disinfection steps. This is important, since triggered monitoring under the

GWR applies only to systems that provide less than 4-log2

 virus inactivation, removal, or State-approved

combination of these technologies. Thus, only systems listed as nondisinfecting in the DV database were

used in this step. This is a large sample, comprising 1,252 system-years3

 of data and 18,467 TC samples
4 There are several reasons why states could not be included in the analysis. Four States, (Alaska, Colorado,

Connecticut, and Illinois), the U.S. Territories and Regional DI programs are not included in this analysis because

data on the percent of systems that do not disinfect are not available, even though DV data are available. Arkansas

had no nondisinfecting systems in the DV sample. Two States, New York and North Dakota, could not be included

because the data verification forms for these States could not be located. Texas requires disinfection by all ground

water systems, but the DV project identified one wholesale system that took samples of source water before

disinfection, and so the one Texas system was included. Data were not included from systems if the systems reported

that no samples were taken, or if there was no information in SDWIS on whether disinfection was used. 

5

 2004, 4th Quarter

6

 USEPA, 1996b

7 In a few cases, the rounding caused the estimated number of systems to drop below the number observed

in the DV inventory, and so in these cases, the DV inventory number was used.

Economic Analysis for the 4-20 October 2006

Final Ground Water Rule

from 43 States4 and is broadly representative of nondisinfecting ground water systems in the United

States. Weights based on the number of samples taken were used to extrapolate these raw rates to the

universe of nondisinfecting systems, as follows:

C The number of nondisinfecting systems was estimated by state, type, and size using two

sources of data: a SDWIS inventory5

 for the number of ground water systems and a

1996 EPA study6

 for the percentages of systems by state that do not disinfect their

ground water. The percentage of systems that do not disinfect was multiplied by number

of systems and rounded to the nearest integer to estimate the total number of

nondisinfecting systems in each state, size, and system type category.7

 

C The DV data provided values for: 1) the number of TC samples taken by each system

according to state and size category and 2) the associated numbers of systems. The

average number of samples taken per system was derived for each state and size category

by dividing its number of TC samples by its number of systems in the DV dataset. The

total national number of samples taken in a size category was then calculated by

multiplying the average number of DV samples per system by the total number of

systems of that size in the US. 

C A weighted TC-positive rate was derived for each size category and type of system by

multiplying its state-specific raw TC-positive rate by the appropriate weight (number of

samples assayed by the state, within the relevant size category and type of system),

summing the weighted TC-positive rates across states, and dividing by the sum of the

weights.

C To improve consistency across size categories, the TC-positive data were combined into

two size categories: those systems serving at most 1,000 people and those serving more

than 1,000 people. The resulting approximate confidence intervals (using a 90 percent

confidence level, about estimates of 0.5) were +/- 4 percent for systems serving at most

1,000 people. For systems serving more than 1,000 people, the confidence intervals were

+/- 11 percent for CWS systems, +/- 29 percent for NTNCWS, and +/- 27 percent for

TNCWS. 
8

 Arkansas was included because there were DV data for disinfecting systems.

Economic Analysis for the 4-21 October 2006

Final Ground Water Rule

C Exhibit 4.9 shows that TC-positive rates varied by size and type of system from 0.71

percent to 6.36 percent. These values are a good representation of the TC-positive rates

for systems in these size and type categories.

Exhibit 4.9 Total Coliform Positive Hit Rates

Type of

System

Size of System

(Population Served)

TC-positive Hit

Rate (percentage

of samples)

CWS #1,000 2.72%

>1,000 0.71%

NTNCWS #1,000 2.98%

>1,000 2.25%

TNCWS #1,000 6.36%

>1,000 3.53%

Source: Appendix I.

Step 2: This step estimates the average number of routine TC samples taken annually by each

system, according to its size and type. The data set for this step was expanded to include disinfecting

systems and includes 2,774 system-years of data and 94,307 TC samples from 44 states8

. This expanded

data set improves the estimate of the average number of samples taken. Systems were grouped according

to their baseline monitoring requirements under the TCR, and the number of samples taken was weighted

by the number of systems subject to triggered monitoring. The average number of samples per system

was calculated by dividing the sum of the weighted number of samples by the number of systems subject

to triggered monitoring. Exhibit 4.10 presents the results of this analysis, and Appendix I presents

additional detail for the calculations used.

Step 3: EPA estimated the frequency of total coliform-positives per year per system by

multiplying the number of TC samples per year (from Exhibit 4.10) by the probability of a TC-positive

(from Exhibit 4.9). So, for example, the estimated number of TC-positive samples per system per year

for CWSs serving less than 100 people is 0.0272 * 14 = 0.38; for TNCWs serving greater than 100,000

people it is 0.0353 * 1,496 = 52.8, Exhibit 4.11 shows these estimated frequencies for all system types

and sizes.
Economic Analysis for the 4-22 October 2006

Final Ground Water Rule

Exhibit 4.10 Estimated Number of Routine Total Coliform Samples 

Taken Per System, Per Year, by Type and Size of System

System Type

Population

Served

TCR Baseline

Number of

Routine Samples

per System

Estimated Actual

Number of

Routine Samples

per System

CWS 

<100 12 14

101-500 12 15

500-1K 12 18

NTNCWS + TNCWS

<100 4 7

101-500 4 8

500-1K 4 9

CWS + NTNCWS + TNCWS

1011-3300 24 31

3301-10K 84 82

10,001-50K 360 311

50,001-100K 960 924

>100,001 2,520 1,496

 Source: Appendix I.

Exhibit 4.11 Estimated Number of TC+ Samples Per System, Per Year, 

by System Size and System Type

System

Type

System Size (Population Served)

<100

101-

500 501-1K

1,001-

3,300

3,301-

10K

10,001-

50K

50,001-

100K >100K

CWS 0.38 0.41 0.49 0.22 0.58 2.2 6.6 10.6

NTNCWS 0.22 0.23 0.28 0.70 1.8 7.0 20.8 33.7

TNCWS 0.47 0.48 0.60 1.1 2.9 11.0 32.6 52.8

Source: Derived from Exhibits 4.9 and 4.10.

The results of these analyses are used in both the benefits and cost models to estimate the number

of indicator samples that systems will have to take to comply with the triggered monitoring provisions of

the GWR. Further discussions of the application of these results are presented in Chapter 5 (section

5.2.5.5) for the benefits model and Chapter 6 (section 6.3.4) for the cost model.
Economic Analysis for the 4-23 October 2006

Final Ground Water Rule

4.3 Water Quality Baseline

This section provides an overview of baseline water quality data that are used in the GWR risk

assessment model. It describes how existing historical, geological, and water quality (e.g., pathogen

occurrence) data are used to characterize the baseline conditions for ground water systems. Next it

describes how this information is used in a risk assessment model to estimate the baseline number of

illnesses and deaths associated with ingesting pathogenic viruses (only) in public ground water systems. 

The standard framework is organized in accordance with EPA Policy for Risk Characterization (USEPA

1995a), EPA’s Guidance for Risk Characterization (USEPA 1995b), EPA’s Policy for Use of

Probabilistic Analysis in Risk Assessment (USEPA 1997b), and with EPA’s developing guidance for

microbial risk assessment.

This standard framework requires the use of scientific data (or reasonable assumptions if data are

not available) to produce estimates of the nature, extent, and degree of a risk. Where there is uncertainty

in the data and assumptions used, that uncertainty is described and its impact on the risk estimates is

characterized. Where feasible, variability and uncertainty are mathematically modeled. The EA accounts

for different risk levels within the affected population (variability) and the confidence bounds on key

parameters of the risk assessment model (uncertainty). Variability arises from true heterogeneity across

people, places and time, and uncertainty represents the lack of knowledge of the true value of the factor

being considered (USEPA 1997b).

According to the 1995 EPA Policy for Risk Characterization (USEPA 1995a), health risk

assessments for environmental contaminants generally involve four components:

1. Hazard Identification addresses the nature of the potential adverse health

effects associated with exposure to the contaminant.

2. Exposure Assessment addresses both the number of people in the population

exposed to the contaminant and the distribution of levels of exposure within that

population.

3. Dose-Response Assessment addresses information concerning the relationships,

quantitatively where possible, between the magnitude of exposure to the

contaminant and the extent and severity of the adverse health effects that may

occur.

4. Risk Characterization combines the hazard identification, dose-response, and

exposure assessment information to describe overall risk to the exposed

population, both in terms of the distribution of risk levels in the population and

the total number of cases of adverse effects anticipated.

The exposure assessment step includes evaluation of the probability of pathogen occurrence in

wells and samples, pathogen concentrations in source water, disinfection treatment effectiveness, daily

drinking water consumption, number of days of exposure, and size of the exposed population. Pathogen

occurrence probabilities and concentration are of particular importance to the performance of the risk

assessment. Pathogen occurrence probabilities include (a) the fraction of ground water sources that have

some pathogen occurrence and (b) for sources with pathogens, the fraction of time that pathogens are
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Final Ground Water Rule

present and can be detected. Pathogen concentration is the amount of a given virus in that source when

present. These parameters are used in conjunction to make the connection between an individual’s

consumption of drinking water and the possibility of contracting an illness as a result of that consumption.

In terms of the risk assessment model, each contaminated well is assigned a probability that designates the

fraction of time, that its source water has a detectable virus contamination. (At other times the water is

assumed to be virus free.) This occurrence modeling is discussed in greater detail in the following

sections. The use of the baseline data to support the GWR risk assessment benefits analysis, and a

detailed description of the entire risk assessment methodology are presented in Chapter 5.

4.3.1 Background

Within the GWR risk assessment framework, two simplifying categorizations are made to

simplify the analysis. The first categorization is the placement of human viral pathogens into two

representative types for analysis (discussed in section 4.3.1.1). The second is the division of the universe

of wells within the US into “more” and “less” vulnerable categories to best represent the available

enterovirus concentration data (discussed in Section 4.3.3).

4.3.1.1 Representative Pathogens

Viruses

For purposes of conducting the GWR risk assessment, EPA has divided the universe of viruses

into two groups, Type A and Type B. These two types of viruses cause illnesses of different severity and

cause illness and death at different rates. A large number of viruses pathogenic to humans exist with

varying levels of occurrence, infectivity, morbidity, severity, and mortality rates. However, few data are

available on dose response relationship and occurrence in source water for most of these viral pathogens. 

EPA has based its risk estimates on two viruses for which dose response data are available. Ground

water occurrence data are also available for some viral pathogens; however, only Type B occurrence data

are available from multiple studies using standardized methods. 

The Type A group represents viruses that have high infectivity but generally have mild

symptoms. Examples of Type A viruses include but are not limited to the following: rotavirus, norovirus,

hepatitis A virus, and some other common viruses such as adenovirus and astrovirus that typically cause

outbreaks in schools and daycare centers. Such viruses generally do not result in life-threatening

illnesses. A common illness associated with Type A viruses is gastroenteritis, sometimes accompanied by

vomiting.

The Type B group represents viruses that have low to moderate infectivity but potentially more

severe health effects, which may result in death. Examples of Type B viruses include but are not limited

to the following: echovirus, coxsackievirus, and other enteroviruses. Illnesses associated with Type B

viruses range from gastroenteritis and meningitis to more severe illnesses such as myocarditis or flaccid

paralysis (due to non-polio enteroviruses).

Bacteria

Outbreak data show that bacterial pathogens occur in ground water (see Exhibit 2.3). Ideally,

EPA would estimate baseline illnesses and deaths for both bacterial and viral pathogens to support this

EA since the GWR will mitigate against risk from both concerns. While data (though limited) are
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Final Ground Water Rule

available to characterize viral occurrence, insufficient data are available to characterize pathogenic

bacterial occurrence. Therefore, the primary analysis in this EA focuses on viral changes in viral

exposure attributed to the GWR. A discussion of the unquantified benefits related to reduction in

bacterial exposure is presented in Chapter 5 (section 5.5).

4.3.2 Enterovirus and E. coli Occurrence in PWS Well Source Ground Water

EPA evaluated all available relevant ground water occurrence studies (EPA, 2006b). This section

explains the rationale for selecting the 15 studies for use in the final GWR economic analyses. The

occurrence data are used to determine the probability that a well or sample will be positive for enterovirus

and/or E. coli. E.coli was selected because EPA expects that most States will select E.coli as their

monitoring target under the final rule. To assist with the analysis, EPA consulted with a group of

statisticians to discuss ways to make optimal use of these limited data. The statisticians strongly

recommended that EPA make use of all the available data unless there were known quality assurance

problems with a data set or the well contamination scenario was outside the normal operating range of US

PWS wells. Thus, EPA used all the available data on enterovirus occurrence in ground water from PWS

wells in the United States except for one data set of alluvial wells from Missouri that were substantially

affected by severe Mississippi River flooding (Vaughn, 1996). Data from the 15 studies selected as

described in the following section were combined into one complete data set. 

Study Selection

EPA has reviewed data from 24 recent studies of pathogen and fecal indicator occurrence in

ground waters that supply PWSs (EPA, 2006b). Each study was conducted independently and with a

unique objective and scope. The available data indicate a wide range of enterovirus occurrence in water

drawn from wells across the United States. EPA selected 15 studies with results that are directly

applicable to evaluating GWR benefits. These studies include the largest data sets characterizing

enteroviral occurrence in the United States. One data set, Lieberman et al., 2002, targeted wells based on

presence of total coliforms and other indicators of vulnerability to fecal contamination. Another data set,

Abbaszadegan et al. 2003, targeted a representation of wells throughout the United States based on

hydrogeological conditions, but excluded any wells that were poorly constructed or without well logs.

Other studies sampled subsets of wells in particular states or in certain hydrogeologic settings within

states. Because most studies were designed to capture subsets of the total PWS well population, each

study description in the following is accompanied by a short discussion about the representativeness of

the subset as compared with the total population. Aside from recognizing the numbers of wells surveyed,

this analysis makes no attempt to weight any of the studies to compensate for any perceived over- or

under-representation of the subset as compared with the total population.

General Considerations for Interpreting Viral Occurrence Data (Including Uncertainty)

When evaluating enteroviral occurrence data, it is important to realize some of the fundamental

challenges in characterizing enterovirus occurrence, including detection, identification and concentration.

Key issues include recognizing the limitations of enterovirus measurement and the limitations of deriving

the probability of a well or sample being enterovirus-positive and the associated enterovirus concentration

estimates from the measured data.
9

 While each cell culture method can detect pathogens such as poliovirus, some coxsackievirus, echovirus,

and reovirus (Type 3), many coxsackie A and other viruses are not detected. For example, no cell culture method

exists to recover noroviruses in stool or environmental samples, yet noroviruses are responsible for the greatest

proportion of water and food-borne disease outbreaks and therefore are most likely to be present in fecal

contamination. Similarly, the BGM cell culture method to detect enteroviruses is inefficient for detecting rotaviruses

in well water. There are few infectious rotavirus occurrence data available for making direct rotavirus health effect

predictions. Rotaviruses are ubiquitous in nature, exemplified by the fact that all adults in the United States are

seropositive for rotavirus, indicating previous infection. These detection method deficiencies minimize infectious

virus recovery for two of the most important viruses and therefore underestimate the health effects predictions.

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Final Ground Water Rule

EPA relies only on the identification of enterovirus in PWS wells using cell culture methods since

they allow identification of infectious pathogenic viruses. However, these measurements are

underestimates of the actual occurrence because a) only a few of the viruses that can occur are detected by

the method9

, b) each viral plaque that is counted as one virus originates from an infection by one or more

viruses, and c) virus recovery is variable depending on the water chemistry and the viral strains present.

Virus recovery can range from less than 20% to greater than 50% (Dahling, 2002; Denis-Mize et al.,

2004; Sobsey and Glass, 1984).

Viruses often aggregate in water or solution. Methods that count host cell infection cannot

differentiate between virus aggregates and solitary viruses and counts them all as solitary viruses (Teunis

et al., 2005; Young and Sharp, 1977). Where more than one virus strain co-occur in placque assays,

statistical analysis has shown that the actual concentration can be as much as 45% greater than the

concentration determined by the standard method, the plaque assay count (Teunis et al., 2005). Thus, the

probability that a well or sample will be positive for viruses pathogenic to humans will be an

underestimate of the true probability and varies depending on the water chemistry, the type of cell culture

used and the type of virus.

The standard host cell line used to recover human viruses is the Buffalo Green Monkey (BGM)

continuous cell line. This cell line is less sensitive than primary cell lines derived from freshly harvested

kidney cells (Ward et al., 1984). In addition, the age of the BGM cell line affects its sensitivity. BGM

cell lines should not be used if they are passaged more than 250 times or if it has been longer than one

week since the last passage.

Furthermore, concentration estimates derived from measured values of infectious viruses will be

underestimates of the actual concentration because some viruses (such as reovirus) may be favored in the

cell line used for testing and may out-compete other viruses (such as echovirus) (Carducci et al, 2002). 

Among the enteroviruses, slower growing enteroviruses are not favored for recovery and identification. 

For example, in BGM cells coxsackie B virus is a fast growing virus whereas Echo 11 grows slowly

(Lieberman et al., 2002). Thus, the probability that a sample will be positive for viruses pathogenic to

humans, given that such viruses are present in the sample, depends on water chemistry, the type of cell

culture used, and the type of virus.

Viral occurrence can be characterized by considering the probability that a well or sample is

virus-positive and the viral concentrations associated with those positive samples. However, the number

of samples taken at a site and the sensitivity of measurement can significantly influence the estimated

probabilities and concentrations per site for the anticipated exposure duration. Available data indicate that

viral concentration at one site taken at different points in time can be highly variable, ranging from below

detect to several orders of magnitude above detect (Lieberman et al., 2002). This is because some wells
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Final Ground Water Rule

may never have a viral occurrence, others may have a short duration contamination, and still others may

have high levels of occurrence and concentration for sustained durations. The possibility of high variation

in viral occurrence at any given site makes estimates of probabilities and concentrations difficult.

 In addition to the general issues regarding viral data characterization discussed above, specific

issues of data representativeness, bias, uncertainty, and variability exist for any individual study. The

interpretations of the data from the 15 primary studies used to support GWR analyses are presented in

detail below.

4.3.2.1 Lieberman et al. 2002 Study

Study Objectives

The major objectives of the Lieberman et al. 2002 study were: 1) to obtain occurrence data for

infectious human enteric viruses using the BGM cell line, 2) to assess the microbial indicators of fecal

contamination, and 3) to develop and to evaluate a molecular biology monitoring method (PCR) to

identify viral genomic material without consideration of the infectiousness of that material. The

objectives were accomplished by sampling wells to confirm total coliform presence and to establish the

presence of other fecal indicators, including somatic coliphage (Phase I) and by choosing a subset of these

for monthly sampling for 1 year (Phase II). Wells were nominated for sampling in Phase I by federal,

State and local drinking-water experts.

Well Selection

In Phase I, 180 wells were nominated, and 98 were selected. Each selected well was sampled

once for total coliform, E. coli, enterococci, Clostridium perfringens spores, and somatic coliphage. 

Nominated wells were identified using historical total coliform occurrence data and any other available

information about the well. In choosing which wells to nominate, other information was considered such

as confirmed waterborne disease outbreaks, proximity to known sources of human fecal contamination

and, in some cases, siting in a sensitive hydrogeologic setting (e.g., karst). Selected wells were located in

22 States, Puerto Rico, and the U.S.Virgin Islands. The wells from Phase I served as the well selection

pool for 21 of the 30 wells chosen for Phase II sampling.

Twenty-seven of the thirty wells selected in Phase II had either a history of total or fecal coliform

occurrence or had any indicator occurrence during Phase I sampling. In aggregate, the 30 wells selected

for monthly sampling represent a group of wells considered to be vulnerable to fecal contamination

primarily due to historical indicator occurrence, but also due to positive results for somatic coliphage,

enterococci, or other indicators from a single sample during Phase I sampling. Proximity to fecal

contamination sources, high nitrate concentrations, and location in a sensitive hydrogeologic setting were

additional selection criteria for several additional wells. The 30 selected wells, located in 17 States and 2

U.S. territories, were sampled monthly for 1 year for total coliform, E. coli, enterococci, Legionella

species, Clostridium perfringens spores, somatic and male-specific coliphage, Bacteroides bacteriophage

and enteric viruses using BGM cell line.
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Sample Results

For viral analyses using cell culture assays, seven of the 30 wells (23 percent) were positive for

enterovirus and 20 samples (6 percent) were positive for enterovirus or reovirus. While 7 of the 30 wells

sampled had a cell culture positive among the twelve samples taken, most of the measurement were below

detects. One of the wells had 5 monthly viral positives, two of the wells had 4 monthly positives, one of

the wells had two monthly positives, and three wells had one positive. Viral strains identified by

serotyping included coxsackievirus and echovirus, as well as the enteric virus reovirus. Virus-positive

samples ranged in concentration from 0.9-212 PFU or MPN/100 liters with a mean infectious virus

concentration of 30.66 PFU or MPN/100 liters (PFU, or plaque forming units, and MPN, or most

probable number, are estimates of concentration) among all the positive samples.

Data Representativeness

Most of the wells selected as part of Phase II of the Lieberman et al. 2002 study had a history of

total coliform occurrence that was confirmed by Phase I sampling. Because most (but not all) of the wells

selected for inclusion in the study had a history of fecal contamination, these data are not representative

of all PWS wells in the United States because not all wells in the United States have a history of fecal

contamination.

The GWR is concerned primarily with ground water sources vulnerable to contamination,

especially the undisinfected sources. Most of the Lieberman et al. 2002 study wells, however, already

employ disinfection, which potentially introduces a bias to the data (i.e., the use of disinfection could be

considered an indication that the source is known to be contaminated). However, the use of disinfection

does not necessarily correlate with known contamination. One enterovirus-contaminated well in the

Lieberman et al. 2002 study was undisinfected and had the highest virus concentration for any single

monthly sample of the entire study. Another factor that mitigates against this potential bias is that many

States and some water systems require ground water disinfection as a matter of policy. For the Lieberman

et al 2002 study, 10 of the 30 wells are located in Alabama, Florida, or Texas; States that require

disinfection of all ground water sources. The existence of disinfection at a ground water system may not

be directly correlated with indicator occurrence at that facility and therefore any selection bias is

unknown.
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4.3.2.2 Abbaszadegan et al. 2003

Study Objectives

Among the objectives of the Abbaszadegan et al. 2003 study were: 1) to determine the

occurrence of virus contamination in source water of public ground water systems, 2) to investigate water

quality parameters and occurrence of microbial indicators in ground water and possible correlation with

human viruses, 3) to develop a statistically based screening method to identify wells at risk of fecal

contamination, and 4) to develop and evaluate a molecular biology monitoring method (PCR).

Well Selection

Wells were selected for the Abbaszadegan et al. 2003 study from a pool of 750 wells. The study

was initiated as a study of 150 samples from AWWSCo wells selected to test and evaluate the PCR

method (Abbaszadegan et al., 1999). With additional funding, the study was expanded to 539 samples

from 448 wells. The additional wells were nominated by State drinking water program or water utility

staff. Study personnel requested nominations of wells not known to be vulnerable to microbial

contamination. The researchers excluded 12 samples included in the first 150 AWWSCo well samples

because they were believed to be under the direct influence of surface water and therefore especially

vulnerable to contamination. Other nominated wells were excluded if well records were not available or if

the well was improperly constructed. All nominated wells were profiled by the well operators or their

designee using a questionaire that included a checklist of 11 different hydrogeologic settings. Researchers

selected wells for inclusion in the study based on the reported hydrogeologic setting information. Wells

were selected for inclusion if they were apparently located in a setting that was proportionately

under-represented as compared with a USGS national hydrogeologic profile derived using these same 11

hydrogeologic settings.

Sample Results

Source water samples were taken from each well and analyzed using a variety of methods to

detect pathogens and indicators. Samples were analyzed to determine the occurrence of viruses (using

both cell culture and polymerase chain reaction (PCR) methods) and total coliform (TC), enterococci, and

C. perfringens bacteria in ground waters of the United States. A total of 539 samples were obtained. Not

all analyses were conducted on all samples, and 25 wells were sampled two or more times. Information

was not available to identify which wells were sampled multiple times. Because the majority were

sampled once, and having no other recourse, EPA’s data were reduced to single samples as though each

of these was the only one assayed for a well. PWSs performed the sampling and were given training on

procedures to collect at least 400 gallons (1,512 L) of water prior to disinfection. Exhibit 4.12 presents a

summary of the Abbaszadegan et al. 2003 study results. 
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Final Ground Water Rule

Exhibit 4.12 Results of the Abbaszadegan et al. 2003 Study

Assay

Percent of Sites with

Positive Samples

(No. positive/samples analyzed)

Enterovirus (cell culture) 4.8%

Total coliform 9.9%

Enterococci 8.7%

Clostridium perfringens spores 1.8%

Male specific coliphage (Salmonella WG-49 host) 9.5%

Somatic Coliphage (E. coli C host) 4.1%

Somatic and Male Specific Coliphage (E. coli C-3000 host) 10.8%

 Source: Abbaszadegan, 2002; Abbaszadegan et al., 1999, 2003

Data Representativeness

The Abbaszadegan et al. 2003 study included a large number of wells that were specifically

chosen to be representative of the range and proportion of the hydrogeological settings of the United

States. To further evaluate the representativeness of the wells with respect to hydrogeologic conditions,

EPA subsequently compared nitrate concentrations from a national database of nitrate concentrations in

ground water (Lanfear, 1992) with nitrate data measured in the Abbaszadegan et al. 2003 study wells to

determine if there was any statistically significant difference between the nitrate levels in the two data

sets. Nitrate was chosen for this comparison because a large, national database is available. The national

nitrate data were selected randomly from a database of more than 100,000 wells. Using U.S. Census data,

EPA stratified the nitrate data into rural and urban components and chose a small random subset of these,

comparable in size to the sample in the Abbaszadegan et al. 2003 study data (all available Abbaszadegan

et al. 2003 study data were used), for comparison. The analysis showed that the Abbaszadegan et al.

2003 study wells had nitrate concentrations that were not significantly different from the national data or

from the urban and rural components. Thus, using nitrate concentration as a surrogate, EPA further

verified that, by this measure, the Abbaszadegan et al. 2003 study wells data appear to be nationally

representative of hydrogeological conditions in the United States.

In the well selection process, the Abbaszadegan et al. 2003 study initially relied on wells that

were owned by AWWSCo and subsequently used wells that were volunteered for the study. Choosing

from among a restricted pool or using a volunteer process introduces a potential bias to the study. The

AWWSCo wells typically serve larger populations, have greater revenues and are more professionally

managed than most wells, and the volunteered wells were selected precisely because they appeared to be

at low risk. Thus, there may be a downward bias in the contamination levels found during the study. As

applied to the GWR risk analysis, this would result in an underestimate of benefits derived from the rule. 

In addition, most wells were only sampled once, which also may underestimate the risks associated with

these wells.
10 In using the cell culture method for enterovirus detection, the Abbaszadegan et al. 2003 study identified

only poliovirus from wells (Abbaszadegan et al., 1999) as compared with the Lieberman et al. 2002 study which

identified no poliovirus.

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Final Ground Water Rule

A potential bias of the Abbaszadegan et al. 2003 study, as with the Lieberman et al. 2002 study,

is that the majority of the study wells already employ disinfection (see discussion above for implications

of this bias). A mitigating factor is that many States and some water system companies require ground

water disinfection as a matter of policy. Fifty-two wells from the Abbaszadegan et al. 2003 study are

located in Alabama, Florida, or Texas; States that require disinfection of all ground water sources. In

addition, a large number of wells in the study are operated by AWWSCo, which also disinfects as a

matter of policy. Therefore, the existence of disinfection at a ground water system may not be directly

correlated to issues of contamination at that facility.

Because the description of the hydrogeologic setting was selected by the well operator or

designee from a checklist, there are potential uncertainties associated with the hydrogeologic setting data.

It is possible that the operator had insufficient data to determine the hydrogeologic setting and was unable

to easily consult with a hydrogeologist. No analysis was conducted to determine whether the reported

hydrogeologic setting data were correct. It would be expected that viruses would more likely be found in

sensitive hydrogeologic settings, as was the case with the Lieberman et al. 2002 data, because the ground

water flow within those aquifers is faster and more direct, and there are fewer opportunities for virus

concentrations to become attenuated due to interaction with the aquifer solid materials. 

The Lieberman et al. 2002 study found higher virus concentrations and a greater range of

concentrations than those measured in the Abbaszadegan et al. 2003 study10. The Abbaszadegan et al.

2003 concentrations were uniformly low. Because of variations in well water matrix, source density,

proximity and the concentrations in each source, virus filtration and recovery and virus analyses, it is

impossible to assess the significance of the differing virus concentrations.

Overall, the magnitude and direction of the biases and uncertainties inherent to the Abbaszadegan

et al. 2003 study cannot be definitively quantified.

4.3.2.3 Pennsylvania Noncommunity Wells (Lindsey et al., 2002)

Study Objectives

The purpose of this study was to measure pathogen and indicator occurrence in a random

stratified sample of non-community water systems (NCWS) wells in primarily carbonate aquifers and

crystalline aquifers, which are hydrogeologically sensitive settings. The United States Geological Survey

(USGS) (Lindsey et al., 2002) analyzed samples from 60 NCWS wells from September to January 2001

to assess the occurrence and distribution of pathogens in ground water used for non-community water

supplies and indicator organisms (evaluated as surrogates for those pathogens). 
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Well Selection

USGS personnel, in collaboration with the Pennsylvania Department of Environmental Protection

(PaDEP), selected random wells from a targeted population of primarily carbonate and crystalline

aquifers. Ten wells were chosen in areas underlain by either siliciclastic bedrock or unconsolidated

surficial aquifers. An unconsolidated aquifer is non-sensitive but the siliclastic aquifer can be either

sensitive or non-sensitive depending on whether it is considered to be a sandstone or a quartzite. Aquifer

sensitivity is best determined by the State, and EPA cannot make that determination based on the

available data. 

The vast majority of the sites were TNC PWS wells. Only two wells were NTNC PWS wells.

Surrounding land use was included as a criterion for selection; a site was more likely to be selected if

potential fecal point sources were located nearby. However, water suppliers with known bacterial

contamination problems declined to participate while suppliers with no contamination history were much

more willing to participate.

Sample Results

Of 60 wells initially selected, 59 samples were analyzed for culturable viruses, Helicobacter

pylori (H. pylori), total coliform, Escherichia coli (E. coli), Clostridium perfringens (C. perfringens),

somatic coliphage, male-specific coliphage, and enterococcus. 

Culturable viruses were detected in 5 wells, H. pylori in 4 wells, E. coli in 7 wells, total coliform

in 27 wells, C. perfringens in 9 wells, somatic coliphage in 5 wells, male-specific coliphage in 2 wells,

and enterococci in 8 wells.

Of the 5 wells with detectable culturable viruses, two were near 0.21 PFU per 100 L, while the

remaining three ranged from 18 to 56 PFU per 100 L.

Data Representativeness

This data set represents the only randomly sampled human pathogenic virus data from TNC wells

among the 24 studies considered. As such, it is an important data set for representing the large number of

untreated TNC wells in the United States.

4.3.2.4 Southeast Michigan (Francy et al., 2004)

Study Objectives

The purpose of this study of small (serving fewer than 3,000 people) public ground water supply

wells was to assess the presence of both viral contamination and microbiological indicators of fecal

contamination, relate the co-existence of indicators and enteric viruses, and consider the factors that affect

the presence of enteric viruses.
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Final Ground Water Rule

Well Selection

Initially, 160 wells from a previously studied USGS National Water-Quality Assessment Program

site were proposed based on nominations from local State and county experts. Wells were nominated if

they produced from shallow sand and gravel aquifers, were undisinfected and did not have well

construction flaws. The 38 selected wells were randomly selected from the 160 nominated wells. Well

screens are typically shallow ranging from 50 to 150 feet below ground surface. In some places the

aquifer is unconfined but more often the aquifer is semiconfined or confined by glacial till. Where

semiconfined or confined aquifer conditions exist, these wells are protected from surficial fecal

contamination sources. From July 1999 through July 2001, researchers collected a total of 169 regular

samples and 32 replicate pairs in southeastern Michigan from 38 wells in discontinuous sand and gravel

aquifers. Not all 38 wells were sampled for all parameters. Only 34 wells (93 samples) were analyzed for

enteric virus by cell culture.

Sample Results

Two wells (two samples) were positive for enteric virus by cell culture. Four wells (four samples

were positive for E. coli. Six wells (7 samples) were positive for enterococci. Two wells (two samples)

were positive for male-specific coliphage and one well (one sample) was positive for somatic coliphage,

based on 1 liter samples. All wells sampled are undisinfected so the semi-confining or confining layers

are not sufficient protection against fecal contamination.

Data Representativeness

This study is unique among the 24 studies considered in that it sampled only undisinfected wells.

Other studies were typically not able to sample undisinfected wells because well operators did not allow

sampling. Thus, this study is representative of the large number of small, undisinfected PWS wells in the

United States. Despite the apparent random well selection process, seven wells were not further

considered for sampling at the request of the well owner or because they were found be unsuitable.

4.3.2.5 New Jersey (Atherholt et al., 2003)

Study Objectives

This study was designed to sample wells in New Jersey for fecal indicator organisms. No samples

were analysed for enteroviruses or other viruses pathogenic to humans. Thus, data from this study was

used only to determine the probability that a sample was fecally contaminated by E. coli.

Well Selection

Twenty-six public water supply wells were sampled for a variety of fecal indicator organisms.

Twelve wells were identified as GWUDI and so data from these wells are not used in this analysis.

Eighty-one samples were collected from the 13 ground water wells (128 from all wells) between June

1999 and February 2002. One well with one sample was not reported as ground water or GWUDI so this

value was not included. All of the wells were located in unconfined aquifers. Although GWUDI wells

were selected to increase the likelihood that fecal indicator organisms were present, no information is

given for the selection of the other wells.
Economic Analysis for the 4-34 October 2006

Final Ground Water Rule

Sample Results

All 13 wells (81 samples) were negative for E. coli.

Data Representativeness

These data represent a subset of community ground water wells in New Jersey that produces

water from unconfined aquifers.

4.3.2.6 Missouri Ozark Plateau #1 (Davis and Witt, 2000)

Study Objectives

The purpose of this study was to determine the water quality in recently constructed community

public water system wells in the Ozark Plateau region of Missouri. This largely rural region is

characterized by carbonate aquifers, both confined and unconfined, with numerous karst features

throughout. A confining layer is defined in this study as a layer of material that is not very permeable to

ground water flow and that overlays an aquifer and acts to prevent water movement into the aquifer.

Well Selection

The US Geological Survey, working with the Missouri Department of Natural Resources,

selected a total of 109 wells, in both unconfined and confined aquifers (Davis and Witt, 2000). In order to

eliminate poorly constructed wells from the study, wells that had been constructed within the last 15 years

were selected primarily. Wells were also selected to obtain good coverage of the aquifer and to reflect the

variability in land use. All wells were sampled twice, once in summer and once in winter. 

Sample Results

One sample was reported as enteric-virus positive but this virus-positive well was not used in the

data analysis for Today's Rule because this sample (and others) had some quality assurance problems due

to cross contamination of samples with the poliovirus control. All wells from this study are counted as

negative for enteroviruses when evaluated for the probability of well (and sample) being positive for

enterovirus.

Data Representativeness

These data are representative of wells in the Ozark Plateau aquifer of Missouri. These data

potentially underestimate the probability of wells and samples being positive for enteroviruses because

one positive well was not included in the data set for Today's Rule.
Economic Analysis for the 4-35 October 2006

Final Ground Water Rule

4.3.2.7 Missouri Ozark Plateau #2 (Femmer, 2000)

Study Objectives

The purpose of this study is to determine the water quality in older (pre-1970) CWS wells in the

Ozark Plateau region of Missouri to supplement the Missouri Ozark Aquifer Study #1, by Davis and Witt

(1998, 1999). This largely rural region is characterized by carbonate aquifers, both confined and

unconfined, with numerous karst features throughout.

Well Selection

The US Geological Survey, working with the Missouri Department of Natural Resources,

sampled a total of 106 wells (Femmer, 1999), in both unconfined and confined aquifers. Wells (all of

which were constructed before 1970) were selected for monitoring to obtain good coverage of the aquifer,

and to reflect the variability in land use. Priority was given to wells that had completion records, well

operation and maintenance history, and wells currently being used. Each well was sampled once (during

the spring). 

Sample Results

No wells were enterovirus-positive by cell culture.

Data Representativeness

These data are representative of PWS wells in the Ozark Plateau aquifer of Missouri.

4.3.2.8 Wisconsin Migrant Worker Camp (USEPA, 1998b)

Study Objectives

The purpose of this study was to determine the quality of drinking water in the 21 public ground

water systems serving migrant worker camps in Wisconsin (USEPA, 1998b). Each well was sampled

monthly for six months, from May through November, 1997. The study conducted sampling for

male-specific coliphage, total coliforms and E. coli. When detection of coliforms occurred, the specific

type of coliform was further identified (speciated). One total coliform positive sample was identified to

contain Klebsiella pneumoniae, which can be due to fecal or non-fecal origins. Along with the microbial

indicators, nitrate and pesticides were also measured.

Other factors were compared to the microbial and chemical sampling results of the study. Well

construction records were available for 14 of the wells. The mean casing depth was 109 feet (range 40 to 

282 feet) and the mean total well depth was 155 feet (range 44 to 414 feet). Most of these 14 wells are

also reported to terminate in a sand or sandstone formation.

Well Selection

These transient, non-community water systems are located in three geographic locations across

the State.
Economic Analysis for the 4-36 October 2006

Final Ground Water Rule

Sample Results

Investigators detected male-specific coliphage in 20 of 21 wells during the six-month sampling

period, but never detected E. coli. In addition, four wells had nitrate levels that exceeded the EPA MCL

for nitrate. No wells were analyzed for enteric virus by cell culture.

Data Representativeness

The data from this study are intended to be representative only of TNC wells in migrant labor

camps.

4.3.2.9 New England (Doherty et al., 1998)

Study Objectives

The purpose of this study was: (1) to determine the prevalence of enteric pathogens in New

England's public water supply wells, (2) to assess the vulnerability of different systems, and (3) to

evaluate various fecal indicators.

Well Selection

Wells were selected based on the following criteria: (1) must have constant withdrawal

throughout the year, (2) must be near septic systems, (3) should have, if possible, a history of violations

of the MCL for total coliforms or elevated nitrate levels, and (4) must not have direct infiltration by

surface water (Doherty, 1998).

Wells were nominated, characterized, selected, and sampled by regulatory staff of Connecticut,

Maine, Massachusetts, New Hampshire, Rhode Island, and Vermont. The selection process considered

wells in different hydrogeologic settings. Of the 124 total wells, 69 (56%) were located in unconfined

aquifers, 31 (25%) were located in bedrock aquifers, 10 (8%) were located in confined aquifer

hydrogeologic settings, and 14 (11%) were located in unknown aquifer settings. Each well was sampled

quarterly for one year. Enterococci were identified in 20 of 124 wells (16%) and in 6 of 31 (19%) bedrock

aquifer wells. 

Sample Results

No wells were positive for enteric virus by cell culture. No wells were positive for E. coli.

Data Representativeness

These wells are intended to be representative of New England PWS wells. Two wells were

provisionally identified as cell culture positive (and reported as positive in EPA, 2000) but were found to

be laboratory contamination when the samples and lab controls were sequenced by CDC. 
Economic Analysis for the 4-37 October 2006

Final Ground Water Rule

4.3.2.10 Three-State Study: (Wisconsin-Battigelli, 1999)

Study Objectives

The Wisconsin study sampled 25 wells quarterly for 2 years 

Well Selection

No explanation is available on the method used in selecting the wells. 

Sample Results

One well in Wisconsin was positive for enteric viruses by cell culture.

Data Representativeness

No information is available to evaluate the representativeness of these data.

4.3.2.11 Three-State Study: (Maryland-Banks et al, 2001)

Study Objectives

The purpose of this study was to sample shallow wells in Worcester and Wicomico Counties on

Maryland's Eastern shore for enteric viruses. Twenty-seven wells were each sampled once. Three other

samples (two from two deep confined wells) were sampled for use as negative control samples. Each well

was sampled for enteric viruses by Buffalo Green Monkey (BGM) and RD (human embryonal

rhabdomyosarcoma) cell culture, Bacteroides fragilis bacteriophage, somatic and male-specific coliphage,

E. coli, Clostridium perfringens, and TC. Serological testing on virus-positive RD cell cultures confirmed

the presence of rotavirus.

Well Selection

The 27 wells were located in two counties that are underlain entirely by sandy coastal plain

aquifers. The selected wells were chosen from 278 small PWS wells by a vulnerability score that

included factors such as historical fecal coliform occurrence, land use, well depth and age, and other

factors.

Sample Results

One well was positive for enteric viruses by cell culture. This sample was identified as rotavirus

by a non-standard test using an assay method normally used to detect rotavirus in stool. Because the assay

method works primarily for rotavirus at high concentrations, this well was considered to be enteric-virus

positive but not necessarily rotavrirus-positive. None of the wells was positive for E. coli. 

Data Representativeness

These data are representative of deep wells in non-sensitive aquifers that are unlikely to be fecally

contaminated.
Economic Analysis for the 4-38 October 2006

Final Ground Water Rule

4.3.2.12 Three-State Study: (Maryland-Banks and Battigelli, 2002)

Study Objectives

The purpose of this study was to sample shallow wells in the Maryland Piedmont physiographic

province. Each well was sampled for enteric viruses by BGM cell culture, Bacteroides fragilis

bacteriophage, somatic and male-specific coliphage, E. coli, Clostridium perfringens and TC. Onehundred-one samples were collected from April 10, 2000 to November 13, 2000. This total included ten

replicate samples for QA purposes.

Well Selection

For this study, 91 small PWS wells were selected for sampling from 263 wells in the fractured

bedrock aquifer of two Maryland Piedmont Physiographic Province counties. Wells were selected to

distribute the sample sites evenly over the population and spatial extent of the study area. One well was

selected randomly.

Sample Results

None of the wells was positive for enteroviruses by cell culture. One well was positive for E. coli.

Data Representativeness

These data are representative of shallow wells in fractured bedrock (sensitive) aquifers with thick

soil and weathered rock (saprolite) cover that acts to protect against fecal contamination. This same

aquifer setting would be more likely to be contaminated if located further north where glacial advances

during the Ice Age removed much of the weathered soil and rock.

4.3.2.13 Three-State Study: (Minnesota-Banks and Battigelli, 2002)

Study Objectives

The purpose of the three-state study is to characterize the extent of viral contamination in PWS

wells by testing wells in differing hydrogeologic regions and considering contamination over time

(Battigelli, 1999). The Minnesota study (Minnesota Department of Health 2000) sampled 76 wells. 

Seventy-four wells were sampled for at least four consecutive calendar quarters. The remaining two wells

were sampled for two consecutive quarters each. In addition to microbial indicator data, one sample from

each well was also analyzed for tritium and tritium/3helium. 

Well Selection

Sampled wells were more likely to be selected if they were small, transient PWSs, and/or were

located in a aquifer that was perceived to be vulnerable. Of the 76 Minnesota wells sampled, six (8

percent) served community systems, 19 (25 percent) served non-community non-transient systems and 51

(67 percent) served transient systems. The aquifer types that are utilized by these wells include dolomite

(six wells), dolomite and sandstone (three wells), fractured crystalline bedrock (nine wells), sandstone (28

wells), sand and gravel (29 wells) and regolith (surficial materials) (one well).
Economic Analysis for the 4-39 October 2006

Final Ground Water Rule

Sample Results

No wells in Minnesota were enteric virus-positive by cell culture.

Data Representativeness

These wells were selected to be representative of wells in Minnesota.

4.3.2.14 EPA Vulnerability Study (USEPA, 1998c)

Study Objectives

The purpose of this study was to conduct a pilot test of a new vulnerability assessment method by

determining whether it could predict microbial monitoring results (USEPA 1998c). The vulnerability

assessment assigned low or high vulnerability to wells according to their hydrogeologic settings, well

construction and age, and distances from contaminant sources. 

Samples were taken and tested for enteroviruses (both by cell culture and PCR), hepatitis A virus

(HAV) (by PCR), rotavirus (by PCR), Norwalk virus (by PCR), and several indicators (total coliforms,

enterococci, male-specific coliphage, and somatic coliphage). The only positive result was one PCR

sample positive for HAV.

Well Selection

A total of 30 wells in eight States were selected to represent ten hydrogeologic settings. Selection

was based on the following criteria: (1) wells representing a variety of conditions relevant to the

vulnerability predictions, (2) wells with nearby sources of potential fecal contamination, and (3) wells

with sufficient well and hydrogeologic information available.

Sample Results

No wells were positive for enteric virus by cell culture. No E.coli data were collected.

Data Representativeness

Wells were selected to be representative of a variety of hydrogeologic settings in the United

States. However, the small number of wells in the study and the large number of hydrogeologic settings

makes such a comparison difficult.

4.3.2.15 Montana Study

Study Objectives

Miller and Meek (2006) sampled source water for E. coli, enterococci, male-specific and somatic

coliphage from wells representing primary aquifer types, bedrock and valley-fill aquifers.
Economic Analysis for the 4-40 October 2006

Final Ground Water Rule

Well Selection

18 small PWS wells (and 20 residential wells) near Helena, Montana were sampled.

Sample Results

No E. coli, male-specific or somatic coliphage were detected in any well. Enterococci were

detected in two wells but it is not known if these wells were PWS or residential wells

Data Representativeness

Wells were selected for sampling to represent both primary aquifer types, bedrock and valley-fill

aquifers. Each well was sampled from one to three times.

4.3.2.16 Summary of New Data

Exhibit 4.13a identifies the new data available since the proposed GWR was published in 2000.

Although all new data were evaluated, not all new data were used in the economic analysis for the GWR.

Of the seven new studies described in Exhibit 4.13a, four studies were included in the occurrence

data compilation described in Section 4.3.2 and used to determine exposure in this EA. These four new

studies are the Pennsylvania study (Lindsey et al, 2002), the Michigan study (Francy et al, 2004), the

New Jersey study (Atheroholt et al, 2003), and the Montana study (Miller and Meek 2006). Other studies

not included were not used for the reasons described in the following.

Karim et al (2003, 2004) - This study selected 20 wells (15 because of enterovirus or indicator

occurrence) from the Abbaszadegan et al. 2003 study for additional (monthly) sampling. However, with

the available data provided by the researchers (raw spreadsheet data and summary reports), it is

impossible to combine the two data sets because the well site identifying characters differ in the two

studies. Thus, there is no alternative other than treating the two studies as if they are separate,

independent data sets. If treated as two data sets, significant bias is introduced. First, the same well is

counted twice. Second, well data are treated as if they are unbiased, independent data when they actually

were selected with based on prior sampling which identified either infectious enterovirus, enteric virus

RNA, one or more fecal indicator bacteria or no contamination. (five wells from each group).

USEPA (2006b) - This study was designed to field test new coliphage assay methods. Because

the objective was to better identify and count fecal indicators, where present, PWS wells with fecal

contamination were more likely to be selected. Most of the wells sampled in this study were not PWS

wells but rather were domestic water wells (not regulated by the GWR). The raw data were not proved by

the investigators so counting and analysis of the PWS wells is subject to error. Because the wells were

mostly not PWS wells and likely represented a biased set of PWS wells, these data are not included in the

exposure compilation in this EA.
Economic Analysis for the 4-41 October 2006

Final Ground Water Rule

Borchardt et al (2004) - This study was designed to use detailed hydrogeologic data and

microbial assays to evaluate wells in one community that are not designated by the State as GWUDI

wells. Four wells were intensively sampled (two additional wells were sampled in one month as

substitutes). The study concluded that two of the four wells had substantial surface water contribution.

Because this study is small, all from the same community and half the wells are likely GWUDI, these data

are not included in the exposure compilation in this EA.

DeBorde et al (1995) - This study sampled two wells from the same community. Because this

study was small and both wells are located in the same community, these data are not included in the

exposure compilation in this EA.

Exhibit 4.13b presents a summary of the virus-positive results obtained from the 1,253 virus

assays performed in the studies described in this section. Exhibit 4.13c presents a similar summary of the

E.coli (indicator) positive results obtained from the 687 assays performed in these studies. Exhibit 4.13d

presents the number virus and E.coli assays used to evaluate wells in each of the 15 studies. These data

were used by EPA for the hit rate analysis discussed later in this chapter.
Economic Analysis for the 4-42 

Final Ground Water Rule

Exhibit 4.13a New Data Available since publication of the Proposed GWR

Study # PWS Wells

Sampled &

Location

Sampling frequency/volume Indicators Monitored (#

Pos. Wells/# Wells Total,

Unless Otherwise Indicated

L

Pennsylvania NoncommunityWells (Lindsey et al., 2002)

60 wells 59 samples.

Virus sample volume (200-1000L)Bacterial sample volume (100mL)No detection limitMeasured values are 0.21, 0.21,18.3, 33.4, and 52.0 MPN/100L.

Male-specific coliphage (3/59)Somatic coliphage (5/59)Total coliform (27/59)E.coli (7/59)Enterococci (8/59)C.perfringens (9/59)H.pylori (by PCR) (4/59)

C

Microbial Indicators for Assessingthe Vulnerability of ground waterto fecal contamination (Karim etal., 2003, 2004)

20 wells (California-2,Illinois-2, Indiana-3,Massachusetts-2,Missouri-2, NewHampshire-2, NewJersey-2, NewMexico-1, Ohio-1,Pennsylvania-3)

Each well was sampled monthly fora year.All indicators sampled using 100 mLand 1L samples (except coliphageMethod 1602, which used only100mL samples)Coliphage analyzed using Method1601 and 1602

Method 1601: Male-specificcoliphage (1/20 for 100mLsample, 4/20 for 1L sample)Somatic coliphage (0/20)Method 1602: Male-specificcoliphage (12/20)Somatic coliphage (2/20)Total coliform (13/20 for 100 mLsample, 16/20 for 1L sample)E.coli (5/20 for 100 mL sample,7/20 for 1L sample)Enterococci (1/20 for 100 mLsample, 7/20 for 1L sample)C.perfringens (1/20 for 100 mLsample, 3/20 for 1 L sample).

Ce((n(
Economic Analysis for the 4-43 

Final Ground Water Rule

Environmental Factors andChemical and MicrobiologicalWater-Quality ConstituentsRelated to the Presence ofEnteric Viruses in Ground Water(SE Michigan) (Francy et al.2004)

38 wells 169 regular samples.

32 replicate pairs.Mostly 5 samples per site.Method 1601 & 1602.

Total coliforms (13/38) (34.2%)(15/152 samples) E.coli (4/38) (10.5%) (4/163samples)enterococci (6/38) (15.8%)(7/158 samples)Male-specific coliphage (2/34)(5.9%) (2/117 samples) (1 L.Sample)Somatic coliphage (1/34) (2.9%)(1/118 samples) (1 L. sample)

C(RHRRN

Validation of methods to detectcoliphages in ground water(USEPA, 2006b)Phase IINot PublishedNote: This study included privateand public wells.

SE region (13 in NCand 4 in FL) - 27wellsSW region (TX, NM) -11 wellsUpper Midwest (MN) -25 wellsNE region (12 in NH,4 in ME, 3 in VT, 6 inMA) - 25 wells

Two phases. Somatic Coliphage SAL (19/116)

(16.4%)F+ Coliphage SAL (13/116)(11.2%)Total Coliphage SAL(14/116)(12%)Somatic Coliphage enrichment(8/116) (6.9%)F+ Coliphage enrichment (4/116)(3.4%)Total Coliphage enrichment(6/116) (5.2%)Fecal coliform (11/80) (13.8%)E.coli (5/116) (4.3%)Enterococci (14/116) (12.1%)

Vulnerability of Drinking WaterWells in La Crosse, Wisconsin toEnteric-Virus Contamination fromSurface Water Contributions(Borchardt et al., 2004)

6 PWS wells (notGWUDI)

Sampled monthly for one year. Twowells were shut down during onesampling period; samples fromnearby wells were used for thatperiod.2 wells have 12 samples; 2 wellshave 11 samples; and 2 wells have1 sample.

TC (0/6)E.coli (0/6)Enterococci (0/6)Somatic coliphage (0/6)Male-specific coliphage (0/6)

RERHNNCEH
Economic Analysis for the 4-44 

Final Ground Water Rule

Mountain Water Company inMissoula, MT (DeBorde et al.,1995)

2 wells Sampled monthly for one year. F+Coliphage (1/2)(8%)

Somatic coliphage (0/2)(0%)

E

New Jersey (Atherholt et al.,2003)Note: This study included wellsthat were ground water under thedirect influence of surface water)

26 wells 128 samples. Wells were sampled

from 1 to 10 times each. Bacteriasample volumes were 100 mL. Coliphage sample volumes were100 mL, but a few samples werelarger.

TC (8/26)E.coli (3/26)Enterococci (2/26)Somatic coliphage (CN 13 host)(5/26)Male-specific coliphage (Famphost) (5/26)

Montana Study (Miller and Meek,2006)

18 wells (nearHelena, Montana)

Wells sampled 1-3 times E.coli (0/18)

Enterococci (2/38) [uncertain ifthe positive wells were PWSwells]Male specific coliphage (0/18)Somatic coliphage (0/18)
Economic Analysis for the 4-45 October 2006

Final Ground Water Rule

 Number of Virus Positives 

Virus 

Assays 

0 1 2 3 4 Total

1 837 28 865

2 122 1 123

3 39 1 40

4 170 2 172

5 1 1 2

6 2 2

8 25 1 26

12 18 3 1 22

14 1 1

Total 1215 35 1 1 1 1253

 Number of E. Coli Positives 

E. Coli

Assays 

0 1 3 5 6 Total

1 282 16 298

2 128 1 129

3 30 30

4 120 1 121

5 28 2 30

6 26 1 27

8 24 2 26

12 12 3 2 2 3 22

11 3 3

14 1 1

Total 653 25 4 2 3 687

Exhibit 4.13b Virus Assays and Positives for 1,253 Wells Assayed for Viruses

Exhibit 4.13c E.coli Assays and Positives for 687 Wells Assayed for E.coli
11 EPA believes this terminology is more appropriate than that used in the proposal (“improperly

constructed” and “properly constructed”) since the Lieberman et al (2002) study did not target poorly constructed

wells, but rather used criteria believed to favor the selection of vulnerable wells.

Economic Analysis for the 4-46 October 2006

Final Ground Water Rule

Study ID Virus E.coli

Abbas 539 0

Lieb 298 298

MD - 3 State, 2002 91 90

MD - 3 State, 2001 30 30

SE Michigan 95 167

MN - 3 State 299 92

MO - 1 218 218

MO - 2 109 109

New England 458 462

PA Noncommunity 60 60

WI Migrant Worker Camp 0 126

WI - 3 State 200 200

EPA Vuln 30 0

NJ Atherholt 0 71

Montana 0 38

Total 2427 1961

Number of Assays

Exhibit 4.13d Number of Virus and E.coli Assays

4.3.3 Well Vulnerability

4.3.3.1 Background

In the EA for the proposed rule EPA estimated that 17 percent of the wells in the United States

were improperly constructed and that 83 percent of the wells were properly constructed (ASDWA, 1997).

EPA used the Lieberman et al. 2002 data set to represent viral occurrence in improperly constructed wells

and the AwwaRF/AWWSC data set to represent properly constructed wells. It was implied that well

construction corresponded with vulnerability (i.e., poorly constructed wells would be vulnerable to

contamination). EPA received public comments that questioned the basis for using Lieberman et al. 2002

data to represent improperly constructed wells because the Lieberman et al. 2002 study sites were chosen

based on the presence of total coliforms and indicators of fecal contamination. To clarify this issue, EPA

is categorizing ground water systems into two groups: those that are more vulnerable and those that are

less vulnerable.11 Neither of the studies discussed above provide data regarding the percentage of ground

water sources that might be more or less vulnerable, and EPA needed to derive such estimates to support
Economic Analysis for the 4-47 October 2006

Final Ground Water Rule

this EA. EPA has used national TCR violation data from SDWIS to estimate the percent range of wells

that are more or less vulnerable. The proportion of wells in each of the well vulnerability categories is

necessary to properly apportion the virus concentration data. Viral concentration data from wells with a

history of TC contamination (i.e. the Lieberman et al. 2002 data) are used for the wells that are identified

as belonging within the more vulnerable group. Following is a description of these estimates and their

basis. 

4.3.3.2 Estimating percent wells in vulnerability categories

EPA categorized systems into two groups: those that are more vulnerable and less vulnerable.

More vulnerable systems: These are systems that may be more vulnerable to source water

contamination, reflected by having MCL violations under the Total Coliform Rule (TCR) during

a calendar year (from SDWIS, USEPA 2003a). 

Less vulnerable systems: These are systems that are expected to be less vulnerable to source

water contamination, reflected by having not had an MCL violation under the Total Coliform

Rule during the same year.

The percentage of systems in the “more vulnerable” category (and also the percentage in the “less

vulnerable” category) varies by system type (i.e., community, nontransient community, and transient

noncommunity) and system size, and ranges from zero to 6.83 percent. These proportions of wells in the

more vulnerable category are identified in Exhibit 4.14. For each element in the exhibit (system size and

type) the proportion of less vulnerable wells is 100% minus the value identified in the exhibit. Detail on

the derivation of these percentages is presented in Exhibit B.18. MCL violations are of two types. Acute

violations indicate that the system tested positive for fecal coliform or E. coli in repeat samples following

samples that are total coliform positive. Non-Acute MCL violations for systems collecting at least 40

samples per month (i.e., those serving more than 33,001 customers) occur when more than 5 percent of

samples test positive for total coliforms during a sample period. For smaller systems, an MCL violation

occurs when more than one sample tests positive for total coliforms during a sample period (violations are

for a reporting period, which for most noncommunity systems is one sample per quarter; thus for these

systems, an MCL violation occurs when a repeat sample is positive for total coliforms). Either of these

two conditions indicates a potential problem with the integrity of the system and may indicate problems

with source water quality or other conditions that may make the system and its wells more vulnerable to

contamination. 
Economic Analysis for the 4-48 October 2006

Final Ground Water Rule

System Size 

(Population 

Served) CWS NTNCWS TNCWS

<100 2.87% 2.84% 2.33%

101-500 2.66% 2.25% 2.40%

501-1,000 1.85% 1.86% 2.30%

1,001-3,300 2.23% 2.34% 3.59%

3,301-10,000 3.48% 2.21% 2.82%

10,001-50,000 3.41% 0.00% 2.94%

50,001-100K 1.82% 0.00% 0.00%

100,001- 1 Million 3.13% 0.00% 0.00%

> 1 Million 0.00% 0.00% 0.00%

Source: Exhibit B.18, derived from SDWIS (2003a)

Exhibit 4.14 Mean Percent of Systems with Acute or Monthly MCL Violations

by System Type and System Size

For ground water systems, the violation of MCLs under the TCR is an indicator of vulnerability,

especially when systems do not disinfect and distribution systems are small or do not exist. There is some

uncertainty associated with the data in Exhibit 4.14 because they include systems that disinfect as well as

those that do not disinfect. Exhibit 4.15 summarizes the available data on disinfecting systems. For

example, 64 percent of ground water systems provide no disinfection, and thus for such systems, TC

sampling under the TCR should reflect contamination in their source water. In transient noncommunity

systems, which essentially have no distribution systems, 82 percent of systems provide no additional

disinfection. In these systems, the influence of non-source water-related contamination is likely to be very

low relative to that of source water. In summary, it is assumed that disinfection has only a small

influence on the identification of more vulnerable wells using TCR violation data.

Exhibit 4.15 Number and Percent of Systems Disinfecting,

By Type of System

Total CWS NTNCWS TNCWS

Number of Systems 147,330 42,361 18,908 86,061

Approximate Percent of

Systems Disinfecting 36% 75% 29% 18%

Source: Derived from Exhibit 4.2
12 Although the GWR is aimed at preventing exposure to all viral pathogens, enterovirus data are used as a

proxy for all viral pathogens in both the viral hit rate and viral concentration analyses.

13 Although the GWR allows different indicators to be used for compliance purposes, E. coli is used as a

proxy for all indicators in the hit rate analyses. 

Economic Analysis for the 4-49 October 2006

Final Ground Water Rule

4.3.4 Occurrence Analyses

To assess potential costs and benefits of the GWR, it is necessary to estimate several occurrence

parameters. Estimates are made for both viral12 and indicator13 hit rates, viral concentrations, and cooccurrence of viruses and indicators. Cost and benefit analyses performed for the EA accompanying the

GWR proposal drew data from two of the occurrence studies to inform the analyses - the Lieberman et al.

2002 and Abbaszadegan et al. 2003 studies. At the time, these two studies were considered to be the best

suited for representing viral and indicator hit rates as well as viral concentration. Specific co-occurrence

parameters derived from the studies were not used in the proposal EA analysis. Instead, a correlation

between indicator and viral occurrence was assumed. In response to comments received on the proposal

analyses, EPA performed further detailed review and analysis of all available occurrence data.

To improve the estimates of viral and indicator hit rates and concentrations using the data

available, EPA convened a 2-day statistical workshop in May 2005. The core workgroup included expert

participants form several government agencies and private consulting firms. A summary of the workgroup

proceedings, including a list of all participants, is included in the final docket for this rulemaking. The

charge to the workgroup was to consider how to obtain improved modeling of:

a) national viral occurrence in wells,

b) indicator efficiencies for identifying fecally contaminated wells,

c) indicator efficiencies for identifying virally contaminated wells, and

d) virus concentrations in virus-positive well water.

By the end of the workshop, approaches for modeling viral and indicator prevalence and viral

concentrations (items a, b, and d) were discussed, but methods for linking indicator occurrence and virus

occurrence (item c) were not. Following the workshop, EPA acted on the workgroup’s recommendations,

provided feedback to participants, and generated model-based national estimates for both viral and

indicator occurrence. The results of this effort led naturally to a combined analysis, which also modeled

co-occurrence of viruses and indicators. This combined model serves as the basis of EPA’s quantitative

occurrence estimates. The sections below describe in detail how these new data are used to model the

occurrence of virus and indicators in ground water sources.

The workgroup also considered the question of data selection with regard to the available

occurrence studies. Individually, the studies are not nationally representative, but represent select

portions of the ground water universe. Collectively, the studies describe a full range of geographic,

geologic, and other characteristics (e.g., variety of system sizes and system types). Workshop participants

recommended against discarding any study’s data without cause but did not feel they had the expertise to

make any final calls regarding specific studies. Because the final selection of data was beyond the scope

of their expertise, the issue was remanded for further consideration by EPA’s subject matter experts. The

discussion of each occurrence study is presented in Section 4.3.2, with a summary of the final use(s) of

each presented in Exhibit 4.12.
Economic Analysis for the 4-50 October 2006

Final Ground Water Rule

4.3.4.1 Viral and Fecal Indicator Hit Rates

This section discusses the estimation of the hit rates for viruses and fecal indicators in the source

waters of ground water wells. The rates are derived from pooled analyses of the data presented in Section

4.3.2, above. Hit rate information is a critical input for both the model of baseline risk of viral infections,

illnesses, and deaths and for modeling the reduction of viral risks from components of the GWR

dependent upon source water monitoring of fecal indicators. Indicator hit rate information is also a

critical input for cost modeling. The application of the hit rates for determining the baseline risk and risk

reductions from the rule options is described in detail in Chapter 5. The application of indicator hit rates

for determining the costs of some of the rule options is described in Chapter 6. 

The term hit rate refers to the probability that a virus or fecal indicator, or both, will ever be

present in the source water of a well and, if so, how frequently each is expected to be present. Hit rates,

therefore, have two components which are referred to here as Pwell and Psample. 

Pwell refers to the probability that a randomly selected well will ever have a virus (or indicator)

present in its source water. Applying this probability to all wells provides an estimate of the number of

wells that ever have virus (or indicator) present in their source water.

Psample refers to the probability that a random sample from a contaminated well will be positive

and will vary from well-to-well.

So, for example, a virus Pwell value of 0.10 implies that 1 out of every 10 wells will have

detectable virus present in its source water at some time. Conversely, it also implies that 9 out 10 wells

will not ever have detectable virus.

A well with a virus Psample value of 0.25 would be expected to have detectable virus in 1 of every 4

samples assayed. 

There are a number of factors that influence the estimation, as well as the interpretation, of Psample. 

Microorganisms in water are dispersed spatially at low average concentrations relative to the volumes of

water typically collected in assays. As a result, a randomly taken sample of some volume V may not have

the microorganism present even when it is known to be in the source water. Often the recovery rate for

these pathogens is less than 100%, and viruses that are present in samples are not always detected. In

addition, the actual presence of microorganisms in the source water is recognized as being intermittent in

nature due to changes in the actual sources of the contamination as well as hydrogeological and other

physical factors affecting transport from the sources to the water used at that well.

It is important to recognize that while the same Pwell value applies to all wells, each individual

contaminated well is expected to have its own Psample value. That is, the underlying data suggest that

among those wells that have a virus or fecal indicator present at some time, the probability of observing it

in a given sample (that is, of it being present in that sample volume on that particular day) will vary from

well to well. Consequently, a distribution of Psample values was derived to reflect Psample variability from

well to well. Specifically, a beta distribution of Psample was derived from the underlying occurrence data.

The beta distribution is often used for this purpose, that is, to describe distributions of probabilities or

other variables that range between zero and one. (The probit and logit distributions are sometimes used

for this purpose, and generally produce estimates similar to those produced using the beta distribution.) 
Economic Analysis for the 4-51 October 2006

Final Ground Water Rule

P1 

(virus, no indicator) 

P3 

(indicator, no virus) 

P2 

(virus and indicator) 

P4 

(no virus, no indicator) 

P4 = 1 – (P1 + P2 + P3)

The beta distribution is a two-parameter distribution; the parameters are usually designated α and β. The

estimation of those parameters for the beta distribution of Psample is described further below. 

The Venn diagram shown in Exhibit 4.16 describes the basic co-occurrence model. This diagram

shows that some fraction of wells (P1) has some virus contamination, but no indicator, while another

fraction of wells (P2) has both virus and indicator, and a third fraction of wells (P3) has indicator, but no

viral occurrence. A fourth fraction of wells (P4), having neither viral nor indicator occurrence is the

remainder: P4 = 1 - (P1+P2+P3).

Exhibit 4.16 Categories of Indicator and Viral Classification Among PWS Wells in

U.S.

To fully characterize both Pwell and Psample for viral pathogens and fecal indicators, and to

characterize their co-occurrence, the model requires the estimation of seven parameters: P1, P2, P3, αvirus,

βvirus, αindicator, and βindicator from the available occurrence data. Pwell for virus is equal to P1+P2, and Pwell

for indicators is equal to P2+P3. Psample for viruses (referred to hereafter as Pvsample) at different wells is
Economic Analysis for the 4-52 October 2006

Final Ground Water Rule

described by a beta distribution with the parameters αvirus and βvirus. Similarly, Psample for indicators

(referred to hereafter as Pisample) at different wells is described by a beta distribution with the parameters

αindicator and βindicator. 

It is important to note that the occurrence model developed by EPA relates virus and indicator

co-occurrence only in terms of Pwell (the fraction of wells having one, the other, or both). It does not

provide for different levels of Pvsample or Pisample in wells having both or only one of the two contaminants. 

Wells having both virus and indicator presence may well have them greater fractions of the time than

wells having only virus or wells having only indicator. A model that would include this feature would

require four parameters to explain variable Pvsample and Pisample in wells having both virus and indicator. 

However, the limited amount of occurrence data is not sufficient for a model with that degree of

complexity. 

Another important point to note is that, while the preceding overview of the occurrence model

refers to the P1, P2 and P3 parameters for Pwell and the α and β parameters for Psample as though only single

“best values” are estimated, the occurrence model is actually designed to capture the uncertainty in those

values and produces a very large number (10,000) of sets of those seven parameters that are subsequently

sampled in the Monte Carlo simulations that are performed for both the risk/benefits model and the cost

model used to evaluate the impact of the ground water rule options.

Parameter Estimation Methods

Markov Chain Monte Carlo (MCMC) methods were used in a Bayesian framework to produce

samples from the joint posterior parameter distribution (the sample of 10,000 discussed in the paragraph

above). This posterior density function is a product of a prior density function and a likelihood function. 

WinBUGS software (Gilks and Spiegelhalter, 1994) was used to produce the large MCMC sample,

which, in turn was used to inform the Rule’s risk and cost analyses. This section describes the prior and

likelihood functions of the seven-parameter model.

Non-Informative Priors

Parameters P1, P2, and P3 [together with P4, where P4 = 1 – (P1 + P2 + P3)] are the fractions of

all ground water wells falling into the four possible subsets as shown in Exhibit 4.11. A relatively

non-informative prior on these is Dirichlet with parameters (1, 1, 1, 1). This is the multivariate extension

of the Beta (1, 1) distribution, which is often used for the one-parameter case. Beta (1, 1) is a uniform

distribution for one unknown over the range [0, 1] and likewise, Dirichlet(1, 1, 1, 1) is uniform over the

three-dimensional space where the sum of P1, P2, and P3 is in the range [0, 1].

Pvsample and Pisample are both assumed to be beta-distributed across wells having virus presence and

wells having indicator presence, respectively. The Beta density function is usually expressed in terms of

its parameters α and β as:

dbeta p( ) , β α, p

α−1 ( ) 1 p − β−1 ⋅ Γα β ( ) +

Γ α( )⋅Γ β( ) ⋅
Economic Analysis for the 4-53 October 2006

Final Ground Water Rule

where p in this expression is one of the Psample variables. Assigning priors with this form of the density is

difficult. First, it is difficult because one cannot think about α (or β) without understanding β (or α). 

Second, a non-informative prior leads to an improper posterior density, with increasing mass as the sum

(α + β) becomes large. In our case, a uniform prior on (α, β) suggests strong knowledge that the

variability of Psample is small about some mean value. Gelman, et al. (1995), discuss this problem in their

book “Bayesian Data Analysis” and suggest reparameterization in terms of the mean, a = α / (α + β) and

the inverse square root of the “sample size,” b = 1/(α + β)

0.5. EPA adopted this parameterization and

utilized disperse uniform priors for the two new parameters (a and b). The conventional beta distribution

parameters can be derived from new parameters a and b as follows:

α = a / b2

β = (1 – a) / b2

Therefore, for parameterization of the occurrence model, avirus, bvirus, ainidicator, and bindicator are

estimated, and the corresponding α and β values for the beta distributions are computed from them as

shown above.

The Likelihood Function

The virus and indicator data for an individual well used as input to EPA’s occurrence model can

be reduced to four integers. The four integers for a well are:

Nv = the total number of virus assays for the well

Kv = the number of virus positives for the well

Ni

 = the total number of indicator assays for the well

Ki

 = the total number of indicator positives for the well

Up to three of these may be zeros; at least one of the values Nv or Ni

 must be >1 for it to be valid

input to the model.

The likelihood of a well’s data, given parameter values (P1, P2, P3, "virus, $virus, "indicator, and

$indicator , and the category of a well), is a function of the parameter values and the well's data (the well's

Nv, Kv, Ni

, and Ki values), where "virus and $virus are parameters for beta-distributed Pvsample for viruses and 

"indicator and $indicator are parameters for beta-distributed Pisample for indicators. The total likelihood (for the

entire data set) is simply the product of these individual well likelihoods.

In general, the likelihood for a well has three parts, the probability of what was observed for

virus, given the number of virus assays, the probability of what was observed for E. coli, given the

number of E. coli assays, and the probability of the well's membership in its category (P1, P2, P3, or P4). 

Below, these two factors are defined for wells of the four different categories (virus only, virus and E.

coli, E. coli only, and no contamination):
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Final Ground Water Rule

L1 Kv Nv , ( ) P1

0

1

Psamplev dbeta Psamplev αv , βv ( ) , dbinom Kv Nv , Psamplev ⋅ ( ) , ⌠

⎮

⌡

⋅ d

L2 Kv Nv , Ki , Ni ( ) , P2 L1 Kv Nv , ( ) ⋅

0

1

Psamplei dbeta Psamplei αi , βi ( ) , dbinom Ki Ni , Psamplei ⋅ ( ) , ⌠

⎮

⌡

⋅ d

L3 Ki Ni ( ) , P3

0

1

Psamplei dbeta Psamplei αi , βi , ( ) dbinom Ki Ni , Psamplei ⋅ ( ) , ⌠

⎮

⌡

⋅ d

1. Well has some virus occurrence, but no E. coli occurrence (in area P1 of Exhibit 4.16):

where dbeta is the beta probability density function and dbinom is the binomial probability mass function. 

A well of this type must have had no E. coli detections, so the probability of observing Ki

 = 0 positives is

1 and its product with L1(Kv, Nv) is simply L1(Kv, Nv). 

2. Well has both virus and E. coli occurrence (in area P2 of Exhibit 4.16):

Note that, to be in this category, it is not necessary that a well actually have observed virus and E. coli

positives. Having no positive, based on a small number of assays, is only weak evidence that a well

belongs to another category. At each uncertainty iteration, wells are assigned to categories according to

the likelihood, conditional on the well's data plus all other parameter values at that time. In this fashion,

parameters P1, P2, P3, and P4 also enter the likelihood. The only wells that are assigned to this category

with certainty are those which were observed to be positive for both viruses and E. coli. At every

iteration, they are placed in this category. All other wells are randomly assigned to different categories

from iteration-to-iteration, according to their likelihoods.

3. Well has E. coli, but no virus occurrence:

4. Well has neither virus nor E. coli occurrence:

Wells having no observed contamination can belong to any category. Wells assigned to this category

must always have negative assays. The likelihood of observing no positives is certain, so the only

contribution to the likelihood is the probability of membership, P4. 

Estimates for Combined Model

Estimates were produced by Markov Chain Monte Carlo methods using WinBUGS software

(Gilks and Spiegelhalter, 1994). An important feature of this MCMC analysis is that it produces a large,

well-mixed sample of outputs wherein each individual output contains a plausible value for each of the

seven parameters in combination with one another. In this modeling, EPA captured 10,000 sets of results
Economic Analysis for the 4-55 October 2006

Final Ground Water Rule

0.0%

10.0%

20.0%

30.0%

40.0%

50.0%

60.0%

70.0%

80.0%

90.0%

012345 P1 P2 P3 P4

for the seven parameters to characterize uncertainty about the parameter values. The MCMC modeling

captures the uncertainty in the parameter estimates through this large number of sets of results with

appropriate correlation structure.

The actual data used to estimate the seven parameters was the enteroviruses cell culture data for

viruses and the E. coli for the indicators data from the 15 occurrence studies described in Section 4.3.2. 

Of those 15 studies, 12 have enterovirus cell culture data and 12 have E. coli data.

The following exhibits provide summaries of the Pwell and Psample results obtained from the

modeling for viruses and indicators. Exhibit 4.17 shows the median values for P1, P2, P3 and P4. The

“error bars” included on the graphs reflect the 5th and 95th percentiles of the 10,000 values estimated. As

indicated earlier (refer to Exhibit 4.11), P1 refers to the fraction of wells having virus at some time (but

no indicator), P2 refers to those wells having virus and an indicator at some time, and P3 refers to those

having an indicator at some time (but no virus). P4 are those wells having neither virus nor indicator

occurrence. Estimates were produced by Markov Chain Monte Carlo methods using WinBUGS software

(Gilks and Spiegelhalter, 1994).

Exhibit 4.17 Median of 10,000 Estimates of P1, P2, P3, and P4

(with error bars showing the 5th and 95th percentiles)

The median values obtained in the model for P1, P2 and P3 are 7.4%, 14.0% and 7.3%,

respectively. The median value for the sum P1+P2+P3 (wells with sometime presence of virus and/or

indicator) is 32.4%. The 5th and 95th percentiles on the sum of P1, P2 and P3 were found to be 18.2% and

70.6%. P4, the remaining wells that have neither virus nor indictor present at anytime is derived from the

model estimates for the other three as 1 minus (P1+P2+ P3). The median P4 value is 67.6%, with 5th and
Economic Analysis for the 4-56 October 2006

Final Ground Water Rule

0.000

0.100

0.200

0.300

0.400

0.500

0.600

0.5 0.7 0.9 1.1 1.3 1.5 1.7 1.9 2.1 2.3 2.5 Pwell Virus Pwell Indicator

95th percentiles on P4 of 29.4% and 81.8%. Thus, approximately 90% of the 10,000 estimates of wells

having either virus or fecal indicator occurrence fall between about 20% and 70%, with a central estimate

of about 32%.

If E. coli was a perfect indicator of virus occurrence, there would be no wells with only virus or

only E. coli. P1 and P3 would both be zero. Clearly, E. coli is not a perfect indicator of viral occurrence.

Exhibit 4.17 shows that most wells with virus occurrence tend to also have E. coli occurrence (P2 is

greater than P1) and that most wells with E. coli occurrence tend to also have virus occurrence (P2 is

greater than P3). Given that approximately 24% of wells have virus occurrence while 23% of wells have

E. coli occurrence, if viruses and E. coli were completely independent, then the fraction of wells having

both (P2) would equal the product 0.24 * 0.23, or 5.5%. The large median value of P2 (14.0%)

demonstrates that, though imperfect, E. coli is a positive indicator of viral occurrence.

As noted previously, two of the important hit rate values are Pwell for viruses and Pwell for

indicators. These are composed of P1+P2 for viruses and P2+P3 for indicators. Exhibit 4.18 provides the

median (and the 5th and 95th percentile values) for Pwell for viruses and for indicators.

Exhibit 4.18 Median of 10,000 Estimates of Pwell for Virus and Indicator

(with error bars showing the 5th and 95th percentiles)

The median value of Pwell for viruses was found to be 23.6% with 5th and 95th percentiles of 9.8%

and 55.5%. The median of Pwell for indicators was 22.5% with 5th and 95th percentiles of 11.6% and

55.5%. As shown in Exhibit 4.18, median values and overall ranges of Pwell for viruses and indicators are

quite similar. However, the distribution of paired values for these covers a very wide range of

combinations. The scatter plot shown in Exhibit 4.19 shows the paired combinations of a sample of 1,000

of the 10,000 values. While most of the pairs tend to fall in the 10% to 20% range for both viruses and
Economic Analysis for the 4-57 October 2006

Final Ground Water Rule

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1

0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1

Pwell for Viruses

Pwell for Indicators

indicators, there are a substantial number that fall above this range including many where one value for

the pair is high and the other relatively low. 

Exhibit 4.19 Scatter Plot of Pwell Pairs for Indicators and Viruses

As described above, the Pvsample for viruses and Pisample for indicators are not single value estimates

but are, rather, distributions of values reflecting the variability in Psample from well to well. As a result, the

occurrence model generates 10,000 of these distributions for both Pvsample and Pisample. It is difficult to

provide a summary of all 10,000 of those distributions, particularly because the beta distribution used in

this analysis can take on a wide range of shapes. 

The beta distributions obtained for Psample have three different shapes: exponential, U-shaped, and

bell-shaped (right-skewed). Representative examples of these three shapes for Psample for viruses are

presented in Exhibit 4-20 as the density functions and in Exhibit 4-21 as the cumulative probability

distributions. (Note that these particular examples were selected because they present values that are

close to the central tendencies for the three distribution shapes of Psample for viruses.)

For Psample for viruses, about 73% of the distributions have the exponential shape, 23% have the

U-shape and 4% have the right-skewed bell shape. For Psample for indicators, about 79% of the

distributions have the exponential shape, 2% have the U-shape and 19% have the right-skewed bell shape.
Economic Analysis for the 4-58 October 2006

Final Ground Water Rule

0.2 0.4 0.6 0.8 0

2

4

6

8

10

Exponential (~73%)

U-shaped (~23%)

Bell (~4%)

Psample (Virus)

Probability Density

0.2 0.4 0.6 0.8

0

0.2

0.4

0.6

0.8

Exponential (~73%)

U-shaped (~23%)

Bell (~4%)

Psample (Virus)

Cumulative Probability

Exhibit 4.20 Density Function Shapes of Psample for Viruses

Exhibit 4.21 Cumulative Distributions of Psample for Viruses

One way to summarize the full set of 10,000 Psample distributions generated by the occurrence

model is in terms of the range and central tendency of their expected values. For Pvsample, the median of

the expected values is 9.4%, with 5th and 95th percentile values are 3.8% and 23.2%, respectively. For

Pisample, the median of the expected values is 12.7%, with 5th and 95th percentile values are 4.9% and

25.0%, respectively. These values are also shown graphically in Exhibit 4.22.
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Final Ground Water Rule

0.000

0.050

0.100

0.150

0.200

0.250

0.300

0.5 0.7 0.9 1.1 1.3 1.5 1.7 1.9 2.1 2.3 2.5 Average Psample Virus Average Psample Indicator

Exhibit 4.22 Median of 10,000 Estimates of Psample for Virus and Indicator

(with error bars showing the 5th and 95th percentiles) 

The range and central tendency of the expected values for Pvsample and Pisample are similar. The

distribution of expected values for Pvsample and Pisample pairs produced by the model, shown in Exhibit 4.23

for a sample of 1,000 pairs, shows a substantial number of pairs where both have values in the 5% to 15%

range. However, there are a number where one of the pair is substantially higher (or lower) than the other

member of the pair.
Economic Analysis for the 4-60 October 2006

Final Ground Water Rule

0

0.05

0.1

0.15

0.2

0.25

0.3

0.35

0.4

0 0.05 0.1 0.15 0.2 0.25 0.3 0.35 0.4

Mean of Psample for Viruses (av)

Mean of Psample for Indicators (ai)

Exhibit 4.23 Scatter Plot of Means of Psample Pairs for Indicators and Viruses

An important relationship that can be seen from the results of the occurrence modeling is between

paired Psample means and Pwell values. For both viruses and indicators, it was found that there is, generally,

an inverse relationship between them. The product of Pwell and the average of Psample is approximately

equal to the overall fraction of samples found to be virus-positive, therefore the inverse relationship is

expected. If either Pwell or the average Psample were increased without increasing the other, then

significantly more virus-positive results should have been observed across the survey data sets. Similarly,

a decrease in one, but not the other, would predict fewer positives than were observed. That is, a

characteristic of the uncertainty revealed by the 10,000 sets of results from the occurrence modeling is

that if the ‘true’ value of Pwell (the fraction of wells that have virus or indicator present at some time) is

high, the chance of finding the organism in a given sample at those wells tends to be low. Conversely, if

the ‘true’ value of Pwell is low, the chance of finding the organism in a given sample at those wells tends

to be higher. These relationships are shown in Exhibits 4.24 and 4.25 for viruses and indicators,

respectively, for a sample of 1,000 from the 10,000 sets of results produced by the occurrence model. 
Economic Analysis for the 4-61 October 2006

Final Ground Water Rule

0

0.05

0.1

0.15

0.2

0.25

0.3

0.35

0.4

0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1

Pwell

Average Psample (av)

0

0.05

0.1

0.15

0.2

0.25

0.3

0.35

0.4

0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1

Pwell

Average Psample (ai

)

Exhibit 4.24 Mean of Psample Versus Pwell for Viruses

(1,000 Pairs from Occurrence Model)

Exhibit 4.25 Mean of Psample Versus Pwell for Indicators

(1,000 Pairs from Occurrence Model)
14 The discussion below can also be applied to estimate the impact of assessment monitoring as an optional

activity under the final rule, as well as under Alternative 3. The difference in the application of the analysis

described below is driven solely by the number of samples taken, which will be more under assessment monitoring

scenarios.

Economic Analysis for the 4-62 October 2006

Final Ground Water Rule

F

n i, Piwelln

0

1

dbeta Ps ( ) , β αn, n 1 1 Ps ( ) − Ps i 1+ − ⎡

⎣ ⎤ ⋅ ⎦ ⌠

⎮

⌡

⋅ d

, 

which simplifies to: 

F

n i, Piwelln

Piwell

n

Γ α( ) n + βn Γ βn ⋅ ( ) + i

Γ αn + βn ( ) + i Γ β( ) n ⋅ − ⋅

. 

Use of Indicator Occurrence for Triggered Monitoring14

This section describes how the occurrence modeling described above, specifically that for the

indicator hit rates, is used to predict the number of wells “captured” by triggered source water monitoring. 

The fraction of wells producing an indicator positive upon their first assay can be estimated as a function

of the following:

Piwell = fraction of wells with some indicator occurrence

αi = first parameter of beta-distributed Pisample

βi = second parameter of beta-distributed Pisample

As discussed in the section above, in each uncertainty iteration of the occurrence model, a set of

parameter values describing indicator occurrence is selected from the MCMC sample (as well as

parameters for Pvwell and Pvsample that describe virus occurrence). The probability that an indicator positive

will be observed by the time of the ith assay can be obtained from Fn,i: 

The probability that the ith assay will be the very first positive for the site is the difference Fn,i -

Fn,i-1. This is, then, the fraction of all wells expected to return an indicator positive upon the ith assay.

These probabilities (the Fn values) were derived for assays i = 1 through 200 for n = 10,000

uncertainty iterations. These probabilities are specifically associated with each set of the seven

occurrence parameters generated by the model as described previously.

Exhibit 4.26 shows the cumulative probability of having an indicator on or before the indicator

assay number. A sample of 1,000 sets was generated from the occurrence model, and three of the 1,000

curves are shown in the graph corresponding to the 5th percentile, median, and 95th percentile of all values

for that assay number. These data are used in the cost model simulation, discussed further in Chapter 6,

to determine whether, and if so when, a given well conducting triggered source water monitoring will
Economic Analysis for the 4-63 October 2006

Final Ground Water Rule

0

0.05

0.1

0.15

0.2

0.25

0.3

0 50 100 150 200

Assay number

Probability of Positive by Assay Number

95th Percentile of n = 1,000 Values

Median of n = 1,000 Values

5th Percenitle of n = 1,000 Values

( 1 2) ( 2 3)

2

P P P P

P

+ ⋅ +

have its first indicator positive and as a result initiate corrective action. These data suggest that of all

wells taking source water indicator samples, just under 20% would be expected to have a positive result

on or before the 200th assay, as a central tendency estimate, with an uncertainty range from

approximately 10% to over 25%.

Exhibit 4.26 Cumulative Probability of an Indicator Positive as a 

Function of Assay Number -- All Wells (used for cost analysis)

Similar data on the occurrence of the first indicator positive as a function of assay number are

used in the risk reduction model, as discussed further in Chapter 5, to determine the effectiveness of

indicator monitoring in source water to “capture” wells that are known to have virus present at some time

(that is, areas P1 + P2 in the Venn diagram shown earlier in this chapter). For this part of the analysis, the

Fn,i values are adjusted to account for assays performed on those wells that are in the P1 + P2 “space”. 

The adjustment made to the value of each assay probability result obtained as shown above is to multiply

it by:

Exhibit 4.27 shows the three corresponding distributions for these adjusted values used for the

risk reduction modeling. These data suggest that of those wells that have sometime presence of a virus

and take source water indicator samples, just under 50% would be expected to have a positive on or
Economic Analysis for the 4-64 October 2006

Final Ground Water Rule

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

0 50 100 150 200

Assay number

Probability of Positive by Assay Number

95th Percentile of n = 1,000 Values

Median of n = 1,000 Values

5th Percentile of n = 1,000 values

before the 200th assay, as a central tendency estimate, with an uncertainty range from approximately 20%

to 80%. The higher values shown here relative to the “all wells” data shown above reflect the outcome

that a much higher proportion of wells having some time virus presence also have some time indicator

presence [i.e., P2/(P1+P2) than do all wells [i.e., (P2+P3)/(P1+P2+P3+P4)].

Exhibit 4.27 Cumulative Probability of an Indicator Positive as a Function of

Assay Number -- Virus-positive Wells (used for risk reduction analysis)

It is important to note also that both of these sets of results indicate that observing an indicator

positive in an early assay is more likely than on a later assay. This is because the structure of the model

accounts for the higher likelihood of observing positives among those wells where the frequency of

occurrence (that is, Psample) is greatest.

4.3.4.2 Pathogen Concentration Analysis

The preceding section addressed hit rates, which comprise the first aspect of characterizing virus

occurrence in source water used by public ground water wells. This section addresses virus

concentrations which comprise the second aspect of occurrence. 
15 Although hit rates were developed for both viruses and indicators, virus concentration modeling is necessary for the

risk and benefits analysis, but E.coli concentration modeling is not. For the indicators, the hit rate information is needed to

estimate risk reduction for the regulatory alternatives.

Economic Analysis for the 4-65 October 2006

Final Ground Water Rule

Hit rates primarily address the consideration of "presence / absence" of virus in the water. The

two components of hit rates are Pwell, which characterizes the fraction of wells where viruses are either

present at some time or are never present, and Psample, which characterizes the fraction of samples or

duration of time that the organisms occur in those wells that have viruses at some time.

If a well is one in which the virus is never detected (which is expected to be the case the majority

of the time), the virus concentration is assumed to be zero. For those wells at which viruses are present at

detectable levels however, it is necessary to characterize the expected concentrations of viruses so that the

baseline risk and the risk reductions from regulatory alternatives can be estimated15.

The available information on virus concentrations in wells is limited. Although the analysis

performed here considers two categories of pathogenic viruses (Type A and Type B), useful information

on virus concentrations are only available from cell culture results for Type B viruses (enteroviruses). 

For the purposes of this analysis, it has been assumed that the concentrations of Type A viruses are

similar to those for Type B.

Just as there is variability in virus occurrence with respect to prevalence (some wells have viruses

while others do not, and for those that do, the frequency of occurrence varies among contaminated wells),

so too, there is variability in expected concentrations of viruses from well to well among those wells

where viruses occur. As will be evident from the information presented, this variability encompasses

both large scale differences between those wells considered to be less vulnerable and those considered to

be more vulnerable, as well as differences from one location to another within each of these two

categories of wells. 

As noted previously, participants in the May 2005 statistics workshop were asked to consider

how to model virus concentrations in virus-positive well water. Several options were considered both for

stratifying the wells into different categories to reflect different ranges of expected concentrations and for

fitting the concentration data to specific distributional forms to use in the baseline risk and risk reduction

modeling. However, no specific recommendations were made.

Following the workshop, EPA decided to stratify wells into two categories according to overall

vulnerability characteristics (more and less vulnerable wells). Unlike the hit rate analyses which draw on

data from 15 different studies, EPA relied upon only three key studies for viral concentration data. The

data from the Lieberman et al. 2002 study are used to represent virus concentrations in more vulnerable

wells and the combined data from the Abbaszadegan et al. 2003 study and the Pennsylvania study are

used to represent concentrations from less vulnerable wells. The Lieberman et al. 2002 concentration

data comes from wells that were included in the study because they had a history of TC contamination or

other evidence of vulnerability. As such, they are most like wells with TCR violations and therefore are

assumed to be representative of this group of more vulnerable wells. The Abbaszadegan et al. 2003 

study and the Pennsylvania study include wells selected for reasons other than a TC occurrence history. 

As such, they are assumed to represent the less vulnerable wells group. Furthermore, the Pennsylvania

wells are exclusively noncommunity wells and therefore the measured concentrations in these wells

represent the group of less vulnerable noncommunity wells.
Economic Analysis for the 4-66 October 2006

Final Ground Water Rule

Virus Concentration Data Used

Concentrations for More Vulnerable Wells

EPA identified the Lieberman et al. 2002 study as providing the most complete set of virus

concentration information for wells considered to be more vulnerable. These data are from cell culture

assays for Type B viruses. As described in section 4.3.2, seven of the 30 wells in this study were found to 

have virus present by the cell culture method. A total of 20 positive values were observed. The

concentrations of the positive values are presented in Exhibit 4.28 below.

Exhibit 4.28 Summary of Virus Concentrations Observed

 in the Lieberman et al. 2002 Study

Study Well Number Concentration (PFU or MPN per 100 L)

29 6.55

29 12.32

29 27.01

29 0.86

29 3.72

29 2.01

29 10.59

31 19.63

31 15.37

31 10.76

31 9.61

47 45.33

47 3.17

47 43.99

47 47.72

61 53.37

61 25.17

91 12.78

97 9.52

99 212.51

Note: Shaded rows indicate State determined GWUDI wells.
Economic Analysis for the 4-67 October 2006

Final Ground Water Rule

 Concentrations for Less Vulnerable Wells

EPA identified the Abbaszadegan et al. 2003 and the Pennsylvania Noncommunity Well studies

as providing the most complete set of virus concentration information for wells considered to be less

vulnerable. These data are from cell culture assays for Type B viruses.

In the Abbaszadegan et al. 2003 data, there were a total of 22 samples taken from 21 different

wells with cell culture concentration data, as summarized in Exhibit 4.29 below.

Exhibit 4.29 Summary of Virus Concentrations Observed

 in the Abbaszadegan et al. 2003 Study

Study Well Number Concentration (viruses per 100 L)

AZ-0001 / 3 1.89

AZ-0001 / 3 0.18

ID-0002 0.09

MO-0001 0.36

NH-1 0.19

IL-5 1.56

CA-1 0.45

PA-7 0.15

PA-21 0.17

NJ-13 0.17

CA-12 0.45

NJ-12 0.18

IL-10 0.18

IN-32 0.64

O-NY-15 0.18

O-WI-10 0.46

O-CA-22 0.92

O-CA-21 0.18

O-OH-6 0.19

OH-1 0.92

OH-3 0.15

IN-31 0.18
Economic Analysis for the 4-68 October 2006

Final Ground Water Rule

In the Pennsylvania Noncommunity Well study, there were a total of 5 samples taken from 5

different wells with cell culture concentration data, as summarized in Exhibit 4.30 below.

Exhibit 4.30 Summary of Virus Concentrations Observed

 in the Pennsylvania Noncommunity Study

Study Well Number Concentration (viruses per 100 L)

HU 425 0.21

JU 372 51.99

CE396 18.30

CH 5994 0.21

BR852 33.4

Application of Virus Concentration Data for Baseline Risk and Risk Reduction Models

As noted above, the participants in the May 2005 statistics workshop discussed alternative

distributional forms to fit to the concentration data for use in the risk and risk reduction models. 

Following the workshop, EPA explored several options for fitting the data but determined that because of

the limited number of data points and the considerable variability in the data even within the two

vulnerability strata, that rather than fitting the data to a specific distributional form it was preferable to

use the data directly and draw from them randomly, with replacement, in the simulation model. 

Therefore, for the baseline risk and risk reduction simulation models as described in Chapter 5,

each well that is identified as having virus present at some time has a concentration value drawn from one

of the 20 values shown above from the Lieberman et al. 2002 study if that well is in the more vulnerable

stratum, and from one of the 27 values shown above from the Abbaszadegan et al. 2003 and

Pennsylvania studies if that well is in the less vulnerable stratum.

The concentration thus selected is assumed to be the average concentration in those samples or on

those days when the virus is present. The use of these concentrations along with the Psample value for the

wells identified as having virus present is described in more detail in Chapter 5.

4.4 Outbreak Baseline and Causes of Contamination

CDC, EPA, and the Council of State and Territorial Epidemiologists have maintained a

collaborative surveillance program for collection and periodic reporting of data on waterborne disease 

outbreaks since 1971. The CDC database and biennial CDC–EPA surveillance summaries include data

reported voluntarily by the States on the incidence and prevalence of waterborne illnesses. According to

the CDC–EPA database for ground water systems, between 1991 and 2000, a total of 68 outbreaks and

10,926 cases of illnesses were reported for GWSs (see Exhibit 4.32). Although CDC has data dating back

to 1971, the 1991 to 2000 data represent the best available data since the implementation of the current
Economic Analysis for the 4-69 October 2006

Final Ground Water Rule

Cause of Contamination Number of 

Outbreaks

Percent

Outbreaks

Cases of

Illness

Percent

Illnesses

Cases

per

Outbreak

Untreated Ground Water 5 26% 167 6% 33

Treatment Deficiency 7 37% 1,624 58% 232

Distribution System Deficiency 5 26% 803 29% 161

Miscellaneous/Unknown 2 11% 183 7% 92

Total 19 100% 2,777 100% 146

Untreated Ground Water 23 47% 4,057 50% 176

Treatment Deficiency 19 39% 3,264 40% 172

Distribution System Deficiency 6 12% 442 5% 74

Miscellaneous/Unknown 1 2% 386 5% 386

Total 49 100% 8,149 100% 166

Untreated Ground Water 28 41% 4,224 39% 151

Treatment Deficiency 26 38% 4,888 45% 188

Distribution System Deficiency 11 16% 1,245 11% 113

Miscellaneous/Unknown 3 4% 569 5% 190

Total 68 100% 10,926 100% 161

Community Water Systems

Noncommunity Water Systems

Combined

drinking water regulations (e.g., Total Coliform Rule). The reported outbreaks resulted from virus

contamination, bacterial contamination, and unknown factors. Exhibit 4.31 shows a summary of

waterborne disease outbreaks for ground water systems. Causes reported as miscellaneous are outbreaks

where insufficient data exist to accurately categorize the source of the contamination.

Exhibit 4.31 Summary of Waterborne Disease Outbreaks Attributable to PWSs

Served by Wells using Ground Water: 1991-2000*

*Excludes disease caused by pathogenic protozoa in PWS since such systems are deemed 

 as ground water under the direct influence (and are subject to surface water treatment rule requiements) .

Sources: CDC, 1993; Kramer et al., 1996; Levy et al., 1998; Barwick et al., 2000; Lee et al., 2002

The number of outbreaks reported to the CDC are believed to be an underestimate of the total

number of waterborne outbreaks that actually occur (National Research Council 1997a, Frost et al.,

1996). Some of the reasons for the lack of recognition and reporting of outbreaks include the following.

C Some States do not have active disease surveillance systems. Thus, States that report the

most outbreaks may not be those in which the most outbreaks occur.

C Health officials may not recognize the occurrence of small outbreaks, even in States with

effective disease surveillance systems. In cities, large outbreaks are more likely to be

recognized than sporadic cases or small outbreaks in which ill persons may consult

different physicians.
Economic Analysis for the 4-70 October 2006

Final Ground Water Rule

C Some States do not always report identified waterborne disease outbreaks to the CDC. 

Reporting outbreaks is voluntary.

C Most cases of waterborne disease are characterized by general symptoms (diarrhea,

vomiting, etc.) that cannot be distinguished from other illnesses.

C Only a small fraction of people who develop diarrheal illness seek medical assistance.

C Many public health care providers may not have sufficient information to request the

appropriate clinical test.

C Even if a clinical test is ordered, the patient must comply, a laboratory must be available

and be proficient, and a positive result must be reported in a timely manner to the health

agency.

C Not all outbreaks are effectively investigated. Outbreaks are included in the CDC

database only if water quality and/or epidemiological data are collected to document that

drinking water was the route of disease transmission. Monitoring after the recognition of

an outbreak may be too late in detecting intermittent or one-time contamination events.

C The vast majority of ground water systems are NCWSs. Outbreaks associated with many

types of NCWSs may be less likely to be recognized than those in CWSs because

NCWSs generally serve nonresidential areas and transient populations.

Although they may be under-reported, documented outbreaks demonstrate that ground water

sources are not free of pathogenic contaminants and thus support the need for the GWR. The true

incidence of waterborne outbreaks and associated illness is unknown. In addition, persistent low to

moderate levels of endemic waterborne illness often go undetected by routine disease surveillance

programs. This lack of knowledge stems from inadequate surveillance of disease outbreaks, insufficient

outbreak detection methods, lack of epidemiologic investigation, and lack of microbial monitoring.

4.5 Summary of Uncertainties in Development of GWR Baselines

Uncertainty in this baseline analysis is due to limitations of the available information. These

uncertainties contribute to uncertainties in the cost and/or benefit estimates presented in Chapters 5 and 6. 

Exhibit 4.32 presents a summary of these uncertainties and indicates their potential impacts on the cost

and benefits estimates.
Economic Analysis for the 4-71 October 2006

Final Ground Water Rule

Exhibit 4.32 Summary of Uncertainties Affecting GWR Baseline Estimates

Uncertainty

Section

with Full

Discussion

of

Uncertainty

Effect on Benefit Estimate Effect on Cost Estimates

UnderestimateOverestimateUnknown

Impact

UnderestimateOverestimateUnknown

Impact

Uncertainty in baseline

data inputs (SDWIS and

1995 CWSS data)

4.2.3 X X

Mixed systems in

baseline 4.2.3 X X

CWS flow equations

used for NCWSs 4.2.4 X X

Percent of wells in

vulnerable category 4.3.3 X X

Percent of sensitive

wells below X X

Viral hit rates 4.3.2,

4.5.4.1, and

below

X

Viral concentrations 4.4.2 and

below X

Indicator hit rates 4.3.2 X X

Wells with viruses have

them at same levels

regardless of indicator

presence 

below X X

Wells with viruses have

them the same fractions

of time regardless of

indicator presence

below X X

Wells with indicator have

it same fractions of time

regardless of virus

presence

below X X

Indicator and virus

occurrence not related

to well’s hydrogeologic

sensitivity

below X X
Economic Analysis for the 4-72 October 2006

Final Ground Water Rule

About half of the impacts are “unknown,” meaning that they could lead to either over- or

under-estimates. Of those whose effect is under- or over-estimation, the two that seem most significant

are those for hit rate and concentration. Viral hit rates tend to be understated because virus recovery is

highly dependent upon the matrix and virus types and because the measurement methods fail to detect

many pathogenic viruses. Assuming zero viruses when none is detected leads to systematic

underestimation of average concentrations. Perhaps more important than these is the fact that the

occurrence model assumed no relationship between indicator occurrence and either a) the fraction of time

that virus is present in virally-contaminanted wells or b) the virus concentration levels that are realized

whenever virus is present. The only relationship modeled between indicator and virus is the fraction of

wells having both (P2) as compared to wells having only virus (P1) or only indicator (P3). It is likely that

wells containing E. coli and virus will have virus more often and at higher concentrations than in wells

containing only virus. Not modeling this relationship between E. coli and virus results in a significant

underestimate of benefits derived from the Rule’s indicator-based corrective action. 

 

 The occurrence models do not distinguish between sensitive and nonsensitive wells. The benefits

analysis assumes no difference between these with respect to virus and indicator hit rates. The effects of

this assumption on the cost and benefits estimates are unknown. If occurrence (hit rates and/or

concentration) in sensitive wells is greater, or if the virus-indicator relationship is stronger, then the

benefits of monitoring are probably underestimated. 
Economic Analysis for the 5-1 October 2006

Final Ground Water Rule 

5. Benefits Analysis

5.1 Introduction

The Ground Water Rule (GWR) reduces the public health risks of illness and death (morbidity

and mortality), by reducing public exposure to viral and bacterial pathogens present in ground water wells

due to intrusion of fecal matter. The health-related benefits of the GWR are due to reductions in both

endemic and outbreak risks and reductions in both acute and chronic illnesses. These health benefits and

non-health benefits are presented in Exhibit 5.1.

Exhibit 5.1 also presents a comparison of the subset of quantified benefits quantified in this EA

with the total (both quantified and nonquantified) GWR benefits. The quantified benefits are a small

subset of the total benefits because 1) of the many ground waterborne viruses avoided, only illnesses and

deaths from subsets of two types of viruses are quantified, 2) no quantified benefits accrue from avoided

acute and chronic bacterial illnesses and deaths, 3) only endemic illnesses and deaths avoided are

included in the analysis (epidemic illnesses and deaths are specifically excluded), 4) of these endemic

illnesses, only avoided acute illnesses and resulting deaths–from two types of viral illnesses!are

quantified, and 5) non-health related benefits are excluded.

Exhibit 5.1 Overview of Quantified and Nonquantified GWR Benefits

(continued on next page)

Benefit

Category

Total Benefits GWR EA Quantified Benefits

Health Benefits

Reduction in

endemic illness

incidence

• viral exposure risk reduction

(morbidity and mortality)

• bacterial exposure risk reduction

(morbidity and mortality)

• chronic sequelae reduction

• reduction in secondary

transmission of viral or bacterial

illness from symptomatic and

asymptomatic individuals

• acute rotavirus (Type A) illnesses

and deaths avoided

• acute enterovirus (Type B)

illnesses and deaths avoided

• subsets of viruses within Type A

and Type B categories and

bacterial illness and death not

quantified

• reduction in secondary

transmission of viral illness from

symptomatic individuals

Reduction in epidemic (outbreak)

illness incidence

• viral exposure risk reduction

(morbidity and mortality)

• bacterial exposure risk reduction

(morbidity and mortality)

• chronic sequelae reduction

• reduction in secondary

transmission of viral or bacterial

illness from symptomatic and

asymptomatic individuals

Not quantified
Benefit

Category

Total Benefits GWR EA Quantified Benefits

Economic Analysis for the 5-2 October 2006

Final Ground Water Rule 

Reduction in

treatment failures

• Decreased illness through

minimizing treatment failures or

fewer episodes with inadequate

treatment

Not quantified

Non-health Benefits

Outbreak

responses

avoided

• Avoided costs to affected water

systems, local governments

(provision of alternate water,

issuing warnings and alerts), and

community (decreased tourism due

to bad press). 

Not quantified

Avoided costs of

averting behavior

• reduced need or perceived need to

use bottled water, point-of-use

devices, etc. (includes time and

material costs)

• less time spent on averting

behavior: hauling/boiling water, etc.

Not quantified

Increased

confidence

• Perceived reduction in risk

associated with perceived

improvement in drinking water

quality

Not quantified

This chapter presents estimates of the GWR health-based benefits, including a discussion of

nonquantified benefits and provides estimates of the monetized value of the quantified avoided illnesses

and deaths. It describes the methodology of the risk assessment and benefits valuation that is outlined in

Exhibit 5.2. In addition, this chapter discusses health and nonhealth benefits of the GWR uncertainties and

sensitivities and presents a comparison of other regulatory alternatives considered. More detail on the risk

assessment for the GWR is presented in Appendices F and G.

5.1.1 Quantified Benefits

The quantified benefits include the avoided endemic acute illnesses (morbidity) and associated

deaths (mortality) each year from a subset of pathogenic viruses. The risk assessment is used to quantify

the number of baseline viral illnesses and deaths (i.e. those under current exposure conditions) and those

remaining after implementation of the GWR for the various regulatory alternatives. The differences

between the baseline estimates and those following implementation of the GWR are the avoided cases of

morbidity or mortality. EPA uses the estimates of avoided illness and deaths to establish the quantified

benefits of the GWR. Section 5.4 of this EA discusses the nonquantified benefits (both endemic and

epidemic), including chronic sequelae, for viruses and bacteria. The GWR total benefits include both the

quantified and nonquantified benefits, which are illustrated in Exhibit 5.1 above.

The risk assessment modeling requires a number of assumptions to be made regarding exposures

to viral pathogens in drinking water. An overview of the risk assessment methodology is presented in
Economic Analysis for the 5-3 October 2006

Final Ground Water Rule 

Lost Work 

Time

Reduced Morbidity Reduced Mortality

Medical

Costs 

Lost Work 

Productivity 

Lost Leisure 

Time

Cost of Illness Analysis Not Quantified: 

Qualitatively Discussed

Benefits Transfer of Value 

of Statistical Life from

Studies of Individuals’

WTP to Avoid Mortality

Risks

Risk of 

Premature

Death

Pain and

Discomfort

Risk Assessment

Endpoint

Effects

Considered

Valuation

Approach

1This schematic presents an overview of only the quantifiable benefits of the GWR. The nonquantified benefits are expected to 

comprise a significant portion of the overall benefits of the Rule and are presented in Section 5.4. 

Lost Work 

Time

Reduced Morbidity Reduced Mortality

Medical

Costs 

Lost Work 

Productivity 

Lost Leisure 

Time

Cost of Illness Analysis Not Quantified: 

Qualitatively Discussed

Benefits Transfer of Value 

of Statistical Life from

Studies of Individuals’

WTP to Avoid Mortality

Risks

Risk of 

Premature

Death

Pain and

Discomfort

Risk Assessment

Endpoint

Effects

Considered

Valuation

Approach

1This schematic presents an overview of only the quantifiable benefits of the GWR. The nonquantified benefits are expected to 

comprise a significant portion of the overall benefits of the Rule and are presented in Section 5.4. 

section 5.2.1. The hazard identification process is presented in section 5.2.2. The assumptions that are

required to assess pathogen exposures are presented in section 5.2.3. The dose response assessment is

presented in section 5.2.4. Baseline risk and the results of the risk reduction analysis (i.e., in terms of

illnesses and deaths avoided) are presented in section 5.2.5. 

The benefits valuation process applies monetary values to the results of the risk reduction analysis

to estimate the value of the illnesses and deaths avoided in exposed populations. The assumptions and

inputs used to determine the unit values of avoided illness and death are discussed in section 5.3.1 and

Appendix A of this EA. The results of this analysis, the monetized benefits of avoided morbidity and

mortality for the GWR, are presented in section 5.3.2 and the results for all regulatory alternatives

considered are compared in section 5.7. The monetized benefits are compared to the rule costs for the

GWR and all regulatory alternatives in Chapter 8 of this EA.

Exhibit 5.2 Overview of Viral Pathogen Risk Assessment and Benefits Valuation

Procedure for Quantified Benefits (Main Analysis)1
Economic Analysis for the 5-4 October 2006

Final Ground Water Rule 

5.1.2 Nonquantified Benefits

There are substantial benefits attributable to the GWR that are not quantified within this EA as part

of the main analyses because of data limitations. Nonquantified benefits due to etiological agents, disease

endpoints and exposure scenarios not considered in the main analysis are discussed in the nonquantified

benefits section (Section 5.4).

The monetized benefits from avoided acute illness due to many viral pathogens and all waterborne

bacterial pathogens are not quantified as a part of the main analysis. Chronic health effects associated with

viral and bacterial contamination are also not quantified. As discussed in section 5.4.2, the benefit of

avoiding these chronic cases may be significant, as affected individuals incur significant costs in medical

care and losses in productivity and quality of life in such instances. EPA considers these nonquantified

factors to be significant and a qualitative discussion of these nonquantified benefits is included in Section

5.4.

The natural history of infectious disease suggests that symptomatic and asymptomatic carriers can

infect other individuals by secondary transmission, either directly by physical contact and respiratory

droplets or indirectly via aerosols and contaminated surfaces. EPA estimates the number of secondary

cases arising from each primary case in the main analysis. Additionally, the nonquantified benefits section

(5.4) and Appendix E address this issue in a qualitative discussion supported by simulations of the

infectious disease process in large, susceptible (capable of being infected) populations.

In addition to the health-based benefits identified above, there are a number of nonhealth benefits

that also arise from promulgation of the rule. Other nonquantified benefits may result from overall system

improvements (e.g., upgrades to distribution systems, increased water treatment plant operational

efficiency and reliability, increased frequency/intensity of system surveillance), from improved risk

perception of drinking water quality, or from avoided outbreak response costs. While the value of these

nonhealth benefits are not quantified for this EA, these potential benefits are discussed qualitatively in

Section 5.4.

5.2 Quantified Health Benefits from Reduction in Exposure to Viruses

This section describes the risk assessment methods and assumptions used to quantify the baseline

health risks and the expected health benefits of the GWR. Quantified health benefits for a subset of

reduced pathogen exposure from the final GWR are derived from the risk assessment estimates of the preand post-GWR annual endemic acute illnesses and deaths attributable to ground water source

contamination. Annual endemic acute illnesses are those that occur as a result of drinking water

contaminated with waterborne pathogens occurring under normal operating conditions. The main analysis

addresses only viral acute illnesses and, specifically, those caused by rotavirus and enteroviruses. Other

illnesses resulting from other etiologic agents, disease endpoints, and exposure scenarios are addressed in

the nonquantified benefits section (Section 5.4).

The two viruses quantified in the main analysis (Type A virus represented by rotavirus data and

Type B virus represented by enterovirus data) were selected because human challenge study data are

available for both viruses and because they are suitable representatives of two broad classes of pathogenic

viruses (Ward et al., 1986 and Schiff et al., 1984).
1 For a more detailed description of the risk assessment process, see Appendix F.

Economic Analysis for the 5-5 October 2006

Final Ground Water Rule 

5.2.1 Overview of Risk Assessment Methodology1

Risk assessment is an analytical tool that can be used to characterize the expected incidence of

adverse health effects associated with exposure to an environmental hazard. For the GWR, the EPA has

developed a risk assessment model to estimate the baseline number of endemic acute illnesses and deaths

associated with ingesting a subset of pathogenic viruses present in public ground water systems (GWSs). 

The risk assessment uses a standard framework that is organized in accordance with EPA Policy for Risk

Characterization (USEPA 1995a), EPA’s Guidance for Risk Characterization (USEPA 1995b), and EPA’s

Policy for Use of Probabilistic Analysis in Risk Assessment (USEPA 1997b).

This standard framework requires the use of scientific data (or reasonable assumptions if data are

not available) to produce estimates of the nature, extent, and degree of a risk. Where there is uncertainty in

the data and assumptions used, that uncertainty is described and its impact on the risk estimates is

characterized. The risk assessment used in the GWR incorporates information on variability and

uncertainty associated with the data that characterize both the distribution of risk levels within the affected

population (variability) and the confidence bounds on key parameters of the risk assessment model

(uncertainty). Variability arises from true heterogenicity across people, places and time, and uncertainty

represents the lack of knowledge of the true value of the factor being considered (EPA 1997b).

According to the 1995 EPA Policy for Risk Characterization (USEPA 1995a), health risk

assessments for environmental contaminants generally involve four components:

• Hazard Identification addresses the nature of the potential adverse health effects associated

with exposure to the contaminant.

• Exposure Assessment addresses both the number of people in the population exposed to

the contaminant and the distribution of levels of exposure within that population.

• Dose Response Assessment addresses information concerning the relationships,

quantitatively where possible, between the magnitude of exposure to the contaminant and

the extent and severity of the adverse health effects that may occur.

• Risk Characterization combines the hazard identification, dose response, and exposure

assessment information to describe overall risk to the exposed population, both in terms of

the distribution of individual risk levels in the population and the total number of cases of

adverse effects anticipated.

Exhibit 5.3 depicts these major elements of the risk assessment for characterizing the risk of illness

(morbidity) and death (mortality) from exposure to viral pathogens in drinking water systems covered by

the GWR. Each of these four components is addressed specifically for the GWR risk assessment in

sections 5.2.2 through 5.2.5.
Economic Analysis for the 5-6 October 2006

Final Ground Water Rule 

Risk Characterization

•Estimated cases of viral illness and 

death in the affected population

•Distribution of individual risks

Hazard Identification

•Viral pathogen health endpoints:

Morbidity and Mortality

Dose-Response Assessment

Relationships for the probability of:

•Infection given exposure

•Illness given infection

•Death given illness

Exposure Assessment

•Number of people exposed to viral

pathogens in drinking water

•Distribution of average daily ingestion

levels across the exposed population

Risk Characterization

•Estimated cases of viral illness and 

death in the affected population

•Distribution of individual risks

Hazard Identification

•Viral pathogen health endpoints:

Morbidity and Mortality

Dose-Response Assessment

Relationships for the probability of:

•Infection given exposure

•Illness given infection

•Death given illness

Exposure Assessment

•Number of people exposed to viral

pathogens in drinking water

•Distribution of average daily ingestion

levels across the exposed population

Exhibit 5.3 Health Risk Assessment Framework

The GWR is expected to reduce the current incidence (baseline) of acute and chronic illness

caused by a wide variety of viral and bacterial pathogens associated with fecal contamination of ground

water. Although the quantified benefits risk assessment accounts for only some viral pathogens and only

some acute illnesses and deaths associated with these viral pathogens, different pathogens can cause

different types of illnesses, and pathogens differ in their virulence, the degree or ability to cause illness or

death. Medical research has not isolated all waterborne pathogens, nor has it thoroughly characterized the

virulence of all of the waterborne pathogens that have been identified. As detailed in Chapter 4, there are

two types of viruses found in water with data judged to be adequate for a risk assessment: Type A

(rotavirus) and Type B (enteroviruses). EPA has chosen to quantify these two types of viruses to represent

the range of waterborne viral pathogens for the GWR risk assessment. A more comprehensive range of

bacterial and viral pathogens addressed by the GWR is discussed in Section 5.4.

The GWR risk assessment is based on routine exposure to two representative virus types (Type A

represented by data on rotavirus and Type B represented by data on echovirus or enterovirus). As

discussed in Chapter 4, Section 4.3.2, the virus assay method used in all viral occurrence studies was

developed and optimized for recovery of poliovirus in water. Poliovirus is a member of the enterovirus

group and so the virus assay is also relatively efficient at recovering the enteroviruses other than poliovirus

with the prominent exception of some coxsackie A viruses, which are not recoverable. Other viruses,

including Type A and similar viruses such as rotavirus and hepatitis A virus are substantially less
Economic Analysis for the 5-7 October 2006

Final Ground Water Rule 

efficiently recovered. Thus, the viral occurrence data used in the risk assessment are based primarily on

enterovirus recovery. Based on EPA’s analyses of the occurrence data, enteric viruses such as Type B

viruses are intermittently present in a virus positive well each year for only short durations (generally from

a few days to a few weeks). EPA assumes that equal concentrations of Type A viruses are also present

when enteric viruses such as Type B are measured in wells during those short intervals of virus

contamination.

The first step of the risk assessment framework is to estimate the baseline (pre-GWR) number of

acute illnesses and deaths occurring from rotavirus (Type A viruses) and enteroviruses (Type B viruses). 

An analysis is then conducted for conditions reflecting changes resulting from the final GWR regulatory

requirements (as well as several other regulatory alternatives) to produce an estimate of the number of

illnesses and deaths remaining after implementation. The quantified health benefits of the GWR are then

obtained from the difference between the baseline and the results under the regulation (the estimated cases

of illness and deaths avoided as a result of the regulation).

5.2.2 Hazard Identification

This section presents summary information on the adverse health effects associated with ingesting

waterborne viral pathogens, including a discussion of the effects on sensitive subpopulations. The acute

and chronic health effects associated with bacterial pathogens are included in the nonquantified benefits

discussion (Section 5.4). 

5.2.2.1 Health Effects of Viral Infections

A review of the medical and epidemiological literature reveals that the extent of acute viral health

effects varies by severity and by population subgroup for each virus. As described previously in Chapter

4, the viruses of concern were categorized as Type A (represented by rotavirus) and Type B (represented

by enterovirus). The subsections below summarize the typical health effects of each virus type. 

Additional descriptions of the health effects of viral illnesses are presented in Chapter 2 and Section 5.4 of

the GWR EA.

Type A Viruses (rotavirus)

Generally, Type A viruses are highly infectious viruses that cause acute gastroenteritis, resulting in

symptoms that include watery diarrhea, fever, abdominal pain, and vomiting. Although they are highly

infectious, Type A viruses generally lead to mild, non-life-threatening acute illnesses. Common strain

rotaviruses typically affect young children, particularly those less than 3 years old, but other strains (G1,

G2 and G9) have been found to be common in adults and the elderly in nursing homes, and found to be

responsible for more severe illness in children (Griffin et al., 2000). As discussed further in Section 5.4,

most ground water-borne gasteroenteritis associated with viral exposure in the U.S. is believed to be the

result of norovirus, although rotavirus outbreaks are known (e.g. Gallay et al, 2006). Norovirus causes

gastroenteritis with vomiting in both adults and children. Due to data limitations, this EA only addresses

the disease burden related to a few strains of rotavirus, which rarely causes illness with debilitating

symptoms in adults and is not often accompanied by vomiting in either adults or children. Therefore, the

EA quantifies only one part of the total Type A virus risk.
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Final Ground Water Rule 

Type B Viruses (enteroviruses)

People of all ages may experience various adverse health conditions as a result of ingesting Type

B viruses. Type B viruses are less infectious than Type A but result in more severe illnesses than Type A

viruses. For this type of virus, acute illnesses are classified into three levels of severity:

• Illness that does not require medical attention (mild symptoms)

• Illness that requires a doctor visit

• Illness that requires hospitalization

Mild enteroviral illness include nonspecific febrile illness, respiratory illness, photophobia or

sensitivity, stiff neck, and gastrointestinal illness. Aseptic meningitis may or may not require a doctor’s

visit, but more severe illnesses such as viral encephalitis, myocarditis, and non-polio flaccid paralysis are

likely to require hospitalization. Most likely to be hospitalized are young infants (<3 months old) with

non-specific febrile illnesses that require treatment to rule out and expectantly treat serious bacterial

illness. Chronic illnesses such as diabetes and dilated cardiomyopathy more likely result from Type B

infection as compared with Type A (chronic illnesses are not quantified in this EA but are discussed in

Section 5.4).

5.2.2.2 Sensitive Subgroups

Although it is generally believed that most people are vulnerable to repeated infection by viruses

and other microorganisms during their lifetime, factors such as being very young, elderly, or

immunocompromised can affect the probability of illness given exposure, the severity of illness, and the

likelihood of a fatal outcome. Virus morbidity and mortality (see section 5.2.4 for further description of

these factors) incorporated in the GWR model include higher rates for some age groups, typically for

neonates (Type B viruses) and children (both Type A and Type B viruses). Some of these sensitive

populations are presented with their percentages of the United States population in Exhibit 5.4.
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Sensitive Population Individuals

% of US 

population1 Citation/Notes

Pregnant Women 6,240,000 2.2 Vital and Health Statistics, CDC (Ventura, 2000)

Neonates ( < 1 month) 2 317,137 0.1 US Bureau of the Census (2000)

Children ( < 5 years) 19,175,798 6.8 US Bureau of the Census (2000)

Elderly ( > 64 years) 34,991,753 12.4 US Bureau of the Census (2000)

Bone marrow transplant recipients 20,000 0.01

National Marrow Donor Program

http://www.marrow.org/MEDIA/facts_figures.pdf

AIDS patients 816,149 0.3

HIV/AIDS Surveillance Report, cases through 

2001 (CDC, 2002)

Organ Transplant Recipients 23,143 0.01

US Bureau of the Census, Stat Abs of US, based 

on 1998 data 2001b)

Compromised Immune Status

Age-based sensitive populations

Pregnant women and neonates

Exhibit 5.4 Sensitive Populations in the United States

1

U.S. Census estimtate July 2000.

2 Reflects the estimated number of newborns age <1 month (1/12 of the 2000 census population for age < 1 year).

The Very Young

The very young [e.g., infants (neonates) less than one month old] are considered to be more likely

to develop severe illness and death from gastroenteritis and other waterborne viral and bacterial infections

than the general population. Most vertical transmission between mother and infant occurs during and after

childbirth. Viral gastroenteritis, caused mainly by Type A viruses, is prevalent among U.S. children. The

Agency’s document, “Health Risks of Enteric Viral Infections in Children” provides a comprehensive

review of viruses that pose adverse health implications for children (USEPA, 2000g). Primary food or

waterborne exposure followed by secondary transmission via the fecal-oral route contributes to high rates

of illness in group settings where care is provided for children that wear diapers such as day-care centers. 

The Centers for Disease Control and Prevention (CDC) has determined that the incidence of rotavirus

diarrhea can reach 0.30 episodes/child/year by age two, with a cumulative incidence approaching 0.80

episodes/child by age five (Glass et al., 1996). Hospitalizations for rotavirus diarrhea are most common in

children 6 months to 3 years of age (Parashar et al., 1998), while self-limiting norovirus infections are

prevalent in school-age children (LeBaron et al., 1990). Although deaths from infectious diarrhea have

generally declined among U.S. children since 1965 because of re-hydration therapy, newborn children,

especially infants born prematurely, remain at risk of death from severe diarrheal illness (Kilgore et al.,

1995).

In addition, some viral pathogens such as coxsackie B virus (a Type B enterovirus) can be

transmitted transplacentally from an infected mother to her child in utero, during birth, or shortly

thereafter. This type of transmission places the infected newborn infant at risk of severe symptomatic

illness from meningitis or myocarditis, for which the case fatality rates are high (Gerba et al., 1996a).
Economic Analysis for the 5-10 October 2006

Final Ground Water Rule 

The Elderly

The elderly (individuals over 65 years of age) are also at greater risk than the general population of

experiencing severe health effects from rotavirus diarrhea, hepatitis, and other viral infections. Sensitivity

among individuals in this age group is due to declining immunity and poorer general health (Gerba et al.,

1996a and Lew et al., 1991). Conditions such as cardiovascular disease make the elderly more susceptible

to complications of diarrhea such as electrolyte imbalance, dehydration, and shock (Maasdam and Anuras

1981). More than half of the diarrheal deaths that occur in the United States are among persons older than

74 years of age, and the risk of death from diarrhea is generally higher among elderly persons confined to

nursing homes and other care facilities (Lew et al., 1991; Gerba et al., 1996b).

In this EA, due to limited data the morbidity and mortality factors assigned to the elderly for Type

A and B virus infections are the same as those used for the general population. These factors

underestimate the risks for elderly individuals. The EPA believes there are insufficient data available to

assign higher morbidity or mortality rates from waterborne viral infections.

The Immunocompromised

Immunocompromised and immunosuppressed persons comprise a population subgroup who are

more susceptible to viral and bacterial infections and are more sensitive to serious health effects from

them. More specifically, Acquired Immunodeficiency Syndrome (AIDS) patients (e.g. Morpeth and

Thielman, 2006), organ transplant patients, and persons undergoing bone marrow transplantation are

considered sensitive to viruses based on compromised immune status. These immunocompromised groups

constitute approximately 0.3 percent of the general population. This estimate is based on best available

data and assumptions as summarized in Exhibit 5.4. The estimate does not include other groups of

immunocompromised people, including those with chronic illness or those cancer patients who are

undergoing chemotherapy and radiation (Morris and Potter, 1997). The population estimate also does not

account for the estimated 25,000 to 50,000 persons in the U.S. with primary immunodeficiency diseases

that primarily affect B-lymphocyte cell function. The most common and serious primary immune diseases

are X-linked Agammaglobulinemia (NICHD, 1999; Gerwurz et al., 1985; McKinney et al., 1987; Hertal et

al., 1989). In addition, the population estimate does not include persons with potentially autoimmune

diseases (e.g. type 1 diabetes, myocarditis, multiple sclerosis and rheumatoid arthritis) who may also

experience more serious adverse health effects brought on by viral and other infections (Fujinami, 2006).

A limited number of available studies suggest that viral infections can contribute to deaths in

immunocompromised persons. Chronic diarrhea is a serious complication of AIDS, and rotavirus and

adenovirus are commonly isolated from stool samples from AIDS patients with diarrhea (Gerba et al.,

1996a). Enteric rotavirus and coxsackievirus infections were reported as the cause of death among bonemarrow transplant patients (Yolken et al., 1982).

In this EA, the morbidity and mortality factors assigned to immunocompromised subgroups for

Type A and B virus infections are the same as those used for the general population. These factors

underestimate risks for these subgroups, but the EPA believes that there are insufficient data available to

assign higher morbidity or mortality rates from waterborne infections based on immune status. However,

because there is a higher cost-of-illness among severely immunocompromised persons having lengthy viral

illnesses, the reductions in numbers of illnesses and deaths attributable to the GWR in this subgroup are

calculated separately by the risk model and valued separately in the monetary benefits calculations.
2

 The risk assessment also considers exposure via secondary spread from those who become ill through

drinking water. This is addressed in section 5.2.4.

Economic Analysis for the 5-11 October 2006

Final Ground Water Rule 

5.2.3 Exposure Assessment

This section discusses the key elements for characterizing human exposure to viral pathogens in

drinking water. The primary exposure pathway is ingestion of drinking water from public ground water

supplies that are contaminated with viruses from fecal pollution.2

 EPA believes that there are three key

exposure scenarios or events whereby virus-contaminated drinking water is delivered to consumers in

public GWSs.

1) Source water contamination under normal operating conditions

2) Source water contamination due to treatment failures

3) Contamination due to distribution system deficiencies

The remainder of this discussion of the main exposure assessment for the GWR addresses only the

first contamination scenario due to data availability. EPA’s modeling of this first scenario includes

exposure from both systems that serve untreated ground water and systems with low levels of viral

inactivation.

With regard to the other scenarios, there is insufficient information on the frequency and severity

of drinking water treatment failures and distribution system deficiencies in ground water public water

systems (PWSs) to directly model these events. However, the proportions of reported outbreaks caused by

the three contamination scenarios listed above serve as an indicator of the relative frequency of GWS

contamination events that cause disease in exposed populations (see Section 5.4.7 and 5.4.8 for further

discussion).

The assessment of exposures to pathogens from ground water sources requires that the following

factors be quantified:

• Occurrence (presence/absence) of pathogens in source water (including duration of time

that it is present)

• Concentration of pathogens in source water when it is contaminated

• Level of pathogen inactivation in the system and resulting pathogen concentration in tap

water

• Size of the exposed population, including sensitive subgroups

• Volume of water ingested daily and how many days per year it is ingested

EPA evaluated available occurrence and exposure data and developed assumptions where needed

regarding these exposure factors, each of which is discussed briefly below.
3

 The infectious viruses counted in the occurrence studies represent a group of enteric viruses that are

favored for recovery because they are most efficient at infecting the host cell line used in the concentration

measurements. Poliovirus is most favored but other closely-related Type B enteroviruses (including echovirus) are

also likely to be recovered. Rotaviruses are also likely to be present because they are shed in fecal material at

concentrations several orders of magnitude greater than the enteroviruses. However, rotavirus is not efficiently

recovered in that commonly used host cell line and other Type A viruses, such as norovirus, are not recoverable.

Economic Analysis for the 5-12 October 2006

Final Ground Water Rule 

5.2.3.1 Source Water Viral Occurrence and Concentration

Virus occurrence values for this exposure assessment are based on occurrence data from 12 studies

of U.S. ground water source quality. Presence/absence of enteroviruses were directly measured in 12

studies using methods optimal for recovering enteroviruses but not other viruses.3

 Viral concentrations are

based on three of the 12 studies that included concentration data (Lieberman et al, 2002; Abbaszadegan et

al, 2003; Lindsey et al., 2003). EPA’s risk model applies a randomly chosen concentration from the data

in these three studies. However, concentration data from the Lieberman data set is only applied to a small

subset (2.5% on average) of wells with predicted viral presence, whereas the concentration data from the

Abbaszadegan and Lindsey data sets are applied to all other wells (97.5% on average) with predicted viral

presence (see section 4.3.4.2 for further discussion). More detailed descriptions of each study are

presented in section 4.3.2 and in the Ground Water Rule Occurrence and Monitoring Document (USEPA,

2006b).

Modeling of the available virus occurrence data predicts that enteric viruses such as Type B

viruses are intermittently present in a virus positive well each year for only short durations (generally from

a few days to a few weeks). EPA assumes that equal concentrations of Type A viruses are also present

when enteric viruses such as Type B are measured in wells during those short intervals of virus

contamination. The probability that a well or sample is virus contaminated is unchanged by this

assumption.

EPA recognizes that Type A virus concentration assumed present in wells could be either an

underestimate or an overestimate. The assumption could be an underestimate if Type A viruses are present

at higher concentrations or if they contaminate wells for longer intervals than assumed because they may

be more prevalent in the human population and may be shed at much higher concentrations than Type B

viruses. The assumption could be an overestimate if the prevalence of Type A viruses in human

populations is less than the Type B viruses.

EPA considered using other assumptions about Type A occurrence but identified problems with

each. EPA considered randomly assigning Type A or Type B to the randomly chosen viruses

concentrations or assigning a fixed percentage to the number wells that are assumed to exhibit Type A

virus concentrations. However, these assumptions would contradict available data by assigning Type A

virus character to samples that are measured using methods that are favorable for recovering Type B

viruses.

5.2.3.2 Finished Water Concentrations in Disinfecting Ground Water Systems

For the purposes of this exposure assessment, EPA assumed that the pathogen concentration in tap

water from GWSs that serve untreated ground water is the same as the pathogen concentration in source
Economic Analysis for the 5-13 October 2006

Final Ground Water Rule 

water. In contrast, properly operating disinfecting systems are assumed to inactivate 99 percent (2-log), or

99.99 percent (4-log) of viral pathogens depending on the disinfection practices employed. Therefore, the

concentration of pathogens in tap water from properly operating disinfecting (4-log inactivation) systems

is assumed to be 0.01 percent of the concentration in source water. For 2-log inactivation, the

concentration is assumed to be 1.0 percent of the concentration in source water. These finished water viral

concentration estimates do not take into account the effects of elevated concentrations from any upsets or

treatment failures that might occur.

5.2.3.3 Size of Exposed Population

As presented in section 4.2.3 and in Exhibit 4.4, ground water CWSs serve over 100 million

people, while ground water NCWSs serve about 14 million people. This population has the potential to be

exposed to pathogens via drinking water from GWSs.

5.2.3.4 Drinking Water Consumption Factors

The amount of drinking water consumed daily by individuals is a key input to the exposure

assessment component of the risk analyses. The higher the average daily consumption of water by an

individual, the higher the risk of infection for a given level of pathogen occurrence. EPA bases its

estimates of per-capita water ingestion on data collected by the U.S. Department of Agriculture’s (USDA)

1994-96 Continuing Survey of Food Intakes by Individuals (CSFII). Data derived from this survey are

presented in the report, “Estimated Per Capita Water Ingestion in the United States” (USEPA 2000c). For

noncommunity water systems, which represent a significant number of the systems potentially impacted by

the GWR and where individuals consume water for shorter periods, EPA further adjusted the USDA

estimates to better reflect drinking water patterns at those systems. These adjustments were based on the

classifications of noncommunity water systems from the EPA report, Geometries and Characteristics of

Public Water Systems (USEPA, 2000a) and EPA estimates of daily ingestion in these systems.

The EPA water ingestion study used to estimate water consumption reports information for two

different aggregations of the population: all respondents (which is used in this exposure assessment) and

the subset who report consuming water directly (“consumers”). The category of all respondents is more

appropriate to this exposure assessment as EPA assumes that all people consume or are exposed to tap

water, even if they reported no tap water consumption during the three day diary period of the CSFII

survey. This is because even people who report no direct consumption may consume some public water at

other times during the year. Furthermore, they still do ingest water indirectly (for example, through

washing vegetables and other foods, and consuming foods prepared in restaurants) or are otherwise

exposed to potential waterborne viruses in tap water (during showers and brushing teeth, for example). 

Exhibit 5.5 summarizes the CSFII data for consumption of water from all sources.
Economic Analysis for the 5-14 October 2006

Final Ground Water Rule 

Exhibit 5.5 Distribution of Individual Daily Drinking Water Consumptionby Age

Group (L/person/day)

Age

(years) Mean

Percentiles

p1 p5 p10 p25 p50 p75 p90 p95 p99

<0.5 0.409 - - - 0.002 0.394 0.696 0.903 0.969 1.307

0.5-0.9 0.569 - 0.03 0.86 0.248 0.548 0.771 1.126 1.272 1.671

1-3 0.417 0.001 0.046 0.09 0.196 0.346 0.580 0.805 0.993 1.393

4-6 0.544 0.004 0.087 0.147 0.276 0.462 0.719 1.017 1.267 2.026

7-10 0.604 0.006 0.115 0.174 0.305 0.512 0.808 1.130 1.422 2.170

11-14 0.811 0.01 0.119 0.209 0.382 0.643 1.066 1.623 1.960 3.025

15-19 0.990 - 0.108 0.231 0.407 0.768 1.276 1.891 2.387 4.020

20-24 1.271 0.001 0.117 0.237 0.554 1.000 1.577 2.506 3.608 5.796

25-54 1.480 0.041 0.301 0.473 0.798 1.272 1.893 2.631 3.333 5.244

55-64 1.529 0.118 0.473 0.652 0.946 1.378 1.952 2.557 2.997 4.393

65+ 1.451 0.245 0.531 0.651 0.935 1.344 1.832 2.323 2.708 3.747

All ages 1.232 0.009 0.163 0.283 0.573 1.037 1.633 2.341 2.908 4.805

 Source: “All Sources” from USEPA 2000c. Includes bottled water and tap water; see text describing the

adjustment made to account for bottled water consumption.

The survey also reports information by type of source water (community water, bottled water,

other sources, and non-reported source). The survey questions categorized respondents based on their

reported “main” source of direct water and indirect water. Thus, many respondents who reported that their

main source of drinking water was bottled water or another source, may still consume water from

community sources at least some of the time. Likewise, respondents who categorize their drinking water

as being mainly from a community source may also consume bottled water and water from other sources.

More importantly, those who are not now served by community water systems would report “other

sources” or bottled water as their main source of water. These groups are presented as components of the

national average and cannot be subtracted from the total without affecting the value of the national

average. Thus, the consumption of those who reported no source or “other sources” as their main source

of drinking water are included in the national average, because subtracting these categories would lead to

an underestimate of average consumption levels. Their consumption patterns are assumed to be similar to

those served only by community systems (or at least, cannot be adjusted using the available data). 
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Final Ground Water Rule 

Therefore, there were no adjustments for those who reported no source or other sources as their main

source of water. 

The consumption of bottled water, however, is thought to reflect a replacement of tap water, and

thus an adjustment for this is more appropriate. Further, there is evidence that consumption of bottled

water is significant. In the CSFII study, 13.4 percent of all water was consumed by those who categorized

bottled water as their “main” source of water for direct or indirect ingestion. The implicit assumption is

that the distribution of consumption for bottled water drinkers is proportionally about the same as for all

individuals. EPA believes the closest approximation of the distribution of consumption for the GWR is the

distribution for “All Sources Less Bottled Water” (13.4 percent). Because the survey did not attempt to

determine for each individual the proportion of water from each source, the approach used in the exposure

assessment (i.e., applying the 13.4 percent reduction to all mean values) may understate or overstate actual

consumption from public water systems, depending on the extent and direction of overlap in drinking

water sources. EPA believes however, that making this adjustment produces an estimate of drinking water

consumption closer to actual practices. In the EA model, EPA used the mean values for each size category

in Exhibit 5.5, adjusted downward by 13.4 percent. EPA used this approach rather than considering the

percentile distribution because this gives similar estimates and reduces modeling complexity.

To better estimate the daily drinking water consumption patterns for the populations served by

noncommunity GWSs, which reflect a significant number of systems potentially impacted by the GWR,

EPA further adjusted its estimates of daily consumption. Adjustments were made based on the system

classification (non-transient or transient) and the area served (i.e. campgrounds, restaurants, etc).

Nontransient noncommunity water systems, by definition, serve the same population each day and

many of these system are businesses where employees spend their work day. Based on this definition,

EPA assumes that populations are served by these systems for 8 eight hours of each day and then return

home to be served by a CWS. For the purposes of estimating exposure, EPA assumes that populations

served by NTNCWs consume 50 percent of the mean daily consumption levels (first reduced by 13.4

percent) from Exhibit 5.5 for each population category.

For transient noncommunity GWSs, EPA estimated daily consumption for the 25 types of transient

noncommunity GWSs, that serve the largest transient populations. EPA used Best Professional Judgement

to estimate daily consumption in each of these 25 system types and weighted these consumption levels by

the populations served by these systems. This weighting captures the influence of the significant

differences in populations served by different types of systems. To estimate exposure in all transient non

community GWSs, EPA used the average of all 25 weighted daily consumption estimates. As with the

NTNCWS adjustment described above, the average TNCWS consumption factor of 0.4 is applied to the

mean daily consumption levels (first reduced by 13.4 percent) from Exhibit 5.5. Details of this analysis

are presented in Exhibit 5.6 below.
Economic Analysis for the 5-16 October 2006

Final Ground Water Rule 

A B C = A * B C / Total Population

Restaurants 0.3 2,255,959 676,788 0.0669

Churches 0.25 1,301,552 325,388 0.0322

State Parks 0.5 842,518 421,259 0.0416

Wholesalers 0.5 791,429 395,715 0.0391

Summer Camps 1 765,742 765,742 0.0757

Campgrounds 0.5 639,160 319,580 0.0316

Hotels/Motels 0.5 558,443 279,222 0.0276

Highway Rest Areas 0.25 516,369 129,092 0.0128

Misc. Recreational Services 0.5 337,152 168,576 0.0167

Service Stations 0.25 326,644 81,661 0.0081

Golf & Country Clubs 1 254,016 254,016 0.0251

Mixed Service Areas 0.5 214,345 107,173 0.0106

Medical Facilities 0.25 208,623 52,156 0.0052

Office Parks 0.5 197,600 98,800 0.0098

Retailers - Non-Food Related 0.25 184,128 46,032 0.0045

Manufacturing: Food 0.5 158,301 79,151 0.0078

Schools 0.5 150,365 75,183 0.0074

Retailers - Food Related 0.25 142,988 35,747 0.0035

Federal Parks 0.5 93,665 46,833 0.0046

Amusement Parks 1 88,038 88,038 0.0087

Mobile Home Parks 1 66,797 66,797 0.0066

Day Care Centers 0.5 10,213 5,107 0.0005

Manufacturing: Misc. 0.5 8,991 4,496 0.0004

Non-water utilities 0.5 6,025 3,013 0.0003

Total N/A 10,119,063 4,525,560 0.4

Daily 

Consumption * 

Total Poulation

Weighted Daily 

Consumption

% Daily 

Consumption 

Relative to CWS TNCWS Type

Total Population 

Among All 

TNCWSs Within 

Type

Exhibit 5.6 Derivation of Transient Noncommunity Water System Consumption

Factor

Sources: [A] Geometries and Characteristics of Public Water Systems (USEPA, 2000a).

[B] EPA Estimate.

In addition to daily consumption, EPA estimated the number of days per year tap water is

consumed by users of different types of water systems. EPA’s estimates for exposure days are presented

in Exhibit 5.7. For the TNCWSs, it is assumed that the average number of days of exposure per year for

each individual consuming water at one of these systems is 10. To account for all of the individuals who

are expected to be consume water at a TNCWS over the course of a year, an adjustment was made to the

population reported in SDWIS for these systems. The population for TNCWS reported in SDWIS is

intended to reflect the population served during the peak month of operation. Assuming 30 days in the

peak month, and an average of 10 days of exposure for each individual at a TNCWS, the total number of

different individuals exposed per month at each TNCWS is assumed to be 3 times the reported SDWIS

population number (that is, the peak month serves 3 cohorts of 10 days each). Further, it is assumed that

TNCWSs are open on average of 6 months per year, with an uncertainty range of 3 months to 9 months. 

(This number of months of operation for TNCWS is included in the risk model as a triangular distribution

with minimum = 3, mode = 6 and maximum = 9 months.) Therefore, for TNCWSs, the risk model

assumes 10 days of exposure for each individual and a total population exposed ranging from 9 to 27 times
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Final Ground Water Rule 

the peak month population served reported in SDWIS (i.e., 3 cohorts / month * 3 months (=9) to 3 cohorts/

month * 9 months (=27). Since the SDWIS population values reflect the peak month of operation, the

total population served by TNCWS for their duration of operation as determined here should be considered

a likely overestimate.

Exhibit 5.7 Estimated Exposure Days by System Type1

Type of System Exposure Days Per Year

CWS 350

NTNCWS 250

TNCWS 10

1 Number of days in which tap water is consumed per individual in each system 

type. See text for additional discussion pertaining to the TNCWS exposure.

5.2.4 Probability of Infection, Illness, and Mortality

This section presents information on the relationship between ingestion of viruses and the

probability of infection, illness, and mortality. Specific elements of the dose response relationships

addressed in this section include the following:

• Infectivity (the ability of a microorganism to colonize in the body of the host, expressed as

probability of infection, a function of dose)

• Morbidity (the probability of illness given infection)

• Secondary Spread (the expected additional illnesses due to contact with those affected

directly by ground water consumption)

• Mortality (the probability of death given illness)

5.2.4.1 Infectivity from Dose response Modeling of Human Challenge Study Data

All of the elements listed above depend on high quality infectivity data and an appropriate

dose-response model. Two key publications report high quality human challenge study data suitable for

dose-response modeling. One, by Ward et al (1986), reports dose-response data for rotavirus, which

represents Type A viruses. The other, by Schiff et al (1984), reports dose-response data for echovirus type

12, which represents Type B viruses. The summary data from the two studies, shown in Exhibits 5.8 and

5.9, are simple, but their use in dose-response modeling involves a number of key decisions or

assumptions that are discussed below.

Microbial risk assessment requires an estimate of the dose required to cause infection in humans. 

These data can be prospectively determined directly by dosing volunteers, indirectly by dosing animals, or

can be retrospectively estimated using outbreak data. The highest quality data are acquired from dosing

human volunteers. However, human volunteer data are necessarily biased for ethical reasons. All studies
Economic Analysis for the 5-18 October 2006

Final Ground Water Rule 

with human participants must be approved by an ethical review board. Limitations in pathogen human

feeding studies include using only low virulence pathogens (not necessarily representative of the virulence

encountered in nature) and studying only healthy populations (whose response to the experiment is not

indicative of that of sensitive subpopulations). For example, the echovirus type 12 strain used in the

human challenge study by Schiff (1984) was a benign strain not associated with serious human illness. In

fact the strain was originally recovered from a child with a clinical diagnosis of erythema infectiosum

(fifth disease), a mild facial rash. 

Human challenge study data are also available for poliovirus (and for aerosol exposure to

coxsackievirus [Couch, 1970]), which together with echovirus, comprises the enteroviruses which are one

of the target viruses for determining GWR benefits. Three poliovirus challenges studies were conducted,

all using infants. Two studies used poliovirus I (Minor et al., 1981; Lepow et al., 1962) and one study

used poliovirus III (Katz and Plotkin, 1967).

EPA considered using data from all four enterovirus human challenge studies to represent the

Type B enterovirus dose response. (EPA did not think it appropriate to use the coxsackievirus dose

response data because of the route of exposure.) All the poliovirus challenge study data are from infants

who, unlike adults exposed to Echovirus type 12, exhibit lifetime immunity after infection. Even among

identical strains, there are potential virulence differences between laboratory-maintained isolates and

isolates recovered in human or environmental samples. Because poliovirus is no longer a health issue in

the U.S. and because of differences among the challenge studies, EPA decided to use only the echovirus 12

data. However, EPA believes that a meta-analysis of all the enterovirus human challenge study data would

document that the enteroviruses are more infectious than is predicted by the echovirus 12 human challenge

study data. EPA believes that the echovirus 12 data substantially underestimates the infectivity of the

enteroviruses. The GWR EA would predict more enteroviral infections, illnesses and deaths if other

enterovirus human challenge study data were considered.

The rotavirus human challenge study by Ward et al (1986) is the only published Type A human

challenge study data. The rotavirus challenge study was conducted using the CJN strain which was

recovered from an infected infant. The CJN strain is now classified as a Group A rotavirus and is among

the most common strains currently identified in the United States. The proportion of adult volunteers

infected by the CJN rotavirus strain at a dose of 1000 FFU in Ward et al (1986) was confirmed in a later

challenge study (13 of 14 adults infected in Ward et al, 1991). Thus, unlike the echovirus data, EPA

believes that the rotavirus human challenge study data are representative of the rotaviruses. However, the

infectivities of other Type A viruses, such as norovirus, are not necessarily represented by the rotavirus

human challenge study data. Funded under an EPA cooperative agreement, Moe et al. (2001) reported on

human challenge studies using Norwalk virus (now known as norovirus). They conclude that norovirus “is

one of the most infectious agents that has ever been described.” Infection was observed at doses below

one PCR dectectable unit (which represents as few as one physical virus particle) (Moe et al, 2001). 

Although the norovirus human challenge study data are not yet published, EPA believes that the

noroviruses are at least as infectious as the rotavirus, and likely more infectious. If the norovirus data were

made available to EPA, EPA would use the norovirus rather than rotavirus human challenge study data to

characterize Type A viruses, because norovirus disease affects all populations equally. Epidemiological

data suggests that other Type A viruses such as hepatitis A virus, adenovirus and astrovirus are also highly

infectious and could be more infectious than the rotaviruses. Thus, EPA believes that the rotavirus human

challenge study data, while representative of the rotaviruses, may underestimate the infectivity of the Type

A viruses. If so, then the GWR EA under-predicts Type A infections, illnesses and deaths.
Economic Analysis for the 5-19 October 2006

Final Ground Water Rule 

Exhibit 5.8 Rotavirus Dose-Response Data

Exhibit 5.9 Echovirus Dose-Response Data

Rotavirus Dose-Response Modeling

The human feeding study data shown in Exhibit 5.8 cover a wide dose range (0.009 to 90,000

units). Ground water concentrations are expected to be similar to those found for echovirus, that is,

generally less than 2 per 100 liters. If contamination is intermittent, such that it is present about 1% of the

time, then the average concentration would be 0.02 per 100 liters or 0.0002 per liter. A person ingesting

one liter per day would receive a dose of 0.0002 infectious units, which is considerably smaller than the

smallest dose used in the human feeding study. Predicting risks for such low doses requires extrapolation,

using a biologically-plausible dose-response model.

The World Health Organization (WHO, 2003) has considered the issue of low-dose modeling /

extrapolation, and recommends using models that have the following characteristics: absence of a

threshold and independent action among infectious units, i.e., absence of synergistic action. Based on

these factors, WHO (2003) identified a family of acceptable models and these included the Beta-Poisson

and exponential models, while excluding the Probit model.

Dose (Poisson), 

focus-forming units 

(ffu)

Subjects 

receiving 

Dose

Subjects 

Infected

0.009 7 0

0.09 7 0

0.9 7 1

9 11 8

90 7 6

900 8 7

9,000 7 5

90,000 3 3

Dose (Poisson), 

plaque-forming 

units (pfu)

Subjects 

receiving 

Dose

Subjects 

Infected

330 50 15

1000 20 9

3300 26 19

10000 12 12

33000 4 2

330000 3 2
Economic Analysis for the 5-20 October 2006

Final Ground Water Rule 

Ward, et al. used data collected at the dose range 0.009 to 90,000 ffu to estimate parameters of a

probit model. Other authors, notably Teunis and Havelaar, use these same data, but with a beta-Poisson

model (Teunis et al. 1996). These two models (probit and beta-Poisson) predict similar infection

probabilities across the range of doses employed in the study. As discussed above, EPA does not believe

that the probit model’s predictions outside of the dose range of the study are biologically plausible. For

this reason, EPA has selected the beta-Poisson model for rotavirus dose-response modeling. In the main

analysis (reported in this section), all of the data shown in Exhibit 5.8 are used to inform the beta-Poisson

model.

Arguably, the most significant dose in terms of environmental exposure is that nearest 1 ffu: 0.9. 

One of seven subjects was infected at that dose. Given the beta-Poisson model, and data at all of the

higher doses, this outcome at dose 0.9 ffu is not surprising, i.e. at order of magnitude or greater doses most

subjects were infected and at order of magnitude or lower doses no subjects were infected. However,

since most exposures to populations receiving contaminated ground water occur near one viral infectious

unit, there is a question as to the usefulness of other dose response data being used well outside this range

for estimating infection probability at this dose level. The smallest dose, 0.009 ffu, is smaller than 0.9 ffu

by a factor of 100. The greatest dose, 90,000 ffu, is greater by a factor of 100,000. To address this

concern about the influence of extreme dose data, EPA has estimated the parameter of an exponential

model using only the fact that one of seven subjects was infected at dose 0.9. This alternative or

sensitivity analysis is described in Appendix F. 

EPA recognizes that there is significant uncertainty associated with measuring viruses in

environmental samples and has summarized that uncertainty in Chapter 4, Section 4.3.2. Virus

aggregation in routine environmental exposure is especially difficult to quantify, so there is considerable

uncertainty associated with the assumption above that most ground water consumers are getting a virus

dose of about one ffu. Virus occurrence and concentration is measured in the laboratory after the sample is

manipulated to disaggregate virus clusters by changing the ground water ionic strength. After

disaggregation, the highest measured virus concentration in any ground water sample (Exhibit 4.28) is 2.12

PFU (or MPN) per liter. Clusters may exist in routine ground water exposure (in aquifers where ionic

strength is relatively stable) and ground water consumers may get doses higher than one FFU on occasion

as a result.

Echovirus Dose-Response Modeling

The echovirus data shown in Exhibit 5.9 cover a narrower relative range than rotavirus (from 330

to 330,000 pfu), but all doses are significantly greater than the environmentally-relevant dose of 1 pfu. 

Using any dose-response models with these data to predict environmental risks involves extrapolation and

the potential to over- or underestimate the low-dose risk. 

 Before discussing the modeling, it is important to understand how the data in Exhibit 5.9 were

derived. Schiff et al. described how their data were generated in two phases. In the first, a “range-finding”

phase, small numbers of subjects were dosed at each level over a wide range. Three or four subjects were

dosed at each of some number of levels between 330 and 330,000 pfu. Exhibit 5.9 only shows that four

subjects received dose 33,000 and three subjects received dose 330,000. In the second phase, numerous

additional subjects were challenged with doses in the 330 to 10,000 pfu range (for these doses, Exhibit 5.9

includes subjects from both phases). 
Economic Analysis for the 5-21 October 2006

Final Ground Water Rule 

EPA considered two published echovirus dose-response analyses: that of the original researchers,

Schiff et al. (1984), and that of Teunis and Havelaar (Teunis et al., 1996). In their dose response analysis,

Schiff et al. discarded the data from doses 33,000 and 330,000 and used the remaining data to estimate

parameters of a probit model. Teunis and Havelaar utilized all of the echovirus dose-response data

(including 33,000 and 330,000) and fit a beta-Poisson model. After assessing the published analyses, EPA

decided to use the full data set with the beta-Poisson model in the main analysis and the partial data set

with the exponential model as a sensitivity analysis.

EPA based its analysis of the full data set on the analysis of Teunis and Havelaar (Teunis et al.,

1996). An important feature of this model is its ability to explain variable susceptibility; the notion that

human subjects may differ. Technically, this model acts as though each subject has his/her own

exponential dose-response parameter (probability of infection, given exactly one infectious unit) and that

these parameters are beta-distributed. EPA decided to employ the beta-Poisson model in its analysis of the

full data set.

For the analysis of the low-dose echovirus data, EPA examined the Schiff analysis (Schiff et al.,

1984). Although Schiff used a probit model, EPA discovered it behaves implausibly when extrapolating to

estimate the risk of environmental exposures. Theoretically, risk at low doses should be approximately

proportional to probability of ingesting an infectious unit, but in this application, the probit model predicts

extreme sublinear behavior. In contrast, the simple exponential and beta-Poisson models (which is a

derivation of the simple exponential) both feature approximate low dose linearity. When applied to the

data below dose 33,000, the exponential model fits very well. The extra parameter provided in the

beta-Poisson model doesn't seem to add significantly to the goodness-of-fit (or likelihood), so EPA

decided to employ the exponential model in its analysis of the low-dose echovirus data.

Two reasonable options are therefore available for echovirus modeling: utilizing the partial data

set with an exponential model and utilizing the full data set with the beta-Poisson model. As detailed in

Appendix F, these two analyses produce considerably different predictions of low-dose risk for echovirus. 

Taken together, the results demonstrate considerable model uncertainty.

5.2.4.2 Morbidity and Mortality Data Sources and Uncertainty

EPA based its analysis of morbidity and mortality on epidemiologic data published in the scientific

literature. The literature includes epidemic (outbreak) and endemic disease studies conducted using a

variety of epidemiological methods, both prospective and retrospective. Some study cohorts represented

the entire U.S. population, other cohorts represented selected sub-populations. The studies used in the EA

include data based on person-to-person spread, foodborne exposures, and waterborne exposures, as well as

those for which no source of viral exposure or transmission mode was identified. Due to the limited

number of published studies on water as a primary route of exposure, viral morbidity and mortality rates

incorporate information derived from all routes of exposure and transmission. EPA used to the extent

possible, prospective, endemic data of study cohorts that represent the entire U.S. population. Prospective

studies are assumed to have less reporting bias than retrospective studies (only those who got ill are likely

to have a reason to report their exposure and the likelihood of reporting increases with illness severity). 

Where such data were not available, EPA used retrospective endemic disease studies of the entire

population. At times, general population study data were not available and so EPA used prospective (and

retrospective, as necessary) studies of sub-populations and applied these values to the general population,

but noted the associated uncertainty or bias. This EA describes the data source, the type of study, the
Economic Analysis for the 5-22 October 2006

Final Ground Water Rule 

population cohort studied and the assumptions and limitations associated with epidemiological data that, at

times, were not optimal.

Morbidity rates are based, to the extent possible, on prospective epidemiological studies of

endemic illness in the general population. Morbidity data were specifically excluded if they were based

on; 1) retrospective outbreak studies, 2) retrospective or prospective sensitive sub-population studies

(limited prospective age related sub-population studies were included), 3) retrospective passive disease

reporting studies or 4) predictions from infectious disease simulation of illness acquisition and spread. The

majority of studies cited in the EA were conducted in the U.S. or Canada. Where U.S. (and Canadian) data

were identified as limited, incomplete or biased, data from other developed countries were used to inform

data ranges for sub-populations.

EPA excluded the above four categories of morbidity data because of an assumption that including

these data would bias the illness predictions upward. However, there are some uncertainties associated

with that EPA assumption. The following text addresses these uncertainties about the estimated morbidity

rates for each of the four exclusions listed.

Retrospective outbreak studies have an inherent apparent disease burden bias. That is, common

source outbreaks come to the attention of public health authorities and are more likely to be reported to

CDC if the outbreak is large or causes illness that is relatively severe, compared with milder disease

endpoints such as rash or muscle stiffness. (Other factors, not related to disease burden, such as

occurrence in a locality with more effective public health surveillance and sufficient laboratory capacity

also affect outbreak reporting.) EPA excluded retrospective outbreak studies because of a concern that

outbreak data may not be reflective of endemic illness rates. However, in doing so EPA may be biasing

the estimated viral morbidity rates downward because the more virulent etiologic agents more likely

associated with outbreaks may be excluded from the analysis.

For the more highly infectious viruses, such as rotavirus and norovirus (Type A viruses), there

may be little difference between small epidemics and endemic illness. Unlike bacteria, waterborne viruses

do not have known animal reservoirs so the agent is continually circulating within the human population

within the U.S. (albeit supplemented by travelers coming or returning to the U.S.). A small outbreak

(CDC defines an outbreak as two or more contemporaneous illnesses), such as one occurring within a

family, may be counted as either endemic or epidemic disease. For especially infectious agents, epidemic

rather than endemic cases might be observed. Thus, there is uncertainty as to how to separate endemic

versus epidemic disease for the Type A viruses because they are highly infectious, continually circulating

within the human population, cause only mild illness and may be counted as either endemic or epidemic

disease, depending on the definitions used in the compilation.

EPA excluded sub-population morbidity data (with the exception of some age related data

discussed later) because of a concern that it may not reflect endemic illness in the general U.S. population. 

Studies of sub-populations in the U.S. report differing likelihood of becoming ill or severely ill. As

discussed in Section 5.2.2. sensitive subpopulations comprise a substantial proportion of U.S. population,

as much as 20% in one estimate (Gerba, 1996). EPA recognizes that the EA underestimates the number of

illnesses and deaths because greater morbidity and mortality rates among some sensitive sub-populations,

such as pregnant women (e.g. in developing countries, twenty percent of pregnant women have a fatal

outcome due to Hepatitis E viral illness) are not recognized in the main analysis. In addition, some

sensitive sub-populations have greater morbidity rates than the general population. Because the EA does
Economic Analysis for the 5-23 October 2006

Final Ground Water Rule 

not consider data on a large portion of the population that generally is more highly affected by rotavirus

and enterovirus, it underestimates the morbidity and mortality rates for rotavirus and enterovirus.

With respect to age related sub-populations, EPA captured as much of the age related difference as

possible but could not do so comprehensively. Age is important because sub-populations divided by age

have significantly differing rates of morbidity and mortality. All waterborne viruses, and especially

rotavirus, are more likely to affect children under five than other age groups. As discussed by Ramig

(2004) the reason that children are more likely to become ill from rotavirus is due to several possibilites. 

Ramig lists three reasons that apply to children in the U.S. (a fourth reason is malnutrition); one reason is

that children are less likely to be previously exposed and therefore have no pre-existing partial immunity. 

The other two reasons have to do with role of key enzymes with prevalence that changes with age. The

GWR accounted for some age heterogeneity among the general population by, for example, using differing

rotavirus morbidity rates for children under two and determining echovirus case-fatality ratios among

neonates. However, EPA recognizes that some age related sub-populations, such as the elderly, that may

have differing morbidity and/or mortality rates are not explicitly characterized.in the EA and that absence

contributes to uncertainty.

EPA explicitly excluded enteroviral disease data reported to CDC for three reasons. First, the data

are not current because passive enteroviral etiology reporting was discontinued in 1994 (Currently,

hepatitis A virus is the only potentially waterborne virus reported to CDC.). Second, as recognized by

CDC (Mead et al., 1999), disease reporting is designed and administered so that reporting is done

voluntarily by State and local public health agencies and laboratories. Third, an enteroviral etiology comes

to the attention of State and local public health authorities primarily when significant illness and/or

significant frequency occurs. Because many enteroviral illnesses do not result in symptoms sufficiently

grave so as to require a physician’s care, the passively reported illnesses associated with an enterovirus

etiology are assumed to be biased toward the more severe outcomes.

EPA explicitly excluded some rotavirus and enteroviral illnesses due to disease secondary

transmission within a community. EPA identifies primary illnesses as those that are acquired by

consuming rotavirus and enterovirus from a contaminated PWS well. Secondary illnesses are those cases

that are acquired by individuals who do not consume the contaminated drinking water, but instead acquire

illness through person-to-person exposure from a primary case. The EA does include a secondary disease

transmission factor to account for the number of secondary illnesses that are estimated to arise from each

primary illness. However, as is discussed in Section 5.2.4.3, this secondary disease transmission factor is

not a secondary morbidity rate because it assumes that only ill individuals can make others ill by

secondary transmission. As is well known from the case of Typhoid Mary, asymptomatic individuals can

also serve as carriers of disease, and thus infected individuals can infect others who can also become ill or

who can become carriers also. As a result of neglecting secondary cases that arise from asymptomatic

carriers as opposed to symptomatic carriers, the EA underestimates the total number of secondary cases.

In addition to estimating morbidity rates, EPA has estimated illness severity. Severity is important

because monetization of the rotavirus and enterovirus disease burden bestows greater benefits (avoided

costs), such as hospitalization costs and physicians’s office visit costs, if the disease is more severe. In this

EA, fatal outcomes occur for the general population (non-neonates) ill from enterovirus only if disease is

severe. Thus, to estimate mortality rates, the number of severe cases must be determined.

EPA used total disease burden estimates from CDC to account for the relative proportion of severe

enterovirus (Type B) outcomes. EPA defines severe outcome as any illness resulting in hospitalization. 
4

 Enteroviral type 71 disease was particularly virulent in Taiwan in 1998 where there was over 129,000

cases and 78 deaths, 90% among children less than 5 years old (Lin et al, 2003; Chang et al, 2004). In severe cases,

hand, foot and mouth disease proceeds to encephalomyelitis and cardiopulmonary collapse. The widespread

transmission is enhanced by the long period of viral shedding (as much as 5 weeks) in infected individuals. 

Infection rates for parents (41%) were higher than other adults (26%). These data suggest that enterovirus 71 is

efficiently transmitted by asymptomatic or mildly symptomatic adults (Chang et al, 2004). It is likely that most

hand, foot and mouth disease in the United States is also due to contact with other individuals. However, enterovirus

71 is copiously shed via the gut and can, along with other fecal/oral agents, be transmitted via ground water,

although the available data seem to indicate that this pathway is not likely. Three possible reasons that enterovirus

71 is not likely to be transmitted via ground water are that it may not survive long at ground water temperatures, it

may not be mobile in the subsurface and/or the infectious dose required to cause illness is so large that dilute

environmental samples cannot transmit infection. However, as the data from Taiwan indicate, the disease can cause

fatal outcomes at rates greater than the rates used in this EA for the enteroviruses, albeit perhaps not in developed

countries.

Economic Analysis for the 5-24 October 2006

Final Ground Water Rule 

CDC estimates that about 10 million cases of enteroviral disease occur each year in the U.S.. EPA

estimated that about 100,000 severe outcomes result from illness (myocarditis, encephalitis, and viral

meningitis) potentially caused by enteroviruses. The ratio of 100,000 severe outcomes divided by 10

million cases was used in the EA to estimate that 1% of enteroviral cases are severe. There are

uncertainties in using this 1% severity factor for the enteroviruses. In determining enteroviral severity,

EPA believes that a large proportion of the 10 million enteroviral cases in the U.S. could be due to hand,

foot and mouth disease (e.g. Pichichero et al. (1998) found in a four month study that 244 of 372

physician's office visits were due to symptomatic (stomatitis) or diagnosed hand, foot and mouth disease)

which is a benign childhood disease (in the United States but not necessarily elsewhere such as Taiwan)

caused by enterovirus 70 and 71.4

 Enterovirus 70 or 71 has never been found in drinking water or ground

water and is not believed to be waterborne in the U.S.. Rather, it is spread almost exclusively by person to

person transmission. Because enterovirus 70 and 71 illness is included in the total cases of enteroviral

disease, this EA could significantly underestimate the proportion of severe outcomes due to enterovirus in

the general population. However, in years or seasons for which no data are available, depending on which

enterovirus strains predominate, clinical symptoms not characteristic of enterovirus 70 or 71 could be more

likely observed and could account for more or most of the enteroviral illness.

As compared with the expansive definition of Type B (enteroviral) disease severity described

above, Type A disease severity is restricted to consideration only of the rotaviruses. For the Type A

viruses, only rotavirus is included in the estimate of the total disease burden despite the fact that norovirus

disease is widespread and norovirus makes both adults and children ill at significant rates. Other Type A

viruses, such as adenovirus and hepatitis A virus also disproportionately cause illness in younger adults. 

As a result of restricting the Type A disease burden to rotavirus only, the EA significantly underestimates

the proportion of severe Type A disease in the general (adult) population.

Mortality from ground waterborne agents, especially viruses, is sufficiently infrequent that a

mortality rate for the general population is difficult to determine from the scientific literature. This

difficulty is compounded for Type A virus because the available data are limited to rotavirus which is

highly infectious but has relatively mild severity. Mortality data are available only for sub-populations at

greatest risk of a fatal outcome. For enterovirus, data are available from a study of neonates with

enteroviral infection supplemented with fatal outcome case data from several other studies and applied to

the neonate population. For rotavirus, a fatal outcome is based on deaths in children under five identified

by CDC as part of a study to assess the costs and benefits of a rotavirus vaccine (subsequently removed
Economic Analysis for the 5-25 October 2006

Final Ground Water Rule 

from the market due to unintended intestinal obstruction effects). Thus, the available mortality data are

limited to data from children. No U.S. endemic mortality data are available for fatal outcomes in the

sensitive subpopulations, such as the elderly, a population also greatly susceptible to dehydration-related

mortality due to gastroenteritis. 

As discussed in Section 5.2.4.3, only rotavirus mortality rates in children are applied to the entire

population. The neonate mortality rate for enterovirus is restricted to neonates and not used to inform

mortality rates for other population sub-groups. EPA believes that, for the enteroviruses, neonate mortality

rates are higher than for the general population and thus the neonate data cannot be applied more broadly. 

On the other hand, EPA has no data on rotavirus mortality in population subgroups other than children

under 5 years in age, so EPA cannot determine if the rotavirus mortality rate in children is high or low

compared to other subgroups. EPA applies the rotavirus mortality to all age groups, recognizing that this

is a source of uncertainty (it could be an over or underestimate). The enterovirus mortality rates for the

non-neonates is based on a simple calculation that estimates the number of severe (hospitalized)

enterovirus cases together with an estimate of the number of fatal outcomes in severe cases. This mortality

rate is sensitive to the proportion of severe cases as discussed above and could be an underestimate if the

number of severe cases is underestimated.

Another source of uncertainty in the EA estimates of morbidity and mortality rates for rotavirus

(Type A virus) is whether or to what degree these rates could change due to a rotavirus vaccine. In 2006,

the U.S. Food and Drug Administration (FDA) approved a new pentavalent vaccine for rotavirus (Vesikari

et al, 2006) in children. The vaccine protects against the most common rotaviruses now found in the U.S.

(serotypes G1, G2, G3, G4, G9) but does not protect again all rotaviruses found in the U.S. or all

rotaviruses. Most current rotavirus infections in the U.S. are G1 serotype so Vesikari et al (2006) were

able to demonstrate that the vaccine was 74.9% (95% CI: 67.3-80.9) efficient in protecting against G1

gastroenteritis. Because few rotavirus cases occurred in the U.S. for the other serotypes during the study,

Vesikari et al (2006) report protection efficiency with very large uncertainty [G2 - 63.4% (95% CI: 2.6-

88.2); G3 - 82.7% (95% CI: <0-99.6%); G4 - 48.1 (95% CI: <0-91.6%); G9 - 65.4 (95% CI: (<0-99.3%)]. 

These data suggest that after a prolonged vaccination program, substantial rotavirus gastroenteritis will

continue to occur in the U.S., most from G1 serotype, but some from G2, G3, G4 and G9 serotype in

vaccinated children as well as from other rotavirus serotypes and additionally, in unvaccinated children

and adults. The most common rotavirus strains found in the U.S. could change in the future, either

naturally or as an unintended result of vaccination. EPA believes that norovirus, rather than rotavirus is

the more important health concern in the U.S. as a result of Type A viral exposure from ground water. 

EPA believes that, successfully implemented, the rotavirus vaccine has the potential to affect the future

number of health effects in children. Within the first 25 years of GWR implementation, all children that

are vaccinated would have reduced likelihood of incurring illness from rotavirus. Similarly, rotavirus

secondary spread, which in this EA is assume to originate only from children less than five years in age,

would be significantly reduced.

Most importantly, a rotavirus vaccine will have no impact on norovirus illnesses or other Type A

viral illnesses resulting from ground water exposure. Type A virus morbidity and mortality rates are

estimated with data on rotavirus because only rotavirus human challenge study data are available to

determine the likelihood of infection given a virus dose. No such infectivity data are currently available

for other Type A viruses (see Section 5.4.1 for a discussion of other Type A data including unpublished

norovirus infectivity data). EPA believes that the total Type A disease burden, especially in adults, is not

captured by monetizing rotavirus illness, with or without consideration of a rotavirus vaccine. 
Economic Analysis for the 5-26 October 2006

Final Ground Water Rule 

P P Annual Daily

D =− − 1 1( )

5.2.4.3 Quantified GWR Benefits (Predictions of Illnesses and Deaths)–Model Input Values

The quantified GWR benefits are determined for rotavirus and enterovirus using dose response

models fitted to human challenge study data, morbidity, mortality and secondary illness factor when

ingested from ground water sources. These data are summarized in Exhibit 5.10 and described in more

detail below.

Exhibit 5.10 Dose Response Assumptions of Viral Pathogens for the

GWR Risk Assessment (continued on next page)

Pathogen

Hazards Infectivity1

Morbidity Mortality

M (M m) p M s

Definition Infectivity measures the

probability of infection for

exposure to a specified

dose. “Annual infectivity

risk” estimates risk for a

year for exposure to a

daily dose, N, for a given

number of days, D, during

the year (see text for

details.) Dose response

function for annual risk is:

(see below for estimating

the probability of daily

infection PDaily)

Primary morbidity is

the probability of

illness given

infection; it can vary

from person to

person and can be

greater in sensitive

subgroups.

Secondary

morbidity is the

probability of

illness given

exposure to an

asymptomatic or

symptomatic ill

person.

Mortality is the

probability of

death as a

result of 

illness.
Economic Analysis for the 5-27 October 2006

Final Ground Water Rule 

P N Daily = ×

+

⎛

⎝

⎜ ⎞

⎠

⎟ α

α β

P N

Daily =− +

⎛

⎝

⎜ ⎞

⎠

⎟

−

1 1

β

α

Pathogen

Hazards Infectivity1

Morbidity Mortality

M (M m) p Ms

Type A

viruses

(Highly

infective

virus)

Represente

d by data on

Rotavirus

Dose response function

for daily risk of infection is

given by the expected

value of the Beta Poisson

dose response function:

PDaily for a single exposure

to one Type A infectious

unit is estimated to be

22.4% with 90%

confidence bounds of

8.8% and 41.4% reflecting

uncertainty in the " and $

parameters.

< 3 yrs 2

 = 0.10-

0.88, uniform

distribution

< 3 yrs2a = 0.55

(applied to the

entire exposed

population)

All ages 4 = 

5.7 x 10-6 - 

7.3 x10-6,

uniform

distribution

$ 3 yrs 3 = 0.10-

0.50, uniform

distribution

$ 3 yrs = 0

(assumed)

Type B

viruses

(Moderately

infective

virus)

Represente

d by data on

Echovirus or

Enterovirus

Dose response function

for daily risk of infection is

given by the Pareto

approximation to the Beta

Poisson dose response

function:

PDaily for a single exposure

to one Type B infectious

unit is estimated to be

0.44% with 90%

confidence bounds of

0.06% and 1.65%

reflecting uncertainty in

the " and $ parameters.

< 5 yrs 5

 = 0.5 -

0.78, uniform

distribution 

Triangular

distribution (all

age groups) 6,

from 0.11 to 0.55;

mode = 0.35

< 1 month 7

= 

9.2 x 10-3

$ 5 - 19 years 5 =

0.12 - 0.57, uniform

distribution

$ 1 month 8 =

.02

(applied only

to illnesses

that require

hospitalization

, which are

1% of all

illnesses)

> 19 years 5

 = 0.12 -

0.33, uniform

distribution

1 See Appendix F for details of infectivity dose response functions. 2 Based on Rodriguez et al. (1987) for the upper range value and Perez-Schael (1984) for the lower range value. 2a Based on Kim et al. (1977) 3 The range for older children and adults based on Ward et al. (1986) (upper range value), Kim et al. (1977) (lower

range value), and Wenman et al. (1979)

4 From Tucker et al. (1998) and Kapikian (2001) for children less than 5 years old and assumed to apply to all

ages. 

5

 Hall et al. (1970); Kogon et al. (1969) 

6 Morens et al., 1978 [citing Karzon et al (1961), Winkelstein et al (1957) and Lehan et al (1957)] 7 From Jenista et al. (1984), Modlin (1986) and Kaplan and Klein (1983) 8 Based on data from Melnick (1996), Modlin (1995) and Bennet et al. (1987). 

Notes: Mortality rates are rates of mortality given illness.
Economic Analysis for the 5-28 October 2006

Final Ground Water Rule 

Morbidity

In the EA, Type A viruses are represented by data on rotavirus because published data from

human challenge studies to determine the probability of infection given a virus dose are available only for

rotavirus (see Section 5.4.1 for a discussion on other Type A viruses, including unpublished human

challenge study data for norovirus which are not used in this analysis). For rotavirus, separate morbidity

factors were used for children less than 3 years old and for individuals greater than or equal to 3 years old. 

For children less than 3 years old, a morbidity factor was taken as a uniform distribution from 0.10 to 0.88

(Perez-Schael et al, 1984; Rodriguez et al, 1987). The lower range value was reported by Perez-Schael et

al (1984) and the upper range value was reported by Rodriquez et al (1987). There are significant

differences in the two study designs that may account for the great variability in the reported morbidity

rate. Rodriguez studied children under 3 while Perez-Schael studied newborns. Newborns are protected

against illness by maternal antibodies which fade by about 6 months in age. Older children can report a

wide range of clinical symptoms (e.g. pharyngitis and otitis media) in contrast to newborns who cannot

report symptoms. Thus Rodriquez used multiple disease endpoints while Perez-Schael was able to use

only diarrhea as a clinical symptom of disease. The Rodrizquez study was conducted in a private pediatric

medical practice in Virginia USA while the Perez-Schael study was conducted in a large maternity hospital

in Caracas, Venzuela. Because of the differences in the study designs used to determine rotavirus

morbidities, there is significant uncertainty in the rotavirus morbidity range.

For people aged 3 years or more, this EA uses a uniform distribution from 0.10 to 0.50. The lower

bound of 0.10 is from Kim et al (1977). Kim et al. (1977) found that 3 parents of infant children

hospitalized with rotavirus illness were ill (with gastroenteritis) among the 26 parents exposed to those ill

children and infected with rotavirus. The upper bound of 0.50 is from Ward et al. (1986). Ward et al.

(1986) found a 50% diarrhea (other ill individuals exhibited differing disease endpoints) morbidity rate in

adults challenged with a rotavirus dose under experimental conditions. Wenman et al. (1979) reported that

17 parents became ill of 43 parents infected by rotavirus (40%) in a prospective study of diarrhea in

households with newborn children in Canada. As discussed in Section 5.2.4.2, the G1 serotype is most

common in the U.S. and most adults have had one or more exposures to this serotype. Rotaviral immunity

to reinfection and illness is short (as opposed to lifetime immunity characteristic of poliovirus and hepatitis

A virus) and multiple infections are possible (Anderson and Weber, 2004; Koopman and Monto, 1989).

Griffin et al. (2002) analyzed rotavirus outbreaks and identified one rotavirus serotype (G2) that is

associated with outbreaks in adults. Outbreak data from nursing homes in Australia (Marshall et al, 2003)

identified G1, G4 and G9 rotavirus strains as causing outbreaks among adults. Because multiple serotypes

can produce rotavirus disease in adults, these data suggest that the morbidity value for adults can differ

from the morbidity identified from a single strain. If the human subjects in Ward et al (1986) were

challenged by G2, G4 and G9 strains, in addition to G1, then it is likely that a greater percentage would

become ill. There is uncertainty in the EA estimate of rotavirus morbidity for adults because it is based

primarily on infections produced by only one strain of rotavirus (G1). It is possible that other rotavirus

strains, such as G2, and consideration of disease endpoints other than diarrhea, would provide higher

morbidity estimates.

Type B viruses are represented by data on echovirus or enterovirus. The morbidity data for Type

B viruses are taken directly from two virus watch studies in Seattle (Hall et al., 1970) and New York

(Kogon et al, 1969) which are prospective epidemiological investigations undertaken in a general

population cohort. As such, they are high quality (and costly) data.and represent the best prospective

enterovirus morbidity data available for the general population. To the extent that current molecular
Economic Analysis for the 5-29 October 2006

Final Ground Water Rule 

methods are more sensitive in determining infection by identifying viruses shed in stool, the cell culture

methods used in the virus watch studies may underestimate the number of infected individuals. 

Exhibit 5.11 shows echovirus morbidity data from both the Seattle and New York Virus Watch

studies. Coxsackievirus (another subgroup of the Type B enteroviruses) are also reported from the New

York Virus Watch study and shown in Exhibit 5.11. However, only echovirus data were used in the EA to

represent the Type B viruses.

Three age-based morbidity rates ranges for echovirus (one group of the enteroviruses) from the

Seattle (Hall et al., 1970) and New York virus watch studies (Kogon et al., 1969) are used in the EA, each

in the form of a uniform distribution. The morbidity rate used for children less than 5 years of age is 0.5 -

0.78; for children 5 years to 19 years is 0.12 - 0.57; and for adults greater than 19 years old is 0.12 - 0.33. 

For children less than five years old, the lower bound comes from the Seattle study and the upper bound

comes from the New York study. For children between ages 5 and 19, the lower bound comes from the

New York study and the upper bound comes from the Seattle study. For adults, the lower bound comes

from the New York study and the upper bound comes from the Seattle study. The coxsackievirus

morbidity data from the New York study were not used.

As shown in Exhibit 5.11, the Seattle virus watch reported data for children aged 5 to 19 years and

for individuals over 19 years; the New York virus watch data reported data only for individuals under and

over four years in age. Because the New York virus watch only reported data for the over four age group,

these data (0.12) were used to populate both the 5 to 19 year group and the greater than 19 year group. For

the Seattle virus watch study, a total of 43 individuals were infected by echovirus and 20 people became

ill. For the New York virus watch study, 53 individuals were infected by echovirus and 24 people became

ill. Thus, despite the high quality of the data, the total number of people used to determine morbidity is

small.

There is large uncertainty associated with the Type B morbidity values currently used in the EA

because they are based only on echovirus data. For other parameters in the GWR EA (e.g., disease

severity) data from all enteroviruses were used. A significant uncertainty is the exclusion of the

coxsackievirus morbidity data. If coxsackievirus (also an enterovirus) morbidity data were used from the

New York viral watch study (Kogon et al, 1969) then the mean morbidity rates would be significantly

higher because coxsackievirus is more likely to cause illness than echovirus, upon infection. Kogon et al

(1969) report 10 illnesses resulting from 15 infections. Thus, the moribidity range for the 5-19 year olds

would change from 0.12 - 0.57 to 0.12 - 0.67 and the morbidity range for adults would change from 0.12 - 

0.12 - 0.67. For all age groups in the New York Viral Watch study, Kogon reported 53 illnesses resulting

from 103 infections.

In this EA, only echovirus data were used to determine Type B virus morbidity rates (despite the

availability of coxsackievirus morbidity data) to ensure consistency with the infectivity data for Type B

viruses. The human challenge study data representative of Type B viruses was conducted using echovirus

(type 12). By using only echovirus morbidity data, both infection and illness rates are determined using

only echovirus data, thereby ensuring that the predicted number of illnesses is more closely represented by

the challenge doses.

Exhibit 5.11 presents a summary of the morbidity data from the Seattle and New York Virus

Watch studies discussed above.
Economic Analysis for the 5-30 October 2006

Final Ground Water Rule 

Exhibit 5.11 Summary of Virus Watch Morbidity Data

Seattle Virus Watch Study

(Hall et al, 1970)

New York Virus Watch Study

(Kogon et al, 1969)

Age

Bins

Echovirus

Morbidity

Coxsackievirus

Morbidity

Age

Bins

Echovirus 

Morbidity

Coxsackievirus

Morbidity

0-5 years 12 ill/

24 infected

(50%)

no data 0-4 years 21 ill/

27 infected

(78%)

28 ill/

54 infected

(52%)

5-19 years 4 ill/

7 infected

(57%)

no data 5-9 years

(Coxsackievirus)

5+ years

(Echovirus)

3 ill/

26 infected

(12%)

15 ill/33 infected

(45%)

19+ years 4 ill/

12 infected

(33%)

no data 10+ years

(Coxsackievirus)

see above 10 ill/15 infected

(67%)

The mean morbidity rate is based on the observed range and assumed distribution for both Type A

(rotavirus) and Type B (echovirus) illnesses. This value is likely underestimated because viral pathogens

other than the surrogate types will also be avoided by rule implementation and may include agents with

greater capability to cause illness, as is shown in the above example for coxsackievirus, thereby increasing

the upper part of the range and the corresponding mean value. The potential benefits of reducing illness

from pathogens other than enterovirus are discussed in section 5.4 of this chapter. In particular, section 5.4

identifies norovirus as a common waterborne etiologic agent that, unlike rotavirus, causes illness in adults

as well as in children. Thus, in choosing a differing Type A surrogate virus, the mean morbidity rate in the

general population (adults and children) could increase, as compared with rotavirus that causes illness

primarily in children.

Secondary Spread

Secondary spread can occur from contact with an infected or ill individual. It is likely that most

secondary spread occurs from contact with asymptomatic carriers (e.g., Typhoid Mary) because, for most

age groups, there are no clinical symptoms expressed to keep others away. Because data on secondary

spread from asymptomatic carriers are not available, in this analysis, it is assumed that only ill persons are

capable of causing secondary transmission. Thus, the secondary spread value used is the EA is not a

secondary morbidity rate (which includes contact with both symptomatic and asymptomatic carriers) but

rather a secondary spread factor. This assumption underestimates the secondary spread morbidity rates

which ideally should be applied to the total number of infected rather than ill individuals.

Secondary spread of waterborne illnesses is a reasonable assumption because the pathogens of

concern for the GWR are also commonly transmitted by respiratory or direct contact (fecal-oral) pathways.

 Aerosols containing fecal-oral viruses can be transmitted either by the ingestion or the inhalation route. 
Economic Analysis for the 5-31 October 2006

Final Ground Water Rule 

Some waterborne-viruses, such as coxsackievirus and adenovirus cause eye infections (conjunctivitis) and

so they may be transmitted by the dermal pathway via primary or secondary exposure.

Because the enteroviruses and rotavirus do not have animal reservoirs, they circulate only within

the human population. For the viral strain to avoid dying out, each individual with a viral infection must,

on average, transmit at least one additional infection to maintain that virus strain within the human

population. Thus, high rates of secondary transmission are necessary for virus viability.

Most available secondary morbidity data are obtained from studies of households. In these

households, both parents and children become ill and secondary transmission values are based on data

and/or assumptions about whether parents or children were the primary case. Few data are available to

evaluate secondary transmission outside the household (within the community) or within other higher risk

settings such as nursing homes. For rotavirus, a virus watch study was used to collect data from

Tecumseh, Michigan (Koopman and Monto, 1989; Koopman et al, 1989) and an infectious disease

simulation was conducted to determine the secondary morbidity rates (Longini and Koopman, 1982). As

discussed in section 5.2.4.2, data derived from infectious disease simulations are specifically excluded

from consideration in the GWR EA. 

For rotavirus (Type A), the secondary spread factor was determined separately for children under

3 and all others. For all individuals over age 3, it is assumed that there is no secondary spread of rotavirus. 

This assumption is based on the apparent exposure of most individuals to multiple strains of rotavirus early

in life. As a result, it is assumed that most individuals have acquired some temporary immunity to

rotavirus by age 3 and so, while there is a likelihood of developing clinical illness from primary exposure,

it is expected that there would be a lower likelihood of developing clinical illness from secondary

exposure. Primary exposure morbidity data from Ward et al. (1986) and secondary morbidity data from

Wenman et al. (1979) (assuming adults are secondarily exposed in Wenman) show that the higher

rotavirus morbidity rates comes from primary exposure while the lower (but not zero) rates come from

exposures that might be secondary. The EA underestimates the number of illnesses and deaths in adults

from rotavirus by assuming no clinical illness in individuals over age three by secondary transmission.

For children under age 3, the rotaviral secondary illnesses factor is 0.55 (i.e. for every two primary

rotavirus illnesses among children under age 3, there is about one secondary illness in individuals of any

age that is included in the GWR EA benefits analysis). This value is based on Kim et al. (1977). Kim et

al. (1977) is a study of the adult contacts of pediatric patients with gastroenteritis. It was not designed to

determine secondary transmission values, either secondary morbidity rates or secondary illness factors. 

For example, there are no data that definitively identify whether the adults or the children were the primary

case and either assumption is appropriate. EPA has identified at least two differing analyses for

determining secondary illness using the Kim paper. Fortunately, the two differing analyses (either may be

correct) give approximately similar results which are presented here (Exhibit 5.10).

Echovirus (Type B) secondary illness factor is a triangular distribution for individuals of all ages. 

The range is 0.11 - 0.55 with a mode of 0.35. These data are derived from echovirus outbreak data

reported by Morens et al (1991) (Table 17-3) in a reference work on the enteroviruses. The lower value in

the range comes from a study of a New York aseptic meningitis outbreak in 1956 (Karzon et al, 1961). 

The upper value in the range comes from a New York aseptic meningitis outbreak in 1955 (Winkelstein et

al, 1957). The mode is informed by the other aseptic meningitis outbreak (in Iowa) listed in the table

(Lehan et al, 1957).
Economic Analysis for the 5-32 October 2006

Final Ground Water Rule 

In general, primary sources are used in the GWR EA to determine input values for the risk

assessment. However, secondary transmission data are very difficult to acquire and evaluate because key

data describing which household members are primary and which are secondary cases are typically not

available. There are no data on secondary transmission of echovirus or other enteroviruses (Type B)

outside the household. For these reasons, the echovirus secondary illness factor used in the EA is taken

directly from a reference work where, it is presumed that the authors had adequate expertise to evaluate the

original paper and make an informed judgement as to whether to use these data to inform secondary spread

values.

The enterovirus secondary transmission factor is defined only by echovirus data. Because of low

infectivity rates, secondary transmission data are rare for the other enteroviruses. It is likely that, if other

enteroviruses, such as coxsackievirus, were considered, the secondary transmission values could differ. 

For example, most enterovirus 70 or 71 is acquired by secondary transmission via person to person

contact. Thus, if secondary transmission data were available and used in this EA, the secondary spread

factor would likely be higher.

The use of observational epidemiologic data in the quantitative benefits analysis is an appropriate

and acceptable method to determine the number of secondary cases. However, it is not the only

appropriate and acceptable method. In Appendix E, Potential Implications of Population Dynamics and

Secondary Transmission of Infection on the Benefits of the Ground water Rule, another method is

described and results are presented for the number of secondary cases that might accrue, after infection or

illness from a primary ground water exposure. One difference between these two methods is that in the

quantified benefits section of the GWR EA, EPA assumes that only ill individuals can make others ill. As

is well known from the case of Typhoid Mary, asymptomatic individuals can also serve as carriers of

disease, and thus infected individuals can infect others who can also become ill or who can become

carriers also. The number of secondary cases is limited by the number of susceptible individuals in the

population under consideration and the length of acquired immunity, if appropriate, for the agent. 

Appendix E presents a different modeling approach which accommodates dynamic phenomena

typical of real infectious disease transmission systems. A dynamic model is described and results are

presented for the number of secondary cases that might accrue in a large community after Type A virus

(e.g. rotavirus) infection and illness is introduced into a subset of travelers who acquire the infection from

drinking contaminated ground water at a TNCWS well outside their home community. The travelers

return to the home community and secondary cases accrue from normal interactions among infected and ill

individuals who transmit the disease to others in their household or their community. The analysis

considers only infection and illness from two Type A viruses, rotavirus and norovirus.

One important difference between the simple secondary spread factor multiplier used in the GWR

EA and the partial differential equation methodology of Appendix E is in the assumptions about the

characteristics of secondary spread of Type A virus. The GWR EA assumes that 1) only rotavirus causes

Type A illness and 2) all children younger than 3 years of age can infect other individuals with rotavirus,

while older (than 3 years) children and adults can not transmit rotavirus to others. Norovirus is not

considered in the quantified benefits analysis of the EA. The alternative analysis in Appendix E assumes

1) Type A viruses other than rotavirus, such as norovirus are causing illness in the people that consume

water from the hypothetical TNCWS well and 2) symptomatic and asymptomatic individuals of all ages

infected with a Type A virus can infect others who can also become ill or can become asymptomatic

carriers. 
Economic Analysis for the 5-33 October 2006

Final Ground Water Rule 

The results of the analysis, presented in Appendix E, suggest that population dynamics could

substantially impact the potential benefits calculated quantitatively in this EA, depending on the suite of

population dynamic elements considered. The results demonstrated that important assumptions had a

strong influence on the estimated number of secondary cases. Model parameters that strongly influence

the estimate include the duration of clinical disease, duration of shedding (etiological agent carrier),

etiologic agent infectivity, duration of protective immunity, and person-to-person transmission

characteristics of the infectious agent. 

The population dynamic simulation results illustrate that the number of additional illnesses due to

secondary exposure could either increase or decrease relative to the method used in the GWR EA,

depending on the choice of elements. For example, using median values for the elements, it is determined

that approximately 0.18 additional secondary illnesses, on average, would result from each primary

infection and illness. The median value analysis also showed that the number of secondary illnesses due to

asymptomatic carriers is roughly equal to the number of secondary illnesses due to contact with ill

individuals. However, simulations using different model parameters (sensitivity analysis) also demonstrate

that the predicted number of additional illnesses due to secondary transmission could either increase by

approximately an order of magnitude or be reduced to effectively zero, depending on the assumptions

about infection transmission parameters. 

The model results presented in Appendix E serve to demonstrate the concept and method of

dynamic transmission system analysis to predict the number of secondary cases that might accrue.

Mortality

For rotavirus (Type A), the mortality factor for all ages used in this analysis is a uniform

uncertainty distribution from 5.7 x 10-6 to 7.3 x 10-6. This range is based on data from a cost-effectiveness

analysis of a rotavirus immunization program (Tucker et al. 1998). The cumulative total for rotavirus

diarrhea was 2,730,000 cases (by year five in a birth cohort), and the estimate of rotaviral deaths for that

same birth cohort was 20. To determine the upper value of the mortality rate range, the deaths are divided

by the diarrhea events (20/2,730,000) resulting in 0.00073%. The lower value for that range is based on a

differing estimate for the for the total number of rotavirus cases. Kapikian (2001) estimated 3.5 million

rotavirus cases as compared with the CDC estimate of 2.73 million. Applying the CDC estimate of 20

deaths to the Kapikian value for the number of cases yields a lower bound factor of 5.7 x 10-6. These rates

are assumed to apply applied to all age categories.

For Type B viruses, the mortality factor for infants less than 1 month old is based on case fatality

rates from three sources (Jenista 1984, Modlin 1986, Kaplan and Klein 1983). Jenista (1984) reported a

case-fatality rate of 3% for neonates with culture-proven enterovirus infection in the Strong Memorial

Hospital study. Modlin (1986) reported 7 of 206 infants in newborn nurseries who became ill during

echovirus outbreaks died (3.4%). Kaplan and Klein (1983) reported that 6 of 77 patients younger than

three months of age hospitalized with cultures positive for Coxsackievirus died (7.8%). The mean from

these studies is 4.9%. Since this is a hospital case fatality rate, it is necessary to multiply by the proportion

of infants hospitalized to arrive at the mortality rate. Jenista (1984) reported the percent of enteroviralinfected infants (re-)admitted to the hospital with suspected sepsis was 18.7%. The final mortality rate for

neonates of 0.0092 was calculated as 0.187 * 4.9%. This analysis assumes that neonate enteroviral illness

severity is represented by the Jenista (1984) cohort. Modlin (1986) reports differing severity depending on

whether the neonate is infected by echovirus in utero as compared with during and after birth. The EA
Economic Analysis for the 5-34 October 2006

Final Ground Water Rule 

mortality rate is based on hospitalization data from all neonates in a prospective study (Jenista, 1984)

rather than data only from sensitive subgroups such as neonates with infection acquired in utero.

For Type B viruses, the mortality factor used for persons of all ages (other than neonates) is

0.02%. It is assumed that 1% of cases are severe enough to require hospitalization. Modlin (1995) finds

that 0-4% (mode of 2%) of cases that require hospitalization result in death. Currently a general mortality

value of 0.001% for cases that do not require hospitalization is used when specific rates are not available

(Bennet et al., 1987). Therefore, the calculated mortality rate is (0.01 x 0.02) + (.00001* 0.99) = .02%.

The proportion of severe cases is determined to be 1% based on the following calculation. CDC

estimates about 10 million enteroviral illnesses each year (e.g. Strikas et al, 1986). By compiling data on

the annual number of severe enterovirus cases, assumed to be encephalitis (19,000 cases; Khetsuriani et al,

2002), myocarditis (60,000 cases; Kim et al, 2001), and viral meningitis and meningioencephalitis (34,000

cases; Khetsuriani et al, 2003), it is estimated that about 100,000 severe acute illnesses occur each year. 

The number of severe cases divided by the total number of cases yields a factor of 1% of cases. As

discussed in Section 5.4, the severe chronic illnesses due to echovirus or other enterovirus, such as dilated

cardiomyopathy and Type I diabetes are not included in the tally of severe cases. In addition, as discussed

in Section 5.2.4.2, the total number of cases (ten million) includes a substantial number of mild hand, foot

and mouth disease cases caused by enterovirus 70 and 71. Thus, the percentage of cases that are severe

would likely be higher if only waterborne enterovirus were considered.

5.2.5 Risk Characterization

Risk characterization combines the hazard identification, exposure assessment, and dose-response

information to describe the overall risk to the exposed population. The following sections will describe the

risk assessment methodology for the baseline risk calculations, provide results of the risk calculations, and

describe the methods used in estimating the reduction in risk from the regulatory alternatives.

5.2.5.1 Risk Assessment Methodology for Baseline (Pre-GWR) Risk Calculations

This section summarizes the risk assessment modeling approach used by EPA to estimate the

baseline number of annual endemic infections, illnesses and deaths due to viruses in GWSs. For a more

complete and detailed discussion of the risk assessment model, the reader is referred to Appendix G.

A Monte Carlo simulation model was used for this risk assessment so that the effects of those

model inputs for which variability and/or uncertainty could be described quantitatively could be reflected

in the estimated cases of illness and deaths.

The risk model operates on 2,376 distinct population categories. The 2,376 population categories

considered in the risk model reflect differences in virus occurrence and individual exposure factors that

influence individual risks of infection and resulting illnesses and deaths in both the pre-GWR baseline and

following implementation of the final GWR (or the other regulatory alternatives considered). The 2,376

strata result from the 3 system types, 9 systems size categories, 8 well types, and 11 age groups that are

considered (3 * 9 * 8 * 11 = 2,376). The 3 system types are CWS, NTNCWS, and TNCWS. The 9 system

size categories are those described in Chapter 4 and provide information on the number of people served

per entry point (well) in each size group of each system type. The 8 well types reflect the various
Economic Analysis for the 5-35 October 2006

Final Ground Water Rule 

combinations of being more or less vulnerable to contamination, disinfecting or nondisinfecting, and

construction to standards (2 * 2 * 2 = 8). The 11 age groups, as described in the preceding section, reflect

differences in average daily water consumption. The risk assessment model has three major parts that are

summarized below. 

The first major part of the risk model generates information on the annual individual risks of

infection for 2,376 population categories. There are two types of outputs from this first part of the model

for each of the 2,376 population categories: (1) uncertainty distributions of average risk of infection and

(2) variability distributions of individual risk of infection. 

The second major part of the risk model uses the uncertainty distributions of average individual

risk of infection in each population category as its inputs to calculate the expected number of annual

endemic illnesses and deaths in each of the 2,376 strata, which are then aggregated to arrive at the national

totals. 

The third major part of the risk model uses the variability distributions of individual infectivity

risks generated in the first part of the model. In this third part of the model, these 2,376 individual risk

distributions are drawn from to generate an overall individual infectivity risk curves for the baseline and

post-regulatory conditions. 

One of the key factors considered in constructing the risk model in parts was to efficiently

accommodate addressing the variability and the uncertainty in the model inputs. The computation of the

range of individual risks of infection in the population groups served by GWSs involves inputs that reflect

both variability and uncertainty. However, the computation of cases of illnesses and deaths, based on the

individual infectivity risks, involves inputs that reflect uncertainty only. The third part of the model

addresses only variability in individual risks of infection.

The first part of the risk model was therefore constructed as a two-dimensional (2D) Monte Carlo

simulation to properly manage both the variability and uncertainty factors involved. For each of the 2,376

population categories, the modeling involved 250 uncertainty loops with 1,000 variability loops within

each of the uncertainty loops. (The specific inputs considered as variability and uncertainty items are

described later in this section.) The first output of this first part of the model (for each of the 2,376

categories) is a set of 250 average individual infection values (that is, the average of each of the 1,000

estimates of individual risk in each of the 250 uncertainty loops). The second output of this first part of the

model (again for each of the 2,376 categories) is a distribution of 1,000 individual infectivity risk values

averaged across the 250 uncertainty loops (where each is first sorted from lowest to highest risk values).

The second part of the risk model is a one dimensional Monte Carlo simulation model that uses the

first output of part one of the model, which is an uncertainty distribution, along with other inputs that are

either constants or are distributions reflecting uncertainty. Again, this second part of the risk model

produces estimates of cases of illness and death, presented as uncertainty distributions from which the best

estimate (taken as the mean) and the lower and upper 90% confidence bounds on the cases (taken from the

5th and 95th percentiles, respectively) are obtained.

The third part of the risk model is also a one dimensional Monte Carlo simulation model in which

values are drawn from the 2,376 distributions of individual risk variability in proportion to the population

that they each represent to construct overall risk distribution curves for both the baseline conditions and for

post-regulatory conditions. 
Economic Analysis for the 5-36 October 2006

Final Ground Water Rule 

The following provides some further discussion of each of the three parts of the risk assessment

model. Again, the reader is referred to Appendix G for details of the modeling performed. Exhibit 5.12

provides a summary description of the various factors used in the risk calculation and indicates whether

they were inputs as variability distributions, uncertainty distributions, or constants.
Economic Analysis for the 5-37 October 2006

Final Ground Water Rule 

Exhibit 5.12 Summary Table of Risk Calculation Factors, Distribution Category

(Variability, Uncertainty, Constant) and Distribution Type) (continued on next page)

Risk Calculation

Factor

Description and

Use in Calculations Variability Uncertainty Constant Type

% Vulnerable Wells Used in Step 1 to

characterize whether

the well is less or more

vulnerable

X

Different point

estimates for

different system

types and sizes

Occurrence Hit Rate

(Pwell)

Used in Step 1 to

characterize the

fraction of systems (and

therefore of population)

having viruses present

in the source water.

X

Multiple input

sets from

MCMC model

output

Occurrence Hit

Rate (Psample)

Used in Step 1 to

determine the

number of days of

exposure to water

with virus present

X X

Multiple input

sets of

distributions

from MCMC

model output 

(uncertainty);

selection of a

specific value

from the

distributions

for each well

(variability)

Occurrence

Concentration 

Used in Step 1 to

characterize the

concentrations of

viruses in source

water.

X sample with

replacement

Fraction of

Disinfecting and

Non-disinfecting

Systems

Used in Step 1 to

separate those

systems currently

practicing disinfection

from those that do

not.

X

Different point

estimates for

different

system types

and sizes

Log Removal for

Disinfecting

Systems

Used in Step 1, an

assumed 2 or 4-log

removal of virus

concentration in

source water for

those systems

practicing

disinfection.

X point estimate
Risk Calculation

Factor

Description and

Use in Calculations Variability Uncertainty Constant Type

Economic Analysis for the 5-38 October 2006

Final Ground Water Rule 

Viability Used in Step 1 to

indicate the fraction

of viruses in water

considered to be

infectious (assumed

here to be 1.0).

X point estimate

Drinking Water

Consumption

Used in Step 1 to

characterize the daily

water consumption

by various age

groups in the

exposed population.

X

point estimate

for each age

group derived

from

distributions 

Type A and Type

B Dose response

Equation

Parameters

Used in Step 1,

empirically derived

parameters in

equations used to

calculate daily and

annual risk of

infection.

X

multiple pairs

of parameters

obtained by

simulation

Days of

Consumption

Used in Step 1 to

indicate the number

of days per year an

exposed individual

consumes water from

ground water

sources.

X

(for

TNCWSs)

X

(for CWSs

and

NTCWSs)

triangular for

TNCWS,

constants for

CWSs and

NTCWSs 

Population

Exposed

Used in Step 1 to

indicate the

population

consuming drinking

water from ground

water sources.

X

point

estimates

Average Annual

Individual Risk of

Infection

Product of the Step 1

calculation used in

Step 2 to calculate

cases of illness and

death.

X calculated in

risk model
Risk Calculation

Factor

Description and

Use in Calculations Variability Uncertainty Constant Type

Economic Analysis for the 5-39 October 2006

Final Ground Water Rule 

P P Annual Daily

D

=− − 1 1( )

Population Served Used in Step 2 to

scale up the annual

individual infection

risks to total cases of

infection, and

ultimately to total

cases of illness and

death in the exposed

population.

X point

estimates

Primary Morbidity

Factors

Used in Step 2 to

estimate the number

of illnesses per

infection in the

exposed population. 

X point estimate

Secondary

Morbidity Factors

Used in Step 2 to

estimate the number

of additional illnesses

resulting from contact

with individuals

becoming ill through

primary consumption

of drinking water.

X

(for Type B

virus)

X

(for Type

A virus)

point estimate

(Type A)

triangular

(Type B)

Mortality Factors Used in Step 2 to

estimate the number

of deaths in the

exposed population.

X point estimate

Part 1. Estimation of the Annual Individual Risk of Infection

The key value calculated in Part 1 of the risk assessment model is the annual individual risk of

infection. The algorithm used for this calculation is:

In this algorithm, it is implied that an individual's risk of being infected at some time during the

year is the result of his or her experiencing an average daily risk of infection given by PDaily for D days of

exposure during the year. The value for D in this algorithm is generated from the value selected for a

given well from the Psample distribution. The Psample value, which falls between 0 and 1 and represents the

duration of fraction of time that a contaminated well has virus present, is multiplied by the days of

exposure for each type of well as shown in Exhibit 5.7 to give the days of exposure to water with virus

present.
Economic Analysis for the 5-40 October 2006

Final Ground Water Rule 

P N Daily = ×

+

⎛

⎝

⎜ ⎞

⎠

⎟ α

α β

P N

Daily =− +

⎛

⎝

⎜ ⎞

⎠

⎟

−

1 1

β

α

For reasons discussed in detail in Appendix F, there were different, though related, forms of the

dose-response model for determining the average daily risk of infection for the Type A and Type B virus. 

Both model forms are rooted in the Beta-Poisson dose-response model described by Haas et al. (1999). 

For Type A viruses, the model form used was:

where N is the expected number of viruses ingested per day, and " and $ are the parameters of a beta

distribution that characterizes the variability in the survival probability of the Type A viruses that are

ingested.

For Type B viruses, the model form used was:

where N is again the expected number of viruses ingested per day, and " and $ are the parameters of a

Pareto Distribution used here as an approximation to the exact Beta Poisson distribution.

The expected number of viruses ingested per day, N, in this model is the product of the average

concentration of the virus in the water consumed and the average daily amount of water consumption of

the individual consuming that water. Also, for those categories of wells that practice disinfection, the

concentration of virus was further reduced to reflect either 2-log or 4-log inactivation in proportion to the

fraction of disinfecting systems in that category achieving those levels of disinfection. 

As indicated earlier, this part of the risk model was structured as a 2D Monte Carlo simulation to

accommodate both variability and uncertainty in various inputs.

The inputs to this part of the model that were treated as uncertainty items were:

• The hit rate, used to characterize the probability that a well would have virus present in the

source water;

• The " and $ parameters used in the daily risk dose-response functions; and

• The fraction of wells that are either more or less vulnerable.

The inputs to this part of the model that were treated as variability items were:

• The concentration of virus in source water when present, and

• The daily water consumption amount (varied by age group).
5

 It is necessary to modify some of the age categories within these 2,376 groups to apply the morbidity and

secondary spread factors to reflect the specific age ranges as shown in Exhibit 5.10 for which they have been

developed.

6

 As with the morbidity and secondary spread factor noted above, some adjustment of the age groups is

made to apply the morbidity factors to reflect the specific age ranges as shown in Exhibit 5.10. 

Economic Analysis for the 5-41 October 2006

Final Ground Water Rule 

∑ ( ) =

× × × +

792

1

( ) ( ) ( ) 1

i

Popi PAnnual i MP i MS i

∑ ( ) =

× × × + ×

792

1

( ) ( ) 1 ( ) ( )

i

Popi PAnnual i MP i MS i MM i

More details on the characterization of uncertainty in the hit rates and of variability in virus

concentration for the various well types is presented in Chapter 4. More information on water

consumption variability distributions is presented in section 5.2.3 of this chapter. Also, a more thorough

discussion of the derivation of the " and $ parameters of the infectivity dose-response functions to reflect

uncertainty in those values is provided in Appendix F.

Part 2. Estimation of the Annual Cases of Illness and Death

In the second part of the risk assessment model, the uncertainty distributions of average individual

risk of infection for each of the 2,376 population categories are used together with information on the

number of individuals in each of these categories, risk of illness given infection (morbidity factor), and

factors describing secondary spread of illness to compute the number of cases of annual endemic illnesses. 

The basic algorithm for the calculation of illnesses across all 2,376 categories is:5

These calculations are carried out as a Monte Carlo simulation using 1,000 iterations. In addition

to the uncertainty distributions for individual risk of infection that are used as inputs (PAnnual(i)), uncertainty

is also reflected in the secondary spread factor used for Type B viruses. The resulting output of this step is

an uncertainty distribution of estimated annual endemic cases of illnesses for each virus type from which

the mean is used as the best estimate of the annual cases and the 5th and 95th percentile values are used as

the lower and upper 90% confidence bounds.

The basic algorithm for the calculation of annual endemic deaths is a simple extension of the

algorithm for total illnesses shown above:

which includes the mortality factor (MM(i)) for each category.6

 In the risk assessment model, deaths are 

calculated in tandem with illnesses in the simulation as noted above. Similarly, the output for this step is

an uncertainty distribution of estimated annual endemic deaths for each virus type from which the mean is
Economic Analysis for the 5-42 October 2006

Final Ground Water Rule 

used as the best estimate of the annual cases and the 5th and 95th percentile values are used as the lower and

upper 90% confidence bounds.

Part 3. Characterization of the Distribution of Individual Risks

The outputs of the second part of the model focus on estimates of the number of cases of illnesses

and deaths in the population. Those estimates are built up from consideration of the average or expected

risk of infection from the consumption of virally contaminated ground water applied to the population

groups to which those averages apply. It is noteworthy that these average annual risks of infection span

the full range from 0 (for the vast majority of the population consuming water where there is no “hit” and

therefore no virus present) to a risk of 1 (for those individuals found to be consuming water where viruses

are present at levels sufficiently high to ensure an infection occurring at some point during the course of a

year of exposure). 

This third part of the risk assessment model is aimed at providing some insights into how the

annual risks of infection are distributed in the population within this range of 0 to 1. In part 1 of the risk

model, for each of the 2,376 population groups, the simulation produces 1,000 estimates of individual risk

for 250 alternative sets of uncertainty inputs. In Part 3 of the model, the 1,000 individual risk estimates in

each of these 250 distributions of the 2,376 population groups is sorted from lowest to highest risk value. 

An overall “expected individual risk” distribution for each of the 2,376 population groups is created by

computing the average of the sorted 1,000 values across the 250 sorted distributions. 

Then, in a separate simulation, a probability is assigned to each of these 2,376 “expected

individual risk” distributions reflecting the fraction of the total population served by ground water that

each represents. Then 25,000 individual values are drawn from these 2,376 distributions in proportion to

these probabilities to determine which distribution to draw from on a given iteration, and then randomly

from that “expected individual risk” distribution that was selected. 

The result of this process is an overall distribution of individual risk that reflects the entire exposed

population. The shape of this distribution for the baseline conditions can then be compared to similar

distributions constructed for the post-GWR conditions to provide insights into how the rule affects not

only the number of cases of illness and death, but also how it differentially affects those individuals

experiencing different levels of risk prior to the rule.

5.2.5.2 Results of the Baseline Risk Calculations

Estimated annual numbers of endemic illnesses from ingestion of Type A and Type B viruses in

ground water PWSs are summarized in Exhibit 5.13. These are the average of the avoided illnesses and

deaths calculated for each of the 25 years following rule promulgation. This table presents the calculated

mean, as well as the 5th and 95th percentile estimates of annual illness and deaths for Type A and Type B

viruses from the Monte-Carlo simulation. The mean from the simulation is the expected number and the

5th and 95th percentile reflect uncertainty around that reflection.
Economic Analysis for the 5-43 October 2006

Final Ground Water Rule 

mean 5th 95th mean 5th 95th

Type A 175,168 32,652 435,381 1.16 0.22 2.92

Type B 10,018 501 40,718 2.01 0.04 8.10

Total 185,186 33,153 476,099 3.18 0.26 11.02

Virus Type

Illnesses per Year Deaths per Year

Exhibit 5.13 Estimates of Annual Baseline Viral Illness and Death1

1

 Illnesses are rounded to nearest whole number and deaths to the nearest tenth. Detail may not sum

 due to independent statistical analyses.

It is important to recognize that the two-step procedure for calculating the number of cases of

illness and death in the population from exposure to viruses in ground water was carried out separately for

the Type A and Type B virus categories (reflecting different occurrence distributions and dose-response

relationships), different age groups (reflecting different morbidity and mortality factors), different water

system size groups (reflecting different numbers of people served), and different water system types

(reflecting different exposure days of consumption per year for CWSs and NCWSs). The results of these

many separate estimates of risk and cases of illness and death are then summed to obtain the overall

estimates presented in Exhibit 5.13 (for Type A and Type B viruses).

In presenting the results of this two-step procedure for computing the baseline illnesses and deaths

as shown in Exhibit 5.13, the best estimate is the mean of the iterations run in the second step. The

uncertainty in that estimate is characterized by the 5th percentile and 95th percentile values obtained from

those iterations (90 percent confidence bounds). These imply that, given the variability and uncertainty

factors explicitly included in the analysis, there is a 5 percent chance that the actual number of cases falls

below the 5th percentile value, and a 5 percent chance that it falls above the 95th percentile value, and

therefore a 90 percent chance of falling within the specified bounds.

Summing the estimates of illness for both types of viruses gives a combined estimate of more than

180,000 illnesses each year, the majority of which are attributable to the highly infective, but less lethal,

Type A viruses. The estimated combined number of deaths per year is approximately three, with slightly

more of those being due to the more lethal, but less infectious, Type B viruses.

5.2.5.3 Baseline Illnesses and Deaths in Sensitive Subgroups

Exhibit 5.13 above summarizes the total estimated numbers of illnesses and deaths each year from

ingestion of virally contaminated ground water under baseline exposure conditions. Of these illnesses and

deaths, a portion will occur in sensitive subgroups (see Exhibit 5.4). The sensitive subgroups included in

this analysis include the following:

• Immunocompromised persons in all age groups: bone marrow transplant recipients, AIDS

patients, and organ transplant patients.

• Children less than 5 years old

• Elderly adults greater 64 years old
Economic Analysis for the 5-44 October 2006

Final Ground Water Rule 

Virus Type

Health 

Effect 

Immunocompromised1 

(all ages)

Infants and 

Young 

Children 

<5 years old2

Elderly 

Adults 

>65 years 

old2

Total 

Sensitive 

Subgroups

Illness 526 11,413 23,370 35,308 

Death 0.0 0.1 0.2 0.2 

Illness 30 761 6,542 7,333 

Death 0.0 0.2 1.3 1.5 

Type A

Type B

Footnotes: 1) The immunocompromised population is estimated to account for 0.3% of the total number 

of illnesses and deaths. 2) The Immunocomprised portion has been excluded from "Infants and Young 

Children" and "Elderly" subgroups to avoid counting them twice. 

Sources: U.S. population data is from the 2000 U.S. census.

These sensitive subgroups comprise approximately 33 percent of the total exposed population

(37.7 million exposed sensitive / 114.3 million total exposed = 33%) (from Exhibits 4.4 and 5.24). The

baseline illnesses and deaths for these sensitive subgroups are shown in Exhibit 5.14. For Type B

illnesses, the high mortality rate of enteroviruses among neonates (infants less than one month old)

contributes to a higher proportion of deaths in sensitive subgroups, which account for approximately 75

percent of the echovirus deaths (1.5 / 2.0 = 75%) (Exhibits 5.13 and 5.14). For this dose response

assessment, there is no specific morbidity and mortality information for the elderly or for the

immunocompromised. Also, persons with autoimmune disorders were not included as part of the sensitive

population. Although these persons may experience severe consequences of infection, their increased

severity has not been modeled or included as part of the economic analysis.

Exhibit 5.14 Baseline Illnesses and Deaths in Sensitive Subgroups

5.2.5.4 Baseline Risk to a Highly Exposed Individual

The annual risk of illness was also estimated for a highly exposed individual. For this calculation,

it is assumed that a typical, highly-exposed individual would ingest drinking water from an untreated,

more vulnerable well contaminated by virus. The source water from such a system is assumed to be

contaminated with viral pathogens at a concentration of 40 viruses/100 L, which approximates the mean

value (41.5) of the 7 virus concentration values from the Lieberman data used for the More Vulnerable

wells. Because the source water is not disinfected, there is no inactivation of viral pathogens in the

system. This person would be a member of the age category with the highest water ingestion rate at the

75th percentile, which is 55-64 years. The 75th percentile of daily intake of drinking water for this age

group is 1.925 L/day. Annual exposure under this scenario is 49 days, based on 350 days/year

consumption from a CWS and a Psample value of 0.14, which is the 75th percentile of the expected values

from the Psample distributions. The analysis also assumes dose response parameter inputs and morbidity

factor inputs corresponding to mean values of their respective distributions.

Using these assumptions for drinking water exposure, the calculated annual probability of Type A

viral illness for a person with these characteristics is 0.30. For Type B illness, the annual probability of

illness is 0.035. These results reflect the higher infectivity of Type A viruses in comparison to the

moderately infective Type B viruses.
Economic Analysis for the 5-45 October 2006

Final Ground Water Rule 

5.2.5.5 Sensitivity of Baseline Estimates to Quantified Uncertainty Inputs

The Monte Carlo simulation model includes several inputs for which EPA has explicitly

considered uncertainty. In some cases, these values are selected from a specific distribution describing the

range and probability of particular values. In other cases, these values are selected from a set of plausible

values that have been generated using Bayesian methods as described previously. In some cases, a

particular uncertain input value is specifically related to one or more other uncertain input values.

 This section describes an analysis performed by EPA to assess the relative influence of these

inputs on the estimated annual cases of illness. The inputs fall into two general categories: occurrence

inputs and dose-response morbidity inputs.

Uncertainty in Occurrence Inputs

The key occurrence inputs to the are: Pwell, Psample distribution parameters, and Percent More

Vulnerable Wells.

The Pwell, and Psample distribution parameters used in the model are selected from a set of 10,000

values generated by a Bayesian analysis as described in Section 4.3.4.1 of Chapter 4 of the GWR EA. It is

important to note that Pwell, and Psample are selected from the dataset for input to the model as paired values. 

As described previously, there is an inverse relationship between Pwell, and the expected value of the Psample

distribution. As Pwell, increases, the expected value for Psample decreases and vice versa. Therefore, it is

necessary to select an appropriately paired set of Pwell, and Psample values as inputs to each iteration of the

model to ensure that this relationship is maintained. 

The Percent More Vulnerable parameter is sampled from uniform distributions that are determined

for each water system type and size based on acute and non-acute MCL violation data (see Section 4.3.4.2

in Chapter 4). In the risk model, the More Vulnerable wells typically have higher virus concentrations,

which are expected to result in higher numbers of infections and illnesses. Note, however, that the range

of the uniform uncertainty distributions of Percent More Vulnerable wells is relatively small (typically

0.5% to 5%), so the overall influence of this uncertainty input on the number of cases of illnesses is small

(Exhibits 5.15a-b).

Uncertainty in Dose Response Inputs 

The key dose-response inputs are the parameters for the infectivity dose-response equations and

the morbidity factors.

The infectivity dose-response relationships for Type A and Type B virus include two parameters

(alpha and beta). For the risk model input, a set of 1,000 pairs of parameters were developed for both

Type A and Type B viruses from the challenge studies (see Section 5.2.4.1 in Chapter 5). In each iteration

of the Monte Carlo simulation model, a parameter pair (alpha, beta) is selected for Type A and another is

independently selected for Type B. 

The uncertainties in the primary morbidity factors are incorporated as uniform distributions that

differ for the two virus types and by certain age groups for each virus. Since these factors are applied to

the number of cases of infection, higher morbidity factor values will result in higher cases of illness. 
Economic Analysis for the 5-46 October 2006

Final Ground Water Rule 

For Type B viruses there is also uncertainty in the secondary spread factor, which is included as a

symmetrical triangular distribution. As with the primary morbidity factors, higher values for this factor

will lead to increases in the number of illnesses estimated. 

Approach to Sensitivity Analysis

A sensitivity analysis was performed to evaluate the relative influence of the selected

uncertain inputs on the range of estimates of baseline cases of illness. Because of the complexity of the

risk assessment simulation model and the total number (2,376) of strata of well types and population age

groups, this sensitivity analysis was limited to one specific age group (20-24 year olds) served by CWSs,

but it does consider all well-types and size categories. A separate model run was performed using 100

uncertainty loop iterations and 250 inner loop iterations. The output captured the number of cases of

illness estimated for each virus for each of the 100 loops, as well as the 100 specific values selected for the

uncertain inputs in each iteration.

For the uncertain Pwell and Psample occurrence inputs, a metric was used to combine the effect of the

selected values since these inputs are linked and have an inverse relationship as described above. The

metric used was the product of Pwell and the expected value of the Psample distribution for that iteration,

referred to here as Pw*Ps. The reason for using this metric was that the product of these values reflects the

combination of the fraction of wells that are virally contaminated and the fraction of time that

contaminated wells have virus present. Higher values of Pw*Ps would be expected to result in a higher

number of cases of illness.

For the uncertain inputs for the parameters for the infectivity dose-response equations, a metric

was also used to reflect the combined effect of the alpha and beta parameters. For the selected parameters

in a given iteration, the probability of infection from an exact dose of one viral infectious unit was

computed.

For the other uncertain inputs, the actual values selected for the given iteration were used.

The Pearson Correlation Coefficient was computed based on the uncertain input values (or metric

is described above) and the estimated annual cases of illness obtained. Pearson Correlation Coefficients

are always values that fall between -1 and +1. Positive values indicate that increases in the uncertain input

values lead to increases in the estimates of cases; negative values imply that increases in the input values

lead to decreases in the estimates of cases. The larger the absolute value of the coefficient, the more

pronounced is its influence on the results.

The results obtained are summarized below and shown graphically in Exhibits 5.15a and 5.15b for

Type A and Type B viruses, respectively.

Virus Type A:

Pw*Ps: 0.323

Percent More Vulnerable Wells: 0.114

Infectivity Dose-Response Parameters: 0.531

Primary Morbidity Factor: 0.384
Economic Analysis for the 5-47 October 2006

Final Ground Water Rule 

Summary of Pearson Correlation Coefficients for Uncertain Inputs - Virus Type B

-1.00 -0.80 -0.60 -0.40 -0.20 0.00 0.20 0.40 0.60 0.80 1.00

Primary Morbidity Factor

Pw*Ps

Infectivity Dose-Response

Paramters

Secondary Spread Factor

Percent More Vulnerable Wells

Virus Type B:

Pw*Ps: 0.054

Percent More Vulnerable Wells: -0.027

Infectivity Dose-Response Parameters: 0.033

Primary Morbidity Factor: 0.114

Secondary Spread Factor: -0.025

These results indicate that for Type A viruses, the uncertainty in the dose-response parameters is

the main factor affecting the number of illnesses, while for Type B viruses it is the Primary Morbidity

Factor. It should be pointed out, however, that because the values of all of these correlation coefficients

are relatively low, none would be considered strong drivers of the outcome individually. Rather, it would

appear that it is the random combinations of multiple uncertain input factors that lead to higher (or lower)

estimates of cases of illness.

Exhibit 5.15a Summary of Pearson Correlation Coefficients for Uncertain Inputs, 

Virus Type A 
Economic Analysis for the 5-48 October 2006

Final Ground Water Rule 

Summary of Pearson Correlation Coefficients for Uncertain Inputs - Virus Type A

-1.00 -0.80 -0.60 -0.40 -0.20 0.00 0.20 0.40 0.60 0.80 1.00

Infectivity Dose-Response

Paramters

Primary Morbidity Factor

Pw*Ps

Percent More Vulnerable Wells

Exhibit 5.15b Summary of Pearson Correlation Coefficients for Uncertain Inputs, 

Virus Type B

5.2.5.6 Methodology for Estimating Risk Reductions

The methodology for estimating the reduction in risk for the regulatory alternatives builds upon

the approach and assumptions used to establish the baseline risk as described in the preceding section. The

primary difference between the modeling for estimating the baseline risk model and the modeling for

estimating the risk reduction from a given regulatory alternative is that the latter incorporates a change in

the concentration of viral pathogens reaching the finished drinking water of the exposed population. 

These changes reflect either a reduction in pathogen concentration between source water and finished

water due to disinfection or the complete elimination of the pathogen in the finished water from other

non-treatment corrective actions addressing the source water contamination. In addition to accounting for

the magnitude of pathogen exposure reduction, an important component of the risk reduction modeling is

to account for the timing of when those reductions occur over a 25 year analysis timeframe following

promulgation of the rule.

As discussed in the description of the baseline risk analysis in Section 5.2.5.1, each well in the

simulation process is designated as either having a virus present at some time or never having a virus

present based on the Pwell probability. Also, for those wells having some viral occurrence, values are

assigned for Psample and for the virus concentration. The risk reduction part of the model uses the exact

same simulated wells as those generated in the baseline risk part of the model. 
Economic Analysis for the 5-49 October 2006

Final Ground Water Rule 

For the sake of efficiency in implementing the simulation modeling process, those wells

designated as never having a virus present are recognized as having zero risk reduction potential and are

counted as such in the model outputs, but are not run through the detailed steps of the risk reduction

model.

For those wells that do have a virus present, the risk reduction model answers the following three

questions:

1) Is a corrective action performed on this well as a result of the regulatory alternative being

considered?

2) What is the finished water virus concentration following corrective action?

3) In what year following rule implementation is the corrective action performed?

The risk reduction model then processes the reduced virus concentrations through the dose

response functions for infectivity, morbidity and mortality as in the baseline risk assessment.

In the baseline risk analysis, the primary outputs are estimates of annual cases of illness and deaths

due to endemic infection from Type A and Type B viruses, and these are assumed to be the same for each

of the 25 years following rule promulgation. The outputs from the risk reduction model are the same - the

cases of illness and death that remain in each of the 25 years following rule promulgation. These are the

remaining cases each year resulting from the virus concentrations that remain after the corrective actions

are performed. The risk reductions, in terms of cases of illness and deaths avoided, are then obtained by

subtracting the cases remaining after the rule from the baseline cases.

Exhibit 5.16 shows an example of what the model might predict for a particular well with a viral

pathogen present. In this example, the baseline annual cases of illness resulting from the presence of a

pathogen in the undisinfected source water is assumed to be 1,000. The baseline risk shows these 1,000

cases each year for the 25 year period. If 4-log disinfection is implemented as a corrective action after

year 10 as a result of the rule, the remaining number of baseline cases would be 1, beginning in year 11

and continuing through year 25. The cases avoided each year for this well are, then, 0 for the first 10 years

and 999 for years 11 through 25. 
Economic Analysis for the 5-50 October 2006

Final Ground Water Rule 

Year

Baseline 

Cases

Cases 

Remaining

Cases 

Avoided

1 1,000 1,000 0

2 1,000 1,000 0

3 1,000 1,000 0

4 1,000 1,000 0

5 1,000 1,000 0

6 1,000 1,000 0

7 1,000 1,000 0

8 1,000 1,000 0

9 1,000 1,000 0

10 1,000 1,000 0

11 1,000 1 999

12 1,000 1 999

13 1,000 1 999

14 1,000 1 999

15 1,000 1 999

16 1,000 1 999

17 1,000 1 999

18 1,000 1 999

19 1,000 1 999

20 1,000 1 999

21 1,000 1 999

22 1,000 1 999

23 1,000 1 999

24 1,000 1 999

25 1,000 1 999

Exhibit 5.16 Example of Baseline Cases, Cases Remaining, and Cases Avoided

at the Well Level

Estimates of cases avoided calculated for all of the individual wells are then aggregated to arrive at

the total national estimates of risk reduction. In addition, some of the assumptions and data used in the

risk reduction model are uncertain and are therefore input as uncertainty distributions. As a result of the

uncertainty reflected in those inputs, together with the uncertainty reflected in other inputs to the baseline

risk model that are also carried into the risk reduction model, the output of the model is a range of values

of cases avoided. The range is used by EPA to determine the expected value and the 90 percent

confidence bounds on that expected value.

 The following sections describe in more detail the specific assumptions and inputs–including

considerations of uncertainty–that are used to model risk reduction for the sanitary survey and triggered

monitoring components of the GWR.
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Final Ground Water Rule 

Sanitary Surveys

The Sanitary Survey component of the rule applies to all ground water wells, including those wells

that are currently disinfecting and meeting 4-log reductions. As described in the baseline information in

Chapter 4 and in the estimation of the baseline risk, all wells are stratified into 8 major categories that

reflect the 2x2x2 (=8) combinations of the well characteristics of: Disinfecting or Nondisinfecting; More

Vulnerable or Less Vulnerable; and Proper or Improper well construction.

As discussed in Chapter 4 (Section 4.3.3), the fraction of wells considered More Vulnerable varies

from 0% to approximately 7% as a function of systems system size and type. The average (weighted by

number of systems) is that about 2.5% are in the More Vulnerable stratum (the remaining 97.5% are,

therefore, in the Less Vulnerable stratum). To estimate the benefits from correcting significant

deficiencies, each of these strata must be further defined in regards to well construction.

Construction status of a well (i.e., whether a well is properly or improperly constructed) is

estimated based on ASDWA survey data (ASDWA, 1997). Those wells identified as improperly

constructed are likely to be identified by states during a sanitary survey. Different percentages of improper

construction are estimated based on historical total or fecal coliform detections. EPA believes that a

history of detection of these contaminants is indicative of wells that fall into the More Vulnerable

classification within the benefits model. The percentages of properly and improperly constructed wells are

estimated as follows.

Less vulnerable wells - The ASDWA survey of States found that of community GWSs with no TC

or fecal coliform detections, 83.6 percent of the systems had wells that were constructed according to State

standards. Thus, 16.4 percent of systems had wells identified by State officials as not being constructed to

State standards and are considered to be improperly constructed.

More vulnerable wells - The same survey found that of community GWSs with TC detections, but

no fecal coliform detections, 217 of 277 systems had wells constructed according to State standards. A

third group consisted of systems with positive fecal coliform detections, of which 164 of 231 systems had

wells constructed according to State standards. Thus, for systems with TC or fecal coliform detections,

381 of 508 systems (75.0 percent) had wells that were constructed according to State standards. Therefore,

25.0 percent of systems had wells identified by State officials as not being constructed to State standards

and are considered to be improperly constructed.

The combination of the vulnerability and well construction estimates described above can be used

to approximate the percent of all wells having virus present that are expected to be identified and corrected

by sanitary surveys. To arrive at this estimate, the percent of all wells that are improperly constructed is

first calculated as the weighted average for the More and Less Vulnerable strata as:

• More vulnerable (2.5%), Improperly constructed (25.0%): 

 2.5% * 25.0% = 0.6%

• Less vulnerable (97.5%), Improperly constructed (16.4%): 

97.5% * 16.4% = 16.0%

The total fraction of all wells that are improperly constructed is the sum of these, which is 16.6%.
Economic Analysis for the 5-52 October 2006

Final Ground Water Rule 

 It is assumed that the sanitary survey provisions of the ground water rule will result in identifying

some (but not all) wells that are improperly constructed. It is assumed that corrective actions will be

performed on those improperly constructed wells. Specifically, EPA has estimated that for those wells that

are improperly constructed and also have a virus present, 50% will be identified and the contamination

eliminated by a corrective action. To recognize the uncertainty in this estimate of the effectiveness of

sanitary surveys, EPA has assumed a uniform distribution of 40% to 60% (mean = 50%). Therefore, as a

central value, it is expected that the sanitary survey and corrective action alternative of the rule will result

in corrective actions being performed and contamination eliminated at approximately half of the 16.6% of

all wells that are improperly constructed, which is 8.3% of all wells. Therefore, it can be estimated that

this rule alternative will result in the reduction of 8.3% of the baseline cases of illnesses and deaths per

year by the 25th year after rule promulgation.

For those wells that have virus present in the source water that are caught by a sanitary survey, the

corrective action is assumed to eliminate the virus completely. Therefore, the finished water concentration

as well as the source water concentration for these wells is set to zero for the risk reduction calculations for

those wells. While the fraction of wells corrected by sanitary survey is the same for both the disinfecting

and the nondisinfecting strata, almost all of the risk reduction (i.e., cases avoided) from sanitary surveys

will be from the nondisinfecting wells. This is because for the disinfecting wells that are currently

achieving 4-log removal, most of the virus present in the source water is already being inactivated so that

the incremental risk reduction from eliminating the source entirely is very small and contributes very little

to the total benefits achieved. Nevertheless, the risk reduction for disinfecting wells that is achieved

through sanitary surveys is calculated in the risk reduction model for completeness sake.

With respect to when this reduction in virus concentration and risk occurs, it is assumed that

identifying the (approximately) 8.3% of wells that are improperly constructed wells and performing a

corrective action on them as a result of sanitary surveys will occur across the entire 25 year analysis

period. It is assumed that no corrective actions will occur in the first three years, and that all of the

corrective actions performed will be evenly distributed across the remaining years. Therefore, in the

benefits model, each well that undergoes a corrective action from a sanitary survey is assigned a year

between year 4 and year 25 with equal probability of it occurring in any one of the years in the time

period.

Triggered Monitoring

The triggered monitoring component of the rule applies only to the nondisinfecting subset of wells

and any wells that are applying disinfectant but not achieving 4-log removal of viruses. For the wells that

are currently achieving 4-log removal, the sanitary survey requirements still apply and the output

developed in that part of the model as described above are retained for those wells 

For the triggered monitoring component of the risk reduction analysis, each well goes through a

2-step process. In the first step of the process, estimates are made of the number of TC positives–and

therefore the number of source water indicator samples–that occur during the 22 years between year 4 and

year 25 (it is assumed that no corrective actions will be taken during the first 3 years after rule

implementation). The number of TC positives expected per year for each well of a given type and size are

obtained from the DV data as described in chapter 4 (Section 4.2.7). The total number of TC positives

expected through year 25 is then calculated as the number TC positives per year times 22. If, for example,

a well is in the CWS size 10,000-50,000 category, the DV data indicate that these wells average 2.21 TC 
Economic Analysis for the 5-53 October 2006

Final Ground Water Rule 

positives per year; over 22 years, then, it is expected that these wells will have 48.6 TC positives and

therefore take up to 49 source water indicator samples between years 4 and 25.

In the second step of the process, a simulation is performed to determine which, if any, of the

indicator samples taken through year 25 is the first positive indicator result. As described in Chapter 4, in

each uncertainty loop of the risk reduction model a set of values for both virus and indicator hit rates is

selected. Included among this set of values is the probability that the first positive of an indicator will

occur on a given assay number (contingent on these assays being performed in wells that are known to

have a virus present at some time). Exhibit 4.27 showed the probability of the first indicator positive

occurring on a given assays for the median and the 5th and 95th percentiles of a sample of 1,000 of these

uncertainty sets of occurrence values. The curve for the median set of values shown in that exhibit

indicates that there is about a 40% probability that the first indicator positive will occur on or before the

49th assay. The data for each uncertainty set provides these cumulative probabilities of observing the first

positive on or before each specific assay number. In the risk reduction model, a random value between 0

and 1 is generated for each well. That value is used as a look-up value to determine what assay number

would produce the first positive. 

For example, if the curve shown as the median data set in Exhibit 4.27 were the set of values being

used for a particular uncertainty loop, and the random number between 0 and 1 generated for a well in the

CWS size 10,000-50,000 category were 0.25, the look-up function would indicate that the first indicator

positive would occur on assay number 8. Since these wells are expected to take 48.6 indicator assays over

the 22 year period, the 8th assay would occur in the 6th year (48.6 / 8 ~ 6). Since there are no samples

taken in years 1 through 3, the 6th year of sampling corresponds to year 9 of the 25 year modeling period. 

Therefore, this well would be “caught” by triggered monitoring in year 9. This prediction is then

compared to the year in which the well is captured (if it is) by the sanitary survey provisions. The

corrective action is assigned to the rule provision (SS or TM) that occurs the earliest in the 25 year period. 

If both occur in the same year, one of the two is selected randomly.

It is important to note that this analysis assumes no correlation between the occurrence of total

coliform in the distribution system and the occurrence of fecal contamination in the well water source. In

fact, the two are positively correlated in systems that do not disinfect. Bacteria in the source water of

systems that do not disinfect can directly cause total coliform positives in samples taken from the

distribution system. Although this relationship is known to exist, EPA has insufficient data to include it in

an occurrence model. As a result, only about 3% of TC positives are estimated to lead to indicator

positives in the triggered monitoring samples. The true rate of indicator positives is expected to be greater,

with more disinfecting systems taking corrective action. Not modeling the relationship between TC

positives and fecal contamination at the source contributes to underestimation of the effectiveness of

triggered monitoring. As a result, both benefits and costs (to a lesser degree) are underestimated.

Based on the number of TC positives expected per well across all well types and sizes, together

with the expected values of indicator positives as a function of assay number across all of the uncertainty

sets available to draw from for the simulation model, it can be estimated that approximately one-third
7

 The effect of taking five repeat samples for any positive indicator sample is not included in this analysis.

Based on repeat sampling, some wells will not be caught as described in this section (i.e., all repeat samples will be

negative) and benefits will not accrue to those wells. The effect of this omission is a slight overestimate of benefits,

however, the number of systems with five negative repeat samples is expected to be small. 

Economic Analysis for the 5-54 October 2006

Final Ground Water Rule 

(33%) of nondisinfecting wells with virus present should be caught and corrected by the triggered

monitoring provision of the rule by the 25th year of the modeling timeframe.7

 

Because there are some nondisinfecting wells that will be caught in the simulation model by both

sanitary survey and triggered monitoring (where the one occurring earliest is selected for corrective

action), the total wells ultimately caught by both components of this rule alternative will be less than the

sum of the two individual components (i.e., ~8.3% for SS and 27.5% for TM). The expected fraction of

nondisinfecting wells that are captured by either SS or TM can be estimated from the sum of these minus

the product (to account for the overlap):

(8.3% + 27.5%) - (8.3% * 27.5%) = 33.5%

Therefore, the SS + TM alternative should, by the 25th year after rule promulgation, result in

corrective actions being performed at approximately 33.5% of all non-disinfecting wells and 8.3% of all

(4-log) disinfecting wells that have virus present in their source water. Because most of the baseline risk

is found in nondisinfecting wells, it is also, therefore, expected that this rule will result in approximately a

33.5% reduction in the baseline cases of illness and death.

5.2.5.7 Results for Risk Reduction for the Final GWR

The final GWR, the risk targeted approach, includes sanitary surveys, triggered monitoring,

corrective action, and compliance monitoring. The estimated reduction in illnesses and deaths are

presented by system size and type in Exhibit 5.17 and in summary in Exhibit 5.18. These values are the

annual average cases avoided across the 25 year analysis timeframe, and they include the initial three years

after implementation when no corrective actions are performed as a result of sanitary surveys or triggered

monitoring.

Exhibit 5.19 provides a summary of the estimated cases avoided per year in the 25th year following

rule implementation. This summary provides an indication of the magnitude of the annual benefits that

can ultimately be achieved by the GWR. The cases of illness avoided shown here, 41,868, 

represent an approximately 22.6% reduction of baseline cases of 185,186 shown in Exhibit 5.13. A

detailed breakdown of illnesses and deaths avoided by age group is presented in Appendix B.
Economic Analysis for the 5-55 October 2006

Final Ground Water Rule 

Illnesses Deaths Illnesses Deaths Illnesses Deaths

A B C D E=A+C F=B+D

338 0.00 26 0.01 363 0.0

783 0.01 57 0.01 840 0.0

752 0.00 55 0.01 807 0.0

1,844 0.01 132 0.03 1,977 0.0

4,619 0.03 327 0.06 4,946 0.1

4,394 0.03 338 0.07 4,732 0.1

8,832 0.06 582 0.12 9,414 0.2

8,336 0.06 615 0.12 8,951 0.2

0 0.00 0 0.00 0 0.0

29,900 0.20 2,131 0.42 32,031 0.6

134 0.00 6 0.00 141 0.0

428 0.00 19 0.00 447 0.0

395 0.00 22 0.00 416 0.0

489 0.00 35 0.01 524 0.0

241 0.00 14 0.00 255 0.0

151 0.00 8 0.00 159 0.0

52 0.00 3 0.00 55 0.0

93 0.00 4 0.00 97 0.0

0 0.00 0 0.00 0 0.0

1,983 0.01 111 0.02 2,094 0.0

1,806 0.01 40 0.01 1,846 0.0

2,555 0.02 62 0.01 2,617 0.0

1,081 0.01 30 0.01 1,111 0.0

913 0.01 24 0.01 937 0.0

469 0.00 12 0.00 481 0.0

491 0.00 11 0.00 501 0.0

75 0.00 1 0.00 76 0.0

170 0.00 3 0.00 173 0.0

0 0.00 0 0.00 0 0.0

7,560 0.05 184 0.04 7,743 0.1

39,442 0.26 2,426 0.48 41,868 0.7

Source: Appendix B

Note: Detail may not add to totals due to independent rounding. The figures presented in this exhibit represent only the 

quantifiable benefits of the GWR. The unquantified benefits are expected to comprise a significant portion of the overall 

benefits of the Final Rule and are presented in Section 5.4.

Type B Viruses

<100

101-500

Type A Viruses

501-1,000

1,001-3,300

3,301-10K

10,001-50K

50,001-100K

100,001-1M

>1 Million

All Sizes

50,001-100K

<100

101-500

501-1,000

<100

101-500

501-1,000

1,001-3,300

>1 Million

All Sizes

Total

3,301-10K

10,001-50K

50,001-100K

100,001-1M

Total

Community Water Systems (CWSs)

Nontransient Noncommunity Water Systems (NTNCWSs)

Transient Noncommunity Water Systems (TNCWSs)

100,001-1M

>1 Million

All Sizes

1,001-3,300

3,301-10K

10,001-50K

Exhibit 5.17 Annual Viral Illnesses and Deaths Avoided for the GWR by System

Size and Type
Economic Analysis for the 5-56 October 2006

Final Ground Water Rule 

Mean 5th Percentile 95th Percentile Mean 5th Percentile 95th Percentile

Type A 10,093 39,442 79,925 0.3 0.1 0.5 

Type B 181 2,426 8,114 0.5 0.0 1.6 

Total 10,274 41,868 88,039 0.7 0.1 2.1 

Illnesses per Year Deaths per Year Virus type

Mean 5th Percentile 95th Percentile Mean 5th Percentile 95th Percentile

Type A 59,126 15,387 121,578 0.4 0.1 0.8 

Type B 3,583 259 12,372 0.7 0.0 2.4 

Total 62,709 15,646 133,951 1.1 0.1 3.2 

Illnesses per Year Deaths per Year Virus type

Exhibit 5.18 Summary of Annual Viral Illnesses and Deaths Avoided for the GWR

Note: Details may not add to totals due to independent rounding and independent statistical analyses.

Source: Appendix B

Exhibit 5.19 Viral Illnesses and Deaths Avoided in the 25th Year 

after Implementation of the GWR

Note: Details may not add to totals due to independent rounding and independent statistical analyses.

Source: Appendix B

5.2.5.8 Results for Reduction in Individual Risks for the Final GWR

Exhibits 5.20a and 5.20b present the distributions of individual annual risks of infection for the

population using ground water for Type A and Type B viruses, respectively. These graphs show the risks

separately for individuals consuming water from CWS, NTNCWS and TNCWS systems. Baseline risks

and annual risks following the full implementation (25 years) of the rule alternatives are presented. Note

that curves that are further to the right indicate more risk, those to the left indicate less risk.

In general, the graphs show a relatively small reduction in individual risk from the Sanitary Survey

and Corrective Action alternative, somewhat larger risk reductions for the Risk Targeted and Multi-Barrier

alternatives, and substantially greater reductions for the 4-log across-the-board disinfection alternative. 

These changes in individual risk track well with the estimated reductions in annual cases of illness and

deaths for the various rule alternatives presented in previous sections. In addition, the annual individual

infection risks are substantially higher for Type A than Type B viruses, which corresponds to the

differences in the dose response functions for the two types of viruses.

Also note that these graphs imply that the annual individual baseline risks for CWS consumers is

lower than that for the noncommunity water systems, and that individual risk for NTNCWSs is slightly

higher than that for TNCWSs. This can be understood in terms of the differences in current disinfection

and differences in water consumption days and amounts. (Virus occurrence is assumed to be the same in

all system types in the primary analysis.) Although there is more water consumption both in terms of days

of consumption and volume per day per individual in CWSs than in either NTNCWS or TNCWS (which

would tend to push individual risk up), a much larger portion of the CWS wells are currently disinfecting

than the NTNCWS or TNCWS wells, which pushes the overall individual risk distribution for CWS down. 

Between NTNCWSs and TNCWSs, both the percent of wells disinfecting and water consumption are
Economic Analysis for the 5-57 October 2006

Final Ground Water Rule 

lower in the TNCWSs than in NTNCWSs and this is reflected in the comparing these baseline graphs. 

(Note that for the 4-log rule alternative which results in all wells in all system types being disinfected, a

comparison of the risk curves across the three types of systems shows the greatest risk in CWS, slightly

less in NTNCWS, and much less in TNCWS. This is because with this alternative, only differences in

water consumption days and volume per day drive the individual risk levels for consumers at these

different systems types.
Economic Analysis for the 5-58 October 2006

Final Ground Water Rule 

CWS

90%

91%

92%

93%

94%

95%

96%

97%

98%

99%

100%

1.00E-08 1.00E-07 1.00E-06 1.00E-05 1.00E-04 1.00E-03 1.00E-02 1.00E-01 1.00E+00

Annual Individual Risk of Infection

Percent of Population Below Indicated Risk

Baseline

SS

SSTM

SSRM

4-log

NTNCWS

90%

91%

92%

93%

94%

95%

96%

97%

98%

99%

100%

1.00E-08 1.00E-07 1.00E-06 1.00E-05 1.00E-04 1.00E-03 1.00E-02 1.00E-01 1.00E+00

Annual Individual Risk of Infection

Percent of Population Below Indicated Risk

Baseline

SS

SSTM

SSRM

4-log

TNCWS

90%

91%

92%

93%

94%

95%

96%

97%

98%

99%

100%

1.00E-08 1.00E-07 1.00E-06 1.00E-05 1.00E-04 1.00E-03 1.00E-02 1.00E-01 1.00E+00

Annual Individual Risk of Infection

Percent of Population Below Indicated Risk

Baseline

SS

SSTM

SSRM

4-log

Exhibit 5.20a Comparison of Average Annual Individual Infectivity Risk

Distributions for Baseline and Rule Alternatives for Type A Viruses
Economic Analysis for the 5-59 October 2006

Final Ground Water Rule 

CWS

90%

91%

92%

93%

94%

95%

96%

97%

98%

99%

100%

1.00E-08 1.00E-07 1.00E-06 1.00E-05 1.00E-04 1.00E-03 1.00E-02 1.00E-01 1.00E+00

Annual Individual Risk of Infection

Percent of Population Below Indicated Risk

Baseline

SS

SSTM

SSRM

4-log

TNCWS

90%

91%

92%

93%

94%

95%

96%

97%

98%

99%

100%

1.00E-08 1.00E-07 1.00E-06 1.00E-05 1.00E-04 1.00E-03 1.00E-02 1.00E-01 1.00E+00

Annual Individual Risk of Infection

Percent of Population Below Indicated Risk

Baseline

SS

SSTM

SSRM

4-log

NTNCWS

90%

91%

92%

93%

94%

95%

96%

97%

98%

99%

100%

1.00E-08 1.00E-07 1.00E-06 1.00E-05 1.00E-04 1.00E-03 1.00E-02 1.00E-01 1.00E+00

Annual Individual Risk of Infection

Percent of Population Below Indicated Risk

Baseline

SS

SSTM

SSRM

4-log

Exhibit 5.20b Comparison of Average Annual Individual Infectivity Risk

Distributions for Baseline and Rule Alternatives for Type B Viruses
Economic Analysis for the 5-60 October 2006

Final Ground Water Rule 

5.2.5.9 Potential Increases in Health Risks

It is unlikely that the GWR will result in a significant increase in risk from other contaminants,

although adding disinfection to currently non-disinfecting systems could result in some increased risk. 

When disinfection is first introduced into a previously undisinfected system, the disinfectant can react with

pipe scale causing increased risk from some contaminants and water quality problems. Contaminants that

could be released include lead, copper, and arsenic. It could also possibly lead to a temporary

discoloration of the water as the scale is loosened from the pipe. These risks can be addressed by

gradually phasing in disinfection to the system, by targeted flushing of distribution system mains, and by

maintaining a proper corrosion control program.

Using a chemical disinfectant could also result in an increased risk from disinfection byproducts

(DBPs). Risk from DBPs has already been addressed in the Stage 1 Disinfection Byproducts Rule (DBPR)

(USEPA, 1998d) and additional consideration of DBP risk has been addressed in the recently published

final Stage 2 DBPR (USEPA, 2006e). In general, GWSs are less likely to experience high levels of DBPs

than surface water systems, because they have lower levels of naturally occurring organic materials

(generally represented by total organic carbon (TOC)) that contribute to DBP formation. For the most

part, GWSs with high levels of TOC in their ground water source are located in States that already require

GWSs to disinfect, therefore decreasing the chance that significant disinfection byproduct problems would

result from this rule.
8

 See Appendix B of EPA’s Handbook for Non-Cancer Health Effects Valuation (USEPA, 2000c) for a review of these

studies.

Economic Analysis for the October 2006

Final Ground Water Rule 5-61

5.3 Monetized Benefits from Reduction in Exposure to Waterborne Pathogens

Once the annual illnesses and deaths avoided as a result of the GWR implementation are

estimated using the risk model described in the previous sections, monetary unit values can be applied to

these estimates to establish the monetary benefits attributable to the rule. As discussed earlier, only a

portion of the illnesses and deaths avoided are quantified. Further, the only benefits estimated and

monetized for the main analysis in this EA are acute health effects of viral infections. The following

sections explain how the value of reductions in illnesses and deaths was derived and presents results of

the monetized benefits calculations.

5.3.1 Value of Reduction in Type A and Type B Virus Cases

5.3.1.1 Value of Viral Illnesses Avoided

The goal of this analysis is to provide as complete an accounting as possible of the social welfare

impacts of the regulatory requirements under consideration. Based on the principles of welfare

economics, the preferred approach for valuing reductions in the risk of Type A and Type B virus

morbidity is to rely on estimates of willingness to pay (WTP) for these risk reductions. However, there

are no direct studies of WTP for avoided morbidity from the viral illnesses considered in the benefits

analysis. As a minimum estimate of that value, this analysis estimates the value of averted morbidity

risks based on the (1) avoided medical costs and (2) the value of avoided time losses for the illness they

cause. The rationale for and limitations of this approach are discussed below, and greater detail is

provided in Appendix A.

The calculation of medical costs includes the costs of medical services and medications received

by ill individuals. The assumption behind using these costs as a benefit measure is that a policy that

reduces the incidence of illness will yield benefits at minimum equal to the costs avoided. Cost of illness

(COI) estimates, however, may significantly underestimate individual willingness to pay for a variety of

reasons. In particular, these estimate do not: (1) address the value of avoiding pain and suffering; (2)

include costs that individuals incur to avoid the illness (i.e., defensive or averting expenditures); (3)

reflect aversion to risk (the fear of becoming ill); (4) consider ex ante values (they are based on ex post

costs); and (5) consider whether treatment returns individuals to their original health state (i.e., is

equivalent to avoiding the illness entirely).

A number of researchers have explored the relationship between the COI and individual WTP for

risk reductions. This research suggests that the ratio of these two types of values varies greatly depending

on the nature of the health effect, the characteristics of the individuals studied, and the factors included in

the construction of each estimate. Comparison studies result in WTP to COI ratios ranging from about a

factor of 2 to as much as a factor of 79 (in one case); many of the ratios are between 3 and 6.8

 In other

words, the COI estimates were typically one-third to one-sixth of the WTP estimates, but the ratio varied

greatly.
9

 Paid care is included in the medical cost component of the analysis and hence is not discussed in the

discussion of time losses.

Economic Analysis for the October 2006

Final Ground Water Rule 5-62

In some cases, COI studies include indirect, as well as direct costs. These indirect costs usually

include lost earnings due to missed market work time, and may also include costs associated with reduced

productivity while at work and/or lost nonmarket work time (e.g., child care or housekeeping). 

Typically, these costs are estimated using the human capital approach, which focuses on the value of

goods and services that are bought and sold in the marketplace and ignores other aspects of time use that

affect individual well-being.

The analysis of Type A and Type B virus-related morbidity uses two measures of the

COI–referred to in this EA as Traditional and Enhanced. Both approaches include direct medical costs

and the value of lost work time, but differ in the assessment of value of lost work time. They both

consider the impact of time losses on foregone market production, which affects the individual worker

(e.g., in terms of lost income) as well as other members of society (who benefit from the availability of

the goods or services produced as well as the taxes paid), and foregone nonmarket (household and

volunteer) production, which affects the individual and other household members and often has impacts

outside the home. The Traditional COI includes nonmarket (unpaid) work time based on replacement

costs and does not include a value for the time lost of children under 16 years of age. The other approach,

the Enhanced COI, values nonmarket work time based on opportunity costs and places a value on the lost

time of children. Both approaches also include values for the nonmarket time lost by friends or family

members caring for those who are sick,9

 but the approaches use different values for this lost time. 

The Enhanced COI also includes the value of lost leisure time and lost productivity—the reduced

utility (or sense of well-being) associated with decreased enjoyment of time spent in both market and

nonmarket activities. The Enhanced COI is an attempt to more completely measure the loss of welfare

from an illness.

A search of the literature suggests that researchers have not attempted to estimate directly (e.g.,

through surveys) the difference between the value of time in a well state compared to time in an ill state. 

This analysis relies instead on wage and compensation data to estimate the opportunity costs of time

usage. This approach recognizes that, because resources are limited, any decision to use resources for one

purpose means that they cannot be used for other purposes. One minimal measure of the value of a

resource, therefore, is the value of its next best use.

The application of the opportunity cost approach to paid work time is relatively clear, since

compensation can be used to estimate these costs. For other (unpaid) time spent in nonmarket work or

leisure activities, wage data are also used based on the assumption that (at the margin) the wage

represents the opportunity cost of engaging in such activities.

More precisely, lost market work is valued at the median gross (pre--tax) wage rate plus benefits,

also referred to as total compensation or employer’s costs. This approach is most representative of the

full social impact of lost work because it incorporates both the loss to the individual in terms of lost

income and the loss to society in terms of reduced tax revenue or decreased production of goods and

services. Lost nonmarket work and leisure time is valued at the median net (post-tax) wage rate. This

approach reflects the assumption that, at the margin, an individual will choose to engage in nonmarket

work or leisure activities only if the value of these activities exceeds the wage rate that the individual
10 There are a number of other simplifying assumptions inherent in the application of this approach that

may lead it to under- or overstate the value of time losses, related to factors such as the functioning of the labor

market, the treatment of individuals who are not labor force participants, the use of average or median (rather than

marginal) earnings data, and the possibility that substitute activities (e.g., watching TV instead of normal activities)

have some positive value. It is unclear whether, in total, these practical limitations serve to increase or decrease the

bias that results from the sources discussed in this paragraph.

Economic Analysis for the October 2006

Final Ground Water Rule 5-63

would otherwise earn. Sleep time presents special problems in this analysis, both because data on the

effect of Type A and Type B virus--related morbidity on the amount or quality of sleep time is not

available and because current literature on valuing lost time has not settled on an accepted valuation

method. This analysis, thus, conservatively assumes that lost sleep time has zero value.

These values are applied to both complete losses of time (time spent in illness-related activities

rather than normal activities) as well as to partial losses (time spent in normal activities that is less

productive or pleasurable than in the absence of illness). In the latter case, however, the dollar value of

the loss is prorated to reflect the fact that the individual does not completely lose the productivity or

utility associated with the activity. These values are applied to such time losses incurred by the ill

individual.

The use of medical costs and the opportunity cost of time losses to value morbidity related to

Type A and Type B viruses may understate the value of these risk reductions for a variety of reasons.10

As noted earlier, COI estimates generally understate WTP for a variety of reasons, e.g., because they

exclude consideration of the value of avoided pain and suffering or of risk aversion. In addition, the use

of wage and compensation data to value lost time may understate the utility of time spent in its preferred

use. The use of wage rates may understate the total utility associated with an activity even in the case of

paid work, because individuals may derive intrinsic pleasure from the activity above and beyond the

income they receive. For nonmarket work and leisure, the value of the activity to the individual may

exceed the opportunity cost for similar reasons. In addition, nonmarket work and other activities can

provide benefits to other members of society that are not reflected in the individual wage rate. Finally,

this approach does not include the value of lost sleep time.

In addition, relying on wage data for valuing lost time presents difficulties in the case of

individuals for whom these data are not available, such as children, the unemployed, and those out of the

labor market. For the Enhanced COI approach, all lost time of children is valued at the median post-tax

wage rate. No estimates exist, however, for the indirect cost of illness. EPA transferred the method used

for days lost due to illness (equal to the duration of illness) to children. EPA further assumes that a

caretaker stays home with these children, introducing additional lost caretaker days. The rationale for this

approach is discussed in more detail below. It is unclear whether this approach under- or overstates the

value of time losses for the individuals in these other categories, given the available information on these

values. However, the Agency’s Children’s Health Valuation Handbook states: “To the extent that a

caregiver is more likely to be involved when a child is recuperating, the total value of lost time is likely to

be higher for a child’s illness than for an adult’s.” (USEPA, 2002)

COI Calculations

The primary risk of illness that the GWR addresses is from endemic exposure to Type A and

Type B viruses and the resulting acute cases of illnesses. Many elements of the COI come from a
Economic Analysis for the October 2006

Final Ground Water Rule 5-64

literature review of current medical studies; other elements have been assumed. The literature review

yielded information on the duration of illness from Type A and Type B viruses, the type of medical care

sought, if any, and the costs associated with these services. The data from the literature review, as well as

assumptions made in this analysis, are described in Appendix A.

The computation of COI involves two broad categories of costs—direct and indirect medical

costs. All costs are updated to a common year (2003) used as the starting point for projecting benefits

into future time periods. For Type A viruses, each cost component has a separate estimate made based on

age and the health state of the individual (healthy or immunocompromised). For Type B viruses, cost

components have separate estimates based both on age and on the type of care required: no medical care

(93% of cases); outpatient care (6% of cases); or inpatient care (1% of cases). Detail on these breakouts

is also provided in Appendix A. The next two subsections discuss the details of the computations used to

derive direct and indirect medical costs.

Direct Medical Costs

For both the Enhanced COI and Traditional COI, the cost for a case of Type A or Type B viral

illness is derived by summing the costs of outpatient and inpatient care. Outpatient care consists of an

initial physician visit ($114.55) and product of the cost of each follow-up visit ($66.18) and the number

of follow-up visits. Multiplying this sum by the percentage of patients that utilize outpatient services

yields the weighted unit cost of outpatient care. The cost of inpatient care consists of the costs of the

initial doctor visit in the hospital ($152.87), any follow-up visits ($52.25), and the hospital charges

(calculated on a per day basis, with costs ranging from $1,007 per day to $4,870 per day). As with

outpatient costs, multiplying the sum of doctor visits and hospital charges by the percentage of patients

who require inpatient care yields the weighted unit cost of inpatient care. The sum of the weighted unit

costs of outpatient and inpatient care equals the weighted direct costs.

Exhibits 5.21a – 5.21b and 5.22a – 5.22b show the weighted direct medical costs per case of Type

A viral illness, ranging from an average cost of $0 (for healthy patients, 5 years or older) to an average

cost of $4,486 (for immunocompromised patients younger than 5 years old). The weighted direct medical

costs per case of Type B viral illness (Exhibits 5.21c–5.21e and 5.22c–5.22e) range from an average of $0

(for patients requiring no medical care) to $23,431 (for patients less than 1 year old requiring inpatient

care). Costs for doctor visits, follow-up visits, and hospital stays constitute the direct medical costs. 

Costs for initial and follow-up doctor visits are obtained in 2000 dollars and updated to 2003 dollars using

the consumer price index (CPI) for medical care services.
Economic Analysis for the October 2006

Final Ground Water Rule 5-65

Symptom duration--

reported days (range) [A]

Direct Costs

Outpatient costs

Initial physician visit [B]

Average # of follow-up visits [A]

Cost per follow-up [B]

$115 - $710 $115 - $710 

Percent Outpatient [A]

$16 - $101 $16 - $99 

Inpatient costs

Duration of hospital stay (days) [A]

Hospital cost per day [B]

Total hosptial cost [C]

Initial physician visit [B]

Average # of follow-up visits [A]

Cost per follow-up [B]

Total Unit Cost [C]

Percent Inpatient [A]

Weighted Unit Cost [C]

$16 - $101 $16 - $99 $0 - $0 $0 - $0 

Indirect Costs

Value of lost patient day [D]

Lost patient days (No Medical 

Care/Outpatient) [A]

Lost patient days (Inpatient) [A]

Value of caregiver day [D]

Caregiver days (No Medical 

Care/Outpatient) [A]

Caregiver days (Inpatient) [A]

Value of lost productivity day [E]

Lost productivity days [A]

Total Indirect Costs [C]

$1,310 - $1,395 $1,309 - $1,393 

1.5

1 (15.3%), 0 (84.7%)

[Note 1]

$641 $103 

0

5

$1,293

$1,390

3

[C]

$68.34

$641 

0

$59.81

$103 

1

$59.81 $59.81

$66.18

$1,007.19

$76

0

N/A N/A

$1,007.19

$97

$152.87

4 

5 

[C]

$114.55

0.5

(0-9)

$66.18

5 

$52.25

1.4%

$5,398

$148

Cost Category 2003$

Average Cost Per Patient

<2 years 2 to 4 years 5 to 15 years >16 years

Weighted Unit Cost

$21

$148

$21

14%

[C]

[C]

14%

Total Unit Cost

$152.87

Total Cost of Illness

$5,036 $4,029

$61

Total Weighted Direct Costs

$82 

3

0

$227.79

3

$114.55

0.5

(0-9)

2.5

$114.55

N/A

3

N/A

$66.18

$1,293

$1,376 

$199.36

5

$227.79

5

1.4%

$66.18

1.5

$227.79

$227.79

N/A

$227.79

$199.36 $199.36

5

3 3

4 

$0 

$4,391

$52.25

$0 

$52.25

N/A

$0

$4,338

$0

N/A

$1,007.19

$52.25

$4,029

0.0%

$4,338

0.0%

$4,029

$152.87

N/A

$115 

$0 

0.0%

$152.87

N/A

$1,007.19

$115 

0.0%

$0 

N/A

3

$114.55

Exhibit 5.21a Estimates for Average Cost and Average Cost per Healthy Patient

of Type A Illness, by Age (Enhanced COI)

Note 1: For the healthy population >16 years, the severity of symptom manifestation is dependent on the rotavirus

strain and can be divided into two groups. The G2 & G9 strains represent 15.3% of illnesses, while all other strains

comprise the remaining 84.7%. 

Sources:

[A] Appendix A, Exhibit A.1

[B] Appendix A, Exhibit A.2

[C] Calculations based on data presented in the table.

[D] Appendix A, Exhibit A.7

[E] Weighted average per day value of time ($227.79) multiplied by percent loss productivity (30 percent, rounded

from Harrington et al. 1991)
Economic Analysis for the October 2006

Final Ground Water Rule 5-66

Exhibit 5.21b Estimates for Average Cost and Average Cost per

Immunocompromised Patient of Type A Illness, by Age (Enhanced COI)

Sources:

[A] Appendix A, Exhibit A.1

[B] Appendix A, Exhibit A.2

[C] Calculations based on data presented in the table.

[D] Appendix A, Exhibit A.7

[E] Weighted average per day value of time ($227.79) multiplied by percent loss productivity (30 percent, rounded

from Harrington et al. 1991)

Symptom duration--

reported days (range) [A]

Direct Costs

Initial physician visit [B]

Average # of follow-up visits [A]

Cost per follow-up [B]

$115 - $710 $115 - $710 

Percent Outpatient [A]

$115 - $710 $115 - $710

Inpatient costs

Duration of hospital stay (days) [A]

Hospital cost per day [B]

Total hosptial cost [C]

Initial physician visit [B]

Average # of follow-up visits [A]

Cost per follow-up [B]

Total Unit Cost [C]

Percent Inpatient [A]

Weighted Unit Cost [C]

$4,453 - $5,049 $4,453 - $5,049

Indirect Costs

Value of lost patient day [D]

Lost patient days [A]

Value of caregiver day [D]

Caregiver days [A]

Value of lost productivity day [E]

Lost productivity days [A]

Total Indirect Costs [C]

Total Cost of Illness $6,589 - $7,184 $5,734 - $6,330

$6,622 $5,767 

[C]

$227.79

0

$68.34

0

$2,136 $1,281 $1,281 $569

$4,338

Total Weighted Direct Costs

$4,486 $4,486 

[C]

$4,338 $4,338 $4,338

100%

Total Unit Cost

$148 $148

$4,029 $4,029 $4,029 $4,029

Weighted Unit Cost

$148 $148

$115 

$227.79

2.5

$4,338

100%

$52.25 $52.25

$4,338

$199.36

$115 $115

$115

$4,338

$52.25 $52.25

2 2 

$1,007.19

5

0

$59.81

3

$227.79

3

0

$199.36

3

100%

$199.36

$4,453 

100%

4 2 

$4,338

$152.87 $152.87 $152.87 $152.87

$1,007.19 $1,007.19 $1,007.19

5 3 3 2.5

100% 100% 100.0% 100.0%

0

$66.18 $66.18 $66.18 $66.18

Outpatient costs

0.5

(0-9)

0.5

(0-9) 0

3 3

Average Cost Per Patient

2003$

<2 years 2 to 4 years 5 to 15 years >16 years

2.5

[C]

[C]

Cost Category

5

$114.55 $114.55 $114.55 $114.55

$4,453 

$5,734 $5,022 

$227.79

5

$59.81

0

$227.79

3

$59.81
Economic Analysis for the October 2006

Final Ground Water Rule 5-67

5 to 15 years >16 years

Symptom duration--

reported days (range) [A] 3 (1-6) 3 (1-6)

Direct Costs

Outpatient costs

Initial physician visit [B] NA NA

Average # of follow-up visits [A] NA NA

Cost per follow-up [B] NA NA

Total Unit Cost [C] NA NA

Percent Outpatient [A] 0.0% 0.0%

Weighted Unit Cost [C] $0.00 $0.00

Inpatient costs

Duration of hospital stay [A] NA NA

Hospital cost per day NA NA

Total hosptial cost NA NA 

Initial physician visit NA NA 

Average # of follow-up visits [A] NA NA

Cost per follow-up NA NA 

Total Unit Cost NA NA 

Percent Inpatient [A] 0% 0%

Weighted Unit Cost [C] $0.00 $0.00 

 Total Weighted Direct Costs [C] $0 $0 

Indirect Costs

Value of lost patient day [D] $199.36 $227.79 

Lost patient days [A] 1.5 1.15

Value of caregiver day [D] $227.79 $227.79 

Caregiver days [A] 1.5 0

Value of lost productivity day [E] $59.81 $68.34 

Lost productivity days [A] 0 1.09

$427 - $2,563 $427 - $2,563 

$427 - $2,563 $427 - $2,563 

Average Cost per Patient

2003$

<1 Year 1 to 4 years

NA

NA

Total Indirect Costs1

3 (1-6)

NA

$0.00

3 (1-6)

Total Cost of Illness

$1,281

NA

NA

NA

NA

NA

NA

NA

0.0%

$0.00

NA

0.0%

NA

NA NA

NA

0%

 NA 

 NA 

$0.00

NA NA 

NA NA

 NA 

0%

$0.00 

$0 

3 (1-6) 3 (1-6)

$0 

3 (1-6) 3 (1-6)

$199.36 $199.36

$641 $336

$641 $336

$1,281 $1,281 

$1,281

Cost Category

[C]

[C]

0

$59.81 $59.81

0

$227.79 $227.79

Exhibit 5.21c: Estimates for Average Cost and Average Cost per Case of Type B

Illness Requiring No Medical Care, by Age (Enhanced COI)

1 Total Indirect Costs is shown as a range for those age categories for which the duration of symptoms, and hence

lost patient days, was a range determined from best available data.

Sources:

[A] Appendix A, Exhibit A.3

[B] Appendix A, Exhibit A.4

[C] Calculations based on data presented in the table

[D] Appendix A, Exhibit A.7,E] Weighted average per day value of time ($227.79) multiplied by percent loss

productivity (30 percent, rounded from Harrington et al. 1991)NA: Not applicable to mild cases.
Economic Analysis for the October 2006

Final Ground Water Rule 5-68

Exhibit 5.21d Estimates for Average Cost and Average Cost per Case of Type B

Illness Requiring Outpatient Care, by Age (Enhanced COI)

Sources:

[A] Appendix A, Exhibit A.3

[B] Appendix A, Exhibit A.4

[C] Calculations based on data presented in the table.

[D] Appendix A, Exhibit A.7

[E] Weighted average per day value of time ($227.79) multiplied by percent loss productivity (30 percent, rounded

from Harrington et al. 1991)

* No data available

Symptom duration--

reported days (range) [A]

Direct Costs

Outpatient costs

Initial physician visit [B]

Average # of follow-up visits [A]

Cost per follow-up [B]

Total Unit Cost [C]

Percent Outpatient [A]

Weighted Unit Cost [C]

Inpatient costs

Duration of hospital stay [A]

Hospital cost per day [B]

Total hosptial cost [C]

Initial physician visit [B]

Average # of follow-up visits [A]

Cost per follow-up [B]

Total Unit Cost [C]

Percent Inpatient [A]

Weighted Unit Cost [C]

 Total Weighted Direct Costs [C] 

Indirect Costs

Value of lost patient day [D]

Lost patient days [A]

Value of caregiver day [D]

Caregiver days [A]

Value of lost productivity day [E]

Lost productivity days [A]

$ 854 - $ 5,126 $ 854 - $ 4,272 $ 854 - $ 2,990 $456 - $2,050

$ 1,035 - $ 5,307 $ 1,035 - $ 4,452 $ 1,035 - $ 3,171 $ 636 - $ 2,231

Average Cost per Patient

2003$

<1 Year 1 to 4 years 5 to 15 years >16 years

5 (2-9)

$114.55 $114.55

5 (2-12) 5 (2-10) 5 (2-7)

$114.55

1

$66.18

$181

100% 100.0%

1

$66.18

$181

100%

$114.55

1

$66.18

$181

1

$66.18

$181

100.0%

$181

NA NA NA NA

$181 $181 $181

NA

NA

NA NA NA

NA NA NA

NA NA

NA

NA NA NA NA

NA NA NA

$199.36

5 (2-12)

NA NA

0% 0% 0% 0%

NA NA NA

$0.00 $0.00 $0.00 $0.00

NA

$1,139

$181

$68.34

0

$227.79

5 (2-9)

$227.79

0

$227.79 $227.79

Total Indirect Costs

$2,136 $2,136 $2,136

$59.81

0

$181

5 (2-10)

$59.81

0

5 (2-12)

$59.81

0

$181

$227.79

5 (2-7)

$199.36

5 (2-10)

$199.36

5 (2-7)

$2,316 $1,320 

Cost Category

[C]

Total Cost of Illness [C]

$2,316 $2,316 

$181
Economic Analysis for the October 2006

Final Ground Water Rule 5-69

Exhibit 5.21e Estimates for Average Cost and Average Cost per Case of Type B

Illness Requiring Inpatient Care, by Age (Enhanced COI)

Sources:

[A] Appendix A, Exhibit A.3

[B] Appendix A, Exhibit A.4

[C] Calculations based on data presented in the table.

[D] Appendix A, Exhibit A.7

[E] Weighted average per day value of time ($227.79) multiplied by percent loss productivity (30 percent, rounded

from Harrington et al. 1991)

* No data available

Symptom duration--

reported days (range) [A]

Direct Costs

Outpatient costs

Initial physician visit [B]

Average # of follow-up visits [A]

Cost per follow-up [B]

Total Unit Cost [C]

Percent Outpatient [A]

Weighted Unit Cost [C]

Inpatient costs

Duration of hospital stay-- 

reported days [A]

Hospital cost per day [B]

Total hosptial cost [C]

Initial physician visit [B]

Average # of follow-up visits [A]

Cost per follow-up [B]

Total Unit Cost [C]

Percent Inpatient [A]

Weighted Unit Cost [C]

 Total Weighted Direct Costs [C] 

Indirect Costs

Value of lost patient day [D]

Lost patient days [A]

Value of caregiver day [D]

Caregiver days [A]

Value of lost productivity day [E]

Lost productivity days [A]

$ 854 - $ 5,980 $ 854 - $ 5,980 $ 854 - $ 5,980 $456 - $3,189 

$ 24,285 - $ 29,411 $ 10,041 - $ 15,167 $ 5,890 - $ 11,016 $ 5,492 - $ 8,225 

$8,026 $6,631 

Cost Category

[C]

Total Cost of Illness [C]

$26,421 $12,177 

$9,187 $5,036

$227.79

7 (2-14)

$199.36

7 (2-14)

$199.36

7 (2-14)

$59.81

0

$5,036

7 (2-14)

$59.81

0

7 (2-14)

$59.81

0

Total Indirect Costs

$2,990 $2,990 $2,990 $1,595

$23,431

$68.34

0

$227.79

7 (2-14)

$227.79

0

$227.79 $227.79

$23,250 $4,855

$23,250 $9,006 $4,855 $4,855

$4,855

$199.36

7 (2-14)

$52.25 $52.25

100% 100% 100% 100%

$9,006

$52.25 $52.25

$152.87

4 4 22

$152.87 $152.87 $152.87

$1,839.15

$4,598

$4,869.90 $1,839.15 $1,839.15

$22,889 $8,644 $4,598

100.0%

$181

4.7 4.7 2.5 2.5

$181 $181 $181

$66.18

$181

1

$66.18

$181

1

$66.18

$181

100% 100.0%

1

$66.18

$181

100%

1

7 (2-14)

$114.55 $114.55

7 (2-14) 7 (2-14) 7 (2-14)

$114.55 $114.55

Average Cost per Patient

2003$

<1 Year 1 to 4 years 5 to 15 years >16 years
Economic Analysis for the October 2006

Final Ground Water Rule 5-70

Symptom duration--

reported days (range) [A]

Direct Costs

Outpatient costs

Initial physician visit [B]

Average # of follow-up visits [A]

Cost per follow-up [B]

$115 - $710 $115 - $710 

Percent Outpatient [A]

$16 - $101 $16 - $99 

Inpatient costs

Duration of hospital stay (days) [A]

Hospital cost per day [B]

Total hosptial cost [C]

Initial physician visit [B]

Average # of follow-up visits [A]

Cost per follow-up [B]

Total Unit Cost [C]

Percent Inpatient [A]

Weighted Unit Cost [C]

$16 - $101 $16 - $99 $0 - $0 $0 - $0 

Indirect Costs

Value of lost patient day [D]

Lost patient days (No Medical 

Care/Outpatient) [A]

Lost patient days (Inpatient) [A]

Value of caregiver day [D]

Caregiver days (No Medical 

Care/Outpatient) [A]

Caregiver days (Inpatient) [A]

Value of lost productivity day [E]

Lost productivity days [A]

Total Indirect Costs [C]

$274 - $359 $274 - $357 

1.5

1 (15.3%), 0 (84.7%)

[Note 1]

$128 $39 

0

5

$258

$354

3

[C]

$25.54

$128 

0

$0.00

$39 

1

$0.00 $0.00

$66.18

$1,007.19

$76

0

N/A N/A

$1,007.19

$97

$152.87

4 

5 

[C]

$114.55

0.5

(0-9)

$66.18

5 

$52.25

1.4%

$5,398

$148

Cost Category 2003$

Average Cost Per Patient

<2 years 2 to 4 years 5 to 15 years >16 years

Weighted Unit Cost

$21

$148

$21

14%

[C]

[C]

14%

Total Unit Cost

$152.87

Total Cost of Illness

$5,036 $4,029

$61

Total Weighted Direct Costs

$82 

3

0

$85.12

3

$114.55

0.5

(0-9)

2.5

$114.55

N/A

3

N/A

$66.18

$258

$340 

$0.00

5

$85.12

5

1.4%

$66.18

1.5

$85.12

$85.12

N/A

$85.12

$0.00 $0.00

5

3 3

4 

$0 

$4,391

$52.25

$0 

$52.25

N/A

$0

$4,338

$0

N/A

$1,007.19

$52.25

$4,029

0.0%

$4,338

0.0%

$4,029

$152.87

N/A

$115 

$0 

0.0%

$152.87

N/A

$1,007.19

$115 

0.0%

$0 

N/A

3

$114.55

Exhibit 5.22a Estimates for Average Cost and Average Cost per Healthy Patient

of Type A Illness, by Age (Traditional COI)

Note 1: For the healthy population >16 years, the severity of symptom manifestation is dependent on the rotavirus

strain and can be divided into two groups. The G2 & G9 strains represent 15.3% of illnesses, while all other strains

comprise the remaining 84.7%.

Sources:

[A] Appendix A, Exhibit A.1.

[B] Appendix A, Exhibit A.2.

[C] Calculations based on data presented in the table.

[D] Appendix A, Exhibit A.7

[E] Weighted average per day value of time ($85.12) multiplied by percent loss productivity (30 percent, rounded from

Harrington et al. 1991)
Economic Analysis for the October 2006

Final Ground Water Rule 5-71

Exhibit 5.22b Estimates for Average Cost and Average Cost per

Immunocompromised Patient of Type A Illness, by Age (Traditional COI)

Sources:

[A] Appendix A, Exhibit A.1.

[B] Appendix A, Exhibit A.2.

[C] Calculations based on data presented in the table.

[D] Appendix A, Exhibit A.7

[E] Weighted average per day value of time ($85.12) multiplied by percent loss productivity (30 percent, rounded from

Harrington et al. 1991)

Symptom duration--

reported days (range) [A]

Direct Costs

Initial physician visit [B]

Average # of follow-up visits [A]

Cost per follow-up [B]

$115 - $710 $115 - $710 

Percent Outpatient [A]

$115 - $710 $115 - $710 

Inpatient costs

Duration of hospital stay (days) [A]

Hospital cost per day [B]

Total hosptial cost [C]

Initial physician visit [B]

Average # of follow-up visits [A]

Cost per follow-up [B]

Total Unit Cost [C]

Percent Inpatient [A]

Weighted Unit Cost [C]

$4,453 - $5,049 $4,453 - $5,049

Indirect Costs

Value of lost patient day [D]

Lost patient days [A]

Value of caregiver day [D]

Caregiver days [A]

Value of lost productivity day [E]

Lost productivity days [A]

Total Indirect Costs [C]

$4,879 - $5,474 $4,708 - $5,304 

$4,453 

$4,708 $4,666 

$85.12

5

$0.00

0

$85.12

3

$0.00

[C]

[C]

Cost Category

5

$114.55 $114.55 $114.55 $114.55

3 3

Average Cost Per Patient

2003$

<2 years 2 to 4 years 5 to 15 years >16 years

2.5

Outpatient costs

0.5

(0-9)

0.5

(0-9) 0 0

$66.18 $66.18 $66.18 $66.18

100% 100% 100.0% 100.0%

5 3 3 2.5

$152.87 $152.87

$1,007.19 $1,007.19 $1,007.19

4 2 

$4,338

$152.87 $152.87

$0.00

3

100%

$0.00

$4,453 

100%

5

0

$0.00

3

$85.12

3

0

$115 $115

$115

$4,338

$52.25 $52.25

2 2 

$1,007.19

$115 

$85.12

2.5

$4,338

100%

$52.25 $52.25

$4,338

$0.00

Total Unit Cost

$148 $148

$4,029 $4,029 $4,029 $4,029

Weighted Unit Cost

$148 $148

$4,338

Total Weighted Direct Costs

$4,486 $4,486 

[C]

$4,338 $4,338 $4,338

100%

$426 $255 $255 $213

$85.12

0

$25.54

0

Total Cost of Illness

$4,912 $4,741 

[C]
Economic Analysis for the October 2006

Final Ground Water Rule 5-72

5 to 15 years >16 years

Symptom duration--

reported days (range) [A] 3 (1-6) 3 (1-6)

Direct Costs

Outpatient costs

Initial physician visit [B] NA NA

Average # of follow-up visits [A] NA NA

Cost per follow-up [B] NA NA

Total Unit Cost [C] NA NA

Percent Outpatient [A] 0.0% 0.0%

Weighted Unit Cost [C] $0.00 $0.00

Inpatient costs

Duration of hospital stay [A] NA NA

Hospital cost per day NA NA

Total hosptial cost NA NA 

Initial physician visit NA NA 

Average # of follow-up visits [A] NA NA

Cost per follow-up NA NA 

Total Unit Cost NA NA 

Percent Inpatient [A] 0% 0%

Weighted Unit Cost [C] $0.00 $0.00 

 Total Weighted Direct Costs [C] $0 $0 

Indirect Costs

Value of lost patient day [D] $0.00 $85.12 

Lost patient days [A] 1.5 1.15

Value of caregiver day [D] $85.12 $85.12 

Caregiver days [A] 1.5 0

Value of lost productivity day [E] $0.00 $25.54 

Lost productivity days [A] 0 1.09

$85 - $511 $85 - $511 

$85 - $511 $85 - $511 

Cost Category

[C]

[C]

0

$0.00 $0.00

0

$85.12 $85.12

$128 $126

$128 $126

$255 $255 

$255

$0 

3 (1-6) 3 (1-6)

$0 

3 (1-6) 3 (1-6)

$0.00 $0.00

$0.00

NA NA 

NA NA

 NA 

0%

$0.00 

NA NA

NA

0%

 NA 

 NA 

NA

NA

NA

NA

0.0%

$0.00

NA

0.0%

NA

$0.00

3 (1-6)

Total Cost of Illness

$255

NA

NA

NA

Average Cost per Patient

2003$

<1 Year 1 to 4 years

NA

NA

Total Indirect Costs

3 (1-6)

NA

Exhibit 5.22c Estimates for Average Cost and Average Cost per Case of Type B

Illness Requiring No Medical Care, by Age (Traditional COI)

Sources:

[A] Appendix A, Exhibit A.3.

[B] Appendix A, Exhibit A.4.

[C] Calculations based on data presented in the table.

[D] Appendix A, Exhibit A.7

[E] Weighted average per day value of time ($85.12) multiplied by percent loss productivity (30 percent, rounded from

Harrington et al. 1991)

NA: Not applicable to mild cases.
Economic Analysis for the October 2006

Final Ground Water Rule 5-73

Symptom duration--

reported days (range) [A]

Direct Costs

Outpatient costs

Initial physician visit [B]

Average # of follow-up visits [A]

Cost per follow-up [B]

Total Unit Cost [C]

Percent Outpatient [A]

Weighted Unit Cost [C]

Inpatient costs

Duration of hospital stay [A]

Hospital cost per day [B]

Total hosptial cost [C]

Initial physician visit [B]

Average # of follow-up visits [A]

Cost per follow-up [B]

Total Unit Cost [C]

Percent Inpatient [A]

Weighted Unit Cost [C]

 Total Weighted Direct Costs [C] 

Indirect Costs

Value of lost patient day [D]

Lost patient days [A]

Value of caregiver day [D]

Caregiver days [A]

Value of lost productivity day [E]

Lost productivity days [A]

$170 - $1,021 $170 - $851 $170 - $596 $170 - $766 

$351 - $1,202 $351 - $1,032 $351 - $777 $351 - $947 

$606 $606 

Cost Category

[C]

Total Cost of Illness [C]

$606 $606 

$181 $181

$85.12

5 (2-7)

$0.00

5 (2-10)

$0.00

5 (2-7)

$0.00

0

$181

5 (2-10)

$0.00

0

5 (2-12)

$0.00

0

Total Indirect Costs

$426 $426 $426 $426

$181

$25.54

0

$85.12

5 (2-9)

$85.12

0

$85.12 $85.12

NA NA

$0.00 $0.00 $0.00 $0.00

NA

$0.00

5 (2-12)

NA NA

0% 0% 0% 0%

NA

NA NA

NA

NA NA NA NA

NA NA NA

NA

NA

NA NA NA

NA NA NA

100.0%

$181

NA NA NA NA

$181 $181 $181

$66.18

$181

1

$66.18

$181

1

$66.18

$181

100% 100.0%

1

$66.18

$181

100%

1

5 (2-9)

$114.55 $114.55

5 (2-12) 5 (2-10) 5 (2-7)

$114.55 $114.55

Average Cost per Patient

2003$

<1 Year 1 to 4 years 5 to 15 years >16 years

Exhibit 5.22d Estimates for Average Cost and Average Cost per Case of Type B

Illness Requiring Outpatient Care, by Age (Traditional COI)

Sources:

[A] Appendix A, Exhibit A.3.

[B] Appendix A, Exhibit A.4.

[C] Calculations based on data presented in the table.

[D] Appendix A, Exhibit A.7

[E] Weighted average per day value of time ($85.12) multiplied by percent loss productivity (30 percent. rounded from

Harrington et al. 1991)

* No data available.
Economic Analysis for the October 2006

Final Ground Water Rule 5-74

Symptom duration--

reported days (range) [A]

Direct Costs

Outpatient costs

Initial physician visit [B]

Average # of follow-up visits [A]

Cost per follow-up [B]

Total Unit Cost [C]

Percent Outpatient [A]

Weighted Unit Cost [C]

Inpatient costs

Duration of hospital stay-- 

reported days [A]

Hospital cost per day [B]

Total hosptial cost [C]

Initial physician visit [B]

Average # of follow-up visits [A]

Cost per follow-up [B]

Total Unit Cost [C]

Percent Inpatient [A]

Weighted Unit Cost [C]

 Total Weighted Direct Costs [C] 

Indirect Costs

Value of lost patient day [D]

Lost patient days [A]

Value of caregiver day [D]

Caregiver days [A]

Value of lost productivity day [E]

Lost productivity days [A]

$170 - $1,192 $170 - $1,192 $170 - $1,192 $170 - $1,192 

$23,601 - $24,623 $9,357 - $10,378 $5,206 - $6,228 $5,206 - $6,228 

Average Cost per Patient

2003$

<1 Year 1 to 4 years 5 to 15 years >16 years

7 (2-14)

$114.55 $114.55

7 (2-14) 7 (2-14) 7 (2-14)

$114.55 $114.55

1

$66.18

$181

100% 100.0%

1

$66.18

$181

100%

1

$66.18

$181

1

$66.18

$181

100.0%

$181

4.7 4.7 2.5 2.5

$181 $181 $181

$1,839.15

$4,598

$4,869.90 $1,839.15 $1,839.15

$22,889 $8,644 $4,598

$52.25 $52.25

$152.87

4 4 22

$152.87 $152.87 $152.87

$0.00

7 (2-14)

$52.25 $52.25

100% 100% 100% 100%

$23,250 $4,855 $9,006

$23,250 $9,006 $4,855 $4,855

$4,855

$596

$23,431

$25.54

0

$85.12

7 (2-14)

$85.12

0

$85.12 $85.12

Total Indirect Costs

$596 $596 $596

$0.00

0

$5,036

7 (2-14)

$0.00

0

7 (2-14)

$0.00

0

$9,187

$85.12

7 (2-14)

$0.00

7 (2-14)

$0.00

7 (2-14)

$5,632 $5,632 

Cost Category

[C]

Total Cost of Illness [C]

$24,027 $9,782 

$5,036

Exhibit 5.22e Estimates for Average Cost and Average Cost per Case of Type B

Illness Requiring Inpatient Care, by Age (Traditional COI)

Sources:

[A] Appendix A, Exhibit A.3.

[B] Appendix A, Exhibit A.4.

[C] Calculations based on data presented in the table.

[D] Appendix A, Exhibit A.7

[E] Weighted average per day value of time ($85.12) multiplied by percent loss productivity (30 percent, rounded from

Harrington et al. 1991)

* No data available.

Indirect Medical Costs

For the Enhanced COI, the total indirect cost associated with a case of Type A viral illness ranges

from an average of $103 (for healthy patients 16 years old and older) to $2,136 (for patients under 2 years

of age). Indirect costs associated with cases of Type B viral illness range from $336 (for patients 16 years
11 See Appendix A.

Economic Analysis for the October 2006

Final Ground Water Rule 5-75

old and older requiring no medical care) to $2,990 (for patients under 16 years of age requiring inpatient

care). Total indirect cost is the sum of the value of patient days lost, the value of productivity lost, and

the value of care giver days lost. Exhibit 5.21 also includes this information. The value of a lost day is

set at $227.79 for adults 16 years of age and older, and $199.36 for children under 16 years of age. As

described in Appendix A, the figure for adults is calculated by summing the product of hours of market

work per day and the median gross (pre-tax) wage and benefits ($20.82), the product of hours of

nonmarket work per day and the median post-tax wage ($12.46), and the product of hours of leisure time

per day and the median post-tax wage ($12.46), and the product of hours of sleep per day and a rate of

zero. The figure for children uses a median post-tax wage ($12.46) for all lost time (16 waking hours).

For the Traditional COI, the total indirect medical cost associated with a case of Type A viral

illness ranges from an average of $39 (for healthy patients 16 years old and older) to $426 (for

immunocompromised patients 2 years of age and younger). Indirect costs associated with cases of Type

B viral illness range from $126 (for patients 16 years old and older requiring no medical care) to $596

(for patients requiring inpatient care). Total indirect cost is the sum of the value of patient days lost, the

value of productivity lost, and the value of care giver days lost. Exhibit 5.22 also includes this

information. The value of a lost day for adults and caregivers is set at $85.12. As shown in Appendix A,

this figure is calculated by summing the product of hours of market work per day and the median gross

(pre-tax) wage and benefits ($20.82), and the product of hours of nonmarket work per day and the median

post-tax wage ($6.23).

While the methodology used to derive the indirect cost of illness for adults is straightforward, the

valuation of children’s time presents unique problems. The best approach when valuing children’s health

effects is the use of child-specific valuations of these effects. For direct costs, EPA has used such

valuations. Indirect costs, however, prove more challenging. As noted in the Children’s Health

Valuation Handbook (USEPA, 2002), “[children’s] time lost to sickness also has value, although no direct

measure exists for this loss.” In this instance, the Handbook states that, “as a second-best option,

...transfer benefit values estimated for adults to children.” The Enhanced COI uses this guideline, in

conjuncture with Executive Order 13045 (“Protection of Children from Environmental Health Risks and

Safety Risks”), and assumes a day lost due to illness for the duration of illness for patients younger than

16 years to be valued at $199.36 (based on the median post-tax wage). In contrast, the Traditional COI

assigns no value for a lost day for children under 16 years of age. Both the Traditional and Enhanced

COI approaches assume that a caretaker stays home with these children, introducing additional lost

caretaker days for each lost patient day. According to the Handbook, “the productivity loss of both

affected individuals should be included in the valuation estimate of a child’s illness.” The number of

days lost entirely to illness, either by the patient or care giver, is multiplied by $227.79 (for the Enhanced

COI) or $85.12 (for the Traditional COI), the average value of a lost day. 

Often patients return to work or school while still experiencing symptoms that affect their

productivity. Because patients are only fractionally as productive at work as well people, the loss

associated with the less productive days (lost productivity) is a portion of the value of a full lost day,

specifically 30 percent11 (rounded from Harrington, 1991). Since there is only a fractional productivity

loss, the days with lessened productivity are multiplied by $68.34 (30 percent of $227.79 for Enhanced

COI) or $25.54 (30 percent of $85.12 for Traditional COI). No productivity losses are assigned to

children under 16 years of age under either the Traditional or Enhanced COI approaches. 
Economic Analysis for the October 2006

Final Ground Water Rule 5-76

5.3.1.2 Value of Mortality Avoided

Benefits of the GWR also derive from avoiding fatalities due to Type A and Type B virus

infections. The Value of a Statistical Life (VSL) is used to measure the value of these benefits. The VSL

represents an estimate of the monetary value of reducing risks of premature death. The VSL, therefore, is

not an estimate of the value of saving a particular individual’s life. The value of a “statistical” life

represents the sum of the values placed on small individual risk reductions across an exposed population. 

For example, if a regulation were to reduce the risk of premature death from Type B viral infection by

1/1,000,000 for one million exposed individuals, the regulation would “save” one statistical life

(1,000,000 X 1/1,000,000). If each of the 1,000,000 people were willing to pay $5 to achieve the risk

reduction anticipated from the regulation, the VSL would be $5 million ($5 X 1,000,000).

An EPA study characterized the range of possible VSL values as a Weibull distribution with a

mean of $4.8 million (1990 price level) based on 26 individual study estimates (USEPA 1997b). This

represents the value recommended for use in benefits analyses in EPA’s Guidelines for Preparing

Economic Analyses (USEPA 2000e) and endorsed by the Science Advisory Board (SAB) Arsenic review

panel (USEPA 2001b). For purposes of the GWR benefits analysis, the VSL Weibull distribution (with

parameters of location = 0, scale = 5.32, shape = 1.51) was incorporated into the benefits model MonteCarlo simulation. This enables quantification of the uncertainty surrounding benefits estimates derived

from the VSL. The mean VSL, after all adjustments were made, was $7.4 million in year 2003 dollars

(using a CPI adjustment factor). These adjustments are explained further in the following sections, and

the mean VSL by year of the analysis can be found in Appendix B (Exhibit B.6) of this EA.

5.3.1.3 Measuring Benefits Over the GWR Implementation Schedule

In order to extract benefits data from the model and present these benefits in comparable terms to

a similarly calculated stream of costs, it is necessary to calculated the present value of all benefits over the

lifetime of the implementation schedule. GWR implementation occurs over several years as States and

PWSs learn the requirements, inform their staffs, perform sanitary surveys, and implement source water

and compliance monitoring. A 25-year horizon was chosen for this analysis, because most treatment

technologies evaluated in this EA are estimated to have 20-year life-cycle. In addition, systems have

several years to begin treatment associated with the GWR. Calculating a shorter time frame would include

less of the complete value associated with the cost of technologies. A complete schedule of when costs

and benefits are estimated to be incurred is presented in Appendix B.

5.3.1.4 Adjustments for Income Elasticity

Although the price level (year 2003) is held constant across all benefits projections, real income

increases over time, and therefore benefit values in future years are adjusted to reflect income elasticity or

income growth, depending on the benefits category being assessed. Benefits based on potentially fatal

health effects are adjusted for income elasticity and income growth. Benefits based on the value of lost

time are adjusted for income growth, but not income elasticity. This section describes how these

adjustments are carried out. Benefits derived from medical costs, the third broad category of benefits, are

adjusted for neither income elasticity nor income growth.
12 Ideally, income elasticity and income growth measurements would be calculated using real per capita

personal income growth. Real per capita GDP, however, is used as a proxy for real per capita personal income

growth owing to lack of appropriate data projections for real personal income growth. Historical data suggests that

GDP and personal income grow at similar rates (i.e., Table B-31 of the 2002 Economic Report of the President

shows that both real per capita GDP and disposable personal income grew at an average annual rate of 2.3 percent

between 1959 and 2000).

13 See Appendix A of Kleckner and Neuman (2000) for additional information on the derivation and

application of income elasticity adjustments.

14 The distribution of VSL values used in this EA is derived based on a meta-analysis of 26 different VSL

studies, all representing different year price levels. These price levels were updated to a common 1990 price level as

part of the analysis in “The Benefits and Costs of the Clean Air Act, 1970-1990" (USEPA, 1997c), from which the

distribution used in this EA is taken.

Economic Analysis for the October 2006

Final Ground Water Rule 5-77

In the case of avoided-death benefits, income elasticity adjustments are applied to values in future

years. In general, income elasticity represents changes in valuation in relation to changes in real income. 

For example, if, for every 1 percent increase in real income, a particular consumer’s willingness to pay for

a particular item increases by 1 percent, this would be represented by an income elasticity of one. For

most items, income elasticity values are actually less than one, reflecting slower growth in willingness to

pay than in income.

In order to apply the income elasticity values in the benefits model, they must be combined with

projections of real income growth over the time frame for analysis. To accomplish this, population and

real gross domestic product (GDP) projections are combined to calculated per capita real GDP values12

(see Appendix B, Exhibit B.5–income elasticity calculations). Percent changes in these values over time

can then be combined with income elasticity figures to derive a single adjustment factor.13 Given any two

points in time, this factor is calculated as follows:

Income elasticity adjustment factor = (E I1 - E I2 - I2 - I1) / (E I2 -E I1 - I2 - I1) where:

E = income elasticity

I1 = real income (per capita GDP) in the base year

I2 = real income (per capita GDP) in the year of analysis

When applying this formula, income elasticity adjustment factors are calculated from the same

base year as the values subject to adjustment. In this case, income elasticity factors for fatal cases of viral

illness are calculated from a 1990 base year (I1 = 1990 in the above formula) because that is the base year

used in the study from which VSL estimates are derived.14

Kleckner and Neuman (2000) identified published studies from which elasticity values could be

derived for potentially fatal health effects. They suggest a triangular distribution with a mode of 0.40,

and endpoints at 0.08 and 1.00. In the Monte-Carlo simulation that assigns dollar values to benefits,

income elasticity values (E in the above equation) are drawn from this probability distribution. Based on

this formula and inputs, income elasticity factors are computed and applied to avoided-death benefits in

future years. At the average income elasticity value (0.49), the income elasticity factors applied range

from 1.213 (2008) to 1.445 (2029).
15 See EPA’s Guidelines for Preparing Economic Analyses (USEPA, 2000e) for a full discussion of the use of social

discount rates in the evaluation of policy decisions.

Economic Analysis for the October 2006

Final Ground Water Rule 5-78

The second type of adjustment for income growth is applied to the portion of future benefits

derived from the value of lost time. The methodology here is more straightforward. The same per capita

GDP values referenced above (and presented in Appendix B) are employed to compute simple ratios

(income growth factors) between the future year and the year 2003 (the baseline year for COI

calculations). Lost time benefits values are then multiplied by these factors, which range from 1.15 in

2008 to 1.64 in 2029.

5.3.1.5 Present Value of Future Benefits

To allow comparison of future streams of costs and benefits, it is common practice to adjust both

streams to a present value (PV) using a social discount rate. This process takes into account the time

preference that society places on expenditures and benefits and allows comparison of cost and benefit

streams that vary over a given time period.15 A present value for any future period can be calculated

using the following equation:

PV = Vt

/(1 + R)t 

where: t = the number of years from the reference period (year 0 of the benefits stream)

R = social discount rate

Vt

 = the benefits occurring t years from the reference period

There is much discussion among economists of the proper social discount rate to use for policy

analysis. For this EA, therefore, PV calculations are made using two social discount rates thought to best

represent current policy evaluation methodologies, 3 and 7 percent. Historically, the use of 3 percent is

based on rates of return on relatively risk-free investments, as described in the Ex anteGuidelines for

Preparing Economic Analyses (USEPA, 2000e). The rate of 7 percent is a recommendation of the Office

of Management and Budget (OMB) as an estimate of “before-tax rate of return to incremental private

investment” (USEPA, 1996c). To allow evaluation on an annual basis, the total PV of benefits are

annualized using the same social discount rates.

5.3.2 Summary of Quantified Benefits of GWR

The risk assessment methodology described in this chapter estimates quantified benefits of

reducing endemic acute infections caused by a portion of Type A and Type B viruses. Exhibits 5.23a-b

provide a summary of the cumulative monetary benefits estimated for the GWR for all system sizes and

categories (CWSs, NTNCWSs, and TNCWSs). Nonquantified benefits are discussed in Section 5.4. 

The costs for rule alternatives are presented in Chapter 6, and cost/benefit comparisons are evaluated in

Chapter 8.
Economic Analysis for the October 2006

Final Ground Water Rule 5-79

3% Discount Rate 7% Discount Rate

Lower

(5th %ile)

Upper

(95th %ile)

Lower

(5th %ile)

Upper

(95th %ile)

$ 0.1 0.2 $ 0.5 $ 0.2 $ 0.0 $ 0.3 $ 

$ 0.2 0.4 $ 1.0 $ 0.4 $ 0.1 $ 0.8 $ 

$ 0.1 0.4 $ 1.0 $ 0.3 $ 0.1 $ 0.8 $ 

$ 0.3 1.0 $ 2.4 $ 0.8 $ 0.3 $ 2.0 $ 

$ 0.9 2.5 $ 5.7 $ 2.1 $ 0.7 $ 4.8 $ 

$ 0.8 2.4 $ 5.3 $ 2.1 $ 0.7 $ 4.6 $ 

$ 1.5 4.7 $ 11.0 $ 4.1 $ 1.3 $ 9.6 $ 

$ 1.5 4.3 $ 10.1 $ 3.8 $ 1.3 $ 8.8 $ 

$ 0.0 0.0 $ 0.0 $ 0.0 $ 0.0 $ 0.0 $ 

$ 5.4 16.0 $ 37.0 $ 13.7 $ 4.6 $ 31.6 $ 

$ 0.0 0.1 $ 0.1 $ 0.1 $ 0.0 $ 0.1 $ 

$ 0.1 0.2 $ 0.4 $ 0.2 $ 0.1 $ 0.4 $ 

$ 0.1 0.2 $ 0.5 $ 0.2 $ 0.0 $ 0.4 $ 

$ 0.1 0.2 $ 0.6 $ 0.2 $ 0.1 $ 0.5 $ 

$ 0.0 0.1 $ 0.3 $ 0.1 $ 0.0 $ 0.2 $ 

$ 0.0 0.1 $ 0.2 $ 0.1 $ 0.0 $ 0.1 $ 

$ 0.0 0.0 $ 0.1 $ 0.0 $ 0.0 $ 0.0 $ 

$ 0.0 0.0 $ 0.1 $ 0.0 $ 0.0 $ 0.1 $ 

$ - - $ - $ - $ - $ - $ 

$ 0.3 0.9 $ 2.2 $ 0.8 $ 0.2 $ 1.8 $ 

$ 0.2 0.6 $ 1.4 $ 0.5 $ 0.1 $ 1.1 $ 

$ 0.3 0.9 $ 2.2 $ 0.8 $ 0.2 $ 1.8 $ 

$ 0.1 0.4 $ 1.0 $ 0.3 $ 0.1 $ 0.8 $ 

$ 0.1 0.3 $ 0.8 $ 0.3 $ 0.1 $ 0.6 $ 

$ 0.1 0.2 $ 0.4 $ 0.1 $ 0.0 $ 0.3 $ 

$ 0.0 0.2 $ 0.4 $ 0.1 $ 0.0 $ 0.3 $ 

$ 0.0 0.0 $ 0.1 $ 0.0 $ 0.0 $ 0.0 $ 

$ 0.0 0.1 $ 0.1 $ 0.0 $ 0.0 $ 0.1 $ 

$ - - $ - $ - $ - $ - $ 

$ 0.8 2.7 $ 6.2 $ 2.3 $ 0.7 $ 5.1 $ 

$ 6.5 19.7 $ 45.4 $ 16.8 $ 5.5 $ 38.6 $ 

Source: Appendix C

1,001-3,300

>1 Million

All Sizes

TOTAL

3,301-10K

10,001-50K

50,001-100K

100,001-1M

Transient Noncommunity Water Systems (TNCWSs)

<100

101-500

501-1,000

50,001-100K

100,001-1M

>1 Million

All Sizes

501-1,000

1,001-3,300

3,301-10K

10,001-50K

All Sizes

Nontransient Noncommunity Water Systems (NTNCWSs)

<100

101-500

10,001-50K

50,001-100K

100,001-1M

>1 Million

Mean

Value

501-1,000

1,001-3,300

3,301-10K

Detail may not add to totals due to independent rounding. The Traditional COI only includes valuation for 

medical costs and lost work time (including some portion of unpaid household production). The Enhanced COI 

also factors in valuations for lost personal time (non-work time) such as childcare and homemaking (to the extent 

not covered by the Traditional COI), time with family, and recreation, and lost productivity at work on days when 

workers are ill but go to work anyway.

The figures presented in this exhibit represent only the quantifiable benefits of the GWR. The unquantified 

benefits are expected to comprise a significant portion of the overall benefits of the Rule and are presented in 

Section 5.4.

90 Percent

Confidence Bound

Community Water Systems (CWSs)

<100

101-500

System Size

(Population Served)

Mean

Value

90 Percent

Confidence Bound

Exhibit 5.23a Annualized Quantified Benefits of Illnesses and Deaths Avoided,

Final Rule, Enhanced COI, All Systems by System Size and Type

($Millions, 2003)
Economic Analysis for the October 2006

Final Ground Water Rule 5-80

3% Discount Rate 7% Discount Rate

Lower

(5th %ile)

Upper

(95th %ile)

Lower

(5th %ile)

Upper

(95th %ile)

$ 0.0 0.1 $ 0.3 $ 0.1 $ 0.0 $ 0.2 $ 

$ 0.1 0.2 $ 0.6 $ 0.2 $ 0.0 $ 0.5 $ 

$ 0.0 0.2 $ 0.6 $ 0.2 $ 0.0 $ 0.5 $ 

$ 0.1 0.5 $ 1.4 $ 0.4 $ 0.1 $ 1.2 $ 

$ 0.3 1.3 $ 3.4 $ 1.1 $ 0.3 $ 2.8 $ 

$ 0.3 1.2 $ 3.2 $ 1.1 $ 0.3 $ 2.8 $ 

$ 0.5 2.4 $ 6.7 $ 2.1 $ 0.4 $ 5.9 $ 

$ 0.5 2.2 $ 6.0 $ 1.9 $ 0.5 $ 5.3 $ 

$ 0.0 0.0 $ 0.0 $ 0.0 $ 0.0 $ 0.0 $ 

$ 1.9 8.2 $ 22.3 $ 7.1 $ 1.6 $ 19.1 $ 

$ 0.0 0.0 $ 0.1 $ 0.0 $ 0.0 $ 0.1 $ 

$ 0.0 0.1 $ 0.3 $ 0.1 $ 0.0 $ 0.2 $ 

$ 0.0 0.1 $ 0.3 $ 0.1 $ 0.0 $ 0.2 $ 

$ 0.0 0.1 $ 0.3 $ 0.1 $ 0.0 $ 0.3 $ 

$ 0.0 0.1 $ 0.1 $ 0.0 $ 0.0 $ 0.1 $ 

$ 0.0 0.0 $ 0.1 $ 0.0 $ 0.0 $ 0.1 $ 

$ 0.0 0.0 $ 0.0 $ 0.0 $ 0.0 $ 0.0 $ 

$ 0.0 0.0 $ 0.1 $ 0.0 $ 0.0 $ 0.0 $ 

$ - - $ - $ - $ - $ - $ 

$ 0.1 0.5 $ 1.3 $ 0.4 $ 0.1 $ 1.0 $ 

$ 0.1 0.3 $ 0.7 $ 0.3 $ 0.1 $ 0.6 $ 

$ 0.1 0.4 $ 1.2 $ 0.4 $ 0.1 $ 1.0 $ 

$ 0.0 0.2 $ 0.6 $ 0.2 $ 0.0 $ 0.5 $ 

$ 0.0 0.2 $ 0.4 $ 0.1 $ 0.0 $ 0.4 $ 

$ 0.0 0.1 $ 0.2 $ 0.1 $ 0.0 $ 0.2 $ 

$ 0.0 0.1 $ 0.2 $ 0.1 $ 0.0 $ 0.2 $ 

$ 0.0 0.0 $ 0.0 $ 0.0 $ 0.0 $ 0.0 $ 

$ 0.0 0.0 $ 0.1 $ 0.0 $ 0.0 $ 0.1 $ 

$ - - $ - $ - $ - $ - $ 

$ 0.3 1.3 $ 3.4 $ 1.1 $ 0.2 $ 2.8 $ 

$ 2.2 10.0 $ 27.0 $ 8.6 $ 1.9 $ 22.9 $ 

Source: Appendix C

Detail may not add to totals due to independent rounding. The Traditional COI only includes valuation for 

medical costs and lost work time (including some portion of unpaid household production). The Enhanced COI 

also factors in valuations for lost personal time (non-work time) such as childcare and homemaking (to the extent 

not covered by the Traditional COI), time with family, and recreation, and lost productivity at work on days when 

workers are ill but go to work anyway.

The figures presented in this exhibit represent only the quantifiable benefits of the GWR. The unquantified 

benefits are expected to comprise a significant portion of the overall benefits of the Rule and are presented in 

Section 5.4.

90 Percent

Confidence Bound

Community Water Systems (CWSs)

<100

101-500

System Size

(Population Served)

Mean

Value

90 Percent

Confidence Bound

Mean

Value

501-1,000

1,001-3,300

3,301-10K

10,001-50K

50,001-100K

100,001-1M

>1 Million

All Sizes

Nontransient Noncommunity Water Systems (NTNCWSs)

<100

101-500

501-1,000

1,001-3,300

3,301-10K

10,001-50K

50,001-100K

100,001-1M

>1 Million

All Sizes

Transient Noncommunity Water Systems (TNCWSs)

<100

101-500

501-1,000

1,001-3,300

>1 Million

All Sizes

TOTAL

3,301-10K

10,001-50K

50,001-100K

100,001-1M

Exhibit 5.23b Annualized Quantified Benefits of Illnesses and Deaths Avoided,

Final Rule, Traditional COI, All Systems, by System Size and Type

($Millions, 2003)
Economic Analysis for the October 2006

Final Ground Water Rule 5-81

Population US Census1

Population 

Potentially 

Affected 

(served by 

GW systems)

No. of 

Illnesses 

Avoided

No. of 

Deaths 

Avoided

Annual Benefits 

Using 3 % 

Discount Rate 

and Enhanced 

COI2

($Millions)

 All ages 844,266 342,772 126 0.002 $0.62

 Elderly ( >65 yrs) 34,791,627 14,125,401 5,559 0.10 $1.55

 Children ( <5 yrs) 19,079,280 7,746,187 2,780 0.06 $4.99

Children ( <5 yrs) Type A:

<2 yrs 7,587,829 3,080,659 1,684 0.01 $2.81

2-4 yrs 11,491,436 4,665,523 904 0.01 $1.51

Children ( <5 yrs) Type B:

<1 month 315,541 128,110 3 0.00 $0.01

1 month - <1 yr 3,470,952 1,409,207 37 0.01 $0.13

1-4 yrs 15,292,787 6,208,872 151 0.03 $0.52

Total Nonimmunocompromised Sensitive 53,870,907 37,363,958 8,339 0.15 $7.17

Total 54,715,173 37,706,730 8,465 0.15 $7.79

Immunocompromised (0.3%)

Nonimmunocompromised Sensitive (99.7%)

5.3.3 Quantified Benefits to Sensitive Subpopulations

Exhibits 5.23a and 5.23b presented the annualized benefits of the GWR across the general

population. However, a large portion of these benefits will be realized by sensitive subpopulations. As

described previously in section 5.2.2.2, EPA is considering three sensitive populations for the purpose of

the GWR: the immunocompromised, children (< 5 years old), and the elderly (> 65 years old). Exhibit

5.24 presents the benefits of the GWR to sensitive populations.

Exhibit 5.24 Annual Illnesses and Deaths Avoided at Full Implementation,

and Quantified Benefits of the GWR in Sensitive Populations

Notes: Detail may not sum due to independent statistical analyses and rounding. The figures presented in this

exhibit represent only the quantifiable benefits of the GWR. The nonquantified benefits are expected to comprise a

significant portion of the overall benefits of the Rule and are presented in Section 5.4. The Immunocompromised

population includes bone marrow transplant recipients, AIDS patients, and organ transplant patients.

1

 The U.S. Census data is modified to show the number of people that are estimated to be immunocompromised (0.3

% of the population) and not immunocompromised (99.7% of the population). Therefore, the U.S. Census population

estimates shown above for the Elderly and Children categories are 99.7% of the estimates shown in Exhibit 5.4.

2

The Enhanced COI factors in valuations for lost personal time (non-work time) such as childcare and homemaking

(to the extent not covered by the Traditional COI), time with family, and recreation, and lost productivity at work on

days when workers are ill but go to work anyway. (The Traditional COI only includes valuation for medical costs and

lost work time (including some portion of unpaid household production).

Source: U.S. Census Population from 2000 Census data (U.S. Bureau of the Census, 2000); Population Potentially

Affected derived from SDWIS (USEPA 2003a); Number of Illnesses Avoided, Deaths Avoided, and Annual Benefits

from GWR Model Output.
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5.4 Nonquantified Benefits of GWR Provisions

Due to the limited availability of data, EPA was only able to quantify some of the benefits it

believes are associated with the GWR. The EA for the GWR monetizes benefits associated with Type A

viruses represented by rotavirus data and Type B represented by enterovirus or echovirus data. As

discussed in Section 5.1., the EA quantifies only the endemic, acute illnesses due to rotavirus and

enterovirus. Other benefits, not quantified, are discussed in this section. As discussed in Section 5.2 and

5.3, even in the case where benefits are quantified, data limitations remain and certain factors used in the

analysis have significant associated uncertainties.

The nonquantified health benefits are: 1) decreased incidence of gastroenteritis caused by other

Type A viruses such as norovirus, astrovirus and adenovirus, 2) decreased incidence of other acute

disease endpoints (e.g., hepatitis, conjunctivitis), 3) decreased incidence of chronic illness sequelae

associated with Type B virus (e.g., diabetes, dilated cardiomyopathy, hypertension and reduced kidney

function), 4) decreased incidence of illness and death caused by bacteria, 5) decreased incidence of 

waterborne disease outbreaks and epidemic illness, and 6) decreased illness through minimizing

treatment failures or fewer episodes with inadequate treatment.

The nonquantified non-health benefits are: 1) improved perception of ground water quality and

perception about reduced risk associated with PWS wells, 2) reduced use of bottle water and point-of-use

devices, 3) reduced time spent on averting behavior such as obtaining alternative water supplies, and 3)

avoided costs associated with outbreak response.

EPA believes that, collectively, these benefits, both health and non-health, are likely to

substantially exceed those which EPA was able to quantify, and are the primary basis for supporting the

preferred regulatory alternative. Each of these major nonquantified benefits is discussed further below. 

5.4.1 Decreased Incidence of Illness Caused by Other Type A Viruses

5.4.1.1 Norovirus

 Noroviruses have been suggested as “the single most significant cause of intestinal infectious

disease in the developed world.” (Carter, 2005) However, no cell culture method exists to recover

noroviruses in stool or environmental samples, therefore published human infectivity data for norovirus

were not available to use in the EA. This detection method deficiency and resulting lack of published

infectivity data prevented quantification of monetized benefits for norovirus occurrence reduction in the

GWR EA. In this section, the norovirus disease burden is qualitatively discussed together with

information that suggests additional benefit from full implementation of the GWR.
16Common source outbreaks arise primarily from food or water (ice is considered to be water by EPA but is

commonly treated as food in outbreak compilations). Propagation by secondary (person-to-person) transmission

may also occur but is not the immediate cause of the outbreak. Outbreaks that are not common source arise and

propagate only by person-to-person transmission.

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Norovirus Disease in the United States

In recent years, numerous common source outbreaks16 have been attributed to norovirus

contamination. CDC retrospectively evaluated 4,050 U.S. common source outbreaks that occurred

during 1998--2000 and determined that at a minimum, 28% could be attributable to norovirus (Turcios, et

al, 2006). In another study of outbreaks occurring during the period from 2000 to 2004, fecal samples

from 226 outbreaks (12 waterborne) of acute gastroenteritis suspected of calicivirus causality were

analyzed by CDC for norovirus and other caliciviruses (Blanton et al, 2006). Caliciviruses (primarily

norovirus but also sapovirus) were detected in 184 (81%) of those outbreaks. These data suggest that

norovirus represents a large component of the total gastroenteritis epidemic disease burden in the United

States. This perspective is further supported by CDC who estimated total U.S. annual illnesses from

Norwalk-like (now called norovirus) viruses of 23,000,000 cases (Mead et al 1999).

The identification of the etiologic agent of a waterborne, or any common source or person-toperson outbreak depends on a number of factors: the timely recognition of the outbreak and timely stool

sample collection, laboratory capacity and capability, active requests for non-routine tests, and many

other factors (Lee et al., 2002). When routine analysis of stool is requested, the sample is typically tested

only for some enteric bacteria and some protozoan parasites (typically Giardia); testing for viruses and

especially norovirus, is not common. Viral agents are less easily identified than most enteric bacteria and

norovirus is among the most difficult viral agents to identify (Blanton et al., 2006). It is only within the

last ten years that molecular methods have become sufficiently advanced so norovirus strains can be

specifically identified in stool samples. Unlike bacterial agents, no routine, commercially available test

for identifying norovirus exists and therefore ill persons who submit a stool specimen are not routinely

tested for norovirus (Blanton et al., 2006).

Norovirus has a low infectious dose, prolonged asymptomatic shedding, substantial strain

diversity and considerable environmental stability (CDC, 2001a). As a result of a low infectious dose, a

small dose readily allows infection in exposed individuals (CDC, 2001a). Prolonged shedding allows

opportunity for individuals to come in contact with norovirus. Norovirus does not provide lasting

immunity upon infection partly because there are many different serotypes (Carter, 2005). The

substantial strain diversity may prevent individuals from acquiring a general immunity that prevents

illness from any norovirus. Environmental stability allows norovirus to survive in ground water and

elsewhere in the environment until acquired by another host (Schwab and Bae, 2005). Thus, noroviruscontaminated ground water or a norovirus-contaminated surface will continue to maintain infectious

norovirus. Individuals can acquire primary norovirus infection by drinking that ground water or can

acquire secondary infectious norovirus by contact with a contaminated surface or persons.

Although a small percentage (about 20%) of individuals in the United States are likely genetically

immune to norovirus infection (Lindesmith et al., 2003), the remaining population is subject to repeated

episodes of infection and illness. Norovirus is shed in appreciable numbers, at concentrations similar to

enteroviruses (Carter, 2005). Because norovirus is highly infectious (Moe et al., 2001), individuals may

easily acquire infection. Once infected, norovirus is easily transmitted to others. Individuals can easily
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spread infection and illness to family members and others (both children and adults) outside the

household by casual contact with asymptomatic carriers who shed for long periods.

Using molecular epidemiology tools, diverse cases may be tracked backwards in time and

exposure history to identify an index case or a common source exposure. One norovirus strain, the

Farmington Hills strain, is identified as a cause of multiple large outbreaks on cruise ships (Widdowson et

al., 2004). The norovirus attack rates (30% of passengers became ill) resulting during cruise ships

outbreaks suggests a defining character, it's capability to spread rapidly and efficiently via secondary

transmission from a primary infected individual. This norovirus characteristic has significance when

estimating the number of secondary cases which is illustrated further in Appendix J.

Norovirus Ground Water Outbreaks

Norovirus is recognized as the confirmed cause for some ground water outbreaks and is suspected

in many others. In general, the etiological agent of many common source gastroenteritis outbreaks has

not been identified. For example, of greater than 2,500 outbreaks reported to CDC from 1993 to 1997,

68% were of "unknown etiology" (Widdowson et al, 2005). Similarly, most common source outbreaks

resulting from ground water fecal contamination are of unknown etiology. Of 342 ground water

outbreaks in the United States between 1971 and 1994, 212 were of "undetermined" etiology (Craun and

Calderon, 1997).

Two recent ground water outbreaks in Wyoming were both recognized as norovirus outbreaks. In

South Pass, Wyoming, an epidemiological investigation linked illness to the well water and ice

(Parshionkar et al, 2003). A total of 84 illnesses were identified. The well supplied a TNC PWS system

producing water from a sensitive (fractured bedrock) aquifer. A chlorination device malfunctioned due to

poor maintenance. In Big Horn, Wyoming, 35 illnesses were identified due to fecal contamination of an

unchlorinated PWS well in a sensitive (fractured bedrock) aquifer (Anderson et al, 2003). In 1989,

norovirus was identified in an outbreak with 110 illnesses in Sedona, AZ (Lawson et al, 1991). Most

recently, norovirus illness and campylobacterois were the most common illnesses associated with fecal

contamination of PWS wells on South Bass Island, OH in 2004 (Ohio EPA, 2005). It is estimated that

about 1450 individuals became ill from consuming well water tapping a sensitive aquifer with widespread

fecal contamination (many PWS as well as some private wells were fecally contaminated). Other

norovirus ground water outbreaks are identified from Yukon, Canada (Beller et al., 1997), Braun Station,

TX (D'Antonio et al., 1985), Pierce County, WA (Taylor et al, 1981), Onondaga, NY (Chatterjeee et al.

2004), Monroe County, PA (Wilson et al., 1982), Henderson County, IL (Parsonnet et al., 1989),

southeastern PA (Cannon et al, 1991), South Dakota (CDC, 1988) and elsewhere. Among outbreaks that

have been specifically attributed to norovirus exposure in ground water, most have occurred in sensitive

aquifers (see the GWR Occurrence and Monitoring Background Document for a discussion of outbreaks

in sensitive aquifers).

Norovirus Disease Burden and Severity

The health effects of norovirus illness include acute onset of nausea, vomiting, abdominal

cramps, and diarrhea. Vomiting is relatively more prevalent among children. Many adults experience

vomiting as well as diarrhea. Constitutional symptoms (e.g., headache, fever, chills, and myalgia) are

frequently reported. Although rare, severe dehydration caused by norovirus gastroenteritis can be fatal,

with this outcome occurring among susceptible persons (e.g., older persons with debilitating health
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conditions). No long-term sequelae of norovirus infection have been reported (CDC, 2001a). Duration of

illness is typically 12–60 hours. 

Norovirus is suggested in waterborne disease when vomiting is a symptom because norovirus is

fairly unique among the common gastrointestinal agents in that vomiting often accompanies diarrhea. In

a prospective study of Dutch patients with norovirus in a community cohort (not an outbreak), 74% of 99

patients of all ages experienced vomiting. Vomiting enhances the ability of norovirus to spread

efficiently via fomites, suspended particles and aerosols.

The avoided illnesses from Type A viruses determined quantitatively in this EA are based only on

rotavirus infection and illness. There are significant differences between rotaviral and noroviral disease. 

The total ground water-borne disease burden would change significantly if norovirus were included in the

quantitative analysis. EPA believes that, if norovirus was included in the quantified benefits, there would

be significantly greater total benefits for two reasons. First, norovirus, unlike rotavirus, is a disease of

older teenagers and adults (Carter, 2005) as well as of children. In a study of 1,484 norovirus patients,

the mean age was 43 years (Fankhauser et al. 2002). Similarly, in a study of 1,010 norovirus cases, the

median age was 47 years (Blanton et al, 2006). This distinction is important; the monetized rotavirus

disease burden in this EA provides only a small benefit for adult rotaviral disease because most adults are

immune to rotavirus. Thus, noroviral disease in adults, which is quite prevalent, would be a significant

additional avoided illness and monetized benefit if norovirus were included in the quantified analysis in

this EA.

Second, unlike rotavirus, adults with norovirus experience vomiting and some experience only

vomiting (CDC, 2001a). Most individuals experienced vomiting in a norovirus outbreak. In an analysis

of symptoms, Widdowson et al (2005) found that more than half the ill persons experience vomiting in

almost all norovirus outbreaks (i.e., in 86 percent of 136 outbreaks, greater than 50 percent of people

experienced vomiting as a clinical symptom).

In monetizing the benefits associated with rotavirus or norovirus, the clinical symptoms are

important. Norovirus is unique among the waterborne etiologic agents in that large proportions of ill

individuals experience vomiting. Because adults with rotavirus experience gastroenteritis only, EPA

assumes that each adult ill with rotavirus has one day of lost productivity and a subset (16%) have one

lost patient day. In contrast, for adults with norovirus illness that manifests as vomiting (with nausea and

gastroenteritis), EPA believes that norovirus likely produces greater lost leisure time and more lost

productivity days, and therefore lost patient days, as compared with rotavirus because vomiting is so

debilitating. Thus, a case of noroviral disease, when monetized, would likely produce greater benefit than

rotaviral disease in adults.

In an analysis of care, Widdowson et al. (2005) compiled data on 3,370 persons affected in 112

norovirus outbreaks in the United States. Of these, 329 (10%) sought care from a physician and 33 (1%)

were hospitalized. Because these data are from outbreak investigations, the outbreak cases may be biased

toward the more severe end of the disease spectrum. It has been hypothesized that outbreaks are more

likely recognized when the disease is more severe. Conversely, endemic cases or unrecognized outbreak

cases may be milder disease. Mead et al. (1999) estimated norovirus hospitalization rates at 0.2% rather

than the 1% value determined from outbreaks.

This EA quantifies the benefits for Type A viruses using data only from rotavirus. Unlike

rotavirus, the norovirus human challenge study data to determine norovirus infectivity are not yet
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published (Moe, 2001). For this reason alone, rotavirus data are used to quantitatively determine the

benefits for the Type A viruses. As discussed above, EPA believes that the more severe clinical

symptoms associated with norovirus, as compared with rotavirus, suggests that the norovirus disease

burden associated with PWS wells is important, especially for adults.

EPA believes that the disease burden for norovirus and rotavirus is similar, although children are

more likely to experience vomiting from norovirus. However, vomiting in children does not result in

additional benefits when the illness is monetized. In contrast, the person-days ill metric does not account

for the clinical symptoms and disease severity in adults who experience those person-days of illness and

this severity provides additional benefits when monetized. EPA believes that consideration of the more

severe clinical symptoms associated with norovirus illness among adults implies that adults will have

more lost-patient days, as well as more lost productivity days.

Norovirus Cost of Illness 

EPA believes that the clinical severity of norovirus illness in adults is significant. While EPA has

data on the proportion of cases with vomiting and on the duration of illness, EPA has no data on duration

of vomiting. Consideration of vomiting for norovirus illness suggests that the lost productivity for

norovirus illness in adults could be much greater than is assumed for rotavirus in the quantified benefits

because vomiting is typically sufficiently debilitating (and infectious to others) that most people cannot

(or should not) work. The EA currently assumes a weighted mean value of 0.16 lost patient days and one

day of lost productivity for adults when ill from rotavirus. EPA believes that this value is low compared

with the likely norovirus illness lost productivity and lost patient days.

5.4.1.2 Other Type A viruses

Hepatitis A Virus

Viral pathogens, other than the enteroviruses, rotavirus and the caliciviruses are also transmitted

by the fecal-oral pathway and thus are potential etiologic agents for ground waterborne disease. Hepatitis

A (HAV) virus is the only waterborne virus that is reportable to CDC. About 28,000 HAV cases are

reported to CDC each year, although that number is expected to decline with time because children are

currently vaccinated for HAV in high risk states and newer recommendations are for increased

vaccination coverage. More generally, however, because HAV is more severe as an adult disease, an

aging U.S. population may have greater disease burden. Mead et al (1999) estimate about 83,000 HAV

cases each year, with a hospitalization rate of 13% and a mortality rate of 0.3%. Like all fecal/oral

pathogens, HAV is acquired through a variety of pathways. Hepatitis has a long incubation period and

the virus remains viable in the environment and especially ground water for months. Thus, the infection

source is often obscure. Ground water HAV outbreaks have been identified (Georgetown, TX (Hejkal et

al, 1982), Racine, MO (Missouri Department of Health, 1992); Lancaster, PA (Bowen and McCarthy,

1983); Quebec, Canada (De Serres et al., 1999); all in sensitive aquifers). HAV is not favored in typical

cell lines used in cell culture and so identification is difficult in environmental samples. As a result of the

relatively large hepatitis A disease burden in locales where hygiene is poor, hepatitis A virus is believed

to be highly infectious, perhaps as infectious as norovirus or rotavirus. HAV tends to present more

serious symptoms than other viruses discussed thus far. Unlike norovirus or rotavirus, HAV infection

confers lifetime immunity. No human dose response study data are available at differing doses. Because
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of this and the fact that HAV cannot be routinely identified in well water, the benefits of avoiding HAV

disease through full implementation of the GWR cannot be quantified.

Hepatitis E virus

Hepatitis E (HEV) virus is another fecal oral virus that is potential transmitted via ground water. 

Using serology and case histories of individual patients, HEV is established as endemic within the United

States (Tsang et al, 2000). However, the data suggest that only one or a few percent of the population has

been infected. Unlike HAV, no ground water outbreaks of HEV have occurred in the United Sates,

although they have occurred elsewhere (China and Somalia). HEV is not culturable and no data on

environmental occurrence in ground water are available. The disease is severe (up to 20% mortality

among pregnant women in developing countries) and thus no human dose response data are available. 

Because infectious HEV cannot be identified in well water and no human dose response data are

available, the benefits of avoiding HEV disease through full implementation of the GWR cannot be

quantified.

Adenovirus

The adenovirus are a large group of viruses that produce diverse symptoms. Two adenovirus

serotypes adenovirus 40 and 41 produce primarily enteric symptoms, but several other adenoviruses are

also capable of producing such symptoms. Some cause conjunctivitis. Most significantly, adenoviruses

caused a fatal outcome in otherwise health young males in military settings. (CDC, 2001b) All

adenoviruses, no matter the infection site and characteristic illness, are shed copiously through the gut and

are thus fecal\oral viruses (Carter, 2005). Adenoviruses are not efficiently recovered using commonly

available cell lines and methods and no human dose response data are available. No waterborne disease

outbreaks have been reported for adenovirus in the United States, but adenovrius was among several

pathogens identified in wells sampled during the South Bass Island, OH outbreak (CDC, 2005). The

GWR does not quantify the benefits from avoided adenovirus illness.

Astrovirus

Astrovirus, like rotavirus, is commonly acquired in child care settings, causes mild disease in

children and most children are exposed at an early age. However, like rotavirus, a small percentage of

that large population suffer more significant health effects and may require in-patient care. Like

rotavirus, the disease burden in older children and adult populations is underestimated because the disease

is mild (Carter, 2005). Astroviruses are shed in stool at large numbers (similar to enteroviruses Carter,

2005) and, in France, prospective epidemiology studies have implicated untreated ground water as a route

of infection (Gofti-Laroche, et al, 2003). Astroviruses are not favored for recovery in environmental

samples using common cell lines and no human dose-response data exist. No waterborne disease

outbreaks have been identified for Astrovirus in the United States. The benefits from avoiding astrovirus

illness via the GWR can only be qualitatively be described.

Reovirus

Reovirus is recovered in environmental samples using the BGM cell line and is commonly found

co-occurring with the enteroviruses in PWS wells. Carducci et al (2002) found that, in some cases,

enterovirus detection was limited because reovirus reproduction was so highly favored. Reovirus is more

closely related to rotavirus and thus has some similar characteristics. Unlike rotavirus, reovirus rarely
17The presence of reovirus in environmental samples complicates the recovery, or detection and

quantification, of enteroviruses. Additionally, reovirus rarely results in illness. Therefore, reovirus occurrence can

cause underestimates of enteroviral occurrence, and can elevate viral concentrations without adding to the disease

burden associated with a contaminated water source. Hence, it can result in an underestimate of the quantified

benefits that accrue from the GWR. 

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causes disease but it is now recognized as a human pathogen in children (Tyler et al, 2004). Although

reovirus is probably not a significant component of the total disease burden, it is important because it

likely reduces the enterovirus recovery efficiency17, which is typically not greater than 50 percent under

optimal conditions. No waterborne disease outbreaks have been identified for Reovirus in the United

States. 

5.4.2 Decreased Incidence of Other Illness Caused by Type B Viruses

Other Type B viral diseases, such as diabetes or cardiomyopathy, may lead to chronic disease. 

Because the causal relationship is not well established and the number of cases associated with drinking

water is unknown, the Agency was not able to quantify benefits from the GWR on reducing chronic

diseases. While this EA does not quantify in dollar terms the benefit of avoiding chronic illness, this

section discusses the potential benefits qualitatively and illustrates the significance of these secondary

benefits.

 The total number of people with two types of chronic illnesses, diabetes and heart disease in the

United States is substantial. Between 1990-92, there was an annual average of seven million people with

diabetes (all kinds) and four million people with chronic heart disease (including myocarditis and

cardiomyopathy) (Collins, 1997). Additionally, 3.5 percent of heart disease deaths in 1993 were due to

cardiomyopathy (NHLBI, 1996). The potential benefits of avoiding some of these health effects cannot

be overlooked, and may be significant.

An extensive literature review proved that costs of a single case of diabetes or heart disease are

significant. Cost estimates for a case of diabetes and a case of chronic myocarditis (using the cost per

case of an “average case of heart disease” as a proxy for chronic myocarditis) are presented below to

demonstrate the magnitude of potential benefits per avoided case of chronic illness. Potential

implications of diabetes, myocarditis, and cardiomyopathy through consumption of ground water are

briefly discussed below. 

Diabetes

There is considerable information that Type 1 diabetes may be associated with enterovirus

infection, including infection with coxsackievirus and echoviruses (Maria et al. 2005; Vreugdenhil et al,

2000). Epidemiological studies have shown a strong correlation between diabetes and enterovirus

infection. Individual case studies have reported diabetes development after enterovirus infection

(Roivainen, 1998). A mechanism for producing disease suggests that entervirus infection triggers

autoimmunity response. While these data are suggestive, they are not definitive. Recently, Maria et al

(2005) reported simultaneous (on the same day) diabetes onset in mother and son coincident with

enteroviral infection. With these data, it is now clear that at least some Type 1 diabetes cases result from

enterovirus infection. The GWR EA considered the severe acute illnesses resulting from enterovirus

infection in quantitatively determining the benefits (illnesses avoided), but only considers qualitatively
18 Costs updated from January 1995 dollars to 2003 (annual) dollars using the CPI-U for “medical care

services” (= 278.8 ÷ 219.8 = 1.3).

19 Costs updated from January 1997 dollars to 2003 (annual) dollars using the CPI-U for “all items” (=

177.1 ÷ 159.1 = 1.1).

20 Life Tables. Table 6–3. “Expectation of Life at Single Years of Age, by Race and Sex: United States,

1995.” (NCHS, 1998).

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Final Ground Water Rule 5-89

the diabetes cases avoided as a result of corrective actions performed due to enterovirus contamination of

PWS wells.

The most comprehensive work regarding the economic burden of diabetes (both Type I and Type

II) in the United States was conducted for the American Diabetes Association. In their report “Economic

Consequences of Diabetes Mellitus in the United States in 1997,” Fox et al. (1998) presented the direct

medical and indirect costs attributable to diabetes, as well as a total and per capita estimate of

expenditures of people with and without diabetes. Improving on their estimates and methodology from

their 1992 effort (Fox et al., 1993), this national prevalence-based COI study also compares the health

care expenditures of diabetics in 1997 to nondiabetics.

The authors created a holistic estimate of the health care expenditures attributable to diabetes in

1997 by including: 1) medical expenditures attributable to diabetes (i.e., the cost due to the excess

prevalence of diabetes related chronic complications and general medical conditions in people with

diabetes), and 2) total medical expenditures incurred among people with diabetes (i.e., the cost for all

services for people with diabetes). Annual per capita expenditure estimates were also calculated and

defined as the sum of the expenditures for diabetics in 1997, divided by the 1997 diabetic population. 

The estimates do not, however, include pain and suffering nor do they include lost productive and leisure

time.

The per capita annual medical expenditures for people with diabetes was $13,092 for people with

diabetes versus $3,470 among people without diabetes. Therefore, the annual cost of diabetic care is

$9,622 per person.18 The annual net productivity loss for each person due to diabetes totaled $1,650 for

18–64 year olds and $528 for those 65 and older.19 These are sums of costs attributable to diabetes from

productivity loss from work, from restricted-activity and from bed-disability.

According to the 1980–1987 Hospital Cost and Utilization Project (HCUP), a national sample of

more than 500 hospitals that represent an unweighted 20 percent sample of discharges, the mean age of

diagnosis for a case of diabetes mellitus within the study was 53 (Elixhauser et al., 1993). Assuming that

a patient incurs treatment for diabetes each year throughout the duration of his expected life from age 53

(29.6 years)20, the present value estimate of the direct medical costs and indirect costs of illnesses would

be $227,032 using a 3 percent discount rate and $143,733 using a 7 percent discount rate. This figure

could be even greater if the cost of premature death or pain and suffering were incorporated. While this is

a simple approximation of the magnitude of a COI value for this illness, it captures the lifetime costs of

diabetes in those who survive the first year through their life expectancy period from the age of diagnosis.
21 Cost updated from January 1995 dollars to 2003 (annual) dollars using the CPI-U for “medical care

services” (= 278.8 ÷ 219.8 = 1.3).

Economic Analysis for the October 2006

Final Ground Water Rule 5-90

Myocarditis and Dilated Cardiomyopathy

Viral infection of the heart is relatively common and usually of little consequence (Kearney et al.,

2001). However, virus infection can lead to substantial cardiac damage and severe acute heart failure and

can also evolve into chronic heart failure (Kearney et al, 2001). Viral infection is the most common cause

of myocarditis. Viruses for which ground water is one possible route of exposure such as Coxsackie A

and B virus, echovirus and adenovirus can cause myocarditis (Kim et al, 2001; Magnani and Dec, 2006;

Huhn et al. 2005) with Coxsackie B virus the most often (of all viruses) associated with myocarditis

(Kearney et al. 2001). In addition to myocarditis, epidemiological studies from Finland have documented

an association between enterovirus infection and heart attacks (myocardial infarction) in men with no

prior evidence of heart disease (Reunanen et al, 2002).

Mean age of patients with active myocarditis is 42 years (Kearney et al., 2001). Sixty percent of

myocarditis patients had antecedent symptoms indicative of recent infection (Kearney et al. 2001). 

Myocarditis accounted for 22% of sudden unexpected death under age 30 and 11% of those between 30

and 40. Mortality is 20% at one year and 56% at four years (unless transplant occurs) (Kearney et al,

2001) largely due to chronic heart failure (dilated cardiomyopathy).

Myocarditis is included in the quantified benefits as a severe illness that can be caused by

echovirus and other enterovirus infection. However, myocarditis can lead to chronic heart disease

(dilated cardiomyopathy) which, like all chronic disease sequelae, are not quantified in the EA benefits. 

Myocarditis is a common cause of dilated cardiomyopathy, which in developed countries is the

underlying etiology in about 45% of patients undergoing heart transplants (Kearney et al. 2001). The EA

underestimates the benefits associated with preventing acute viral heart infections by coxsackievirus (and

adenovirus) because it focuses primarily on echovirus disease endpoints. Also and perhaps most

importantly, the EA quantifies only severe acute cases due myocarditis and neglects the chronic disease

sequelae associated with all enteroviral heart infections.

The annual direct COI associated with an “average case of heart disease” is estimated to be

$5,12921. This estimate is derived from data originally computed by of the National Center for Health

Statistics (NCHS) for “heart disease” (which includes International Class of Diseases, 9th Revision

(ICD–9) codes 391–398, 402, 404, 410–416, 420–429)(Hodgson, 1984; Hodgson, 1998). Since no

specific cost data were available for chronic myocarditis, or cardiomyopathy (ICD–9 code 425), annual
22 Chronic illness prevalence rates (cases per 1,000 individuals) for “heart disease” were multiplied by the

total U.S. population to obtain the total number of heart disease cases in 1995. The “average cost of heart disease”

per person in 1995 was subsequently calculated by dividing the total cost of heart disease in 1995 by the total

number of heart disease cases in 1995. Prevalence figures were from Current Estimates of the National Health

Interview Survey, 1995 (Benson and Marano, 1998), and the total U.S. population was obtained from the Census

Bureau.

23 Without more detailed information, this simplified method assumes that the cost of any heart disease,

whether ischemic or other, would be the same within this major disease group. This is a major limitation of these

estimates, as hospital costs for coronary heart disease may not be the same for hypertensive disease, for example.

24 Costs updated from January 1977 dollars to 2003 (annual) dollars using the CPI-U for “all items: (=

177.1 ÷ 58.5 = 3.0).

25 Costs updated from January 1977 dollars to 2003 (annual) dollars using the CPI-U for “all items: (=

177.1 ÷ 58.5 = 3.0).

Economic Analysis for the October 2006

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per capita costs for an “average case of heart disease” were computed using data on “heart disease” in

conjunction with prevalence numbers from the 1995 National Health Interview Survey.22,23

Indirect costs of “other heart disease” were estimated by Cropper and Krupnick (1990) who used

information from the 1978 Social Security Survey of Disabled and Work to model the effects of disease

on labor participation and earnings. Cropper and Krupnick found that the annual indirect cost ranged

from $3,447 to $7,074 depending on the age of the individual and the age of illness onset.24 Again, it is

important to note that these costs do not include pain and suffering.

According to the 1980–1987 HCUP study of 500 hospitals, the mean age of diagnosis for

cardiomyopathy was 60 (Elixhauser et al., 1993). Using this diagnostic category as a proxy for chronic

myocarditis,25 the lifetime COI could be substantial. For example, the present value of both direct and

indirect costs for a patient with the condition would be $61,117 given an average life expectancy of 21.1

years (7 percent discount rate). This figure could be even greater if the costs of lost earnings and of

premature death were incorporated.

Flaccid Paralysis

Flaccid paralysis is a rare but severe consequence of enterovirus infection. Flaccid paralysis

occurs most commonly upon poliovirus infection (about 1 in 200 infections) but vaccination has

eliminated almost all poliovirus cases. However there is no vaccine to prevent flaccid paralysis from

echovirus, coxsackievirus or enterovirus 70 and 71 (Grimwood et al, 2003; Rotbart, 1995) infection. 

Flaccid paralysis is more likely with echovirus than coxsackievirus but rare. For example, no flaccid

paralysis cases occurred as the result of an echovirus 18 outbreak in 2001 in 29 cases of viral meningitis

from (surface) drinking water at an Alaska camp (McLaughlin et al, 2004). In an echovirus 33 outbreak

in New Zealand in 2000, one healthy three-year old (of 75 infected persons) suffered flaccid paralysis

(Grimwood et al, 2003); two infants died (Huang, et al. 2003). McMinn et al. 2001 report two cases of

Guillain-Barre paralysis among 14 children neurologically ill from enterovirus 71 during a 1990 outbreak

in Western Australia. For the period 1970-1979, CDC reports 58 paralysis cases due to enteroviruses

with most cases due to echovirus (Moore, 1982). The EA does not explicitly include benefits associated

with preventing flaccid paralysis because the disease is so infrequent.
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Final Ground Water Rule 5-92

5.4.3 Decreased Incidence of Bacterial Illness and Death

Although the EA does not quantify the benefits of bacterial illnesses that may be avoided by the

GWR, EPA believes that these benefits could be substantial. EPA believes that if a fecal indicator occurs

in a PWS well it demonstrates that a pathway exists for pathogens to travel from a fecal contaminant

source to the well. Furthermore, if such a pathway exists, EPA believes it is only a matter of time before

pathogens (viral or bacterial) excreted by infected animals or individuals reach the well. Such exposure

might then cause illness among populations using undisinfected water from the well. There is a larger

range for bacterial sources of contamination than sources of viral contamination because bacterial

pathogens that also cause illness in humans can originate from animal reservoirs (infected livestock)

whereas most viruses that cause illness in humans do not. Identifying and eliminating or treating such

sources of contamination under the GWR will result in reduced exposure to bacterial pathogens and

illness avoided. Bacterial contamination can occur in wells in both sensitive and non-sensitive aquifers. 

However, because the bacteria are larger than the viruses, they are less mobile in non-sensitive aquifers

and are more likely to occur in wells in sensitive aquifers and in shallow wells in non-sensitive aquifers. 

The nonquantified benefits of bacterial illness avoided could be much larger than that predicted for

viruses because the severity of some of the symptoms associated with bacterial illness are worse than

some of the symptoms of viral illness. The following is a discussion of different bacterial pathogens

found in ground water and their associated clinical symptoms if ingestion results in illness.

5.4.3.1 Bacterial Pathogen Occurrence

The bacterial pathogens can be divided into two groups; the frank pathogens such as E. coli

O157:H7 and the opportunistic pathogens, such as Pseudomonas aeruginosa. The opportunistic bacterial

pathogens found in drinking water have been well summarized by Rusin et al (1997) and will be

discussed later when exposure scenarios other than contaminated source water are considered. This

discussion will focus on the frank bacterial pathogens that are found in fecally contaminated ground

water. Unlike the viral pathogens, the frank bacterial pathogens can be excreted by animals (typically

birds and mammals) but some, such as Helicobacter Pylori and Legionella pneumophila are naturally

present in ground water.

E. coli

The group of bacteria known as E. coli contain both pathogenic and non-pathogenic isolates. The

most dangerous E. coli bacteria contain the gene for producing Shiga toxins. E. coli O157:H7 is the most

widespread shiga-toxin producing E. coli but at least 81 serotypes have been identified (Prager et al,

2005). Release of toxins in the body can result in kidney failure, shock and death in otherwise healthy

individuals, especially small children. Typically, kidney failure occurs in 2-7% of illnesses. Death or

end-stage renal disease occurs in about 12% of patients four years after diarrhea-associated kidney failure

(Garg et al, 2003). Twenty five percent of kidney failure survivors demonstrate long-term renal sequelae

(Garg et al, 2003). For patients with moderate and severe gastroenteritis caused by E. coli, long-term

study shows that they have an increased risk of hypertension and reduced kidney function (Garg et al.

2005). CDC estimates that drinking water is responsible for 15% of the 73,000 illnesses each year from

E. coli O157:H7 in the United States (Rangel, 2005).

Ground water outbreaks due to E. coli O157:H7 are prominent because of the fatal outcomes

associated with those outbreaks. In Walkerton, Ontario, 6 individuals died and 27 developed kidney
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Final Ground Water Rule 5-93

failure from ground water contaminated with E. coli O157:H7 (and Campylobacter jejuni) (Health

Canada, 2000). The aquifer was sensitive (karst) and fecal contamination often occurred. The outbreak

coincided with a reduction in chlorination treatment coincident with a large fecal contamination event. In

Washington County, NY, two individuals (including an otherwise healthy two year old child) died from

E. coli O157:H7 contamination of a county fair water supply system. The aquifer was thin and shallow

but not sensitive. (The fair ground’s water supply system was not recognized as a PWS system because it

was used for less than 60 days each year.) Four individuals died in Cabool, MO due to E. coli O157:H7

(Swerdlow et al, 1992). This aquifer was sensitive (karst) and multiple illnesses (above normal levels)

occurred before a water main break so the outbreak was likely due to source water contamination. 

Another E. coli O157:H7 outbreak occurred in ground water in Minnesota but no kidney failures resulted.

Although manure is often considered to be the source of shiga-toxin producing E. coli, they have

also been isolated from municipal sewage (Holler et al, 1999). E. coli O157:H7 was found to survive on

a pasture surface for almost 4 months. About 4-15% of cases are acquired via secondary transmission

(Parry and Salmon, 1998). In addition to the shiga-toxin producing E. coli, there are a substantial number

of other pathogenic E. coli bacteria, mostly through production of other toxins. Hunter (2003) identifies

62 E. coli strains capable of causing diarrheal disease. Little data are available on the hazard associated

with waterborne transmission for most of the pathogenic E. coli other than E. coli O157:H7.

Although E. coli is monitored in PWS wells via the Total Coliform Rule, the EPA-approved

methods are not capable of identifying the shiga-toxin producing E. coli. Because E. coli are often found

in ground water supplies and because low doses can result in infection and secondary transmission is

significant, it is likely that disease due to E. coli is quite prevalent in association with PWS wells. Few

data on pathogenic E. coli in PWS wells are available. Dose response data are limited to a single point

value from a carefully documented outbreak in Japan. This point value suggests that the infectious dose

is very low compared with most pathogenic bacteria. Because few data are available on the occurrence of

pathogenic E. coli in PWS wells and dose response data are limited, the benefits of avoided illness and

chronic sequelae from the GWR can only be qualitatively discussed.

Shigella

Shigella bacteria are distinct because they are often associated with bloody diarrhea (bacillary

dysentery). The enterohemorraghic E. coli bacteria acquired the capability to produce toxins by

exchanging plasmids with Shigella. Thus, Shigella often also cause kidney failure and chronic kidney

disease. Shigella contamination only results from human fecal contamination and thus it is probably less

common than E. coli contamination, which has both human and animal sources. Shigella are one of the

most easily recognized causes of waterborne disease outbreaks because the advent of bloody diarrhea

spurs detailed investigations and often a cause is identified, even though Shigella are difficult to cultivate. 

One large ground water outbreak in a sensitive aquifer occurred recently in Island Park, Idaho due,

perhaps, to an unidentified broken sewer line contaminating the well water (CDC, 1996). Because

Shigella is associated only with human feces, there is little incentive to look for Shigella as compared

with all the other bacterial pathogens that have both human and animal sources. As a result, no data are

available on occurrence although limited dose response data are available. EPA is unable to quantify the

benefits from avoided Shigella illness because no occurrence data are available.
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Campylobacter and Arcobacter

Campylobacter (like Salmonella) are very common contaminants of food and water. 

Campylobacter is commonly associated with animal manure, especially cow and chicken manure. 

Campylobacter and Salmonella are associated with many common source (food or water) exposure

deaths, probably in large part because there are a large number of illnesses. More deaths may be

associated with Campylobacter and Salmonella than with viruses. Uniquely, Campylobacter is often

associated with Guillain-Barre paralysis that can last for weeks or months. About 1 paralysis case occurs

for every 1000 cases of campylobacteriosis (Altekruse et al, 1999). About 20% of paralysis patients are

left with some disability and approximately 5% die. Campylobacterosis is also associated with Reiter

syndrome (reactive arthritis). Approximately 1% of patients with camplybacterosis have arthritis onset in

one or more joints (especially the knee) in the 7 to 10 days after diarrheal onset (Altekruse et al. 1999).

The E. coli O157:H7 ground water outbreak in Walkerton, Ontario was also a large outbreak of

campylobacterosis. Arcobacter (now a separate genus from Campylobacter) was responsible for a ground

water outbreak at a camp in Coeur d'Alene, Idaho (McMillan, 1996). The sensitive aquifer was

contaminated by a septic tank. Campylobacter were associated with the recent outbreak in South Bass

Island, Ohio due to widespread fecal contamination in a sensitive aquifer (Ohio EPA, 2005). Like all

bacterial pathogens, special enrichment methods are needed to identify Campylobacter and Arcobacter in

environmental samples and so no data are available on the occurrence of these ubiquitous pathogens in

PWS well water. Campylobacter, like Vibrio has a viable but non-culturable environmental form which

makes it difficult to detect at times in water (Rollins and Colwell, 1986; Koenraad et al., 1997). Limited

dose-response data are available for Camplybacter (but not for Arcobacter). Because no occurrence data

are available, EPA is unable to quantify the benefits associated with avoided camplybacterosis (and

arcobacterosis) and their chronic sequelae (Guillane-Barre paralysis and reactive arthritis).

Salmonella

Salmonella causes typhoid fever, once a common and dangerous waterborne disease. Typhoid is

no longer a problem in the United States, and in recent years, Salmonella has become increasingly less

common as a common source outbreak agent while campylobacterosis outbreaks have correspondingly

increased. The reasons for this change are unclear. Salmonella was identified in most fecally

contaminated PWS wells during the South Bass Island, OH outbreak in 2004 (Ohio EPA, 2005). The

main problems associated with Salmonella result from scenarios other than fecal source water

contamination. For example, the seven deaths that occurred due to Salmonella contamination in a ground

water PWS system in Gideon, Missouri were due to bird entry into a storage tank (Angulo et al., 1997).

Salmonella resulted in a very large outbreak in a ground water utility in Riverside, California during the

1960s (16,000 illnesses, 70 hospitalizations and 3 deaths) prior to the advent of the Total Coliform Rule

(Boring et al., 1971). This issue will be discussed further below. Limited dose-response data are

available for Salmonella but no occurrence data. The GWR EA provides nonquantified benefits resulting

from corrective actions such as disinfection that would mitigate against salmonellosis resulting from

animal entry into the distribution system or Salmonella contamination of PWS wells in general.

Legionella

Legionella are opportunistic bacterial pathogens that colonize water distributions systems. An

estimated 8,000-10,000 cases of Legionaires disease and Pontiac fever occur in the U.S. each year due to

Legionella. Twenty-one of 48 known species are able to infect humans. A study of 46 PWS wells from
26Because viral illnesses are generally more difficult to identify than bacterial illnesses, all illnesses with

unidentified causes were considered to be viral illnesses. This assumption most likely leads to an underestimate of

the ratio of bacterial to viral illness associated with reported outbreaks.

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16 water utilities in the United States and Canada showed that 38 wells (82%) were positive for

Legionella. Also, 33% of 114 PWS well samples were positive for Legionella. About half the identified

Legionella species were pathogenic forms. The authors conclude that this is the “first study that has

unambiguously proven that Legionella constitute a part of the microflora of ground water not known to be

under the direct influence of surface waters” (Riffard et al., 2004). EPA calculates benefits associated

with fecal contamination. However, Legionella are present in ground water in the absence of fecal

contamination and constitute a potential disease hazard if the bacterium is inhaled during showering.

Although nationally representative Legionella occurrence data are available for ground water, the

methods used are not typical or standardized. Also, no dose-response data exist so it is not possible to

quantify the disease burden from ground water exposure. If disinfection is required as a corrective

action, it will minimize the Legionella contamination of the distribution system. However, the GWR EA

only qualitatively accounts for the avoided illnesses from Legionella inhalation.

5.4.3.2 Estimate of Potentially Avoided Bacterial Caused Deaths by GWR

The quantified benefits in the EA predicts that among the 27% of the wells having sometime fecal

contamination about 34% (of the 27%) of these wells will be identified by triggered monitoring and be

required to take remedial action. The subsets of wells that fall into this category include 1) wells

predicted to have both viral and E. coli presence and identified by indicator monitoring (about 2/3 of the

27%) and 2) wells predicted to have E. coli presence but no viral presence and identified by indicator

monitoring (about 1/3 of the 27%). The quantified benefits model only addresses avoiding viral illness in

the first of these categories.

Although EPA did not formally quantify the benefits of avoided bacterial illness, EPA developed

a rough estimate of the potential deaths that might be prevented by reduced exposure to bacterial

pathogens under the GWR (to supplement the quantified benefits from virus exposure). The following

analytical steps were taken to generate such an estimate.

1) Estimate potential bacterial illnesses avoided 

Analysis of outbreak data from 1991 through 2000, shows a total of 2,346 bacterial illnesses

compared to 1,806 viral illnesses and 4,523 illnesses of unknown etiology (see Exhibit 2.3) in section

2.2.1, compiled from CDC 1993, Kramer et al., 1996, Levy et al., 1998, Barwick et al., 2000, and Lee et

al., 2002). If the illnesses of unknown etiology are assumed to be viral26, then a total of 6,329 waterborne

viral illnesses would be associated with the waterborne outbreaks. The ratio of bacterial waterborne

illness to viral waterborne illness in outbreaks is therefore 0.37:1.

If we assume that this ratio of bacterial to viral waterborne illness also pertains to the relative rate

of endemic bacterial and viral illness prevented due to the GWR, then for every viral illness avoided

under the GWR we will also avoid an additional 0.37 of bacterial illness; i.e., relative to the quantified

cases of viral disease avoided, we would avoid 16,805 bacterial illnesses per year (41,868 predicted viral

illnesses avoided per year x 0.37 = 15,491).
27Bacterial illnesses are more likely to be diagnosed than viral illnesses because of their severity. However,

most cases of diarrhea associated with outbreaks are not identified by etiology and identifying etiology is

unnecessary in order to identify an outbreak.

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Final Ground Water Rule 5-96

It is possible that the ratio of bacterial to viral endemic illness due to ground water is lower than

0.37:1 because the likelihood of detecting an outbreak due to bacterial illness may be greater than that of

detecting a viral outbreak27. However, any potential overestimate is likely to be compensated by the

assumption that all cases of outbreak illness of unknown etiology are viral. EPA recognizes that the

extrapolation from the ratio of outbreak etiology to the ratio of endemic illness etiology remains a major

uncertainty in this analysis and that the impacts of the two opposing biases on the extrapolated estimate is

unknown. 

2) Estimate a mortality rate for waterborne bacterial illness 

The approach taken for this step was to a) recognize the types and distribution of bacterial illness

associated with waterborne disease, b) characterize mortality rates for the different types of bacterial

illness identified in “a”, and c) estimate a composite mortality rate considering “a” and “b”. 

For a), EPA used the same waterborne disease outbreak information from Exhibit 2.3, cited

above, to inform the types and distribution of bacterial illness in ground water systems.

For b), EPA used data from Mead et al (1999) (Table 3) to estimate mortality rates for each type

of bacterial illness identified in waterborne disease outbreaks in ground water systems (from Exhibit 2.3).

While Table 3 in Mead et al. (1999) provides estimates for illnesses, hospitalizations and deaths caused

by foodborne pathogens for specific bacterial agents, some of these agents have also been recognized as

causing waterborne disease (namely E. coli O157:H7, Salmonella non-typhoidal, Salmonella typhi,

Shigella, and Campylobacter spp). Therefore, EPA considers it appropriate to apply the calculated

mortality rates from Mead et al. (1999) to the same bacterial pathogens identified in waterborne disease

outbreaks. These mortality rates estimated from Mead ranged from 3.64 per 1,000 illnesses for

Salmonella typhi to 0.055 per 1,000 illnesses for Campylobacter spp. Fatality rates of other illnesses

caused by potentially waterborne bacterial pathogens included 0.83 per 1,000 illnesses for E. coli O157,

0.41 per 1000 for Salmonella non-typhoidal, and 0.16 per 1,000 for Shigella, and 2.54 for Vibrio the least

frequently reported ground water associated waterborne bacterial illness.

For c), EPA applied the above case fatality rates, calculated from Mead et al. (1999), to the illness

case rate reported in Exhibit 2.3, for each of these bacterial illnesses. EPA then calculated a weighted

average mortality rate for waterborne bacterial illness of 0.64 deaths per 1000 illnesses (see Exhibit 5.25). 

In using mortality rates associated with foodborne illness, EPA assumes that differences in exposure

scenarios do not lead to differences in illness manifestation. 

EPA thinks that the above estimate is not unreasonable because the spread among the mortality

rates of the different bacteria in Exhibit 5.25 is relatively small and therefore, giving a different weight

(e.g. based on additional information) to one particular agent over another would not significantly change

the estimate. The four most influential pathogens (Shigella, Campylobacter spp., E. coli O157,

Salmonella (non-typhoidal) in the weighted average had a relatively small difference in their case fatality

rate. The illness with the lowest case fatality rate, Vibrio, had a very small reported incidence of

waterborne disease associated with it.
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Final Ground Water Rule 5-97

Pathogen

Illnesses 

(thousands) Hospitalizations

Hospitalizations/1000 

cases of illness

Cases of 

illness in 

WBDO

Fraction of 

WBDO illness

WBD illness 

hospitalizations/

1000 cases

A B C = B/A D E = D/Total D F = (C/1000) * E

Campylobacter spp 2,454.0 13,174 5.37 223 0.095 5.10E-04

E. coli O157 * 73.5 2,168 29.50 807 0.344 1.01E-02

Salmonella typhi 0.8 618 750.00 124 0.053 3.96E-02

Salmonell non-typhoidal 1,412.0 16,430 11.64 625 0.266 3.10E-03

Shigella 448.0 6,231 13.91 556 0.237 3.30E-03

Vibrio other 7.9 99 12.56 11 0.005 5.89E-05

 2,346 Composite 

case 

hospitalization 

rate: 

5.68E-02

Source:

(A) Data of pathogen specific illnesses from Table 3 in Mead paper.

(B) Data of pathogen specific deaths from Table 3 in Mead paper.

WBDO Total Cases:

* EPA assumed that E. coli O157 represents pathogenic E. coli identified in drinking water because it was the E. coli strain identified as the 

etiologic agent responsible all of the pathogenic E. coli related ground water outbreaks. Other strains of pathogenic E. coli also cause 

waterborne illness; however, they have not been identified as the etiologic agent of a ground water associated disease outbreak in the CDC 

waterborne outbreak surveillance reports referenced in Exhibit 2.3.

** vibrio (other): i.e., not V. cholerae or vulnificus

Note: Estimated Total number of hospitalizations due to bacterial illness = estimated number of cases (15,491) x Bacterial 

Composite Case Hospitalization Rate (15,491x 0.0568 = 880 hospitalizations/year).

(D) Cases of illness from CDC outbreak surveillance reports in Exhibit 2.3. "Etiology of Waterborne Outbreaks in Ground Water Systems, 1991 - 

2000," (Kramer et al., 1996; Levy et al., 1998; Barwick et al., 2000; and Lee et al., 2002).

With regard to E. coli, EPA only considered O157 in the mortality rate estimate because most of

the pathogenic E. coli in reported waterborne disease outbreaks were identified as O157. The Mead paper

reports two O157 strains with essentially the same case fatality rate and two other E. coli strains that are

not associated with mortality. Any E. coli o157 before 1993 would probably not have been identified as

such since it was only recognized as a pathogen in 1982 and more broadly recognized only in 1993 after a

multi-state foodborne E. coli outbreak (Rangel et al., 2005). However, it is probable that all four strains

cause sporadic cases or even unidentified outbreaks of waterborne disease. If all four strains were

included in the calculation of mortality rate for pathogenic E. coli and weighted equally, the case fatality

rate for all pathogenic E. coli would have dropped by approximately 50% and the composite mortality

rate factor, calculated in Exhibit 5.25, would have dropped by approximately 15%.

3) Estimate potential annual bacterial deaths avoided by the GWR

EPA multiplied the composite mortality rate from (2) above (6.41 x 10-4) by the estimated annual

bacterial illnesses avoided in (1) (15,491) to estimate 10 potential deaths avoided per year. The

assumptions underlying these calculations are dependent on a variety of judgements. Other assumptions

are equally likely. EPA believes this calculation provides a plausible estimate of potential additional

deaths avoided from exposure to bacteria in GWSs. 

Exhibit 5.25 Estimated Bacterial Illnesses and Deaths Avoided
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Final Ground Water Rule 5-98

5.4.3.3 Estimate of a Hospitalization Rate for Waterborne Bacterial Illness

EPA used the same approach for estimating potential hospitalizations avoided by a reduction in

the incidence of bacterial illness, as it did for estimating potential deaths avoided. In order to estimate a

hospitalization rate due to waterborne bacterial illnesses, a composite hospitalization rate was developed

that represents the hospitalization rate for all waterborne bacterial pathogens adjusted by the frequency of

their occurrence as the etiologic agent in WBDOs. The data presented in Mead et al. (1999) represent

bacterial illnesses and hospitalizations due to all different exposures, e.g. food, person to person spread,

waterborne. By using information on the relative frequency of illness caused by different waterborne

pathogens under outbreak conditions we have developed a weighting scheme specific for considering

waterborne illness health effects and associated burden (hospitalization). 

Exhibit 5.26 below presents the data used in the calculations and the results of the calculations

described as follows: The hospitalization rates (in column 4) were calculated from the cases of illness due

to all causes (column 2) and the number of hospitalizations (column 3) from Table 3 of Mead P.S. et al,

(1999). In order to develop the composite waterborne bacterial hospitalization rate, the etiologic fraction

was calculated by dividing cases of illness of a specific etiology from WBDOs by the total number of

WBDO cases of illness. An occurrence weighted hospitalization rate is calculated by multiplying the

etiologic fraction of WBDO cases (column 6) by the etiologic agent’s hospitalization rate (column 4). 

Lastly, the composite bacterial hospitalization rate is calculated by summing the weighted rates in column

7. The result is an integrated, or composite bacterial hospitalization rate of 57 hospitalizations/ 1000

cases of waterborne bacterial illness.

EPA estimated the potential hospitalizations avoided (from reduced bacterial illness) by

multiplying the estimate for bacterial illness avoided (15,491) by the composite bacterial hospitalization

rate of 57/1000 cases of illness to indicate 880 annual potential hospitalizations. If the average bacterial

hospitalization cost is assumed to be greater than the Type B viral illness adult hospitalization cost used in

the quantified benefits section ($5,000 - see Exhibit 5.22 E), then the benefits of preventing bacterial

illness would be $4.4 million or more.
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Final Ground Water Rule 5-99

Pathogen

Illnesses 

(thousands) Hospitalizations

Hospitalizations/1000 

cases of illness

Cases of 

illness in 

WBDO

Fraction of 

WBDO illness

WBD illness 

hospitalizations/

1000 cases

A B C = B/A D E = D/Total D F = (C/1000) * E

Campylobacter spp 2,454.0 13,174 5.37 223 0.095 5.10E-04

E. coli O157 * 73.5 2,168 29.50 807 0.344 1.01E-02

Salmonella typhi 0.8 618 750.00 124 0.053 3.96E-02

Salmonell non-typhoidal 1,412.0 16,430 11.64 625 0.266 3.10E-03

Shigella 448.0 6,231 13.91 556 0.237 3.30E-03

Vibrio other 7.9 99 12.56 11 0.005 5.89E-05

 2,346 Composite 

case 

hospitalization 

rate: 

5.68E-02

Source:

(A) Data of pathogen specific illnesses from Table 3 in Mead paper.

(B) Data of pathogen specific deaths from Table 3 in Mead paper.

WBDO Total Cases:

* EPA assumed that E. coli O157 represents pathogenic E. coli identified in drinking water because it was the E. coli strain identified as the 

etiologic agent responsible all of the pathogenic E. coli related ground water outbreaks. Other strains of pathogenic E. coli also cause 

waterborne illness; however, they have not been identified as the etiologic agent of a ground water associated disease outbreak in the CDC 

waterborne outbreak surveillance reports referenced in Exhibit 2.3.

** vibrio (other): i.e., not V. cholerae or vulnificus

Note: Estimated Total number of hospitalizations due to bacterial illness = estimated number of cases (16,805) x Bacterial 

Composite Case Hospitalization Rate (15,491x 0.0568 = 880 hospitalizations/year).

(D) Cases of illness from CDC outbreak surveillance reports in Exhibit 2.3. "Etiology of Waterborne Outbreaks in Ground Water Systems, 1991 - 

2000," (Kramer et al., 1996; Levy et al., 1998; Barwick et al., 2000; and Lee et al., 2002).

Exhibit 5.26 Waterborne Bacterial Illness Hospitalization Rates
Economic Analysis for the October 2006

Final Ground Water Rule 5-100

Summary of Nonquantified Benefits for Bacterial Illness Avoided

EPA estimated that the total benefits could increase by a factor of five by only accounting for

additional deaths and hospitalizations caused by bacterial illness being avoided. The actual number of

hospitalizations and deaths avoided could be higher or lower. Within the context of best available science,

given all the other nonquantified benefits for chronic bacterial illnesses avoided, EPA believes that the

total nonquantified benefits for bacteria could exceed a factor of four relative to the quantified benefits

for viruses. If a value of $7.5 million is assumed for each death avoided (see Section 5.3.1.2), then the

value of bacterial deaths avoided each year would be approximately $75 million (year 2003 dollars). If a

value of $5,000 is assumed for each hospitalization avoided (see Exhibit 5.22e), then the value of

bacterial hospitalizations avoided each year would be approximately $4.4 million (year 2003 dollars). 

Taken together, these additional benefits would result in benefits that are five times the quantified

benefits for viruses (four times quantified benefits plus quantified benefits) [i.e., (75 + 4.4+ 19.7)/19.7 =

5].

5.4.4 Other Chronic and Acute Illness Potentially Avoided

As discussed in Section 5.1, the GWR EA quantifies only a small subset of the total benefits. 

Only acute illnesses arising from Type A virus represented by rotavirus data and Type B virus

represented by enterovirus data are quantified. Acute illnesses from other viral etiologies and from

bacterial infection are not quantified. Also, chronic illnesses resulting from either viral or bacterial illness

are not quantified. This section addresses some of the chronic disease endpoints that are not quantified in

this EA and are only qualitatively assessed.

Hypertension and Reduced Kidney Function

As a result of the large number of illnesses, hospitalizations and deaths due to E. coli O157:H7

and Camplybacter contamination at Walkerton, Ontario, a long term study was undertaken to evaluate

chronic sequelae (Garg et al, 2005). This is the largest and longest study ever of chronic sequella after

ground water exposure. After a mean follow-up of 3.7 years after the outbreak, patients with moderate

and severe gastroenteritis had an adjusted relative risk of hypertension of 1.15 (0.97-1.35) and 1.28

(1.04-1.56) respectively. A similar association was seen for reduced kidney function. The authors (Garg

et al., 2005) conclude:

“Adults with symptomatic bacterial gastroenteritis from drinking contaminated water were more

likely than asymptomatic adults to have newly diagnosed hypertension and reduced renal

function during the follow-up period of almost 4 years after infection.”

This new finding documents that an acute self-limiting bacterial gastroenteritis is likely to be

followed by hypertension and reduced kidney function in a significant subset of individuals. As

discussed in Section 5.4.3.1, bacterial gastroenteritis is a frequent occurrence in the U.S. resulting from

both epidemic and endemic exposure. It is likely that a similar study of endemic acute self-limiting

bacterial gastroenteritis would also document increased likelihood of these two chronic disease sequelae.

The GWR EA quantifies only acute illnesses resulting from some virus infection. The EA does

not quantify acute bacterial disease, including acute self-limiting bacterial gastroenteritis. The EA also

does not quantify the chronic disease sequelae such as hypertension and reduced renal function that can
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Final Ground Water Rule 5-101

arise from acute illness. Because bacterial disease and their chronic sequelae are considered only

qualitatively, the GWR EA underestimates the benefits associated with bacterial illness.

Helicobacter pylori

Helicobacter pylori is often associated with ground water (Hegarty et al. 1999; Rolle-Kampzczyk

et al, 2004) and is known to cause gastric ulcers. However, Helicobacter is not culturable and so

occurrence data from ground water are fairly uncertain. Improved hygiene and water treatment have

together reduced the number of ulcers caused by this organism over the last few decades but it is

impossible to quantify that decrease. Nevertheless, corrective action and especially disinfection resulting

from the GWR will likely provide a reduction in the number of intestinal colonizations by Helicobacter

pylori and a corresponding decrease in gastric ulcers. The GWR EA does not quantify the benefits

associated with avoiding bacterial disease. Because chronic infection by Helicobacter pylori can lead to

gastric ulcers, there are significant health effects potentially avoided due to Helicobacter pylori infection

that are considered in this EA only qualitatively.

Reactive Arthritis, Irritable Bowel Syndrome and Persistent Diarrhea

A recent study (Rees, et al, 2004) evaluated the chronic sequelae resulting from enteric infection

identified but the California FoodNet Surveillance. Eight percent of respondents reported new joint pain

after infection and 35% reported new gastrointestinal symptoms including persistent diarrhea and irritable

bowel syndrome. Reiter's Disease is form of reactive arthritis which, as discussed in the section

describing the nonquantified benefits associated with Campylobacter, is often associated with

Campylobacter infection.

Primary Amoebic Meningioencephalitis (PAM)

In 2003, two five-year old boys living in the same water service area near Phoenix AZ died in the

same week from Primary Amoebic Meningioencephalitis (PAM) (Marciano-Cabral et al, 2003). Both

boys lived in homes supplied by untreated PWS wells. Atypically, the wells in that area provide water at

elevated temperatures, representing the elevated geothermal gradient in the subsurface. Seventeen

samples taken from the boys homes were positive for Naegleria fowleri and N. fowleri was also

responsible for the boy's deaths from PAM. It is likely that the heated ground water provided a suitable

habitat for N. fowleri colonization and growth either in the aquifer, the well, the distribution system or the

household plumbing. N. fowleri is effectively treated with disinfection or chlorination. The final GWR

may require systems with elevated ground water temperature to take corrective action such as disinfection

if, for example, the elevated temperature is noted in a sanitary survey. However, EPA is unable to

quantify the number of PAM cases that would be avoided in the future, so the benefits are presented only

qualitatively.

Cryptosporidium and Giardia

Cryptosporidium and Giardia are associated with surface water rather than ground water PWS

systems. If Cryptosporidium or Giardia are recognized in well water, the system should be considered as

a surface water system (ground water under the direct influence of surface water [GWUDI]) rather than as

a ground water system. As a GWUDI system, these wells are regulated by the Long Term 2 Surface

Water Treatment Rule and not by the GWR. However, on several occasions, PWS wells were regulated

as if they were ground water rather than as surface water until a cryptosporidiosis or Giardiasis outbreak
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was recognized. Examples of Cryptosporidiosis outbreaks associated with ground water wells (not

recognized as GWUDI wells) located in sensitive aquifers includes outbreaks in Braun Station, TX

(D'Antonio et al, 1985), Reading, PA (Moore et al, 1993), Brushy Creek, TX (Lee et al., 2001) and

Yakima, WA (Dworkin et al, 1996). The sanitary survey and hydrological sensitivity assessments under

the GWR rule may identify some systems as being under the direct influence of surface water and thereby

make such systems subject to surface water treatment technique requirements and avoid potential

outbreaks. Such actions would result in both increased costs and benefits for such systems. 

5.4.5 Reduction in Outbreak Risk and Response Costs

Besides reducing the endemic risk of illnesses from waterborne pathogens, the GWR will reduce

the likelihood of major outbreaks from occurring. These avoided illnesses and other costs are not

estimated or included in the GWR benefits estimates and would be difficult to quantify. The economic

value of reducing the risk of outbreaks could be quite high when the magnitude of potential costs is

considered. Other types of costs associated with outbreaks include spending by local, State, and national

public health agencies; emergency corrective actions by utilities; and possible legal costs if liability is a

factor. Affected water systems and local governments may incur costs through provisions of alternative

water supplies and issuing customer water use warnings and health alerts. Commercial establishments

(e.g., restaurants) and their customers may incur costs due to interrupted and lost service. Local

businesses, institutions, and households may incur costs associated with undertaking averting and

defensive actions. Cost-benefit analyses of large engineering works typically include probabilistic failure

assessment to determine the likely benefits of avoiding catastrophic effects. Such analyses are not

included in the EA quantified or nonquantified benefits because there are too many likely failure

scenarios. Thus, to the extent that GWR reduces the likelihood of waterborne disease outbreaks, avoided

response costs are potentially numerous and significant.

During outbreaks, consumers and businesses may use alternative water sources or practice

behaviors to reduce risk, such as boiling water. If the rule reduces the need for these averting behaviors,

an economic benefit will accrue. To give a sense of the possible scale, the expenditures on averting

behaviors during an outbreak of Giardiasis, such as hauling in safe water, boiling water, and purchasing

bottled water, were estimated at between $3.10 to $9.80 per person per day (year 2003 dollars) during the

outbreak (Harrington et al., 1991). If these figures are applied to even a small drinking water system

serving 10,000 customers, total expenditures on averting behavior during a waterborne disease outbreak

could range between $31,000 and $98,000 per day. Determining the precise reduction in outbreak risk

and the resulting benefits due to reduced or avoided averting behavior is not possible given current

information, but potential benefits are expected to be substantial.

Five studies were identified that used the averting cost approach to estimate household and other

costs attributable to short-term contamination of drinking water supplies (Abdalla, 1990; Abdalla et al.,

1992; Harrington et al., 1991; Sun et al., 1992; Van Houtven et al., 1997). The most relevant of these for

the GWR analysis is a study by Harrington et al. (1991), that analyzes the costs associated with drinking

water contamination by Giardia in Luzerne County, Pennsylvania. The December 1983 outbreak resulted

in 366 confirmed Giardiasis cases resulting from sewage leaking into the unfiltered source water. The

total affected population was 75,000 individuals across Pittston Burough and 17 other municipalities. 

The Harrington study also developed a theoretical and empirical example of how outbreak costs are

incurred, based on the Luzerne County example.
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The four steps associated with a waterborne outbreak that may impose costs on society are

discovery, survey and testing, reaction, and aftermath (Harrington et al., 1991). These are described

below:

• Discovery. Health care providers or State, local, or hospital laboratory technicians send

reports to State authorities notifying them of the need for further investigation when the

rate of new cases suddenly increases above the normal rate.

• Survey and testing. A host of epidemiological surveys may be conducted, along with

tests of the water supply, once a few cases are confirmed.

• Reaction. Local authorities and the water system may issue boil-water advisories, or

other warnings to reduce exposure once a link is made between the drinking water supply

and the disease outbreak. Businesses, as well as households, may be affected by such

action, requiring government agencies to begin surveillance and enforcement activities

and, in some cases, provide alternative water sources.

• Aftermath. This final step involves discussions of any long-term solutions to the

problem, and how the costs of the outbreak and prevention of future ones may be shared.

These discussions can only take place once the outbreak is contained by actions taken

during the previous phase.

The Luzerne County outbreak resulted in losses due to actions taken by individuals to avoid the

contaminated water that are estimated to be between $36.8 million and $109.4 million (year 2003 dollars). 

The predominant cost was time lost to boiling water. Losses due to averting actions for restaurants, bars,

schools and other businesses during the outbreak exceeded $1.8 million. The burden for government

agencies was $407,300 and the outbreak cost the water supply utility $3.2 million. These costs do not

include legal fees, outbreak effects on businesses that were not investigated, leisure activities, or net

losses due to substituting more expensive beverages for tap water. During a waterborne disease outbreak

in Walkerton, Ontario (population 5,000), an analysis conservatively estimated the economic impact

excluding medically related costs to be over $43 million in Canadian dollars (approximately $32 million

in U.S. dollars) (year 2003 dollars) (Livernois, 2002).

5.4.6 Reduced Disinfection Treatment Failure Rates and Associated Waterborne Disease

Implementation of the GWR may lead to additional benefits from reductions in disinfection

failures. Such benefits would stem from the increased oversight of treatment processes as part of

compliance with regulatory requirements (e.g., during sanitary surveys and compliance monitoring, or

with upgrades in disinfection to 4 log inactivation of viruses). 

Direct data on the numbers of illnesses and deaths resulting from treatment failure are not

available. However, these numbers could be substantial given that the relative rates outbreak related

illness attributed to treatment deficiencies versus outbreak related illnesses attributed to source water

deficiencies in untreated ground waters. Of the outbreak-related illnesses due to viral, bacterial, and

unknown agents reported in GWSs during 1991–2000 (see Exhibit 4.31), 4,224 were attributable to

drinking untreated ground water and 4,888 were attributable to a treatment deficiency. 
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EPA’s baseline estimate among disinfected supplies assumes that all disinfected supplies are

providing either 2 log or 4 log inactivation of viruses and does not account for occasional disinfection

failures or upsets. Given this simplifying assumption, the baseline estimate for viral disease among

disinfected supplies is about 2,500 cases, whereas the baseline risk for the undisinfected supplies is about

179,700 cases (approximately 1.4% of illnesses we estimate to occur in currently disinfecting wells).

However, based on outbreak data, an additional 1.16 (4,888/4,224) outbreak-related illnesses occur in

systems using disinfection with treatment failures for every outbreak-related illness in systems with

untreated ground water. If this same ratio were to apply to endemic illness in disinfected versus

undisinfected supplies, the baseline incidence of disease in disinfected supplies (taking disinfection

failures into account) would be roughly 80 times higher than currently estimated, i.e., 1.16 x

179,700/2,500 additional illnesses per year. Even small percent reductions in disinfection failures or

upsets resulting from this rule (e.g., 10%) could therefore lead to substantial reductions in baseline risk

among disinfected supplies which is currently not accounted for in the quantified benefits. 

As with the analysis of bacterial illnesses, there is no way of knowing whether the ratio of 1.16 is

generally higher or lower for non-outbreak illnesses. It is possible, that outbreaks represent a larger or

smaller portion of total cases for treatment deficiencies than for untreated ground water. Similarly, it is

not possible to estimate with any degree of confidence the percent reduction in treatment failures that

might result from this rule. In any case, benefits from reduced treatment are likely to result from this rule

and would be additive to benefits estimates in the main analysis.

5.4.7 Distribution System Contamination

The GWR will lead to additional systems providing disinfection at the source and this will lead to

some disinfectant residual provided in the distribution system. Opportunistic bacterial pathogens are soil

and other environmental bacteria that can colonize distribution systems and typically are harbored and

protected in distribution system biofilms where substantial bacterial population growth can occur. 

Periodic biofilm sloughing can introduce these pathogens into untreated ground water. Major groups of

opportunistic bacterial include Pseudomonas, Acinetobacter, Xanthamonas, Moraxella, Mycobacterium

and Serratia (Rusin et al. 1997 a, b). Each of these bacteria is capable of causing disease, typically

pneumonia, meningitis and septicemia, but also other diseases, in sensitive subpopulations. Sensitive

subpopulations are estimated to be 20% of the U.S. population (Gerba et al., 1996). Although sensitive

subpopulations are often advised to drink only treated or bottled water, it is often difficult to know the

water source for all exposures, especially water from transient systems. Corrective action, including

disinfection can have substantial benefit in reducing exposure to opportunistic pathogens in untreated

distribution systems. The GWR only qualitatively accounts for the benefits that might accrue for reduced

exposure and illness among sensitive subpopulations due to opportunistic bacterial pathogens.

5.4.8 Benefits From the Reduction of Co-Occurring and Emerging Contaminants

While the benefits analysis for the GWR only includes reductions in illness and mortality

attributable to illnesses from Type A and Type B viruses, the GWR is expected to reduce exposure to

other pathogens. For example, some membrane technologies installed to remove viruses can reduce or

eliminate many other drinking water contaminants including arsenic and bacteria. Strengthened

regulatory requirements will translate into increased removal of additional pathogens and a resulting

reduction in risk. This may prove essential, as the impact of emerging pathogens is not well established. 
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Unfortunately, EPA is unable to quantify the resultant benefit associated with a reduction in risk from

emerging pathogens due to current data limitations. 

5.4.9 Reduced Uncertainty/Costs to Households to Avert Infection

To the extent that the GWR decreases consumers’ uncertainty about expected health outcomes

from consumption of drinking water, the rule should provide direct benefits independent of risk reduction

benefits. In other words, drinking water consumers may be willing to pay a premium for regulatory

action if it reduces their uncertainty about whether they will become ill (Moore, 1990).

Conceptually, whether consumers would be willing to pay something extra to reduce uncertainty

in the GWR context depends on several complicated factors, including consumers’ degree of risk

aversion, their perceptions about drinking water quality, and the expected probability and severity of

human health effects associated with microbial contamination of drinking water. For example, risk

premiums would be expected only for consumers who are risk averse. Further, the magnitude of any

premium would be expected to be positively related to the probability and severity of expected health

outcomes, and the degree to which consumers perceive them to be affected by regulatory action.

In addition, to the extent that the GWR can be expected to reduce a household’s perceptions of

the health risks associated with drinking water, regulatory action should reduce household averting

actions and costs. Any such cost savings would represent a regulatory benefit. Examples of household

averting actions include: 1) securing drinking water from alternative sources (e.g., bottled water), 2)

installation of home treatment systems (e.g., point-of-use and point-of-entry treatment), and 3) boiling tap

water used for consumption. These actions can involve significant cash outlays and implicit costs (e.g.,

time costs).

A number of factors, however, limit the relevance of this potential benefit in the GWR context. 

One is the possibility that regulatory action may not affect household perceptions of health risks enough

to motivate them to forego averting actions. A related factor is that many households that undertake

averting action for health reasons may be especially risk averse (e.g., households with infants or

immuncompromised persons). These households might be expected to pursue averting actions regardless

of the level of regulatory control if they believe such actions may provide added protection against

microbial risks. However, any treatment that also improves taste and odor as well as microbial protection

may likely result in households forgoing averting behavior.

5.4.10 Summary of Nonquantified Benefits

The total benefits in this EA include both quantified and nonquantified components. The

quantified benefits are summarized in Exhibit 5.23. The total nonquantified benefits are captured by

several additional analyses and are summarized here but discussed in more detail throughout this EA. 

EPA estimates that, based on avoided bacterial illnesses and deaths alone, which are discussed only in the

nonquantified benefits section, the total benefits could be underestimated by a factor of five. Other

benefits will also accrue but are not quantified.

The nonquantified benefits result from multiple factors. First, the quantified benefits are based on

limited, well-defined data and key assumptions that restrict the input parameters in the quantified benefit
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calculation. Typically, these assumptions resulted in low mean values and narrow uncertainty ranges in

the benefits analysis. This EA, where applicable, discusses alternative assumptions. For example, the

enterovirus morbidity fractions are, by assumption, not determined using coxsackievirus (an enterovirus)

data although the enterovirus severity data use all enterovirus data. If coxsackievirus data were available,

the mean morbidity values would be greater. Choosing alternative values and ranges and differing key

assumptions, which might also be deemed reasonable, would increase the quantified benefits in this EA.

Second, the quantified benefits are based on data and assumptions that pertain to only partial

representation of Type A and Type B viruses potentially found in PWS wells with fecal contamination. 

Due to limited available data, only rotavirus and some enterovirus data were used to calculate the

quantified benefits. As is more completely discussed in Section 5.4. other viruses as well as pathogenic

bacteria may contribute to the disease burden, both acute and chronic, associated with PWS wells with

fecal contamination. Most importantly, bacterial illnesses can result in more frequent and lengthier

hospitalization and more frequently have fatal outcomes. If bacterial diseases were considered in the

quantified benefits, the monetized benefits could be substantially greater because bacterial disease can be

more severe and can result in higher mortality rates.

Third, the quantified benefits are based on data and assumptions that limit the characterization of

acute disease. For rotavirus, only acute gastroenteritis illness and fatal dehydration associated with that

illness are monetized. Norovirus disease is not considered. For the enteroviruses, all acute disease

endpoints are considered, but the prevalence of severe endemic cases may be substantially diluted by the

large number of hand, foot, and mouth disease cases that are not likely to be waterborne. Thus, the

proportion of severe cases in the quantitative benefits is likely to be underestimated. As is discussed more

completely in Section 5.4, in neither instance, either for rotavirus or the enteroviruses, are chronic

diseases identified or monetized in the quantitative benefits calculation.

Fourth, the quantified benefits are based explicitly on what has been directly measured in PWS

wells, yet there is great difficulty in identifying and counting all infectious viral pathogens in dilute

drinking water samples. Indeed, some viral pathogens like infectious norovirus can never be identified in

any sample. Section 4.3.2 discusses these difficulties in more detail. Standard fecal indicator data such

as total coliforms and E. coli, commonly used to identify water treatment deficiencies and potential

human health hazards, are explicitly not used to determine human exposure for the purposes of

quantifying the benefits in this EA.

Fifth, the quantified benefits are assumed to be based only on one contamination scenario, fecal

contamination of source water. Other contamination scenarios are thoroughly documented in the ground

water contamination and outbreak scientific literature. However, these scenarios, such as inadequate

disinfection, are not explicitly considered in calculating the quantified benefits in this EA.

Sixth, the quantified benefits are assumed to be based only on avoidance of endemic disease. The

GWR will likely also decrease the incidence of epidemic disease (outbreaks). If epidemic illnesses and

the avoided non-health-related costs of ground waterborne disease outbreaks were included, the

quantified benefits would increase.

In summary, this EA quantifies a subset of the total health and non-health related benefits. In a

sample calculation, discussed in Section 5.4.3.2, EPA estimated that the total benefits could increase by a

factor of five by only accounting for additional deaths and hospitalizations caused by bacterial illness

being avoided. While EPA recognizes that this estimate includes substantial uncertainty, given all the
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other nonquantified factors described above, EPA believes that the total benefits from the GWR are likely

to be more than five times those which have been quantified.

5.5 Alternative Analyses

To quantify the effects that differences in major modeling assumptions would have on benefits

analyses, several alternative analyses were performed. This section presents discussion and results for

four such analyses: use of an alternative baseline for viral concentration; use of two alternative dose

response functions for Type A viruses; use of an alternative dose response function for Type B viruses;

and use of an alternative set of occurrence data (Exhibit 5.27).

5.5.1 Alternative Viral Concentration Baseline

The main analysis of this EA applies data on viral concentrations derived from the Abbaszadegan

and Pennsylvania studies to estimate viral concentrations in those wells defined in this EA as “less

vulnerable” (see Chapter 4). Data from Lieberman are used to estimate viral concentrations for those

wells defined as “more vulnerable.” These data are applied to each category of public water system, e.g.,

CWS, NTNCWS, and TNCWS in the main analysis. 

As a sensitivity analysis, these same studies are applied differentially to the six categories (based

on three system types and their status as more or less vulnerable): Abbaszadegan’s concentration data are

applied to only less vulnerable CWSs; Lieberman’s concentration data are applied to more vulnerable

CWSs; and the Pennsylvania study’s concentration data are applied to both the more vulnerable and less

vulnerable NTNCWSs and TNCWSs. This alternative would increase the quantified benefits of rule

implementation by a range of $1.1 million to $1.7 million (an increase of approximately 7 to 9 percent,

using a 7 percent and 3 percent discount rate, respectively) (Exhibit 5.27). Benefits would decrease for

CWSs and increase for both NTNCWSs and TNCWSs.

5.5.2 Alternative Type A Dose response

Two alternative dose response models were developed by EPA for Type A viruses using the same

study data (Ward et al., 1986) that were used for the dose response function in the main analysis. In both

alternative analyses, only the results for the 7 subjects exposed to 0.9 viruses were used since this dose

level is most similar to doses likely to be experienced by those consuming contaminated water. As

described in detail in Appendix F.5.1, an exponential model form was used having the form P = 1 - e -

 -

D*r. In this model, D is the expected daily dose of virus and r is the model parameter. 

In the first analysis, a large sample of r values were generated using an MCMC method to capture

uncertainty in the true value of the r parameter. This alternative leads to a higher estimate of risk and

quantified benefits related to Type A viruses. The results, in terms of the monetized benefits using this

alternative dose response function (with all other aspects kept the same as in the main model), are shown

in Exhibit 5.27. This alternative dose response function would increase the annualized quantified benefits

by a range of $1.7 million to $2.1 million (approximately 10 percent) relative to the annualized benefits

for the main analysis, using a 7 percent and 3 percent discount rate, respectively.
28 Studies omitted from the alternative occurrence model are those used for the primary analysis (detailed in

Ch. 4 of the EA) that were either not published or not peer reviewed prior to publication: Missouri Alluvial Aquifer 

(Vaughn, 1996), Wisconsin Migrant Worker Camp (USEPA et al., 1998), EPA Vulnerability (USEPA, 1998), New

England (Doherty et al., 1998), Three-State Study #3: Minnesota (Battigelli, 1999), Three-State Study #1: 

Wisconsin (Battigelli, 1999), and the Montana Study (Miller and Meek, 1996).

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In the second alternative dose response analysis for Type A viruses, the r value was estimated

without consideration of uncertainty. This alternative leads to a lower estimate of risk and benefits

related to Type A viruses by a range of $1.7 million to $2.0 million (approximately 10 percent in both

cases) relative to the annualized quantified benefits for the main analysis, using a discount rate of 7

percent and 3 percent, respectively.

5.5.3 Alternative Type B Dose Response

An alternative dose response model was developed by EPA for Type B viruses using the same

study data (Schiff et al., 1984) that were for the dose response function in the main analysis. In this

alternative analysis, the two highest dose groups (33,000 and 330,000 pfu) were excluded from the

analysis. As described in detail in Appendix F, an exponential model form was used having the form P =

1 - e - - D*r. In this model, D is the expected daily dose of virus and r is the model parameter. A large

sample of r values were generated using a MCMC method to capture uncertainty in the true value of the r

parameter. 

This alternative leads to a lower estimate of risk and benefits related to Type B viruses. The

results, in terms of the monetized benefits using this alternative dose response function (with all other

aspects kept the same as in the main model), are shown in Exhibit 5.27. This alternative dose response

function would decrease the annualized benefits by a range of $3.7 million to $4.3 million (approximately

22 percent) relative to the annualized benefits for the main analysis, using a 7 percent and 3 percent

discount rate, respectively.

5.5.4 Alternative Occurrence (Peer Review) Data

The Agency performed an alternative benefits analysis by running the benefits model using a

subset of the studies that were the basis for the fecal indicator and viral occurrence rates in the primary

analysis. This subset comprised just those studies which had undergone peer review prior to publication28

and so consisted only of peer-reviewed data (a parallel analysis was performed for the cost model–see

section 6.4.8). Compared to the primary analysis, this alternative benefits model results in an increase in

the annualized benefits by a range of $10.4 million to $12.2 million (an approximately 62% increase),

using 7 percent and 3 percent discount rates, respectively (Exhibit 5.27).
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3% Discount Rate 7% Discount Rate

Primary Analysis $19.7 $16.8

Alternative Viral Concentration 

Baseline $1.7 $1.1

First Alternative Type A Dose 

Response $2.1 $1.7

Second Alternative Type A Dose 

Response ($2.0) ($1.7)

Alternative Type B Dose Response ($4.3) ($3.7)

Peer Review (Subset of Data Used in 

Primary Analysis) $12.2 $10.4

Analysis

Incremental Difference in Mean Benefits from Primary 

Notes: The figures presented in this exhibit represent only the quantifiable benefits of the GWR. The unquantified benefits are

expected to comprise a significant portion of the overall benefits of the Rule and are presented in Section 5.4.

Source: GWR Model Output

Exhibit 5.27 Results of Alternative Analyses

5.6 Summary of Uncertainty

This chapter presents the data, assumptions, and methods used to estimate the baseline risks, in

terms of illnesses and deaths, from the presence of viral pathogens in ground water used as source water

for public drinking water systems. It also presents estimates of the reductions in those risks (benefits)

resulting from the implementation of the GWR, and of the monetized value of those benefits. Throughout

this chapter, an attempt has been made to address uncertainty in the inputs to and the results obtained

from the baseline risk and risk reduction modeling. Exhibit 5.28 summarizes the major uncertainties for

modeling GWR benefits as well as any anticipated influence on the cost model. Additional discussion of

the uncertainty and variability factors influencing the benefits model follows (see Chapter 6 for additional

discussion of uncertainty and variability in the cost model estimates). 
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Exhibit 5.28 Summary of Uncertainties Affecting GWR Estimates

(continued on next page)

Uncertainty

Section

Discussion

of

Uncertainty

Effect on Benefits Estimates Effect on Cost Estimates

UnderestimateOverestimateUnknown

Impact

UnderestimateOverestimateUnknown

Impact

Viral and indicator

occurrence

Exhibit 4.32 X X

Effectiveness of

indicator monitoring

Exhibit 4.32

5.2.3.6 X X

Rotavirus used to

represent Type A

infectivity

5.2.4.1 X None

Model/data used for

rotavirus dose

response

Appendix F X None

Echovirus 12 used

to represent Type B

infectivity

5.2.4.1 X None

Model/data used for

echovirus dose

response

Appendix F X None

Rotavirus Used to

represent Type A

morbidity

5.2.4.1 X None

Echovirus 12 used

to represent Type B

morbidity

5.2.4.1 X None

Population rates in

TNCWSs 5.2.3.4 X None

Secondary spread 5.2.4.2

5.2.4.3

Appendix E

X X None

Infectivity risk of

sensitive subgroups 5.2.5.3 X None

Morbidity and

mortality risk for

elderly or immunocompromised

5.2.5.3 X None

Value of health

outcomes (COI)

5.2.4.2

5.4.10 X None

Five repeat samples

(not modeled) 5.2.5.6 X X
Uncertainty

Section

Discussion

of

Uncertainty

Effect on Benefits Estimates Effect on Cost Estimates

UnderestimateOverestimateUnknown

Impact

UnderestimateOverestimateUnknown

Impact

Economic Analysis for the October 2006

Final Ground Water Rule 5-111

Treatment failure

(not modeled) 5.4.7 X X

Distribution system

risk (not modeled) 5.4.8 X X

Bacterial illness (not

included in main

benefits)

5.4.3.1 X None

In the inputs to the exposure estimates for the risk model, the same elements of variability and

uncertainty that were discussed in Chapter 4 for the viral and indicator occurrence data and modeling

apply to their use here in the baseline risk and risk reduction modeling. Of particular note are the

concerns that the limited monitoring data available on viral pathogen occurrence may lead to

underestimates of the number of wells and the number of people potentially affected. In addition, the

limited data on indicator and pathogen co-occurrence may be resulting in an underestimate of the

effectiveness of indicator monitoring of source water to identify those wells that are expected to have

viral pathogens present.

Uncertainty exists in the dose response functions for infectivity developed for Type A and Type

B viruses based on rotavirus and echovirus challenge data, respectively. In the main analysis, this

uncertainty is considered to some extent by virtue of the large set of dose response function parameters

that were generated and used in the simulation model. In addition, in an effort to address the uncertainty

in the risk of infection, the alternative dose response functions were developed using data from the

challenge studies that was considered most representative of likely exposures via drinking water.

Variability and uncertainty are considered in the morbidity factors used in the risk model. 

Variability is accounted for by applying different factors for young children versus the rest of the

population. Uncertainty is also considered as uniform uncertainty distributions in these morbidity factors. 

Secondary spread is included in the analysis, and variability is included in secondary spread rate

for Type A viruses as a function of age of the primary infected individual, while uncertainty in the

secondary spread factor is included for Type B viruses. Beyond this, however, there is some concern that

secondary spread is being underestimated because of limited data which required use of a metric where

secondary cases are associated with primary cases of illness rather than with primary cases of infection.

In the risk and benefits analysis, there is recognition of three sensitive subgroups: young, old and

immunocompromised. There are, however, only limited quantitative considerations of the potential

increased impacts on these subgroups. There is no difference included for any of these subgroups with

respect to infectivity risk relative to the population at large. An increased morbidity factor is included for

the very young, and an increased mortality factor for neonates is included for Type B viruses. There is no
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consideration of increased morbidity or mortality risk for older persons or the immunocompromised

subgroups. (Note that the analysis does consider increased severity of illness for the

immunocompromised in terms of medical costs incurred.)

In the valuation of benefits analysis, a cost-of-illness (COI ) approach has been used rather than a

willingness-to-pay (WTP) approach due to lack of available data. Generally, WTP is considered a more

appropriate approach to estimating the benefits of avoiding risks and typically leads to higher benefits

than the COI approach. Therefore, there is some concern that the value of the GWR benefits may be

understated because they are based on COI rather than WTP.

As described previously, EPA's national occurrence dataset includes information on virus and

indicator occurrence from 1309 wells among 15 studies. These wells serve community and

noncommunity public water systems of different sizes and types (e.g., disinfecting/nondisinfecting), and

the wells are situated in shallow and deep aquifers, located in sensitive or nonsensitive hydrogeologic

settings, and are geographically dispersed across the US. Although all these types of wells are included in

the dataset, their numbers in the dataset do not necessarily relate to their numbers in the population of

wells that will be affected by the GWR. In other words, these 1309 wells may not be perfectly

representative of the larger population of affected wells. Because the surveyed wells have not all been

characterized or characterized similarly for these features (system size, hydrogeologic setting,

vulnerability, etc.), EPA is not able to assess the degree to which the dataset may have overstated or

understated our national occurrence estimates.

5.7 Regulatory Alternatives

In addition to model runs to calculate benefits for the Final GWR requirements, analyses were

conducted for the other rule alternatives considered as part of the rule development process. The five

modeled regulatory conditions are: Baseline, Final GWR, Sanitary Survey and Corrective Action, MultiBarrier Approach, and Across-the-board Disinfection (see Chapter 3 for a full description of these

alternatives). The following exhibits present the estimated illnesses and deaths remaining for each

regulatory scenario (Exhibit 5.29), the reduction in illnesses and deaths for each of the regulatory

scenarios (Exhibit 5.30) and the annualized value of illnesses and deaths avoided for regulatory

alternatives (Exhibit 5.31). Benefits and costs of the Final GWR are compared in relation to these

alternatives in Chapter 8.
Economic Analysis for the October 2006

Final Ground Water Rule 5-113

Mean 5th Percentile 95th Percentile Mean 5th Percentile 95th Percentile

Type A 32,652 175,168 435,381 1.2 0.2 2.9 

Type B 501 10,018 40,718 2.0 0.0 8.1 

Total 185,186 476,099 33,153 3.2 11.0 0.3 

Type A 22,559 135,726 355,455 0.9 0.1 2.4 

Type B 320 7,592 32,605 1.5 0.0 6.5 

Total 143,318 388,060 22,879 2.4 8.9 0.2 

Type A 31,065 168,154 420,404 1.1 0.2 2.8 

Type B 470 9,535 38,688 1.9 0.0 7.8 

Total 177,689 459,092 31,535 3.0 10.6 0.2 

Type A 21,207 132,332 348,839 0.9 0.1 2.3 

Type B 307 7,435 32,094 1.5 0.0 6.4 

Total 139,768 380,933 21,514 2.4 8.7 0.2 

Type A 5,248 28,295 70,474 0.2 0.0 0.5 

Type B 80 1,609 6,540 0.3 0.0 1.3 

Total 29,904 77,014 5,328 0.5 1.8 0.0 

Illnesses per Year Deaths per Year Regulatory Alternative Virus Type

Baseline

Final Rule

Risk Targeted Approach

Alternative 4

Across-the-Board 

Disinfection

Alternative 3

Multi-Barrier Approach

Alternative 1

Sanitary Survey and 

Corrective Action

Mean 5th Percentile 95th Percentile Mean 5th Percentile 95th Percentile

Final Rule

Risk Targeted Approach 41,868 88,039 10,274 0.7 2.1 0.1 

Alternative 1

Sanitary Survey and 

Corrective Action 7,497 17,007 1,618 0.1 0.4 0.0 

Alternative 3

Multi-Barrier Approach 45,419 95,166 11,639 0.8 2.3 0.1 

Alternative 4

Across-the-Board 

Disinfection 155,282 399,085 27,824 2.7 9.2 0.2 

Illnesses per Year Deaths per Year Regulatory Alternative

Exhibit 5.29 Remaining Number of Annual Viral Illnesses and Deaths

for Each Regulatory Alternative

Notes: Details may not add to totals due to independent rounding and independent statistical analyses. Only endemic

illnesses are estimated. The figures presented in this exhibit represent only the quantifiable benefits of the GWR. 

The nonquantified benefits are expected to comprise a significant portion of the overall benefits of the Rule and are

presented in Section 5.4.

Source: Appendix C

Exhibit 5.30 Comparison of Number of Annual Viral Illnesses and Deaths Avoided

for Regulatory Alternatives

Note: Details may not add to totals due to independent rounding. Only endemic illnesses are estimated.

 Source: Appendix C.
Economic Analysis for the October 2006

Final Ground Water Rule 5-114

Mean 5th Percentile 95th Percentile Mean 5th Percentile 95th Percentile

Final Rule $19.7 $6.5 $45.4 $16.8 $5.5 $38.6

Alternative 1 $3.6 $0.9 $9.3 $2.9 $0.7 $7.5

Alternative 3 $21.3 $7.1 $48.7 $18.2 $6.0 $41.6

Alternative 4 $70.2 $18.3 $177.0 $61.9 $16.1 $156.3

Final Rule $10.0 $2.2 $27.0 $8.6 $1.9 $22.9

Alternative 1 $1.9 $0.3 $5.5 $1.5 $0.2 $4.5

Alternative 3 $10.8 $2.5 $28.9 $9.3 $2.1 $24.8

Alternative 4 $35.5 $6.5 $102.4 $31.5 $5.7 $90.8

Source: Appendix C

Notes: Detail may not add to totals due to independent rounding. The Traditional COI only includes valuation for medical costs and lost work time (including 

some portion of unpaid household production). The Enhanced COI also factors in valuations for lost personal time (non-work time) such as childcare and 

homemaking (to the extent not covered by the Traditional COI), time with family, and recreation, and lost productivity at work on days when workers are ill 

but go to work anyway.

The figures presented in this exhibit represent only the quantifiable benefits of the GWR. The unquantified benefits are expected to comprise a significant 

portion of the overall benefits of the Rule and are presented in Section 5.4.

3% Discount Rate 7% Discount Rate Regulatory Alternative

Traditional COI

Enhanced COI

Exhibit 5.31 Annualized Value of Viral Illnesses and Deaths Avoided for

Regulatory Alternatives
1

 The term “State” in the context of this chapter refers to any State or other primacy agency that has

oversight authority for drinking water programs.

Economic Analysis for the October 2006

Final Ground Water Rule 6-1

6. Cost Analysis

6.1 Introduction

This chapter presents estimates for the total national and household costs for the Ground Water

Rule (GWR). To estimate the national costs of the GWR, the United States Environmental Protection

Agency (EPA or Agency) calculated the incremental cost for rule components that expand current State

practices (e.g., sanitary surveys) and the additional cost of new activities required under the rule. Cost

analyses include estimates to implement the rule, conduct sanitary surveys, perform triggered source

water monitoring, implement corrective actions (including drilling a new well, installation/operation of

treatment, etc.), and perform compliance monitoring. Assessment monitoring and hydrogeologic

sensitivity assessments (HSAs) are optional and are not included in the cost estimates.

System costs are estimated for different system types and size categories (nine size categories are

used based on population served, consistent with the Drinking Water Baseline Handbook (USEPA,

2001a)). State1

 cost analyses include estimates of the labor burdens that States would face, including staff

training on GWR requirements, conducting sanitary surveys, reviewing monitoring reports, reviewing and

approving corrective action plans, and recordkeeping. EPA estimated unit costs for these various

components using cost models, equipment price lists and quotes, wage rates from government and

engineering sources (Bureau of Labor Statistics, R.S. Means, and States), stakeholder inputs, and other

relevant assumptions used in economic analyses performed for existing drinking water rules (e.g., Arsenic

Rule).

The national costs are estimated using a Monte-Carlo simulation model specifically developed for

the GWR. The GWR cost model was developed in a SAS© software platform utilizing a Monte-Carlo

simulation. The main advantage to this modeling approach is that, in addition to providing average

compliance costs, it also estimates the range of costs within each public water system (PWS) size and

type category. The GWR cost model allows for variability and uncertainty in PWS configuration, current

treatment in-place, and source water quality to be captured in the compliance cost estimates. This

information forms the basis for examining impacts to PWSs and technology affordability.

The remainder of this chapter is organized as follows:

• Section 6.2 describes the general costing and compliance assumptions used to estimate

national costs of the GWR.

• Section 6.3 describes the methodology of projecting costs over a 25-year period according to

the GWR compliance schedule, estimating the present value of each cost, and annualizing

each over a 25-year period.

• Section 6.4 describes the methodology for developing costs for all rule activities.
Economic Analysis for the October 2006

Final Ground Water Rule 6-2

• Section 6.5 presents household cost estimates.

• Section 6.6 presents a discussion of nonquantified costs.

• Section 6.7 presents a discussion of uncertainties in cost estimates.

• Section 6.8 presents the total annualized cost for the Final GWR.

• Section 6.9 presents a comparison of cost estimates for the Final GWR to estimates for other

rule alternatives considered.

6.2 General Costing Assumptions and Methodology

The GWR Cost Model incorporates several baseline data elements, including the numbers, types,

and sizes of ground water systems in the United States, the percentage of ground water systems that

disinfect, and the percentage of disinfecting systems that attain 4-log treatment of viruses (using

inactivation, removal, or State-approved combination of these technologies) before or at the first

customer. Because many of the assumptions apply not to systems but to entry points, where appropriate,

exhibits in this chapter use entry point estimates. Derivations of these baselines for the GWR are

discussed in Chapter 4. In addition to those baseline elements, there are several additional baseline

costing assumptions used as inputs to the GWR Cost Model. The derivation of these inputs is discussed

in detail below.

6.2.1 Labor Rates

For costing purposes, EPA estimates the labor needs and hourly labor rates of systems and States

for two labor categories: managerial and technical. EPA recognizes that there may be significant

variation in labor rates across all PWSs. However, for purposes of this EA, and to implement national

policy, EPA uses national-level estimates from Labor Costs for National Drinking Water Rules (USEPA,

2003b). The technical and managerial wage rates vary with system size and include fringe benefits. The

technical and managerial wage rates (2003$) are shown in Exhibit 6.1.
Economic Analysis for the October 2006

Final Ground Water Rule 6-3

25-100 101-500 500-3.3k 3.3k-10k 10k-100k >100k

Technical Wage Rate 21.44 $ 23.09 $ 24.74 $ 25.34 $ 26.05 $ 31.26 $ 

Managerial Wage Rate 44.36 $ 47.78 $ 51.20 $ 51.20 $ 51.20 $ 51.20 $ 

Labor Cost (per hour) 21.44 $ 23.09 $ 24.74 $ 30.51 $ 31.08 $ 35.25 $ 

Loaded Wage Rate ($2003)

System Size (Population Served)

Exhibit 6.1 Wage Rates by System Size

Notes: EPA estimates that systems with population greater than 3,300 use a combination of operators (technical)

and engineers (managerial), with an 80/20 ratio between the two, respectively. Loaded rate includes a 60

percent factor to account for the cost of fringe benefits.

Source: Labor Costs for National Drinking Water Rules (USEPA, 2003b).

To account for the general composition of staff at PWSs of smaller sizes (e.g., systems serving

3,300 people or fewer), EPA uses only the technical rate. For systems serving more than 3,300 people,

EPA uses a ratio of 80 percent technical labor to 20 percent managerial labor to arrive at a labor cost, or

weighted labor rate, of $30.51 for systems serving 3,301-10,000 people, $31.08 for systems serving

10,001-100,000 people, and $35.25 for systems serving greater than 100,000 people.

Labor costs attributable to States for administrative tasks are estimated based on an average

annual full time equivalent (FTE) labor cost, including overhead and fringe benefits, of $65,255 (2001$). 

This rate was established based on data from the 2001 State Drinking Water Needs Analysis (ASDWA,

2001). For use in the GWR EA analyses, the $65,255 annual rate was updated to a year 2003 price level

($70,132) and converted to an hourly basis (1 FTE = 2,080 hours) to establish a State rate of $33.60 per

hour. For sanitary surveys and corrective action plan review, the year 1998 wage rate of $31.00 for a

field engineer is used. The field engineer rate comes from R.S. Means (1998) and includes a 60 percent

loading factor to account for the cost of fringe benefits. This wage rate is updated to 2003 dollars,

resulting in a field engineer rate of $37.34 per hour. Exhibit 6.2 displays these labor rates and their

derivations.
2

EPA assumed that systems serving fewer than 10,000 people would conduct 25% of the laboratory analyses in-house

and 75% would be sent to a commercial laboratory; for systems serving 10,000 to 50,000 people EPA assumed that 75% of the

laboratory analyses would be conducted in-house and 25% would be sent to a commercial laboratory; and systems serving

greater than 50,000 people were assumed to conduct all laboratory analyses in-house. 

Economic Analysis for the October 2006

Final Ground Water Rule 6-4

Base Hourly 

Labor Cost

ECI in Year of

Data ECI 2003 Q4 2003 Labor Cost

A B C D=A*(C/B)

Field Engineer 31.00 $ 139.80 $ 168.40 $ 37.34 $ 

State Employee 31.37 $ 153.20 $ 164.10 $ 33.60 $ 

Cost Element

Exhibit 6.2 State Labor Rates

Sources: (A) Wage rate for a Field Engineer (1998$) from R.S. Means, 1998. Wage rate for State employee from 2001 State

Drinking Water Needs Analysis ($65,255 yearly for 2080 hours per year) (ASWDA, 2001)

(B & C) Employment Cost Index (ECI) for a Field Engineer from BLS (2003) from 1998 (Civilian; Total

compensation; Professional, specialty, and technical occupations). ECI for State Employee from BLS (2003) from

2001 (State and local government; Total compensation; Professional, specialty, and technical occupations). 

www.bls.gov.

6.2.2 Laboratory Fees

A laboratory fee, or cost per sample, is associated with source water monitoring. For the purpose

of this cost analysis, EPA assumed that States will select E. coli as the indicator of fecal contamination for

source water analysis. Since States may designate alternative indicators for some sites (e.g., coliphage or

enterococci), and such analysis is more costly, this assumption may underestimate costs. EPA estimated

the cost of monitoring for both the use of an in-house and a commercial laboratory2

, as shown in Exhibit

6.3. For in-house laboratories, EPA’s estimate of the cost per sample includes the cost of laboratory

analysis materials ($8.95) and a total of 1.0 hour of the system staff’s time to collect the sample and

conduct the analysis. For commercial laboratory analysis, EPA’s estimate of the cost per sample includes

a shipping and commercial analysis fee ($74.80) and 0.5 hours of the system staff’s time to collect the

sample and arrange for delivery to the laboratory. The estimated burden required to collect samples

includes travel time and reflects a national average. Individual systems may realize collection burden that

is either less than or greater than this average depending on the locations of sampling points in a

particular system. No additional costs are assumed for installation of a tap or re-piping of wells to permit

sampling, since EPA assumed all wells are equipped with existing taps for sampling. 

Rates may vary due to regional variations in laboratory fees, the number of samples processed

(quantity discounts), and laboratory capacity. Although laboratory costs are often lower for multiple

samples, there are no estimates of the number of systems that may be able to take advantage of this

savings. Therefore, the rates used in this analysis may overestimate the actual costs incurred by systems. 
Economic Analysis for the October 2006

Final Ground Water Rule 6-5

Labor

Cost

(per hour)

Sampling

Labor Burden

(hours)

Total

Sampling

Cost

Analysis

Labor Burden

(hours)

Operation &

Maintenance

Total

Analysis

Cost

A B C=A*B D E F=(A*D)+E G=B+D H=C+F

25-100 21.44 $ 0.5 10.72 $ 0.5 8.95 $ 19.67 $ 1.0 30.39 $ 

101-500 23.09 $ 0.5 11.55 $ 0.5 8.95 $ 20.50 $ 1.0 32.04 $ 

500-3.3k 24.74 $ 0.5 12.37 $ 0.5 8.95 $ 21.32 $ 1.0 33.69 $ 

3.3k-10k 30.51 $ 0.5 15.26 $ 0.5 8.95 $ 24.21 $ 1.0 39.46 $ 

10k-100k 31.08 $ 0.5 15.54 $ 0.5 8.95 $ 24.49 $ 1.0 40.03 $ 

>100k 35.25 $ 0.5 17.62 $ 0.5 8.95 $ 26.57 $ 1.0 44.20 $ 

25-100 21.44 $ 0.5 10.72 $ 0.0 74.80 $ 74.80 $ 0.5 85.52 $ 

101-500 23.09 $ 0.5 11.55 $ 0.0 74.80 $ 74.80 $ 0.5 86.35 $ 

500-3.3k 24.74 $ 0.5 12.37 $ 0.0 74.80 $ 74.80 $ 0.5 87.17 $ 

3.3k-10k 30.51 $ 0.5 15.26 $ 0.0 74.80 $ 74.80 $ 0.5 90.06 $ 

10k-100k 31.08 $ 0.5 15.54 $ 0.0 74.80 $ 74.80 $ 0.5 90.34 $ 

>100k 35.25 $ 0.5 17.62 $ 0.0 74.80 $ 74.80 $ 0.5 92.42 $ 

Sources: (A) Labor rates from Exhibit 6.1.

(B & D) Labor hours for sampling and analysis reflect EPA estimate.

Analysis Conducted

Sampling Analysis

Total

Burden

(hours)

Total

Cost

(E) Operation and management costs based on best professional judgement. They are the cost of laboratory analysis materials for in-house 

laboratories and the total cost for commercial laboratories, respectively.

In-house

Commercial laboratory

Exhibit 6.3 Source Water Monitoring Costs per Sample

6.2.3 Technology Unit Costs and Compliance Forecasts

EPA has assumed that systems may use a variety of existing technologies to achieve 4-log

treatment of viruses (using inactivation, removal, or State-approved combination of these technologies)

before or at the first customer. These technologies include the use of hypochlorination, chlorine gas

disinfection, ozonation and nanofiltration, chlorine dioxide, and anodic oxidants disinfection. Other

technologies or combinations of technologies (i.e., UV and chloramines, etc.) may be used to meet rule

requirements. However, technologies used in the compliance forecast (and their associated unit costs) are

based on representative use by the majority of systems. Unit cost estimates for these technologies are in

the form of “dollars per entry point” for initial capital and yearly operation and maintenance (O&M)

activities. EPA uses population-flow equations for each of the nine system size categories (see section

4.2.4) to estimate unit costs for each technology for each system type and size category. Population used

in population flow equations is based on the population served for a particular entry point. Detailed

explanations of the unit cost derivations for these technologies are presented in the Technology and Cost

Document for the Final Ground Water Rule (USEPA, 2006d).

Compliance forecasts (or technology selection forecasts) are estimates of which technologies

systems undergoing corrective action will use. Sections 6.4.6.1 and 6.4.6.2 provide detail on the

methodology used to generate compliance forecasts for sanitary survey corrective actions and source

water contamination corrective actions.
3

 The choice of an appropriate discount rate is a complex and controversial issue among economists and

policy makers. Therefore, the Agency compares streams of future national level costs and benefits using two

alternative discount rates, 3 and 7 percent. The underlying logic for each discount rate can be found in Guidelines

for Preparing Economic Analyses (USEPA, 2000e).

Economic Analysis for the October 2006

Final Ground Water Rule 6-6

6.2.4 Cost Model

The GWR cost model uses the system baseline data and assumptions regarding labor hours,

laboratory costs, and labor rates to generate system costs for rule implementation, sanitary surveys,

triggered monitoring, and compliance monitoring. It also combines unit cost estimates with the predicted

number of entry points at which various corrective actions are predicted to be used to produce the cost of

correcting significant deficiencies and source water contamination. Finally, the model includes State

costs.

6.2.5 Modeled Variability and Uncertainty in National Costs

As noted throughout this EA, EPA recognizes that there is variability among many of the input

parameters to the GWR cost model (e.g., entry points per system, population served, flow per population,

labor rates, and occurrence distributions) and several rule compliance assumptions. In some cases, EPA

is able to describe this variability as distributions that are used as inputs to the cost model. In other cases,

there is insufficient information to fully characterize the distribution of variability on a national scale and

EPA uses mean values for these latter input parameters.

EPA also recognizes that there is uncertainty in the national cost estimates, and has characterized

the uncertainty around the mean unit technology costs (as described in section 6.4.9) in the GWR cost

model. There is also uncertainty built into the compliance assumptions regarding whether a system

chooses a treatment or nontreatment corrective action. To simulate the effect of this uncertainty on

national costs, the model performs a Monte-Carlo simulation. The results for the uncertainty analysis are

presented in the form of 90 percent confidence bounds around mean national cost estimates.

6.3 Projecting and Discounting National Costs

Costs must be expressed in common units so they can be added together to calculate total annual

costs and compared to benefits to compute net benefits. For this rule, some activities occur once, such as

installing new treatment technologies. Other O&M activities phase in as new technologies are installed,

then continue each year into the future. These activities do not occur instantly or simultaneously; to make

such values comparable, the year or years in which all costs are expended must be determined and the

costs must be brought back to their present value. For the purposes of this EA, one-time and yearly costs

were projected over a 25-year time period to coincide with the estimated life span of capital equipment

and a time lag of 5 to 10 years for treatment technology installation after rule promulgation. PWSs also

often finance their capital improvements over a 20-year period. The present values of costs are calculated

using discount rates of 3 and 7 percent based on EPA policy and Office of Information and Regulatory

Affairs of the Office of Management and Budget (OMB) guidance.3
Economic Analysis for the October 2006

Final Ground Water Rule 6-7

There are two adjustments made to the cost estimates in this EA. One adjustment is made when

costs are being used as part of the national cost estimate. These present value costs are then annualized

using the same discount rate so that the costs of each regulatory alternative can be directly compared with

the corresponding annual benefits. A summary of the steps in this adjustment is as follows:

• Project all undiscounted costs (noncorrective action, corrective action, and State) over a 25-

year time horizon based on the rule implementation schedule.

• Calculate total present value costs using 3 and 7 percent discount rates (the same rates were

used as for the benefits calculation).

• Annualize the costs over 25 years using the same discount rates.

• Calculate ninety percent confidence bounds to reflect the bounds commonly used by

statisticians to assess the overall uncertainty and variability of modeled estimates.

Appendix D contains results from each step above for the final rule. Exhibits D.1 through D.5

show the nominal costs projected over the rule schedule and the present value of each cost calculated to

the expected year of rule implementation for the final regulatory alternative. Exhibits D.6 through D.8

show the results for Alternatives 1, 3, and 4.

A different adjustment is made when the cost estimates are used for the analysis of householdlevel costs. In this case, rather than use a discount rate for determining the present value and annualized

costs, an after-tax cost-of-capital rate is used. This rate should reflect the true after-tax cost of capital

PWSs face, net of any government grants or subsidies. To annualize capital costs when determining the

costs to households, EPA uses different discount rates for private and public systems of different sizes

(annualized household costs are presented in Exhibit 6.31). The rate differences between systems

represent many factors (e.g., the different borrowing sources each type of system has available to it, bond

ratings, etc.) and vary from 5.20 to 6.27 percent depending on system size and ownership. These rates are

shown in Exhibit 6.4.

Exhibit 6.4 Discount Rates for Private and Public Systems

System Size

(Population Served) Public Rate Private Rate

<100 5.31% 6.22%

101-500 5.31% 6.22%

501-1,000 5.51% 6.22%

1,001-3,300 5.51% 6.22%

3,301-10,000 5.51% 6.22%

10,001-50,000 5.20% 5.66%

50,001-100,000 5.24% 6.27%

100,001-1,000,000 5.24% 6.27%

>1,000,000 5.24% 6.27%

Source: Development of Cost of Capital Estimates for Public Water Systems, Final 

Report (USEPA, 2000f).
Economic Analysis for the October 2006

Final Ground Water Rule 6-8

6.4 Derivation of Costs for Systems and States

This section presents the methodology and unit costs used to derive national costs for systems and

States to perform GWR related activities. Chapter 1 contains a summary of the GWR that describes these

activities. The following subsections provide a brief summary of each activity and the assumptions used

to estimate the burden and costs attributable to both systems and States for each:

6.4.1 Rule Implementation and Annual Administration

6.4.2 Sanitary Surveys (SSs)

6.4.3 Triggered Monitoring (TM)

6.4.4 Corrective Actions (CAs)

6.4.5 Compliance Monitoring (CM)

This chapter uses information from the baseline analysis in Chapter 4 as a starting point for

analysis of PWSs subject to each rule requirement. Exhibits 6.5a-c present key baseline information and

intermediate model outputs that are referenced throughout this section. Because many of the assumptions

apply not to systems but to entry points, Exhibits 6.5a and 6.5b use both system and entry point estimates

where appropriate.

There are also 57 States that will incur costs as a result of the rule. As noted previously, the term

“State” in the context of this chapter refers to any State or other primacy agency that has oversight

authority for drinking water programs.
Economic Analysis for the October 2006

Final Ground Water Rule 6-9

System Size

Total Number 

of Systems

Number of 

Entry Points 

per System

Number of 

Wells per 

System

Number of 

Wells per 

Entry Point

Entry Points 

with at least 4 

logs of Viral 

Disinfection

Entry Points with 

less than 4 logs 

of Viral 

Disinfection

Entry Points 

without 

Disinfection

A B C D = C/B E F G

Community Water Systems (CWSs) 

<100 12,843 1.3 1.5 1.1 3,996 3,689 9,168 

101-500 14,358 1.6 2.0 1.2 8,873 8,191 6,343 

501-1,000 4,649 2.0 2.3 1.2 3,547 3,274 2,262 

1,001-3,300 5,910 2.4 3.1 1.3 5,378 4,964 4,002 

3,301-10K 2,884 3.2 4.6 1.4 3,547 3,274 2,459 

10,001-50K 1,444 5.6 9.8 1.7 3,856 3,559 698 

50,001-100K 167 11.3 16.1 1.4 583 538 770 

100,001-1 Million 103 12.4 49.9 4.0 545 503 227 

> 1 Million 3 11.4 49.9 4.4 34 - - 

Nontransient Noncommunity Water Systems (NTNCWSs)

<100 9,456 1.0 1.5 1.5 850 1,892 6,714 

101-500 6,758 1.0 2.0 2.0 608 1,352 4,798 

501-1,000 1,894 1.0 2.3 2.3 170 379 1,345 

1,001-3,300 715 1.0 3.1 3.1 64 143 508 

3,301-10K 73 1.0 4.6 4.6 7 15 52 

10,001-50K 10 1.0 9.8 9.8 1 2 7 

50,001-100K 1 1.0 16.1 16.1 0 0 1 

100,001-1 Million 1 1.0 49.9 49.9 0 0 1 

> 1 Million - 1.0 49.9 49.9 - - - 

Transient Noncommunity Water Systems (TNCWSs)

<100 64,448 1.0 1.5 1.5 1,160 10,441 52,847 

101-500 18,993 1.0 2.0 2.0 342 3,077 15,574 

501-1,000 1,940 1.0 2.3 2.3 35 314 1,591 

1,001-3,300 585 1.0 3.1 3.1 11 95 480 

3,301-10K 74 1.0 4.6 4.6 1 12 61 

10,001-50K 19 1.0 9.8 9.8 0 3 16 

50,001-100K 1 1.0 16.1 16.1 0 0 1 

100,001-1 Million 1 1.0 49.9 49.9 0 0 1 

> 1 Million - 1.0 49.9 49.9 - - - 

Sources: (A) Exhibit 4.1, Column U

(B) Exhibit 4.3, Column A

(C) Wells per system from US EPA Drinking Water Baseline Handbook (2001). 

(E) Exhibit 4.3, Column H

(F) Exhibit 4.3, Column W

(G) Exhibit 4.3, Column R

Exhibit 6.5a GWR Baselines: Number of Systems, Entry Points, and Wells
Economic Analysis for the October 2006

Final Ground Water Rule 6-10

System Size

Systems 

Receiving 

Sanitary 

Survey

Systems with 

Corrective 

Actions for 

Significant 

Deficiencies

Entry Points 

with 

Triggered 

Monitoring

Entry Points 

with 

Corrective 

Actions for 

Triggered 

Monitoring

Entry Points with 

Viral Disinfection 

Increased from 

less than 4 logs 

to 4 logs

Previously Nondisinfecting Entry Points 

Taking Corrective Action

Entry Points 

with 

Incremental 

Compliance 

Monitoring

A B C D E F G

Community Water Systems (CWSs) 

<100 12,843 2,181 12,797 1,249 358 891 248 

101-500 14,358 2,444 14,819 1,625 917 709 292 

501-1,000 4,649 789 5,578 608 360 248 105 

1,001-3,300 5,910 1,001 8,910 712 396 317 130 

3,301-10K 2,884 492 5,638 617 353 264 111 

10,001-50K 1,444 245 4,357 655 548 107 54 

50,001-100K 167 28 1,295 226 93 133 46 

100,001-1 Million 103 18 749 136 94 42 20 

> 1 Million 3 - - - - - - 

Nontransient Noncommunity Water Systems (NTNCWSs)

<100 9,456 1,608 8,609 687 150 537 149 

101-500 6,758 1,148 6,149 533 119 415 170 

501-1,000 1,894 322 1,724 149 33 117 50 

1,001-3,300 715 121 651 86 19 67 27 

3,301-10K 73 12 66 10 2 8 3 

10,001-50K 10 2 9 2 0 1 1 

50,001-100K 1 0 1 0 0 0 0 

100,001-1 Million 1 0 1 0 0 0 0 

> 1 Million - - - - - - - 

Transient Noncommunity Water Systems (TNCWSs)

<100 64,448 10,990 63,295 6,915 1,143 5,772 1,602 

101-500 18,993 3,234 18,648 2,026 337 1,689 696 

501-1,000 1,940 329 1,905 208 35 174 73 

1,001-3,300 585 99 574 76 12 63 26 

3,301-10K 74 13 73 12 2 10 4 

10,001-50K 19 3 19 3 1 3 1 

50,001-100K 1 0 1 0 0 0 0 

100,001-1 Million 1 0 1 0 0 0 0 

> 1 Million - - - - - - - 

Sources: Cost Model Outputs

Notes:

(G) indicates number of entry points with treatment corrective actions.

(F) - (G) indicates non treatment corrective actions.

Exhibit 6.5b Summary of Rule Implications
Economic Analysis for the October 2006

Final Ground Water Rule 6-11

Rule 

Implementation & 

Annual 

Administration

Sanitary 

Surveys

Corrective 

Actions for 

Significant 

Deficiencies

Triggered 

Monitoring

Corrective Actions 

for Triggered 

Monitoring

Compliance 

Monitoring Total Costs

A B C D E F G

Mean $0.93 $0.21 $8.46 $5.44 $25.64 $9.35 $50.02

Lower Bound

(5th %ile) $0.93 $0.11 $5.74 $5.32 $14.90 $3.02 $34.28

Upper Bound

(95th %ile) $0.93 $0.31 $11.60 $5.56 $38.39 $16.97 $68.76

Mean $9.20 $1.45 $0.56 $0.09 $0.46 $0.00 $11.77

Lower Bound

(5th %ile) $9.20 $0.66 $0.52 $0.06 $0.32 $0.00 $10.87

Upper Bound

(95th %ile) $9.20 $2.23 $0.61 $0.12 $0.61 $0.01 $12.64

Mean $10.13 $1.66 $9.02 $5.52 $26.10 $9.36 $61.79

Lower Bound

(5th %ile) $10.13 $0.77 $6.25 $5.38 $15.22 $3.02 $45.15

Upper Bound

(95th %ile) $10.13 $2.54 $12.21 $5.67 $39.00 $16.98 $81.41

Mean $1.33 $0.20 $8.13 $5.39 $27.20 $8.32 $50.57

Lower Bound

(5th %ile) $1.33 $0.10 $5.51 $5.27 $15.89 $2.65 $35.22

Upper Bound

(95th %ile) $1.33 $0.30 $11.14 $5.51 $40.96 $15.17 $69.00

Mean $9.18 $1.39 $0.54 $0.10 $0.52 $0.00 $11.74

Lower Bound

(5th %ile) $9.18 $0.63 $0.50 $0.07 $0.36 $0.00 $10.87

Upper Bound

(95th %ile) $9.18 $2.14 $0.59 $0.13 $0.69 $0.01 $12.61

Mean $10.51 $1.59 $8.67 $5.48 $27.72 $8.32 $62.31

Lower Bound

(5th %ile) $10.51 $0.74 $6.01 $5.34 $16.26 $2.65 $46.09

Upper Bound

(95th %ile) $10.51 $2.44 $11.73 $5.64 $41.65 $15.18 $81.61

Notes: Detail may not add to totals due to independent rounding and independent cost model runs.

Source: Cost Model Outputs

States

Total

Systems

3%

7%

Systems

States

Total

Exhibit 6.5c Annualized Costs for Meeting Each of the GWR Provisions to

Systems and States ($Millions, 2003$)

6.4.1 Rule Implementation and Annual Administration

PWSs

All systems subject to the GWR will incur one-time costs that include time for staff to read the

rule and become familiar with its provisions and to train employees on rule requirements. All systems

subject to the GWR will perform implementation activities; the number of systems performing

implementation activities is shown in column A of exhibit 6.5a. The technical and managerial labor rates

presented in section 6.2.1 are used along with estimates of labor hours to generate implementation costs
Economic Analysis for the October 2006

Final Ground Water Rule 6-12

for all systems. Technical rates apply to systems serving 3,300 or fewer people, and the 80/20 blend of

technical and managerial labor rates apply to systems serving populations greater than 3,300. Based on

previous experience with rule implementation, EPA estimates that systems will require a total of 3 hours

for the implementation activities associated with sanitary surveys, and a total of 2 - 4 hours for the

implementation of monitoring requirements. The planning and mobilization burden estimates under

monitoring implementation activities include time required to develop a sampling plan for source water

monitoring under triggered monitoring. These unit costs are presented in Exhibit 6.6.
Economic Analysis for the October 2006

Final Ground Water Rule 6-13

Sanitary Surveys 

Triggered and 

Compliance Monitoring

Read and 

Understand Rule 

(hours/

system)

Planning

and Mobilization 

(hours/

system)

Unit

Cost

Read and 

Understand Rule 

(hours/

system)

Planning

and

Mobilization 

(hours/

system)

Unit

Cost

A B C D=A*(B+C) E F G=A*(E+F) H=B+C+E+F I=A*H

$ 2 1 64.32 21.44 $ 1 2 64.32 $ 6 129 $ 

$ 2 1 69.27 23.09 $ 1 2 69.27 $ 6 139 $ 

501-1,000 24.74 $ 2 1 74.22 $ 1 2 74.22 $ 6 148 $ 

1,001-3,300 24.74 $ 2 1 74.22 $ 1 2 74.22 $ 6 148 $ 

3,301-10K 30.51 $ 2 1 91.54 $ 1 2 91.54 $ 6 183 $ 

10,001-50K 31.08 $ 2 1 93.24 $ 1 3 124.32 $ 7 218 $ 

50,001-100K 31.08 $ 2 1 93.24 $ 1 3 124.32 $ 7 218 $ 

100,001-1 Million 35.25 $ 2 1 105.74 $ 1 3 140.99 $ 7 247 $ 

$ 2 1 105.74 35.25 $ 1 3 140.99 $ 7 247 $ 

$ 2 1 64.32 21.44 $ 1 1 42.88 $ 5 107 $ 

$ 2 1 69.27 23.09 $ 1 1 46.18 $ 5 115 $ 

501-1,000 24.74 $ 2 1 74.22 $ 1 1 49.48 $ 5 124 $ 

1,001-3,300 24.74 $ 2 1 74.22 $ 1 1 49.48 $ 5 124 $ 

3,301-10K 30.51 $ 2 1 91.54 $ 1 1 61.02 $ 5 153 $ 

10,001-50K 31.08 $ 2 1 93.24 $ 1 1 62.16 $ 5 155 $ 

50,001-100K 31.08 $ 2 1 93.24 $ 1 1 62.16 $ 5 155 $ 

100,001-1 Million 35.25 $ 2 1 105.74 $ 1 1 70.50 $ 5 176 $ 

$ 2 1 105.74 35.25 $ 1 1 70.50 $ 5 176 $ 

$ 2 1 64.32 21.44 $ 1 1 42.88 $ 5 107 $ 

$ 2 1 69.27 23.09 $ 1 1 46.18 $ 5 115 $ 

501-1,000 24.74 $ 2 1 74.22 $ 1 1 49.48 $ 5 124 $ 

1,001-3,300 24.74 $ 2 1 74.22 $ 1 1 49.48 $ 5 124 $ 

3,301-10K 30.51 $ 2 1 91.54 $ 1 1 61.02 $ 5 153 $ 

10,001-50K 31.08 $ 2 1 93.24 $ 1 1 62.16 $ 5 155 $ 

50,001-100K 31.08 $ 2 1 93.24 $ 1 1 62.16 $ 5 155 $ 

100,001-1 Million 35.25 $ 2 1 105.74 $ 1 1 70.50 $ 5 176 $ 

$ 2 1 105.74 35.25 $ 1 1 70.50 $ 5 176 $ 

Notes: Detail may not add to totals due to independent rounding.

Sources: (A) Labor rates from Exhibit 6.1.

(B,C,E, & F) Labor hours for reading and understanding rule and planning and mobilization reflect EPA estimates.

System Size

(Population 

Served)

<100

101-500

<100

Nontransient Noncommunity Water Systems (NTNCWSs)

Total

Unit

Start-Up

Burden

(hours)

Total

Unit

Start-Up

Cost

Labor 

Cost 

(per hour)

> 1 Million

> 1 Million

Community Water Systems (CWSs) 

<100

101-500

Transient Noncommunity Water Systems (TNCWSs)

> 1 Million

101-500

Exhibit 6.6 PWS Unit Burden and Cost Estimates for Implementation Activities
Economic Analysis for the October 2006

Final Ground Water Rule 6-14

States

States will incur administrative costs while implementing the GWR. These implementation costs

are not directly required by specific provisions of GWR alternatives, but are necessary for States to ensure

the provisions of the GWR are properly carried out. States will need to allocate time for their staff to

establish and then maintain the programs necessary to comply with the GWR, including developing and

adopting State regulations and modifying data management systems to track new required system reports

to the States. For those GWR requirements that include monitoring with a laboratory method not

currently required by the State, the State must devote a portion of its staff time to certifying laboratories

for the new method. Time requirements for a variety of State agency activities and responses are

estimated in this EA and Exhibit 6.7a lists the activities required to start the program following

promulgation of the GWR along with their respective costs and burden.

In addition to these one-time costs, States will use resources to continue administrative activities. 

On an annual basis, States must coordinate with their particular EPA Region to be certain that the State’s

program is consistent with federal requirements. States will also continue to train State and PWS staffs,

maintain laboratories’ certifications, and report system compliance information to the Safe Drinking

Water Information System (SDWIS). Exhibit 6.7b lists these annual activities with their respective costs

and burden.

States will also be required to spend time responding to PWSs with fecally contaminated ground

water sources or significant deficiencies. These costs are beyond any items specifically described and

costed as part of the cost model and include items such as time to provide additional consultation to

systems, prepare violation letters, and conduct data entry, etc. Because time requirements for

implementation and annual administration activities vary among State agencies, EPA recognizes that the

burden and cost estimates presented in Exhibits 6.7a and 6.7b may be an over- or under-estimate for some

States.
Economic Analysis for the October 2006

Final Ground Water Rule 6-15

Labor Cost

(per hour) Hours FTEs Cost

A B C=B/2,080 D=A*B

$ 60 33.60 0.03 2,016 $ 

$ 1,040 33.60 0.50 34,946 $ 

$ 800 33.60 0.38 26,882 $ 

$ 2,080 33.60 1.00 69,892 $ 

$ 2,080 33.60 1.00 69,892 $ 

$ 520 33.60 0.25 17,473 $ 

Per State Total 221,101 6,580 $ 

National Totals (57 States/Primacy Agencies) 12,602,743 375,060 $ 

Notes: Detail may not add due to independent rounding.

Sources: (A) Labor rate for state employee from Exhibit 6.2.

(B) Labor hours for start-up activities reflect EPA estimate.

(C) Full-time equivalent (FTE) assumes individual working 40 hours per week, 52 weeks per year.

Staff Training

Read and Understand Rule

Compliance Activity

Regulation Adoption and Program Development

Initial Laboratory Certification

Modify Data Management Systems

System Training and Technical Assistance

Annual Administrative Activities

Labor Cost

(per hour) Hours FTEs Cost

A B C=B/2,080 D=A*B

$ 1,040 33.60 0.50 34,946 $ 

$ 1,040 33.60 0.50 34,946 $ 

$ 1,040 33.60 0.50 34,946 $ 

$ 1,040 33.60 0.50 34,946 $ 

$ 880 33.60 0.42 29,570 $ 

$ 104 33.60 0.05 3,495 $ 

Per State Total 172,848 5,144 $ 

National Totals (57 States/Primacy Agencies) 9,852,357 293,208 $ 

Notes: Detail may not add due to independent rounding.

Sources: (A) Labor rate for state employee from Exhibit 6.2.

(B) Labor hours for start-up activities reflect EPA estimate.

(C) Full-time equivalent (FTE) assumes individual working 40 hours per week, 52 weeks per year.

SDWIS Reporting

Recordkeeping

Staff Training

Coordination with EPA

Lab Certification

Ongoing Technical Assistance

Compliance Activity

Exhibit 6.7a State Burden and Cost Estimates for Implementation Activities

Exhibit 6.7b State Burden and Cost Estimates for Annual Administration
Economic Analysis for the October 2006

Final Ground Water Rule 6-16

Mean

Lower 

Bound

(5th %ile)

Upper 

Bound

(95th 

%ile) Mean

Lower 

Bound

(5th %ile)

Upper 

Bound

(95th 

%ile) Mean

Lower 

Bound

(5th %ile)

Upper 

Bound

(95th 

%ile)

3% $0.93 $0.93 $0.93 $9.20 $9.20 $9.20 $10.13 $10.13 $10.13

7% $1.33 $1.33 $1.33 $9.18 $9.18 $9.18 $10.51 $10.51 $10.51

Notes: Detail may not add to totals due to independent rounding and independent cost model runs.

Source: Cost Model Outputs

Systems States Total

Annualized Costs for Implementation and Annual Administration Activities

Annualized cost estimates for systems and States to perform implementation activities for the

preferred regulatory alternative are presented in Exhibit 6.8.

Exhibit 6.8 PWS and State Cost Estimates for Implementation and Annual

Administration Activities ($Millions, 2003$)

6.4.2 Sanitary Surveys

PWSs

Under the sanitary survey provision of the GWR, community water systems (CWSs) and 

noncommunity water systems (NCWSs) will undergo sanitary surveys once every three and five years,

respectively, to address eight specific components of a PWS. The exception to these frequencies is some

CWSs. Those CWSs that provide 4-log treatment of viruses (using inactivation, removal, or Stateapproved combination of these technologies) before or at the first customer, or have an outstanding

performance record (i.e., no significant deficiencies) and no history of total coliform maximum

contaminant level (MCL) or monitoring violations under the Total Coliform Rule (TCR) may undergo

sanitary surveys every 5 years. To account for this EPA assumes, based on best professional judgement,

that the number of CWSs receiving sanitary surveys every 5 years is calculated by summing 50% of the

non-disinfecting and disinfecting to less than 4-log systems with the number of 4-log disinfecting

systems.

Sanitary surveys may increase either in scope or in frequency or in both scope and frequency

under the GWR for some systems. Systems not currently performing surveys at the frequencies specified

under the GWR will incur costs for performing additional full surveys (i.e., full sanitary survey costs). 

The scope of sanitary surveys may also increase to completely address eight specific components of a

PWS. The sanitary surveys in this case are called incremental surveys (only having an incremental

increase in survey effort). Incremental surveys may also be applicable to some systems under the same

survey frequencies. Although States or designated agents perform the surveys, systems will incur costs to

accompany State inspectors during a review of the treatment plant and the distribution system, as well as

to review and discuss the sanitary survey report. The primary increase in costs that systems will incur as

a result of this rule provision is the additional number of surveys undertaken during the period of analysis

(i.e., full survey costs). 
4

 No differentiation in inspection burden is made between systems providing greater than or equal to 4-log

treatment or less than 4-log treatment.

Economic Analysis for the October 2006

Final Ground Water Rule 6-17

EPA estimates that surveys for all PWSs currently average once every 5 years. Exceptions to this

frequency are those NCWSs that may be on a 10 year schedule as allowed under TCR, because they have

reliable disinfection and are deemed not vulnerable by the State. Thus, CWSs now required by the GWR

to receive sanitary surveys every 3 years will either undergo an increase in full surveys or incremental

surveys. For CWSs now on the three year schedule, the number of additional full surveys required to be

conducted is calculated as the difference between the frequency of conducting sanitary surveys on a three

year schedule and a five year schedule: 22 years/3years - 22 years/5 years = 2.9 (assuming that the first

survey cycle starts as soon as compliance begins at the beginning of fourth year after the rule

promulgation and the rule stays effective through the 25th year). For systems on the five year schedule

that have to do incremental surveys, the number is 4.4 incremental surveys (22years/5 years). 

NCWSs are either on a 5 year or a 10 year schedule as allowed for under the TCR. EPA assumes

that all NCWSs serving greater than 4,400 people are on a 10 year schedule. All other NCWSs are

assumed to be on a 5 year schedule. For those NCWSs on a 10 year schedule, the number of additional

full surveys required to be conducted is calculated as the difference between the frequency of conducting

sanitary surveys on a five year schedule and a ten year schedule: 22 years/5years - 22 years/10 years =

2.2. For systems on the five year schedule that have to do incremental surveys, the number is 4.4

incremental surveys (22years/5 years).

For any system incurring costs for incremental effort to comply with GWR requirements, EPA

assumes that the incremental effort will be 50% of current efforts. This assumption is based on the

expectation that many elements of a sanitary survey are similar to the requirements (compliance with

eight elements) of the GWR. In addition, based on examination of State sanitary survey requirements,

90% of systems are already required to comply with eight elements required under the GWR. Therefore,

only 10% of systems are anticipated to incur any incremental costs. These 50% and 10% factors are

applied to the unit cost estimates presented in Exhibits 6.11 and 6.12 to derive a weighted unit cost which

is then used in the cost model. 

Exhibit 6.9 provides a schematic of the sanitary survey process for one system size and type to

show the process used in the cost model. Exhibit 6.10 details the number of full and incremental sanitary

surveys for systems on both the 3 and 5 year schedule. PWS unit costs to perform sanitary surveys are

provided in Exhibit 6.11a for systems with treatment and in Exhibit 6.11b for systems with no treatment. 

Systems performing either full or incremental sanitary surveys are divided out by whether or not they

perform treatment because treatment status impacts unit costs applied in the cost model (i.e., additional

burden is estimated to inspect the system with treatment)4

. All burden estimates used in the cost model

are based on consultations with EPA, State, and industry professionals with significant experience

conducting sanitary surveys on ground water systems. Lower unit costs are applied to NCWSs because

they are normally simpler than CWSs.
Economic Analysis for the October 2006

Final Ground Water Rule 6-18

SS Conducted by State

2,884 Systems

(1,102 systems disinfecting 4-log or 

greater + 1,018 systems disinfecting 

less than 4-log + 764 nondisinfecting 

systems) 

New Full Survey due to a Higher 

Frequency

891 Systems

891 Systems * 2.9 Surveys / System 

= 2,584 Surveys

Incremental Survey for complete 

coverage

891 Systems * 10% = 89 Systems 

89 Systems * 4.4 Incremental Surveys / 

System = 392 Incremental Surveys

Treatment

86.8% Disinfecting * 

891 Systems = 773 

Systems

No Treatment

13.2% 

Nondisinfecting * 891 

Systems = 118 

Systems

Did State identify any 

significant deficiencies?

See Section 6.4.4 on 

Corrective Actions

Continue performing 

SS at specified 

intervals

Yes No

Incremental Survey for complete 

coverage

1,993 Systems * 10% = 199 Systems 

199 Systems * 4.4 Incremental 

Surveys / System 

= 877 Incremental Surveys

Treatment

86.8% Disinfecting * 877 

Systems = 761 Systems

CWS [50% (systems not disinfecting + 

systems disinfection < 4-log)]

891 Systems

Systems disinfecting to 4-log + 

CWS [50% (systems not disinfecting + systems 

disinfection < 4-log)]

1,993 Systems

No Treatment

13.2% Nondisinfecting 

* 877 Systems = 116 

Systems

All systems 

subject to GWR

Treatment

86.8% Disinfecting * 89 

Systems = 77 Systems

No Treatment

13.2% 

Nondisinfecting * 89 

Systems = 12 

Systems

17% * 2,884 Systems 

= 490 Systems

83% * 2,884 Systems 

= 2,394 Systems

3-year 

Schedule

5-year 

Schedule

Exhibit 6.9 Schematic of Sanitary Survey Process

(Numbers based on 3,301 - 10,000 population category for CWSs)
Economic Analysis for the October 2006

Final Ground Water Rule 6-19

States

As required by this rule, systems must provide all of necessary information and assistance

requested from states for conducting surveys. The difference in costs between systems and States stems

from differing unit costs for performing sanitary surveys. State unit costs are significantly higher than the

system unit costs because the States are actually performing the surveys while systems are only required

to provide information and assistance to support the surveys. State unit costs to perform sanitary surveys

are provided in Exhibits 6.12a and 6.12b. As with the system unit costs estimates, all burden estimates

used in the cost model are based on consultations with EPA, State, and industry professionals with

significant experience conducting sanitary surveys on ground water systems. Lower unit costs are applied

to NCWSs because they are normally simpler than CWSs.

The total annualized costs estimates for both systems and States to perform sanitary surveys are

presented in Exhibit 6.13.
Economic Analysis for the October 2006

Final Ground Water Rule 6-20

Number of Systems 

Receiving Sanitary 

Survey

Number of 

Additional Full 

Surveys

Number of Incremental 

Surveys for Systems 

Performing Additional Full 

Surveys

Number of Incremental 

Surveys for Systems 

Already on GWR 

Schedule

A BC D

<100 12,843 2.9 4.4 4.4

101-500 14,358 2.9 4.4 4.4

501-1,000 4,649 2.9 4.4 4.4

1,001-3,300 5,910 2.9 4.4 4.4

3,301-10K 2,884 2.9 4.4 4.4

10,001-50K 1,444 2.9 4.4 4.4

50,001-100K 167 2.9 4.4 4.4

100,000-1M 103 2.9 4.4 4.4

>1,000,000 3 2.9 4.4 4.4

<100 9,456 2.2 2.2 4.4

101-500 6,758 2.2 2.2 4.4

501-1,000 1,894 2.2 2.2 4.4

1,001-3,300 715 2.2 2.2 4.4

3,301-10K 73 2.2 2.2 4.4

10,001-50K 10 2.2 2.2 4.4

50,001-100K 1 2.2 2.2 4.4

100,000-1M 1 2.2 2.2 4.4

>1,000,000 0 NA NA NA

<100 64,448 2.2 2.2 4.4

101-500 18,993 2.2 2.2 4.4

501-1,000 1,940 2.2 2.2 4.4

1,001-3,300 585 2.2 2.2 4.4

3,301-10K 74 2.2 2.2 4.4

10,001-50K 19 2.2 2.2 4.4

50,001-100K 1 2.2 2.2 4.4

100,000-1M 1 2.2 2.2 4.4

>1,000,000 0 NA NA NA

Note: Incremental surveys reflect CWSs moving from a 5 year to a 3 year schedule and NCWSs moving from a 10 year to 

a 5 year schedule.

System Size

(Population Served)

Community Water Systems (CWSs) 

Nontransient Noncommunity Water Systems (NTNCWSs)

Transient Noncommunity Water Systems (TNCWSs)

Exhibit 6.10 Number of Full and Incremental Sanitary Surveys for Systems
Economic Analysis for the October 2006

Final Ground Water Rule 6-21

Labor

Cost 

(per hour)

Review/

Inspect 

Wells

Review/

Inspect 

Treatment

Review/

Inspect 

Distribution 

System

Report 

Review and 

Discussion 

w/ State

Total

Unit Burden

(hours)

Unit Cost

(Full Survey)

Weighted 

Unit Cost

(Incremental Survey)

A BC D E F=sum(B-E) G=A*F H=0.05*G

Community Water Systems (CWSs) 

<100 21.44 $ 1.1 0.8 1.2 1.1 4.3 92 $ 5 $ 

101-500 23.09 $ 1.2 0.8 1.2 1.1 4.3 99 $ 5 $ 

501-1,000 24.74 $ 1.5 1.1 1.7 1.2 5.4 135 $ 7 $ 

1,001-3,300 24.74 $ 2.2 1.3 2.9 1.4 7.7 191 $ 10 $ 

3,301-10K 30.51 $ 2.7 1.6 3.6 1.8 9.6 291 $ 15 $ 

10,001-50K 31.08 $ 3.7 2.0 4.3 1.9 11.8 368 $ 18 $ 

50,001-100K 31.08 $ 9.0 3.0 12.0 3.0 27.0 839 $ 42 $ 

100,000-1M 35.25 $ 15.0 8.0 24.0 3.0 50.0 1,762 $ 88 $ 

>1,000,000 35.25 $ 24.0 10.0 36.0 4.0 74.0 1,762 $ 88 $ 

Nontransient Noncommunity Water Systems (NTNCWSs)

<100 21.44 $ 1.0 0.8 1.0 1.3 4.0 87 $ 4 $ 

101-500 23.09 $ 1.0 0.8 1.1 1.3 4.2 96 $ 5 $ 

501-1,000 24.74 $ 1.1 0.9 1.3 1.2 4.5 110 $ 6 $ 

1,001-3,300 24.74 $ 1.1 1.1 1.2 1.3 4.7 116 $ 6 $ 

3,301-10K 30.51 $ 1.5 1.5 1.7 1.5 6.2 188 $ 9 $ 

10,001-50K 31.08 $ 1.3 0.8 1.8 1.3 5.0 155 $ 8 $ 

50,001-100K 31.08 $ 1.5 0.8 2.3 1.3 5.8 179 $ 9 $ 

100,000-1M 35.25 $ 8.0 1.0 10.0 1.5 20.5 723 $ 36 $ 

>1,000,000 35.25 $ NA NA NA NA NA NA NA

Transient Noncommunity Water Systems (TNCWSs)

<100 21.44 $ 0.7 0.6 0.6 0.9 2.7 59 $ 3 $ 

101-500 23.09 $ 0.7 0.6 0.6 0.9 2.7 63 $ 3 $ 

501-1,000 24.74 $ 1.0 0.8 1.0 0.9 3.7 92 $ 5 $ 

1,001-3,300 24.74 $ 0.9 1.0 0.9 1.1 3.9 96 $ 5 $ 

3,301-10K 30.51 $ 1.2 1.3 1.2 1.2 4.8 147 $ 7 $ 

10,001-50K 31.08 $ 0.8 0.5 1.3 0.8 3.3 101 $ 5 $ 

50,001-100K 31.08 $ 1.3 0.5 1.3 0.8 3.8 117 $ 6 $ 

100,000-1M 35.25 $ 8.0 1.0 10.0 1.0 20.0 705 $ 35 $ 

>1,000,000 35.25 $ NA NA NA NA NA NA NA

Notes:

() f C S f

System Size

(Population 

Served)

Weighted unit costs equal 5% of the unit costs. This factor accounts for 50% effort for an incremental survey and 

10% of systems that do not already comply with rule requirements (see text discussion).

Exhibit 6.11a PWS Unit Burden and Cost Estimates for Performing Full and

Incremental Sanitary Surveys (Treatment)
Economic Analysis for the October 2006

Final Ground Water Rule 6-22

Labor

Cost 

(per hour)

Review/

Inspect 

Wells

Review/

Inspect 

Distribution 

System

Report 

Review and 

Discussion 

w/ State

Total

Unit Burden

(hours)

Unit Cost

(Full Survey)

Weighted 

Unit Cost

(Incremental Survey)

A BC D E=sum(B-D) F=A*E G=0.05*F

Community Water Systems (CWSs) 

<100 21.44 $ 1.1 1.2 1.1 3.5 75 $ 4 $ 

101-500 23.09 $ 1.2 1.2 1.1 3.5 81 $ 4 $ 

501-1,000 24.74 $ 1.5 1.7 1.2 4.4 108 $ 5 $ 

1,001-3,300 24.74 $ 2.2 2.9 1.4 6.4 159 $ 8 $ 

3,301-10K 30.51 $ 2.7 3.6 1.8 8.0 243 $ 12 $ 

10,001-50K 31.08 $ 3.7 4.3 1.9 9.8 305 $ 15 $ 

50,001-100K 31.08 $ 9.0 12.0 3.0 24.0 746 $ 37 $ 

100,000-1M 35.25 $ 15.0 24.0 3.0 42.0 1,480 $ 74 $ 

>1,000,000 35.25 $ 24.0 36.0 4.0 64.0 1,480 $ 74 $ 

Nontransient Noncommunity Water Systems (NTNCWSs)

<100 21.44 $ 1.0 1.0 1.3 3.3 70 $ 4 $ 

101-500 23.09 $ 1.0 1.1 1.3 3.4 79 $ 4 $ 

501-1,000 24.74 $ 1.1 1.3 1.2 3.6 89 $ 4 $ 

1,001-3,300 24.74 $ 1.1 1.2 1.3 3.6 89 $ 4 $ 

3,301-10K 30.51 $ 1.5 1.7 1.5 4.7 142 $ 7 $ 

10,001-50K 31.08 $ 1.3 1.8 1.3 4.3 132 $ 7 $ 

50,001-100K 31.08 $ 1.5 2.3 1.3 5.0 155 $ 8 $ 

100,000-1M 35.25 $ 8.0 10.0 1.5 19.5 687 $ 34 $ 

>1,000,000 35.25 $ NA NA NA NA NA NA

Transient Noncommunity Water Systems (TNCWSs)

<100 21.44 $ 0.7 0.6 0.9 2.2 46 $ 2 $ 

101-500 23.09 $ 0.7 0.6 0.9 2.2 50 $ 2 $ 

501-1,000 24.74 $ 1.0 1.0 0.9 2.9 72 $ 4 $ 

1,001-3,300 24.74 $ 0.9 0.9 1.1 2.9 72 $ 4 $ 

3,301-10K 30.51 $ 1.2 1.2 1.2 3.5 107 $ 5 $ 

10,001-50K 31.08 $ 0.8 1.3 0.8 2.8 85 $ 4 $ 

50,001-100K 31.08 $ 1.3 1.3 0.8 3.3 101 $ 5 $ 

100,000-1M 35.25 $ 8.0 10.0 1.0 19.0 670 $ 33 $ 

>1,000,000 35.25 $ NA NA NA NA NA NA

Notes:

System Size

(Population 

Served)

Weighted unit costs equal 5% of the unit costs. This factor accounts for 50% effort for an incremental survey and 10% of 

systems that do not already comply with rule requirements (see text discussion).

Exhibit 6.11b PWS Unit Burden and Cost Estimates for Performing Full and

Incremental Sanitary Surveys (No Treatment)
Economic Analysis for the October 2006

Final Ground Water Rule 6-23

Labor

Cost 

(per hour)

Review/

Inspect 

Wells

Review/

Inspect 

Treatment

Review/

Inspect 

Distribution 

System

Report

Documenta

tion/

File Review

Report 

Develop

ment Data Entry

Report 

Review and 

Discussion 

w/ PWS Travel

Total

Unit Burden

(hours)

Unit Cost

(Full Survey)

Weighted Unit Cost

(Incremental Survey)

A B C D EFG H I J=sum(B-I) K=A*J L=0.05*K

Community Water Systems (CWSs) 

<100 37.34 $ 1.1 0.8 1.2 2.3 5.7 0.8 1.1 1.8 14.8 551 $ 28 $ 

101-500 37.34 $ 1.2 0.8 1.2 2.3 5.8 0.8 1.1 1.8 14.9 557 $ 28 $ 

501-1,000 37.34 $ 1.5 1.1 1.7 2.6 7.4 0.8 1.2 1.8 18.0 671 $ 34 $ 

1,001-3,300 37.34 $ 2.2 1.3 2.9 3.4 8.8 1.2 1.4 1.8 22.8 851 $ 43 $ 

3,301-10K 37.34 $ 2.7 1.6 3.6 3.7 9.6 1.3 1.8 1.8 25.9 967 $ 48 $ 

10,001-50K 37.34 $ 3.7 2.0 4.3 5.3 10.1 1.4 1.9 1.8 30.3 1,132 $ 57 $ 

50,001-100K 37.34 $ 9.0 3.0 12.0 12.0 12.0 2.0 3.0 1.8 54.8 2,044 $ 102 $ 

100,000-1M 37.34 $ 15.0 8.0 24.0 18.0 18.0 3.0 3.0 1.8 90.8 3,389 $ 169 $ 

>1,000,000 37.34 $ 24.0 10.0 36.0 18.0 18.0 4.0 4.0 1.8 115.8 3,389 $ 169 $ 

Nontransient Noncommunity Water Systems (NTNCWSs)

<100 37.34 $ 1.0 0.8 1.0 1.9 5.1 1.0 1.3 1.8 13.8 515 $ 26 $ 

101-500 37.34 $ 1.0 0.8 1.1 2.0 5.3 1.0 1.3 1.8 14.2 531 $ 27 $ 

501-1,000 37.34 $ 1.1 0.9 1.3 2.1 6.5 0.8 1.2 1.8 15.6 583 $ 29 $ 

1,001-3,300 37.34 $ 1.1 1.1 1.2 2.1 6.2 0.8 1.3 1.8 15.6 581 $ 29 $ 

3,301-10K 37.34 $ 1.5 1.5 1.7 2.2 6.7 0.8 1.5 1.8 17.6 657 $ 33 $ 

10,001-50K 37.34 $ 1.3 0.8 1.8 2.5 5.0 0.8 1.3 1.8 15.0 560 $ 28 $ 

50,001-100K 37.34 $ 1.5 0.8 2.3 2.5 5.0 0.8 1.3 1.8 15.8 588 $ 29 $ 

100,000-1M 37.34 $ 8.0 1.0 10.0 8.0 10.0 1.0 1.5 1.8 41.3 1,540 $ 77 $ 

>1,000,000 NA NA NA NA NA NA NA NA 1.8 NA NA NA

Transient Noncommunity Water Systems (TNCWSs)

<100 37.34 $ 0.7 0.6 0.6 1.5 5.1 0.8 0.9 1.8 11.9 443 $ 22 $ 

101-500 37.34 $ 0.7 0.6 0.6 1.5 5.3 0.8 0.9 1.8 12.1 452 $ 23 $ 

501-1,000 37.34 $ 1.0 0.8 1.0 1.8 5.8 0.8 0.9 1.8 13.9 518 $ 26 $ 

1,001-3,300 37.34 $ 0.9 1.0 0.9 1.7 4.7 0.8 1.1 1.8 12.9 480 $ 24 $ 

3,301-10K 37.34 $ 1.2 1.3 1.2 1.5 5.2 0.8 1.2 1.8 14.1 526 $ 26 $ 

10,001-50K 37.34 $ 0.8 0.5 1.3 1.3 3.8 0.8 0.8 1.8 10.8 401 $ 20 $ 

50,001-100K 37.34 $ 1.3 0.5 1.3 1.3 3.8 0.8 0.8 1.8 11.3 420 $ 21 $ 

100,000-1M 37.34 $ 8.0 1.0 10.0 3.0 8.0 0.5 1.0 1.8 33.3 1,242 $ 62 $ 

>1,000,000 NA NA NA NA NA NA NA NA 1.8 NA NA NA

Notes:

System Size

(Population 

Served)

Weighted unit costs equal 5% of the unit costs. This factor accounts for 50% effort for an incremental survey and 10% of systems that do not already comply with rule requirements (see 

text discussion).

Exhibit 6.12a State Unit Burden and Cost Estimates 

for Performing Full and Incremental Sanitary Surveys (Treatment)
Economic Analysis for the October 2006

Final Ground Water Rule 6-24

Labor

Cost 

(per hour)

Review/

Inspect 

Wells

Review/

Inspect 

Distribution 

System

Report

Documenta

tion/

File Review

Report 

Develop

ment Data Entry

Report 

Review and 

Discussion 

w/ PWS Travel

Total

Unit Burden

(hours)

Unit Cost

(Full Survey)

Weighted Unit Cost 

(Incremental Survey)

A B C DE F GH I=sum(B-H) J=A*I K=0.05*J

Community Water Systems (CWSs) 

<100 37.34 $ 1.1 1.2 2.3 5.7 0.8 1.1 1.8 13.9 521 $ 26 $ 

101-500 37.34 $ 1.2 1.2 2.3 5.8 0.8 1.1 1.8 14.1 526 $ 26 $ 

501-1,000 37.34 $ 1.5 1.7 2.6 7.4 0.8 1.2 1.8 16.9 631 $ 32 $ 

1,001-3,300 37.34 $ 2.2 2.9 3.4 8.8 1.2 1.4 1.8 21.5 803 $ 40 $ 

3,301-10K 37.34 $ 2.7 3.6 3.7 9.6 1.3 1.8 1.8 24.3 909 $ 45 $ 

10,001-50K 37.34 $ 3.7 4.3 5.3 10.1 1.4 1.9 1.8 28.3 1,058 $ 53 $ 

50,001-100K 37.34 $ 9.0 12.0 12.0 12.0 2.0 3.0 1.8 51.8 1,932 $ 97 $ 

100,000-1M 37.34 $ 15.0 24.0 18.0 18.0 3.0 3.0 1.8 82.8 3,090 $ 155 $ 

>1,000,000 37.34 $ 24.0 36.0 18.0 18.0 4.0 4.0 1.8 105.8 3,090 $ 155 $ 

Nontransient Noncommunity Water Systems (NTNCWSs)

<100 37.34 $ 1.0 1.0 1.9 5.1 1.0 1.3 1.8 13.0 487 $ 24 $ 

101-500 37.34 $ 1.0 1.1 2.0 5.3 1.0 1.3 1.8 13.5 503 $ 25 $ 

501-1,000 37.34 $ 1.1 1.3 2.1 6.5 0.8 1.2 1.8 14.8 551 $ 28 $ 

1,001-3,300 37.34 $ 1.1 1.2 2.1 6.2 0.8 1.3 1.8 14.5 540 $ 27 $ 

3,301-10K 37.34 $ 1.5 1.7 2.2 6.7 0.8 1.5 1.8 16.1 601 $ 30 $ 

10,001-50K 37.34 $ 1.3 1.8 2.5 5.0 0.8 1.3 1.8 14.3 532 $ 27 $ 

50,001-100K 37.34 $ 1.5 2.3 2.5 5.0 0.8 1.3 1.8 15.0 560 $ 28 $ 

100,000-1M 37.34 $ 8.0 10.0 8.0 10.0 1.0 1.5 1.8 40.3 1,503 $ 75 $ 

>1,000,000 NA NA NA NA NA NA NA NA NA NA NA

Transient Noncommunity Water Systems (TNCWSs)

<100 37.34 $ 0.7 0.6 1.5 5.1 0.8 0.9 1.8 11.3 421 $ 21 $ 

101-500 37.34 $ 0.7 0.6 1.5 5.3 0.8 0.9 1.8 11.5 431 $ 22 $ 

501-1,000 37.34 $ 1.0 1.0 1.8 5.8 0.8 0.9 1.8 13.0 487 $ 24 $ 

1,001-3,300 37.34 $ 0.9 0.9 1.7 4.7 0.8 1.1 1.8 11.9 443 $ 22 $ 

3,301-10K 37.34 $ 1.2 1.2 1.5 5.2 0.8 1.2 1.8 12.8 476 $ 24 $ 

10,001-50K 37.34 $ 0.8 1.3 1.3 3.8 0.8 0.8 1.8 10.3 383 $ 19 $ 

50,001-100K 37.34 $ 1.3 1.3 1.3 3.8 0.8 0.8 1.8 10.8 401 $ 20 $ 

100,000-1M 37.34 $ 8.0 10.0 3.0 8.0 0.5 1.0 1.8 32.3 1,204 $ 60 $ 

>1,000,000 NA NA NA NA NA NA NA NA NA NA NA

Notes:

System Size

(Population 

Served)

Weighted unit costs equal 5% of the unit costs. This factor accounts for 50% effort for an incremental survey and 10% of systems that do not already comply with rule 

requirements (see text discussion).

Exhibit 6.12b State Unit Burden and Cost Estimates 

for Performing Full and Incremental Sanitary Surveys (No Treatment)
5

 If TC is detected in more than one sample collected at a single location during the same sampling event,

only one triggered monitoring sample is required to be taken from a water source directly related to that location.

Economic Analysis for the October 2006

Final Ground Water Rule 6-25

Mean

Lower 

Bound

(5th %ile)

Upper 

Bound

(95th 

%ile) Mean

Lower 

Bound

(5th %ile)

Upper 

Bound

(95th 

%ile) Mean

Lower 

Bound

(5th %ile)

Upper 

Bound

(95th 

%ile)

3% $0.21 $0.11 $0.31 $1.45 $0.66 $2.23 $1.66 $0.77 $2.54

7% $0.20 $0.10 $0.30 $1.39 $0.63 $2.14 $1.59 $0.74 $2.44

Notes: Detail may not add to totals due to independent rounding and independent cost model runs.

Source: Cost Model Outputs

Systems States Total

Annualized Costs for Sanitary Survey Activities

Exhibit 6.13 PWS and State Cost Estimates for Sanitary Survey Performance

($Millions, 2003$)

1 6.4.3 Triggered Source Water Monitoring

2 PWSs

3 Systems that do not achieve 4-log treatment of viruses (using inactivation, removal, or State4 approved combination of these technologies) before or at the first customer will be subject to triggered

5 source water monitoring. Under this provision, systems are required to collect and analyze samples at

6 the ground water source following the detection of total coliform (TC) in one or more samples collected

for compliance with the TCR.5 7 Systems are not required to conduct triggered source water monitoring if,

8 according to State criteria or a State determination, the cause of the total coliform-positive sample

9 collected under the TCR directly relates to the distribution system. While States have the option of

10 requiring the triggered monitoring samples to be tested for the presence of a State-specified fecal

11 indicator, for the purpose of this cost analysis, EPA assumed that States will select E. coli as the indicator

12 for analysis.

13 If a system detects the State-specified fecal indicator at its source, then the system must take five

14 additional samples within 24 hours unless the State determines that corrective action must be taken

15 immediately. If any of the additional samples is positive, the system must implement a corrective action. 

16 Corrective actions fall into two major categories: non-treatment and treatment (see Section 6.4.4 for

17 detailed discussion). Several compliance estimates were considered to develop estimates of the cost

18 associated with triggered monitoring: the frequency with which systems will have to perform triggered

19 monitoring; the frequency that a TC positive is deemed to be related to the distribution system; the year in

20 which the triggered monitoring occurs; and the number of systems that are expected to test positive for

21 the fecal indicator. These factors are discussed in greater detail below. Exhibit 6.14 presents a schematic

22 of the triggered monitoring process as applied in the cost model.
Economic Analysis for the October 2006

Final Ground Water Rule 6-26

Triggered Monitoring

-Collect source water sample within 24 hours of receiving 

initial notification of TC+

-If purchased system, notify wholesaler of TC+ within 24 

hours. Wholesaler must must sample source water within 

24 hours of receiving notification of TC+ sample result.

5,638 EPs * 0.58 samples / EP/year = 

3,267 samples/year (approx.)

Has system tested 

positive for the 

fecal indicator?

617 EPs

(cost model output, see Exhibit 6.5b) 

617 EPs/22 years = 28 EPs/year 

Continue TM at 

specified intervals

Yes No

EPs not achieving 4-log virus treatment

5,638 EPs

(cost model output, see Exhibit 6.5b)

See section 6.4.4 on 

Corrective Action

5,021 EPs

1 Exhibit 6.14 Schematic of Triggered Monitoring Process

2 (Numbers based on 3,301 - 10,000 population category for CWSs)

3 * Each positive sample corresponds to either one entry point predicted to have treatment corrective action or one well per entry

4 point to have a nontreatment corrective action. Systems must provide corrective actions if a source water positive sample is also

5 followed by a positive additional source water sample. The State, at its discretion, may require corrective action based on the

6 initial positive source water sample (See sections 6.4.3 and 6.6 for discussion).

7 Frequency of Performing Triggered Monitoring: EPA estimated the number of times per year

8 that a ground water system’s total coliform sampling produced a positive result, which would trigger the

9 GWR source water monitoring requirements. The GWR allows States to determine which well within a

10 system may be related to each TC-positive. EPA makes the simplifying assumption that monitoring at

11 one EP within a system will approximate this rule provision. Due to the uncertainty in DV data, this

12 assumption may over- or under-estimate the number of EPs subject to triggered monitoring (see Appendix

13 I for further discussion). A summary of the methodology used to estimate the annual number of TC14 positive samples per system is presented in Section 4.2.7 and additional detail on the analysis is presented
6

 Estimated costs for additional triggered monitoring ($200,000) are calculated as the product of all entry

points (by system size and type) taking corrective action for triggered monitoring (Exhibit 6.5b, column D) and

sampling unit costs (Exhibit 6.3). Estimated costs savings from samples already taken under the TCR are calculated

as the product of all entry points serving 1,000 or fewer people (by system size and type) subject to triggered

monitoring (Exhibit 6.5b, column C), the average number of TC positive samples per year under TCR routine

monitoring (Exhibit 6.15), and sampling unit costs (Exhibit 6.3). Under both scenarios, costs are apportioned on an

annual basis and final costs are calculated as annualized present values using a three percent discount rate.

Economic Analysis for the October 2006

Final Ground Water Rule 6-27

1 in Appendix I. The results presented in that Section 4.2.7 (Exhibit 4.11) are repeated in Exhibit 6.15

2 below for convenience. These estimates reflect the annual number of samples taken by systems of

3 different sizes and types. Sampling costs for triggered monitoring are calculated by multiplying the

4 annual number of triggered monitoring samples taken by the sampling unit costs presented previously in

5 Exhibit 6.3. 

6

7 Exhibit 6.15 Estimated Number of Triggered Samples Per Year Per Entry Point

8 System

9 Type

System Size (Population Served)

<100

101-

500 501-1K

1,001-

3,300

3,301-

10K

10,001-

50K

50,001-

100K >100K

10 CWS 0.38 0.41 0.49 0.22 0.58 2.2 6.6 10.6

11 NTNCWS 0.22 0.23 0.28 0.70 1.8 7.0 20.8 33.7

12 TNCWS 0.47 0.48 0.60 1.1 2.9 11.0 32.6 52.8

13 Source: Exhibit 4.11

14 Total Coliform Positive Samples Related to the Distribution System: Systems are not required to

15 conduct triggered source water monitoring if, according to State criteria or a State determination, the

16 cause of the total coliform-positive sample collected under the TCR directly relates to the distribution

17 system. Since it is difficult to predict the number of TC positives that are due to source water versus

18 distribution system contamination, EPA assumes each TC positive will result in a triggered source water

19 monitoring sample. The assumption likely overestimates triggered monitoring sample costs.

20 The Five Additional Samples Following an Initial Indicator Positive Sample: Neither the

21 schematic nor this cost analysis includes additional sampling (the cost model assumes that systems take

22 corrective action based on the first positive indicator sample result). EPA expects about 3% of the initial

23 triggered monitoring assays will be positive and therefore require additional sampling. The total number

24 of assays (triggered plus additional samples) would therefore be about 15% greater than the total number

25 of initial triggered monitoring samples that are included in the cost analysis. EPA believes that this factor

26 (understating the cost of triggered plus additional monitoring by $200,000 per year) is more than offset by

27 including costs for samples that are already collected and assayed under the Total Coliform Rule

(estimated value of more than $3 million per year).6 28 The GWR allows selected samples that are collected

29 under the TCR to be used in satisfying both the TCR repeat sample requirements and (per State approval)

30 the initial source water fecal indicator under this GWR. The costs of these assays can therefore be

31 attributed to the TCR rather than the GWR. By attributing all of these costs to the GWR, this analysis has
Economic Analysis for the October 2006

Final Ground Water Rule 6-28

1 probably overestimated the triggered monitoring costs by more than $3 million. In addition, although

2 additional sampling will add to the total cost of monitoring, it will cause a decrease in the cost estimate

3 for providing corrective actions (i.e., some systems with an initial positive sample will not have any

4 positive additional samples). Since the costs of corrective actions are higher than the costs of additional

5 sampling, the net cost may be an overestimate. This overestimation coupled with the TCR-related

6 overestimation more than offsets the underestimation due to not including additional samples

7 (approximately $200,000) and the net effect is an overestimation of costs.

8 Percent of EPs Testing Positive: The triggered monitoring component of the model applies only

9 to the nondisinfecting subset of EPs (and any EPs that are applying disinfectant but not achieving 4-log

10 treatment of viruses using inactivation, removal, or State-approved combination of these technologies,

11 before or at the first customer). It is assumed that no triggered monitoring samples are taken during the

12 first three years following rule promulgations, but may be taken during any of the 22 years from year 4

13 through year 25.

14 For the triggered monitoring component of the cost analysis, each EP not achieving 4-log

15 treatment of viruses using inactivation, removal, or State-approved combination of these technologies,

16 before or at the first customer, goes through a 2-step process similar to that described in Chapter 5 for the

17 risk reduction model. In the first step of the process, estimates are made of the number of TC positives -

18 and therefore the number of source water indicator samples - that occur during the 22 years of the

19 compliance period between year 4 and year 25. The number of TC positives expected per year for each

20 EP of a given type and size are obtained from the DV data as described in chapter 4. The number of TC

21 positives per year, and therefore the expected number of triggered indicator samples taken per year, are

22 summarized in Exhibit 6.15. The total number of TC positives expected through year 25 is then

23 calculated as the number of TC positives per year times 22. If, for example, an EP is in the CWS size

24 10,000-50,000 category, the DV data indicate that these EPs average 2.21 TC positives per year; over 22

25 years, then, it is expected that each EP in this system size category will have 48.6 TC positives and

26 therefore take up to 49 source water indicator samples between years 4 and 25.

27 In the second step of the process, a simulation is performed to determine which, if any, of the

28 indicator samples taken through year 25 is the first fecal positive indicator result. In each uncertainty

29 loop of the cost model a set of values is selected reflecting the probability that the first positive of an

30 indicator will occur on a given assay number. Exhibit 4.21 showed the probability of the first fecal

indicator positive occurring on a given assay for the median and the 5th and 95th 31 percentiles of a sample of

32 1,000 of these uncertainty sets of occurrence values.

33 The data for each uncertainty set provide the cumulative probabilities of observing the first fecal

34 positive on or before each specific assay number. In the cost model, a random value between 0 and 1 is

35 generated for each EP. That value is used as a look-up value to determine what assay number would

36 produce the first fecal positive.

37

38 For example, if the curve shown as the median data set in Exhibit 4.26 were the set of values

39 being used for a particular uncertainty loop, and the random number between 0 and 1 generated for an EP

40 in the CWS size 10,000-50,000 category were 0.095, the look-up function would indicate that the first

41 fecal indicator positive would occur on assay number 8. Since these EPs are expected to take 48.6 fecal

indicator assays over the 22 year period, the 8th assay would occur in the 4th 42 year [(22 years/48.6

43 assays)*8 assays ~ 3.6]. Since there are no triggered monitoring samples taken in years 1 through 3
Economic Analysis for the October 2006

Final Ground Water Rule 6-29

following promulgation, the 4th 1 year of sampling corresponds to year 7 of the 25 year modeling period. 

2 Therefore, this well would be "caught" by triggered monitoring in year 7. 

3 EPs that test positive (both with initial and additional samples) for an indicator of fecal

4 contamination must perform corrective action. Costs for performing corrective actions are discussed in

5 Section 6.4.4. In addition, a report must be submitted to the State notifying them of the problem. EPA

6 estimates that this report will require, on average, 2.5 hours to complete and submit. EPA has developed

7 and systems will have access to automated forms that will minimize the burden to systems in complying

8 with this reporting requirement. Exhibit 6.16 below presents system unit costs for triggered monitoring

9 reporting requirements.

10 

11 Based on the number of TC positives expected per EP across all EP types and sizes, together with

12 the expected values of fecal indicator positives as a function of assay number across all of the uncertainty

13 sets available to draw from for the simulation model, it can be estimated that approximately 10.2% (90%

14 confidence bounds of 7.4% - 13.4%) of all nondisinfecting EPs will have a fecal indicator positive from

the triggered monitoring provision of the rule by the 25th 15 year of the modeling timeframe. The 10.2% of

16 all nondisinfecting EPs that are identified over the 25-year timeframe as having fecal indicator occurrence

17 comprise nearly 40% of the subset of those EPs that are expected to have fecal contamination at some

18 time. This is because the occurrence analysis shows that about 26.2% of all EPs are believed to have

19 some fecal contaminant occurrence. The estimate of 26.2% of EPs having some fecal contaminant

20 occurrence is based on the mean values of P2 and P3 from a sample of 10,000 estimates, where P2

21 (~16.5%) is the fraction of EPs having both viral and fecal indicator occurrence and P3 (~9.7%) is the

22 fraction having fecal indicator, but no viral occurrence. Therefore the fraction of all fecally contaminated

23 wells that are identified over the 25-year period can be estimated as 10.2% / 26.2% = 38.9% = ~40%. See

24 Chapter 4, Section 4.3.4.1 for the derivation of P2, P3, and other viral and fecal indicator hit rate

25 parameters.

26 Invalidation of Samples: The GWR allows a State to invalidate a positive source water sample if

27 it believes that the positive is due to improper analysis. States may also invalidate positive source water

28 samples that are due to circumstances not reflecting source water quality. Systems must resample after a

29 sample is invalidated. For costing purposes, EPA, based on best professional judgement, estimates that

30 States will invalidate a minimal number of samples resulting in a negligible cost and burden.
Economic Analysis for the October 2006

Final Ground Water Rule 6-30

Report

Prep

(hours)

Labor

Cost

(per

hour)

Unit

Cost

A B C=A*B D E F G=E*F

Community Water Systems (CWSs) 

<100 12,797 0.38 4,842 57 2.5 21.44 $ 53.60 $ 

101-500 14,819 0.41 6,076 74 2.5 23.09 $ 57.73 $ 

501-1,000 5,578 0.49 2,760 28 2.5 24.74 $ 61.85 $ 

1,001-3,300 8,910 0.22 1,975 32 2.5 24.74 $ 61.85 $ 

3,301-10K 5,638 0.58 3,267 28 2.5 30.51 $ 76.28 $ 

10,001-50K 4,357 2.21 9,609 30 2.5 31.08 $ 77.70 $ 

50,001-100K 1,295 6.56 8,492 10 2.5 31.08 $ 77.70 $ 

100,001-1 Million 749 10.63 7,958 6 2.5 35.25 $ 88.12 $ 

> 1 Million - 10.63 - - 2.5 35.25 $ 88.12 $ 

Totals 54,142 44,979 265 

Nontransient Noncommunity Water Systems (NTNCWSs)

<100 8,609 0.22 1,887 31 2.5 21.44 $ 53.60 $ 

101-500 6,149 0.23 1,384 24 2.5 23.09 $ 57.73 $ 

501-1,000 1,724 0.28 485 7 2.5 24.74 $ 61.85 $ 

1,001-3,300 651 0.70 457 4 2.5 24.74 $ 61.85 $ 

3,301-10K 66 1.84 122 0 2.5 30.51 $ 76.28 $ 

10,001-50K 9 6.99 64 0 2.5 31.08 $ 77.70 $ 

50,001-100K 1 20.78 19 0 2.5 31.08 $ 77.70 $ 

100,001-1 Million 1 33.67 31 0 2.5 35.25 $ 88.12 $ 

> 1 Million - 33.67 NA NA NA 35.25 $ NA

Totals 17,209 4,447 67 

Transient Noncommunity Water Systems (TNCWSs)

<100 63,295 0.47 29,605 314 2.5 21.44 $ 53.60 $ 

101-500 18,648 0.48 8,955 92 2.5 23.09 $ 57.73 $ 

501-1,000 1,905 0.60 1,144 9 2.5 24.74 $ 61.85 $ 

1,001-3,300 574 1.10 633 3 2.5 24.74 $ 61.85 $ 

3,301-10K 73 2.88 209 1 2.5 30.51 $ 76.28 $ 

10,001-50K 19 10.97 205 0 2.5 31.08 $ 77.70 $ 

50,001-100K 1 32.60 32 0 2.5 31.08 $ 77.70 $ 

100,001-1 Million 1 52.83 52 0 2.5 35.25 $ 88.12 $ 

> 1 Million - 52.83 NA NA NA 35.25 $ NA

Totals 84,515 40,835 420 

Grand Total 155,867 90,261 752 

Notes: Detail may not add to totals due to independent rounding.

NA Not applicable (no NCWSs of this size category).

Costs of repeat samples are not included. See Section 6.6 for discussion.

Source: (A) Number of entry points from Exhibit 6.5b.

(B) Mean triggered samples per system calculated from Exhibit 6.15.

(F) Labor rates from Exhibit 6.1.

(E) Labor hours for report preparation based on EPA experience with similar rule requirements.

(D) Values in Column D, Exhibit 6.5b are divided by 22 years to obtain postive triggered monitoring EPs/year. 

System Size

(Population Served)

Average Fecal 

Positive

 Triggered

Monitoring

Entry 

Points/year

Entry Points

Triggered

Monitoring

Mean

Number

of Samples

per EP per 

Year

Triggered

Monitoring

Samples/year

Reporting/Positive Triggered Monitoring 

Sample

1 Exhibit 6.16 PWS Unit Costs for Triggered Monitoring
Economic Analysis for the October 2006

Final Ground Water Rule 6-31

Mean

Lower 

Bound

(5th %ile)

Upper 

Bound

(95th 

%ile) Mean

Lower 

Bound

(5th %ile)

Upper 

Bound

(95th 

%ile) Mean

Lower 

Bound

(5th %ile)

Upper 

Bound

(95th 

%ile)

3% $5.44 $5.32 $5.56 $0.09 $0.06 $0.12 $5.52 $5.38 $5.67

7% $5.39 $5.27 $5.51 $0.10 $0.07 $0.13 $5.48 $5.34 $5.64

Notes: Detail may not add to totals due to independent rounding and independent cost model runs.

Source: Cost Model Outputs

Systems States Total

Annualized Costs for Triggered Monitoring Performance

1 States

2 State costs for triggered monitoring are assumed to be solely administrative. States incur costs to

3 review several paperwork requirements: reports of positive samples (including the results of additional

4 samples) and sample invalidation documentation. Each of these reports and associated costs is explained

5 below. 

6 Review Reports of Source Water Positives: The GWR requires systems that find a source water

7 sample positive for fecal contamination to report this to the State. Based on its experience with similar

8 reporting requirements, EPA estimates that States will require 3.5 hours to review the report. Using a

9 labor cost of $33.60 per hour, EPA estimates a unit cost of $117.61 to review the report. This estimate is

10 greater than the burden estimated for systems to prepare and submit the report because it is anticipated

11 that the State will have less familiarity with any particular system and will be required to look up

12 additional historical information to make any assessments/determinations regarding the report. 

13 Invalidation of Samples: As noted above, the GWR allows a State to invalidate a fecal positive

14 source water sample result that is due to improper analysis. States may also invalidate a fecal positive

15 source water sample results that are due to circumstances not reflecting source water quality. For costing

16 purposes, EPA estimates that States will invalidate a minimal number of samples, resulting in a negligible

17 cost and burden.

18 Annualized cost estimates for systems and States to perform triggered monitoring are presented in

19 Exhibit 6.17.

20 Exhibit 6.17 PWS and State Cost Estimates for Performing Triggered Monitoring

21 ($Millions, 2003$)

22

23
Economic Analysis for the October 2006

Final Ground Water Rule 6-32

6.4.4 Corrective Actions

The purpose of conducting sanitary surveys is to identify significant deficiencies in PWSs that

need correction. Systems also conduct source water monitoring to detect fecal contamination in source

water. Identification of significant deficiencies as well as the detection of fecal indicators requires

systems to take corrective action under the GWR. National costs of these corrective actions comprise the

majority of the costs associated with the GWR. This section explains the methodology used for

estimating the national costs of implementing corrective actions under the GWR. This section includes

discussions of the compliance forecast used to determine the corrective actions undertaken by PWSs,

estimation of the burden and costs of corrective action plans, and the derivation of capital and O&M costs

associated with the various corrective actions. Where available, existing data on treatment practices were

used to determine compliance forecasts, burden, and cost estimates. In the absence of data, EPA used

best professional judgement based on consultations with Agency, industry, and State experts and

representative organizations (e.g., ASDWA) to make estimates.

6.4.4.1 Sanitary Survey Corrective Actions

Compliance Forecast

The GWR requires each PWS to correct any significant deficiencies found during a sanitary

survey. Because States have the authority to define significant deficiencies under the GWR, EPA

predicted the types of deficiencies that will be found and corrected as a result of the rule. EPA consulted

with experts from within the Agency and from States to develop a list of corrective actions to address

deficiencies that are likely to be identified in sanitary surveys of ground water systems (USEPA, 1996b). 

Potential significant deficiencies identified can occur at the source of water, in a treatment plant, or in the

distribution system.

EPA lacks adequate data to quantify the number of significant deficiencies that will be detected

and corrected in the distribution system as well as in the treatment processes. Therefore, costs associated

with these deficiencies are not included in the cost model (see section 6.6 for further discussion of the

nonquantified costs). Similarly, the associated benefits are not included in the benefits model. To

estimate costs for significant deficiencies detected at or near the source, the following corrective actions

are used in the cost model.

• Replace a sanitary well seal

• Rehabilitate an existing well

By limiting the corrective actions considered to the two options listed above, EPA has created a

simplified, but representative estimate of actions that may be taken by systems. In general, EPA believes

the costs for these significant deficiencies represent the range of costs systems would be expected to incur

for providing correction of significant deficiencies. Many other specific corrective actions may be taken

to adequately address significant deficiencies identified at or near the source. Some actions, such as

drilling a new well or purchasing water from another supplier, would be more expensive than these

options. However, based on discussions with experts, EPA believes that a majority of corrective actions

(e.g., fencing off or providing other limited access to infrastructure to protect wells) may actually be less

expensive than the two used in the cost model. Other well repairs that could correct source contamination
Economic Analysis for the October 2006

Final Ground Water Rule 6-33

such as installation of pump block seals, pump block/well pad repair, or correcting runoff and drainage

problems would be less expensive, and as such, be the first consideration for any system looking to most

cost-effectively correct a problem. This is especially true for small systems which often have to address

such issues with limited resources.

To further account for uncertainty in the corrective actions that will be taken, PWSs are assigned

one of the two potential significant deficiencies listed above according to one of two probability

distributions. Exhibit 6.18 presents these distributions. Because the corrections of significant

deficiencies are dependent upon the deficiencies defined as significant by States and the conditions of

specific systems, both of which are highly variable, EPA used a high scenario/low scenario estimating

procedure to bound the cost estimates. The low-cost scenario assumes a greater percentage of the systems

with significant deficiencies will have deficiencies that are less expensive to correct (e.g., more systems

will have to replace their sanitary well seal than will have to perform a complete rehabilitation of their

well). This high/low bounding provides an estimate of the uncertainty with respect to the percentages of

each type of defect to be corrected.

Exhibit 6.18 Estimated Distribution of Significant Deficiency Corrective Actions

Corrective Action

Low Cost

Distribution

High Cost

Distribution

Percentage Number Percentage Number

ABCD

Replace a sanitary well seal 60 15,028 40 10,018

Rehabilitate an existing well 40 10,018 60 15,028

Source: (A,C) Distribution of corrective actions based on best professional judgement.

(B,D) based on (A,C), 147,330 total number of systems subject to the GWR (Exhibit 4.1), and 17% percent

of systems not constructed according to applicable State regulations (ASDWA survey).

The number of PWSs identifying a significant deficiency during a sanitary survey is determined

based on survey data from the Association of State Drinking Water Administrators (ASDWA) (1997). 

Based on responses to the ASDWA survey, it was determined that 17% of systems had wells that were

not constructed according to applicable State regulations. This percentage is used as an estimate of the

number of systems that will find significant deficiencies at or near the source over the 25-year cost model

analysis period. Within the cost model, the assignment of significant deficiencies is applied equally in

years 4 - 25 of the analysis, resulting in approximately 0.77% of systems (17% / 22 years) being assigned

a corrective action in each of those years.

Unit Cost Estimates

Once a corrective action has been selected, a unit cost for that change is applied based on system

size. The costs for correction of significant deficiencies identified during sanitary surveys are dependent

upon the nature of the deficiency. Costs were developed based on the Technology and Cost Document for

the Final Ground Water Rule (USEPA, 2006d) to correct each of the identified significant deficiencies
Economic Analysis for the October 2006

Final Ground Water Rule 6-34

Size Category (Population Served)

<100 101-500

501-

1,000

1,001-

3,300

3,301-

10,000

10,001-

50,000

50,001-

100,000

100,001-

1 Million >1 Million

$3,627 $3,627 $3,627 $3,627 $3,627 $3,627 $3,627 $3,627 $3,627

$11,986 $11,986 $11,986 $11,986 $11,986 $11,986 $11,986 $11,986 $11,986

Source: GWR Technology and Cost Document

Corrective Action

Replace a Sanitary

Well Seal

Rehabilitate an

Existing Well

and are presented in Exhibit 6.19 below. These costs are considered one-time expenditures that occur in

the year the significant deficiency is found.

Exhibit 6.19 Estimated Unit Costs of Significant Deficiency Corrective Actions

Corrective Action Plans

All systems are required to take corrective action for a significant deficiency that is identified

during sanitary surveys. Systems must consult with States and develop a corrective action plan, submit it

to the State for approval, and implement the corrective action (or combination of actions) approved by the

State. Exhibit 6.20a details the burden and cost to systems to prepare corrective action plans, as well as

the burden and cost to States to review them. EPA has developed and systems and States will have access

to automated forms that will minimize the burden to systems in complying with this reporting

requirement. These costs also apply for corrective actions due to source water contamination, discussed

below. It is assumed that large systems will have more technical and managerial staff compared to small

systems, and will therefore have less interaction with States than small systems. This assumption is

reflected in column D of Exhibit 6.20a; State burden is incurred on a 1:1 ratio to system burden for small

systems, and on a 0.5:1 ratio for large systems.
Economic Analysis for the October 2006

Final Ground Water Rule 6-35

Corrective

Action

Plan

(hours)

Plan

Labor

Cost

(per hour)

Unit

Plan

Cost

Review

Plan

(hours)

Review

Labor

Cost

(per hour)

Unit

Plan

Review

Cost

A B C=A*B D E F=D*E

Community Water Systems (CWSs) 

<100 12 21.44 $ 257.28 $ 12 37.34 $ 448.10 $ 

101-500 13 23.09 $ 300.17 $ 13 37.34 $ 485.44 $ 

501-1,000 19 24.74 $ 470.06 $ 19 37.34 $ 709.50 $ 

1,001-3,300 29 24.74 $ 717.46 $ 29 37.34 $ 1,082.92 $ 

3,301-10K 58 30.51 $ 1,769.70 $ 58 37.34 $ 2,165.83 $ 

10,001-50K 60 31.08 $ 1,864.80 $ 30 37.34 $ 1,120.26 $ 

50,001-100K 70 31.08 $ 2,175.60 $ 35 37.34 $ 1,306.97 $ 

100,001-1 Million 74 35.25 $ 2,608.35 $ 37 37.34 $ 1,381.65 $ 

 35.25 74 $ 2,608.35 $ 37 37.34 $ 1,381.65 $ 

Nontransient Noncommunity Water Systems (NTNCWSs)

<100 12 21.44 $ 257.28 $ 12 37.34 $ 448.10 $ 

101-500 13 23.09 $ 300.17 $ 13 37.34 $ 485.44 $ 

501-1,000 19 24.74 $ 470.06 $ 19 37.34 $ 709.50 $ 

1,001-3,300 29 24.74 $ 717.46 $ 29 37.34 $ 1,082.92 $ 

3,301-10K 58 30.51 $ 1,769.70 $ 58 37.34 $ 2,165.83 $ 

10,001-50K 60 31.08 $ 1,864.80 $ 30 37.34 $ 1,120.26 $ 

50,001-100K 70 31.08 $ 2,175.60 $ 35 37.34 $ 1,306.97 $ 

100,001-1 Million 74 35.25 $ 2,608.35 $ 37 37.34 $ 1,381.65 $ 

NA 35.25 $ NA NA NA NA

Transient Noncommunity Water Systems (TNCWSs)

<100 12 21.44 $ 257.28 $ 12 37.34 $ 448.10 $ 

101-500 13 23.09 $ 300.17 $ 13 37.34 $ 485.44 $ 

501-1,000 19 24.74 $ 470.06 $ 19 37.34 $ 709.50 $ 

1,001-3,300 29 24.74 $ 717.46 $ 29 37.34 $ 1,082.92 $ 

3,301-10K 58 30.51 $ 1,769.70 $ 58 37.34 $ 2,165.83 $ 

10,001-50K 60 31.08 $ 1,864.80 $ 30 37.34 $ 1,120.26 $ 

50,001-100K 70 31.08 $ 2,175.60 $ 35 37.34 $ 1,306.97 $ 

100,001-1 Million 74 35.25 $ 2,608.35 $ 37 37.34 $ 1,381.65 $ 

NA 35.25 $ NA NA NA NA

Notes: Detail may not add due to independent rounding.

NA= Not applicable (no NCWSs of this size category).

Sources: (A) Labor hours for preparing plan reflect EPA estimate based on best professional judgement.

(B) Labor rates from Exhibit 6.1.

(D) Labor hours for corrective action plan review reflect EPA estimate.

(E) Labor rate for field engineer from Exhibit 6.2.

System Size

(Population Served)

PWSs States

> 1 Million

> 1 Million

> 1 Million

Exhibit 6.20a PWS and State Unit Costs for Corrective Action Plans

Annualized cost estimates for systems and States to perform sanitary survey corrective actions

(including capital, O&M, and corrective action plan costs) are presented in Exhibit 6.20b.
Economic Analysis for the October 2006

Final Ground Water Rule 6-36

Mean

Lower 

Bound

(5th %ile)

Upper 

Bound

(95th 

%ile) Mean

Lower 

Bound

(5th %ile)

Upper 

Bound

(95th 

%ile) Mean

Lower 

Bound

(5th %ile)

Upper 

Bound

(95th 

%ile)

3% $8.46 $5.74 $11.60 $0.56 $0.52 $0.61 $9.02 $6.25 $12.21

7% $8.13 $5.51 $11.14 $0.54 $0.50 $0.59 $8.67 $6.01 $11.73

Notes: Detail may not add to totals due to independent rounding and independent cost model runs.

Source: Cost Model Outputs

Systems States Total

Annualized Costs for Sanitary Survey Corrective Action Activities

Exhibit 6.20b PWS and State Cost Estimates for Sanitary Survey Corrective

Action Activities ($Millions, 2003$)

6.4.4.2 Source Water Contamination Corrective Actions

Compliance Forecast

As discussed in section 6.4.3, unless a system that detects fecal contamination in its source water

from triggered monitoring is directed by the State to take immediate corrective action, the systems must

collect and test an additional five source water samples for the presence of the same State-specified fecal

indicator within 24 hours. If any one of the five additional source water samples tests positive for the

State-specified fecal indicator (E. coli, enterococci, or coliphage), this rule requires the system to take

corrective action. For costing purposes, EPA assumes that the initial indicator positive sample will

correspond to either one entry point predicted to have corrective treatment or one well per entry point to

have a nontreatment corrective action. EPA believes this may underestimate treatment and nontreatment

corrective action costs if more than one entry point or well in a given system requires corrective action. 

However, corrective action costs may be overestimated because if none of the five additional samples are

positive, no corrective action is required under the rule.

Similar to sanitary survey corrective actions, systems must consult with States and develop a

corrective action plan, submit it to the State for approval, and implement the corrective action (or

combination of actions) approved by the state (see Section 6.4.4.1 for estimates of corrective action plan

costs). 

EPA assumed that corrective actions fall into four categories: fixing the deficiency that may lead

to contamination; eliminating the contamination from the source; obtaining an alternative source of water;

or providing disinfection treatment that achieves 4-log treatment of viruses (using inactivation, removal,

or State-approved combination of these technologies) before or at the first customer.
7

 EPA estimated the cost of adding Anodic oxidation in the Technology and Cost Document for the Final

Ground Water Rule (USEPA, 2006d) as a representative technology for mixed oxidants.

Economic Analysis for the October 2006

Final Ground Water Rule 6-37

EPA considered four nontreatment alternatives in the cost estimate for eliminating contamination

identified during source water monitoring:

• Rehabilitate an existing well

• Drill a new well

• Purchase water

• Eliminate contamination source

For systems that employ nontreatment corrective actions, the GWR model assumes interim

disinfection will be installed until the nontreatment corrective action is completed and the cost model

includes the interim disinfection costs for this scenario. While interim disinfection would also apply to

systems installing disinfection as a permanent strategy prior to completion of the permanent strategy,

EPA assumes that the additional costs of interim disinfection for the systems projected to install

permanent disinfection as their corrective actions are insignificant because the long-term disinfection is

assumed in the model to occur immediately after the corrective action is required. Costs for setting up a

temporary chlorine disinfection process depend on the duration of interim disinfection, which is

determined by the nontreatment corrective action chosen. Based on best professional judgement, EPA

estimates that interim disinfection will be performed for a duration of one year for systems rehabilitating

an existing well, for two years for systems either drilling a new well or purchasing water, and for six

months for systems eliminating the source of contamination.

For systems that employ treatment as a corrective action, the Agency developed costs for the

following six disinfection technologies:

• Hypochlorination (with and without additional storage)

• Chlorine gas (with and without additional storage)

• Chlorine dioxide (with and without additional storage)

• Anodic oxidants7

 (with and without additional storage)

• Ozone

• Nanofiltration

To estimate the corrective action chosen by each system, the cost model uses a five-step

compliance forecast. Systems may incur costs that differ from these if the State specifies an alternative

treatment technology (e.g., ultraviolet light). Each step is explained below, and summarized in Exhibits

6.21a and 6.21b.
Economic Analysis for the October 2006

Final Ground Water Rule 6-38

Step 1—Current Treatment Practices: The first step divides entry points requiring corrective

action for source water contamination into those that already have some treatment in place (i.e., <4-log)

and those without treatment. EPA assumes that the ratio of correcting entry points that have disinfection

treatment in place to nondisinfecting entry points performing a corrective action is identical to the ratio of

entry points that disinfect but do not achieve 4-log treatment of viruses (using inactivation, removal, or

State-approved combination of these technologies) before or at the first customer to nondisinfecting entry

points, by system type and size category. Entry points that have some disinfection treatment but do not

achieve 4-log are estimated to choose their corrective action based on the distribution in step five.

Step 2—Current Implementation of Treatment Types: For entry points which do not currently

apply disinfection, EPA assumes that the percentage of entry points that will choose disinfection as a

corrective action for source water contamination is based on a range. The high end of the range is based

on the percentage of CWS entry points currently employing disinfection by system size using information

from the Community Water Systems Survey (CWSS) (USEPA, 1997a). The low end of the range is

assumed to be 10% based on discussions with State representatives, who indicated that the use of the

CWSS data would overestimate the percentage of entry points using disinfection in response to

fecally-contaminated source water. The remaining percentage of non-disinfecting entry points are

predicted to employ nontreatment corrective actions in response to fecal contamination of the source

water. Because of the uncertainty inherent in projecting the number of entry points that would employ

each nontreatment corrective action, EPA assigns equal proportions of the nontreatment corrective actions

into the high- and low-cost scenarios for significant deficiencies.

Step 3—Distribution of Nontreatment Corrective Actions: Each non-disinfecting entry point that

is predicted to require a nontreatment corrective action (from step two), having been assigned to either the

high- or the low-cost scenario, is then assigned a corrective action according to the corresponding

percentages in that distribution, as shown in Exhibit 6.21b.

Step 4 - Distribution of Treatment Corrective Actions: The compliance forecast assigns each nondisinfecting entry point predicted to require a treatment corrective action (from step two) to one of the ten

possible treatment scenarios based on the percentage of CWSs currently engaged in those treatment

practices, which are estimated with the CWSS results (USEPA 1997a).

Step 5 - Distribution of Corrective Actions for Disinfecting Entry Points: Finally, for those entry 

points with disinfection that do not achieve 4-log treatment of viruses (using inactivation, removal, or

State-approved combination of these technologies) before or at the first customer, the compliance forecast

assigns them a corrective action (i.e., add storage or increase disinfectant dose). EPA bases this

probability distribution on AWWA survey data (AWWA, 1998).
Economic Analysis for the October 2006

Final Ground Water Rule 6-39

Water System Entry Points (EP’s) 

Taking Corrective Action Due to 

Source Water Contamination

617 EP

Nondisinfecting

42.9%*617EP=265EP

Nontreatment

Action

58.2%*265EP=154EP

High cost 

distribution

Low cost 

distribution

Rehabilitate an

existing well

35.0%*154EP

=53EP

Drill a new well

25.0%*154EP

=39EP

Purchase water

15.0%*154EP

=23EP

Eliminate 

contamination 

source

25.0%*154EP

=39EP 

Rehabilitate an

existing well

50.0%*154EP

=77EP

Drill a 

new well

15.0%*154EP

=23EP

Purchase

Water

5.0%*154EP

=8EP

Eliminate 

contamination

Source

30.0%*154EP

=46EP

Step #1

Step #2

Step #3

Hypochlorination

27.5%*111EP=30EP

plus storage

21.6%*111EP=24EP

Treatment

Action

41.8%*265EP

=111EP

Disinfecting 

less than 4 log

57.1%*617EP=

352EP

Step #4

Step #5

Sources:SDWIS

CWSS

AWWA

Chlorine gas

27.5%*111EP=30EP

plus storage

21.6%*111EP=24EP

Chlorine dioxide

0%*111EP=0EP

plus storage

0%*111EP=0EP

Anodic oxidants

0.6%111EP=1EP

plus storage

0.5%*111EP=1EP

Ozone

0%*111EP

=0EP

Nanofiltration

0.6%*111EP

=1EP

Add storage

39.0%*352EP

=137EP

Increase dose

(hypochlorination)

61.0%%*352EP

=215EP

Increase dose

(chlorine gas)

0.0%*352EP

=0EP

Water System Entry Points (EP’s) 

Taking Corrective Action Due to 

Source Water Contamination

617 EP

Nondisinfecting

42.9%*617EP=265EP

Nontreatment

Action

58.2%*265EP=154EP

High cost 

distribution

Low cost 

distribution

Rehabilitate an

existing well

35.0%*154EP

=53EP

Drill a new well

25.0%*154EP

=39EP

Purchase water

15.0%*154EP

=23EP

Eliminate 

contamination 

source

25.0%*154EP

=39EP 

Rehabilitate an

existing well

50.0%*154EP

=77EP

Drill a 

new well

15.0%*154EP

=23EP

Purchase

Water

5.0%*154EP

=8EP

Eliminate 

contamination

Source

30.0%*154EP

=46EP

Step #1

Step #2

Step #3

Hypochlorination

27.5%*111EP=30EP

plus storage

21.6%*111EP=24EP

Treatment

Action

41.8%*265EP

=111EP

Disinfecting 

less than 4 log

57.1%*617EP=

352EP

Step #4

Step #5

Sources:SDWIS

CWSS

AWWA

Chlorine gas

27.5%*111EP=30EP

plus storage

21.6%*111EP=24EP

Chlorine dioxide

0%*111EP=0EP

plus storage

0%*111EP=0EP

Anodic oxidants

0.6%111EP=1EP

plus storage

0.5%*111EP=1EP

Ozone

0%*111EP

=0EP

Nanofiltration

0.6%*111EP

=1EP

Add storage

39.0%*352EP

=137EP

Increase dose

(hypochlorination)

61.0%%*352EP

=215EP

Increase dose

(chlorine gas)

0.0%*352EP

=0EP

Exhibit 6.21a Summary Flow Chart

Estimated Distribution of Source Water Contamination Corrective Actions

(Numbers based on 3,301 - 10,000 population category for CWSs)
Economic Analysis for the October 2006

Final Ground Water Rule 6-40

Step 1: Current Treatment Practice

<100 101-500 501-1,000

1,001-

3,300

3,301-

10,000

10,001-

50,000

50,001-

100,000 >100,000

CWSs

Disinfecting less than 4 log 28.7% 56.4% 59.1% 55.4% 57.1% 83.6% 41.2% 68.9%

Nondisinfecting 71.3% 43.6% 40.9% 44.6% 42.9% 16.4% 58.8% 31.1%

NTNCWSs

Disinfecting less than 4 log 22.0% 22.0% 22.0% 22.0% 22.0% 22.0% 22.0% 22.0%

Nondisinfecting 78.0% 78.0% 78.0% 78.0% 78.0% 78.0% 78.0% 78.0%

TNCWSs

Disinfecting less than 4 log 16.5% 16.5% 16.5% 16.5% 16.5% 16.5% 16.5% 16.5%

Nondisinfecting 83.5% 83.5% 83.5% 83.5% 83.5% 83.5% 83.5% 83.5%

Source: Derived from Exhibit 4.3. Taken as percentages of all entry points not achieving 4-log disinfection.

Step 2: Current Implementation of Treatment Types

<100 101-500 501-1,000

1,001-

3,300

3,301-

10,000

10,001-

50,000

50,001-

100,000 >100,000

Nontreatment action 54.4% - 90% 27.1% - 90% 24.9% - 90% 27.9% - 90% 26.5% - 90% 8.6% - 90% 40.7% - 90% 11.8% - 90%

High cost distribution 36.1% 29.3% 28.7% 29.5% 29.1% 24.7% 32.7% 25.5%

Low cost distribution 36.1% 29.3% 28.7% 29.5% 29.1% 24.7% 32.7% 25.5%

Treatment action 10% - 45.6% 10% - 72.9% 10% - 75.1% 10% - 72.1% 10% - 73.5% 10% - 91.4% 10% - 59.3% 10% - 88.2%

Note: EPA assumes that systems points will make treatment corrective action in proportion to entry points' current disinfection practices.

Source: Derived from Exhibit 4.3.

Step 3: Distribution of Nontreatment Corrective Actions

<100 101-500 501-1,000

1,001-

3,300

3,301-

10,000

10,001-

50,000

50,001-

100,000 >100,000

High Cost Distribution

Rehabilitate an existing well 46.3% 33.3% 33.3% 33.3% 35.0% 46.2% 50.0% 50.0%

Drill a new well 27.8% 40.0% 25.0% 25.0% 25.0% 30.8% 26.2% 37.5%

Purchase water 5.6% 10.0% 12.5% 12.5% 15.0% 0.0% 0.0% 0.0%

Eliminate contamination source 20.4% 16.7% 29.2% 29.2% 25.0% 23.1% 23.8% 12.5%

Low Cost Distribution

Rehabilitate an existing well 55.6% 50.0% 50.0% 50.0% 50.0% 61.5% 59.5% 62.5%

Drill a new well 18.5% 20.0% 12.5% 12.5% 15.0% 15.4% 19.0% 25.0%

Purchase water 1.9% 3.3% 4.2% 4.2% 5.0% 0.0% 0.0% 0.0%

Eliminate contamination source 24.1% 26.7% 33.3% 33.3% 30.0% 23.1% 21.4% 12.5%

Note: Percentage of those entry points performing nontreatment corrective action.

Corrective Action

System Size (Population Served)

System Size (Population Served)

System Type/

Disinfection Practice

Category of

Corrective Action

System Size (Population Served)

Exhibit 6.21b Estimated Distribution of Source Water Contamination Corrective

Actions (continued on next page)
Economic Analysis for the October 2006

Final Ground Water Rule 6-41

Step 4: Distribution of Treatment Corrective Actions

<100 101-500 501-1,000

1,001-

3,300

3,301-

10,000

10,001-

50,000

50,001-

100,000 >100,000

Hypochlorination 55.1% 54.8% 56.0% 55.3% 27.5% 0.0% 0.0% 0.0%

Hypochlorination plus storage 43.3% 43.0% 44.0% 43.4% 21.6% 0.0% 0.0% 0.0%

Chlorine gas 0.0% 0.0% 0.0% 0.0% 27.5% 53.8% 54.1% 55.7%

Chlorine gas plus storage 0.0% 0.0% 0.0% 0.0% 21.6% 42.3% 42.5% 43.7%

Chlorine dioxide 0.7% 0.6% 0.0% 0.0% 0.0% 0.3% 1.7% 0.0%

Chlorine dioxide plus storage 0.6% 0.4% 0.0% 0.0% 0.0% 0.3% 1.4% 0.0%

Anodic oxidants 0.2% 0.3% 0.0% 0.4% 0.6% 1.5% 0.0% 0.0%

Anodic oxidants plus storage 0.1% 0.2% 0.0% 0.3% 0.5% 1.2% 0.0% 0.0%

Ozone 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% 0.6%

Nanofiltration 0.0% 0.7% 0.0% 0.6% 0.6% 0.6% 0.3% 0.0%

Step 5: Distribution of Corrective Actions for Disinfecting Entry Points

<100 101-500 501-1,000

1,001-

3,300

3,301-

10,000

10,001-

50,000

50,001-

100,000 >100,000

Add storage 39% 39% 39% 39% 39% 39% 39% 39%

Increase dose - hypochlorination 61% 61% 61% 61% 61% 0% 0% 0%

Increase dose - chlorine gas 0% 0% 0% 0% 0% 61% 61% 61%

Note: EPA assumes that systems add storage or increase dose based on AWWA study.

Corrective Action

System Size (Population Served)

Corrective Action

System Size (Population Served)

Note: EPA assumes that systems will choose treatment in proportion to current treatment practices. Estimates for hypochlorination and chlorine gas based on 

remainder of entry points not performing other treatment practices.

Source: CWSS, Table 1-23 (1997) data. Nanofiltration substituted for all membranes based on professional engineering judgement.

Exhibit 6.21b Estimated Distribution of Source Water Contamination Corrective

Actions (continued)

Unit Cost Estimates

Unit cost estimates for the four nontreatment corrective actions and interim disinfection as

described above are presented in Exhibit 6.22a. Unit costs for installing and operating each of the six

treatment scenarios (and variations) in the compliance forecast are presented in Exhibit 6.22b. For each

corrective action, costs generally increase corresponding to system size. However, some corrective

actions are assumed to be constant (on average) over the range of system sizes (e.g., costs for actions such

as rehabilitating a well or drilling a new well are heavily influenced by factors such as hydrogeologic

setting and well depth that are independent of system size). For further description of the assumptions

and methodologies used to develop all corrective action unit costs see the Technology and Cost Document

for the Final Ground Water Rule (USEPA, 2006d).
Economic Analysis for the October 2006

Final Ground Water Rule 6-42

Size Category (Population Served)

<100 101-500

501-

1,000

1,001-

3,300

3,301-

10,000

10,001-

50,000

50,001-

100,000

100,001-

1 Million >1 Million

$11,986 $11,986 $11,986 $11,986 $11,986 $11,986 $11,986 $11,986 $11,986

$30,172 $30,172 $30,172 $30,172 $30,172 $30,172 $30,172 $30,172 $30,172

$173,180 $173,180 $198,599 $198,599 $242,618 $242,618 $353,697 $390,999 $390,999

$1.12 $1.18 $0.63 $1.44 $2.09 $1.35 $1.39 $0.91 $0.91

$16,533 $16,533 $16,533 $16,533 $16,533 $16,533 $16,533 $16,533 $16,533

$1,874 $1,874 $1,874 $1,874 $1,874 $1,874 $1,971 $2,302 $20,774

$2,636 $2,887 $3,356 $3,936 $4,259 $5,210 $7,579 $19,177 $135,513

$1,874 $1,874 $1,874 $1,874 $1,874 $1,874 $1,971 $2,302 $20,774

$5,272 $5,774 $6,712 $7,871 $8,517 $10,420 $15,158 $38,354 $271,026

$1,874 $1,874 $1,874 $1,874 $1,874 $1,874 $1,971 $2,302 $20,774

$5,272 $5,774 $6,712 $7,871 $8,517 $10,420 $15,158 $38,354 $271,026

$1,874 $1,874 $1,874 $1,874 $1,874 $1,874 $1,971 $2,302 $20,774

$1,318 $1,444 $1,678 $1,968 $2,129 $2,605 $3,790 $9,589 $67,757

Source: Technology and Cost Document for the Final Ground Water Rule (USEPA, 2005d)

Note: Based on best professional judgement, EPA estimates that interim disinfection will be performed for a duration of one year for 

systems rehabilitating an existing well, for two years for systems either drilling a new well or purchasing water, and for six months for 

systems eliminating the source of contamination.

Eliminate Source of 

Contamination

Capital

O&M ($ per kgal)

Interim Disinfection

Drill a New Well

Capital

Capital

Total O&M

Rehabilitate an

Existing Well

Capital

Total O&M

Capital

Corrective Action

Rehabilitate an

Existing Well

Drill a New Well

Purchase Water

Nontreatment Corrective Actions

Total O&M

Total O&M

Eliminate Source of 

Contamination

Purchase Water

Exhibit 6.22a Estimated Unit Costs of Nontreatment Corrective Actions

for Source Water Contamination
Economic Analysis for the October 2006

Final Ground Water Rule 6-43

System Size (Population Served)

<100 101-500

501-

1,000

1,001-

3,300

3,301-

10,000

10,001-

50,000

50,001-

100,000

100,001-

1 Million > 1 Million

Chlorine gas feed

capital cost $ 29,868 29,868 $ 29,868 $ 29,868 $ 29,868 $ 58,781 $ 65,006 $ 96,958 $ 337,511 $ 

Chlorine gas feed

annual O&M cost $ 6,227 6,192 $ 6,307 $ 6,456 $ 6,857 $ 16,951 $ 18,197 $ 21,854 $ 61,772 $ 

Chlorine gas feed & storage

capital cost $ 33,354 31,216 $ 37,960 $ 46,039 $ 66,058 $ 152,883 $ 266,275 $ 541,906 $ 2,192,279 $ 

Chlorine gas feed & storage

annual O&M cost $ 6,227 6,192 $ 6,307 $ 6,456 $ 6,857 $ 16,951 $ 18,197 $ 21,854 $ 61,772 $ 

Hypochlorite feed 

capital cost $ 8,970 8,970 $ 15,072 $ 24,402 $ 24,402 $ 72,631 $ 79,658 $ 96,180 $ 187,445 $ 

Hypochlorite

annual O&M cost $ 2,076 1,585 $ 4,180 $ 6,582 $ 7,326 $ 7,558 $ 7,909 $ 19,177 $ 135,513 $ 

Hypochlorite feed & storage 

capital cost $ 12,456 10,318 $ 23,164 $ 40,573 $ 60,593 $ 166,733 $ 280,927 $ 541,128 $ 2,042,213 $ 

Hypochlorite & storage

annual O&M cost $ 2,076 1,585 $ 4,180 $ 6,582 $ 7,326 $ 7,558 $ 7,909 $ 19,177 $ 135,513 $ 

Chlorine Dioxide System

capital cost N/A N/A 35,011 $ 39,299 $ 42,363 $ 80,836 $ 82,091 $ 202,017 $ 371,828 $ 

Chlorine Dioxide

annual O&M cost N/A N/A 15,261 $ 16,897 $ 17,901 $ 19,878 $ 21,705 $ 25,983 $ 59,412 $ 

Chlorine Dioxide System

& storage capital cost N/A N/A 46,196 $ 61,792 $ 89,439 $ 191,678 $ 307,085 $ - $ - $ 

Chlorine Dioxide

& storage annual O&M cost N/A N/A 16,251 $ 17,720 $ 18,733 $ 20,392 $ 22,257 $ - $ - $ 

Anodic Oxidant

capital cost $ 65,151 47,219 $ 87,450 $ 110,256 $ 151,129 $ 255,055 $ 354,880 $ 745,098 $ 2,188,039 $ 

Anodic Oxidant

annual O&M cost $ 5,471 2,911 $ 7,480 $ 9,791 $ 12,855 $ 17,479 $ 22,181 $ 38,439 $ 179,932 $ 

Anodic Oxidant & storage

capital cost $ 68,637 48,568 $ 95,543 $ 126,427 $ 187,320 $ 349,157 $ 556,149 $ 1,190,046 $ 4,042,807 $ 

Anodic Oxidant & storage

annual O&M cost $ 5,471 2,911 $ 7,480 $ 9,791 $ 12,855 $ 17,479 $ 22,181 $ 38,439 $ 179,932 $ 

Ozonation 

capital cost N/A N/A 347,027 $ 431,809 $ 622,023 $ 903,927 $ 1,175,442 $ 1,991,127 $ 6,518,099 $ 

Ozonation 

annual O&M cost N/A N/A 55,668 $ 59,028 $ 60,789 $ 63,718 $ 67,004 $ 87,225 $ 253,317 $ 

Nanofiltration 

capital cost $ 104,856 62,691 $ 182,768 $ 304,122 $ 573,460 $ 1,086,398 $ 1,872,457 $ 5,140,179 $ 29,028,479 $ 

Nanofiltration 

annual O&M cost $ 10,253 7,520 $ 20,140 $ 37,037 $ 63,670 $ 133,397 $ 194,361 $ 541,543 $ 3,873,384 $ 

Add storage

capital cost $ 3,486 1,349 $ 8,093 $ 16,171 $ 36,191 $ 94,102 $ 201,269 $ 444,947 $ 1,854,768 $ 

Increase dose - hypochlorination

annual O&M cost $ 179 72 $ 179 $ 195 $ 470 $ NA NA NA NA

Increase dose - chlorine gas

annual O&M cost NA NA NA NA NA 1,342 $ 2,108 $ 3,846 $ 17,838 $ 

Source: Technology and Cost Document for the Final Ground Water Rule (USEPA, 2005d)

Corrective Action

Systems Adding Treatment

Systems upgrading from less than 4-log to 4-log or greater

Exhibit 6.22b Estimated Unit Costs of Treatment Corrective Actions for Source

 Water Contamination
Economic Analysis for the October 2006

Final Ground Water Rule 6-44

Mean

Lower 

Bound

(5th %ile)

Upper 

Bound

(95th 

%ile) Mean

Lower 

Bound

(5th %ile)

Upper 

Bound

(95th 

%ile) Mean

Lower 

Bound

(5th %ile)

Upper 

Bound

(95th 

%ile)

3% $25.64 $14.90 $38.39 $0.46 $0.32 $0.61 $26.10 $15.22 $39.00

7% $27.20 $15.89 $40.96 $0.52 $0.36 $0.69 $27.72 $16.26 $41.65

Notes: Detail may not add to totals due to independent rounding and independent cost model runs.

Source: Cost Model Outputs

Systems States Total

Annualized Costs for Triggered Monitoring Corrective Action Activities

Annualized cost estimates for systems and States to perform source water contamination

corrective actions are presented in Exhibit 6.23.

Exhibit 6.23 PWS and State Cost Estimates for Triggered Monitoring Corrective

Action Activities ($Millions, 2003$)

6.4.5 Compliance Monitoring

PWSs that provide 4-log treatment of viruses (using inactivation, removal, or State-approved

combination of these technologies) before or at the first customer to meet requirements of the GWR must

monitor the effectiveness and reliability of their treatment. This section presents the assumptions used to

estimate the burden and costs attributable to compliance monitoring. Exhibit 6.24 provides a schematic

of the compliance monitoring process.
Economic Analysis for the October 2006

Final Ground Water Rule 6-45

Does the system provide 4-log treatment of 

viruses?

Total number of systems in size category 

(2,884 systems = (approx.) 9,281 EP)

See section 6.4.3 

on Source Water 

Monitoring

Did the system provide 4-

log treatment of viruses 

prior to the GWR?

Yes No

System must continue 

to perform monitoring 

and notify State of 

level of treatment 

provided

Yes

No

4,164 EP = EP achieving 

4-log prior to GWR+ EP 

corrected to 4-log

3,547 EP

617 EP = EP corrected to 4-log 

(previously partially disinfected, 

353 EP) + (previously 

nondisinfected, 264 EP)

No additional costs 

of compliance 

monitoring

No additional costs 

of compliance 

monitoring

With additional 

costs of 

compliance 

monitoring

353 EP 264 EP

Exhibit 6.24 Schematic of Compliance Monitoring Process

(Numbers based on 3,301 - 10,000 population category for CWSs)
Economic Analysis for the October 2006

Final Ground Water Rule 6-46

PWSs

Different cost assumptions were needed for systems engaged in compliance monitoring of

disinfection treatment in place prior to promulgation of the GWR versus systems having technology

installed as a result of corrective action required by the GWR. The numbers of entry points subject to

each situation are presented in Exhibit 6.25.

Systems Disinfecting Prior to GWR: EPA assumed that systems already employing chemical

disinfection treatment for purposes other than compliance with the GWR, or prior to the Rule’s

promulgation, would already have the monitoring program and monitoring equipment in place to monitor

the disinfection. These systems include systems currently disinfecting to 4-log as well as systems

currently disinfecting to less than 4-log. Therefore, systems which are already disinfecting would incur

no costs for adding disinfection monitoring equipment. EPA bases this assumption on the language

obtained from the pre-existing State disinfection requirements. Most States specify in the State

regulations that systems which disinfect must maintain the prescribed level of disinfection in no less than

5% of monthly samples (suggests at least 20 samples per month), or the system’s disinfectant level may

not be below the prescribed disinfectant level for more than four hours. Furthermore, some States specify

that disinfecting systems must monitor the disinfection at a specified frequency, such as daily or

continuously. This type of language suggests monitoring at a frequency consistent with that specified in

the GWR, resulting in no monitoring equipment purchases for these systems.

For systems using nanofiltration technology, the monitoring capability is built into the

technology’s core process. Therefore, EPA assumes that systems using nanofiltration technology prior to

implementation of the GWR will incur no treatment monitoring costs to comply with the Rule by using

nanofiltration.

Before beginning compliance monitoring, however, systems must inform the State that they

achieve 4-log treatment of viruses (using inactivation, removal, or State-approved combination of these

technologies) before or at the first customer. For costing purposes, EPA assumes that preparing and

submitting notification for the State requires 0.5 hours. Systems must also notify the State each time the

treatment technology used fails to maintain 4-log treatment for more than 4 hours (see Chapter 3 for more

detail on requirements for each treatment technology). For costing purposes, EPA assumes a disinfection

failure rate of 5 percent of entry points engaged in 4-log source water virus treatment. EPA assumes that

preparing and submitting a treatment failure report to the State requires 2.5 hours. EPA has developed

and systems will have access to automated forms that will minimize the burden to systems in complying

with these reporting requirements. Exhibit 6.26 presents the unit burdens and costs for these reporting

requirements.
Economic Analysis for the October 2006

Final Ground Water Rule 6-47

A B=C+D+E C D E

Community Water Systems (CWSs) 

<100 3,998 5,246 3,996 358 891 

101-500 6,440 10,499 8,873 917 709 

501-1,000 2,127 4,155 3,547 360 248 

1,001-3,300 2,509 6,090 5,378 396 317 

3,301-10K 1,294 4,164 3,547 353 264 

10,001-50K 803 4,511 3,856 548 107 

50,001-100K 72 810 583 93 133 

100,001-1 Million 55 681 545 94 42 

> 1 Million 3 34 34 - - 

Totals 17,300 36,189 30,359 3,118 2,712 

Nontransient Noncommunity Water Systems (NTNCWSs)

<100 1,537 1,537 850 150 537 

101-500 1,141 1,141 608 119 415 

501-1,000 320 320 170 33 117 

1,001-3,300 150 150 64 19 67 

3,301-10K 17 17 7 2 8 

10,001-50K 2 2 1 0 1 

50,001-100K 0 0 0 0 0 

100,001-1 Million 0 0 0 0 0 

> 1 Million - - - - - 

Totals 3,167 3,167 1,700 323 1,144 

Transient Noncommunity Water Systems (TNCWSs)

<100 8,075 8,075 1,160 1,143 5,772 

101-500 2,368 2,368 342 337 1,689 

501-1,000 243 243 35 35 174 

1,001-3,300 86 86 11 12 63 

3,301-10K 13 13 1 2 10 

10,001-50K 4 4 0 1 3 

50,001-100K 0 0 0 0 0 

100,001-1 Million 0 0 0 0 0 

> 1 Million - - - - - 

Totals 10,790 10,790 1,549 1,530 7,711 

Grand Total 31,257 50,146 33,608 4,971 11,567 

Notes: Detail may not add to totals due to independent rounding.

Source: (C) Number of entry points from Exhibit 4.3.

(D) Exhibit 6.5b, Column E

(E) Exhibit 6.5b, Column, F

System Size

(Population

Served)

Entry Points

Corrected 

to 4-log; 

previously

nondisinfected

Systems

Subject to

Compliance

Monitoring

Entry Points

Corrected 

to 4-log; 

partially

disinfected

Entry Points

Achieving 

4-log Prior

to GWR

Entry Points 

Subject to 

Compliance 

Monitoring

Exhibit 6.25 Assumptions for Entry Points Subject to Compliance Monitoring
8

 Systems may choose to install monitoring systems that are more complicated and costly (i.e., SCADA

systems) than those presented here. However, this level of monitoring is not required under the rule and therefore is

not included as part of the cost analysis.

Economic Analysis for the October 2006

Final Ground Water Rule 6-48

Systems Treating As a Corrective Action: Systems that adopt treatment as a corrective action for

source water fecal contamination must also install monitoring equipment to perform compliance

monitoring. The unit capital and O&M costs8

 are presented in Exhibit 6.27a (for systems serving 3,300

and fewer people) and Exhibit 6.27b (for systems serving more than 3,300 people). These system size

categories are costed differently due to different compliance monitoring requirements (see Chapter 1 for a

full description of compliance monitoring requirements). 

EPA assumes that all systems serving 3,300 or fewer people will conduct daily grab samples for

chlorine residual measurement and incur 0.5 hours labor burden per day. Because nanofiltration

technologies have monitoring capability incorporated into their core processes, systems that adopt these

treatment techniques are assumed to incur no capital or O&M costs for compliance monitoring.

As noted above, systems must also notify the State each time the treatment technology used fails

to maintain 4-log treatment of virus for more than 4 hours. EPA assumes that preparing and submitting a

treatment failure report to the State requires 2.5 hours. This cost is the same as reported for systems

disinfecting prior to the GWR as listed in Exhibit 6.26.
Economic Analysis for the October 2006

Final Ground Water Rule 6-49

Notification

Preparation

(hours)

Labor Cost

(per hour)

Unit

Report

Cost

Report

Preparation

(hours)

Labor Cost

(per hour)

Unit

Report

Cost

A B C=A*B D E F=D*E

Community Water Systems (CWSs) 

<100 0.5 21.44 $ 10.72 $ 2.5 21.44 $ 53.60 $ 

101-500 0.5 23.09 $ 11.55 $ 2.5 23.09 $ 57.73 $ 

501-1,000 0.5 24.74 $ 12.37 $ 2.5 24.74 $ 61.85 $ 

1,001-3,300 0.5 24.74 $ 12.37 $ 2.5 24.74 $ 61.85 $ 

3,301-10K 0.5 30.51 $ 15.26 $ 2.5 30.51 $ 76.28 $ 

10,001-50K 0.5 31.08 $ 15.54 $ 2.5 31.08 $ 77.70 $ 

50,001-100K 0.5 31.08 $ 15.54 $ 2.5 31.08 $ 77.70 $ 

100,001-1 Million 0.5 35.25 $ 17.62 $ 2.5 35.25 $ 88.12 $ 

0.5 35.25 $ 17.62 $ 2.5 35.25 $ 88.12 $ 

Nontransient Noncommunity Water Systems (NTNCWSs)

<100 0.5 21.44 $ 10.72 $ 2.5 21.44 $ 53.60 $ 

101-500 0.5 23.09 $ 11.55 $ 2.5 23.09 $ 57.73 $ 

501-1,000 0.5 24.74 $ 12.37 $ 2.5 24.74 $ 61.85 $ 

1,001-3,300 0.5 24.74 $ 12.37 $ 2.5 24.74 $ 61.85 $ 

3,301-10K 0.5 30.51 $ 15.26 $ 2.5 30.51 $ 76.28 $ 

10,001-50K 0.5 31.08 $ 15.54 $ 2.5 31.08 $ 77.70 $ 

50,001-100K 0.5 31.08 $ 15.54 $ 2.5 31.08 $ 77.70 $ 

100,001-1 Million 0.5 35.25 $ 17.62 $ 2.5 35.25 $ 88.12 $ 

NA 35.25 $ NA NA 35.25 $ NA

Transient Noncommunity Water Systems (TNCWSs)

<100 0.5 21.44 $ 10.72 $ 2.5 21.44 $ 53.60 $ 

101-500 0.5 23.09 $ 11.55 $ 2.5 23.09 $ 57.73 $ 

501-1,000 0.5 24.74 $ 12.37 $ 2.5 24.74 $ 61.85 $ 

1,001-3,300 0.5 24.74 $ 12.37 $ 2.5 24.74 $ 61.85 $ 

3,301-10K 0.5 30.51 $ 15.26 $ 2.5 30.51 $ 76.28 $ 

10,001-50K 0.5 31.08 $ 15.54 $ 2.5 31.08 $ 77.70 $ 

50,001-100K 0.5 31.08 $ 15.54 $ 2.5 31.08 $ 77.70 $ 

100,001-1 Million 0.5 35.25 $ 17.62 $ 2.5 35.25 $ 88.12 $ 

NA 35.25 $ NA NA 35.25 $ NA

Notes: Detail may not add to totals due to independent rounding.

NA Not applicable (no NCWSs of this size category).

Sources: (A, D) Labor hours for initial notification and treatment failure report reflect EPA estimate.

(B, E) Labor rate from Exhibit 6.1.

Treatment Failure Report for All Systems 

Treating

Initial State Notification for Systems Treating 

Prior to GWR

> 1 Million

> 1 Million

> 1 Million

System Size

(Population Served)

Exhibit 6.26 PWS Unit Costs for Compliance Monitoring for Initial State

Notification and Disinfection Failure Reports
Economic Analysis for the October 2006

Final Ground Water Rule 6-50

Unit 

Cost

(1998)

PPI

(1998)

PPI

(2003)

Unit

Cost

(2003)

Labor 

burden

(per day)

Annual

Cost

Frequency

Annual

Labor

Burden

Annual

Total

Cost

A B C D=A*(C/B) E F G=E*F H=D*E*F

Compliance Monitoring Labor

25-100 N/A N/A N/A 21.44 $ 0.50 365 183 3,913 $ 

101-500 N/A N/A N/A 23.09 $ 0.50 365 183 4,214 $ 

500-3.3k N/A N/A N/A 24.74 $ 0.50 365 183 4,515 $ 

Chlorine Test Kits

25-100 34.00 $ 143.7 150.1 35.50 $ N/A 3.65 N/A 130 $ 

101-500 34.00 $ 143.7 150.1 35.50 $ N/A 3.65 N/A 130 $ 

500-3.3k 34.00 $ 143.7 150.1 35.50 $ N/A 3.65 N/A 130 $ 

Totals

25-100 183 4,042 $ 

101-500 183 4,344 $ 

500-3.3k 183 4,645 $ 

Notes: Detail may not add to totals due to independent rounding.

Sources: (A) Unit cost for test kit from Products for Analysis, 1998 Hach Co. Model 2231-02. Unit cost derivation for system operator 

in section 6.2.1.

(B & C) Producer Price Index (PPI) Commodity Code 3500 (Finished goods less food and energy) from BLS (www.bls.gov).

(D) Labor rate from section 6.2.1.

(E) Labor hours for compliance monitoring reflect EPA estimate.

(F) Monitoring performed daily. New test kit needed every 100 days.

Component

Exhibit 6.27a PWS Compliance Monitoring Unit Costs for Systems 

Serving 3,300 or Fewer People
Economic Analysis for the October 2006

Final Ground Water Rule 6-51

Unit

Cost

(1998)

PPI

(1998)

PPI

(2003)

Unit

Cost

(2003)

Quantity

Purchased

Total

Cost

A B C D=A*(C/B) E F=D*E

Capital Costs

 Chlorine analyzer (Hach CL17) 2,375 $ 121.0 114.7 2,251 $ 1 2,251 $ 

 Power cord 10 $ 121.0 114.7 9 $ 1 9 $ 

 Chart recorder (Honeywell 10" round) 665 $ 121.0 114.7 630 $ 1 630 $ 

 Installation labor (System Operator)

3.3k-10k N/A N/A N/A 25.34 $ 8 203 $ 

10k-100k N/A N/A N/A 26.05 $ 8 208 $ 

>100k N/A N/A N/A 31.26 $ 8 250 $ 

Total Capital Cost

3.3k-10k $ 3,094

10k-100k $ 3,100

>100k $ 3,141

Annual Operation and Maintenance

 Compliance monitoring

3.3k-10k N/A N/A N/A 25.34 $ 80 2,027 $ 

10k-100k N/A N/A N/A 26.05 $ 80 2,084 $ 

>100k N/A N/A N/A 31.26 $ 80 2,501 $ 

 Maintenance kit 140 $ 143.7 150.5 147 $ 1 147 $ 

 Monthly reagents 18 $ 143.7 150.5 19 $ 12 226 $ 

 Charts 15 $ 143.7 150.5 16 $ 1 16 $ 

 Recorder pens 52 $ 143.7 150.5 54 $ 1 54 $ 

Total Annual Operation and Maintenance Costs

3.3k-10k $ 2,470

10k-100k $ 2,527

>100k $ 2,944

Notes: Detail may not add to totals due to indpendent rounding.

Sources: (A) Unit costs for equipment (both capital and O&M) from Products for Analysis, 1998 Hach Co. 

(D) Labor rate from Exhibit 6.1.

(E) 80 hours per year for O&M compliance monitoring.

(B & C) Producer Price Index Commodity Code 117 (Electrical machinery and equipment) for Capital Costs and Commodity Code 

3500 (Finished goods less food and energy) for Annual O & M, BLS (www.bls.gov). December values. 

Component

Exhibit 6.27b PWS Compliance Monitoring Capital Unit and O&M Costs

for Systems Serving More than 3,300 People
Economic Analysis for the October 2006

Final Ground Water Rule 6-52

Labor

Hours

Labor

Cost

(per hour)

Unit

Cost

A B C=A*B

Document Initial Notification 0.5 33.60 $ 16.80 $ 

Review Disinfection Failure Report 3.5 33.60 $ 117.61 $ 

Notes: Detail may not add to totals due to independent rounding.

Sources: (A) Labor hours for rule activities reflect EPA estimate.

(B) Labor rate from Exhibit 6.2.

Cost Component

Mean

Lower 

Bound

(5th %ile)

Upper 

Bound

(95th 

%ile) Mean

Lower 

Bound

(5th %ile)

Upper 

Bound

(95th 

%ile) Mean

Lower 

Bound

(5th %ile)

Upper 

Bound

(95th 

%ile)

3% $9.35 $3.02 $16.97 $0.00 $0.00 $0.01 $9.36 $3.02 $16.98

7% $8.32 $2.65 $15.17 $0.00 $0.00 $0.01 $8.32 $2.65 $15.18

Notes: Detail may not add to totals due to independent rounding and independent cost model runs.

Source: Cost Model Outputs

Systems States Total

Annualized Costs for Compliance Monitoring Activities

States

States incur costs to document the initial notification from systems that achieve 4-log treatment of

viruses (using inactivation, removal, or State-approved combination of these technologies) before or at

the first customer, as well as to review the systems’ disinfection failure reports, presented in Exhibit 6.28. 

For costing purposes, EPA assumes that documenting the PWSs’ notifications requires 0.5 hours and that

reviewing disinfection failure reports requires 3.5 hours. The burden estimate for States to review a

disinfection failure reports is greater than the burden estimated for systems to prepare and submit the

report because it is anticipated that the State will have less familiarity with any particular system and will

be required to look up additional historical information to make any assessments/determinations regarding

the report. EPA has developed and States will have access to automated forms that will minimize the

burden to systems in complying with this reporting requirement.

Exhibit 6.28 State Unit Costs for Compliance Monitoring

Annualized costs for systems and States to perform compliance monitoring is presented in

Exhibit 6.29.

Exhibit 6.29 PWS and State Cost Estimates for Compliance Monitoring Activities

($Millions, 2003$)
Economic Analysis for the October 2006

Final Ground Water Rule 6-53

PWSs Serving <10,000 PWSs Serving > 10,000 Total

Lower

(5th %ile)

Upper

(95th %ile)

Lower

(5th %ile)

Upper

(95th %ile)

Lower

(5th %ile)

Upper

(95th %ile)

$ 29 79 $ 158 $ 62 $ 24 $ 117 $ 141 $ 53 $ 275 $ 

$ 12 31 $ 60 $ 0 $ 0 $ 1 $ 31 $ 12 $ 61 $ 

$ 64 173 $ 339 $ 1 $ 0 $ 2 $ 174 $ 64 $ 341 $ 

$ 105 283 $ 556 $ 64 $ 24 $ 120 $ 346 $ 129 $ 676 $ 

CWS Implementation Costs 5 $ 5 $ 5 $ 0 $ 0 $ 0 $ 5 $ 5 $ 5 $ 

NTNCWS Implementation Costs 2 $ 2 $ 2 $ 0 $ 0 $ 0 $ 2 $ 2 $ 2 $ 

TNCWS Implementation Costs 9 $ 9 $ 9 $ 0 $ 0 $ 0 $ 9 $ 9 $ 9 $ 

Total One-Time PWS Costs $ 16 16 $ 16 $ 0 $ 0 $ 0 $ 17 $ 17 $ 17 $ 

State Start-Up Cost $ 13 13 $ 13 $ 

Total State One-Time Costs $ 13 13 $ 13 $ 

Notes: Detail may not add to totals due to independent rounding.

The mean and confidence bounds are equal for both systems and state implementation costs because EPA derived these costs from point estimates.

Source: Appendix D, Exhibits D.1, D.2, and D.3.

90 Percent

Confidence Bound

Mean

Value

90 Percent

Confidence Bound

Mean

Value

Total Initial PWS Capital Costs

Mean

Value

90 Percent

Confidence Bound

CWS Total Initial Capital

NTNCWS Total Initial Capital

TNCWS Total Initial Capital

6.4.6 Total Capital and One-Time Costs

Exhibit 6.30 presents total capital and one-time costs of the GWR. Note, the bulk of capital costs

are incurred by transient noncommunity water systems (TNCWSs) serving 10,000 or fewer people. Onetime costs for PWSs and States are limited to rule implementation.

Exhibit 6.30 Total Initial Capital and One-Time Costs

($Millions, 2003$)

6.4.7 Uncertainty in Unit Costs

As stated in section 6.2.6, EPA recognizes that there are both variability and uncertainty in unit

cost estimates for treatment. Variability is expected in the actual costs that will be experienced by

different water systems with similar flows installing the same treatment technology. Otherwise similar

systems may experience different capital and/or O&M costs due to site-specific factors. Inputs to unit

costs such as water quality conditions, labor rates, and land costs can be highly variable and increase the

system-to-system variability in unit costs. In developing the unit cost estimates, there is insufficient

information to fully characterize what the distribution of this variability will be on a national scale for all

of the treatments and all possible conditions.

The unit costs for this EA are developed as average or representative estimates of what these unit

costs will be nationally. That is, in developing unit costs, design criteria for the technologies were

selected to represent typical, or average, conditions for the universe of systems. As a result, there is

uncertainty inherent in these unit cost estimates as they are based on independent assumptions with

supporting data and vendor quotes, where available, rather than on a detailed aggregation of State,

regional, or local estimates based on actual field conditions. In this EA, uncertainty in these national
9

 Studies omitted from the alternative occurrence model are those used for the primary analysis (detailed in

Ch. 4 of the EA) that were either not published or not peer reviewed prior to publication: Missouri Alluvial Aquifer 

(Vaughn, 1996), Wisconsin Migrant Worker Camp (USEPA et al., 1998), EPA Vulnerability (USEPA, 1998), 

New England (Doherty et al., 1998), Three-State Study #3: Minnesota (Battigelli, 1999), Three-State Study #1: 

Wisconsin (Battigelli, 1999), and the Montana Study (Miller and Meek, 1996).

Economic Analysis for the October 2006

Final Ground Water Rule 6-54

average unit cost factors for specific technologies is characterized as a triangular distribution with

minimum and maximum values set at the following percentages relative to the best estimate:

• Capital costs: +/- 30 percent

• O&M costs: +/- 15 percent

These percentages were developed by EPA based on input from engineering professionals and

reflect recommendations from the National Drinking Water Advisory Council (NDWAC) (2001) in their

review of the national cost estimation methodology for the Arsenic Rule. EPA believes that the

uncertainties in capital and O&M costs for a given treatment technology are independent of one another

and that uncertainties across all technologies are independent.

The uncertainty in unit costs is reflected in the 90 percent confidence bounds shown in the

national cost summary exhibit in section 6.4.6 and later in this chapter.

6.4.8 Alternative Cost Analysis

The Agency performed an alternative cost analysis by running the cost model using a subset of

the studies that were the basis for the fecal indicator and viral occurrence rates in the primary analysis. 

This subset comprised just those studies which had undergone peer review prior to publication9

 and so

consisted only of peer-reviewed data. This cost model run parallels the alternative benefits model run

described in section 5.5.4. Compared to the primary analysis, this alternative cost model run results in an

increase in the annualized costs by a range of $29.1 million to $29.4 million (an approximately 47%

increase), using 3 percent and 7 percent discount rates, respectively.

6.5 Household Costs

EPA assumes that systems may pass some or all costs of a new regulation on to their consumers

in the form of rate increases. Household costs, which are in units of $ per household per year, are

estimated in this section to provide a measure of the increase in water bills that is expected to result from

the GWR. These cost increases incorporate the costs of rule implementation, sanitary surveys, triggered

monitoring, corrective actions, and compliance monitoring. Exhibit 6.31 presents the mean expected

increases in annual household costs for all CWSs, including those systems that do not have to take

corrective action for significant deficiencies or source water contamination. Exhibit 6.31 also presents the

same information for CWSs that must take corrective action. Household costs tend to decrease as system

size increases, due mainly to the economies of scale for the corrective actions. 
Economic Analysis for the October 2006

Final Ground Water Rule 6-55

Households Mean Median

90th

Percentile

All Community Water Systems (CWSs) 

<100 289,222 16.54 $ 2.81 $ 9.31 $ 

101-500 1,303,890 3.51 $ 0.64 $ 6.11 $ 

501-1,000 1,278,081 0.97 $ 0.16 $ 1.70 $ 

1,001-3,300 4,196,105 0.37 $ 0.04 $ 0.61 $ 

3,301-10K 6,271,380 0.27 $ 0.03 $ 0.43 $ 

10,001-50K 11,468,813 0.21 $ 0.04 $ 0.49 $ 

50,001-100K 4,204,584 0.34 $ 0.10 $ 1.02 $ 

>100,000 9,755,817 0.21 $ 0.04 $ 0.62 $ 

Total 38,767,890 0.51 $ 0.09 $ 0.88 $ 

Corrective Action Community Water Systems (CWSs)

<100 70,563 52.38 $ 18.99 $ 82.21 $ 

101-500 312,484 12.00 $ 4.52 $ 25.76 $ 

501-1,000 302,557 3.23 $ 1.33 $ 6.56 $ 

1,001-3,300 919,133 1.33 $ 0.47 $ 2.59 $ 

3,301-10K 1,487,159 0.80 $ 0.25 $ 2.18 $ 

10,001-50K 2,871,250 0.45 $ 0.18 $ 1.18 $ 

50,001-100K 1,215,544 0.53 $ 0.26 $ 1.36 $ 

>100,000 2,283,144 0.68 $ 0.39 $ 1.65 $ 

Total 9,461,833 1.51 $ 0.60 $ 3.20 $ 

Source: GWR model output.

Systems Size

(Population 

Served)

To calculate household costs, the CWS population subject to each rule requirement is divided by

2.59 people per household (U.S. Bureau of the Census, 2001a) to calculate a number of households

subject to each requirement. The cost of the rule, by size category, is then divided by that number of

households to determine a per-household cost. To annualize capital costs when determining the costs to

households, EPA uses different discount rates for private and public systems and for systems of different

sizes. The rate differences between systems represent the different borrowing sources each type of

system has available to it, differences in risk, and expectations regarding inflation. The rates vary from

5.20 to 6.27 percent depending on system size and ownership, and are summarized in Exhibit 6.4.

As shown in Exhibit 6.31, annual household costs for all CWSs (including both those that do and

those that do not add treatment) range from $0.21 to $16.54, depending on system size. Household costs

for the subset of systems that undertake corrective actions range from $0.45 to $52.38, depending on

system size. EPA estimates that, as a whole, households subject to the GWR face minimal increases in

their annual costs. Approximately 66 percent of the households potentially subject to the rule are

customers of systems serving at least 10,000 people; these systems experience the lowest increases in

costs due to significant economies of scale. Households served by small systems that undertake

corrective actions will face the greatest increases in annual costs. Only CWSs are included in this

analysis because they are the only systems that serve households directly. 

Exhibit 6.31 Summary of Annual Per-Household Costs for the GWR (2003$/Year)
Economic Analysis for the October 2006

Final Ground Water Rule 6-56

6.6 Nonquantified Costs

Although EPA has quantified the significant costs of the GWR, there are some costs that the

Agency did not quantify. Overall, EPA believes that these nonquantified costs are much smaller than the

nonquantified benefits. These nonquantified costs result from uncertainties surrounding rule assumptions

and from modeling assumptions. For example, EPA estimated that some systems may need to acquire

land if they need to build a treatment facility or drill a new well. This was not considered for most

systems because EPA expects that the majority of the technologies that systems will use to comply with

this rule will fit within the existing plant footprint. In addition, if the cost of land is prohibitive, a system

may choose another lower cost alternative such as connecting to another source. EPA has also not

quantified costs for systems already using disinfection to conduct compliance monitoring because EPA

believes such systems are already incurring these costs.

EPA did not include the costs for taking five additional samples following a positive source water

sample. However, EPA overestimated the cost of triggered monitoring because it assumed all systems

would take an additional sample beyond the current TCR requirements. However, many small systems

(and most ground water systems are small) will be able to use one of their TCR samples to also comply

with the GWR. Overall, the impact of not including five additional sample cost (approximately $200,000

per year) is much smaller compared to the overestimate of a few million dollars associated with the initial

fecal indicator sampling cost already conducted for TCR monitoring.

EPA did not include compliance monitoring costs for systems improving disinfection from less

than 4-log to greater than 4-log inactivation because EPA believes that essentially all of these systems are

already measuring their residuals and recording such information on a daily basis as standard operating

procedures. However, there may be some systems that are not doing this, and if so, additional costs

would need to be incurred. 

For some systems, further investigation into problems identified through implementation of GWR

requirements could lead to a determination that the source is more appropriately classified as GWUDI. In

such instances, systems will need to work closely with the State to clarify the source classification. If a

source is reclassified as GWUDI, the system may incur significant additional costs to comply with the

requirements (e.g., filtration) under the various regulations applicable to GWUDI/surface water systems. 

Although a reclassification may be prompted by GWR requirements, the actual costs for complying with

GWUDI requirements fall under the applicable regulations governing GWUDI supplies and are not

included in this EA. 

The optional assessment monitoring provision was not included in the quantitative cost analysis. 

However, EPA was not able to quantify either the benefits or costs of this program.

Due to lack of information, EPA was unable to quantify the costs (as well as benefits) from the

correction of sanitary survey deficiencies in distribution systems and treatment plants. 
Economic Analysis for the October 2006

Final Ground Water Rule 6-57

6.7 Uncertainty Analysis

Many uncertain values are used to derive estimates of costs of this rule. Most, but not all, of

these are mathematically modeled so that a "realization" is selected for them in each "uncertainty

iteration" of this EA. These uncertainties then propagate through the derivation of final estimates so the

total uncertainty of those final estimates can be understood. The paragraphs that follow discuss the most

important of these uncertain quantities. 

The Baseline Numbers of Ground Water Systems, Populations Served, and Associated Disinfection

Practice

The baseline number of systems is uncertain because of data limitations in the Safe Drinking

Water Information System (SDWIS). For example, some systems use both ground and surface water, but

because of other regulatory requirements, they are labeled in SDWIS as surface water systems. In

addition, the SDWIS data on non community water systems do not reflect a consistent reporting

convention for population served. Some States may report the population served by TNCWSs over the

course of a year, while others may report the population served on an average day. For example, a State

park may report the population served yearly instead of daily. Thus, SDWIS data may, in some cases,

overestimate the daily population served. Also, SDWIS does not require States to provide information on

current disinfection practices, resulting in uncertainty in the percentage of disinfecting systems providing

4-log or greater virus treatment. Although these different factors influencing the baseline estimates are

uncertain, EPA believes their relative degree of uncertainty in influencing the estimates within the GWR

EA is small compared to other uncertain components of the EA, so these are not treated probabilistically

in the analysis.

The Baseline Occurrence of Viruses and E. coli in Ground Water Wells

EPA's occurrence analysis is based on monitoring data from over 1,200 public drinking water

supply wells that were tested for culturable viruses, E. coli, or both. Compiled from 15 ground water

surveys that were designed for different purposes, these wells were used to represent the universe of

ground water wells. Although the number of wells is large, the number of assays per well is small, and

most wells were sampled only once for either viruses or E. coli. Because of the limited amount of data,

these data do not provide precise occurrence estimates. EPA's analysis recognizes the limitations of the

data, producing a large "uncertainty sample" of estimates that are consistent with the data. This

uncertainty sample is an input to the probabilistic economic analysis, where these uncertainties are

combined with the uncertainties of other inputs to portray total uncertainty in the GWR cost and benefit

estimates. EPA’s occurrence model includes concentration differences between more and less vulnerable

wells, but applies the same hit rate model to both types of wells. Also, because of data limitations, EPA

was unable to make an assessment of aquifer sensitivity as part of the final rule and, therefore, no

difference in hit rates or concentration levels between sensitive and nonsensitive wells is assumed. 

For the Sanitary Survey Provisions, the Percent of Systems Identified as Having Significant Deficiencies,

the Percent of These Deficiencies That Are Corrected, and Associated Costs and Benefits

For the sanitary survey provisions, EPA estimated the impacts associated with well deficiencies. 

EPA used data from the 1998 ASDWA survey to estimate the percent of wells with deficiencies

(ASDWA, 1997). To estimate benefits, EPA assumed that if a correction of a well defect occurred at a
Economic Analysis for the October 2006

Final Ground Water Rule 6-58

virally contaminated well, some, but not all of these virally contaminated wells would no longer have

viral contamination. EPA used an uncertainty distribution for this estimate.

To estimate costs for significant deficiencies detected at or near the source, EPA chose two

representative corrective actions to use in the cost model: replacement of a sanitary well seal or

rehabilitation of an existing well. Because the corrections of significant deficiencies are dependent upon

the deficiencies defined as significant by States and the conditions of specific systems, both of which are

highly variable, EPA used a high and low scenario to bound the cost estimates. The low-cost scenario

assumes a greater percentage of the systems with significant deficiencies will have deficiencies that are

less expensive to correct (e.g., more systems will have to replace their sanitary well seal than will have to

perform a complete rehabilitation of their well). This high/low bounding provides an estimate of the

uncertainty with respect to the percentages of each type of defect to be corrected.

While the sanitary survey provisions will also result in identification and correction for

deficiencies associated with treatment or distribution system deficiencies, due to insufficient data, EPA

did not quantify either costs or benefits for these types of deficiencies. 

The Predicted Rates at Which Virally Contaminated (and Non-Contaminated) Wells Will Be Required to

Take Action After Finding E. coli Ground Water Sources

EPA’s occurrence model estimates the percentage of wells that have only virus present, both E.

coli and virus present, or only E. coli present. The occurrence model also includes parameters that

describe how often contaminated wells actually have the contaminant present. For example, some

contaminated wells have E. coli present less than one percent of the time, while others have E. coli

present more than 10 percent of the time (some of which will also have sometime viral presence). When

E. coli contaminated wells are tested for the first time, those with frequent E. coli occurrence are the most

likely to be identified as contaminated. As these problems are addressed and corrected, there should be

fewer and fewer wells with frequent E. coli occurrence (as well as viral occurrence since a fraction of E.

coli wells will also have sometime viral presence. This diminishing rate of fecal contamination

identification is included in this EA. Uncertainty about the diminishing rate is due to uncertainty about

the EPA’s estimates of how often E. coli occurs in contaminated wells. As with other key uncertain

inputs, this uncertainty is represented by an uncertainty sample of the relevant parameters. Again, EPA

assumes no difference based on vulnerability or sensitivity. 

Undisinfected wells are subjected to triggered monitoring. The rate at which triggered

monitoring identifies a well as fecally-contaminated depends on both the fraction of time that E. coli is

present in the well and the frequency at which the well is sampled. Data verification (DV) data on total

coliform occurrence in distribution systems provide the basis for estimates of sampling frequency in

different types and sizes of systems. Although the data are limited, EPA has not modeled these as

uncertain estimates. Compared to other uncertain parameters, these have relatively little uncertainty and

are expected to make only minor contributions to the total uncertainty in this EA.

EPA also did not consider the cost impacts of additional sampling on corrective action costs. The

analysis assumes that for every triggered monitoring positive, at least one additional sample will also be

positive, resulting in corrective action. However, it is possible that some systems will not have a positive

additional sample and will therefore not incur costs for corrective action. Accounting for this would

reduce the costs of the rule associated with corrective actions and, to the extent that these systems actually

do have viral or bacterial pathogens present, would reduce the benefits of the rule as well.
Economic Analysis for the October 2006

Final Ground Water Rule 6-59

EPA assumes that the occurrence of fecal contamination will remain constant throughout the

implementation of the rule. However, this might not be the case if increased development results in fecal

contamination of a larger number of aquifers in areas served by ground water systems or if other rules,

such as Concentrated Animal Feeding Operations (CAFO), and Class V Underground Injections Control

(UIC) Well regulations result in decreased fecal contamination. This uncertainty is not mathematically

modeled in this EA.

The Costs of Taking Action After Finding E. coli in Ground Water Sources

EPA recognizes that there are both variability and uncertainty in unit cost estimates for treatment. 

Variability is expected in the actual costs that will be experienced by different water systems with similar

flows installing the same treatment technology. Otherwise similar systems may experience different

capital and/or O&M costs due to site-specific factors. Inputs to unit costs such as water quality

conditions, labor rates, and land costs can be highly variable and increase the system-to-system variability

in unit costs. In developing the unit cost estimates, there is insufficient information to fully characterize

what the distribution of this variability will be on a national scale for all of the treatments and all possible

conditions.

The unit costs for this EA are developed as average or representative estimates of what these unit

costs will be nationally. That is, in developing unit costs, design criteria for the technologies were

selected to represent typical, or average, conditions for the universe of systems. As a result, there is

uncertainty inherent in these unit cost estimates since they are based on independent assumptions with

supporting data and vendor quotes, where available, rather than on a detailed aggregation of State,

regional, or local estimates based on actual field conditions. EPA quantifies the uncertainty in these

national average unit cost factors for specific technologies. The percent uncertainty bounds used to

characterize unit costs were developed based on input from engineering professionals and reflect

recommendations from the National Drinking Water Advisory Council (NDWAC, 2001) in their review

of the national cost estimation methodology for the Arsenic Rule. EPA believes that the uncertainties in

capital and O&M costs for a given treatment technology are independent of one another and that

uncertainties across all technologies are independent.

Optional Assessment Monitoring

The Agency was not able to estimate the benefits or costs resulting from the optional assessment

monitoring program. States can determine what systems they deem most vulnerable to fecal

contamination and require these systems to conduct assessment monitoring. Systems would incur

additional costs from monitoring and reporting results as well as any corrective action associated with

fecal indicator positives. States would incur additional costs for determining what systems would be

required to monitor, assisting systems with corrective actions decisions, and recordkeeping. 

Corrective Actions and Significant Deficiencies

The Agency also did not develop costs for corrective actions for all conceivable significant

deficiencies that a system may encounter. Instead, representative actions that span the range of low cost

to expensive actions were used. The corrective actions that are a result of significant deficiencies

identified during sanitary surveys do not include the ones performed within the treatment plant or in the

distribution system due to lack of adequate data. Exclusion of these costs from the cost analysis results in

an underestimate of potential rule costs, though the magnitude of the underestimate is unknown. 
Economic Analysis for the October 2006

Final Ground Water Rule 6-60

In addition, EPA also recognizes that some costs (as well as benefits) from the correction of

sanitary survey deficiencies identified in the distribution systems and treatment plant have not been

quantified.

Uncertainty Summary

Overall, EPA recognizes that there is uncertainty in various parts of its estimates that could result

in either an over- or underestimate of the costs as presented in this chapter. Exhibit 6.32 presents a

summary of these issues, references the section or appendix where the information is introduced, and

estimates the effects that each may have on national costs. The Agency has been careful to use the best

available data, to account for uncertainty quantitatively when possible, and to avoid any consistent biases

in assumptions and the use of data. The primary known bias is that some benefits and costs have not been

quantified, and therefore are not included in the quantitative comparison of regulatory alternatives.

Exhibit 6.32 Cost Uncertainty Summary

Uncertainty

Section With

Full Discussion

of Uncertainty

Most Likely Effect of Current Assumptions on

Estimate of National Costs

Underestimate Overestimate

Unknown

Impact

Percentage of systems

finding TC positive samples 6.4.3 X

Number of triggered

monitoring samples

attributable to TC positives

under the GWR

6.4.3 X

Percentage of triggered

monitoring systems

receiving indicator-positive

source water

6.4.3 X

Uncertainty in compliance

forecasts for corrective

actions

6.4.4 X

Percentage of disinfection

failures 6.4.5 X

Unit Costs 6.4.7 X

Sanitary Survey corrective

actions 6.6 X

Compliance with multiple

rules 6.7 X
Economic Analysis for the October 2006

Final Ground Water Rule 6-61

Systems States Total

Lower

(5th %ile)

Upper

(95th %ile)

Lower

(5th %ile)

Upper

(95th %ile)

Lower

(5th %ile)

Upper

(95th %ile)

3 percent 50.0 $ 34.3 $ 68.8 $ 11.8 $ 10.9 $ 12.6 $ 61.8 $ 45.2 $ 81.4 $ 

7 percent 50.6 $ 35.2 $ 69.0 $ 11.7 $ 10.9 $ 12.6 $ 62.3 $ 46.1 $ 81.6 $ 

Notes: Detail may not add to totals due to independent rounding.

Source: Cost Model Outputs

Discount

Rate

Mean

Value

90 Percent

Confidence Bound

Mean

Value

90 Percent

Confidence Bound

Mean

Value

90 Percent

Confidence Bound

6.8 Total Annualized Cost for Final GWR Regulatory Alternative

Based on information presented previously in this chapter, EPA developed national cost estimates

for the Final GWR. Exhibit 6.33 presents the total annualized costs to PWSs for the final GWR at 3 and 7

percent discount rates. Exhibit 6.34 presents the total annualized cost for the final GWR by system size

and type at 3 and 7 percent discount rates. 

Exhibit 6.33 Total Annualized Present Value Costs ($Millions, 2003$)
Economic Analysis for the October 2006

Final Ground Water Rule 6-62

At 3% At 7%

Lower

(5th %ile)

Upper

(95th %ile)

Lower

(5th %ile)

Upper

(95th %ile)

$ 2.13 2.91 $ 3.69 $ 2.91 $ 2.16 $ 3.72 $ 

$ 2.54 3.61 $ 4.94 $ 3.59 $ 2.60 $ 4.83 $ 

$ 0.99 1.45 $ 1.98 $ 1.44 $ 1.00 $ 1.94 $ 

$ 1.29 1.96 $ 2.76 $ 1.94 $ 1.30 $ 2.69 $ 

$ 1.40 2.23 $ 3.26 $ 2.26 $ 1.49 $ 3.25 $ 

$ 1.87 2.85 $ 4.06 $ 3.05 $ 2.05 $ 4.41 $ 

$ 1.01 1.78 $ 2.73 $ 1.88 $ 1.11 $ 2.84 $ 

$ 1.14 1.89 $ 2.89 $ 2.12 $ 1.31 $ 3.18 $ 

$ 0.00 0.00 $ 0.00 $ 0.00 $ 0.00 $ 0.00 $ 

$ 12.39 18.67 $ 26.31 $ 19.19 $ 13.03 $ 26.87 $ 

$ 1.34 1.77 $ 2.27 $ 1.78 $ 1.34 $ 2.26 $ 

$ 1.21 1.86 $ 2.60 $ 1.83 $ 1.23 $ 2.53 $ 

$ 0.43 0.67 $ 0.97 $ 0.66 $ 0.42 $ 0.94 $ 

$ 0.28 0.46 $ 0.68 $ 0.46 $ 0.28 $ 0.67 $ 

$ 0.05 0.10 $ 0.16 $ 0.10 $ 0.06 $ 0.17 $ 

$ 0.02 0.04 $ 0.07 $ 0.04 $ 0.02 $ 0.07 $ 

$ 0.00 0.01 $ 0.01 $ 0.01 $ 0.00 $ 0.01 $ 

$ 0.00 0.01 $ 0.01 $ 0.01 $ 0.00 $ 0.02 $ 

$ - - $ - $ - $ - $ - $ 

$ 3.33 4.91 $ 6.77 $ 4.89 $ 3.36 $ 6.68 $ 

$ 12.87 17.74 $ 23.27 $ 17.86 $ 13.11 $ 23.44 $ 

$ 4.75 7.07 $ 9.95 $ 7.00 $ 4.76 $ 9.61 $ 

$ 0.58 0.98 $ 1.45 $ 0.96 $ 0.59 $ 1.38 $ 

$ 0.25 0.42 $ 0.63 $ 0.42 $ 0.26 $ 0.63 $ 

$ 0.07 0.13 $ 0.21 $ 0.14 $ 0.07 $ 0.22 $ 

$ 0.04 0.08 $ 0.14 $ 0.09 $ 0.04 $ 0.15 $ 

$ 0.00 0.01 $ 0.01 $ 0.01 $ 0.00 $ 0.01 $ 

$ 0.01 0.01 $ 0.02 $ 0.01 $ 0.01 $ 0.02 $ 

$ - - $ - $ - $ - $ - $ 

$ 18.56 26.44 $ 35.68 $ 26.49 $ 18.84 $ 35.46 $ 

$ 34.28 50.02 $ 68.76 $ 50.57 $ 35.22 $ 69.00 $ 

Notes: Detail may not be consistent with summary presentations due to independent statistical analysis.

Source: Cost Model Outputs, Exhibit 6.6.

90 Percent

Confidence Bound

<100

101-500

Mean

Value

90 Percent

Confidence Bound

Mean

Value

System Size

(Population Served)

Community Water Systems (CWSs)

501-1,000

1,001-3,300

3,301-10K

10,001-50K

100,001-1M

50,001-100K

100,001-1M

>1 Million

All Sizes

1,001-3,300

3,301-10K

10,001-50K

50,001-100K

501-1,000

50,001-100K

100,001-1M

>1 Million

501-1,000

1,001-3,300

3,301-10K

10,001-50K

>1 Million

All Sizes

TOTAL

Nontransient Noncommunity Water Systems (NTNCWSs)

Transient Noncommunity Water Systems (TNCWSs)

All Sizes

<100

101-500

<100

101-500

Exhibit 6.34 Total Annualized Costs to Systems by System Size and Type

($Millions, 2003$)

6.9 Comparison of Regulatory Alternatives

During the development of the GWR, the Agency considered several regulatory alternatives. 

Exhibit 6.35 provides a comparison of the total annual cost of compliance across the four regulatory

alternatives evaluated for the GWR. The cost of the final rule lies between the least costly and most costly

alternatives. The costs increases, however, by more than a factor of ten from the final rule to the acrossthe-board disinfection alternative. This increase in costs results from the fact that the final rule and

Alternatives 1 and 3 first are tailored to focus on PWSs that have a demonstrated risk of providing their

customers fecally contaminated drinking water. Across-the-board disinfection, as the name implies,

requires all PWSs to treat their source water, even if there is no demonstrated potential or actual fecal
Economic Analysis for the October 2006

Final Ground Water Rule 6-63

Lower

(5th %tile) 

Upper

(95th %tile) 

 Lower

(5th %tile) 

Upper

(95th %tile) 

Alternative 1

Sanitary Survey Only $ 11.8 15.3 $ 19.2 $ 15.3 $ 11.9 $ 19.0 $ 

Alternative 2 - Risk-Targeted Approach (Final Rule)

Sanitary Survey and Triggered Monitoring $ 45.2 61.8 $ 81.4 $ 62.3 $ 46.1 $ 81.6 $ 

Alternative 3 - Multi-Barrier Approach

Sanitary Survey, Hydrogeologic Sensitivity Assessment, 

Assessment Monitoring, and Triggered Monitoring $ 49.4 67.9 $ 89.5 $ 69.4 $ 51.0 $ 90.6 $ 

Alternative 4

Across-the-Board Disinfection $ 636.8 686.4 $ 735.4 $ 665.3 $ 612.3 $ 717.0 $ 

Source: Cost Model Outputs

Rule Alternative

Total Annualized Cost ($Millions)

3 Percent Discount Rate 7 Percent Discount Rate

Mean

Estimate

90 Percent

Mean

Estimate

90 Percent

contamination. This means that costs are being incurred by many more PWSs under this alternative than

the others.

The burden associated with State oversight and administration varies among the different

regulatory alternatives. State burden and cost estimates for implementation and annual administration for

the final regulatory alternative are presented in Exhibits 6.7a and 6.7b. These costs are estimated to be 

similar for Alternatives 2 and 3. States incur less burden from oversight and administration of Alternatives

1 and 4 because these alternatives do not have monitoring components of the rule. Additionally,

laboratory certification is eliminated in Alternatives 1 and 4, and due to limited numbers and complexity of

rule components, the burden for the remaining activities is reduced by 50% compared to Alternatives 2 and

3. For Alternative 4, technology selection is allocated in accordance with the compliance forecast for all

systems choosing treatment technologies. 

EPA used the same process for developing costs for the final rule to develop costs for the other

alternatives. Unit costs were multiplied by the number of systems performing various components of each

alternative, and results were summed for all components.

Exhibit 6.35 Comparison of National Annual Costs

by Regulatory Alternative ($Millions, 2003$)
Economic Analysis for the 7-1 October 2006

Final Ground Water Rule

7. Economic Impact Analysis

7.1 Introduction

As part of the rulemaking process, EPA is required to address the direct and indirect burdens that

the GWR may place on certain types of governments, businesses, and populations. This chapter presents

the analyses performed by EPA in accordance with the following 12 Federal mandates.

1) The Regulatory Flexibility Act (RFA) of 1980, as amended by the Small Business Regulatory

Enforcement Fairness Act (SBREFA) of 1996.

2) An analysis of small system affordability to determine variance technologies in accordance with

Section 1415(e)(1) of the SDWA Amendments.

3) Feasible technologies available to all systems as required by Section 1412(b)(4)(E) of the SDWA

Amendments. 

4) A Technical, Financial, and Managerial Capacity Assessment as required by Section 1420(d)(3)

of the 1996 Amendments to the SDWA. 

5) Paperwork Reduction Act (a separate Information Collection Request document contains the

complete analysis). 

6) Unfunded Mandates Reform Act (UMRA) of 1995.

7) Executive Order 13175 (Consultation and Coordination with Indian Tribal Governments).

8) Impacts on sensitive subpopulations as required by Section 1412(b)(3)(c)(i) of the Safe Drinking

Water Act (SDWA) Amendments.

9) Executive Order 13045 (Protection of Children from Environmental Health Risks and Safety

Risks).

10) Executive Order 12898 (Federal Actions to Address Environmental Justice in Minority

Populations and Low-Income Populations).

11) Executive Order 13132 (Federalism).

12) Executive Order 13211 (Actions Concerning Regulations That Significantly Affect Energy

Supply, Distribution, or Use). 

Many of the requirements and executive orders listed above call for an explanation of why the

rule is necessary, the statutory authority for the rule, and the primary objectives that the rule is intended to

achieve (refer to Chapter 2 for more information regarding the objectives of the rule). More specifically,

they are designed to assess the financial and health effects of the rule on sensitive, low-income, and Tribal

populations as well as on small systems. The chapter also examines how much additional capacity

systems will need to meet GWR requirements and whether there are existing, feasible technologies and

treatment techniques available to meet rule requirements.

7.2 Regulatory Flexibility Act and Small Business Regulatory Enforcement Fairness

Act

The Regulatory Flexibility Act (RFA) generally requires an agency to prepare a regulatory

flexibility analysis for any rule subject to notice and comment rulemaking requirements under the

Administrative Procedure Act or other statute, unless the Agency certifies that the rule will not have a

significant economic impact on a substantial number of small entities (5 U.S.C. 602(a)). Small entities

include small businesses, small organizations, and small governmental jurisdictions.
Economic Analysis for the 7-2 October 2006

Final Ground Water Rule

Defining Small Entities Affected by the Rule

 The RFA provides default definitions for each type of small entity. Small entities are defined as:

(1) a small business as defined by the Small Business Administration’s (SBA) regulations at 13 CFR

121.201; (2) a small governmental jurisdiction that is a government of city, county, town, school district,

or special district with a population of less than 50,000; and (3) a small organization that is any “not-forprofit enterprise that is independently owned and operated and is not dominant in its field.” However, the

RFA also authorizes an agency to use alternative definitions that “are appropriate to the activities of the

agency after proposing the alternative definition(s) in the Federal Register and taking comment” (5

U.S.C. 601(3)–(5)) for each category of small entity. In addition, to establish an alternative small

business definition, agencies must consult with SBA’s Chief Council for Advocacy.

The RFA references the definition of “small business” found in the Small Business Act, which

authorizes the SBA to define “small business” further by regulation. The SBA defines small businesses

by category using the North American Industry Classification System (NAICS). The NAICS code for

public water supplies (PWSs) is 22131 (Water Supply and Irrigation Systems), and State agencies that

include drinking water programs are classified as 92411 (Administration of Air and Water Resource and

Solid Waste Management Programs) or 923120 (Administration of Public Health Programs). Ancillary

systems (i.e., those that supplement the function of other establishments like factories, power plants,

mobile home parks, etc.) cannot be categorized in a single NAICS code. For ancillary systems, the

NAICS code is that of the primary establishment or industry. Examples of small businesses include

small, privately-owned PWSs and for-profit businesses where provision of water may be ancillary, such

as mobile home parks or day-care centers. Examples of small organizations include churches, schools,

and homeowner associations.

The GWR applies to all PWSs that use ground water. Although the SBA and the RFA provide

clear definitions for small businesses, organizations, and governmental jurisdictions, small entities are not

necessarily small water systems. The size of the entity has no relation to the number of people it serves as

a water supply. Furthermore, data are not collected on businesses, organizations, and governmental

jurisdictions in terms of the number of water customers they serve. Therefore, EPA chose to use an

alternative definition for small entities.

For purposes of assessing the impacts of the GWR on small entities, EPA considered small

entities to be PWSs serving fewer than 10,000 people. This is the cut-off level specified by Congress in

the 1996 Amendments to the Safe Drinking Water Act for small system flexibility provisions. As

required by the RFA, EPA proposed using this alternative definition in the Federal Register (63 FR 7620;

February 13, 1998), requested public comment, consulted with the SBA, and finalized the alternative

definition for all future drinking water regulations in the Consumer Confidence Reports regulation (63 FR

44511; August 19, 1998). As stated in that final rule, the alternative definition would be applied to this

regulation as well.

Measuring Significant Impacts

EPA has not revised its determination at proposal that the GWR will have a substantial impact

upon a significant number of small water systems. EPA assessed the potential impact of today’s rule on

small entities. There are 147,330 CWSs, NTNCWSs, and TNCWSs providing potable ground water to

the public, 145,580 (99 percent) are classified by EPA as small entities. EPA has determined that all

small ground water systems are impacted by the sanitary survey requirement and a substantial number

these systems will be impacted by additional requirements of today’s final rule including the source water

monitoring requirements and the corrective action requirements. Exhibit 6.5b provides a detailed

summary of the numbers of systems and entry points impacted by each GWR requirement. 
Economic Analysis for the 7-3 October 2006

Final Ground Water Rule

As required by section 604 for the RFA, EPA also prepared a final regulatory flexibility analysis

(FRFA) for today’s final rule. The FRFA addresses the issues raised by public comments on the IRFA,

which was part of the proposal of this rule. The FRFA is available for review in the docket.

Small Entity Outreach and Small Business Advocacy Review Panel

Section 609(b) of the RFA, as amended by SBREFA, and Section 203 of UMRA require EPA to

provide small governments with an opportunity for timely and meaningful participation in the regulatory

development process. In addition, the Agency must consult with small entity stakeholders and convene

an Small Business Advocacy Review (SBAR) Panel prior to publication of a proposed rule. 

EPA convened an SBAR Panel for the proposed rule. The SBAR Panel members for the GWR

included the Small Business Advocacy Chair of EPA, the Director of the Standards and Risk

Management Division in the Office of Ground Water and Drinking Water (OGWDW) within EPA’s

Office of Water, the Administrator for the Office of Information and Regulatory Affairs of OMB, and the

Chief Counsel for Advocacy of the SBA. The SBAR Panel convened on April 10, 1998 and met seven

times before the end of the 60-day period on June 8, 1998. The culmination of these meetings was the

SBAR Panel’s report, Final Report of the SBREFA Small Business Advocacy Review Panel on EPA’s

Planned Proposed Rule for National Primary Drinking Water Regulations: Ground Water. The small

entity stakeholder comments on components of the GWR and the background information provided to the

SBAR Panel and the small entity stakeholders are available for review in the water docket. This

information and the Agency’s response to the SBAR Panel’s recommendations in developing the GWR

are summarized below.

Prior to convening the SBAR Panel, OGWDW consulted with a group of 22 small entity

stakeholders likely to be impacted by a GWR. The small entity stakeholders small system operators, local

government officials, small business owners (e.g., a bed and breakfast with its own water supply), and

small nonprofit organization (e.g., a church with its own water supply). The small entity stakeholders

were provided with background information on the rule, on the need for the rule, and the potential

requirements. The small entity stakeholders were asked to provide input on the potential impacts of the

rule from their perspective. All 22 small entity stakeholders commented on the information provided in

the IRFA. These comments were provided to the SBAR Panel when it convened. After a teleconference

between the small entity stakeholders and the SBAR Panel, the small entity stakeholders were invited to

provide additional comments on the information provided. Three small entity stakeholders provided

additional comments on the rule components after the teleconference.

In general, the small entity stakeholders consulted on the GWR were concerned about the impact

of the rule on small water systems (because of their small staff and limited budgets), the additional

monitoring that might be required, and the data and resources necessary to conduct a hydrogeologic

sensitivity assessment (HSA) or sanitary survey. There was also considerable discussion about whether

the source data was nationally representative. Small entity stakeholders suggested providing flexibility to

the States/Primacy Agencies implementing these provisions and opposed mandatory disinfection acrossthe-board. Small entity stakeholders expressed support for existing monitoring requirements as a means

of determining compliance, and some supported increased requirements for total coliform monitoring.

Consistent with the RFA/SBREFA requirements, the SBAR Panel evaluated the assembled

materials and small entity comments related to the elements of the IRFA. A copy of the SBAR Panel

report is available in the Office of Water docket for the GWR. The SBAR Panel suggested that, given the

number of systems that could be affected by the rule, EPA consider focusing compliance requirements on

those systems most at risk of fecal contamination. From this perspective, the SBAR Panel suggested that

EPA evaluate whether it would be appropriate to establish different rule requirements for systems based
Economic Analysis for the 7-4 October 2006

Final Ground Water Rule

on system type, size, or location. The SBAR Panel also suggested providing States/Primacy Agencies

with maximum flexibility, consistent with ensuring an appropriate minimum level of public health

protection, to tailor specific requirements to individual system needs and resources. The SBAR Panel’s

recommendations to address the small entity stakeholders’ concerns about the GWR were considered in

developing the regulatory alternatives analyzed in this final rulemaking. 

7.3 Small Drinking Water System Variances

Section 1415(e) of SDWA allows States/Primacy Agencies to grant variances to small water

systems that cannot afford to comply with a National Primary Drinking Water Regulation. 

Section 1415(e)(6)(B) of SDWA, however, states that a variance shall not be available for a “national

primary drinking water regulation for a microbial contaminant (including a bacterium, virus, or other

organism) or an indicator or treatment technique for a microbial contaminant.” Therefore, this provision

does not apply, because the GWR is a regulation to control a microbial contaminant.

7.4 Feasible Treatment Technologies for All Systems

In accordance with Section 1412(b)(4)(E) of the 1996 SDWA Amendments, EPA examined

whether there were existing, feasible technologies and treatment techniques available that would allow

systems to meet the GWR requirements. EPA determined that ground water systems of all sizes can meet

the requirements of 4-log virus inactivation by using chlorine (hypochlorination or gas disinfection),

which is also relatively inexpensive and simple for systems to install and operate.

7.5 Effect of Compliance with the GWR on the Technical, Financial, and Managerial

Capacity of Public Water Systems

Section 1420(d)(3) of the SDWA, as amended, requires that, in promulgating a NPDWR, the

Administrator shall include an analysis of the likely effect of compliance with the regulation on the

technical, managerial, and financial (TMF) capacity of PWSs. The following analysis fulfills this

statutory obligation by identifying the incremental impact that the GWR will have on the TMF of

regulated water systems. Analyses presented in this document reflect only the impact of new or revised

requirements, as established by the GWR; the impacts of previously established requirements on system

capacity are not considered.

Overall water system capacity is defined in Guidance on Implementing the Capacity Development

Provisions of the Safe Drinking Water Act Amendments of 1996 (USEPA 1998a) as the ability to plan for,

achieve, and maintain compliance with applicable drinking water standards. Capacity encompasses three

components: technical, managerial, and financial. Technical capacity is the operational ability of a water

system to meet those SDWA requirements. Key issues of technical capacity include the following:

1) Source Water Adequacy—Does the system have a reliable source of water with adequate

quantity? Is the source generally of good quality and adequately protected?

2) Infrastructure Adequacy—Can the system provide water that meets SDWA standards?

What is the condition of its infrastructure, including wells or source water intakes,

treatment, storage, and distribution? What is the infrastructure’s life expectancy? Does

the system have a capital improvement plan?
Economic Analysis for the 7-5 October 2006

Final Ground Water Rule

3) Technical Knowledge and Implementation—Are the system’s operators certified? Do the

operators have sufficient knowledge of applicable standards? Can the operators

effectively implement this technical knowledge? Do the operators understand the

system’s technical and operational characteristics? Does the system have an effective

operation and maintenance (O&M) program?

Managerial capacity is the ability of a water system’s managers to make financial, operating, and

staffing decisions that enable the system to achieve and maintain compliance with SDWA requirements. 

Key issues include:

• Ownership Accountability—Are the owners clearly identified? Can they be held

accountable for the system?

• Staffing and Organization—Are the operators and managers clearly identified? Is the

system properly organized and staffed? Do personnel understand the management

aspects of regulatory requirements and system operations? Do they have adequate

expertise to manage water system operations? Do personnel have the necessary licenses

and certifications?

• Effective External Linkages—Does the system interact well with customers, regulators,

and other entities? Is the system aware of available external resources, such as technical

and financial assistance?

Financial capacity is a water system’s ability to acquire and manage sufficient financial resources

to allow the system to achieve and maintain compliance with SDWA requirements. Key issues include:

• Revenue Sufficiency—Do revenues cover costs?

• Creditworthiness—Is the system financially healthy? Does it have access to capital

through public or private sources?

• Fiscal Management and Controls—Are adequate books and records maintained? Are

appropriate budgeting, accounting, and financial planning methods used? Does the

system manage its revenues effectively?

7.5.1 Requirements of the Final GWR

This capacity analysis is presented only for the Final Rule, although EPA took similar

considerations into account in the selection of the Final Rule over the other alternatives. This process led

to the incorporation of less expensive rule features for systems having fewer capabilities. For example,

EPA allowed flexibility in the triggered monitoring requirements for certain small systems. Very small

systems that must take four repeat samples following a total coliform (TC) positive sample under the TCR

may designate one of the repeat samples as a source water sample, which covers both TCR repeat

sampling and GWR triggered monitoring requirements. In addition, the requirement for performing

assessment monitoring, which was part of the preferred regulatory alternative at proposal, is now a State

option as part of the Final Rule. Flexibility was also built into the GWR through extended compliance

time frames for NCWSs, which are primarily small systems.
Economic Analysis for the 7-6 October 2006

Final Ground Water Rule

The GWR establishes four major requirements that may affect the TMF capacity of affected

PWSs:

1) Sanitary surveys

2) Triggered source water monitoring 

3) Corrective actions

4) Compliance monitoring

In addition, personnel from systems regulated under the GWR will need to familiarize themselves

with the rule and its requirements.

7.5.2 Systems Subject to the GWR

The GWR will apply to all PWSs that use ground water and may affect 42,361 CWSs, 18,908

NTNCWSs, and 86,061 TNCWSs—147,330 systems in all. While most will not, some systems may

require increased TMF capacity to comply with the new requirements, or will need to tailor their

compliance approaches to match their capacities. Refer to section 7.5.4 for a detailed discussion of the

changes in TMF capacity for small and large systems.

7.5.3 Impact of the GWR on System Capacity

The estimates presented in Exhibits 7.1a and 7.1b reflect the anticipated impact of the GWR on

system capacity based on the expected measures that systems will be required to adopt. The extent of the

expected impact of a particular requirement on system capacity is estimated using a scale of 0-5, where 0

represents a requirement that is not expected to have any impact, 1 represents a requirement that is

expected to have a minimal impact, and 5 represents a requirement that is expected to have a very

significant impact on system capacity. Criteria used to develop the scores and associated impacts are

discussed further in section 7.5.4.

These impacts are assessed separately for small systems (Exhibits 7.1a) and for large systems

(Exhibit 7.1b). This distinction is necessary because most large systems will face fewer challenges in

implementing the rule than smaller systems. For both large and small systems, EPA evaluated the

capacity impact of each requirement on those systems affected by that particular requirement. Because in

many cases the requirements only affect a small percentage of systems/entry points, the exhibits also

display the number of systems and percentage of systems/entry points (of the subset of small or large

systems/entry points) estimated to be affected by each specific requirement.
Economic Analysis for the 7-7 

Final Ground Water Rule 

Exhibit 7.1a Estimated Impact of the GWR on Small System’s Technical, Managerial, and Fin

 (0 = no impact, 1 = minimal impact, and 5 = very significant impact)

Requirement

Number and Percent of

Small Systems

Technical Capacity Managerial Capacity 

Source Water

Adequacy

Infrastructure Adequacy

Technical Knowledge &

Implementation

Ownership Accountability

Staffing & Organization

Effective External

Linkages

RSffii

Familiarization with rulerequirements 145,580 (100%) 0 0 01211

Sanitary surveys 145,580 (100%) 0 0 00000Triggered monitoring 128,711 (88%) 0 0 01111Corrective actions forsignificant deficiencies 24,749 (17%) 4 4 44444

Compliance monitoring 3,685 (3%) 2 2 22222

Notes: (1) To analyze the impact of these requirements on system capacity, the requirements believed to have the most and t

affected systems were analyzed first. These initial analyses were then used as the bases against which the relative imrequirements were assessed. The impact estimates developed for each requirement were also compared to those dev

2 Enhanced Surface Water Treatment Rule (LT2ESWTR) and the Stage 2 Disinfectants and Disinfection Byproducts Rensure cross-rule consistency and to enable cross-rule comparisons. 

(2) The scores presented above represent the worst case scenario; the requirements of this rule are expected to have 

capacity of most systems affected by each requirement.

Source: Number and percent of systems subject to each rule activity from Exhibit 6.5b. Impact on capacity is determined relative to prev

the cost and number of systems/plants that require additional capacity to comply with each requirement, as described in section 
Economic Analysis for the 7-8 

Final Ground Water Rule 

Exhibit 7.1b Estimated Impact of the GWR on Large System’s Technical, Managerial, and Fin

 (0 = no impact, 1 = minimal impact, and 5 = very significant impact)

Requirement

Number and

Percent of Large

Systems

Technical Capacity Managerial Capacity 

Source Water

Adequacy

Infrastructure Adequacy

Technical Knowledge &

Implementation

Ownership Accountability

Staffing & Organization

Effective External

Linkages

RSffii

Familiarization with rulerequirements 1,750 (100%) 1 1 11111

Sanitary surveys 1,750 (100%) 0 0 00000Triggered monitoring 964 (55%) 0 0 00000Corrective actions for significantdeficiencies 298 (17%) 3 3 33333

Compliance monitoring 123 (7%) 2 2 22222

Notes: (1) To analyze the impact of these requirements on system capacity, the requirements believed to have the most and t

affected systems were analyzed first. These initial analyses were then used as the bases against which the relative imrequirements were assessed. The impact estimates developed for each requirement were also compared to those dev

LT2ESWTR and the Stage 2 DBPR to ensure cross-rule consistency and to enable cross-rule comparisons. (2) The scores presented above represent the worst case scenario; the requirements of this rule are expected to have 

capacity of most systems affected by each requirement.

Source: Number and percent of systems subject to each rule activity from Exhibit 6.5b. Impact on capacity is determined relative to prev

the cost and number of systems/plants that require additional capacity to comply with each requirement, as described in section 
Economic Analysis for the 7-9 October 2006

Final Ground Water Rule

7.5.4 Derivation of GWR Scores

EPA developed a 5-point scoring system to analyze the impact compliance with all new

regulations will have on the TMF capacity of PWSs. For each regulation, it is necessary to complete the

following steps:

1. Determine the type and number of PWSs to which the regulation applies.

2. List all of the requirements of the regulation.

3. Determine the type and number of PWSs to which each requirement applies.

4. Evaluate the impact of each requirement on the capacity of affected PWSs.

The determination of the universe of affected systems and the evaluation of the capacity impact

of individual requirements requires the use of the cost and technical information contained in SDWIS,

EAs developed for other rules, information collection requests, and other supporting documentation for

the rule. These data sources are also used to develop a qualitative description of the expected response of

affected systems to each requirement.

The overall evaluation of the impact of a requirement on the affected systems, presented in

Exhibit 7.2, is based on the impact each requirement has on nine sub-categories of capacity—three subcategories under each of the broader divisions of TMF capacity. Within these sub-categories, a

professional engineer with extensive water system experience reviewed the costs, number of systems

affected, and complexity of each requirement. After estimating the technical, managerial, and financial

impacts within each sub-category, the professional engineer assigned the scores using best professional

judgment. Costs were considered cumulatively for each requirement for small and large systems. This

score reflects the additional capacity that systems will need to develop to comply with each requirement. 

Due to a lack of available information on operating budgets, this analysis does not include a quantitative

component.

To ensure the ability to make cross-rule comparisons, to standardize the assignment of numerical

scores, and to minimize the subjectivity of the scoring system, the requirements made on systems by the

regulation in question are compared to the requirements of those regulations for which capacity impact

analyses have already been conducted (e.g., Long Term 1 Enhanced Surface Water Treatment Rule

(LT1ESWTR), LT2ESWTR, Stage 2 DBPR). Similar requirements are assigned similar impact scores. 

These group assignments are reviewed by the EPA Rule Manager and other EPA staff cognizant

of small system issues to ensure that they accurately reflect the cumulative impact of the rule

requirements on system capacity. Any disagreements over the assignments are discussed. The EPA Rule

Manager and other EPA staff discuss the rationale for the disagreement and evaluate whether the

assignments need to be adjusted. EPA adjusts the assignments only after review of the rule support

documents and an analysis of the expected system response to the rule requirements.

7.5.4.1 Small Water Systems (Those Serving 10,000 or Fewer People)

Small systems will likely face only a minimal challenge to their technical and managerial

capacity as a result of efforts to familiarize themselves with the GWR and aid the State in conducting

sanitary surveys. Total coliform sampling is already required under the TCR and, therefore, it is not

expected to pose any new technical or managerial capacity issues for systems. On average, PWSs serving

fewer than 3,000 people will only need to take less than 1 triggered samples a year, and small systems
Economic Analysis for the 7-10 October 2006

Final Ground Water Rule

serving fewer than 1,000 people will be able to use one of their required TCR repeat samples to satisfy

triggered monitoring requirements, eliminating any extra burden or cost. 

Small system technical and managerial capacity may be affected by requirements to monitor the

effectiveness and reliability of their disinfection or removal, especially systems not currently using

disinfection. Ground water systems serving 3,300 people or fewer and using disinfection can conduct

daily grab samples to measure disinfection levels instead of installing more costly continuous monitoring

equipment. However, this may also require the system to increase staffing levels in addition to providing

training to ensure that system staff understand the compliance monitoring requirements. Reporting,

record-keeping, and data administration requirements will also affect the managerial capacity of small

systems. 

Small systems that are required to take corrective action are expected to experience the most

significant financial challenge since many corrective actions consist of a large, one-time capital

expenditure to resolve the problem. Changes in treatment may also significantly impact the managerial

and technical capacity of the system. 

7.5.4.2 Large Water Systems (Those Serving at Least 10,000 People)

Large systems will likely not face more than a minimal challenge to their technical and

managerial capacity as a result of efforts to familiarize themselves with the GWR and assist the State with

sanitary surveys. Although larger systems may need to take many source water samples a year to meet

the triggered monitoring requirements, most larger systems are familiar with total coliform monitoring

and already have the TMF capacity to address this increased burden.

Many larger systems already have the TMF capacity to address additional monitoring of the

effectiveness and reliability of disinfection or removal. These systems will be affected less significantly

than smaller systems, especially since some may already be disinfecting and conducting monitoring. 

Large systems are expected to face the most significant challenge meeting the technical, managerial, and

financial requirements associated with corrective action. However, this requirement is only necessary

when a sanitary survey identifies a significant deficiency or when a source water monitoring sample tests

positive for fecal indicators. 

7.6 Paperwork Reduction Act

The information collection requirements for the GWR have been approved by the Office of

Management and Budget (OMB) under the Paperwork Reduction Act, 44 U.S.C. 3501 et seq. The

information collected as a result of this rule will allow the States/Primacy Agencies and EPA to determine

appropriate requirements for specific systems and evaluate compliance with the rule.

The Paperwork Reduction Act requires EPA to estimate the burden on public water systems

(PWSs) and States/Primacy Agencies of complying with the rule. Burden means the total time, effort,

and financial resources required to generate, maintain, retain, disclose, or provide information to or for a

Federal agency. This burden includes the time needed to conduct these activities:

• Review instructions.

• Develop, acquire, install, and employ technology and systems for the purposes of

collecting, validating, verifying, processing, maintaining, and disclosing information.
Economic Analysis for the 7-11 October 2006

Final Ground Water Rule

• Adjust the existing ways to comply with any previously applicable instructions and

requirements.

• Train personnel to respond to information collected.

• Search data sources.

• Complete and review the collection of information.

• Transmit or otherwise disclose the information.

For the first 3 years after publication of the final GWR in the Federal Register, the major

information requirements are for States/Primacy Agencies and PWSs to prepare for implementation of the

rule. The information collection requirements are mandatory under Part 141 for systems and Part 142 for

States/Primacy Agencies. The calculation of GWR information collection burden and costs can be found

in the Information Collection Request for National Primary Drinking Water Regulations: Final Ground

Water Rule (USEPA 2006c).

The total burden associated with GWR requirements over the 3 years covered by the Information

Collection Request is 1,155,791 hours, an average of 385,264 hours per year. This is based on an

estimate that 57 States and territories will each need to provide 1 response each year with an average of

2,193 hours per response, and that 49,110 systems will each provide 2 responses each year with an

average burden of 2.6 hours per response.

The total reporting and recordkeeping cost over the 3-year clearance period of the Information

Collection Request is $30.3 million, an average of $10.1 million per year (simple average over 3 years). 

The average annual cost per response is $103. The recordkeeping and reporting burden does not include

any capital costs for the first 3-year Information Collection Request period. Exhibit 7.2 provides a

summary of the results of the Information Collection Request calculations.

Exhibit 7.2 Average Annual Burden Hours and Costs for the GWR Information

Collection Request 3-Year Approval Period

Responses Burden

Hours

Labor Costs O&M

Costs

Capital

Costs

Total

Annual

Costs

PWSs 98,220 260,244 $5,890,508 $0 $0 $5,890,508

States &

Territories

57 125,020 $4,200,914 $0 $0 $4,200,914

Total 98,277 385,264 $10,091,422 $0 $0 $10,091,422

Note: Data represent burden and cost for only the 3-year Information Collection Request approval period. Data are

based on nominal (or undiscounted) values. Detail may not add due to independent rounding.

Source: Information Collection Request for the National Primary Drinking Water Regulations: Final Ground Water

Rule (USEPA 2006c).
Economic Analysis for the 7-12 October 2006

Final Ground Water Rule

7.7 Unfunded Mandates Reform Act

The UMRA of 1995, Public Law 104-4, consists of four Titles and numerous sections. Sections

201 through 205 of Title II, entitled “Regulatory Accountability and Reform,” are relevant to the GWR

and are discussed in this section. Title II, Section 201 of the UMRA, requires Federal agencies to assess

the effects of their regulatory actions on State, Local, and Tribal governments, and the private sector. 

Under UMRA Section 202, EPA generally must prepare a written statement, including a cost-benefit

analysis, for proposed and final rules with “Federal mandates” that may result in expenditures by State,

Local, and Tribal governments, in the aggregate, or by the private sector, of $100 million or more in any 1

year. Section 203 requires the Agency to establish a small government agency plan before establishing

any regulatory requirements that may significantly or uniquely affect small governments.

Section 204 of the UMRA requires the Agency to develop an effective process to permit elected

officers of State, Local, and Tribal governments to provide meaningful and timely input in the

development of regulatory proposals that contain significant Federal intergovernmental mandates. 

Finally, Section 205 generally requires EPA to identify and consider a reasonable number of regulatory

alternatives and adopt the least costly, most cost-effective, or least burdensome alternative that achieves

the objectives of the rule before promulgating a rule for which a written statement is needed under

Section 202. The provisions of Section 205 do not apply when they are inconsistent with applicable law. 

Moreover, Section 205 allows EPA to adopt an alternative other than the least costly, most cost-effective,

or least burdensome alternative if the Administrator publishes with the final rule an explanation why that

alternative was not adopted.

EPA has determined that this rule will not result in expenditures of $100 million or more for

State, Local, and Tribal governments, in the aggregate or the private sector in any 1 year, as shown in

Exhibit 7.3.
Economic Analysis for the 7-13 October 2006

Final Ground Water Rule

3% Discount 

Rate

7% Discount 

Rate

Percent of 3% 

Grand Total 

Costs

Percent of 7% 

Grand Total 

Costs

Ground Water Systems Costs 29.5 $ 30.0 $ 48% 48%

State Costs 11.8 $ 11.7 $ 19% 19%

Tribal Costs 0.2 $ 0.2 $ 0% 0%

Total Public 41.5 $ 41.9 $ 67% 67%

Ground Water Systems Costs 20.3 $ 20.4 $ 33% 33%

Total Private 20.3 $ 20.4 $ 33% 33%

GRAND TOTAL 61.8 $ 62.3 $ 100% 100%

Exhibit 7.3 Ground Water System, State, and Tribal Estimated Costs

Note: Detail may not add due to independent rounding. All values annualized in millions of 2003$. 

Source: State Costs from Appendix D; Total Public and Private Costs from GWR Cost Model Output.

Although the GWR is not subject to the requirements of Sections 202 and 205 of UMRA, EPA

has prepared a written statement addressing the following items:

• The authorizing legislation (Chapter 2)

• Benefit-cost analysis including an analysis of the extent to which the costs of State, Local

and Tribal governments will be paid for by the Federal government (Chapter 8, section

7.7.1)

• Estimates of future compliance costs and disproportionate budgetary effects (Chapter 6,

section 7.7.2)

• Macroeconomic effects (section 7.7.3)

• A summary of EPA’s consultation with State, Local, and Tribal governments and their

concerns, including a summary of the Agency’s evaluation of those comments and

concerns (sections 7.2, 7.7.7, 7.8, 7.11)

• Identification and consideration of regulatory alternatives and the selection of the least

costly, most cost-effective, or least burdensome alternative that achieves the objectives of

the rule (Chapters 3 and 8)

7.7.1 Social Benefits and Costs

The social benefits are those that primarily accrue to the public through an increased level of

protection from viral and bacterial illness due to exposure to microbial pathogens in drinking water. To

assign a monetary value to the illness, EPA used cost-of-illness (COI) estimates by age categories to

estimate the benefits from the reduction in acute viral illnesses and deaths avoided. This is considered to

be a lower-bound estimate of actual benefits because it does not include the pain and discomfort

associated with the illness. Mortalities were valued using a value of statistical life estimate consistent
Economic Analysis for the 7-14 October 2006

Final Ground Water Rule

Regulatory Alternative

Enhanced 

Annualized 

Benefits (3%) 

($Millions)

Traditional 

Annualized 

Benefits (3%) 

($Millions)

Enhanced 

Annualized 

Benefits (7%) 

($Millions)

Traditional 

Annualized 

Benefits (7%) 

($Millions)

Annualized 

Costs (3%) 

($Millions)

Annualized 

Costs (7%) 

($Millions)

Final GWR 

(Risk Targeted Approach) $19.7 $10.0 $16.8 $8.6 $61.8 $62.3

Alternative 1

(Sanitary Survey and Corrective 

Action) $3.6 $1.9 $2.9 $1.5 $15.3 $15.3

Alternative 3 

(Multi-barrier Approach) $21.3 $10.8 $18.2 $9.3 $67.9 $69.4

Alternative 4 

(Across-the-Board Disinfection) $70.2 $35.5 $61.9 $31.5 $686.4 $665.3

with EPA policy. Chapter 5 presents the benefits analysis, which includes both qualitative and monetized

benefits of improvements to health and safety. The estimated annualized benefit of the GWR using a 3

percent discount rate and the Enhanced COI approach is $19.7 million under the Final GWR.

In addition to reducing the number of viral illnesses and deaths, the GWR will also decrease

bacterial illness associated with fecal contamination of ground water. EPA did not directly calculate the

actual numbers of illnesses associated with bacterially contaminated ground water because the Agency

lacked the necessary pathogen occurrence data to include it in the risk model. However, in order to get an

estimate of the number of bacterial illnesses from fecally contaminated ground water, the Agency

developed an alternative calculation. This analysis of nonquantified benefits from avoided bacterial

illnesses and deaths is presented in section 5.4. This rule also considered but did not monetize the health

benefit from the reduction in chronic illness associated with some viral and bacterial infections.

Measuring the social costs of the rule requires identifying affected entities by ownership (public

or private), considering regulatory alternatives, calculating regulatory compliance costs, and estimating

any disproportionate impacts. Chapter 6 of this document details the cost analysis performed for the

GWR. Under the Preferred Alternative, the likely compliance scenario is expected to result in total

annualized costs of approximately $61.8 million using a 3 percent discount rate (or $62.3 million using a

7 percent discount rate). Exhibit 7.4 summarizes the range of annualized costs and benefits for each

regulatory alternative.

Exhibit 7.4 Mean Total Annualized Benefits and Costs of Regulatory Alternatives

($Millions, 2003$)

Source: Benefits from Exhibit 5.31. Costs from Exhibit 6.35.

Various Federal programs exist to provide financial assistance to State, Local, and Tribal

governments in complying with this rule. The Federal government provides funding to States/Primacy

Agencies that have primary enforcement responsibility for their drinking water programs through the

Public Water Systems Supervision (PWSS) Grants Program. States/Primacy Agencies may use these

funds to develop primacy programs or to contract with other State agencies to assist in the development or

implementation of their primacy programs. However, they may not use these funds to contract with

regulated entities (i.e., water systems). States/Primacy Agencies may use PWSS Grants to set up and

administer a State program that includes such activities as public education, testing, training, technical

assistance, development and administration of a remediation grant and loan or incentive program

(excluding the actual grant or loan funds), or other regulatory or nonregulatory measures.
1 “...[T]he agency shall prepare a written statement containing. . . (3) estimates by the agency, if and to the

extent that the agency determines that accurate estimates are reasonably feasible, of. . . (B) any disproportionate

budgetary effects of the Federal mandate upon any particular regions of the nation or particular State, Local, or

Tribal government, urban or rural or other types of communities, or particular segments of the private sector...”

Economic Analysis for the 7-15 October 2006

Final Ground Water Rule

Additional funding is available from other programs administered by EPA or other Federal

agencies. These include EPA’s Drinking Water State Revolving Fund (DWSRF), the U.S. Department of

Agriculture’s Rural Utilities’ Loan and Grant Program, and the Department of Housing and Urban

Development’s Community Development Block Grant (CDBG) Program.

SDWA authorizes the EPA Administrator to award capitalization grants to States/Primacy

Agencies, which in turn can provide low-cost loans and other types of assistance to eligible PWSs. The

DWSRF assists PWSs with financing the costs of infrastructure needed to achieve or maintain compliance

with SDWA requirements. Each State has considerable flexibility to determine the design of its DWSRF

Program and to direct funding toward its most pressing compliance and public health protection needs. 

States/Primacy Agencies may also, on a one-to-one matching basis, use up to 10 percent of their DWSRF

allotments for each fiscal year to assist in running the State drinking water program. In addition,

States/Primacy Agencies have the flexibility to transfer a portion of funds from their Clean Water State

Revolving Fund accounts to their DWSRF accounts.

A State/Primacy Agency can use the financial resources of the DWSRF to assist small systems. 

In fact, a minimum of 15 percent of a State/Primacy Agency’s DWSRF grant must be used to provide

infrastructure loans to systems serving 10,000 or fewer people. Two percent of the State/Primacy

Agency’s grant is set-aside funding that can only be used to provide technical assistance to small systems. 

In addition, up to 14 percent of the State/Primacy Agency’s grant may be used to provide TMF assistance

to all system sizes. For small systems that are disadvantaged, up to 30 percent of a State/Primacy

Agency’s DWSRF may be used for increased loan subsidies. Tribes have separate set-aside funding that

they can use under the DWSRF.

In addition to the DWSRF, money is available from the Department of Agriculture’s Rural Utility

Service (RUS) and Housing and Urban Development’s CDBG Program. RUS provides loans, guaranteed

loans, and grants to improve, repair, or construct water supply and distribution systems in rural areas and

towns with a population of up to 10,000 people. In fiscal year 2003, RUS had over $1.5 billion of

available funds for water and environmental programs. Also, three sources of funding exist under the

CDBG program to finance building and improvements of public faculties such as water systems. These 

include: 1) direct grants to communities with populations over 200,000; 2) direct grants to States/Primacy

Agencies, which in turn are awarded to smaller communities, rural areas, and coloñas in Arizona,

California, New Mexico, and Texas; and 3) direct grants to U.S. territories and trusts. The CDBG budget

for the formula program for fiscal year 2003 totaled over $4.4 billion.

7.7.2 Disproportionate Budgetary Effects

UMRA is intended to reduce the burden on State, Local, and Tribal governments of Federal

mandates that are not accompanied by adequate Federal funding. Section 202 of UMRA requires an

analysis of possible disproportionate budgetary effects of certain classes of rules, in which the GWR

falls.1

 EPA believes that the cost estimates presented in Exhibit 7.5 accurately characterize future

compliance costs of the GWR. EPA explored possible disproportionate impacts of the GWR on particular

geographic areas and groups of customers. In general, the costs that a PWS, whether publicly- or

privately-owned, will incur to comply with this rule will depend on many factors that are not generally
Economic Analysis for the 7-16 October 2006

Final Ground Water Rule

3 Percent 7 Percent 3 Percent 7 Percent

Non-tribal Systems 12.0 12.0 6.5 7.0

Tribal Systems 0.2 0.2 0 0

Total 12.2 12.1 6.5 7.1

Non-tribal Systems 4.8 4.8 0.1 0.1

Tribal Systems 0.0 0.0 0 0

Total 4.9 4.8 0.1 0.1

Non-tribal Systems 26.3 26.4 0.1 0.1

Tribal Systems 0.0 0.0 0 0

Total 26.3 26.4 0.1 0.1

Grand Total 43.4 $ 43.4 $ 6.7 $ 7.2 $ 

TNCWSs

Source Water Category

CWSs

NTNCWSs

Annualized Cost to 

Systems Serving 

≤ 10,000 People 

($ Millions)

Annualized Cost to 

Systems Serving 

> 10,000 People 

($ Millions)

based on location. However, the data needed to confirm this assessment and to analyze other impacts of

this problem are not available; therefore, EPA looked at two other factors:

• The impacts of the rule on small versus large systems and the impacts within the five

small system size categories

• The costs to publicly-owned versus privately-owned water systems

It is also possible that some States or EPA regions may face greater challenges from the GWR

than other States or regions because they have comparatively more ground water systems. However,

costs are not expected to be highly focused on a particularly geographic region or sector. In addition,

States that have a larger percentage of systems also receive a greater share of money under the PWSS

Grants Program and the DWSRF. 

One measure performed of disproportionate impact is the cost incurred by small and large

systems. As a group, small systems will experience a greater impact than large systems under the GWR. 

The higher total cost to the small ground water systems is due to the large number of these types of

systems (i.e., 99 percent of ground water systems serve fewer than 10,000 people). Other reasons for the

disparity include the following: 1) large systems are more likely to already be disinfecting their ground

water (disinfection exempts a system from triggered monitoring); 2) they typically have greater technical

and operational expertise; and 3) they are more likely to engage in source protection programs. The total

impacts on small systems (those serving fewer than 10,000 people) as well as large and medium systems

(those serving at least 10,000) are presented in Exhibit 7.5 for 3 percent and 7 percent discount rates. 

Exhibit 7.5 Annualized Compliance Costs by Type of Ground Water System

Source: Total Costs from Appendix D minus Tribal Costs; Tribal Costs calculated from 

Appendix D.

The mean cost per system for compliance is shown for large and small systems in Exhibit 7.6. The

cost per system is greater for larger systems, due to increased costs of disinfection and other costs that

increase with the size of the system. Among the small systems, the potential system-level economic

impact will be the greatest for systems serving 3,301 to 10,000 people.
Economic Analysis for the 7-17 October 2006

Final Ground Water Rule

System Size CWSs NTNCWSs TNCWSs

≤100 $ 187 226 $ 275 $ 

101-500 251 $ 275 $ 372 $ 

501-1,000 312 $ 354 $ 506 $ 

1,001-3,300 331 $ 646 $ 721 $ 

3,301-10,000 773 $ 1,361 $ 1,741 $ 

10,001-50,000 1,973 $ 3,769 $ 4,127 $ 

50,001-100,000 10,622 $ 5,813 $ 5,320 $ 

100,001-1 Million 18,369 $ 8,383 $ 11,921 $ 

>1 Million 14 $ - $ - $ 

Exhibit 7.6 Mean Annualized Compliance Cost per Ground Water System by

System Size and Type

 Source: Derived from Appendix D.

A second measure of impact performed on small systems is the total cost to privately-owned

water systems compared to that incurred by publicly-owned water systems. Exhibit 7.3 reveals that 55

percent of small system compliance costs are borne by publicly-owned PWSs, while 45 percent is borne

by privately-owned PWSs. This difference results from the fact that more than 55 percent of small PWSs

using ground water are owned by public entities. EPA, therefore, expects publicly-owned systems as a

group to have a slightly larger share of the total costs of the rule, but it does not expect cost per system to

differ systematically with ownership. Most importantly, the rule protects the health of customers of all

covered drinking water systems regardless of the size or type of system.

7.7.3 Macroeconomic Effects

Under UMRA Section 202, EPA is required to estimate the potential macroeconomic effects of

the regulation. These include effects on productivity, economic growth, full employment, and Gross

Domestic Product (GDP) (USEPA 2000e). Macroeconomic effects tend to be measurable in nationwide

econometric models only if the economic impact of the regulation reaches 0.25 percent to 0.5 percent of

GDP. In 2003, real GDP was $10,321 billion (U.S. Department of Commerce BEA 2004); thus, a rule

would have to cost at least $26 billion annually to have a measurable effect. A regulation with a smaller

aggregate effect is unlikely to have any measurable impact, unless it is highly focused on a particular

geographic region or economic sector. The GWR should not have a measurable effect on the national

economy; the total annualized costs for the rule range from $61.8 to $62.3 million using a 3 and 7 percent

discount rate, respectively. Using these annualized figures as a measure, the annual cost of the GWR is

an insignificant fraction of a $26 billion annual cost that would be considered a measurable

macroeconomic impact. Thus, annualized GWR costs measured as a percentage of the national GDP will

only decline over time as GDP grows. 
Economic Analysis for the 7-18 October 2006

Final Ground Water Rule

7.7.4 Consultation with Small Governments

Before the Agency establishes any regulatory requirements that may significantly or uniquely

affect small governments, including Tribal governments, it must have developed, under Section 203 of

UMRA, a small government agency plan. The plan must provide for the notification of potentially

affected small governments, enabling officials of affected small governments to have meaningful and

timely input in the development of EPA regulatory proposals with significant Federal intergovernmental

mandates and informing, educating, and advising small governments on compliance with the regulatory

requirements. EPA consulted with small governments to address impacts of regulatory requirements in

the GWR that might significantly or uniquely affect small governments. A variety of stakeholders,

including small governments, were provided with several opportunities to participate early in the

regulatory development process, as described in section 7.4.

7.7.5 Consultation with State, Local, and Tribal Governments

Section 204 of UMRA requires the Agency to develop an effective process to permit elected

officers of State, Local, and Tribal governments (or their designated authorized employees) to provide

meaningful and timely input in the development of regulatory proposals that contain significant Federal

intergovernmental mandates. Consistent with these provisions, EPA held consultations with affected

governmental entities prior to proposal of the rule, as described in sections 7.4 and 7.7. EPA conducted

four public meetings for all stakeholders and two Association of State Drinking Water Administrators

(ASDWA) early involvement meetings. Because of the GWR’s impact on small entities, the Agency

convened a SBAR Panel in accordance with the RFA as amended by the SBREFA to address small entity

concerns, including small local governments specifically. EPA consulted with small entity stakeholders

prior to convening the SBAR Panel to get their input on the GWR. Of the 22 small entity participants,

five represented small governments. EPA also made presentations on the GWR to the national and local

chapters of the American Water Works Association, the Ground Water Foundation, the National Ground

Water Association, the National Rural Water Association, and the National League of Cities. Twelve

State drinking water representatives also participated in the Agency’s GWR workgroup.

In addition to these consultations, EPA circulated a draft of the proposed rule and requested

comment from the public through an informal process. Specifically, on February 3, 1999, EPA posted a

draft proposal on their webpage and mailed out over 300 copies to people who had attended the 1997 and

1998 public stakeholder meetings, as well as people on the EPA workgroup. EPA received 79 letters or

electronic responses to this draft: 34 from State governments (representing 30 different States), 25 from

local governments, 10 from trade associations, 6 from Federal government agencies, and 4 from other

people/organizations. No comments were received from Tribal governments. EPA reviewed the

comments and carefully considered their merit. The GWR reflects many of the commentors’ points and

suggestions. 

EPA will educate, inform, and advise small systems, including those operated by small

governments, about the GWR requirements. One of the most important components of this process will

be the Small System GWR Implementation Guidance, which is required by SBREFA of 1996. This

plain-English guide will explain what actions a small entity must take to comply with the rule. The

Agency is also developing fact sheets that concisely describe various aspects and requirements of the

GWR. Additional details on Tribal involvement in the rulemaking process can be found in section 7.7.
Economic Analysis for the 7-19 October 2006

Final Ground Water Rule

7.7.6 Regulatory Alternatives Considered

As required under Section 205 of UMRA, EPA considered several regulatory alternatives and

numerous methods that would reduce microbial contamination in ground water systems. Chapter 3

provides a detailed discussion of these alternatives. EPA believes that Alternative 2, the risk targeted

approach, is the most cost effective alternative that achieves the rule’s objective to reduce the risk of

illness and death from microbial contamination in PWSs relying on ground water. This alternative is a

targeted approach where costs are driven by the number of systems having to fix fecal contamination

problems and correct significant deficiencies that could lead to fecal contamination. 

7.7.7 Impacts on Small Governments

In developing this rule, EPA consulted with small governments pursuant to Section 203 of

UMRA to address impacts of regulatory requirements in the rule that might significantly or uniquely

affect small governments. In preparation for the GWR, EPA conducted an analysis on small government

impacts and included small government officials or their designated representatives in the rulemaking

process. A variety of stakeholders, including small governments, had the opportunity for timely and

meaningful participation in the regulatory development process through the SBREFA process, public

stakeholder meetings, and Tribal meetings. Representatives of small governments took part in the

SBREFA process for this rulemaking and attended public stakeholder meetings. Through participation

and exchange in the SBREFA process and various meetings, EPA notified some potentially affected small

governments of requirements under consideration and provided officials of affected small governments

with an opportunity to have meaningful and timely input into the development of regulatory proposals. 

EPA has determined that this rule contains regulatory requirements that might significantly or

uniquely affect small governments. As shown in Exhibit 7.6, estimated annual expenditures per small

system for the GWR range from $226 to $773 for CWSs, $187 to $1,361 for NTNCWSs, and $275 to

$1,741 for TNCWSs (at a 3 percent discount rate).

7.8 Indian Tribal Governments

Executive Order 13175, entitled “Consultation and Coordination with Indian Tribal

Governments” (65 FR 67249; November 6, 2000), requires EPA to develop “an accountable process to

ensure meaningful and timely input by Tribal officials in the development of regulatory policies that have

Tribal implications.” The Executive Order defines “policies that have Tribal implications” to include

regulations that have “substantial direct effects on one or more Indian Tribes, on the relationship between

the Federal government and the Indian Tribes, or on the distribution of power and responsibilities

between the Federal government and Indian Tribes.” 

Under Executive Order 13175, EPA may not issue a regulation that has Tribal implications, that

imposes substantial direct compliance costs, and that is not required by statute, unless the Federal

government provides the funds necessary to pay the direct compliance costs incurred by Tribal

governments, or EPA consults with Tribal officials early in the process of developing the proposed

regulation and develops a Tribal summary impact statement.

EPA performed an analysis to estimate the impact of the GWR on Tribal systems. More than 87

percent of PWSs in Indian Country (727 systems) are ground water systems and will, therefore, be

affected by the GWR. Based on the analysis, EPA concluded that the GWR may have Tribal implications

because it may impose substantial direct compliance costs on Tribal governments, and the Federal
Economic Analysis for the 7-20 October 2006

Final Ground Water Rule

government will not provide the funds necessary to pay the direct costs incurred by the Tribal

governments in complying with the rule. Accordingly, EPA provides the following Tribal summary

impact statement as required by Section 5(b) of Executive Order 13175. 

As described in section 7.5.5, EPA held extensive public meetings that provided tribes with the

opportunity for meaningful and timely input into the development of the GWR. Summaries of the

meetings have been included in the public docket for this rulemaking. In addition, the Agency presented

the rule and asked for comment at three Tribal conferences. Two outreach efforts were conducted at

national conferences; one for the National Indian Health Board and the other for the National Tribal

Environmental Council. The third outreach effort took place in conjunction with the Inter-Tribal Council

of Arizona, Inc.

Tribal Summary Impact Statement

EPA performed an analysis to estimate the impact of the GWR on Tribal systems. EPA has

identified 727 Indian Tribal systems that might be subject to the GWR. As seen in Exhibit 7.7, all but

three Tribal systems are classified as small systems (serving fewer than 10,000 people).
Economic Analysis for the 

Final Ground Water Rule 7-21 

% No. % No. % No. % No. % No. % No. % No.

A B C = B * A D E = D * A F G = F * A H I = H * A J K = J * A L M = L * A N O = N * A 

Primarily Disinfecting Ground Water CWSs

≤100 171 100% 171 100% 171 0% 0 76% 130 0% 0 24% 42 31% 53 

$ 

101-500 223 100% 223 100% 223 0% 0 62% 138 0% 0 24% 53 45% 100 

$ 

501-1,000 69 100% 69 100% 69 0% 0 61% 42 0% 0 24% 16 46% 32 

$ 

1,001-3,300 69 100% 69 100% 69 0% 0 63% 43 0% 0 22% 15 42% 29 

$ 

3,301-10,000 21 100% 21 100% 21 0% 0 62% 13 0% 0 24% 5 45% 9 

$ 

10,001-50,000 3 NA NA NA NA NA NA NA NA NA NA NA NA NA NA 

$ 

50,001-100,000 0 NA NA NA NA NA NA NA NA NA NA NA NA NA NA 

$ 

100,001-1 Million 0 NA NA NA NA NA NA NA NA NA NA NA NA NA NA 

$ 

> 1 Million 0 NA NA NA NA NA NA NA NA NA NA NA NA NA NA 

$ 

Subtotal 556 553 553 0 367 0 132 224 

Primarily Disinfecting Ground Water NTNCWSs

≤100 34 100% 34 100% 34 0% 0 91% 31 0% 0 24% 8 16% 6 

$ 

101-500 28 100% 28 100% 28 0% 0 91% 25 0% 0 25% 7 17% 5 

$ 

501-1,000 13 100% 13 100% 13 0% 0 91% 12 0% 0 25% 3 17% 2 

$ 

1,001-3,300 21 100% 21 100% 21 0% 0 91% 19 0% 0 29% 6 21% 4 

$ 

3,301-10,000 2 100% 2 100% 2 0% 0 91% 2 0% 0 31% 1 23% 0 

$ 

10,001-50,000 0 100% 0 100% 0 0% 0 91% 0 0% 0 33% 0 25% 0 

$ 

50,001-100,000 0 NA NA NA NA NA NA NA NA NA NA NA NA NA NA 

$ 

100,001-1 Million 0 NA NA NA NA NA NA NA NA NA NA NA NA NA NA 

$ 

> 1 Million 0 NA NA NA NA NA NA NA NA NA NA NA NA NA NA 

$ 

Subtotal 98 98 98 0 89 0 25 17 

Primarily Disinfecting Ground Water TNCWSs

≤100 57 100% 57 100% 57 0% 0 98% 56 0% 0 28% 16 13% 7 

$ 

101-500 11 100% 11 100% 11 0% 0 98% 11 0% 0 28% 3 12% 1 

$ 

501-1,000 3 100% 3 100% 3 0% 0 98% 3 0% 0 28% 1 13% 0 

$ 

1,001-3,300 1 100% 1 100% 1 0% 0 98% 1 0% 0 30% 0 15% 0 

$ 

3,301-10,000 1 NA NA NA NA NA NA NA NA NA NA NA NA NA NA 

$ 

10,001-50,000 0 100% 0 100% 0 0% 0 98% 0 0% 0 35% 0 20% 0 

$ 

50,001-100,000 0 NA NA NA NA NA NA NA NA NA NA NA NA NA NA 

$ 

100,001-1 Million 0 NA NA NA NA NA NA NA NA NA NA NA NA NA NA 

$ 

> 1 Million 0 NA NA NA NA NA NA NA NA NA NA NA NA NA NA 

$ 

Subtotal 73 72 72 0 71 0 20 9 

TOTALS 727 723 723 0 527 0 177 250 

Systems 

Conducting 

Assessment 

Monitoring

System 

Size/Type

Number of 

Systems 

Affected 

by GWR

A

Systems 

Conducting 

Implementation 

Activities

Systems 

Conducting 

Santitary 

Surveys

Systems 

Conducting 

HSAs

Systems 

Conducting 

Triggered 

Monitoring

Sytems Taking 

Corrective 

Action

Systems 

Conducting 

Compliance 

Monitoring

Exhibit 7.7 Annual Cost of Compliance for Tribal Systems by System

Type and Size (Annualized at 3 Percent)

Source: Derived from Appendix D.
Economic Analysis for the 7-22 October 2006

Final Ground Water Rule

EPA has estimated costs for Indian Tribal systems to comply with the GWR, based on the

assumption that the percentages of systems expected to incur costs for each size category will be the same

for Tribal systems as for systems nationwide. The costs for Tribal systems are calculated in two steps. 

First, the number of Indian Tribal systems in each size category is multiplied by the percentage of systems

nationally in each size category expected to incur costs for various rule activities. Second, the average

cost of each rule requirement is multiplied by the number of Tribal systems expected to incur costs. 

Exhibit 7.7 shows the percentage of systems expected to incur costs for various compliance activities. 

These costs result in an estimated total annualized cost to Indian Tribes of $209,670 for the GWR.

7.9 Impacts on Sensitive Subpopulations

EPA’s Office of Water has historically considered risks to sensitive subpopulations (including

children) in establishing drinking water assessments, advisories or other guidance, and standards. 

Generally, the health effects of many pathogens and viruses on sensitive subpopulations is much more

severe and debilitating than on the general population. These sensitive subpopulations include the young,

elderly (especially those weakened by other conditions), malnourished and disease-impaired (especially

those with diabetes), and a broad category of those with compromised immune systems, such as Acquired

Immune Deficiency Syndrome (AIDS) patients, individuals with Lupus or cystic fibrosis, transplant

recipients, and individuals on chemotherapy (Rose 1997). In total, these subgroups represent almost 20

percent of the current population of the United States.

Pregnant and lactating women may be at an increased risk from enteric viruses as well as act as a

source of infection for neonates. Infection during pregnancy may also result in the transmission of

infection from the mother to the child in utero, during birth, or shortly thereafter. Since very young

children do not have fully developed immune systems, they are at increased risk and are particularly

difficult to treat.

Infectious diseases are also a major problem for the elderly because immune function declines

with age. As a result, outbreaks of waterborne diseases can be devastating on the elderly community

(e.g., nursing homes) and may increase the possibility of significantly higher mortality rates in the elderly

than in the general population. 

Immunocompromised individuals are a growing proportion of the population with the relatively

new and severe problem magnified by the AIDS epidemic and the escalation in organ and tissue

transplantations. Enteric pathogens take advantage of the impaired immune systems of these individuals

and set up generalized and persistent infections in the immunocompromised host. These infections are

particularly difficult to treat and can result in a significantly higher mortality than in immunocompetent

persons.

With regard to sensitive sub-populations, EPA explicitly examined the effects of the GWR on

young children, the elderly, and immunocompromised individuals. Exhibit 5.24 in Chapter 5 shows the

estimated number of illnesses and deaths avoided in each of these categories and the values of the

associated benefits. In addition to the information presented in Chapter 5 of this EA, research outlining

the potential health benefits of the GWR to both sensitive subpopulations and the general public is

discussed in greater detail in the Occurrence and Monitoring Document for the Final Ground Water Rule

(USEPA 2006b). 
Economic Analysis for the 7-23 October 2006

Final Ground Water Rule

7.9.1 Protection of Children from Environmental Health Risks and Safety Risks

Executive Order 13045 (62 FR 19885; April 23, 1997) applies to any rule initiated after April 21,

1998, that (1) is determined to be “economically significant” as defined under Executive Order 12866;

and (2) concerns an environmental, health, or safety risk that EPA has reason to believe may have a

disproportionate effect on children. If the regulatory action meets both criteria, EPA must evaluate the

environmental, health, or safety effects of the planned rule on children, and explain why the planned

regulation is preferable to other potentially effective and reasonably feasible alternatives considered by

the Agency. This final rule is not subject to the Executive Order because it is not economically

significant as defined in Executive Order 12866. As a matter of policy, EPA has examined the

environmental health or safety effects of viruses on children. 

The risk of illness and death due to viruses depends on several factors, including the type of virus,

age, nutrition, exposure, genetic variability, presence of disease, and the immune status of the individual. 

Rotavirus infections can occur in people of all ages, but they primarily affect young children. In addition,

infants and young children have higher rates of infection and disease from enteroviruses than other age

groups (USEPA 1999). Several viruses that can be transmitted through water, including poliovirus,

coxsackievirus, and echovirus, can have serious health consequences in children, which are discussed in

detail in Chapter 5. 

In developing the risk and benefits analysis for the GWR, the effects on children, both in terms of

unique risk and cost-of-illness estimates, were explicitly taken into consideration, as discussed in Chapter

5 of this EA. This analysis suggests that the rule provides a greater per capita health benefit to children

than to adults, mostly due to the high cost-of-illness associated with viral illnesses avoided in young

children. In other words, the analysis suggests that the viral and bacterial illnesses of concern to the

GWR disproportionately affect children, and therefore, the benefits of the proposed rule accrue

disproportionately to children.

7.10 Environmental Justice

Executive Order 12898 (59 FR 7629) establishes a Federal policy for incorporating

environmental justice into Federal agency missions by directing agencies to identify and address

disproportionately high adverse human health or environmental effects of its programs, policies, and

activities on minority and low-income populations. The Agency has considered environmental justice

related issues concerning the potential impacts of this action and consulted with minority and low-income

stakeholders.

Two aspects of the GWR comply with the order that requires the Agency to consider

environmental justice issues in the rulemaking and to consult with stakeholders representing a variety of

economic and ethnic backgrounds. These are: (1) the overall nature of the rule, and (2) the convening of

a stakeholder meeting specifically to address environmental justice issues. 

The GWR applies uniformly to CWSs, NTNCWSs, and TNCWSs that use ground water as their

source. Consequently, this rule provides health protection from pathogen exposure equally to all income

and minority groups served by ground water systems. Existing regulations, such as the Surface Water

Treatment Rule (SWTR) and the Interim Enhanced Surface Water Treatment Rule (IESWTR), provide

similar health benefit protection to communities that use surface water or GWUDI.

The Agency built on the efforts conducted during the IESWTR’s development to comply with

Executive Order 12898. On March 12, 1998, the Agency held a stakeholder meeting to address various
Economic Analysis for the 7-24 October 2006

Final Ground Water Rule

components of pending drinking water regulations and how they might impact sensitive subpopulations,

minority populations, and low-income populations. This meeting was a continuation of stakeholder

meetings that started in 1995 to obtain input on the Agency’s Drinking Water Programs. Topics

discussed included treatment techniques, costs and benefits, data quality, health effects, and the regulatory

process. Participants were national, State, Tribal, municipal, and individual stakeholders. EPA

conducted the meeting by video conference call among 11 cities. The major objectives for the March 12,

1998 meeting included the following:

• Solicit ideas from stakeholders on known issues concerning current drinking water regulatory

efforts.

• Identify key areas of concern to stakeholders.

• Receive suggestions from stakeholders concerning ways to increase representation of

communities in OGWDW regulatory efforts.

In addition, EPA developed a plain-English guide for this meeting to assist stakeholders in

understanding the multiple and sometimes complex issues surrounding drinking water regulations.

The GWR and other drinking water regulations are expected to have a positive effect on human

health regardless of the social or economic status of a specific population. The GWR serves to provide a

similar level of drinking water protection to all groups. To the extent that levels of bacteria and viruses in

drinking water might be disproportionately high now among minority or low-income populations (which

is unknown), the GWR will work to remove those differences. Thus, the GWR meets the intent of

Federal policy requiring incorporation of environmental justice into Federal agency missions.

The GWR applies uniformly to PWSs that use ground water as their source. Consequently, this

rule provides health protection from pathogenic bacteria and viruses exposure equally to all income and

minority groups served by ground water systems.

7.11 Federalism

Executive Order 13132, “Federalism” (64 FR 43255; August 10, 1999), requires EPA to develop

an accountable process to ensure “meaningful and timely input by State and Local officials in the

development of regulatory policies that have Federalism implications.” “Policies that have Federalism

implications” are defined in the Executive Order to include regulations that have “substantial direct

effects on the States, on the relationship between the national government and the States, or on the

distribution of power and responsibilities among the various levels of government.” 

Under Section 6(b) Executive Order 13132, EPA may not issue a regulation that has Federalism

implications, that imposes substantial direct compliance costs, and that is not required by statute, unless

the Federal government provides the funds necessary to pay the direct compliance costs incurred by State

and Local governments, or EPA consults with State and Local officials early in the process of developing

the proposed regulation. 

If EPA complies by consulting, Executive Order 13132 requires EPA to provide to OMB, in a

separately identified section of the preamble to the final rule, a Federalism Summary Impact Statement

(FSIS). The FSIS must include a description of the extent of EPA’s prior consultation with State and

Local officials, a summary of the nature of their concerns, and the Agency’s position supporting the need

to issue the regulation, and a statement of the extent to which the concerns of State and Local officials
Economic Analysis for the 7-25 October 2006

Final Ground Water Rule

have been met. Also, when EPA transmits a draft final rule with Federalism implications to OMB for

review pursuant to Executive Order 12866, EPA must include a certification from the Agency’s

Federalism Official stating that EPA has met the requirements Executive Order 13132 in a meaningful

and timely manner.

EPA has concluded that this rule does not have Federalism implications because it does not

impose substantial direct compliance costs on State and Local governments. The cost to State, Local, and

Tribal governments in the aggregate is $41.5 million (see Exhibit 7.3) on average annually at a 3 percent

discount rate. 

Nonetheless, as discussed in section 7.5.4, EPA met with a variety of State and Local

representatives, including several local elected officials, who provided meaningful and timely input in the

development of the GWR. Summaries of the meetings have been included in the public record for this

rulemaking. EPA consulted extensively with State and Local governments. For example, four public

stakeholder meetings were held in Washington, DC, Portland, OR, Madison, WI, and Dallas, TX. EPA

also held three early involvement meetings with ASDWA. Several key issues were raised by stakeholder

regarding the GWR provisions, many of which were related to reducing burden and increasing flexibility

by creating a targeted risk based approach that builds upon existing State programs. Its should be noted

that this rule is important because it will reduce the incidence of fecally contaminated drinking water

supplies by requiring corrective actions for fecally contaminated systems or systems with a significant

risk of fecal contamination resulting in a reduced waterborne illness.

Initial consultation of the GWR occurred before November 2, 1999, the effective date of

Executive Order 13132. However, EPA initiated discussions with State and Local elected officials

regarding the implications of the rule during the public comment period and took their recommendations

under consideration during the development of the final rule requirements.

7.12 Actions Concerning Regulations That Significantly Affect Energy Supply,

Distribution, or Use

Executive Order 13211, “Actions Concerning Regulations That Significantly Affect Energy

Supply, Distribution, or Use” (66 FR 28355; May 22, 2001), provides that agencies shall prepare and

submit to the Administrator of the Office of Information and Regulatory Affairs, OMB, a Statement of

Energy Effects for certain actions identified as “significant energy actions.” Section 4(b) of Executive

Order 13211 defines “significant energy actions” as “any action by an agency (normally published in the

Federal Register) that promulgates or is expected to lead to the promulgation of a final rule or regulation,

including notices of inquiry, advance notices of proposed rulemaking, and notices of proposed

rulemaking: (1)(i) that is a significant regulatory action under Executive Order 12866 or any successor

order, and (ii) is likely to have a significant adverse effect on the supply, distribution, or use of energy; or

(2) that is designated by the Administrator of the Office of Information and Regulatory Affairs as a

significant energy action.”

The GWR has not been designated by the Administrator of the Office of Information and

Regulatory Affairs as a significant energy action because it is not likely to have a significant adverse

effect on the supply, distribution, or use of energy. This determination is based on the analysis presented

below. 
2 EPA is aware that DOE has updated its 2003 “average national cost of electricity per kilowatt hour per

year” from $0.076 to $0.074. However, EPA continues to use the $0.076 value to maintain consistency with the

Technology and Cost Document for the Final Ground Water Rule (USEPA 2006d). 

Economic Analysis for the 7-26 October 2006

Final Ground Water Rule

Energy Supply

The first consideration is whether the GWR would adversely affect the supply of energy. The

GWR does not regulate power generation, either directly or indirectly, and the public and private PWSs

that the GWR regulates do not, as a rule, generate power. Further, the cost increases borne by customers

of PWSs as a result of the GWR are a low percentage of the total cost of water, except for very few small

systems that will need to spread the cost of installing advanced technologies over a narrow customer base. 

Therefore, the customers that are power generation utilities are unlikely to face any significant effects as a

result of the GWR. In summary, the GWR does not regulate the supply of energy, does not generally

regulate the utilities that supply energy, and is unlikely to significantly affect the customer base of energy

suppliers. Thus, the GWR would not adversely affect the supply of energy.

In response to the GWR, some water utilities are expected to increase their energy use, and those

impacts are discussed later in this section.

Energy Distribution

The second consideration is whether the GWR would adversely affect the distribution of energy. 

The GWR does not regulate any aspect of energy distribution. PWSs that are regulated by the GWR

already have electrical service. The rule is projected to increase peak electricity demand at PWSs by only

0.001 percent (see below). Therefore, EPA assumes that the existing connections are adequate and that

the GWR has no discernable adverse effect on energy distribution.

Energy Use

The third consideration is whether the GWR would adversely affect the use of energy. Because

some PWSs are expected to add treatment technologies and security that use electrical power, this

potential impact of the GWR on the use of energy requires further evaluation. The analyses that underlay

the estimation of costs in Chapter 6 are national in scope and do not identify specific plants or systems

that may install treatment in response to the GWR. As a result, no analysis of the effect on specific

energy suppliers is possible with the available data. The approach used to estimate the impact of energy

use, therefore, focuses on national-level impacts. It estimates the additional energy use due to the GWR

and compares that to the national levels of power generation in terms of average and peak loads.

The first step is to estimate the energy used by the technologies or corrective action expected to be

installed as a result of the GWR. Energy use is not directly estimated in Technology and Cost Document

for the Final Ground Water Rule (USEPA 2006d), but the annual cost of energy for each technology and

corrective action addition or upgrade necessitated by the GWR is provided. An estimate of plant-level

energy use is derived by dividing the total energy cost per plant for a range of flows by an average national

cost of electricity of $0.076 per kilowatt hour per year (kWh/y) (USDOE EIA 2004a2

). The energy use per

plant for each flow range and technology or corrective action is then multiplied by the number of plants
3

 EPA is aware that DOE has updated its estimate of total electricity produced in 2003 from 3,848 million

to 3,883 million. However, EPA continues to use the 3,848 million estimate to maintain consistency with related

electricity estimates used in this EA and the Technology and Cost Document for the Final Ground Water Rule.

Economic Analysis for the 7-27 October 2006

Final Ground Water Rule

Technology/Corrective Action

Plants Selecting 

Technology

Total Annual 

Energy Required 

(kWh/yr)

A B

Gas Chlorination 177 190,099 

Hypochlorination 3,565 3,726,479 

ClO2 11,928 39 

Anodic Oxidation 16 95,342 

Ozonation 0 17,229 

NF 10 479,477 

Total 3,808 4,520,555 

predicted to install each technology in a given flow range. The energy requirements for each flow range

are then added to produce a national total. No electricity use is subtracted to account for the technologies

that may be replaced by new technologies, resulting in a conservative estimate of the increase in energy

use. An incremental national annual energy usage is estimated at 4,521 megawatt hours (MWh); results of

the analysis are shown in Exhibit 7.8. 

Exhibit 7.8 Total Increased Annual National Energy Usage 

Attributable to the GWR

Sources: 

[A] Plants selecting technology taken from Exhibits 6.5b and 6.21b.

[B] ClO2, Ozonation, and NF - Total annual energy required calculated from energy costs 

given in the Technology and Cost Document for the Final Ground Water Rule

(USEPA 2006d) assuming $0.076/kWh. Gas Chlorination, Hypochlorination, and Anodic 

Oxidation - Total annual energy required obtained from the Water and W/W Models.

Exhibit 7.9 provides a sample calculation for chlorine dioxide showing the increase in energy

usage as a result of the GWR.

To determine if the additional energy required for systems to comply with the rule would have a

significant adverse effect on the use of energy, the numbers in Exhibit 7.9 are compared to the national

production figures for electricity. According to the U.S. Department of Energy’s Information

Administration, electricity producers generated 3,848 million MWh of electricity in 2003 (USDOE EIA

2004b3

). Using the assumed energy use for the GWR (4,520,555 kWh/y), the rule would result in only a

0.0001 percent increase in annual average energy use when fully implemented. This calculation is shown

below:

4,521 MWh/y ÷ 3,848,000,000 MWh/y * 100 = 0.0001%
Economic Analysis for the 7-28 October 2006

Final Ground Water Rule

Average Daily Flow Total No. Number of Annual Energy Annual Energy Total Energy Usage for 

Flow of Entry Points Cost per Entry Point Requirement Entry Points Selecting

(MGD) Entry Points Selecting ($/EP/yr) (kWhr/EP/yr) (kWhr/year)

A B C D

E = D/$0.076 per 

kWhr F=C*E

CWSs

< 100 12,857 0.004 3 - - - 

101 - 500 0.014 14,534 3 - - - 

501 - 1,000 0.037 5,536 - 261 3,437 - 

1,001 - 3,300 0.081 8,966 - 261 3,437 - 

3,301 - 10,000 0.199 5,734 - 261 3,437 - 

10,001 - 50,000 0.441 4,257 0 262 3,444 1,114 

50,001 - 100,000 0.718 1,308 1 263 3,455 4,919 

100,001 - 1 Million 2.263 730 - 272 3,576 - 

> 1 Million 18.107 - - 378 4,973 - 

NTNCWSs

< 100 8,606 0.004 2 - - - 

101 - 500 0.022 6,150 2 261 3,437 5,839 

501 - 1,000 0.071 1,724 - 261 3,437 - 

1,001 - 3,300 0.175 651 - 261 3,437 - 

3,301 - 10,000 0.637 66 - 262 3,452 - 

10,001 - 50,000 2.856 9 0 276 3,626 14 

50,001 - 100,000 9.918 1 0 310 4,080 6 

100,001 - 1 Million 17.188 1 - 370 4,868 - 

> 1 Million - - - - - - 

TNCWSs

< 100 63,288 0.003 21 - - - 

101 - 500 0.017 18,651 7 - - - 

501 - 1,000 0.068 1,905 - 261 3,437 - 

1,001 - 3,300 0.159 574 - 261 3,437 - 

3,301 - 10,000 0.619 73 - 262 3,451 - 

10,001 - 50,000 2.124 19 0 273 3,587 31 

50,001 - 100,000 7.649 1 0 297 3,908 6 

100,001 - 1 Million 19.724 1 - 416 5,475 - 

> 1 Million - - - - - - 

TOTALS 155,641 39 75,392 11,928 

System Size 

(population 

served)

Exhibit 7.9 Sample Calculation for Determining Increase in Energy Usage:

Chlorine Dioxide (ClO2 Dose = 1.25 mg/L)

Notes: Detail may not add due to independent rounding. 

Sources: [A] Flows taken from Exhibit 4.6

[B] Total number of entry points taken from Exhibit 4.3

[C] Number of entry plants selecting chlorine dioxide taken from Exhibit 6.21b

[D] Energy cost per entry point interpolated from ClO2 energy costs in the Technology and Cost Document

for the Final Ground Water Rule (USEPA 2006d)

[E] Electricity cost is $0.076/KWh, as presented in the Technology and Cost Document for the Final Ground

Water Rule (USEPA 2006d).
4 EPA is aware that DOE has updated its estimate of capacity exceeding consumption in the summer of

2003 from 160,000 to 159,000 MW. However, EPA continues to use the estimate of 160,000 MW to maintain

consistency with related electricity estimates used in this EA and the Technology and Cost Document for the Final

Ground Water Rule (USEPA 2006d).

Economic Analysis for the 7-29 October 2006

Final Ground Water Rule

In addition to average energy use, the impact at times of peak power demand is important. To

examine whether increased energy usage might significantly affect the capacity margins of energy

suppliers, their peak-season generating capacity reserve was compared to an estimate of peak incremental

power demand by water utilities. Both energy use and water use peak in the summer months, so the most

significant effects on supply would be seen then. During the summer of 2003, U.S. generation capacity

exceeded consumption by 15 percent, or approximately 160,000 MW (USDOE EIA 2004b4

). Assuming

around-the-clock operation of water treatment plants, the total energy requirement for technologies can be

divided by 8,760 hours per year. Twelve hours of operation per day was assumed for the of security

system light bulbs. The sum of these two average power demands was 0.52 MW. Assuming that power

demand is proportional to water flow through the plant and that peak flow can be as high as twice the

average daily flow during the summer months, about 1.03 MW could be needed for treatment technologies

and security installed to comply with the GWR. This is only 0.001 percent of the capacity margin

available at peak use. This calculation is presented below:

1. Treatment Technologies: 4,520,555 kWh/y * (y/8,760 hr) * (MW/1,000 kW) * 2 = 1.03 MW

2. 1.03 MW ÷ 160,000 MW * 100 = 0.001%

Although EPA recognizes that not all regions have a 15 percent capacity margin and that this

margin varies across regions and through time, this analysis reflects the effect of the rule on national

energy supply, distribution, and use. While certain areas have experienced shortfalls in generating

capacity in the recent past, a peak incremental power requirement of 1.03 MW nationwide is not likely to

significantly change the energy supply, distribution, or use in any given area.

Conclusion

The GWR is not a “significant energy action” as defined in Executive Order 13211, “Actions

Concerning Regulations That Significantly Affect Energy Supply, Distribution, or Use” (66 FR 28355;

May 22, 2001) because it is not likely to have a significant adverse effect on the supply, distribution, or

use of energy (as a function of annual average use and conditions of peak power demand). 

The total increase in energy usage by water systems as a result of the GWR is predicted to be

approximately 4.5 million kWh/y, which is only one-ten-thousandth of 1 percent of the total energy

produced in 2003. While the rule may have some adverse energy effects, EPA does not believe that this

constitutes a significant adverse effect on the energy supply.
Economic Analysis for the 8-1 October 2006

Final Ground Water Rule

8. Comparison of Quantified Benefits and Costs of the GWR

8.1 National Quantified Benefits and Costs of the GWR

This chapter presents a summary of the quantified benefits and costs of the Ground Water Rule

(GWR). The nonquantified benefits are summarized in Chapter 5, Section 5.4. EPA estimates that the

quantified benefits are small compared with the nonquantified benefits. In particular, EPA estimates that

the nonquantified benefits associated with bacterial illness would increase total benefits to about five

times the quantified benefits associated with viral illness from Type A virus (represented by data from

rotavirus) and Type B virus (represented by data from enterovirus and echovirus). Other non-bacterial

health and non-health benefits also accrue but are not quantified.

The following sections present summary results from the quantified economic analysis, followed

by a discussion of the results based on evaluation of the total benefits, both quantified and nonquantified. 

The first sections of this chapter focus on analysis of the final GWR, followed by a comparison of these

requirements to the other regulatory alternatives considered.

8.1.1 National Quantified Benefits Summary

The quantified benefits of the GWR derive from the reduction in risk of endemic, acute illness,

specifically the morbidity and mortality from viral illness attributable to consumption of drinking water

from the PWSs affected by the rule. The quantified acute viral illnesses are those associated with Type A

(represented by data from rotavirus) and Type B (represented by data from enterovirus and echovirus) and

are a subset of the total illnesses, both acute and chronic, from all waterborne bacteria and viruses.

The quantified benefits are presented in two forms. Exhibit 8.1 presents a summary of quantified

benefits in terms of the annual endemic, acute illnesses and deaths avoided after full implementation. 

Exhibit 8.2 monetizes estimates of endemic, acute illnesses and deaths avoided into annualized present

values using both the Enhanced and the Traditional COI approaches to allow comparison to cost

estimates. The mean annualized value of quantified benefits of reduced risk ranges from $8.6 million to

$19.7 million, depending on the COI approach and the discount rate used. 

There are substantial benefits attributable to the GWR that are not quantified within this EA as

part of the main analyses because of data limitations. Beneficial aspects of the rule not quantified are

characterized as either health benefits or non-health benefits. Nonquantified health-related benefits

include reducing other acute viral illness (other than those caused by rotavirus and enterovirus); endemic,

acute bacterial illnesses and deaths; and epidemic bacterial and viral acute illness and death (associated

with outbreaks, disinfection failures, and distribution system contamination). Chronic illness, both

bacterial and viral, are also not quantified. The rule will also result in many nonhealth benefits such as

reduced costs for responding to outbreaks, costs for averting behavior, and reduced uncertainly regarding

drinking water safety (see Exhibit 8.3). 
Economic Analysis for the 8-2 October 2006

Final Ground Water Rule

5th 95th 5th 95th

CWS 32,031 8,704 68,994 0.62 0.07 1.81

NTNCWS 2,094 533 4,308 0.03 0.00 0.09

TNCWS 7,743 1,037 14,738 0.09 0.01 0.21

Total 41,868 10,274 88,039 0.74 0.08 2.11

Source: Appendix C

Note: Detail may not add due to independent forecasting. Values presented are average annual illnesses and deaths 

avoided over the 25 year period of analysis following rule promulgation. 

Annual Viral Illnesses Avoided Annual Viral Deaths Avoided

System Type Mean Mean 

90% Confidence Bounds 90% Confidence Bounds

Exhibit 8.1 Summary of Annual Avoided Viral Illnesses and Deaths

by System Type

As mentioned above, there are substantial benefits attributable to the GWR that are not quantified

within this EA as part of the main analyses. These nonquantified benefits are shown in relation to

quantified benefits as part of the total benefits of the GWR in Exhibit 8.3. The nonquantified benefits

result from multiple factors. First, the quantified benefits are based on limited, well-defined data and key

assumptions that restrict the input parameters in the quantified benefit calculation. Typically, these

assumptions resulted in low mean values and narrow uncertainty ranges in the benefit analysis. This EA,

where applicable, discusses alternative assumptions. For example, the enterovirus morbidity fractions

are, by assumption, not determined using coxsackievirus (an enterovirus) data although the enterovirus

severity data use all enterovirus data. If coxsackievirus data were available, the mean morbidity values

would be greater. Choosing alternative values and ranges and differing key assumptions, which might

also be deemed reasonable, would increase the quantified benefits in this EA.

Second, the quantified benefits are based on data and assumptions that pertain to only partial

representation of Type A and Type B viruses potentially found in PWS wells with fecal contamination. 

Due to limited available data, only rotavirus and some enterovirus data were used to calculate the

quantified benefits. As is more completely discussed in Section 5.4. other viruses as well as pathogenic

bacteria may contribute to the disease burden, both acute and chronic, associated with PWS wells with

fecal contamination. Most importantly, bacterial illnesses can result in more frequent and lengthier

hospitalization and more frequently have fatal outcomes. If bacterial diseases were considered in the

quantified benefits, the monetized benefits could be substantially greater because bacterial disease can be

more severe and can result in higher mortality rates.

Third, the quantified benefits are based on data and assumptions that limit the characterization of

acute disease. For rotavirus, only acute gastroenteritis illness and fatal dehydration associated with that

illness are monetized. Norovirus disease is not considered. For the enteroviruses, all acute disease

endpoints are considered, but the prevalence of severe endemic cases may be substantially diluted by the

large number of hand, foot, and mouth disease cases that are not likely to be waterborne. Thus, the

proportion of severe cases in the quantitative benefits is likely to be underestimated. As is discussed more

completely in Section 5.4, in neither instance, either for rotavirus or the enteroviruses, are chronic

diseases identified or monetized in the quantitative benefits calculation.
Economic Analysis for the 8-3 October 2006

Final Ground Water Rule

Fourth, the quantified benefits are based explicitly on what has been directly measured in PWS

wells, yet there is great difficulty in identifying and counting all infectious viral pathogens in dilute

drinking water samples. Indeed, some viral pathogens like infectious norovirus can never be identified in

any sample. Section 4.3.2 discusses these difficulties in more detail. Standard fecal indicator data such

as total coliforms and E. coli, commonly used to identify water treatment deficiencies and potential

human health hazards, are explicitly not used to determine human exposure for the purposes of

quantifying the benefits in this EA.

Fifth, the quantified benefits are assumed to be based only on one contamination scenario, fecal

contamination of source water. Other contamination scenarios are thoroughly documented in the ground

water contamination and outbreak scientific literature. However, these scenarios, such as inadequate

disinfection, are not explicitly considered in calculating the quantified benefits in this EA.

Sixth, the quantified benefits are assumed to be based only on avoidance of endemic disease. The

GWR will likely also decrease the incidence of epidemic disease (outbreaks). If epidemic illnesses and

the avoided non-health-related costs of ground waterborne disease outbreaks were included, the

quantified benefits would increase.

In summary, this EA quantifies a subset of the total health and non-health related benefits. In a

sample calculation, discussed in Section 5.4.3.2, EPA estimated that the total benefits could increase by a

factor of five by only accounting for additional deaths and hospitalizations caused by bacterial illness

being avoided. While EPA recognizes that this estimate includes substantial uncertainty, given all the

other nonquantified factors described above, EPA believes that the total benefits from the GWR are likely

to be more than five times those which have been quantified. See Exhibit 8.5b for estimates of net

benefits that incorporate nonquantified benefits.
Economic Analysis for the 8-4 October 2006

Final Ground Water Rule

5th 95th 5th 95th

CWS 16.0 $ 5.4 $ 37.0 $ 13.7 $ 4.6 $ 31.6 $ 

NTNCWS 0.9 $ 0.3 $ 2.2 $ 0.8 $ 0.2 $ 1.8 $ 

TNCWS 2.7 $ 0.8 $ 6.2 $ 2.3 $ 0.7 $ 5.1 $ 

Total 19.7 $ 6.5 $ 45.4 $ 16.8 $ 5.5 $ 38.6 $ 

CWS 8.2 $ 1.9 $ 22.3 $ 7.1 $ 1.6 $ 19.1 $ 

NTNCWS 0.5 $ 0.1 $ 1.3 $ 0.4 $ 0.1 $ 1.0 $ 

TNCWS 1.3 $ 0.3 $ 3.4 $ 1.1 $ 0.2 $ 2.8 $ 

Total 10.0 $ 2.2 $ 27.0 $ 8.6 $ 1.9 $ 22.9 $ 

Source: Exhibit 5.23a, 5.23b 

Notes: Detail may not add due to independent rounding. The Traditional COI only includes valuation for medical costs and 

lost work time (including some portion of unpaid household production). The Enhanced COI also factors in valuations for 

lost personal time (non-work time) such as childcare and homemaking (to the extent not covered by the Traditional COI), 

time with family, and recreation, and lost productivity at work on days when workers are ill but go to work anyway. 

The figures presented in this exhibit represent only the quantifiable benefits of the GWR. The unquantified benefits are 

expected to comprise a significant portion of the overall benefits of the Rule and are presented in Section 5.4 of Ch. 5 of the

EA.

Enhanced COI

Traditional COI

System Type

Annualized Benefits

at 3% Discount Rate

Annualized Benefits

at 7% Discount Rate

Mean Mean 

90% Confidence Bounds 90%Confidence Bounds

Exhibit 8.2 Summary of Annualized Present Value Quantified Benefits

($Millions, 2003$)
Economic Analysis for the 8-5 October 2006

Final Ground Water Rule

Exhibit 8.3 Summary of Benefits of the GWR

Benefit Category Total Benefits GWR EA Quantified Benefits

Health Benefits

Reduction in

endemic illness

incidence

• viral exposure risk reduction (morbidity

and mortality)

• bacterial exposure risk reduction

(morbidity and mortality)

• chronic sequelae reduction

• reduction in secondary transmission of

viral or bacterial illness from

symptomatic and asymptomatic

individuals

• acute rotavirus (Type A) illnesses and

deaths avoided

• acute enterovirus (Type B) illnesses

and deaths avoided

• reduction in secondary transmission of

viral illness from symptomatic

individuals 

Reduction in epidemic (outbreak)

illness incidence

• viral exposure risk reduction (morbidity

and mortality)

• bacterial exposure risk reduction

(morbidity and mortality)

• chronic sequelae reduction

• reduction in secondary transmission of

viral or bacterial illness from

symptomatic and asymptomatic

individuals

Not quantified

Reduction in

treatment failures

Decreased illness through minimizing

treatment failures or fewer episodes with

inadequate treatment

Not quantified

Non-Health Benefits

Outbreak

responses avoided 

Avoided costs to affected water systems,

local governments (provision of alternate

water, issuing warnings and alerts), and

community (decreased tourism due to bad

press). 

Not quantified

Avoided costs of

averting behavior

• reduced need or perceived need to

use bottled water, point-of-use

devices, etc. (includes time and

material costs)

• less time spent on averting behavior:

hauling/boiling water, etc.

Not quantified

Increased

confidence

Perceived reduction in risk associated with

perceived improvement in drinking water

quality

Not quantified
Economic Analysis for the 8-6 October 2006

Final Ground Water Rule

5th 95th 5th 95th

CWS 18.7 $ 12.4 $ 26.3 $ 19.2 $ 13.0 $ 26.9 $ 

NTNCWS 4.9 $ 3.3 $ 6.8 $ 4.9 $ 3.4 $ 6.7 $ 

TNCWS 26.4 $ 18.6 $ 35.7 $ 26.5 $ 18.8 $ 35.5 $ 

States 11.8 $ 10.9 $ 12.6 $ 11.7 $ 10.9 $ 12.6 $ 

Total 61.8 $ 45.2 $ 81.4 $ 62.3 $ 46.1 $ 81.6 $ 

Source: Exhibits 6.33 and 6.34 

Notes: Detail may not add due to independent rounding.

System Type

Annualized Costs

at 3% Discount Rate

Annualized Costs

at 7% Discount Rate

Mean Mean 

90% Confidence Bounds 90%Confidence Bounds

8.1.2 National Cost Summary

The national annual cost of the GWR results from activities associated with rule implementation,

sanitary surveys, triggered source water monitoring, corrective actions, and compliance monitoring. The

estimated annualized cost of the GWR is $61.8 million at a three percent discount rate and $62.3 million

at a seven percent discount rate. Exhibit 8.4 presents these costs further broken out by system type.

Exhibit 8.4 Summary of Quantified Costs, Final Rule ($Millions, 2003$)

8.1.3 Comparison of National Quantified Benefits and Costs

Exhibit 8.5a compares estimated quantified benefits with estimated costs. Based on the

comparison of these values, the estimated quantified benefits of the rule range from approximately onethird to about one-seventh of the value of the costs, depending on the discount rate and COI approach. 

The estimated quantified benefits for the Enhanced COI approach are greater than the corresponding

estimated benefits for the Traditional COI approach. The quantified estimate of the benefits significantly

understates the true benefit of the rule. As discussed in Section 8.1.1 and Exhibit 8.3, the nonquantified

health and non-health benefits far exceed those that EPA was able to quantify, and are the primary basis

for supporting the preferred regulatory alternative. Section 5.4.3 of the EA discusses the potential value

of nonquantified benefits, in particular avoided bacterial illnesses and deaths, which would significantly

increase the net benefits of the final GWR. Exhibit 8.5b presents these estimates based on primary

benefits using the Enhanced COI approach.
Economic Analysis for the 8-7 October 2006

Final Ground Water Rule

5th 95th 5th 95th

Benefits 19.7 $ 6.5 $ 45.4 $ 16.8 $ 5.5 $ 38.6 $ 

Costs 61.8 $ 45.2 $ 81.4 $ 62.3 $ 46.1 $ 81.6 $ 

Net Benefits (42.1) $ Note 1 Note 1 (45.5) $ Note 1 Note 1

Benefits 10.0 $ 2.2 $ 27.0 $ 8.6 $ 1.9 $ 22.9 $ 

Costs 61.8 $ 45.2 $ 81.4 $ 62.3 $ 46.1 $ 81.6 $ 

Net Benefits (51.8) $ Note 1 Note 1 (53.7) $ Note 1 Note 1

Decreased incidence of other acute viral disease endpoints

Decreased incidence of bacterial illness and death

Decreased incidence of chronic bacterial and viral illness sequelae

Decreased incidence of waterborne disease outbreaks and epidemic illness

Decreased illness through minimizing treatment failures or fewer episodes with inadequate treatment

Decreased use of bottle water and point-of-use devices (material costs)

Decreased time spent on averting behavior

Avoided costs associated with outbreak response

Perceived improvement in drinking water quality and reduction in risk associated with ingestion

Benefits from optional Assessment Monitoring 

Costs for optional Assessment Monitoring

Some land costs depending on the treatment technology 

Source: Exhibts 8.2 and 8.4

Enhanced COI

Traditional COI

Note 1: Because benefits and costs are calculated using different model modules, bounds are not calculated on net benefits. 

Notes: Detail may not add due to independent rounding. The Traditional COI only includes valuation for medical costs and lost

work time (including some portion of unpaid household production). The Enhanced COI also factors in valuations for lost personal 

time (non-work time) such as childcare and homemaking (to the extent not covered by the Traditional COI), time with family, and

recreation, and lost productivity at work on days when workers are ill but go to work anyway.

Benefits from correction of sanitary survey deficiencies identified in the distribution systems and treatment 

plant

Nonquantified 

Costs

Nonquantified 

Benefits

Costs from correction of sanitary survey deficiencies identified in the distribution systems and

treatment plant

Cost for five repeat samples but this is small compared to the overestimate of cost for the initial

fecal-indicator sample that systems would take. 

Costs for compliance monitoring for some systems that already disinfect

Estimate 

Category

3% Discount Rate 7% Discount Rate

Mean

90% Confidence Bounds

Mean 

90%Confidence Bounds

Exhibit 8.5a Estimated Annualized National Benefits and Costs for the GWR

($Millions, 2003$)
Economic Analysis for the 8-8 October 2006

Final Ground Water Rule

Estimate Category

Benefits 3% 7%

Quantified Benefits (ECOI) 19.7 $ 16.8 $ 

Bacterial Illness and Death Avoidance Benefits $ 83.8 98.6 $ 

Total 118.3 $ 100.6 $ 

Costs $ 62.3 61.8 $ 

Net Benefits $ 38.3 56.5 $ 

Discount Rate

Notes: Costs and Quantified Benefits are output from the GWR model as annualized estimates that incorporate annual 

adjustments for income elasticity, changes in real income, and a CPI increase factor (all affecting the VSL). The GWR model 

also incorporates a schedule for implementation that affects the timing of benefits accrual throughout the analysis period for the 

GWR, which affects all components of benefits (direct and indirect). The model also discounts both costs and benefits (shown 

above at 3 and 7 percent). See Ch. 5 and Appendix B of the EA for detail on these adjustments. The estimated value of 

avoiding bacterial illness and death is not generated in the primary analysis model but is calculated as shown in Ch. 5, Sec. 

5.4.3. Therefore, the components of the estimated value of avoiding bacterial illness and death (affecting VSL and Direct 

Medical Costs) are not adjusted for these factors.

Exhibit 8.5b Estimated Net Benefits Including Annual Bacterial Illness and Death

Avoidance Estimate ($Millions 2003$)

8.2 Effect of Uncertainties and Nonquantified Benefit/Cost Estimates on the Estimation

of Net National Benefits

Detailed discussions of the assumptions and uncertainties associated with national benefits and

costs are contained in Chapters 4, 5, and 6. Several of the most important assumptions and data

uncertainties, and the effect of those uncertainties on the benefits and cost analyses, are discussed below.

The GWR EA attempted to capture the full range of uncertainty in the analysis. In the quantified

analysis, parameters were described using a distribution rather than a point value where sufficient

information is available. Where information is limited, distributions are chosen based on informed

professional judgment. Otherwise, distributions were determined by statistical models that allowed the

data to inform the distribution. Choice of statistical models were based on examining the data combined

with use of scientific principles. Alternative assumptions were tested and described in alternative

analyses. The EA also includes detailed discussion of the additional uncertainty associated with

nonquantified factors and untested assumptions.

The quantified GWR benefits are calculated using Monte Carlo sampling of the parameter

distributions and are expressed in monetary terms. The calculated results are presented as ranges with

means and confidence bounds. The most likely quantified value is within this calculated range but the

total benefit range, considering the non quantified benefits, is greater than the calculated benefit range. 

As summarized in Exhibit 5.32 and described throughout Chapter 5, because of limited available data,

almost all of the factors in the quantified analysis were chosen to provide a conservative estimate of

benefit, thus underestimating the quantified benefits. Furthermore, the factors discussed but not quantified

in the benefits analysis primarily act to provide additional GWR benefits, albeit nonquantified. Based on

these two uncertainty sources, EPA concludes that the total mean benefits are expected to be several times

greater than the quantified mean benefits and are likely to be greater than the calculated upper confidence

bound as well. The formal peer review of the GWR EA yielded comments and summary statements that

endorse EPA’s conclusion that the GWR EA quantified benefits are small compared to the total benefits.
Economic Analysis for the 8-9 October 2006

Final Ground Water Rule

Most of the significant costs that EPA has identified have been quantified. The only significant

costs that have not been quantified are for certain corrective actions that are a result of significant

deficiencies identified during sanitary surveys. Exclusion of these costs from the EA cost analysis results

in an underestimate of potential rule costs. However, as described in Chapter 6 of the EA, the impact on

the overall cost/benefit ratios from excluding costs for correction of treatment or distribution system

significant deficiencies is minimal since data limitations also exclude quantifying any benefits that may

be realized for correcting these significant deficiencies. 

There is uncertainty in the cost analysis that could result in either an over- or underestimate of the

costs as presented in this chapter. Exhibit 6.32 in Chapter 6 of the EA presents a summary of these issues

and estimates the effects that each may have on national costs. The greatest uncertainties affecting the

costs of the GWR are in the percentages used to estimate compliance and costs for each regulatory

alternative. However, by using a Monte-Carlo analysis, a best estimate (mean of range of estimates) of

costs can be calculated as well as the uncertainty bounds around that estimate.

Overall, EPA believes that the nonquantified costs are much smaller than the nonquantified

benefits and the estimates of the national net benefits are conservative. Detailed discussion of

nonquantified benefits and costs are presented in chapters 5 and 6, respectively.

8.3 Breakeven Analysis

In the face of uncertainties, it is helpful to evaluate the range over which the regulation meets the

critical test of benefits exceeding costs. Thus, the number of illnesses or deaths that would have to be

avoided annually to compensate for costs, or for the GWR to “break even,” can be calculated. If the

estimated present annual cost of the rule is $61.8 million using a three percent discount rate and $62.3

million using a seven percent discount rate, then 131,234 or 155,609 illnesses, respectively, would need

to be avoided annually using the Enhanced COI approach. Using the Traditional COI approach, 257,887

or 304,696 illnesses would have to be avoided annually. The breakeven number of illnesses that need to

be avoided for both the Enhanced and Traditional COI approaches is above the estimated number of

quantified illnesses (41,868 as shown in Exhibit 8.1) avoided by the final GWR. To “break even” using

deaths avoided as a measure, approximately 8 deaths would have to be avoided for either a three or seven

percent discount rate. Although this number of deaths exceeds the bounds of the quantified number of

deaths avoided in the primary analysis, it is small in absolute terms when considering potential effects of

viruses and bacteria not quantified as part of the analysis. Section 5.4.3.2 describes the methodology for

estimating ten additional deaths due to bacterial illness from contaminated PWS wells. Bacterial illness

and death is not considered in the breakeven analysis.

It must be noted, again, that this analysis does not account for the nonquantified health and nonhealth benefits, which far exceed those that EPA was able to quantify, and are the primary basis for

supporting the preferred regulatory alternative. The nonquantified benefits of the final GWR include all

of the nonquantified benefits that accrue to each alternative, as described in Chapter 5.
Economic Analysis for the 8-10 October 2006

Final Ground Water Rule

3% Discount Rate 7% Discount Rate

Enhanced COI 131,234 155,609

Traditional COI 257,887 304,696

VSL 8.3 8.4

Source: Derived from Exhibits 8.1 and 8.5a

Estimated Number of Cases to Avoid to Break Even1

Measure

Notes: Detail may not add due to independent rounding. The Traditional COI only includes valuation for medical costs and 

lost work time (including some portion of unpaid household production). The Enhanced COI also factors in valuations for 

lost personal time (non-work time) such as childcare and homemaking (to the extent not covered by the Traditional COI), 

time with family, and recreation, and lost productivity at work on days when workers are ill but go to work anyway.

1

 Breakeven illnesses and deaths are derived by dividing the regulation cost by an estimate of the average benefit per 

illness or death avoided as shown in Exhibit 8.1. Illnesses or deaths avoided may be of bacterial or viral etiology; since this 

analysis is based on the viral COI described in Ch. 5 of the EA for Type A and Type B viruses, for reasons also explained in 

Ch. 5 the COI could be an underestimate for cases of other types of viral or bacterial illness avoided. This could result in 

an overestimate of the number of illnesses or deaths that need to be avoided in order to break even with the costs of the 

rule. 

 Ilnesses

 Deaths

Exhibit 8.6 Estimated Breakeven Points

8.4 Comparison of Regulatory Alternatives

As discussed in Chapter 3, the development and evaluation of several regulatory alternatives was

undertaken as part of a consultation process that included stakeholder meetings and public comments. 

The four alternatives in the final EA are listed below.

Alternative 1—Sanitary surveys and corrective action.

Final GWR—Risk Targeted Approach (Sanitary surveys, triggered monitoring, optional

assessment monitoring, corrective action, and compliance monitoring).

Alternative 3—Multi-Barrier Approach (Sanitary surveys, triggered monitoring, optional

hydrogeologic sensitivity assessment, assessment monitoring, corrective action, and compliance

monitoring).

Alternative 4—Across-the-board disinfection (Sanitary surveys, install/upgrade and maintain

treatment).

The following sections evaluate the benefits and costs for the Final GWR requirements in

comparison to the three other alternatives.
Economic Analysis for the 8-11 October 2006

Final Ground Water Rule

5th 95th 5th 95th

Alternative 1 15.3 $ 11.8 $ 19.2 $ 15.3 $ 11.9 $ 19.0 $ 

Final Rule 61.8 $ 45.2 $ 81.4 $ 62.3 $ 46.1 $ 81.6 $ 

Alternative 3 67.9 $ 49.4 $ 89.5 $ 69.4 $ 51.0 $ 90.6 $ 

Alternative 4 686.4 $ 636.8 $ 735.4 $ 665.3 $ 612.3 $ 717.0 $ 

Source: Exhibit 6.35

Rule Alternative

Annualized Costs

at 3% Discount Rate

Annualized Costs

at 7% Discount Rate

Mean

90% Confidence Bounds

Mean 

90% Confidence Bounds

5th 95th 5th 95th

Alternative 1 7,497 1,618 17,007 0.14 0.01 0.44

Final Rule 41,868 10,274 88,039 0.74 0.08 2.11

Alternative 3 45,419 11,639 95,166 0.80 0.09 2.33

Alternative 4 155,282 27,824 399,085 2.67 0.21 9.25

Source: Exhibit 5.30

Rule Alternative

Illnesses Avoided Deaths Avoided

Mean

90% Confidence Bounds

Mean 

90% Confidence Bounds

8.4.1 Comparison of Benefits and Costs

To make meaningful comparisons between regulatory alternatives, it is first necessary to look at

the final benefit and cost numbers derived for each. Exhibit 8.7 presents the annualized present value

costs for each alternative considered, followed by presentations of benefits in Exhibits 8.8 and 8.9.

Exhibit 8.7 Annualized Costs, by Regulatory Alternative ($Millions, 2003$)

Exhibit 8.8 Number of Annual Quantified Viral Illnesses and Deaths Avoided

 Regulatory Alternatives
Economic Analysis for the 8-12 October 2006

Final Ground Water Rule

5th 95th 5th 95th

Alternative 1 3.6 $ 0.9 $ 9.3 $ 2.9 $ 0.7 $ 7.5 $ 

Final Rule 19.7 $ 6.5 $ 45.4 $ 16.8 $ 5.5 $ 38.6 $ 

Alternative 3 21.3 $ 7.1 $ 48.7 $ 18.2 $ 6.0 $ 41.6 $ 

Alternative 4 70.2 $ 18.3 $ 177.0 $ 61.9 $ 16.1 $ 156.3 $ 

Alternative 1 1.9 $ 0.3 $ 5.5 $ 1.5 $ 0.2 $ 4.5 $ 

Final Rule 10.0 $ 2.2 $ 27.0 $ 8.6 $ 1.9 $ 22.9 $ 

Alternative 3 10.8 $ 2.5 $ 28.9 $ 9.3 $ 2.1 $ 24.8 $ 

Alternative 4 35.5 $ 6.5 $ 102.4 $ 31.5 $ 5.7 $ 90.8 $ 

Source: Exhibit 5.31

Notes: Detail may not add due to independent rounding. The Traditional COI only includes valuation for medical costs and lost

work time (including some portion of unpaid household production). The Enhanced COI also factors in valuations for lost 

personal time (non-work time) such as childcare and homemaking (to the extent not covered by the Traditional COI), time with 

family, and recreation, and lost productivity at work on days when workers are ill but go to work anyway.

The figures presented in this exhibit represent only the quantifiable benefits of the GWR. The unquantified benefits are expected 

to compose a significant portion of the overall benefits of the Rule and are presented in Section 5.4 of Ch. 5 of the EA.

Enhanced COI

Traditional COI

Rule Alternative

At 3% At 7%

Mean

90% Confidence Bounds

Mean 

90% Confidence Bounds

Exhibit 8.9 Annualized Value of Quantified Viral Illnesses and Deaths Avoided,

by Regulatory Alternative ($Millions, 2003$)

Net benefit is the difference between the monetized benefit and cost estimates. Exhibit 8.10a

presents net benefits based on the annualized present value of quantified benefits at three and seven

percent discount rates, using both the Enhanced and the Traditional COI approach. The data are based on

the average benefits less the average values for costs. As discussed in Section 8.1.1 and Exhibit 8.3, the

nonquantified health and nonhealth benefits far exceed those that EPA was able to quantify, and their

incorporation into the quantified analysis would result in substantial increases in net benefits. Exhibit

8.10b demonstrates how by using a multiplier (based on bacterial hospitalizations and deaths avoided),

the net benefits of the final GWR are positive using the enhanced COI and are very close to positive using

the traditional COI. Based on consideration of the large number of nonquantified benefits, EPA believes

that this level of additional nonquantified benefits in relation to quantified benefits will be easily

achieved. Therefore, consideration of these nonquantified benefits provides a basis for supporting the

preferred regulatory alternative. To the extent that additional benefits are realized, those populations at

greatest risk from ground water contamination (e.g., sensitive sub-populations, including children and the

immunocompromised) will be better protected. 
Economic Analysis for the 8-13 October 2006

Final Ground Water Rule

3% 7%

Alternative 1 (11.7) $ (12.4) $ 

Final Rule (42.1) $ (45.5) $ 

Alternative 3 (46.6) $ (51.2) $ 

Alternative 4 (616.2) $ (603.4) $ 

Alternative 1 (13.5) $ (13.8) $ 

Final Rule (51.8) $ (53.7) $ 

Alternative 3 (57.1) $ (60.1) $ 

Alternative 4 (650.9) $ (633.8) $ 

Source: Derived from Exhibits 8.7 and 8.9

Notes: Detail may not add due to independent rounding. The Traditional COI 

only includes valuation for medical costs and lost work time (including some 

portion of unpaid household production). The Enhanced COI also factors in 

valuations for lost personal time (non-work time) such as childcare and 

homemaking (to the extent not covered by the Traditional COI), time with family, 

and recreation, and lost productivity at work on days when workers are ill but go 

to work anyway.

The figures presented in this exhibit represent only the quantifiable benefits of 

the GWR. The unquantified benefits are expected to compose a significant 

portion of the overall benefits of the Rule and are presented in Section 5.4 of Ch. 

5 of the EA.

Enhanced COI

Traditional COI

Rule Alternative

Annualized Value

3% 7%

Quantified Net Benefits Only (42.1) $ (45.5) $ 

Nonquantified = 5X Quantified 56.5 $ 38.3 $ 

Quantified Net Benefits Only (51.8) $ (53.7) $ 

Nonquantified = 5X Quantified (1.6) $ (10.9) $ 

Source: Derived from Exhibits 8.7 and 8.9

Multiple of Benefits Representing 

Nonquantified Benefits 

Annualized Net Benefit Value - 

Final Rule

Enhanced COI

Traditional COI

Notes: Detail may not add due to independent rounding. The Traditional COI only includes 

valuation for medical costs and lost work time (including some portion of unpaid household 

production). The Enhanced COI also factors in valuations for lost personal time (non-work time) 

such as childcare and homemaking (to the extent not covered by the Traditional COI), time with 

family, and recreation, and lost productivity at work on days when workers are ill but go to work 

anyway.

Exhibit 8.10a Annualized Net Benefits by Regulatory Alternative

($Millions, 2003$)

Exhibit 8.10b Annualized Mean Net Benefits for Final Rule Including Estimates

for Nonquantified Benefits ($Millions, 2003$)
Economic Analysis for the 8-14 October 2006

Final Ground Water Rule

8.4.2 Cost-Effectiveness Measures

Cost-Effectiveness–Traditional Approach

Cost-effectiveness analysis is a policy evaluation tool that allows comparisons of regulatory

alternatives. The concept of cost-effectiveness can be defined simply as getting the greatest benefits for a

given expenditure or imposing the least cost for a given level of benefits. In Exhibits 8.11a and 8.11b, the

test is to see if any alternative falls to the right and completely below any other alternative on the graph. 

If so, the alternative to the right and below would be more cost-effective and “dominate” the alternative

that provided fewer benefits at higher costs.

In the strict sense, each of the regulatory alternatives is cost effective—no regulatory alternative

provides more benefits at the same or a lower cost than another, and no alternative can achieve lower

costs for the same or a greater level of benefits than another. Thus, no alternative dominates any other or

is more cost effective. Instead, the alternatives offer increasing levels of benefits at increasing levels of

cost, as seen in Exhibits 8.11a and 8.11b.
Economic Analysis for the 8-15 October 2006

Final Ground Water Rule

Source: Exhibits 8.7 and 8.9

3 Percent Discount Rate

$-

$100.0

$200.0

$300.0

$400.0

$500.0

$600.0

$700.0

$800.0

$- $25.0 $50.0 $75.0 $100.0

Benefits ($Millions)

Costs ($Millions)

Alt 3

Alt 4

Alt 1

Final 

Rule

Source: Exhibits 8.7 and 8.9

Notes: Detail may not add due to independent rounding. The Traditional COI only includes valuation for medical 

costs and lost work time (including some portion of unpaid household production). The Enhanced COI also 

factors in valuations for lost personal time (non-work time) such as childcare and homemaking (to the extent not 

covered by the Traditional COI), time with family, and recreation, and lost productivity at work on days when 

workers are ill but go to work anyway.

7 Percent Discount Rate

$-

$100.0

$200.0

$300.0

$400.0

$500.0

$600.0

$700.0

$- $25.0 $50.0 $75.0 $100.0

Benefits ($Millions)

Costs ($Millions)

Alt 3

Alt 4

Alt 1

Final 

Rule

Exhibit 8.11a Mean Annualized Costs at Mean Benefit Level, Enhanced COI,

by Regulatory Alternative
Economic Analysis for the 8-16 October 2006

Final Ground Water Rule

Source: Exhibits 8.7 and 8.9

Note: The Traditional COI only includes valuation for medical costs and lost work time (including some 

portion of unpaid household production). The Enhanced COI also factors in valuations for lost personal 

time (non-work time) such as childcare and homemaking (to the extent not covered by the Traditional 

COI), time with family, and recreation, and lost productivity at work on days when workers are ill but go to 

work anyway.

7 Percent Discount Rate

$-

$100.0

$200.0

$300.0

$400.0

$500.0

$600.0

$700.0

$- $10.0 $20.0 $30.0 $40.0 $50.0

Benefits ($Millions)

Costs ($Millions)

Alt 3

Alt 4

Alt 1

Final 

Rule

3 Percent Discount Rate

$-

$100.0

$200.0

$300.0

$400.0

$500.0

$600.0

$700.0

$800.0

$- $10.0 $20.0 $30.0 $40.0 $50.0

Benefits ($Millions)

Costs ($Millions)

Alt 3

Alt 4

Alt 1

Final 

Rule

Exhibit 8.11b Mean Annualized Costs at Mean Benefit Level, Traditional COI,

by Regulatory Alternative
Economic Analysis for the 8-17 October 2006

Final Ground Water Rule

3% 7% 3% 7%

Alternative 1 2,045 $ 2,044 $ 107.4 $ 107.4 $ 

Final Rule 1,476 $ 1,488 $ 83.1 $ 83.8 $ 

Alternative 3 1,495 $ 1,527 $ 85.0 $ 86.9 $ 

Alternative 4 4,420 $ 4,284 $ 257.4 $ 249.5 $ 

Cost per Viral Death Avoided

($Millions)

Rule Alternative

Cost per Viral Illness Avoided 

($)

Note: The figures presented in this exhibit represent only the quantifiable benefits of the GWR. The unquantified benefits are

expected to compose a significant portion of the overall benefits of the Rule and are presented in Section 5.4 of Ch. 5 of the EA.

Source: Derived from Exhibits 8.7 and 8.8

Cost per Case of Illness or Death Avoided

Another measure related to cost-effectiveness that EPA used to evaluate the regulatory

alternatives is the cost for each case of illness and death avoided. EPA has performed this analysis for the

quantified benefits of the GWR. For purposes of evaluating the alternatives, the lower the cost per case

or death avoided, the more cost-effective the alternative is believed to be. Exhibit 8.12 presents the

average cost per case of viral illness and death avoided for each regulatory alternative.

Exhibit 8.12 Cost Per Viral Illness or Death Avoided

by Regulatory Alternative (2003$)

Exhibit 8.12 shows that the cost per case avoided for the final GWR is lower than the cost per

case avoided for each of the other alternatives considered. Thus, the Final GWR is the most efficient

alternative by this measure. Given the substantial nonquantified benefits of the final GWR as described

in Chapter 5, the actual cost per case is lower than calculated in Exhibit 8.12. 

Incremental Net Benefits

EPA also assessed the incremental net benefits of the regulatory alternatives. Incremental costs

and benefits are those that are incurred or realized in reducing viral illness, bacterial illness, and outbreaks

from one rule alternative to the next. Estimates of incremental costs and benefits are useful in considering

the economic efficiency of different regulatory options considered by the Agency. Generally, the goal of

an incremental analysis is to identify the option where incremental benefits most closely equal

incremental costs (net social benefits are maximized). However, the usefulness of this analysis is limited

because the benefits from the rule that are not quantified or monetized far exceed those that EPA was able

to quantify, and these nonquantified benefits are the primary basis for supporting the preferred regulatory

alternative.

Exhibit 8.13 presents the four regulatory alternatives in order of increasing level of reduction in

waterborne pathogens, or increasing levels of protection from illness. As a result, it is possible to

compare incremental net benefits from the baseline and alternative to alternative. As shown in Exhibits

8.13a and b, incremental net benefits for all alternatives are negative. The benefits of non-quantified

bacterial illness and death avoided would add benefits to all alternatives without any increase in costs. 
Economic Analysis for the 8-18 October 2006

Final Ground Water Rule

Annual 

Costs

Annual 

Benefits

Incremental 

Costs

Incremental 

Benefits

Incremental 

Net Benefits

A B C D E=D-C

Alternative 1: Sanitary Survey and Corrective Action $ 3.6 15.3 $ 15.3 $ 3.6 $ (11.7) $ 

Alternative 2 (Final Rule): Risk Targeted Approach $ 19.7 61.8 $ 46.5 $ 16.1 $ (30.4) $ 

Alternative 3: Multi-Barrier Approach $ 21.3 67.9 $ 6.1 $ 1.6 $ (4.5) $ 

Alternative 4: Across-the-board Disinfection $ 70.2 686.4 $ 618.5 $ 48.9 $ (569.6) $ 

Alternative 1: Sanitary Survey and Corrective Action $ 2.9 15.3 $ 15.3 $ 2.9 $ (12.4) $ 

Alternative 2 (Final Rule): Risk Targeted Approach $ 16.8 62.3 $ 47.0 $ 13.9 $ (33.1) $ 

Alternative 3: Multi-Barrier Approach $ 18.2 69.4 $ 7.1 $ 1.4 $ (5.7) $ 

Alternative 4: Across-the-board Disinfection $ 61.9 665.3 $ 595.9 $ 43.8 $ (552.2) $ 

Sources: (A) Exhibit 8.7, (B) Exhibit 8.9 

Rule Alternative

3% Discount Rate

7% Discount Rate

Notes: The Traditional COI only includes valuation for medical costs and lost work time (including some portion of unpaid household production). The Enhanced COI 

also factors in valuations for lost personal time (non-work time) such as childcare and homemaking (to the extent not covered by the Traditional COI), time with family, 

and recreation, and lost productivity at work on days when workers are ill but go to work anyway. All values are annualized in 2003$. 

The figures presented in this exhibit represent only the quantifiable benefits of the GWR. The unquantified benefits are expected to compose a significant portion of the 

overall benefits of the Rule and are presented in Section 5.4 of Ch. 5 of the EA.

EPA estimated that the total benefits are likely to increase by more than a factor of five by accounting for

additional deaths and hospitalizations caused by reduced bacterial illness and death alone. These

non-quantified benefits have a significant positive impact on the incremental benefits and net incremental

benefits. Both Alternative 3 and Alternative 2 would have positive net incremental benefits if the

bacterial benefits are considered. The next highest alternative, Alternative 4, has such highly negative

incremental net benefits, and the difference is so substantial that non-monetized benefits would be

unlikely to compensate. However, comparisons between Alternative 4 and the other alternatives may be

between two separate sets of benefits, in the sense that they may be distributed to somewhat different

populations. However, based on consideration of all factors, EPA has determined that the final GWR

provides the maximum benefits at a cost that is justified.

The cost-effectiveness of the final GWR and alternatives was also considered in terms of the

quality-adjusted life years (QALYs) saved for avoided viral illnesses or deaths. The QALYs analysis

shows that the final GWR performs the best in terms of this measure. Appendix H provides the detail of

this analysis.

Exhibit 8.13a Incremental Net Quantified Benefits by Rule Alternative -

Enhanced COI (Annualized Present Value Mean, $Millions, 2003$)
Economic Analysis for the 8-19 October 2006

Final Ground Water Rule

Annual 

Costs

Annual 

Benefits

Incremental 

Costs

Incremental 

Benefits

Incremental 

Net Benefits

A B C D E=D-C

Alternative 1: Sanitary Survey and Corrective Action $ 1.9 15.3 $ 15.3 $ 1.9 $ (13.5) $ 

Alternative 2 (Final Rule): Risk Targeted Approach $ 10.0 61.8 $ 46.5 $ 8.2 $ (38.3) $ 

Alternative 3: Multi-Barrier Approach $ 10.8 67.9 $ 6.1 $ 0.8 $ (5.3) $ 

Alternative 4: Across-the-board Disinfection $ 35.5 686.4 $ 618.5 $ 24.7 $ (593.8) $ 

Alternative 1: Sanitary Survey and Corrective Action $ 1.5 15.3 $ 15.3 $ 1.5 $ (13.8) $ 

Alternative 2 (Final Rule): Risk Targeted Approach $ 8.6 62.3 $ 47.0 $ 7.1 $ (39.9) $ 

Alternative 3: Multi-Barrier Approach $ 9.3 69.4 $ 7.1 $ 0.7 $ (6.4) $ 

Alternative 4: Across-the-board Disinfection $ 31.5 665.3 $ 595.9 $ 22.2 $ (573.7) $ 

Sources: (A) Exhibit 8.7, (B) Exhibit 8.9 

Rule Alternative

3% Discount Rate

7% Discount Rate

Note: The Traditional COI only includes valuation for medical costs and lost work time (including some portion of unpaid household production). The Enhanced COI 

also factors in valuations for lost personal time (non-work time) such as childcare and homemaking (to the extent not covered by the Traditional COI), time with family, 

and recreation, and lost productivity at work on days when workers are ill but go to work anyway. All values are annualized in 2003$.

The figures presented in this exhibit represent only the quantifiable benefits of the GWR. The unquantified benefits are expected to compose a significant portion of the 

overall benefits of the Rule and are presented in Section 5.4 of Ch. 5 of the EA.

Exhibit 8.13b Incremental Net Quantified Benefits by Rule Alternative -

Traditional COI (Annualized Present Value Mean, $Millions, 2003$)

8.5 Summary of Conclusions

The Agency also performed a number of other analyses related to the final rule. This process

included an analysis of net benefits, as well as cost effectiveness and efficiency analyses. In addition, the

Agency performed a number of comparisons among the four regulatory alternatives that are described in

more detail earlier in this chapter. The following is a summary of these analyses. 

The GWR likely passes economic threshold criteria:

• The GWR has positive net benefits when both quantified and nonquantified benefits are

considered. For the Enhanced COI approach, the quantified benefits alone are approximately

27 to 32 percent of the costs of the GWR (Exhibit 8.5a) depending on discount rate. For the

Traditional COI approach, the quantified benefits are approximately 14 to 16 percent of the

costs of the GWR. Considering that nonquantified benefits are expected to be significantly

larger than the quantified benefits, it appears likely that the final GWR would have positive

net benefits regardless of the discount rate or cost of illness approach used. Section 5.4.3.2

presents a discussion of nonquantified benefits and estimates a portion of their value, based

only on bacterial illnesses avoided, at four times the primary analysis benefits (resulting in
Economic Analysis for the 8-20 October 2006

Final Ground Water Rule

total benefits that are five times the primary benefits). This includes consideration of the

value of deaths and hospitalization costs avoided for ground water borne cases of bacterial

illness prevented by the rule. Including only these estimated bacterial illness and death

benefits, the total net benefits of the GWR would be positive using the Enhanced COI

approach. Total net benefits would still be slightly negative using the Traditional COI

approach, however, other nonquantified benefits such as indirect (non-medical) costs

associated with waterborne bacterial illness or the value of avoiding other chronic (either

bacterial or viral) or other viral illnesses (not accounted for in this analysis) would most

likely make this value positive.

• The number of illnesses that must be avoided to break even with costs (Exhibit 8.6) is well

above the estimated number of viral cases avoided (Exhibit 8.1), but is most likely within the

bounds of cases avoided once nonquantified cases (both bacterial and viral) are considered. 

The number of deaths that must be avoided to break even, while outside the bounds of the

quantitative analysis, is small in absolute terms. Consideration of all nonquantified benefits

is predicted to result in favorable break even results. 

• The GWR is cost-effective (using either the Enhanced or the Traditional COI approach): no

other alternative achieves greater benefits at the same cost or the same benefits at lower cost

(Exhibit 8.11).

Final GWR determinations:

C The economic analysis for this rule, considering quantified and nonquantified benefits,

supports the basis for selecting the final GWR over other alternatives. However, the

distinction between Alternative 2 and 3 on an economic basis, is not great. 

C EPA chose the final GWR because EPA believes it is more flexible, targeted, and costeffectively protective than Alternative 3. Optional assessment monitoring allows States to

most effectively target those systems at greatest risk and minimize unnecessary monitoring. 

EPA took the following considerations into account in making this judgment:

1) Under Alternative 3, some States may not be able to conduct HSAs and thereby require

systems in nonsensitive aquifers to conduct assessment monitoring unnecessarily. For

systems not at risk this additional monitoring would provide no benefit.

2) Systems with frequent TC positives in the distributions system (and subsequent frequent

triggered monitoring) would benefit little from assessment monitoring regardless if they

were sensitive or not because the source water would already be thoroughly evaluated. 

Under Alternative 3, such systems in sensitive (or undetermined) aquifers would be

required to do assessment monitoring.

3) Systems identified as having significant risk factors pertaining to potential fecal

contamination at their source (e.g., aquifer condition, well characteristics, proximity to

sewage or septic), but infrequent triggered monitoring source water samples, would

benefit from assessment monitoring. States will be able to identify such systems on an

ongoing basis through a variety of tools and information readily available to them.
Economic Analysis for the 8-21 October 2006

Final Ground Water Rule

C The EPA believes that the final rule is a logical outgrowth of the proposed rule, that it is

supported by comments, and that it provides public health benefits while apportioning costs

in a more flexible targeted manner. 

As a result of all of these considerations, EPA has determined that the final GWR will provide

important protection against illnesses and deaths attributable to fecally contaminated ground water. EPA

also believes that the GWR will provide a desired level of protection from ground water pathogen

contamination at a justifiable cost.
Economic Analysis for the R-1 October 2006

Final Ground Water Rule 

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