# Economic Analysis for the Final Ground Water RuleOffice of Water (4606-M) EPA 815-R-06-014 October 2006 www.epa.gov/safewaterEconomic 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 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2-12Economic Analysis for the ii October 2006 Final Ground Water Rule 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 . . . . . . . . . . . . . . . . . 4-70Economic Analysis for the iii October 2006 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 fro m 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 (P redictions 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 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5-92Economic Analysis for the iv October 2006 Final Ground Water Rule 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 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6-62Economic Analysis for the v October 2006 Final Ground Water Rule 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 Environmen tal 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. ReferencesEconomic 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 Bene fits 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 Rat es 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 ModelEconomic 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 Va lue 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 B aseline: 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 . . . . . . . . . . . . . . . . . . 4-42Economic 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 P well for Virus and Indicator (with error bars showing the 5th and 95th percentiles) . . . . . . . . . . . . . . . . . . . . . . . . 4-56 Exhibit 4.19 Scatter Plot of P well Pairs for Indicators and Viruses . . . . . . . . . . . . . . . . . . . . . . . . . . 4-57 Exhibit 4.20 Density Function Shapes of P sample for Viruses . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4-58 Exhibit 4.21 Cumulative Distributions of P sample for Viruses . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4-58 Exhibit 4.22 Median of 10,000 Estimates of P sample for Virus and Indicator (with error bars showing the 5th and 95th percentiles) . . . . . . . . . . . . . . . . . . . . . . . 4-59 Exhibit 4.23 Scatter Plot of Means of P sample Pairs for Indicators and Viruses . . . . . . . . . . . . . . . . . 4-60 Exhibit 4.24 Mean of P sample Versus P well for Viruses (1,000 Pairs from Occurrence Model) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4-61 Exhibit 4.25 Mean of P sample Versus P well 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 Quantif ied 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 Da ily 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 . . . 5-26Economic 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 Death 1 . . . . . . . . . . . . . . . . . . . . . . . . 5-43 Exhibit 5.14 Baseline Illnesses and Deaths in Sensitive Subgroups . . . . . . . . . . . . . . . . . . . . . . . . 5-44 Exhibit 5.15a Summary of Pearson Correlation Coeffi cients 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 25 th 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 a nd 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 a nd Average Cost per Case of Type B Illness Requiring Outpatient Care, by Age (Enhanced COI) . . . . . . . . . . . . . . . . . . . . . . . . . 5-68 Exhibit 5.21e Estimates for Average Cost a nd 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 a nd 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 a nd Average Cost per Case of Type B Illness Requiring Outpatient Care, by Age (Traditional COI) . . . . . . . . . . . . . . . . . . . . . . . . 5-73 Exhibit 5.22e Estimates for Average Cost a nd 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 Avoi ded 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 . . . . . . . . . . . . . . . . . . . . . . . 5-110Economic 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 A nnual 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 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6-42Economic 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$) . . . 6-62 Exhibit 6.35 Comparison of National A nnual Costs by Regulatory Alternative ($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 a nd 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 Benef its 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 (ClO 2 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 Presen t Value Quantified Benefits ($Millions, 2003$) . . . . . 8-4 Exhibit 8.3 Summary of Benefits of the GWR . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8-5Economic 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 In cluding 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 Quantif ied Viral Illnesses and Deaths Avoided by Regulatory Alternatives . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8-11 Exhibit 8.9 Annualized Value of Quantif ied 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 D eath Avoided by Regulatory Alternative (2003$) . . . . . . . 8-17 Exhibit 8.13a Incremental Net Quantified Bene fits by Rule Alternative - Enhanced COI (Annualized Present Value Mean, $Millions, 2003$) . . . . . . . . . . . . . . . . . . . . . . . . . 8-18 Exhibit 8.13b Incremental Net Quantified Benef its by Rule Alternative - Traditional COI (Annualized Present Value Mean, $Millions, 2003$) . . . . . . . . . . . . . . . . . . . . . . . . . 8-19

9. ReferencesEconomic 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 ClO 2 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 RuleEconomic 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 μ g/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 acidEconomic 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 PayEconomic Analysis for the xvi October 2006 Final Ground Water Rule 

## Health Risk Reduction and Cost Analysis

Under the Safe Drinking Water Act (SDWA) Am endments 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 Agen cy) must conduct a health risk reduction and cost analysis (HRRCA). A HRRCA addresses seven requireme nts, 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 eval uation of the benefits and costs of the Ground Water Rule (GWR). The analysis is perfo rmed 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 ec onomic impact of rules that have an annual effect on the economy of over $100 million and make that anal ysis 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 Regul atory Impact Analysis) to accompany the May 2000 proposed GWR.
EPA developed the GWR in collaboration with St ates and other interested stakeholders. The primary goal of the GWR is to improve public hea lth by identifying public ground water systems (GWSs) that are susceptible to fecal contamination and to ensu re 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 includ es 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 exis ting sanitary survey requirements for GWSs. The reduction in risk will be accomplished through implem entation of the GWR’s risk-targeted approach. Because of the difficulties involved in monitoring for th e wide range of specific pathogenic bacteria and viruses that could occur in ground water, one of th e 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 r esults, 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 propos al 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 alterna tives 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: sanita ry 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, th e 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 suscep tible to fecal contamination. A flowchart that illustrates the compliance steps for sy stems is illustrated in Exhibit ES.1. The components of the risktargeted strategy are used to identify source contam ination 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 compone nts: (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 a nd 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 pe rformance record as determined by the State (e.g., no significant deficiencies documented in previous assessments and no history of total coliform MCL orEconomic 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 combinati on 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 technologi es) must conduct triggered source water monitoring for the presence of at least one of the fo llowing State-specified fecal indicators: E. coli , enterococci, or somatic coliphage. The triggered monitoring requirement s apply to systems that are notified that a Total Coliform Rule (TCR) routine sample is total colifor m-positive. Within 24 hours of receiving the total coliform-positive notice, GWSs must collect a sour ce 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 re quire 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 ta rget 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 de ficiencies; 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 fi nal 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-a pproved 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 SystemsEconomic Analysis for the ES-5 October 2006Final Ground Water RuleFinal GWR publicationdate (2006); final ruletakes effect 3 yearsafter published inFederal RegisterNCWSsCWSsStateYear 11Year 10Year 9Year 8Year 7Year 6Year 5Year 4Year 3Year 2Year 1ImplementationConduct Sanitary SurveysReview Triggered Source Water MonitoringReview & Approve Corrective ActionReview Compliance MonitoringImplementationImplementationTriggered Source Water MonitoringTriggered Source Water MonitoringPerform Corrective ActionPerform Compliance Monitoring1stround Sanitary Surveys2ndround Sanitary SurveysPerform Corrective ActionPerform Compliance Monitoring1stround Sanitary Surveys2ndround Sanitary SurveysPrimacyApplicationPossibleExtension forPrimacy3rdround SanitarySurveysFinal GWR publicationdate (2006); final ruletakes effect 3 yearsafter published inFederal RegisterNCWSsCWSsStateYear 11Year 10Year 9Year 8Year 7Year 6Year 5Year 4Year 3Year 2Year 1ImplementationConduct Sanitary SurveysReview Triggered Source Water MonitoringReview & Approve Corrective ActionReview Compliance MonitoringImplementationImplementationTriggered Source Water MonitoringTriggered Source Water MonitoringPerform Corrective ActionPerform Compliance Monitoring1stround Sanitary Surveys2ndround Sanitary SurveysPerform Corrective ActionPerform Compliance Monitoring1stround Sanitary Surveys2ndround Sanitary SurveysPrimacyApplicationPossibleExtension forPrimacy3rdround SanitarySurveysExhibit ES.2 Implementation Timeline for the GWR2 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 w ith newly installed treatment to achieve 4-log viral inactivation or removal. The number of entry points pe rforming 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 complia nce monitoring). This baseline is derived from EPA’s Safe Drinking Water Information System (SDWIS) inventory, 4 th quarter 2003 data. 2 The systems are subdivided by type [community water system s (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 b ased on conducting a sanitary survey. The remaining activities are evaluated at the entry point into the di stribution system. Column C indicates that all entry points that do not achieve 4-log treatment of viru ses 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 leve ls of disinfection (i.e., increased disinfection or installation of new disinfection) resulting from tho se 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. 3Economic Analysis for the ES-7 October 2006Final Ground Water RuleSystem SizeSystemsReceivingSanitarySurveySystems withCorrective Actionsfor SignificantDeficienciesEntry Points withTriggeredMonitoringEntry Points withCorrective Actionsfor TriggeredMonitoringEntry Points with ViralDisinfection Increasedfrom less than 4 logsto 4 logsPreviously Nondisinfecting EntryPoints TakingCorrective ActionsEntry Points withIncrementalComplianceMonitoringAB C D E F GCommunity Water Systems (CWSs)<100 12,8432,18112,7971,249358891248101-500 14,3582,44414,8191,625917709292501-1,000 4,6497895,5786083602481051,001-3,300 5,9101,0018,9107123963171303,301-10K 2,8844925,63861735326411110,001-50K 1,4442454,3576555481075450,001-100K 167281,2952269313346100,001-1 Million 10318749136944220> 1 Million 3------Nontransient Noncommunity Water Systems (NTNCWSs)<100 9,4561,6088,609687150537149101-500 6,7581,1486,149533119415170501-1,000 1,8943221,72414933117501,001-3,300 715121651861967273,301-10K 7312661028310,001-50K 1029201150,001-100K 1010000100,001-1 Million 1010000> 1 Million -------Transient Noncommunity Water Systems (TNCWSs)<100 64,44810,99063,2956,9151,1435,7721,602101-500 18,9933,23418,6482,0263371,689696501-1,000 1,9403291,90520835174731,001-3,300 58599574761263263,301-10K 74137312210410,001-50K 19319313150,001-100K 1010000100,001-1 Million 1010000> 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 Implications4 There is much discussion among economists of the prope r 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. Historica lly, 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 increm ental 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 th e 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 ch aracterized as either health benefits or non-health benefits. Nonquantified health-relate d benefits include reducing other acu te 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 outbreak s, disinfection failures, and distribution system contamination). Chronic illnesses, both bacterial and vi ral, 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 re garding 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 bene fits (resulting in total benefits that are five times the primary benefits). This includes consideration of the value of deaths and hospitalization costs avoidedfor waterborne cases of bacterial illness prevented by the rule. This does not include indirect (nonmedical) costs associated with waterborne bacterial illn ess or the value of avoiding other chronic or viral illnesses.

Sections ES.5.1 and ES.5.2 summarize the methods u sed 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 deat hs 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 cont amination 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 na tional costs), and compliance monitoring. Note that two estimates for national costs and monetized be nefits 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 appendi ces 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 in cidence of acute and chronic illness caused by a wide variety of viral and bacterial pathogens that ar e 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 endpoi nt. 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 organi sms to infect humans and cause illness and death. Risk from bacterial pathogens was not characterized in the risk model b ecause occurrence data for bacterial pathogens in drinking water are limite d (however, the discussion of nonquantified benefits assesses the potential impact). For th e 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 ro tavirus 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 en terovirus 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 illn ess risk that could result from all viruses.
The Agency, having identified representative vi ruses for modeling purposes, used probability of virus occurrence in wells and samples along with estimat ed concentrations of enteric viruses to estimate the population’s exposure to Type A and Type B viru ses. Combining these occurrence and concentration data with daily drinking wa ter 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 numbe r of viral illnesses and deaths avoided by the final GWR, EPA estimates the percentage reduction in vi ral occurrence as a result of systems implementing changes to meet all rule requirements. The estim ated 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 a nd deaths. The value of avoiding cases of viral illness is based on estimates of the direct and indirect co sts 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 Tr aditional 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 acro ss an exposed population. Other economic factors are taken into consideration when calculating be nefits over time, such as income growth, income elasticity of demand, and social discount rates.
EPA estimates the quantified benefits of avoi ded 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 subs tantial 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 Exhi bit ES.6. The nonquantified benefits result from multiple factors. First, the quantified bene fits 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 uncer tainty ranges in the benefit analysis. This EA, where applicable, discusses alternative assumptions. For example, the enterovirus morbidity fractions are, by assumption, not determined using coxsackievi rus (an enterovirus) data although the enterovirus severity data use all enterovirus data. If coxsackievi rus 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 incr ease 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 discu ssed 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 gastroenter itis illness and fatal dehydration associated with that illness are monetized. Norovirus disease is not cons idered. For the enteroviruses, all acute disease endpoints are considered, but the prevalence of sever e 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, e ither for rotavirus or the enteroviruses, are chronic diseases identified or monetized in the quantitative benefits calculation.
Fourth, the quantified benefits are based explic itly on what has been directly measured in PWS wells, yet there is great difficulty in identifying a nd 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 contamin ation scenarios are thoroughly documented in the ground water contamination and outbreak scientific literatu re. However, these scenar ios, 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 ep idemic disease (outbreaks). If epidemic illnesses and the avoided non-health-related costs of ground wa terborne disease outbreaks were included, the quantified benefits would increase.
In summary, this EA quantifies a subset of the to tal health and non-health related benefits. In a sample calculation, discussed in Section 5.4.3.2, EPA es timated that the total benefits could increase by a factor of five by only accounting for additional d eaths and hospitalizations caused by bacterial illness being avoided. While EPA recognizes that this estim ate includes substantial uncertainty, given all the other nonquantified factors described above, EPA believ es 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 quantifiedEconomic 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 triggere d source water monitoring, undergo corrective actions, and perform compliance monitoring. State cost analy ses include estimates of the labor burdens that States would face for implementation and other annual admi nistrative tasks (e.g., recordkeeping), conducting sanitary surveys, responding to PWS reports for sour ce water and compliance monitoring, and reviewing corrective action plans. The methodology for es timating corrective action and noncorrective actionrelated costs for systems is discussed in the ne xt 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 in cur 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 es timates 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. Deriva tion 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 charact erize 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 r ecognizing 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 t echnologies 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 nati onal 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 r esult 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) Uppe r (95th %ile) Lower (5th %ile) Uppe r (95th %ile) Lowe r (5th %ile) Uppe r (95th %ile)

79 $ 29 $ 158 $ 62 $ 24 $ 117 $ 141 $ 53 $ 275 $
31 $ 12 $ 60 $ 0 $ 0 $ 1 $ 31 $ 12 $ 61 $
173 $ 64 $ 339 $ 1 $ 0 $ 2 $ 174 $ 64 $ 341 $
283 $ 105 $ 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 Va lue Costs of the GWR ($Millions, 2003$)

ES.6 Projected Impacts on Household Costs

The household cost analysis assumes that systems ma y 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 anal ysis because they are the only systems that serve households directly. The top half of the exhibit s hows summary statistics for all households affected by the rule, including households that will incur minima l costs (e.g., those served by systems incurring only implementation costs). The bottom half shows st atistics 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 ch anges represent the majority of rule costs, this provides insight into how the rule will affect the seg ment 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 corr ective actions range from $0.45 to $52.38, depending on system size. EPA estimates that, as a whole, hou seholds 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 syst ems experience the lowest increases in costs due toEconomic 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 be nefits of the rule range from approximately 14% to 32% of the costs, depending on the discount rate and CO I approach. The estimated quantified benefits for the Enhanced COI approach are greater than the co rresponding estimated benefits for the Traditional COI approach. The quantified estimate of the benefits signi ficantly understates the true benefit of the rule. As discussed in Section ES.5.1 and Exhibit ES.6, the nonqua ntified 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 tim e) 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 an alyses related to the final rule. This process included an analysis of net benefits, as well as cost e ffectiveness 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 follo wing 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 bot h quantified and nonquan tified benefits are considered. For the Enhanced COI approach, th e 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 approxi mately 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 estimat es 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 estim ated 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 sligh tly 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 chr onic (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 a nd viral) are considered. The number of deaths that must be avoided to break ev en, while outside the bounds of the quantitative analysis, is small in absolute terms. Consid eration of all nonquantified benefits is predicted to result in favorable break even results.


### C The GWR is cost-effective (using either the E nhanced or the Traditional COI approach): no other alternative achieves greater benefits at th e same cost or the same benefits at lower cost.

Final GWR determinations:


### C The economic analysis for this rule, cons idering quantified and nonquantified benefits, supports the basis for selecting the final GW R 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 logi cal outgrowth of the proposed rule, that it is supported by comments, and that it provides pub lic 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 c ontamination. 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 d eaths attributable to ground water contamination. EPA also believes that the GWR will provide th is 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 eval uation of the benefits and costs of the Ground Water Rule (GWR). The analysis is perfo rmed 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 comp lete EA for this rule. EPA also prepared an EA (formerly known as the Regulatory Impact Analys is) that accompanied the May 2000 proposed GWR.
EPA developed the GWR in collaboration with St ates and other interested stakeholders. The primary goal of the GWR is to improve public hea lth by identifying public ground water systems (GWSs) that are susceptible to fecal contamination and to ensu re 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 GW R 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 noncomm unity 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 su rface 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.Economic Analysis for the 1-2 October 2006 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 Prim ary 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 regulator y alternatives considered are compared.
• Chapter 7 discusses distributional analyses perform ed to evaluate the effects of the rule on different segments of the population, and considers various executive orders and requirements, including the Regulatory Fl exibility Act (RFA) and Unfunded Mandates Reform Act (UMRA).
• Chapter 8 compares the rule’s benefits and co sts to evaluate the potential net benefits and cost-effectiveness of the rule. The results ar e discussed and compared to other regulatory alternatives considered.



### 1.3 Calculations and Citations
This EA presents results from detailed and comple x 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 effectiven ess analysis of the rule alternatives using a quality-adjusted life years approach.



### S Appendix I provides detailed analysis of tota l 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 cont amination of ground wate r-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 in activation of microbiological contaminants for all public water systems (PWSs), including systems supplied by ground water sources. The 1996 Amendments included more specific language regard ing ground water disinfection, specifying that the Administrator must publish NPDWRs requiring disinf ection 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 rati onale 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 concerne d about any potential adverse health risks that may be associated with ground water sources and, in particul ar, the risks associated with fecal contamination. Fecal contamination includes all of the bacter ia 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 fede ral regulations currently require filtration or disinfection of ground water sources to remove microbi al 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, si nce pathogenic bacteria and viruses are shed in low numbers by a few infected individuals and for a limite d 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 ar e bacteriophages (viruses th at 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 persis t 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 cont amination of those sources. EPA has evaluated data on outbreaks and the occurrence of waterborne pathoge ns and indicators of fecal contamination in ground water supplying PWS wells. These data indicate that th ere is a subset of GWSs that are susceptible toEconomic 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) re ports that between 1991, the year in which the TCR became effective, and 2000, GWSs were asso ciated 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 th e 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 occurren ce 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 th e 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 unco rrected 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 flex ible, 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 sam pling or sanitary surveys. The GWR establishes treatment technique requirements that allow multiple options to address significant deficiencies and fecal contamination. Furthermore, the final GWR estab lishes 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 pot ential adverse health effects associated with consuming fecally contaminated ground water.

2.2.1 Contaminants and Their Health Effects
Pathogenic enteric viral and bacterial microorga nisms 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 microorganism s is the intestinal tract of animals and humans. Enteric microorganisms, sometimes referred to as in testinal 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 micr oflora 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 hum ans. Once infected, human s 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 ha ve 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 illn ess, 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). O pportunistic pathogens usually cause illness only in immunocompromised persons or in other sensitive s ubpopulations, 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 b acterial 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 Irvi ng 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, meningiti s, 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 Irvi ng 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 5 136 26.3% 2 25 4.1% 7 161 10.3% Cryptosporidium 3 1,539 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 1 83 5.3% 4 473 8.2% 5 556 7.4% Campylobacter 1 172 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 1 124 5.3% - - 0.0% 1 124 1.5% E. coli 1 22 5.3% 2 785 4.1% 3 807 4.4% Vibrio 1 11 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 Preventi on (CDC) data provide an indication of the types of pathogens that have caused waterborne di sease 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 associat ed 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) outbr eaks; however, EPA suspects that many of these were caused by viruses, given that it is generally more di fficult 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, Kram er et al. 1996, Levy et al. 1998, Ba rwick 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 mi crobes associated with each source.1 For a more detailed discussion of the factors affec ting 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, microbi al activity, moisture content, and type of pathogen all affect pathogenic fate and transport. Other fact ors, such as climatic changes and agriculture and land use practices, influence, and may alter, the comple x 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 wa ter. 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 atte nuation 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 amount s of human waste into the subsurface. Canter and Knox (1984) estimated the volume of septic tank w aste 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 cess pools can enter ground water sources through the subsurface. Other sources of fecal contamination incl ude improperly treated wastewater used to recharge ground water or to irrigate crop la nd 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 applica tion of waste waters associated with food processing or animal slaughter may also contribute to the c ontamination 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 s ubsurface 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 abandone d wells, and the presence of test holes or exploratory wells.Economic Analysis for the 2-7 October 2006 Final Ground Water Rule Well Location and/or Construction
Fecal contamination can enter inappropriately lo cated 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 contamina tion if it is not adequately cased and grouted. An improperly constructed water-supply well may allow su rface runoff or surface waters to enter through a non-existent or broken well seal. Ground water contam ination 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 gui delines. 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 th rough an improperly construc ted well penetrating the same aquifer as the properly constructed well.

Abandoned Wells
Historically, well abandonment and plugging have ge nerally 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 wa ter to spread more rapidly to other zones within an aquifer or allow contaminants to enter adjacen t aquifers at lower hydraulic pressures (USEPA, 1990). Other wells may not have been adequately plugge d, 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 ha ve 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 prope rly constructed or abandone d, 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 sy stem remains clean, contamination may occur within the distribution system. Numerous contamin ation incidents in distribution systems have been reported from systems using ground water sources. Fo r example, if proper precautions are not taken, water in the distribution system can become contam inated following routine maintenance or emergency repairs (e.g., flushing or chlorinati on). Inadequately disinfected distribution systems, including storage towers, can develop microbial mats or biofilms. Initially, biofilms may function as a filter, adsorbing pathogens (Seunghyun and Corapci oglu, 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 regulati ng the quality of drinking water. The SDWA establishes this responsibility and defines the mechan isms at the Agency’s disposal to protect public health. EPA sets standards by identifying which c ontaminants 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 usi ng 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 promulgate d regulations requiring disinfection for systems that use ground water. In th e 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 regulati ons (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 pa rt of the regulations for determining whether disinfection should be required as a treatment tec hnique 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 h as adopted regulations that are no less stringent than EPA’s. To obtain primacy for the final GWR, States mu st adopt comparable regulations within two years of EPA’s promulgation of the final rule, unless a two y ear extension is granted. State primacy requires, among other things, adequate enforcement (includi ng 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 revisi ons 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 monito ring, record keeping and reporting regulations to assist the Administrator in determining compliance w ith 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 ar e 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 rul es addressing microbial contaminants, rules addressing disinfectants and disinfection byproduc ts (DBPs), and other rules that we re considered (e.g., to determine conflict or overlap of requirements) during the ev aluation 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 ch loroform, 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. Colif orms 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. Co liform monitoring frequency is determined by population served, the type of system (community or noncommun ity systems), and the type of source water (surface water, ground water under the direct influence of su rface water (GWUDI), or ground water). In addition, the TCR required sanitary surveys every five y ears (ten years for noncommunity systems using disinfected ground water) for systems that collect fewe r 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 I CR requirements cover GWSs serving 50,000 to 99,999 people. The ICR authorized EPA to collect occu rrence and treatment information from water treatment plants to help evaluate the possi ble need for changes to the current microbial requirements and existing microbial treatment practices and to help evaluate th e 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 contamin ants. 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, UV 254 absorbency, bromide, ammonia, and disinfectant residual. These data provide some indica tion 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 ch emical 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 a nd all GWSs must comply beginning January 2004.
The Stage 1 DBPR sets Maximum Disinfectant R esidual Level Goals (MRDLGs) for chlorine (4 mg/L as Cl 2 ), chloramines (4 mg/L as Cl 2 ), and chlorine dioxide (0.8 mg/L as ClO 2 ) 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 L eevels (MRDLs) for chlorine (4.0 mg/L as Cl 2 ), chloramines (4.0 mg/L as Cl 2 ), and chlorine dioxide (0.8 mg/L as ClO 2 ) 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 chlor ite 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/softeni ng—is specified for the removal of DBP precursors.

2.4.5 2001 Arsenic Rule
The Arsenic Rule (66 FR 6976, January 2001) in creases the level of public health protection against exposure to arsenic in drinking water. Th e 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 inorga nic 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 complian ce standards set by the Stage 1 DBPR. The Stage 2 DBPR was promulgated concurrently w ith 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 TTH M and HAA5. In addition, the Stage 2 DBPR addresses systems that are in full compliance with the St age 2 DBPR LRAA MCLs but have individual DBP measurements that exceed the MCLs. The rule pr ovides a formula for determining averages for TTHM and HAA5. If these averages exceed certain levels, th e 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 cau se a violation of any primary drinking water regulation or otherwise adversely affect human hea lth. To prevent such fluid movement, EPA or the appropriate State regulatory agency may require certa in 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 wast e 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 w ith 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 re gulations 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 cess pools by April 2005. It also bans new motor vehicle waste disposal wells nationwide. Operati on of existing motor vehicle waste disposal wells in ground water source water areas or other sensitive gr ound 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 c hoosing 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 th at it intends to address (including, where applicable, the failures of the private mark ets 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 propo sed action, the analysis should discuss whether the problem constitutes a significant market failure” (USEPA, 1996a).
In a perfectly competitive market, prices and quan tities 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 ha ve 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 d ecisions 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 ma rket, 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 si ngle supplier and hostile to alternative suppliers. In such natural monopolies, suppliers have fewer in centives for providing quality services or maintaining competitive prices. In these situations, governments of ten 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 wa ter or installing point of use filtration) most often represent a higher water cost to consumers th an 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 toxicol ogical 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 in formation 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 system s in a dialogue about health issues, the transactionEconomic Analysis for the 2-13 October 2006 Final Ground Water Rule costs of such interaction (measured in personal tim e and monetary outlays) present another significant impediment to consumer expression of risk reduction preferences.
SDWA regulations are intended to provide a leve l 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 th e 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 re duction 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 treatme nt technique for all ground water PWSs only “as necessary.” To address this mandate and the public hea lth concerns presented in Chapter 2 of this EA, EPA developed the Ground Water Rule (GWR). Th e Agency convened workgroups, held stakeholder meetings, published a proposed rule, and evaluated pub lic 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 mi crobial contamination in ground water systems (GWSs). In 1993, EPA published a preliminary dr aft 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 informa tion 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 disinf ection practices gathered from 50 State drinking water programs (USEPA, 1996b). In 1997, EPA initiated a nother 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 mee tings. 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 Dall as, TX) to facilitate rule development and allow stakeholders the opportunity to comment on the regulation.
In addition to the public meetings with stake holders, 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 preliminar y draft preamble for the GWR and solicited comment. The preliminary draft preamble describ ed 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 el ements of the multi-barrier approach were sanitary surveys, triggered monitoring, HSAs, routine monito ring, 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 elem ents 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 r ecords, 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 perform ance 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 with in 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 monito ring to ensure that the treatment is effective.
Alternative 2: Risk-Targeted Approach (Final Rule Alternative)
In addition to all the sanitary survey component s 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 sampl e 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 in itial 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 corr ective 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 incl udes 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, thereb y increasing the possibility of fecal contamination. Under this alternative, each State has the opti on 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 th at do not maintain at least a 4-log treatment of viruses (using inactivation, removal, or State-appr oved 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 twel ve 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 ru le). 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 re quired 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 alte rnative 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 e ffective. 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 i ndividuals and organizations representing a wideEconomic 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 altern ative. 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 a nd 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-targete d 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 RequirementsEconomic Analysis for the 3-6 October 2006 Final Ground Water Rule 3.4.1 Mandatory Rule Components
The following subsections describe the GWR re gulatory 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 in formation that will enable the State to perform the sanitary survey. The final GWR goes beyond the exis ting 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 outlin ed 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 perfo rmance 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 th at 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, th ey must be evaluated within the required three- or five-year frequency interval. Also, the final GWR a llows 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 co rrect any significant deficiencies identified in sanitary surveys. Significant deficiencies, as determ ined by the State, include, but are not limited to, defects in design, operation, or maintenance, or a fa ilure 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 St ate 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 St ate may specify appropriate follow-up corrective action steps in the notice or may notify the GWS of appr opriate corrective actions during the consultationEconomic Analysis for the 3-7 October 2006 Final Ground Water Rule period. After receiving the written notification, the GW S 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 correc tion date. (See also the discussion of corrective actions below.)
Triggered Source Water Monitoring
A GWS must conduct triggered source water mon itoring 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-pos itive 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 inactiv ation and removal) before or at the first customer for each ground water source;
(2) the GWS is notified that a positive sam ple 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 th e 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 app lication, the State must include criteria that will be used to determine that the cause of a total co liform-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 CF R 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 th an 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 re presentative 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 s ite. 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 th e 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 r esponsible 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 receiv es 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 correc tive action. Consultation must take place within 30 days. In any event, the State may specify correctiv e action without consultation. In the consultation process, the State may approve and/or modify co rrective 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 w ithin 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, Stat es 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 documen tation 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 pos itive 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., repa irs to well pads and sanitary seals, repairs to piping tanks and treatment equipmen t, 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 existi ng 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 Providi ng At Least 4-log Treatment of Viruses
The final GWR also establishes compliance mon itoring requirements for GWSs that provide at least 4-log treatment of viruses as a corrective ac tion. The final GWR also establishes compliance monitoring requirements for those systems that have no tified 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 m onitoring 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 chlo rine, 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 alternat e 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 combin ation 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 Stat e-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 forEconomic 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 sy stem 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 mon itor 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 low est 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 th e 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 disi nfectant 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 measure ment 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 di sinfectant residual level to the State specified level within four hours. If continuous disinfectant mon itoring 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 resi dual disinfectant level to that required for 4-log inactivation of viruses within four hours, using eith er 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 requireme nts (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 tr eatment technology must monitor and operate the alternative treatment in accordance with all complia nce requirements that the State determines to be necessary to demonstrate that at least 4-log treatme nt 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 ofEconomic Analysis for the 3-11 October 2006 Final Ground Water Rule viruses must have State approval and must comply w ith 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 (HSA s) as a tool to identify high risk systems for assessment source water monitoring. States have other in formation available to them to target high risk systems, such as source water assessments, wellhead pr otection plans, and historical monitoring data. Data on past indications of source water fecal c ontamination, particularly from TCR monitoring, in combination with GWR triggered source water mon itoring 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 sy stems, EPA recommends equally distributing 12 samples or sampling during consecutive years. EPA r ecommends that States require corrective action for sources that are fecally contaminated.



### 3.5 Other Changes Since Proposal

In addition to modifications made to Alterna tive 2 since proposal, updates were made based on comments to the assumptions, data, and analytical pr ocesses 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, o ccurrence 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 m eet requirements of the GWR. The baseline allows a consistent comparison of public health impacts (dev eloped 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 a nd 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—su mmarizing the relevant characteristics of ground water sources.
Section 4.2 characterizes the water industry, in cluding the baseline estimates of systems, entry points, and population subject to the GWR. This sec tion 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 signifi cant uncertainties in the baseline analysis.
This chapter presents an analysis that is at a level of detail and precisi on appropriate to support subsequent analyses and regulatory decisions under c onsideration for the GWR. Therefore, it does not give an exhaustive review of the water suppl y 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 4 th 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 averag e 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 data base for the drinking water program. It includes information on the nation’s 170,000 public water system s (PWSs) and on violations of drinking water regulations. For more informati on 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 th e Water Industry Baseline Handbook (Baseline Handbook) (USEPA, 2001a) published in May 2001, which compil es 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 th at provided a sampling frame for the main data collection in Phase 2. The survey sample in Ph ase 2 was stratified according to water system size (residential population served), owne rship (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 questionna ire. 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 a nd 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 wh ich 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 subdivi sions 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 wa ter and surface water and are referred to as “mixed systems.” In SDWIS and the Baseline Ha ndbook, 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 anal ysis 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 wate r 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 serve d (i.e., not including population of wholesale customers). In the analyses that follow, nine size cat egories 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 technol ogies 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 syst ems are owned by private corporations or individuals. Public systems are owned by public entities such as m unicipalities, 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 system s 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 c onsecutive 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 sm all 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 so lely 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 sour ce). 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 acc ount 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 sy stem 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 th e 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 b aseline 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-onlysystems 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 bene fits. The contrasting over- and under-accounting for ground water entry points are expected to offset one anot her 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 pr esented 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 da ta (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 select ed 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 we re 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 system s chosen represent the full range of population served within any given size category. The resulting syst em 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 ≤100 174 1,402 120 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 1,576 15,858 569 23,496 41,499 4,850 3,813 1,854 823 11,340 NTNCWSs ≤100 11 1,913 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 51 6,559 32 12,266 18,908 TNCWSs ≤100 71 51,730 521 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 134 56,444 583 28,900 86,061 Grand Total 1,761 78,861 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 360 325 116 60 862 1,936 16,183 685 23,556 42,361 NTNCWSs ≤100 11 1,913 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 51 6,559 32 12,266 18,908 TNCWSs ≤100 71 51,730 521 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 134 56,444 583 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 Syst ems (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 re presents 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, re moval, or State-approved combination of these technologies) before or at the first customer. Exhi bit 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 Disinfectin g Ground 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 1,529 12,925 514 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 15 1,902 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 24 10,160 105 5,202 15,491 110 46,284 478 23,698 70,570 Grand Totals 1,568 24,987 629 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 m illion people. The three ground water systems serving >1 million people all perform disinfection. NTNCWS and TNCWS percent disinfecting derived from Ground Water Dis infection Practices in the United States (USEPA 1996b).

System Size (population

served) Percentage 2 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: Disinfecting 1 

### and Nondisinfecting SystemsEconomic 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 m onitoring in response to GWR requirements. Ground water systems can consist of one entry point suppl ying all water to the population, or multiple entry points treating water, possibly from different sources.
As with the system baseline, the GWR require ments at the entry point level also depend on whether disinfection is applied. In order to estimat e baseline disinfection rates, EPA analyzed data from a survey of disinfection practices in CWSs servi ng 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 curre ntly 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 treatme nt 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 ach ieved 4-log inactivation of viruses before the first customer. Because of their small size and usually si mple design as well as the transient nature of the populations they serve, TNCWSs are believed to be th e 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 viru ses before the first customer. Many NTNCWSs are relatively simple systems that share many character istics with TNCWSs. However, many also share characteristics more like CWSs (e.g., systems serving la rge institutions). Because of this dichotomy, EPA estimated that the percentage of NTNCWSs that a pply 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 entr y 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 distributi on of costs and benefits of the GWR can be assessed. Exhibit 4.4 presents the system-level population base line and Exhibit 4.5 presents the entry point-level baseline.
As presented in Exhibit 4.4, ground water CW Ss serve over 100 million people, while ground water NCWSs serve about 14 million people. Overla ps 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 popul ations 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 1.3 45.6% 52.0% 59 439 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 1,720 15,581 488 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 5 590 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 2 1,016 10 520 1,549 132 55,428 573 28,380 84,512 Grand Totals 1,727 17,186 501 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

136 1,007 94 7,931 9,168 55 405 38 3,191 3,689 303 1,908 137 3,996 6,343 391 2,463 177 5,159 8,191 158 1,331 45 729 2,262 228 1,926 65 1,055 3,274 267 2,834 67 834 4,002 331 3,516 83 1,034 4,964 186 1,888 29 356 2,459 248 2,514 39 474 3,274 50 538 7 102 698 256 2,746 37 520 3,559 50 576 7 137 770 35 403 5 96 538 20 170 3 34 227 45 377 6 75 503

- - - - - - - - - - 1,170 10,252 389 14,117 25,929 1,588 14,351 450 11,604 27,992

8 1,358 9 5,338 6,714 2 383 3 1,505 1,892 13 2,184 10 2,592 4,798 4 616 3 730 1,352 5 825 2 513 1,345 1 233 1 144 379 6 266 1 236 508 2 75 0 66 143 3 20 1 28 52 1 6 0 8 15 2 4 - 1 7 1 1 - 0 2

- 1 - - 1 - 0 - - 0

- - - 1 1 - - - 0 0

- - - - - - - - - - 36 4,657 23 8,709 13,425 10 1,312 6 2,454 3,783

58 42,419 427 9,943 52,847 12 8,380 84 1,964 10,441 27 3,094 37 12,416 15,574 5 611 7 2,453 3,077 15 510 7 1,059 1,591 3 101 1 209 314 7 220 4 248 480 1 43 1 49 95 1 34 2 25 61 0 7 0 5 12 1 7 1 7 16 0 1 0 1 3 1 - - - 1 0 - - - 0

- 1 - - 1 - 0 - - 0

- - - - - - - - - - 110 46,284 478 23,698 70,570 22 9,144 94 4,682 13,942 1,316 61,193 890 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 p eople. Ground water systems serving >1 million people (3) all perform disinfection. NTNCWS and TNCWS percent disinfecting derived from Ground Water Disinfe ction 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 Purchased NonPurchased Purchased NonPurchased Purchased NonPurchased 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 58 5,882 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 6,462,088 67,937,134 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 50 161 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 30,350 715,762 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 38 488 355,608 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 18,984 700,897 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 6,511,422 69,353,793 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 Population Total Average Population per System Nondisinfecting Systems Population 

### Exhibit 4.4 Ground Water Rule System Population BaselineEconomic 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 Purchased NonPurchased Purchased NonPurchased Purchased NonPurchased 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 44 2,641 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 Mi llion 16,727 807,902 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 2,935,880 32,995,805 487,848 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 Mi llion 110,000 - - - 9,889 9,889 - - - 100,111 100,111 > 1 Million - - - - - - - - - - - National Totals 9,409 221,886 1,128 230,418 462,841 95,247 2,246,259 11,416 2,332,632 4,685,555 TNCWSs ≤100 38 49 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 Mi llion 125,000 - 2,250 - - 2,250 - 122,750 - - 122,750 > 1 Million - - - - - - - - - - - National Totals 1,898 70,090 1,197 84,154 157,340 103,567 3,823,784 65,314 4,591,087 8,583,753 Grand Totals 2,947,187 33,287,781 490,172 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 Purchased NonPurchased Purchased NonPurchased Purchased NonPurchased 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

6,060 44,743 4,188 352,511 407,502 2,438 18,002 1,685 141,834 163,960 43,689 275,256 19,777 576,465 915,187 56,413 355,415 25,537 744,341 1,181,706 57,444 484,903 16,311 265,589 824,247 83,162 702,000 23,614 384,496 1,193,271 202,119 2,147,537 50,666 631,825 3,032,147 250,715 2,663,869 62,848 783,734 3,761,167 325,599 3,304,641 51,401 622,721 4,304,361 433,476 4,399,537 68,431 829,041 5,730,486 183,619 1,971,158 26,888 372,898 2,554,563 936,711 10,055,659 137,168 1,902,300 13,031,838 287,937 3,316,557 40,045 787,639 4,432,178 201,372 2,319,471 28,006 550,844 3,099,693 336,437 2,847,909 46,481 566,631 3,797,458 745,756 6,312,758 103,032 1,256,010 8,417,556

- - - - - - - - - - 1,442,904 14,392,704 255,758 4,176,277 20,267,644 2,710,043 26,826,712 450,321 6,592,600 36,579,676

394 68,514 466 269,294 338,668 111 19,309 131 75,896 95,447 2,889 493,696 2,247 585,823 1,084,655 814 139,139 633 165,103 305,689 3,343 555,013 1,433 344,853 904,643 942 156,420 404 97,190 254,956 8,816 412,137 1,102 365,854 787,909 2,485 116,153 311 103,109 222,057 14,636 102,449 3,659 146,355 267,098 4,125 28,873 1,031 41,247 75,277 44,228 73,713 - 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

- - - - - - - - - - 74,306 1,752,383 8,906 1,819,766 3,655,361 20,942 493,876 2,510 512,866 1,030,194

2,223 1,619,993 16,316 379,742 2,018,274 439 320,047 3,223 75,022 398,732 4,788 547,445 6,529 2,197,036 2,755,799 946 108,154 1,290 434,049 544,438 9,455 326,736 4,728 678,160 1,019,079 1,868 64,550 934 133,978 201,330 10,452 311,234 5,807 351,880 679,372 2,065 61,488 1,147 69,518 134,217 4,114 168,687 8,229 123,429 304,459 813 33,326 1,626 24,385 60,149 12,931 116,382 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

- - - - - - - - - - 86,482 3,192,977 54,539 3,833,698 7,167,696 17,085 630,808 10,775 757,389 1,416,057 1,603,691 19,338,064 319,204 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 di vided 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 discu ssion 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, contai ning data for over 170,000 PWSs. SDWIS stores Statereported information on each water system, includi ng name, ID number, population served, type of system, and source of water (ground water or su rface 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 wa ter 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 representati on of the total universe of CWSs. This weighting factor was used in all evaluations of data. Th e 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 publishe d report by confidence bounds (95 percent) on the means and proportions provided. While these confid ence 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 th e 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 ar e 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 44 0.016 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 50 0.02 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 38 0.01 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) re lating 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*X 0.97708 )/1,000
Average Daily Flow (MGD) = (0.06428*X 1.07652 )/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 entr y 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 estim ate 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 tota l 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 d esign flow to population were not performed for the NCWSs. Other drinking water rules have eval uated flows for NCWSs according to service categories (e.g., schools, restaurants, hotels, and industry) inst ead 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 Ch apter 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 equa tions to NCWSs, recognizing that this may over-estimate flows and, therefore, costs. This ove r-estimation is addressed as part of the uncertainties summarized in section 4.5. Mean plant flows fo r 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 w ith the GWR, the EA takes into account the percentage of systems presently employing certain typ es 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 ru le 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 numbe r 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 wate r 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 Purchased NonPurchased Purchased NonPurchased Purchased NonPurchased <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 2,495,015 26,230,554 412,121 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 Treatme nt 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 to tal 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. The2 X-log virus inactivation or removal means that only one of every 10 x 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 syst ems, 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 Ve rification (DV) project were used as the primary inputs for modeling the occurrence of TC-positive sampl es, while data from other sources were used for weighting results. The following is a summary of th e 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 di screpancies between the two records. State files contain the water systems’ reports on the numbers of total coliform sam ples taken to comply with the TCR and the numbers of TC-positive samples. Using these data, EPA deri ved 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 a nd 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 sy stem. 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-log 2 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-years 3 of data and 18,467 TC samples4 There are several reasons why states could not be incl uded in the analysis. Four States, (Alaska, Colorado, Connecticut, and Illinois), the U.S. Territories and Regiona l 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 c ould not be located. Texas requires disinfection by all ground water systems, but the DV project identified one wholes ale system that took samples of source water before disinfection, and so the one Texas system was included. Da ta 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, 4 th Quarter

6 USEPA, 1996b

7 In a few cases, the rounding caused the estimated num ber 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 States 4 and is broadly representative of nondisinf ecting 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 inventory 5 for the number of ground water systems and a 1996 EPA study 6 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 ra te 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 states 8 . This expanded data set improves the estimate of the average numbe r 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 th e 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 Chap ter 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 wate r quality data that are used in the GWR risk assessment model. It describes how existing histor ical, geological, and water quality (e.g., pathogen occurrence) data are used to ch aracterize the baseline conditions for ground water systems. Next it describes how this information is used in a ri sk assessment model to estimate the baseline number of illnesses and deaths associated with ingesting pathoge nic viruses (only) in public ground water systems. The standard framework is organized in accordan ce with EPA Policy for Risk Characterization (USEPA 1995a), EPA’s Guidance for Risk Characteri zation (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 scien tific data (or reasonable assumptions if data are not available) to produce estimates of the nature, exte nt, 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 uncerta inty 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 distri bution 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 d escribe 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 sour ce water, disinfection treatment effectiveness, daily drinking water consumption, number of days of e xposure, and size of the exposed population. Pathogen occurrence probabilities and concentration are of par ticular 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 pa thogens, the fraction of time that pathogens areEconomic Analysis for the 4-24 October 2006 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 contaminat ed well is assigned a probability that designates the fraction of time, that its source water has a detectab le virus contamination. (At other times the water is assumed to be virus free.) This occurrence modeli ng is discussed in greater detail in the following sections. The use of the baseline data to suppor t 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 (di scussed in section 4.3.1.1). The second is the division of the universe of wells within the US into “more” and “less” vulne rable 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, sev erity, 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 ar e 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 vi ruses generally do not result in life-threatening illnesses. A common illness associated with Type A vi ruses is gastroenteritis, sometimes accompanied by vomiting.
The Type B group represents viruses that have lo w 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 ot her 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 bot h bacterial and viral pathogens to support this EA since the GWR will mitigate against risk from both concerns. While data (though limited) areEconomic Analysis for the 4-25 October 2006 Final Ground Water Rule available to characterize viral o ccurrence, insufficient data are av ailable to characterize pathogenic bacterial occurrence. Therefore, the primary anal ysis 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 wa ter occurrence studies (EPA, 2006b). This section explains the rationale for selecting the 15 studies fo r 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 expect s 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 u se of these limited data. The statisticians strongly recommended that EPA make use of all the ava ilable 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 co mbined 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 inde pendently 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 sel ected 15 studies with results that are directly applicable to evaluating GWR benefits. These st udies 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 vulne rability to fecal contamination. Another data set, Abbaszadegan et al. 2003, targeted a representati on of wells throughout the United States based on hydrogeological conditions, but excluded any wells that were poorly constructe d 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 captu re 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 Vi ral Occurrence Data (Including Uncertainty)
When evaluating enteroviral occurrence data, it is important to realize some of the fundamental challenges in characterizing enterovi rus occurrence, including detection, identification and concentration. Key issues include recognizing the limitations of ente rovirus 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 viruse s 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 de tect enteroviruses is inefficient for detecting rotaviruses in well water. There are few infectious rotavirus occurren ce data available for making direct rotavirus health effect predictions. Rotaviruses are ubiquitous in nature, exemplif ied 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 a nd therefore underestimate the health effects predictions.

Economic Analysis for the 4-26 October 2006 Final Ground Water Rule EPA relies only on the identification of enteroviru s in PWS wells using cell culture methods since they allow identification of infectious pat hogenic 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 method 9 , 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 dependi ng on the water chemistry and the viral strains present. Virus recovery can range from less than 20% to gr eater 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 con centration 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 dependi ng on the water chemistry, the type of cell culture used and the type of virus.

The standard host cell line used to recover hum an 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 mo re than 250 times or if it has been longer than one week since the last passage.

Furthermore, concentration estimates derived fro m 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 othe r 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 sam ple, depends on water chemistry, the type of cell culture used, and the type of virus.
Viral occurrence can be characterized by cons idering 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 anticip ated exposure duration. Available data indicate that viral concentration at one site ta ken 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 wellsEconomic Analysis for the 4-27 October 2006 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 es timates of probabilities and concentrations difficult.
In addition to the general issues regarding vi ral 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 evalua te a molecular biology monitoring method (PCR) to identify viral genomic material without considerati on 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 we re 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 to tal 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 se tting (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 Ph ase I sampling. In aggregate, the 30 wells selected for monthly sampling represent a group of wells consid ered 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 we lls. 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.Economic Analysis for the 4-28 October 2006 Final Ground Water Rule 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 fo r enterovirus or reovirus. While 7 of the 30 wells sampled had a cell culture positive among the twelve sam ples taken, most of the measurement were below detects. One of the wells had 5 monthly viral positiv es, two of the wells had 4 monthly positives, one of the wells had two monthly positives, and three we lls 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 contaminati on. 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 existen ce 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.Economic Analysis for the 4-29 October 2006 Final Ground Water Rule 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 i ndicators 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 evalua te 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 we re 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 checklis t 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 appare ntly 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 an alyzed 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.Economic Analysis for the 4-30 October 2006 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 propor tion 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 measure d in the Abbaszadegan et al. 2003 study wells to determine if there was any statistically significant di fference 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 urba n components and chose a small random subset of these, comparable in size to the sample in the Abbaszadegan et al. 2003 st udy 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 we lls 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, wh ich also may underestimate the risks associated with these wells.10 In using the cell culture method for enterovirus det ection, 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.

Economic Analysis for the 4-31 October 2006 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 disi nfection 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 analys is 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 mo re direct, and there are fewer opportunities for virus concentrations to become attenuated due to in teraction with the aquifer solid materials.
The Lieberman et al. 2002 study found higher vi rus concentrations and a greater range of concentrations than those measured in the Abbaszadegan et al. 2003 study 10 . 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, vi rus 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 bi ases 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 (N CWS) wells in primarily carbonate aquifers and crystalline aquifers, which are hydrogeologically sen sitive 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 pathoge ns in ground water used for non-community water supplies and indicator organisms (evaluated as surrogates for those pathogens).Economic Analysis for the 4-32 October 2006 Final Ground Water Rule Well Selection
USGS personnel, in collaboration with the Pennsyl vania 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 consid ered to be a sandstone or a quartzite. Aquifer sensitivity is best determined by the State, a nd EPA cannot make that determination based on the available data.
The vast majority of the sites were TNC PW S 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 we lls, male-specific coliphage in 2 wells, and enterococci in 8 wells.

Of the 5 wells with detectable culturable viru ses, 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 sampl ed human pathogenic virus data from TNC wells among the 24 studies considered. As such, it is an im portant 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 fe wer 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 a nd enteric viruses, and consider the factors that affect the presence of enteric viruses.Economic Analysis for the 4-33 October 2006 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 aqui fers, 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 exis t, 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 Mich igan from 38 wells in discontinuous sand and gravel aquifers. Not all 38 wells were sampled for all parame ters. 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 we ll (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 undi sinfected wells because well operators did not allow sampling. Thus, this study is representative of the la rge 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 we ll 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 pat hogenic 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 gr ound water wells (128 from all wells) between June 1999 and February 2002. One well with one sample w as 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 i ndicator 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 th e 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 confin ed 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 c onfined 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 a quifer 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 sampl e (and others) had some quality assurance problems due to cross contamination of samples with the polioviru s 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 wa ter 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 character ized 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 bot h unconfined and confined aquifers. Wells (all of which were constructed be fore 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 curren tly 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 th e 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 Nove mber, 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 determin e 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 crite ria: (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 Isla nd, 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 aquife rs, 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 fo r enteric viruses by cell culture.

Data Representativeness

No information is available to eval uate 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 shallo w 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 sam pled 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 cu lture. This sample was identified as rotavirus by a non-standard test using an assay method normally used to detect rotaviru s in stool. Because the assay method works primarily for rotavirus at high concentra tions, this well was considered to be enteric-virus positive but not necessarily rotavrirus-positiv e. None of the wells was positive for E. coli

. Data Representativeness
These data are representative of deep wells in non-sen sitive 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 Pi edmont Physiographic Province counties. Wells were selected to distribute the sample sites evenly over the population a nd spatial extent of the study area. One well was selected randomly.
Sample Results
None of the wells was positive for enterovi ruses by cell culture. One well was positive for E. coli

. Data Representativeness
These data are representative of shallow wells in fr actured 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 contaminat ed 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 charact erize 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 a ddition 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 vul nerable. 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), fract ured crystalline bedrock (nine wells), sandstone (28 wells), sand and gravel (29 wells) and rego lith (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 repr esenting a variety of conditions relevant to the vulnerability predictions, (2) wells with nearby s ources 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 th e 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 aquife r 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 availa ble 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 identif ied 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 wate r wells (not regulated by the GWR). The raw data were not proved by the investigators so counting and analysis of the PW S 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 commun ity 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 f our wells had substantial surface water contribution. Because this study is small, all from the same comm unity 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 an alysis discussed later in this chapter.Economic Analysis for the 4-42 October 2006Final Ground Water RuleExhibit 4.13a New Data Available since publication of the Proposed GWRStudy # PWS WellsSampled &LocationSampling frequency/volume Indicators Monitored (#Pos. Wells/# Wells Total,Unless Otherwise IndicatedPathogenic Viruses,Legionella,(#Pos. Wells/ #Wells Total, UnlessOtherwise Indicated)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)Cell culture: enteric virus (5/59)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 1602Method 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).Cell culture:enterovirus (2/20), Rotavirus(7/20), RT-PCR: enterovirus(5/20), rotavirus (9/20),norovirus (8/20), adenovirus(1/20)Economic Analysis for the 4-43 October 2006Final Ground Water RuleEnvironmental 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)Cell culture: enterovirus (2/34)(2/93 samples)RT-PRCR: enterovirus (4/38)HAV (5/38)Rotavirus (0/34)Reovirus (0/34)Norovirus (0/34)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 wellsTwo 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)RT-PCR:Enterovirus (5/6)Rotavirus (4/6)Hepatitis A (3/6)Norovirus G1 (3/6)Norovirus G2 (0/6)Cell culture:Enterovirus (0/6)Hepatitis A (3/6)Economic Analysis for the 4-44 October 2006Final Ground Water RuleMountain 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%)Enterovirus (0/2)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 sampledfrom 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 timesE.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.coli11 EPA believes this terminology is more appropriate than that used in the proposal (“improperly constructed” and “properly constructed”) since the Lieber man 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 th at 17 percent of the wells in the United States were improperly constructed and th at 83 percent of the wells were properly constructed (ASDWA, 1997). EPA used the Lieberman et al. 2002 data set to repr esent 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 vulne rability (i.e., poorly constructe d 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 becau se 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: t hose that are more vulnerable and those that are less vulnerable. 11 Neither of the studies discussed above provi de data regarding the percentage of ground water sources that might be more or less vulnerable, and EPA needed to derive such estimates to supportEconomic 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 da ta. 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 viola tions 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 vulnerabl e” 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% mi nus the value identified in the exhibit. Detail on the derivation of these percentages is presented in Exhi bit 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 sam ple 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 ma y 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-s ource water-related contamination is likely to be very low relative to that of source water. In summa ry, it is assumed that disinfection has only a small influence on the identification of more vul nerable wells using TCR violation data.



### Exhibit 4.15 Number and Per cent 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 4.212 Although the GWR is aimed at preventing exposure to a ll 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 viral 12 and indicator 13 hit rates, viral concentrations, and cooccurrence of viruses and indicators. Cost and be nefit analyses performed for the EA accompanying the GWR proposal drew data from two of the occurrence st udies 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 works hop in May 2005. The core workgroup included expert participants form several government agencies and pr ivate consulting firms. A summary of the workgroup proceedings, including a list of all participants, is in cluded in the final docket for this rulemaking. The charge to the workgroup was to consid er 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 work shop, EPA acted on the workgroup’s recommendations, provided feedback to participan ts, and generated model-based na tional 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 comb ined model serves as the basis of EPA’s quantitative occurrence estimates. The sections be low 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. Collectivel y, 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. B ecause the final selection of data was beyond the scope of their expertise, the issue was remanded for further consideration by EPA’s subj ect matter experts. The discussion of each occurrence study is presented in Sec tion 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 rat es 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 indicator s. 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 fre quently each is expected to be present. Hit rates, therefore, have two components which are referred to here as P well and P sample .
P well 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.

P sample 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 P well 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 P sample 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 th e estimation, as well as the interpretation, of P sample . 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 ar e present in samples are not always detected. In addition, the actual presence of microorganisms in th e source water is recognized as being intermittent in nature due to changes in the actual sources of th e 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 P well value applies to all wells, each individual contaminated well is expected to have its own P sample 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 P sample values was derived to reflect P sample variability from well to well. Specifically, a beta distribution of P sample 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. (T he probit and logit distributions are sometimes used for this purpose, and generally produce estimates simila r 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 distri bution; the parameters are usually designated α and β . The estimation of those parameters for the beta distribution of P sample 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, a nd 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 a nd Viral Classification Among PWS Wells in U.S.

To fully characterize both P well and P sample for viral pathogens and fecal indicators, and to characterize their co-occurrence, th e model requires the estimation of seven parameters: P1, P2, P3, α virus , β virus , α indicator , and β indicator from the available occurrence data. P well for virus is equal to P1+P2, and P well for indicators is equal to P2+P3. P sample for viruses (referred to hereafter as Pv sample ) at different wells isEconomic Analysis for the 4-52 October 2006 Final Ground Water Rule described by a beta distribution with the parameters α virus and β virus . Similarly, P sample for indicators (referred to hereafter as Pi sample ) at different wells is described by a beta distribution with the parameters

α indicator and β indicator .

It is important to note that the occurrence m odel developed by EPA relates virus and indicator co-occurrence only in terms of P well (the fraction of wells having one, the other, or both). It does not provide for different levels of Pv sample or Pi sample 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 Pv sample and Pi sample 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 P well and the α and β parameters for P sample as though only single “best values” are estimated, the occurrence model is act ually 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 pe rformed 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 distributi on (the sample of 10,000 discussed in the paragraph above). This posterior density f unction 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, wher e 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 likew ise, 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].

Pv sample and Pi sample are both assumed to be beta-distributed across wells having virus presence and wells having indicator presence, respectively. The Be ta density function is usually expressed in terms of its parameters α and β as:

dbeta p α , β
, 

### ( ) 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 P sample 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 imprope r 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 P sample 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 parame ters (a and b). The conve ntional beta distribution parameters can be derived from ne w parameters a and b as follows:

α = a / b 2 β = (1 – a) / b 2

Therefore, for parameterization of the occurrence model, a virus , b virus , a inidicator , and b indicator 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:

N v = the total number of virus assays for the well K v = the number of virus positives for the well N i = the total number of indicator assays for the well K i = the total number of indicator positives for the well
Up to three of these may be zeros; at least one of the values N v or N i 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 th e parameter values and the well's data (the well's N v , K v , N i , and K i values), where 

### " virus and 

### $ virus are parameters for beta-distributed Pv sample for viruses and



### " indicator and 

### $ indicator are parameters for beta-distributed Pi sample 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 pa rts, 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 th e four different categories (virus only, virus and E. coli
, E. coli only, and no contamination):Economic Analysis for the 4-54 October 2006 Final Ground Water Rule L1 K v N v , 

# ( ) P1
0 1 Psample v dbeta Psample v α v

, β v , 

# ( ) dbinom K v N v , Psample v , 

# ( )

⋅ ⌠ ⎮ ⌡ d

⋅

L2 K v N v , K i , N i , 

# ( ) P2 L1 K v N v , 

# ( )

⋅ 0 1 Psample i dbeta Psample i α i , β i , 

# ( ) dbinom K i N i , Psample i , 

# ( )

⋅ ⌠ ⎮ ⌡ d

⋅

L3 K i N i , 

# ( ) P3
0 1 Psample i dbeta Psample i α i , β i , 

# ( ) dbinom K i N i , Psample i , 

# ( )

⋅ ⌠ ⎮ ⌡ 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 th e binomial probability mass function. A well of this type must have had no E. coli detections, so the probability of observing K i = 0 positives is 1 and its product with L1(K v , N v ) is simply L1(K v , N v ).

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 numbe r 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 othe r parameter values at that time. In this fashion, parameters P1, P2, P3, and P4 also enter the likeli hood. 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 ot her 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 contamina tion 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 resultsEconomic 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 P 3 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 parame ters was the enteroviruses cell culture data for viruses and the E. coli for the indicators data from the 15 occurre nce studies described in Section 4.3.2. Of those 15 studies, 12 have enterovi rus cell culture data and 12 have E. coli data.
The following exhibits provide summaries of the P well and P sample 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 5 th and 95 th 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 Ch ain 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+P 2+P3 (wells with sometime presence of virus and/or indicator) is 32.4%. The 5 th and 95 th 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 viru s 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 5 th andEconomic 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 Indica tor 95 th 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 fa ll 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, th en 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 P well for viruses and P well for indicators. These are composed of P1+P2 for viruses and P2+P3 for indicators. Exhibit 4.18 provides the median (and the 5 th and 95 th percentile values) for P well for viruses and for indicators.



### Exhibit 4.18 Median of 10,000 Estimates of P well 

### for Virus and Indicator (with error bars showing the 5th and 95th percentiles)

The median value of P well for viruses was found to be 23.6% with 5 th and 95 th percentiles of 9.8% and 55.5%. The median of P well for indicators was 22.5% with 5 th and 95 th percentiles of 11.6% and 55.5%. As shown in Exhibit 4.18, median values and overall ranges of P well for viruses and indicators are quite similar. However, the distribution of pa ired 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 andEconomic 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 VirusesPwell 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 P well 

### Pairs for Indicators and Viruses

As described above, the Pv sample for viruses and Pi sample for indicators are not single value estimates but are, rather, distributions of values reflecting the variability in P sample from well to well. As a result, the occurrence model generates 10,000 of these distributions for both Pv sample and Pi sample . 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 P sample have three different shapes: exponential, U-shaped, and bell-shaped (right-skewed). Representativ e examples of these three shapes for P sample 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 exampl es were selected because they present values that are close to the central tendencies for the three distribution shapes of P sample for viruses.)

For P sample 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 P sample 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 P sample 

### for Viruses

Exhibit 4.21 Cumulative Distributions of P sample 

### for Viruses

One way to summarize the full set of 10,000 P sample distributions generated by the occurrence model is in terms of the range and central tendency of their expected values. For Pv sample , the median of the expected values is 9.4%, with 5 th and 95 th percentile values are 3.8% and 23.2%, respectively. For Pi sample , the median of the expected values is 12.7%, with 5 th and 95 th percentile values are 4.9% and 25.0%, respectively. These values are also shown graphically in Exhibit 4.22.Economic Analysis for the 4-59 October 2006 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 A verage Psample Virus Average Psample Indicator 

### Exhibit 4.22 Median of 10,000 Estimates of P sample 

### for Virus and Indicator (with error bars showing the 5th and 95th percentiles)

The range and central tendency of the expected values for Pv sample and Pi sample are similar. The distribution of expected values for Pv sample and Pi sample pairs produced by the model, shown in Exhibit 4.23 for a sample of 1,000 pairs, shows a substantial numbe r of pairs where both have values in the 5% to 15% range. However, there are a number where one of the pa ir 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 (a v )Mean of Psample for Indicators (ai) 

### Exhibit 4.23 Scatter Plot of Means of P sample 

### Pairs for Indicators and Viruses

An important relationship that can be seen from the results of the occurrence modeling is between paired P sample means and P well values. For both viruses and indicators, it was found that there is, generally, an inverse relationship between them. The product of P well and the average of P sample is approximately equal to the overall fraction of samples found to be virus-positive, therefore the inverse relationship is expected. If either P well or the average P sample 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 th e 10,000 sets of results from the occurrence modeling is that if the ‘true’ value of P well (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 P well 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 set s 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
PwellAverage 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
PwellAverage Psample (ai) 

### Exhibit 4.24 Mean of P sample 

### Versus P well 

### for Viruses (1,000 Pairs from Occurrence Model)

Exhibit 4.25 Mean of P sample 

### Versus P well 

### for Indicators (1,000 Pairs from Occurrence Model)14 The discussion below can also be applied to estimat e 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 samp les taken, which will be more under assessment monitoring scenarios.

Economic Analysis for the 4-62 October 2006 Final Ground Water Rule F n i

, Piwell n 0 1 Ps

dbeta Ps α n , β n , 

# ( ) 1 1 Ps

− ( ) i 1 +

− 

### ⎡ ⎣ ⎤ ⎦

⋅ ⌠ ⎮ ⌡ d

⋅



### , which simplifies to:

F

n i

, Piwell n Piwell n Γ α n β n + 

# ( ) Γ β n i + 

# ( )

⋅ Γ α n β n + i + 

# ( ) Γ β n 

# ( )

⋅ ⋅ −



### . Use of Indicator Occurrence for Triggered Monitoring 14

This section describes how the occurrence modeli ng 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:

Pi well = fraction of wells with some indicator occurrence

α i = first parameter of beta-distributed Pi sample β i = second parameter of beta-distributed Pi sample As discussed in the section above, in each uncertain ty iteration of the occurrence model, a set of parameter values describing indicator occurren ce is selected from the MCMC sample (as well as parameters for Pv well and Pv sample that describe virus occurrence). Th e probability that an indicator positive will be observed by the time of the i th assay can be obtained from F n,i : The probability that the i th assay will be the very first positive for the site is the difference F n,i -

F n,i-1 . This is, then, the fraction of all wells e xpected to return an indicator positive upon the i th assay.
These probabilities (the F n values) were derived for assays i = 1 through 200 for n = 10,000 uncertainty iterations. These probabilities are speci fically 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 5 th percentile, median, and 95 th percentile of all values for that assay number. These data are used in the co st model simulation, discussed further in Chapter 6, to determine whether, and if so when, a given well conducting triggered source water monitoring willEconomic 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 numberProbability 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



### ) 3 2 ( ) 2 1 ( 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 unde r 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 furthe r 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 F n,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 pr obability result obtained as shown above is to multiply it by:

Exhibit 4.27 shows the three corresponding distribu tions 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 unde r 50% would be expected to have a positive on orEconomic 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 numberProbability 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 200 th 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 late r 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, P sample ) is greatest.
4.3.4.2 Pathogen Concentration Analysis
The preceding section addressed hit rates, which co mprise the first aspect of characterizing virus occurrence in source water used by public ground water wells. This section addresses virus concentrations which comprise th e second aspect of occurrence.15 Although hit rates were developed for bot h viruses and indicators, virus concen tration modeling is necessary for the risk and benefits analysis, but E.coli concentration modeling is not. For the indicat ors, 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 "p resence / absence" of virus in the water. The two components of hit rates are P well , which characterizes the fraction of wells where viruses are either present at some time or are never present, and P sample , 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 detect ed (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 fro m regulatory alternatives can be estimated 15

.
The available information on virus concentrati ons in wells is limited. Although the analysis performed here considers two categories of pathogeni c 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 assume d that the concentrations of Type A viruses are similar to those for Type B.
Just as there is variability in virus occurrence w ith respect to prevalence (some wells have viruses while others do not, and for those that do, the fre quency of occurrence varies among contaminated wells), so too, there is variability in expected concen trations of viruses from well to well among those wells where viruses occur. As will be evident from th e information presented, this variability encompasses both large scale differences between those wells consider ed 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 Ma y 2005 statistics workshop were asked to consider how to model virus concentrations in virus-positive we ll 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 baselin e 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 we lls). Unlike the hit rate analyses which draw on data from 15 different studies, EPA relied upon only thr ee 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 vulnerabl e 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 mo st 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 vulne rable wells group. Furthermore, the Pennsylvania wells are exclusively noncommunity wells and ther efore 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 a nd the Pennsylvania Noncommunity Well studies as providing the most complete set of virus concentr ation 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 we re a total of 22 samples taken from 21 different wells with cell culture concentration da ta, 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 0.18Economic 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 concentra tion 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 Ma y 2005 statistics workshop discussed alternative distributional forms to fit to the concentration da ta 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 considerab le 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 reduc tion 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 P sample 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 a nd periodic reporting of data on waterborne disease outbreaks since 1971. The CDC database and bienni al 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 availa ble data since the implementation of the currentEconomic 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 Ru le). 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 influenc e (and are subject to surface wate r 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 o ccur (National Research Council 1997a, Frost et al., 1996). Some of the reasons for the lack of rec ognition and reporting of outbreaks include the following.


### C Some States do not have active disease surveillan ce 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 occurre nce of small outbreaks, even in States with effective disease surveillance systems. In c ities, large outbreaks are more likely to be recognized than sporadic cases or small out breaks 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 ha ve 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 investigat ed. 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 in termittent or one-time contamination events.


### C The vast majority of ground water systems ar e 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, documente d 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 inad equate 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 a nd/or benefit estimates presented in Chapters 5 and 6. Exhibit 4.32 presents a summary of these uncertainti es 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 Uncertainti es Affecting GWR Baseline Estimates

Uncertainty Section with Full Discussion of Uncertainty Effect on Benefit Estimate Effect on Cost Estimates

Underestimate Overestimate Unknown Impact Underestimate Overestimate Unknown 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 XEconomic 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 h it 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 indicat or 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 m odeled between indicator and virus is the fraction of wells having both (P2) as compared to wells having only vi rus (P1) or only indicator (P3). It is likely that wells containing E. coli and virus will have virus more often a nd at higher concentrations than in wells containing only virus. Not mode ling 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 th e 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 vira l and bacterial pathogens present in ground water wells due to intrusion of fecal matter. The health-relate d benefits of the GWR are due to reductions in both endemic and outbreak risks and reductions in both acu te 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 sub set of quantified benefits quantified in this EA with the total (both quantified a nd 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 quan tified, 2) no quantified be nefits 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 Quanti fied 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 individualsReduction 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 quantifiedBenefit 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 • A voided 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 • P erceived 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 hea lth and nonhealth benefits of the GWR uncertainties and sensitivities and presents a comparison of other regulator y 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 pathoge nic 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 be nefits, 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 overv iew of the risk assessment methodology is presented inEconomic 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

1 This schematic presents an overview of only the quantifiable be nefits 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

1 This schematic presents an overview of only the quantifiable be nefits 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 pr esented 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 resu lts 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 va lues to the results of the risk reduction analysis to estimate the value of the illnesses and deaths a voided in exposed populations. The assumptions and inputs used to determine the unit values of avoide d illness and death are discussed in section 5.3.1 and Appendix A of this EA. The results of this analys is, 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 Pathoge n Risk Assessment and Benefits Valuation Procedure for Quantified Benefits (Main Analysis) 1Economic 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. N onquantified benefits due to etiological agents, disease endpoints and exposure scenarios not considered in th e main analysis are discussed in the nonquantified benefits section (Section 5.4).

The monetized benefits from avoided acute illness due to many viral pathoge ns 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 quantif ied. As discussed in section 5.4.2, the benefit of avoiding these chronic cases may be significant, as affect ed 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, e ither 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 analys is. Additionally, the nonqua ntified benefits section (5.4) and Appendix E address this issue in a qua litative discussion supported by simulations of the infectious disease process in large, susceptible (capable of being infected) populations.

In addition to the health-based benefits identif ied above, there are a number of nonhealth benefits that also arise from promulgation of the rule. Ot her nonquantified benefits may result from overall system improvements (e.g., upgrades to distribution systems, increased water treatment plant operational efficiency and reliability, increased frequency/intens ity 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 th e GWR. Quantified health benefits for a subset of reduced pathogen exposure from the final GWR are de rived from the risk assessment estimates of the preand post-GWR annual endemic acute illnesses and d eaths 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, tho se 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 suita ble 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 Methodology 1

Risk assessment is an analytical tool that can be used to characterize th e 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 fra mework that is organized in accordance with EPA Policy for Risk Characterization (USEPA 1995a), EPA’s Guidance fo r 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 scien tific 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 assessmen t used in the GWR incorporates information on variability and uncertainty associated with the data that characterize bot h 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 heteroge nicity across people, places and time, and uncertainty represents the lack of knowledge of the true va lue 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 th e 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 le vels of exposure within that population.
• Dose Response Assessment addresses information concerning the relationships, quantitatively where possible, between the magn itude of exposure to the contaminant and the extent and severity of the adve rse health effects that may occur.

• Risk Characterization combines the hazard id entification, 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 vi ral 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 in cidence (baseline) of acute and chronic illness caused by a wide variety of viral and bacterial pa thogens associated with fecal contamination of ground water. Although the quantified benefits risk assessm ent accounts for only some viral pathogens and only some acute illnesses and deaths associated with th ese viral pathogens, different pathogens can cause different types of illnesses, and pathogens differ in th eir virulence, the degree or ability to cause illness or death. Medical research has not isolated all wate rborne pathogens, nor has it thoroughly characterized the virulence of all of the waterborne pa thogens that have been identified. As detailed in Chapter 4, there are two types of viruses found in water with data j udged to be adequate for a risk assessment: Type A (rotavirus) and Type B (enteroviruses). EPA has cho sen 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 expos ure to two representative virus types (Type A represented by data on rotavirus and Type B repr esented 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 efficien t 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 rotavi rus and hepatitis A virus are substantially lessEconomic Analysis for the 5-7 October 2006 Final Ground Water Rule efficiently recovered. Thus, the viral occurrence da ta used in the risk assessment are based primarily on enterovirus recovery. Based on EPA’s analyses of the occurrence data, enteri c 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 equa l 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 (Typ e A viruses) and enteroviruses (Type B viruses). An analysis is then conducted for conditions refl ecting 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. Th e 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 a dverse 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 bacteria l 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 literatu re 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 vi ral 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 vi ruses that cause acute gastroenteritis, resulting in symptoms that include watery diarrhea, fever, a bdominal pain, and vomiting. Although they are highly infectious, Type A viruses generally lead to m ild, 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 adu lts 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 child ren. Due to data limitations, this EA only addresses the disease burden related to a few strains of rota virus, which rarely causes illness with debilitating symptoms in adults and is not often accompanied by vom iting in either adults or children. Therefore, the EA quantifies only one part of the total Type A virus risk.Economic Analysis for the 5-8 October 2006 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 encepha litis, 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 dilate d cardiomyopathy more likely result from Type B infection as compared with Type A (chronic illnesses ar e 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 incl ude 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.Economic Analysis for the 5-9 October 2006 Final Ground Water Rule Sensitive Population Individuals % of US population 1 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 Populat ions 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 vira l and bacterial infections than the general population. Most vertical transmissi on between mother and infant occurs during and after childbirth. Viral gastroenteritis, caused mainly by Ty pe 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 imp lications for children (USEPA, 2000g). Primary food or waterborne exposure followed by secondary transmissi on via the fecal-oral route contributes to high rates of illness in group settings where care is provided for ch ildren that wear diapers such as day-care centers. The Centers for Disease Control and Prevention (CDC) h as determined that the incidence of rotavirus diarrhea can reach 0.30 episodes/child/year by age tw o, with a cumulative incidence approaching 0.80 episodes/child by age five (Glass et al., 1996). Hosp italizations 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 b ecause 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 cox sackie 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 inf ected 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 diarrh ea, hepatitis, and other vira l infections. Sensitivity among individuals in this age group is due to declini ng 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 im balance, 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 el derly 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 a nd 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 pers ons comprise a population subgroup who are more susceptible to viral and bacterial infections a nd are more sensitive to serious health effects from them. More specifically, Acquired Immunodeficien cy Syndrome (AIDS) patients (e.g. Morpeth and Thielman, 2006), organ transplant patients, and persons undergoing bone marrow transplantation are considered sensitive to viruses b ased 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 infec tions were reported as the cause of death among bonemarrow transplant patients (Yolken et al., 1982).
In this EA, the morbidity and mortality fact ors assigned to immunocompromised subgroups for Type A and B virus infections are the same as tho se used for the general population. These factors underestimate risks for these subgroups, but the EPA belie ves that there are insufficient data available to assign higher morbidity or mortality rates from waterbor ne 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 charact erizing 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-contamin ated drinking water is delivered to consumers in public GWSs.

1) Source water contaminati on 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 gr ound 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 distributi on system deficiencies in ground water public water systems (PWSs) to directly model these events. Ho wever, 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 popul ations (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 exposur e 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 st udies 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 clos ely-related Type B enteroviruses (including echovirus) are also likely to be recovered. Rotaviruses are also likely to be present because they ar e 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 T ype 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 assessmen t 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 concentr ation data (Lieberman et al, 2002; Abbaszadegan et al, 2003; Lindsey et al., 2003). EPA’s risk model a pplies a randomly chosen concentration from the data in these three studies. However, concentration data fro m 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 equa l 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 concentrati on 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 we lls 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 th e number wells that are assumed to exhibit Type A virus concentrations. However, these assumptions w ould 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 assu med that the pathogen concentration in tap water from GWSs that serve untreated ground water is the same as the pathogen concentration in sourceEconomic 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 pat hogens depending on the disinfection practices employed. Therefore, the concentration of pathogens in ta p water from properly operating disinfecting (4-log inactivation) systems is assumed to be 0.01 percent of the concentrati on in source water. For 2-log inactivation, the concentration is assumed to be 1.0 percent of the con centration in source water. These finished water viral concentration estimates do not take into account the e ffects 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 Exhib it 4.4, ground water CWSs serve over 100 million people, while ground water NCWSs serve about 14 milli on 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 highe r 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 Individua ls (CSFII). Data derived from this survey are presented in the report, “Estimated Per Capita Wate r Ingestion in the United States” (USEPA 2000c). For noncommunity water systems, which represent a signifi cant 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 popula tion: all respondents (which is used in this exposure assessment) and the subset who report consuming water directly (“c onsumers”). 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 th ree day diary period of the CSFII survey. This is because even people who report no di rect 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 Distributi on of Individual Daily Drinking Water Consumption by 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 wa ter. 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 repor ted no source or “other sources” as their main source of drinking water are included in the national averag e, because subtracting these categories would lead to an underestimate of average consumption levels. Th eir consumption patterns are assumed to be similar to those served only by community systems (or at least, cannot be adjusted using the available data).Economic Analysis for the 5-15 October 2006 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 t hought 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 percen t 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 wate r 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 fro m each source, the approach used in the exposure assessment (i.e., applying the 13.4 percent reduction to a ll mean values) may understate or overstate actual consumption from public water systems, depending on th e 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 sim ilar estimates and reduces modeling complexity.
To better estimate the daily drinking water c onsumption 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 consump tion. 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 sp end 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 da ily consumption for the 25 types of transient noncommunity GWSs, that serve the largest transien t populations. EPA used Best Professional Judgement to estimate daily consumption in each of these 25 syst em types and weighted these consumption levels by the populations served by these systems. This we ighting 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 wei ghted daily consumption estimates. As with the NTNCWS adjustment described above, the average TNCW S consumption factor of 0.4 is applied to the mean daily consumption levels (first reduced by 13.4 pe rcent) 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 N oncommunity Water System Consumption Factor

Sources: [A] Geometries and Characteristi cs of Public Water Systems (USEPA, 2000a). [B] EPA Estimate.
In addition to daily consumption, EPA estimat ed 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 th e 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 p eak month of operation. Assuming 30 days in the peak month, and an average of 10 days of exposur e 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 cohor ts 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 in cluded 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 timesEconomic Analysis for the 5-17 October 2006 Final Ground Water Rule the peak month population served reported in SDWIS (i.e ., 3 cohorts / month * 3 m onths (=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 he re 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 relati onship 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 additiona l 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 Mo deling of Human Challenge Study Data
All of the elements listed above depend on hi gh quality infectivity data and an appropriate dose-response model. Two key publications report hi gh 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 da ta 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 th e 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 studiesEconomic 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 pat hogens (not necessarily representative of the virulence encountered in nature) and studying only healthy popul ations (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 st rain 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 availa ble 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 ente rovirus 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, exhi bit lifetime immunity after infection. Even among identical strains, there are potential virulence di fferences 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 en teroviral infections, illnesses and deaths if other enterovirus human challenge st udy 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 st udy 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 th e 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 Wa rd 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 norovi rus, are not necessarily represented by the rotavirus human challenge study data. Funded under an EPA c ooperative agreement, Moe et al. (2001) reported on human challenge studies using Norwalk virus (now know n as norovirus). They conclude that norovirus “is one of the most infectious agents that has ever b een 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 ra ther 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 ro taviruses. Thus, EPA believes that the rotavirus human challenge study data, while representative of the rota viruses, may underestimate the infectivity of the Type A viruses. If so, then the GWR EA under-pre dicts 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 Exhib it 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 infecti ous units, which is considerably smaller than the smallest dose used in the human feeding study. Pred icting 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 am ong 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 2Economic Analysis for the 5-20 October 2006 Final Ground Water Rule Ward, et al. used data collected at the dose ra nge 0.009 to 90,000 ffu to estimate parameters of a probit model. Other authors, notably Teunis and Ha velaar, use these same data, but with a beta-Poisson model (Teunis et al. 1996). These two models (pr obit 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 show n 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. Gi ven 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 contamin ated ground water occur near one viral infectious unit, there is a question as to the usefulness of othe r 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 subject s was infected at dose 0.9. This alternative or sensitivity analysis is described in Appendix F.
EPA recognizes that there is significant uncer tainty associated with measuring viruses in environmental samples and has summarized that uncer tainty in Chapter 4, Section 4.3.2. Virus aggregation in routine environmental exposure is especi ally 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 concentra tion 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 concentra tion in any ground water sample (Exhibit 4.28) is 2.12 PFU (or MPN) per liter. Clusters may exist in r outine ground water exposure (in aquifers where ionic strength is relatively stable) and ground water cons umers 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 pr edict 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 le vel 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 th e 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 echovi rus 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 Havel aar utilized all of the echovirus dose-response data (including 33,000 and 330,000) and f it 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 inf ection, 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 discove red it behaves implausibly when extrapolating to estimate the risk of environmental exposures. Theo retically, risk at low doses should be approximately proportional to probability of ingesting an infectious un it, but in this application, the probit model predicts extreme sublinear behavior. In contrast, the simp le exponential and beta-Poi sson models (which is a derivation of the simple exponential) both feature a pproximate low dose linearity. When applied to the data below dose 33,000, the exponential model fits ve ry 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 diffe rent predictions of low-dose risk for echovirus. Taken together, the results demonstr ate 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, foodbor ne 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 e xposure 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 re trospective studies (only those who got ill are likely to have a reason to report their exposure and th e 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 we re 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, theEconomic Analysis for the 5-22 October 2006 Final Ground Water Rule population cohort studied and the assumptions and limitati ons associated with epidemiological data that, at times, were not optimal.
Morbidity rates are based, to the extent possi ble, on prospective epidemiological studies of endemic illness in the general population. Morbidity da ta were specifically excluded if they were based on; 1) retrospective outbreak studies, 2) retrosp ective or prospective sensitive sub-population studies (limited prospective age related sub-population studi es 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 a ddresses 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 hea lth 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 retr ospective 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 contem poraneous 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 th ey are highly infectious, continually circulating within the human population, cause only mild illness a nd may be counted as either endemic or epidemic disease, depending on the definitions used in the compilation.
EPA excluded sub-population morbidity data (w ith the exception of some age related data discussed later) because of a concern that it may not re flect endemic illness in the general U.S. population. Studies of sub-populations in the U.S. report diffe ring 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 mo rtality 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 rec ognized in the main analysis. In addition, some sensitive sub-populations have greater morbidity rat es than the general population. Because the EA doesEconomic Analysis for the 5-23 October 2006 Final Ground Water Rule not consider data on a large portion of the population th at generally is more highly affected by rotavirus and enterovirus, it underestimates the morbidity a nd 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 beco me ill from rotavirus is due to several possibilites. Ramig lists three reasons that apply to children in th e 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 en zymes 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 re lated 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 repor ted to CDC for three reasons. First, the data are not current because passive enteroviral etiol ogy 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 enter oviral illnesses do not result in symptoms sufficiently grave so as to require a physician’s care, the passi vely 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 identif ies primary illnesses as those that are acquired by consuming rotavirus and enterovirus from a contam inated 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 indi viduals 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 h as estimated illness severity. Severity is important because monetization of the rotavirus and enterovi rus disease burden bestows greater benefits (avoided costs), such as hospitalization costs and physicians’s offi ce 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 sever e outcome as any illness resulting in hospitalization.4 Enteroviral type 71 disease was particularly vi rulent 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 encephalomy elitis and cardiopulmonary collapse. The widespread transmission is enhanced by the long period of viral she dding (as much as 5 weeks) in infected individuals. Infection rates for parents (41%) were higher than other a dults (26%). These data suggest that enterovirus 71 is efficiently transmitted by asymptomatic or mildly symptoma tic 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 pathwa y 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 infecti ous 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 th e 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 water borne 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 consid eration 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 al so 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 difficu lt 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. Mo rtality 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 outco me 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 bene fits of a rotavirus vaccine (subsequently removedEconomic Analysis for the 5-25 October 2006 Final Ground Water Rule from the market due to unintended intestinal obstructi on effects). Thus, the available mortality data are limited to data from children. No U.S. endemic mort ality data are available for fatal outcomes in the sensitive subpopulations, such as the elderly, a populati on also greatly susceptible to dehydration-related mortality due to gastroenteritis.
As discussed in Section 5.2.4.3, only rotavirus mort ality rates in children are applied to the entire population. The neonate mortality rate for enteroviru s is restricted to neonates and not used to inform mortality rates for other population sub-groups. EPA be lieves 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 mo rtality 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 rotavi rus mortality to all age groups, recognizing that this is a source of uncertainty (it could be an over or unde restimate). 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 num ber of fatal outcomes in severe cases. This mortality rate is sensitive to the proportion of severe cases as di scussed 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 ra tes 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 agai nst 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 th e 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 rotavi rus cases occurred in the U.S. for the other serotypes during the study, Vesikari et al (2006) report protection efficiency w ith 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 serot ype, 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 rotavi rus vaccine has the potentia l 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 incu rring illness from rotavirus. Similarly, rotavirus secondary spread, which in this EA is assume to orig inate 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 rotavi rus 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 to tal 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 fo r rotavirus and enterovirus using dose response models fitted to human challenge study data, mo rbidity, 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 Infectivity 1 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 P Daily ) 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 Infectivity 1 Morbidity Mortality (M m ) M p M s 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:

P Daily 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 yrs 2a = 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:

P Daily 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 infe ctivity dose response functions.
2 Based on Rodriguez et al. (1987) for the upper range va lue 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 child ren 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), Mod lin (1986) and Kaplan and Klein (1983)
8 Based on data from Melnick (1996), Mod lin (1995) and Bennet et al. (1987). Notes: Mortality rates are ra tes 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). Th e 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 a bout 6 months in age. Older children can report a wide range of clinical symptoms (e.g. pharyngitis a nd otitis media) in contrast to newborns who cannot report symptoms. Thus Rodriquez used multiple di sease endpoints while Perez-Schael was able to use only diarrhea as a clinical symptom of disease. The R odrizquez study was conducted in a private pediatric medical practice in Virginia USA while the Perez-Sch ael 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 uncertain ty 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 gast roenteritis) 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 e xhibited differing disease endpoints) morbidity rate in adults challenged with a rotavirus dose under experime ntal conditions. Wenman et al. (1979) reported that 17 parents became ill of 43 parents infected by rota virus (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 life time immunity characteristic of poliovirus and hepatitis A virus) and multiple infections are possible (A nderson and Weber, 2004; K oopman 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 cau sing 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 estimat e 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 e ndpoints 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 epidemiol ogical investigations undertaken in a general population cohort. As such, they are high quality (a nd costly) data.and represent the best prospective enterovirus morbidity data available for the general population. To the extent that current molecularEconomic 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 fro m 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 echovi rus (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 ra te 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 lowe r bound comes from the Seattle study and the upper bound comes from the New York study. For children be tween 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 wa tch data reported data onl y for individuals under and over four years in age. Because the New York viru s 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 individua ls were infected by echovirus and 20 people became ill. For the New York virus watch study, 53 individua ls were infected by echovirus and 24 people became ill. Thus, despite the high quality of the data, the to tal number of people used to determine morbidity is small.
There is large uncertainty associated with the Ty pe B morbidity values currently used in the EA because they are based only on echovirus data. Fo r 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 cau se illness than echovirus, upon infection. Kogon et al (1969) report 10 illnesses resulting from 15 infections. T hus, the moribidity range for the 5-19 year olds would change from 0.12 - 0.57 to 0.12 - 0.67 and the mo rbidity 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 de termine 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 representa tive 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 predic ted 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 observe d 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 sec tion 5.4 of this chapter. In particular, section 5.4 identifies norovirus as a common waterborne etiologic agent that, unlike rotavi rus, 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 child ren) could increase, as compared with rotavirus that causes illness primarily in children.
Secondary Spread
Secondary spread can occur from contact with an in fected or ill individual. It is likely that most secondary spread occurs from contact with asympto matic 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 w ith 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 num ber 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 r espiratory or direct contact (fecal-oral) pathways. Aerosols containing fecal-oral viruses can be transmitte d 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 a nd 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 infecti on 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 a nd 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 vi rus 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 inf ectious disease simulations are specifically excluded from consideration in the GWR EA.
For rotavirus (Type A), the secondary spread fact or 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 mo st individuals to multiple strains of rotavirus early in life. As a result, it is assumed that most i ndividuals have acquired some temporary immunity to rotavirus by age 3 and so, while there is a likeli hood 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 Wa rd et al. (1986) and secondary morbidity data from Wenman et al. (1979) (assuming adults are secondar ily exposed in Wenman) show that the higher rotavirus morbidity rates comes from primary exposur e while the lower (but not zero) rates come from exposures that might be secondary. The EA underes timates 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 pediatri c 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 identif y 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. Fo rtunately, 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 re ference 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 echoviru s 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 fo r the other enteroviruses. It is likely that, if other enteroviruses, such as coxsackieviru s, were considered, the secondary transmission values could differ. For example, most enterovirus 70 or 71 is acqui red 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 th e 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 diffe rence 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 th e length of acquired immunity, if appropriate, for the agent.
Appendix E presents a different modeling a pproach 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 seconda ry 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 th e 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) symp tomatic 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 Appe ndix E, suggest that population dynamics could substantially impact the potential benefits calculate d 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 protec tive immunity, and person-to-person transmission characteristics of the infectious agent.
The population dynamic simulation results illustra te 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, us ing 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 al so showed that the number of secondary illnesses due to asymptomatic carriers is roughly equal to the num ber of secondary illnesses due to contact with ill individuals. However, simulations us ing different model parameters (sen sitivity 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 redu ced 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 fo r 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 (Tucke r 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 ro tavirus 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 in fants 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-p roven 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 Klei n (1983) reported that 6 of 77 patients younger than three months of age hospitalized with cultures positiv e for Coxsackievirus died (7.8%). The mean from these studies is 4.9%. Since this is a hospital case fa tality rate, it is necessary to multiply by the proportion of infants hospitalized to arrive at the mortality ra te. Jenista (1984) reported the percent of enteroviralinfected infants (re-)admitted to the hospital with susp ected 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 EAEconomic Analysis for the 5-34 October 2006 Final Ground Water Rule mortality rate is based on hospitalization data fro m 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 fo r persons of all ages (other than neonates) is 0.02%. It is assumed that 1% of cases are severe e nough to require hospitalization. Modlin (1995) finds that 0-4% (mode of 2%) of cases that require hospitali zation result in death. Currently a general mortality value of 0.001% for cases that do not require hospitaliza tion is used when specific rates are not available (Bennet et al., 1987). Therefore, the calculated mort ality 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 me ningioencephalitis (34,000 cases; Khetsuriani et al, 2003), it is estimated th at 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 milli on) 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 water borne enterovirus were considered.

5.2.5 Risk Characterization

Risk characterization combines the hazard iden tification, exposure assessment, and dose-response information to describe the overall risk to the expo sed population. The following sections will describe the risk assessment methodology for the baseline risk calculati ons, provide results of the risk calculations, and describe the methods used in estimating the re duction 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 modeli ng 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 assessmen t 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 popula tion 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 resulti ng illnesses and deaths in both the pre-GWR baseline and following implementation of the final GWR (or the ot her 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 variousEconomic 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. Th e risk assessment model has three major parts that are summarized below.
The first major part of the risk model genera tes 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, wh ich 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 i ndividual infectivity risk curves for the baseline and post-regulatory conditions.
One of the key factors considered in construc ting 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 popula tion groups served by GWSs involves inputs that reflect both variability and uncertainty. However, the co mputation 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 uncer tainty 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 infec tion 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 di stribution 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 dimens ional Monte Carlo simulation model that uses the first output of part one of the model, which is an un certainty distribution, along with other inputs that are either constants or are distributions reflecting uncer tainty. 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 indi vidual risk variability in proportion to the population that they each represent to construct overall risk dist ribution 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 Calc ulation Factors, Di stribution 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 (P well ) 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 (P sample ) 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 estimateRisk 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 modelRisk 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 P Daily 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 P sample distribution. The P sample 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, th ere were different, though related, forms of the dose-response model for determining the average daily ri sk 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 tho se 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 probab ility 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 categor ies within these 2,376 groups to apply the morbidity and secondary spread factors to reflect the specific age ra nges 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 i S i P i Annual i 

# M M P Pop



# ( ) ∑

= 

# × + × × × 792

1 ) ( ) ( ) ( ) ( 

# 1

i i M i S i P i Annual i 

# M M M P Pop More details on the characterization of uncertainty in the hit rates and of variability in virus concentration for the various well types is presen ted in Chapter 4. More information on water consumption variability distributions is presented in sec tion 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 co mpute 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 Carl o simulation using 1,000 iterations. In addition to the uncertainty distributions for individual risk of infection that are used as inputs (P Annual(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 es timate of the annual cases and the 5 th and 95 th percentile values are used as the lower and upper 90% confidence bounds.
The basic algorithm for the calculation of annual e ndemic 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 not ed above. Similarly, the output for this step is an uncertainty distribution of estimated annual endemi c deaths for each virus type from which the mean isEconomic Analysis for the 5-42 October 2006 Final Ground Water Rule used as the best estimate of the annual cases and the 5 th and 95 th 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 bu ilt 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 notewor thy 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 in fection 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 w ithin 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 fracti on 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 b aseline 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 5 th and 95 th 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 5 th and 95 th 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 T yp e Illnesses per Year Deaths per Year 

### Exhibit 5.13 Estimates of Annual Baseline Viral Illness and Death 1

1 Illnesses are rounded to nearest whole number and deat hs 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 vi ruses 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 mo rtality 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 pro cedure 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 5 th percentile and 95 th percentile values obtained from those iterations (90 percent confidence bounds). Th ese 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 5 th percentile value, and a 5 percent chance that it falls above the 95 th percentile value, and therefore a 90 percent chance of falling within the specified bounds.
Summing the estimates of illness for both types of vi ruses gives a combined estimate of more than 180,000 illnesses each year, the majority of which are attri butable to the highly infective, but less lethal, Type A viruses. The estimated combined number of deat hs 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 unde r 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 oldEconomic Analysis for the 5-44 October 2006 Final Ground Water Rule Virus Type Health Effect Immunocompromised 1 (all ages) Infants and Young Children <5 years old 2 Elderly Adults >65 years old 2 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 es timated 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 e xposed = 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 sen sitive 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 mort ality 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 sev ere 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. Th e source water from such a system is assumed to be contaminated with viral pathogens at a concentr ation of 40 viruses/100 L, which approximates the mean value (41.5) of the 7 virus concentration values fro m the Lieberman data used for the More Vulnerable wells. Because the source water is not disinfected, th ere is no inactivation of viral pathogens in the system. This person would be a member of the age cat egory with the highest water ingestion rate at the 75 th percentile, which is 55-64 years. The 75 th percentile of daily intake of drinking water for this age group is 1.925 L/day. Annual exposure under th is scenario is 49 days, based on 350 days/year consumption from a CWS and a P sample value of 0.14, which is the 75 th percentile of the expected values from the P sample 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 inf ectivity 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 ar e selected from a specific distribution describing the range and probability of particular values. In othe r 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 re lated 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 i nputs fall into two general categories: occurrence inputs and dose-response morbidity inputs.
Uncertainty in Occurrence Inputs
The key occurrence inputs to the are: P well , P sample distribution parameters, and Percent More Vulnerable Wells.

The P well , and P sample 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 P well , and P sample are selected from the dataset for i nput to the model as paired values. As described previously, there is an inverse relationship between P well , and the expected value of the P sample distribution. As P well , increases, the expected value for P sample decreases and vice versa. Therefore, it is necessary to select an appropriately paired set of P well , and P sample 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 a nd non-acute MCL violation data (see Section 4.3.4.2 in Chapter 4). In the risk model, the More Vulner able 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 un certainty 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 Ty pe 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 factor s 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 eval uate the relative influence of the selected uncertain inputs on the range of estimates of baselin e 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 itera tions. The output captured the number of cases of illness estimated for each virus for each of the 100 l oops, as well as the 100 specific values selected for the uncertain inputs in each iteration.

For the uncertain P well and P sample occurrence inputs, a metric was u sed 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 P well and the expected value of the P sample distribution for that iteration, referred to here as P w *P s . 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 P w *P s 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 combin ed effect of the alpha and beta pa rameters. For the selected parameters in a given iteration, the probability of infection fro m an exact dose of one viral infectious unit was computed.
For the other uncertain inputs, the actual valu es 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. Pos itive values indicate that increases in the uncertain input values lead to increases in the estimates of cases; nega tive values imply that increases in the input values lead to decreases in the estimates of cases. The larger the absolute va lue of the coefficient, the more pronounced is its influence on the results.

The results obtained are summarized below and show n graphically in Exhibits 5.15a and 5.15b for Type A and Type B viruses, respectively.
Virus Type A:

P w *P s : 0.323 Percent More Vulnerable Wells: 0.114 Infectivity Dose-Response Parameters: 0.531 Primary Morbidity Factor: 0.384Economic 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:

P w *P s : 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, th e uncertainty in the dose-response parameters is the main factor affecting the number of illnesses, wh ile for Type B viruses it is the Primary Morbidity Factor. It should be pointed out, however, that b ecause the values of all of these correlation coefficients are relatively low, none would be considered strong dr ivers 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 Correlati on Coefficients for Uncertain Inputs, Virus Type AEconomic 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 Correla tion 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 describ ed in the preceding section. The primary difference between the modeling for estima ting the baseline risk model and the modeling for estimating the risk reduction from a given regulatory alte rnative is that the latter incorporates a change in the concentration of viral pathogens reaching the fi nished drinking water of the exposed population. These changes reflect either a reduction in pathoge n concentration between source water and finished water due to disinfection or the complete eliminati on of the pathogen in the finished water from other non-treatment corrective actions addressing the source wa ter contamination. In addition to accounting for the magnitude of pathogen exposure reduction, an im portant 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 S ection 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 P well probability. Also, for those wells having some viral occurrence, values are assigned for P sample and for the virus concentration. The ri sk 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 implementi ng the simulation modeling process, those wells designated as never having a virus present are recogni zed 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, th e 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 implemen tation is the corrective action performed?
The risk reduction model then processes the re duced 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 out puts 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 concen trations 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 afte r 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 baselin e 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 C ases, Cases Remaining, and Cases Avoided at the Well Level

Estimates of cases avoided calculated for all of the i ndividual wells are then aggregated to arrive at the total national estimates of risk reduction. In add ition, some of the assumptions and data used in the risk reduction model are uncertain and are therefore i nput as uncertainty distributions. As a result of the uncertainty reflected in those inputs, together with th e uncertainty reflected in other inputs to the baseline risk model that are also carried into the risk reducti on 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 deta il the specific assumptions and inputs–including considerations of uncertainty–that are used to mode l risk reduction for the sanitary survey and triggered monitoring components of the GWR.Economic Analysis for the 5-51 October 2006 Final Ground Water Rule Sanitary Surveys
The Sanitary Survey component of the rule a pplies to all ground water wells, including those wells that are currently disinfecting and meeting 4-log reduc tions. 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 charact eristics 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 frac tion 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 fu rther 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 indi cative of wells that fall into the More Vulnerable classification within the benefits model. The percen tages of properly and imprope rly 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 system s had wells that were constructed according to State standards. Thus, 16.4 percent of systems had wells id entified 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 we lls 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 c onstruction estimates described above can be used to approximate the percent of all wells having virus pr esent that are expected to be identified and corrected by sanitary surveys. To arrive at this estimate, th e percent of all wells that are improperly constructed is first calculated as the weighted average fo r 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%), Imprope rly 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 constr ucted. It is assumed that corrective actions will be performed on those improperly constructed wells. Speci fically, EPA has estimated that for those wells that are improperly constructed and also have a virus pr esent, 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 distributi on of 40% to 60% (mean = 50%). Therefore, as a central value, it is expected that the sanitary survey and corrective acti on alternative of the rule will result in corrective actions being performed and contaminati on eliminated at approximately half of the 16.6% of all wells that are improperly construc ted, 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 sour ce water that are caught by a sanitary survey, the corrective action is assumed to eliminate the virus comple tely. 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 ri sk reduction (i.e., cases avoided) from sanitary surveys will be from the nondisinfecting wells. This is b ecause 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 s ource 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 th e 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 su rveys will occur across the entire 25 year analysis period. It is assumed that no corrective actions will o ccur 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 correc tive 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 ach ieving 4-log removal of viruses. For the wells that are currently achieving 4-log removal, the sanita ry survey requirements still apply and the output developed in that part of the model as descr ibed 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 num ber 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 TCEconomic Analysis for the 5-53 October 2006 Final Ground Water Rule positives per year; over 22 years, then, it is expect ed 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 positiv e 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 th e first indicator positive will occur on or before the 49th assay. The data for each uncertainty set provid es 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 u sed 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 capture d (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 assu mes 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 cau se 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 ra te 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 cont ributes 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-third7 The effect of taking five repeat samples for any positiv e 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 eff ect of this omission is a slight overestimate of benefits, however, the number of systems with five negativ e 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 s hould 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 th e one occurring earliest is selected for corrective action), the total wells ultimately caught by both compone nts of this rule alternative will be less than the sum of the two individual components (i.e., ~8.3% fo r 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 th eir source water. Because most of the baseline risk is found in nondisinfecting wells, it is also, therefore, e xpected 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 pe rformed as a result of sanitary surveys or triggered monitoring.
Exhibit 5.19 provides a summary of the estimated cases avoided per year in the 25 th year following rule implementation. This summary provides an indi cation 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 b aseline cases of 185,186 shown in Exhibit 5.13. A detailed breakdown of illnesses and deaths avoide d 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 TypeEconomic Analysis for the 5-56 October 2006 Final Ground Water Rule Mean 5th Percentil e 95th Percentile Mean 5th Percentile 95th Percentil e T

y

pe A 39,442 10,093 79,925 0.3 0.1 0.5 T

y

pe B 2,426 181 8,114 0.5 0.0 1.6 Total 41,868 10,274 88,039 0.7 0.1 2.1 Illnesses per Year Deaths per Year Virus type

Mea n 5th Percentil e 95th Percentile Mean 5th Percentil e 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 25 th 

### 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 vi ruses, 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 y ears) 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 re duction in individual risk from the Sanitary Survey and Corrective Action alternative, somewhat larger ri sk reductions for the Risk Targeted and Multi-Barrier alternatives, and substantially great er 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 annua l 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 th ere 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 areEconomic 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 th e 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 th e 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 InfectionPercent 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 InfectionPercent 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 InfectionPercent of Population Below Indicated Risk

Baseline SS SSTM SSRM 4-log 

### Exhibit 5.20a Comparison of Averag e Annual Individual Infectivity Risk Distributions for Baseline and Rule Alternatives for Type A VirusesEconomic 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 InfectionPercent 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 InfectionPercent 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 InfectionPercent of Population Below Indicated Risk

Baseline SS SSTM SSRM 4-log 

### Exhibit 5.20b Comparison of Averag e Annual Individual Infectivity Risk Distributions for Baseline and Rule Alternatives for Type B VirusesEconomic 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 si gnificant 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 previous ly undisinfected system, the disinfectant can react with pipe scale causing increased risk from some contaminan ts 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 consider ation 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 wa ter 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 prev ious sections, monetary unit values can be applied to these estimates to establish the monetary benefits attr ibutable to the rule. As discussed earlier, only a portion of the illnesses and deaths avoided are quantifie d. 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 illn esses 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 comple te 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 reduc tions in the risk of Type A and Type B virus morbidity is to rely on estimates of willingness to pa y (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, th is 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 co sts 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 mi nimum 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) a ddress 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 i ndividuals to their original health state (i.e., is equivalent to avoiding the illness entirely).
A number of researchers have explored the rela tionship 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 nonmarke t work time (e.g., child care or housekeeping). Typically, these costs are estimated using the hum an 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 Enhan ced. Both approaches include direct medical costs and the value of lost work time, but differ in th e assessment of value of lost work time. They both consider the impact of time losses on foregone mark et production, which affects the individual worker (e.g., in terms of lost income) as well as other memb ers 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 a nd 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 va lues 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 lo st leisure time and lost productivity—the reduced utility (or sense of well-being) associated with decr eased enjoyment of time spent in both market and nonmarket activities. The Enhanced COI is an attemp t 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 tim e in a well state compared to time in an ill state. This analysis relies instead on wage and compensa tion data to estimate the opportunity costs of time usage. This approach recognizes that, because res ources 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 b ased 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 th e median gross (pre--tax) wage rate plus benefits, also referred to as total compensation or employer’s co sts. This approach is most representative of the full social impact of lost work because it incorpor ates both the loss to the individual in terms of lost income and the loss to society in terms of redu ced tax revenue or decreased production of goods and services. Lost nonmarket work and leisure time is valu ed 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 individual10 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 for ce participants, the use of av erage 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 morb idity 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, conservativel y 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 th e individual does not completely lose the productivity or utility associated with the activity. These values ar e applied to such time losses incurred by the ill individual.
The use of medical costs and the opportunity co st 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 ri sk aversion. In addition, the use of wage and compensation data to value lost time ma y understate the utility of time spent in its preferred use. The use of wage rates may understate the tota l utility associated with an activity even in the case of paid work, because individuals may derive intrin sic pleasure from the activity above and beyond the income they receive. For nonmarket work and leisur e, 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 ar e 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, su ch 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 indi rect 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 add itional 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 aEconomic 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 ser vices. 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 subsec tions 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 a nd inpatient care. Outpatient care consists of an initial physician visit ($114.55) and product of the co st of each follow-up visit ($66.18) and the number of follow-up visits. Multiplying this sum by the pe rcentage 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 fo llow-up visits ($52.25), and the hospital charges (calculated on a per day basis, with costs rangi ng 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 obtai ned in 2000 dollars and upda ted 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 V alue of lost patient day [D] Lost patient days (No Medical Care/Outpatient) [A] Lost patient days (Inpatient) [A] V alue of caregiver day [D] Caregiver days (No Medical Care/Outpatient) [A] Caregiver days (Inpatient) [A] V alue 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

> 16 years <2 years 2 to 4 years 5 to 15 years

Wei g hted Unit Cost $21 $148

$21 14% [C]

[ C ] 14% Total Unit Cost

$152.87

Total Cost of Illness $5,036 $4,029

$61

Total Wei g hted 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 severi ty of symptom manifestation is dependent on the rotavirus strain and can be divided into two groups. The G2 & G9 stra ins represent 15.3% of illnesse s, 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 dat a presented in the table. [D] Appendix A, Exhibit A.7 [E] Weighted average per day value of time ($227.79) mu ltiplied 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 dat a presented in the table. [D] Appendix A, Exhibit A.7 [E] Weighted average per day value of time ($227.79) mu ltiplied 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

- $ 7 10 $11 5 - $ 7 10 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
, 4 5 3

- $ 5, 049 $4
, 4 5 3 - $ 5, 049 Indirect Costs V alue of lost patient day [D] Lost patient days [A] V alue of caregiver day [D] Caregiver days [A] V alue of lost productivity day [E] Lost productivity days [A]

Total Indirect Costs [C]

$6,589

- $ 7, 184 $ 5,7 34 - $6
, 330 Total Cost of Illness $6,622 $5,767 [C] $227.79 0 $68.34 0 $569 $2,136 $1,281 $1,281 $4,338

Total Wei g hted 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 Wei g hted 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 $59.81Economic 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] N A N A 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 V alue of lost patient day [D] $199.36 $227.79 Lost patient days [A] 1.5 1.15 V alue of caregiver day [D] $227.79 $227.79 Caregiver days [A] 1.5 0 V alue 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 Costs 1 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 det ermined from best available data. Sources: [A] Appendix A, Exhibit A.3 [B] Appendix A, Exhibit A.4 [C] Calculations based on dat a presented in the table [D] Appendix A, Exhibit A.7,E] Wei ghted 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 dat a presented in the table. [D] Appendix A, Exhibit A.7 [E] Weighted average per day value of time ($227.79) mu ltiplied by percent loss productivity (30 percent, rounded from Harrington et al. 1991) * No data available S ymp t om d ura ti on-- 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 V alue of lost patient day [D] Lost patient days [A] V alue of caregiver day [D] Caregiver days [A]

Value of lost productivity day [E] Lost productivity days [A]

$ 8 5 4 - $ 5, 126 $ 8 5 4 - $ 4
, 2 7 2 $ 8 5 4 - $ 2
, 990 $4 5 6 - $2
, 0 5 0

$ 1
, 03 5 - $ 5, 30 7 $ 1
, 03 5 - $ 4
, 4 5 2 $ 1
, 03 5 - $ 3
, 1 7 1 $ 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 $181 100.0% 100% 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 ]

[ C ] Total Cost of Illness $2,316 $2,316 $181Economic 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 dat a presented in the table. [D] Appendix A, Exhibit A.7 [E] Weighted average per day value of time ($227.79) mu ltiplied by percent loss productivity (30 percent, rounded from Harrington et al. 1991) * No data available S ymp t om d ura ti on-- 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 V alue of lost patient day [D] Lost patient days [A] V alue 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
, 28 5 - $ 29
, 411 $ 10
, 041 - $ 1 5, 16 7 $ 5, 890 - $ 11
, 016 $ 5, 492 - $ 8
, 22 5 $8,026 $6,631 Cost Category

[C]

[ C ] Total Cost of Illness $26,421 $12,177 $5,036 $9,187

$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 $181 100.0% 100% 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 yearsEconomic 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 V alue of lost patient day [D] Lost patient days (No Medical Care/Outpatient) [A] Lost patient days (Inpatient) [A] V alue of caregiver day [D] Caregiver days (No Medical Care/Outpatient) [A] Caregiver days (Inpatient) [A] V alue 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

> 16 years <2 years 2 to 4 years 5 to 15 years

Wei g hted Unit Cost $21 $148

$21 14% [C]

[ C ] 14% Total Unit Cost

$152.87

Total Cost of Illness $5,036 $4,029

$61

Total Wei g hted 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 severi ty of symptom manifestation is dependent on the rotavirus strain and can be divided into two groups. The G2 & G9 stra ins represent 15.3% of illnesse s, 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 dat a presented in the table. [D] Appendix A, Exhibit A.7 [E] Weighted average per day value of time ($85.12) mult iplied 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 dat a presented in the table. [D] Appendix A, Exhibit A.7 [E] Weighted average per day value of time ($85.12) mult iplied 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
, 4 5 3

- $ 5, 049 $4
, 4 5 3 - $ 5, 049 Indirect Costs V alue of lost patient day [D] Lost patient days [A] V alue of caregiver day [D] Caregiver days [A] V alue 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 Wei g hted Unit Cost $148 $148

$4,338

Total Wei g hted Direct Costs $4,486 $4,486 [C] $4,338 $4,338 $4,338 100%

$213 $426 $255 $255 $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] N A N A 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 V alue of lost patient day [D] $0.00 $85.12 Lost patient days [A] 1.5 1.15 V alue of caregiver day [D] $85.12 $85.12 Caregiver days [A] 1.5 0 V alue 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 dat a presented in the table. [D] Appendix A, Exhibit A.7 [E] Weighted average per day value of time ($85.12) mult iplied 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 S ymptom 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 sta y [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 V alue of lost patient day [D] Lost patient days [A] V alue 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 ]

[ C ] Total Cost of Illness $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 $181 100.0% 100% 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) multip lied 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 S ymptom d urat i on-- 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 V alue of lost patient day [D] Lost patient days [A] V alue 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 $181 100.0% 100% 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% $9,006 $23,250 $4,855
$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 ]

[ C ] Total Cost of Illness $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) multip lied 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 year s 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 years11 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 (fo r 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 in cludes 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) wa ge 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 wa ge ($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 medi cal 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 a nd caregivers is set at $85.12. As shown in Appendix A, this figure is calculated by summing the product of hour s 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, pr ove 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 ch ildren.” 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 illn ess 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 y ears of age. Both the Traditional and Enhanced COI approaches assume that a caretaker stays hom e 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 va luation 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 percent 11 (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 avoidi ng 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 reduci ng 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 indi vidual 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, th e 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 u se in benefits analyses in EPA’s Guidelines for Preparing Economic Analyses (USEPA 2000e) and endorsed by the Scien ce Advisory Board (SAB) Arsenic review panel (USEPA 2001b). For purposes of the GWR benef its 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 mode l 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 impl ementation 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 consta nt 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 in come elasticity. This section describes how these adjustments are carried out. Benefits derived from medi cal 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. Th ese 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 elas ticity adjustments are applied to values in future years. In general, income elasticity represents chang es 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 fra me for analysis. To accomplish this, population and real gross domestic product (GDP) projections are co mbined to calculated per capita real GDP values 12 (see Appendix B, Exhibit B.5–income elasticity calcula tions). 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 I 1 - E I 2 - I 2 - I 1 ) / (E I 2 -E I 1 - I 2 - I 1 ) where:
E = income elasticity I 1 = real income (per capita GDP) in the base year I 2 = 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 (I 1 = 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 publishe d 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-Carl o 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 ar e computed and applied to avoided-death benefits in future years. At the average income elasticity va lue (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 Appe ndix 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 disc ount rate. This process takes into account the time preference that society places on expenditures and bene fits 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 = V t /(1 + R)t
where: t = the number of years from the reference period (year 0 of the benefits stream) R = social discount rate V t = 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 ar e 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 ri sk-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 “b efore-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 th is 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 benef its estimated for the GWR for all system sizes and categories (CWSs, NTNCWSs, and TNCWSs). Nonquan tified 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)

0.2 $ 0.1 $ 0.5 $ 0.2 $ 0.0 $ 0.3 $ 0.4 $ 0.2 $ 1.0 $ 0.4 $ 0.1 $ 0.8 $ 0.4 $ 0.1 $ 1.0 $ 0.3 $ 0.1 $ 0.8 $ 1.0 $ 0.3 $ 2.4 $ 0.8 $ 0.3 $ 2.0 $ 2.5 $ 0.9 $ 5.7 $ 2.1 $ 0.7 $ 4.8 $ 2.4 $ 0.8 $ 5.3 $ 2.1 $ 0.7 $ 4.6 $ 4.7 $ 1.5 $ 11.0 $ 4.1 $ 1.3 $ 9.6 $ 4.3 $ 1.5 $ 10.1 $ 3.8 $ 1.3 $ 8.8 $ 0.0 $ 0.0 $ 0.0 $ 0.0 $ 0.0 $ 0.0 $ 16.0 $ 5.4 $ 37.0 $ 13.7 $ 4.6 $ 31.6 $

0.1 $ 0.0 $ 0.1 $ 0.1 $ 0.0 $ 0.1 $ 0.2 $ 0.1 $ 0.4 $ 0.2 $ 0.1 $ 0.4 $ 0.2 $ 0.1 $ 0.5 $ 0.2 $ 0.0 $ 0.4 $ 0.2 $ 0.1 $ 0.6 $ 0.2 $ 0.1 $ 0.5 $ 0.1 $ 0.0 $ 0.3 $ 0.1 $ 0.0 $ 0.2 $ 0.1 $ 0.0 $ 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 $

- $ - $ - $ - $ - $ - $ 0.9 $ 0.3 $ 2.2 $ 0.8 $ 0.2 $ 1.8 $

0.6 $ 0.2 $ 1.4 $ 0.5 $ 0.1 $ 1.1 $ 0.9 $ 0.3 $ 2.2 $ 0.8 $ 0.2 $ 1.8 $ 0.4 $ 0.1 $ 1.0 $ 0.3 $ 0.1 $ 0.8 $ 0.3 $ 0.1 $ 0.8 $ 0.3 $ 0.1 $ 0.6 $ 0.2 $ 0.1 $ 0.4 $ 0.1 $ 0.0 $ 0.3 $ 0.2 $ 0.0 $ 0.4 $ 0.1 $ 0.0 $ 0.3 $ 0.0 $ 0.0 $ 0.1 $ 0.0 $ 0.0 $ 0.0 $ 0.1 $ 0.0 $ 0.1 $ 0.0 $ 0.0 $ 0.1 $

- $ - $ - $ - $ - $ - $ 2.7 $ 0.8 $ 6.2 $ 2.3 $ 0.7 $ 5.1 $ 19.7 $ 6.5 $ 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 Be nefits 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)

0.1 $ 0.0 $ 0.3 $ 0.1 $ 0.0 $ 0.2 $ 0.2 $ 0.1 $ 0.6 $ 0.2 $ 0.0 $ 0.5 $ 0.2 $ 0.0 $ 0.6 $ 0.2 $ 0.0 $ 0.5 $ 0.5 $ 0.1 $ 1.4 $ 0.4 $ 0.1 $ 1.2 $ 1.3 $ 0.3 $ 3.4 $ 1.1 $ 0.3 $ 2.8 $ 1.2 $ 0.3 $ 3.2 $ 1.1 $ 0.3 $ 2.8 $ 2.4 $ 0.5 $ 6.7 $ 2.1 $ 0.4 $ 5.9 $ 2.2 $ 0.5 $ 6.0 $ 1.9 $ 0.5 $ 5.3 $ 0.0 $ 0.0 $ 0.0 $ 0.0 $ 0.0 $ 0.0 $ 8.2 $ 1.9 $ 22.3 $ 7.1 $ 1.6 $ 19.1 $

0.0 $ 0.0 $ 0.1 $ 0.0 $ 0.0 $ 0.1 $ 0.1 $ 0.0 $ 0.3 $ 0.1 $ 0.0 $ 0.2 $ 0.1 $ 0.0 $ 0.3 $ 0.1 $ 0.0 $ 0.2 $ 0.1 $ 0.0 $ 0.3 $ 0.1 $ 0.0 $ 0.3 $ 0.1 $ 0.0 $ 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 $

- $ - $ - $ - $ - $ - $ 0.5 $ 0.1 $ 1.3 $ 0.4 $ 0.1 $ 1.0 $

0.3 $ 0.1 $ 0.7 $ 0.3 $ 0.1 $ 0.6 $ 0.4 $ 0.1 $ 1.2 $ 0.4 $ 0.1 $ 1.0 $ 0.2 $ 0.0 $ 0.6 $ 0.2 $ 0.0 $ 0.5 $ 0.2 $ 0.0 $ 0.4 $ 0.1 $ 0.0 $ 0.4 $ 0.1 $ 0.0 $ 0.2 $ 0.1 $ 0.0 $ 0.2 $ 0.1 $ 0.0 $ 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 $

- $ - $ - $ - $ - $ - $ 1.3 $ 0.3 $ 3.4 $ 1.1 $ 0.2 $ 2.8 $ 10.0 $ 2.2 $ 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 portio n 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 Census 1 Population Potentially

Affected (served by GW systems) No. of Illnesses Avoided No. of Deaths Avoided Annual Benefits Using 3 % Discount Rate and Enhanced COI 2 ($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 benef its will be realized by sensitive subpopulations. As described previously in section 5.2.2.2, EPA is c onsidering 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 statistica l analyses and rounding. The figures presented in this exhibit represent only the quantifiable benefits of the GW R. The nonquantified benefits ar e expected to comprise a significant portion of the overall benef its of the Rule and are presented in Section 5.4. T he Immunocompromised population includes bone marrow transplant recipients, AIDS patients, and or gan 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 i mmunocompromised (99.7% of t he population). Therefore, the U.S. Census population estimates shown above for the Elderly and Children categorie s 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 fr om 2000 Census data (U.S. Bureau of t he Census, 2000); Population Potentially Affected derived from SDWIS (USEPA 2003a); Number of I llnesses Avoided, Deaths Avoided, and Annual Benefits from GWR Model Output.Economic Analysis for the October 2006 Final Ground Water Rule 5-82 

### 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 GW R. 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 discu ssed in this section. As discussed in Section 5.2 and 5.3, even in the case where benefits are quantified, da ta 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 ad enovirus, 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, dila ted cardiomyopathy, hypertension and reduced kidney function), 4) decreased incidence of illness and deat h 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 we lls, 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 benef its, both health and non-health, are likely to substantially exceed those which EPA was able to qua ntify, and are the primary basis for supporting the preferred regulatory alternative. Each of these majo r 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) Ho wever, no cell culture method exists to recover noroviruses in stool or environmental samples, theref ore published human infectivity data for norovirus were not available to use in the EA. This detec tion method deficiency and resulting lack of published infectivity data prevented quantification of moneti zed 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.16 Common source outbreaks arise primarily from food or wa ter (ice is considered to be water by EPA but is commonly treated as food in outbreak compilations). Pr opagation by secondary (person-to-person) transmission may also occur but is not the immediate cause of the outbreak. Outbreaks that ar e not common source arise and propagate only by person-to-person transmission.

Economic Analysis for the October 2006 Final Ground Water Rule 5-83 Norovirus Disease in the United States
In recent years, numerous common source outbreaks 16 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 gastroen teritis 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: th e 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 bact erial agents, no routine, commercially available test for identifying norovirus exists and therefore ill pers ons who submit a stool specimen are not routinely tested for norovirus (Blanton et al., 2006).
Norovirus has a low infectious dose, prolonge d 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 w ith norovirus. Norovirus does not provide lasting immunity upon infection partly because there are many different serotypes (Carter, 2005). The substantial strain diversity may prevent individua ls 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 a nother host (Schwab and Bae, 2005). Thus, noroviruscontaminated ground water or a norovirus-contaminat ed surface will continue to maintain infectious norovirus. Individuals can acquire primary norovi rus infection by drinking that ground water or can acquire secondary infectious norovirus by cont act with a contaminated surface or persons.
Although a small percentage (about 20%) of indivi duals 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 highl y infectious (Moe et al., 2001), individuals may easily acquire infection. Once infected, norovirus is easily transmitted to others. Individuals can easilyEconomic Analysis for the October 2006 Final Ground Water Rule 5-84 spread infection and illness to family members a nd others (both children and adults) outside the household by casual contact with asymptomatic carriers who shed for long periods.
Using molecular epidemiology tools, diver se 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 whic h 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 agen t 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) a quifer. 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 (Anders on 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 Y ukon, 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 Dakot a (CDC, 1988) and elsewhere. Among outbreaks that have been specifically attributed to norovirus expos ure 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 pers ons (e.g., older persons with debilitating healthEconomic Analysis for the October 2006 Final Ground Water Rule 5-85 conditions). No long-term sequelae of norovirus in fection have been reporte d (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 agen ts 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. Vom iting 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 significan t 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 benef it 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 norovi rus 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 mo re 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 rota virus 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 w ith rotavirus experience gastroenteritis only, EPA assumes that each adult ill with rotavirus has one da y 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 likel y 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 outbr eak 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 yetEconomic Analysis for the October 2006 Final Ground Water Rule 5-86 published (Moe, 2001). For this reason alone, rotaviru s 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 a nd 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 a dults who experience those person-days of illness and this severity provides additional benefits when mone tized. EPA believes that consideration of the more severe clinical symptoms associated with noroviru s 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 noroviru s illness in adults is significant. While EPA has data on the proportion of cases with vomiting and on th e 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 (a nd infectious to others) that most people cannot (or should not) work. The EA currently assumes a wei ghted mean value of 0.16 lost patient days and one day of lost productivity for adults when ill from rotavi rus. 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, ro tavirus and the caliciviruses are also transmitted by the fecal-oral pathway and thus are potential e tiologic 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 e xpected to decline with time because children are currently vaccinated for HAV in high risk st ates and newer recommendations are for increased vaccination coverage. More ge nerally, 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 path ways. Hepatitis has a long incubation period and the virus remains viable in the environment and esp ecially ground water for months. Thus, the infection source is often obscure. Ground water HAV outbreaks ha ve been identified (Georgetown, TX (Hejkal et al, 1982), Racine, MO (Missouri Department of H ealth, 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 wh ere 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. BecauseEconomic Analysis for the October 2006 Final Ground Water Rule 5-87 of this and the fact that HAV cannot be routinely id entified 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 vi rus that is potential transmitted via ground water. Using serology and case histories of individual patient s, 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 outbreak s 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 availa ble. The disease is severe (up to 20% mortality among pregnant women in developi ng 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 character istic illness, are shed copiously through the gut and are thus fecal\oral viruses (Carter, 2005). Adenoviru ses are not efficiently recovered using commonly available cell lines and methods and no human dose res ponse 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 th e South Bass Island, OH outbreak (CDC, 2005). The GWR does not quantify the benefits from avoided adenovirus illness.

Astrovirus
Astrovirus, like rotavirus, is commonly acqui red in child care settings, causes mild disease in children and most children are exposed at an early ag e. 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). Astroviru ses are not favored for recovery in environmental samples using common cell lines and no human dose-r esponse 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 sampl es 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 re production was so highly favored. Reovirus is more closely related to rotavirus and thus has some sim ilar characteristics. Unlike rotavirus, reovirus rarely17 The presence of reovirus in environmental sample s complicates the recovery, or detection and quantification, of enteroviruses. Additionally, reovirus ra rely results in illness. Therefore, reovirus occurrence can cause underestimates of enteroviral occurrence, and can el evate viral concentrations without adding to the disease burden associated with a contaminated water source. He nce, it can result in an underestimate of the quantified benefits that accrue from the GWR



### . Economic Analysis for the October 2006 Final Ground Water Rule 5-88 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 efficiency 17 , 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 Oth er 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 qua ntify 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, ther e 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 cost s of a single case of diabetes or heart disease are significant. Cost estimates for a case of diabetes a nd 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 cardi omyopathy 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 str ong correlation between diabetes and enterovirus infection. Individual case studies have reported di abetes development after enterovirus infection (Roivainen, 1998). A mechanism for producing disease suggests that entervirus infection triggers autoimmunity response. While these data are suggestiv e, they are not definitive. Recently, Maria et al (2005) reported simultaneous (on the same day) diab etes onset in mother and son coincident with enteroviral infection. With these data, it is now cl ear 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 benef its (illnesses avoided), but only considers qualitatively18 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 (a nnual) 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).

Economic Analysis for the October 2006 Final Ground Water Rule 5-89 the diabetes cases avoided as a result of corrective acti ons performed due to enterovirus contamination of PWS wells.
The most comprehensive work regarding the ec onomic 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 Stat es 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 pr evalence-based COI study also compares the health care expenditures of diabetics in 1997 to nondiabetics.

The authors created a holistic estimate of the hea lth 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 complicati ons and general medical conditions in people with diabetes), and 2) total medical expenditures incurre d 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 diabeti cs in 1997, divided by the 1997 diabetic population. The estimates do not, however, include pain and sufferi ng 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 th roughout 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 percen t 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 va lue for this illness, it captures the lifetime costs of diabetes in those who survive the first year through th eir 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 substan tial 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 myo carditis (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 hear t 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 be nefits as a severe illness that can be caused by echovirus and other enterovirus infection. Howeve r, 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 cardiom yopathy, 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 echovi rus 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 “av erage case of heart disease” is estimated to be $5,129 21 . 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, 9 th Revision (ICD–9) codes 391–398, 402, 404, 410–416, 420–429)(H odgson, 1984; Hodgson, 1998). Since no specific cost data were available for chronic my ocarditis, or cardiomyopath y (ICD–9 code 425), annual22 Chronic illness prevalence rates (cases per 1,000 i ndividuals) for “heart disease” were multiplied by the total U.S. population to obtain the total number of heart dis ease 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 ma y not be the same for hypertensive disease, for example.

24 Costs updated from January 1977 dollars to 2003 (annua l) dollars using the CPI-U for “all items: (= 177.1 ÷ 58.5 = 3.0).

25 Costs updated from January 1977 dollars to 2003 (annua l) dollars using the CPI-U for “all items: (= 177.1 ÷ 58.5 = 3.0).

Economic Analysis for the October 2006 Final Ground Water Rule 5-91 per capita costs for an “average case of heart di sease” were computed using data on “heart disease” in conjunction with prevalence numbers from th e 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 hos pitals, the mean age of diagnosis for cardiomyopathy was 60 (Elixhauser et al., 1993). Usi ng 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 woul d 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 consequen ce 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 th ere 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 ol d (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 neurol ogically ill from enterovirus 71 during a 1990 outbreak in Western Australia. For the period 1970-1979, CD C 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.Economic Analysis for the October 2006 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 substan tial. 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 pathwa y 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 undisinf ected 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 orig inate 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 la rger than the viruses, they are less mobile in non-sensitive aquifers and are more likely to occur in wells in sensitive a quifers 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 sympto ms associated with bact erial 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 in to two groups; the frank pathogens such as E. coli O157:H7 and the opportunistic pathogens, such as P seudomonas aeruginosa. The opportunistic bacterial pathogens found in drinking water have been we ll 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 bacteria l 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 ki dney failure, shock and death in otherwise healthy individuals, especially small children. Typically, ki dney failure occurs in 2-7% of illnesses. Death or end-stage renal disease occurs in about 12% of patient s four years after diarrhea-associated kidney failure (Garg et al, 2003). Twenty five percent of kidney fa ilure 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, On tario, 6 individuals died and 27 developed kidneyEconomic Analysis for the October 2006 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 coin cident 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 s upply 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 sensitiv e (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 ot her 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 th e 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 r esult 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 of ten 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 of ten a cause is identified, even though Shigella are difficult to cultivate. One large ground water outbreak in a sensitive aqui fer 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.Economic Analysis for the October 2006 Final Ground Water Rule 5-94 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 pa tients 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, Id aho (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 contaminati on 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 availabl e 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 (Rollin s 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 bene fits associated with avoided camplybacterosis (and arcobacterosis) and their chronic sequelae (Gu illane-Barre paralysis and reactive arthritis).

Salmonella

Salmonella causes typhoid fever, once a common and da ngerous 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 wa ter 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 from26 Because 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.

Economic Analysis for the October 2006 Final Ground Water Rule 5-95 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 conc lude that this is the “first study that has unambiguously proven that Legionella constitute a part of the microf lora of ground water not known to be under the direct influence of surface waters” (Riffa rd 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 th at 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 quantifie d benefits model only addresses avoiding viral illness in the first of these categories.
Although EPA did not formally quantify the benef its 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 quantifie d 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 viral 26 , 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).27 Bacterial illnesses are more likely to be diagnosed than viral illnesses because of their severity. However, most cases of diarrhea associated with outbreaks ar e not identified by etiology and identifying etiology is unnecessary in order to identify an outbreak.

Economic Analysis for the October 2006 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 outbreak 27 . 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) r ecognize the types and distribution of bacterial illness associated with waterborne disease, b) characterize mo rtality rates for the different types of bacterial illness identified in “a”, and c) estimate a compos ite mortality rate considering “a” and “b”.

For a), EPA used the same waterborne disease out break 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) (T able 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 es timates 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 bacteria l 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 re latively small and therefore, giving a different weight (e.g. based on additional information) to one partic ular 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.Economic Analysis for the October 2006 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 bact erial 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 we re 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 approximate ly 50% and the composite mortality rate factor, calculated in Exhibit 5.25, would have dropped by approximately 15%.
3) Estimate potential annual bacteri al 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 estim ate 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 AvoidedEconomic Analysis for the October 2006 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 poten tial hospitalizations a voided by a reduction in the incidence of bacterial illness, as it did for estimati ng potential deaths avoided. In order to estimate a hospitalization rate due to water borne bacterial illnesses, a composite hospitalization rate was developed that represents the hospitalization rate for all water borne bacterial pathogens adjusted by the frequency of their occurrence as the etiologic ag ent in WBDOs. The data presented in Mead et al. (1999) represent bacterial illnesses and hospitalizations due to all differe nt exposures, e.g. food, person to person spread, waterborne. By using information on the relativ e 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 th e 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 hospitalizati ons (column 3) from Table 3 of Mead P.S. et al, (1999). In order to develop the co mposite waterborne bacterial hospita lization 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 hospita lization rate is calculated by multiplying the etiologic fraction of WBDO cases (column 6) by the e tiologic 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 b acterial 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 pot ential hospitalizations. If the average bacterial hospitalization cost is assumed to be greater than th e 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.Economic Analysis for the October 2006 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 bacter ial 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 RatesEconomic 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 in crease by a factor of five by only accounting for additional deaths and hospitalizations caused by b acterial illness being avoided. The actual number of hospitalizations and deaths avoided c ould be higher or lower. Within the context of best available science, given all the other nonquantified bene fits 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 woul d be approximately $4.4 million (year 2003 dollars). Taken together, these additional bene fits 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, chr onic 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 larg est 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 gastroenter itis 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-lim iting bacterial gastroenteritis is likely to be followed by hypertension and reduced kidney functi on 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 in creased 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 sel f-limiting bacterial gastroenteritis. The EA also does not quantify the chronic disease sequelae such as hypertension and reduced renal function that canEconomic Analysis for the October 2006 Final Ground Water Rule 5-101 arise from acute illness. Because bacterial disease a nd 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 uncerta in. 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 reac tive 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 ge othermal 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 temper ature 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 in fluence 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. Howe ver, on several occasions, PWS wells were regulated as if they were ground water rather than as surface water until a cryptosporidiosis or Giardiasis outbreakEconomic Analysis for the October 2006 Final Ground Water Rule 5-102 was recognized. Examples of Cryptosporidiosis outbreaks associated with ground water wells (not recognized as GWUDI wells) located in sensitive a quifers 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 treat ment technique requirements and avoid potential outbreaks. Such actions would result in both in creased costs and benefits for such systems.

5.4.5 Reduction in Outbreak Risk and Response Costs
Besides reducing the endemic risk of illnesses fro m 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 estimat es 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 out breaks 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 warn ings 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 e ngineering works typically include probabilistic failure assessment to determine the likely benefits of avoi ding catastrophic effects. Such analyses are not included in the EA quantified or nonquantified be nefits 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 aver ting 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 avoi ded averting behavior is not possible given current information, but potential benefits are expected to be substantial.

Five studies were identified that used the averti ng 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 Houtve n 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 acr oss 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.Economic Analysis for the October 2006 Final Ground Water Rule 5-103 The four steps associated with a waterborne outbreak that may impose costs on society are discovery, survey and testing, reaction, and af termath (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 be gin 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 be tween $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 anal ysis conservatively estimated the economic impact excluding medically related costs to be over $43 m illion 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 additi onal 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., duri ng 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 substa ntial 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 out break-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 a ttributable to a treatment deficiency.Economic Analysis for the October 2006 Final Ground Water Rule 5-104 EPA’s baseline estimate among disinfected suppli es 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 assu mption, the baseline estimate for viral disease among disinfected supplies is about 2,500 cases, whereas the b aseline 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 additiona l 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 theref ore 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 confid ence the percent reduction in treatment failures that might result from this rule. In any case, benefits fro m 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 s ubstantial bacterial population growth can occur. Periodic biofilm sloughing can introduce these pathogens into untreated ground water. Major groups of opportunistic bacterial include Pseudomonas, Acinet obacter, 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 ot her 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 oppor tunistic 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 vi ruses, the GWR is expected to reduce exposure to other pathogens. For example, some membrane t echnologies 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 im pact of emerging pathogens is not well established.Economic Analysis for the October 2006 Final Ground Water Rule 5-105 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 pr ovide direct benefits inde pendent of risk reduction benefits. In other words, drinking water consum ers 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 willi ng 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 percei ve 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 wate r 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 invol ve 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 rela ted factor is that many households that undertake averting action for health reasons may be especia lly 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 bot h 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 tota l 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 rest rict the input parameters in the quantified benefitEconomic Analysis for the October 2006 Final Ground Water Rule 5-106 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 ente rovirus data. If coxsackievirus data were available, the mean morbidity values would be greater. Choos ing 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 discu ssed 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 gastroenter itis illness and fatal dehydration associated with that illness are monetized. Norovirus disease is not cons idered. For the enteroviruses, all acute disease endpoints are considered, but the prevalence of sever e 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, e ither for rotavirus or the enteroviruses, are chronic diseases identified or monetized in the quantitative benefits calculation.
Fourth, the quantified benefits are based explic itly on what has been directly measured in PWS wells, yet there is great difficulty in identifying a nd 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 contamin ation scenarios are thoroughly documented in the ground water contamination and outbreak scientific literatu re. However, these scenar ios, 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 ep idemic disease (outbreaks). If epidemic illnesses and the avoided non-health-related costs of ground wa terborne disease outbreaks were included, the quantified benefits would increase.
In summary, this EA quantifies a subset of the to tal health and non-health related benefits. In a sample calculation, discussed in Section 5.4.3.2, EPA es timated that the total benefits could increase by a factor of five by only accounting for additional d eaths and hospitalizations caused by bacterial illness being avoided. While EPA recognizes that this estim ate includes substantial uncertainty, given all theEconomic Analysis for the October 2006 Final Ground Water Rule 5-107 other nonquantified factors described above, EPA believ es 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 ma jor modeling assumptions would have on benefits analyses, several alternative analyses were perform ed. This section presents discussion and results for four such analyses: use of an a lternative baseline for viral concentr ation; 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 concentra tions 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 a pplied 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 a pplied differentially to the six categories (based on three system types and their status as more or l ess vulnerable): Abbaszadegan’s concentration data are applied to only less vulnerable CWSs; Lieberman’s c oncentration 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 alternativ e would increase the quantified benefits of rule implementation by a range of $1.1 million to $1.7 m illion (an increase of approximately 7 to 9 percent, using a 7 percent and 3 percent discount rate, respec tively) (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 deve loped 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 subject s exposed to 0.9 viruses were used since this dose level is most similar to doses likely to be experi enced by those consuming contaminated water. As described in detail in Appendix F.5.1, an exponentia l 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 r esults, in terms of the monetized benefits using this alternative dose response function (with all other aspect s kept the same as in the main model), are shown in Exhibit 5.27. This alternative dose response f unction would increase the annualized quantified benefits by a range of $1.7 million to $2.1 million (approximate ly 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 ar e 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 (USE PA 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 5-108 In the second alternative dose response analysis for Type A viruses, the r value was estimated without consideration of uncertainty. This alterna tive leads to a lower estimate of risk and benefits related to Type A viruses by a range of $1.7 milli on to $2.0 million (approximately 10 percent in both cases) relative to the annualized quantified benefits fo r 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 devel oped by EPA for Type B viruses using the same study data (Schiff et al., 1984) that were for the do se 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 cap ture 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 th is alternative dose response function (with all other aspects kept the same as in the main model), are show n 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 publication 28 and so consisted only of peer-review ed 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 milli on to $12.2 million (an approximately 62% increase), using 7 percent and 3 percent discount rates, respectively (Exhibit 5.27).Economic Analysis for the October 2006 Final Ground Water Rule 5-109 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 me thods used to estimate the baseline risks, in terms of illnesses and deaths, from the presence of vira l 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 infl uence 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).Economic Analysis for the October 2006 Final Ground Water Rule 5-110 

### Exhibit 5.28 Summary of Uncerta inties Affecting GWR Estimates (continued on next page)

Uncertainty Section Discussion of Uncertainty Effect on Benefits Estimate s Effect on Cost Estimates

Underestimate Overestimate Unknown Impact Underestimate Overestimate Unknown 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 forelderly 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 XUncertainty Section Discussion of Uncertainty Effect on Benefits Estimate s Effect on Cost Estimates

Underestimate Overestimate Unknown Impact Underestimate Overestimate Unknown 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 ri sk model, the same elements of variability and uncertainty that were discussed in Chapter 4 for th e viral and indicator occurrence data and modeling apply to their use here in the baseline risk and ri sk reduction modeling. Of particular note are the concerns that the limited monitoring data ava ilable 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-occurren ce 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 da ta, 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 r esponse functions were deve loped using data from the challenge studies that was considered most re presentative of likely exposures via drinking water.
Variability and uncertainty are considered in th e morbidity factors used in the risk model. Variability is accounted for by applying different f actors 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, a nd variability is included in secondary spread rate for Type A viruses as a function of age of the primar y 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 illn ess rather than with primary cases of infection.
In the risk and benefits analysis, there is r ecognition of three sensitive subgroups: young, old and immunocompromised. There are, however, only lim ited quantitative considerations of the potential increased impacts on these subgroups. There is no di fference 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 noEconomic Analysis for the October 2006 Final Ground Water Rule 5-112 consideration of increased morbidity or mortality risk for older persons or the immunocompromised subgroups. (Note that the analysis does c onsider increased severity of illness for the immunocompromised in terms of medical costs incurred.)
In the valuation of benefits analysis, a cost-of-illn ess (COI ) approach has b een used rather than a willingness-to-pay (WTP) approach due to lack of av ailable 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 occurre nce 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 si zes and types (e.g., disinfecting/nondisinfecting), and the wells are situated in shallow and deep aquife rs, 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 n ecessarily 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 we lls. 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 de gree to which the dataset may have overstated or understated our national occurrence estimates.



### 5.7 Regulatory Alternatives

In addition to model runs to calculate benef its 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 Disinfec tion (see Chapter 3 for a full description of these alternatives). The following exhibits present th e 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 valu e 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 175,168 32,652 435,381 1.2 0.2 2.9 Type B 10,018 501 40,718 2.0 0.0 8.1 Total 185,186 33,153 476,099 3.2 0.3 11.0 Type A 135,726 22,559 355,455 0.9 0.1 2.4 Type B 7,592 320 32,605 1.5 0.0 6.5 Total 143,318 22,879 388,060 2.4 0.2 8.9
Type A 168,154 31,065 420,404 1.1 0.2 2.8 Type B 9,535 470 38,688 1.9 0.0 7.8 Total 177,689 31,535 459,092 3.0 0.2 10.6
Type A 132,332 21,207 348,839 0.9 0.1 2.3 Type B 7,435 307 32,094 1.5 0.0 6.4 Total 139,768 21,514 380,933 2.4 0.2 8.7

Type A 28,295 5,248 70,474 0.2 0.0 0.5 Type B 1,609 80 6,540 0.3 0.0 1.3 Total 29,904 5,328 77,014 0.5 0.0 1.8 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 Tar g eted A pp roach 41,868 10,274 88,039 0.7 0.1 2.1 Alternative 1 Sanitary Survey and Corrective Action 7,497 1,618 17,007 0.1 0.0 0.4 Alternative 3 Multi-Barrier A pp roach 45,419 11,639 95,166 0.8 0.1 2.3 Alternative 4 Across-the-Board Disinfection 155,282 27,824 399,085 2.7 0.2 9.2 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 quant ifiable benefits of the GWR. The nonquantified benefits are expect ed 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 tim e) 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 expect ed 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 Alternatives1 The term “State” in the context of this chapter re fers 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 (i ncluding 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)). State 1 cost analyses include estimates of the labor burdens that States would face, including staff training on GWR requirements, conducting sanitary surv eys, reviewing monitoring reports, reviewing and approving corrective action plans, and recordkeep ing. 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 perfo rmed for existing drinking water rules (e.g., Arsenic Rule).
The national costs are estimated using a Monte-Ca rlo 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 co sts within each public water system (PWS) size and type category. The GWR cost model allows for vari ability 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 im pacts to PWSs and technology affordability.
The remainder of this chapter is organized as follows:

• Section 6.2 describes the general costing and co mpliance 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 baselin e 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 combina tion 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 estimat es. Derivations of these baselines for the GWR are discussed in Chapter 4. In addition to those base line 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 rat es (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 combinati on of operators (technical) and engineers (managerial), with an 80/20 ratio between t he two, respectively. Loaded rate includes a 60 percent factor to account fo r 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 per cent 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 administ rative tasks are estimated based on an average annual full time equivalent (FTE) labor cost, incl uding overhead and fringe be nefits, 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 be nefits. 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 fe wer than 10,000 people would conduct 25% of the laboratory analyses in-house and 75% would be sent to a commercial laboratory; for syst ems 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 labor atory; 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 o f 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 fo r State employee from 2001 State Drinking Water Needs Analysis ($65,255 y early 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 o ccupations). ECI for State Employee from BLS (2003) from 2001 (State and local government; Total compensation; Pr ofessional, specialty, and technical occupations). www.bls.gov.

6.2.2 Laboratory Fees
A laboratory fee, or cost per sample, is associat ed 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 alte rnative 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 laboratory 2 , 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 analys is, 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 averag e 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. A lthough 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 variet y 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 nanofiltra tion, 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 co mpliance forecast (and their associated unit costs) are based on representative use by the majority of syst ems. 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 populati on 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. Sec tions 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 syst em 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 acti ons 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 poi nts per system, population served, flow per population, labor rates, and occurrence distributions) and sever al 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 characteri ze 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 th e 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 simula tion. 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 benef its. 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. 3Economic Analysis for the October 2006 Final Ground Water Rule 6-7 There are two adjustments made to the cost estim ates 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 a nd 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 uncertain ty 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 sche dule and the present value of each cost calculated to the expected year of rule implementation for the fi nal 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 disc ount 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 subsidi es. To annualize capital costs when determining the costs to households, EPA uses different discount rat es for private and public systems of different sizes (annualized household costs are presented in Exhib it 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 depe nding on system size and ownership. These rates are shown in Exhibit 6.4.



### Exhibit 6.4 Discount Rates fo r 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 Estima tes 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 brie f 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 fro m 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 th roughout 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 r esult 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 WellsEconomic 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 ImplicationsEconomic 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 U pper B oun d (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 Meet ing 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 exhi bit 6.5a. The technical and managerial labor rates presented in section 6.2.1 are used along with estimat es of labor hours to generate implementation costsEconomic 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 syst ems 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 sanita ry surveys, and a total of 2 - 4 hours for the implementation of monitoring requirements. Th e planning and mobilization burden estimates under monitoring implementation activities include time requi red 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

21.44 $ 2 1 64.32 $ 1 2 64.32 $ 6 129 $

23.09 $ 2 1 69.27 $ 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 $

35.25 $ 2 1 105.74 $ 1 3 140.99 $ 7 247 $

21.44 $ 2 1 64.32 $ 1 1 42.88 $ 5 107 $

23.09 $ 2 1 69.27 $ 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 $

35.25 $ 2 1 105.74 $ 1 1 70.50 $ 5 176 $

21.44 $ 2 1 64.32 $ 1 1 42.88 $ 5 107 $

23.09 $ 2 1 69.27 $ 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 $

35.25 $ 2 1 105.74 $ 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 ActivitiesEconomic Analysis for the October 2006 Final Ground Water Rule 6-14 States
States will incur administrative costs while impl ementing 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 modi fying 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 th e 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 u se 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 sy stem compliance information to the Safe Drinking Water Information System (SDWIS). Exhibit 6.7b lis ts these annual activities with their respective costs and burden.
States will also be required to spend time res ponding to PWSs with fecally contaminated ground water sources or significant deficiencies. These cost s 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 da ta 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 33.60 $ 60 0.03 2,016 $ 33.60 $ 1,040 0.50 34,946 $ 33.60 $ 800 0.38 26,882 $ 33.60 $ 2,080 1.00 69,892 $ 33.60 $ 2,080 1.00 69,892 $ 33.60 $ 520 0.25 17,473 $ Per State Total 6,580 221,101 $ National Totals (57 States/Primacy Agencies) 375,060 12,602,743 $ 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 33.60 $ 1,040 0.50 34,946 $ 33.60 $ 1,040 0.50 34,946 $ 33.60 $ 1,040 0.50 34,946 $ 33.60 $ 1,040 0.50 34,946 $ 33.60 $ 880 0.42 29,570 $ 33.60 $ 104 0.05 3,495 $ Per State Total 5,144 172,848 $ National Totals (57 States/Primacy Agencies) 293,208 9,852,357 $ 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 AdministrationEconomic 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 Stat es to perform implementation activities for the preferred regulatory alternative are presented in Exhibit 6.8.



### Exhibit 6.8 PWS and State Cost Es timates 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 san itary surveys once every three and five years, respectively, to address eight specific components of a PWS. The exception to these frequencies is someCWSs. 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 th is 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 curre ntly performing surveys at the frequencies specified under the GWR will incur costs for performing additiona l 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). Incremen tal surveys may also be applicab le to some systems under the same survey frequencies. Although States or designated agen ts perform the surveys, systems will incur costs to accompany State inspectors during a review of the tr eatment plant and the distribution system, as well as to review and discuss the sanitary survey report. Th e primary increase in costs that systems will incur as a result of this rule provision is the additional numbe r of surveys undertaken during the period of analysis (i.e., full survey costs).4 No differentiation in inspection burden is made betw een 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 th e 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 25 th year). For systems on the five year schedule that have to do incremental surveys, the numbe r 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 surv ey 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 un it 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 di fference 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 perfo rming the surveys while systems are only required to provide information and assistance to support the surv eys. 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 gr ound water systems. Lower unit costs are applied to NCWSs because they are normally simpler than CWSs.
The total annualized costs estimates for both syst ems 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 SystemsEconomic 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 syste ms 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 syste ms 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 collect ed at a single location during the same sampling event, only one triggered monitoring sample is required to be ta ken 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 Estima tes for Sanitary Survey Performance ($Millions, 2003$)

6.4.3 Triggered Source Water Monitoring 

### 1

PWSs 

### 2
Systems that do not achieve 4-log treatment of viruses (using inactivation, removal, or State

### 3 approved combination of these technologies) before or at the first customer will be subject to triggered 

### 4 source water monitoring. Under this provision, systems are required to collect and analyze samples at 

### 5 the ground water source following the detection of total coliform (TC) in one or more samples collected 

### 6 for compliance with the TCR. 5 Systems are not required to conduct triggered source water monitoring if, 

### 7 according to State criteria or a State determina tion, the cause of the total coliform-positive sample 

### 8 collected under the TCR directly relates to the di stribution system. While States have the option of 

### 9 requiring the triggered monitoring samples to be t ested for the presence of a State-specified fecal 

### 10 indicator, for the purpose of this cost analysis, EPA assumed that States will select E. coli as the indicator 

### 11 for analysis. 

### 12
If a system detects the State-specified fecal indicator at its source, then the system must take five 

### 13 additional samples within 24 hours unless the State determines that corrective action must be taken 

### 14 immediately. If any of the additional samples is positiv e, the system must implement a corrective action. 

### 15 Corrective actions fall into two major categories: non-treatment and treatment (see Section 6.4.4 for 

### 16 detailed discussion). Several compliance estimates we re considered to develop estimates of the cost 

### 17 associated with triggered monitoring: the frequency w ith which systems will have to perform triggered 

### 18 monitoring; the frequency that a TC positive is deemed to be related to the distribution system; the year in 

### 19 which the triggered monitoring occurs; and the number of systems that are expected to test positive for 

### 20 the fecal indicator. These factors are discussed in gr eater detail below. Exhibit 6.14 presents a schematic 

### 21 of the triggered monitoring process as applied in the cost model. 

### 22Economic 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 

### Exhibit 6.14 Schematic of Triggered Monitoring Process 1 (Numbers based on 3,301 - 10,000 population category for CWSs) 

### 2

* Each positive sample corresponds to either one entry point predicted to have treatment corrective action or one well per entr y 

### 3 point to have a nontreatment corrective action. Systems must provide corrective actions if a source water positive sample is a lso 

### 4 followed by a positive additional source water sample. The State, at its discretion, may require corrective action based on th e 

### 5 initial positive source water sample (See s ections 6.4.3 and 6.6 for discussion). 

### 6

Frequency of Performing Triggered Monitoring : EPA estimated the number of times per year 

### 7 that a ground water system’s total coliform sampling produced a positive result, which would trigger the 

### 8 GWR source water monitoring requirements. The GWR allows States to determine which well within a 

### 9 system may be related to each TC-positive. EPA makes the simplifying assumption that monitoring at 

### 10 one EP within a system will approximate this rule provision. Due to the uncertainty in DV data, this 

### 11 assumption may over- or under-estimate the number of EPs subject to triggered monitoring (see Appendix 

### 12 I for further discussion). A summary of the methodology used to estimate the annual number of TC

### 13 positive samples per system is presented in Section 4.2. 7 and additional detail on the analysis is presented 

### 146 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 numbe r 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 in Appendix I. The results presented in that Section 4.2.7 (Exhibit 4.11) are repeated in Exhibit 6.15 

### 1 below for convenience. These estimates reflect the annual number of samples taken by systems of 

### 2 different sizes and types. Sampling costs for triggered monitoring are calculated by multiplying the 

### 3 annual number of triggered monitoring samples taken by the sampling unit costs presented previously in 

### 4 Exhibit 6.3. 

### 5 6 Exhibit 6.15 Estimated Number of Triggered Samples Per Year Per Entry Point 7

System 

### 8 Type 

### 9 System Size (Population Served)

<100 101- 500 501-1K 1,001- 3,300 3,301- 10K 10,001- 50K 50,001- 100K >100K
CWS 

### 10 0.38 0.41 0.49 0.22 0.58 2.2 6.6 10.6
NTNCWS 

### 11 0.22 0.23 0.28 0.70 1.8 7.0 20.8 33.7
TNCWS 

### 12 0.47 0.48 0.60 1.1 2.9 11.0 32.6 52.8 Source: Exhibit 4.11 

### 13

Total Coliform Positive Samples Related to the Distribution System : Systems are not required to 

### 14 conduct triggered source water monitoring if, according to State criteria or a State determination, the 

### 15 cause of the total coliform-positive sample collected unde r the TCR directly relates to the distribution 

### 16 system. Since it is difficult to predict the number of TC positives that are due to source water versus 

### 17 distribution system contamination, EPA assumes each TC positive will result in a triggered source water 

### 18 monitoring sample. The assumption likely overestimates triggered monitoring sample costs. 

### 19
The Five Additional Samples Following an Initial Indicator Positive Sample : Neither the 

### 20 schematic nor this cost analysis includes additiona l sampling (the cost model assumes that systems take 

### 21 corrective action based on the first positive indicator sam ple result). EPA expects about 3% of the initial 

### 22 triggered monitoring assays will be positive and therefor e require additional sampling. The total number 

### 23 of assays (triggered plus additional samples) would ther efore be about 15% greater than the total number 

### 24 of initial triggered monitoring samples that are included in the cost analysis. EPA believes that this factor 

### 25 (understating the cost of triggered plus additional monitoring by $200,000 pe r year) is more than offset by 

### 26 including costs for samples that are already co llected and assayed under the Total Coliform Rule 

### 27 (estimated value of more than $3 million per year). 6 The GWR allows selected samples that are collected 

### 28 under the TCR to be used in satisfying both the TCR repeat sample requirements and (per State approval) 

### 29 the initial source water fecal indicator under this GWR. The costs of these assays can therefore be 

### 30 attributed to the TCR rather than the GWR. By attri buting all of these costs to the GWR, this analysis has 

### 31Economic Analysis for the October 2006 Final Ground Water Rule 6-28 probably overestimated the triggered monitoring cost s by more than $3 million. In addition, although 

### 1 additional sampling will add to the total cost of m onitoring, it will cause a decrease in the cost estimate 

### 2 for providing corrective actions (i.e., some systems with an initial positive sample will not have any 

### 3 positive additional samples). Since the costs of correc tive actions are higher than the costs of additional 

### 4 sampling, the net cost may be an overestimate. This overestimation coupled with the TCR-related 

### 5 overestimation more than offsets the underes timation due to not including additional samples 

### 6 (approximately $200,000) and the net eff ect is an overestimation of costs. 

### 7
Percent of EPs Testing Positive : The triggered monitoring component of the model applies only 

### 8 to the nondisinfecting subset of EPs (and any EPs th at are applying disinfectant but not achieving 4-log 

### 9 treatment of viruses using inactivation, removal, or State-approved combination of these technologies, 

### 10 before or at the first customer). It is assumed that no triggered monitoring samples are taken during the 

### 11 first three years following rule promulgations, but may be taken during any of the 22 years from year 4 

### 12 through year 25. 

### 13
For the triggered monitoring component of the cost analysis, each EP not achieving 4-log 

### 14 treatment of viruses using inactivation, removal, or State-approved combination of these technologies, 

### 15 before or at the first customer, goes through a 2-step process similar to that descr ibed in Chapter 5 for the 

### 16 risk reduction model. In the first step of the process, estimates are made of the number of TC positives - 

### 17 and therefore the number of source water indicator samples - that occur during the 22 years of the 

### 18 compliance period between year 4 and year 25. The number of TC positives expected per year for each 

### 19 EP of a given type and size are obtained from the DV data as described in chapter 4. The number of TC 

### 20 positives per year, and therefore the expected number of triggered indicator samples taken per year, are 

### 21 summarized in Exhibit 6.15. The total number of TC positives expected through year 25 is then 

### 22 calculated as the number of TC positives per year times 22. If, for example, an EP is in the CWS size 

### 23 10,000-50,000 category, the DV data indicate that these EPs average 2.21 TC positives per year; over 22 

### 24 years, then, it is expected that each EP in this system size category will have 48.6 TC positives and 

### 25 therefore take up to 49 source water indicator samples between years 4 and 25. 

### 26
In the second step of the process, a simulation is performed to determine which, if any, of the 

### 27 indicator samples taken through year 25 is the first fecal positive indicator result. In each uncertainty 

### 28 loop of the cost model a set of values is selected reflecting the probability that the first positive of an 

### 29 indicator will occur on a given assay number. Exhibit 4.21 showed the probability of the first fecal 

### 30 indicator positive occurring on a given assay for the median and the 5 th and 95 th percentiles of a sample of 

### 31 1,000 of these uncertainty sets of occurrence values. 

### 32
The data for each uncertainty set provide the cumulative probabilities of observing the first fecal 

### 33 positive on or before each specific assay number. In the cost model, a random value between 0 and 1 is 

### 34 generated for each EP. That value is used as a look-up value to determine what assay number would 

### 35 produce the first fecal positive. 

### 36 37 For example, if the curve shown as the median da ta set in Exhibit 4.26 were the set of values 

### 38 being used for a particular uncertainty loop, and the random number between 0 and 1 generated for an EP 

### 39 in the CWS size 10,000-50,000 category were 0.095, the look-up function would indicate that the first 

### 40 fecal indicator positive would occur on assay number 8. Since these EPs are expected to take 48.6 fecal 

### 41 indicator assays over the 22 year period, the 8 th assay would occur in the 4 th year [(22 years/48.6 

### 42 assays)*8 assays ~ 3.6]. Since there are no triggered monitoring samples taken in years 1 through 3 

### 43Economic Analysis for the October 2006 Final Ground Water Rule 6-29 following promulgation, the 4 th year of sampling corresponds to year 7 of the 25 year modeling period. 

### 1 Therefore, this well would be "caught" by triggered monitoring in year 7. 

### 2
EPs that test positive (both with initial and additional samples) for an indicator of fecal 

### 3 contamination must perform corrective action. Co sts for performing corrective actions are discussed in 

### 4 Section 6.4.4. In addition, a report must be submitted to the State notifying them of the problem. EPA 

### 5 estimates that this report will require, on average, 2. 5 hours to complete and submit. EPA has developed 

### 6 and systems will have access to automated forms that will minimize the burden to systems in complying 

### 7 with this reporting requirement. Exhibit 6.16 below presents system unit costs for triggered monitoring 

### 8 reporting requirements. 

### 9 10 Based on the number of TC positives expected per EP across all EP types and sizes, together with 

### 11 the expected values of fecal indicator positives as a function of assay number across all of the uncertainty 

### 12 sets available to draw from for the simulation model, it can be estimated that approximately 10.2% (90% 

### 13 confidence bounds of 7.4% - 13.4%) of all nondisinfec ting EPs will have a fecal indicator positive from 

### 14 the triggered monitoring provision of the rule by the 25 th year of the modeling timeframe. The 10.2% of 

### 15 all nondisinfecting EPs that are identified over the 25- year timeframe as having fecal indicator occurrence 

### 16 comprise nearly 40% of the subset of those EPs that are expected to have fecal contamination at some 

### 17 time. This is because the occurrence analysis show s that about 26.2% of all EPs are believed to have 

### 18 some fecal contaminant occurrence. The estimate of 26.2% of EPs having some fecal contaminant 

### 19 occurrence is based on the mean values of P2 and P3 from a sample of 10,000 estimates, where P2 

### 20 (~16.5%) is the fraction of EPs ha ving both viral and fecal indicator occurrence and P3 (~9.7%) is the 

### 21 fraction having fecal indicator, but no viral occurrence. Therefore the fraction of all fecally contaminated 

### 22 wells that are identified over the 25-year period can be estimated as 10.2% / 26.2% = 38.9% = ~40%. See 

### 23 Chapter 4, Section 4.3.4.1 for the derivation of P2 , P3, and other viral and fecal indicator hit rate 

### 24 parameters. 

### 25
Invalidation of Samples : The GWR allows a State to invalidate a positive source water sample if 

### 26 it believes that the positive is due to improper analys is. States may also invalidate positive source water 

### 27 samples that are due to circumstances not reflecting source water quality. Systems must resample after a 

### 28 sample is invalidated. For costing purposes, EPA, based on best professional judgement, estimates that 

### 29 States will invalidate a minimal number of samples resulting in a negligible cost and burden. 

### 30Economic 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 

### Exhibit 6.16 PWS Unit Cost s for Triggered Monitoring 1Economic 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 States 

### 1
State costs for triggered monitoring are assumed to be solely administrative. States incur costs to 

### 2 review several paperwork requirements: reports of positive samples (including the results of additional 

### 3 samples) and sample invalidation documentation. Each of these reports and associated costs is explained 

### 4 below. 

### 5
Review Reports of Source Water Positives : The GWR requires systems that find a source water 

### 6 sample positive for fecal contamination to report this to the State. Based on its experience with similar 

### 7 reporting requirements, EPA estimates that States will require 3.5 hours to review the report. Using a 

### 8 labor cost of $33.60 per hour, EPA estimates a unit cost of $117.61 to review the report. This estimate is 

### 9 greater than the burden estimated for systems to prepare and submit the report because it is anticipated 

### 10 that the State will have less familiarity with any particular system and will be required to look up 

### 11 additional historical information to make an y assessments/determinations regarding the report. 

### 12
Invalidation of Samples : As noted above, the GWR allows a State to invalidate a fecal positive 

### 13 source water sample result that is due to improper analysis. States may also invalidate a fecal positive 

### 14 source water sample results that are due to circumst ances not reflecting source water quality. For costing 

### 15 purposes, EPA estimates that States will invalidate a minimal number of samples, resulting in a negligible 

### 16 cost and burden

. 

### 17

Annualized cost estimates for systems and States to perform triggered monitoring are presented in 

### 18 Exhibit 6.17. 

### 19

Exhibit 6.17 PWS and State Cost Estima tes for Performing Triggered Monitoring 20 ($Millions, 2003$) 21

22

23Economic 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. Na tional 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 correc tive actions under the GWR. This section includes discussions of the compliance forecast used to dete rmine the corrective actions undertaken by PWSs, estimation of the burden and costs of corrective acti on 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 identif ied 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 benef its 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 ma y be taken by systems. In general, EPA believes the costs for these significant deficien cies represent the range of costs syst ems would be expected to incur for providing correction of significant deficiencies. Ma ny other specific corrective actions may be taken to adequately address significant deficiencies identifie d 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. Ot her well repairs that could correct source contaminationEconomic 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 th e 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 correctiv e 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 variab le, 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 th e 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 St ate Drinking Water Administrators (ASDWA) (1997). Based on responses to the ASDWA survey, it was determ ined 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 assignm ent of significant deficiencies is applied equally in years 4 - 25 of the analysis, resulting in approximate ly 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 ch ange is applied based on system size. The costs for correction of significant defici encies 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 deficienciesEconomic 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 correctiv e 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 ac tions due to source water contamination, discussed below. It is assumed that large systems will have mo re 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 M illion 74 35.25 $ 2,608.35 $ 37 37.34 $ 1,381.65 $ 74 35.25 $ 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 M illion 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 M illion 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 reflec t 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 Esti mates 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 sam ples 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 assu mes 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 believ es 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, sy stems 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 S ection 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 scenar io. 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 di sinfection for the systems projected to install permanent disinfection as their corrective actions ar e 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 correctiv e 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 oxidants 7 (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 di ffer from these if the State specifies an alternative treatment technology (e.g., ultraviolet light). Each st ep 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 correc tive 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 b ased 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 re presentatives, 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 remaini ng 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 pr ojecting the number of entry points that would employ each nontreatment corrective action, EPA assigns equa l proportions of the nontreatment corrective actions into the high- and low-cost scen arios for significant deficiencies.
Step 3—Distribution of Nontreatment Corrective Actions : Each non-disinfecting entry point that is predicted to require a nontreatment corrective acti on (from step two), having been assigned to either the high- or the low-cost scenario, is then assigne d 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 tr eatment 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 storag e 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 Wa ter 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 percentag es 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 disinfectio n 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 choos e treatment in proportion to current treatment practices. Estimates for hypochlorinat ion 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. Un it costs for installing and operating each of the six treatment scenarios (and variations) in the complian ce forecast are presented in Exhibit 6.22b. For each corrective action, costs generally increase correspondi ng 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 yea r 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 ContaminationEconomic 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 6,192 $ 6,227 $ 6,307 $ 6,456 $ 6,857 $ 16,951 $ 18,197 $ 21,854 $ 61,772 $ Chlorine gas feed & storage capital cost 31,216 $ 33,354 $ 37,960 $ 46,039 $ 66,058 $ 152,883 $ 266,275 $ 541,906 $ 2,192,279 $ Chlorine gas feed & storage annual O&M cost 6,192 $ 6,227 $ 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 1,585 $ 2,076 $ 4,180 $ 6,582 $ 7,326 $ 7,558 $ 7,909 $ 19,177 $ 135,513 $ Hypochlorite feed & storage capital cost 10,318 $ 12,456 $ 23,164 $ 40,573 $ 60,593 $ 166,733 $ 280,927 $ 541,128 $ 2,042,213 $ Hypochlorite & storage annual O&M cost 1,585 $ 2,076 $ 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 47,219 $ 65,151 $ 87,450 $ 110,256 $ 151,129 $ 255,055 $ 354,880 $ 745,098 $ 2,188,039 $ Anodic Oxidant annual O&M cost 2,911 $ 5,471 $ 7,480 $ 9,791 $ 12,855 $ 17,479 $ 22,181 $ 38,439 $ 179,932 $ Anodic Oxidant & storage capital cost 48,568 $ 68,637 $ 95,543 $ 126,427 $ 187,320 $ 349,157 $ 556,149 $ 1,190,046 $ 4,042,807 $ Anodic Oxidant & storage annual O&M cost 2,911 $ 5,471 $ 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 62,691 $ 104,856 $ 182,768 $ 304,122 $ 573,460 $ 1,086,398 $ 1,872,457 $ 5,140,179 $ 29,028,479 $ Nanofiltration annual O&M cost 7,520 $ 10,253 $ 20,140 $ 37,037 $ 63,670 $ 133,397 $ 194,361 $ 541,543 $ 3,873,384 $

Add storage capital cost 1,349 $ 3,486 $ 8,093 $ 16,171 $ 36,191 $ 94,102 $ 201,269 $ 444,947 $ 1,854,768 $ Increase dose - hypochlorination annual O&M cost 72 $ 179 $ 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 ContaminationEconomic 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 Estima tes for Triggered Monitoring Corrective Action Activities ($Millions, 2003$)

6.4.5 Compliance Monitoring
PWSs that provide 4-log treatment of viruses (u sing 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 treat ment. This section presents the assumptions used to estimate the burden and costs attributable to comp liance 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 comp liance with the GWR, or prior to the Rule’s promulgation, would already have the monitoring pr ogram 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. Therefor e, 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 mainta in 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 disinf ection at a specified frequency, such as daily or continuously. This type of language suggests monitori ng 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 mon itoring 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 presen ts 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 Monitoring8 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 inst all monitoring equipment to perform compliance monitoring. The unit capital and O&M costs 8 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 hour s labor burden per day. Because nanofiltration technologies have monitoring capability incorporated in to their core processes, systems that adopt these treatment techniques are assumed to incur no cap ital 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 Co mpliance Monitoring for Initial State Notification and Disinfection Failure ReportsEconomic 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 A nnual 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 op erator 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 Moni toring Unit Costs for Systems Serving 3,300 or Fewer PeopleEconomic 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 PeopleEconomic 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 notifica tion from systems that achieve 4-log treatment of viruses (using inactivation, removal, or State-appr oved 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 bur den 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 informa tion 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 Estima tes 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

Lowe r (5th %ile) Upper (95th %ile) Lower (5th %ile) Uppe r (95th %ile) Lowe r (5th %ile) Upper (95th %ile)

79 $ 29 $ 158 $ 62 $ 24 $ 117 $ 141 $ 53 $ 275 $
31 $ 12 $ 60 $ 0 $ 0 $ 1 $ 31 $ 12 $ 61 $
173 $ 64 $ 339 $ 1 $ 0 $ 2 $ 174 $ 64 $ 341 $
283 $ 105 $ 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 p oint 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 cost s of the GWR. Note, the bulk of capital costsare 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 co sts due to site-specific factors. Inputs to unit costs such as water quality conditions, labor rates, a nd land costs can be highly variable and increase the system-to-system variability in unit costs. In deve loping the unit cost estimates, there is insufficient information to fully characterize what the distributi on 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 aver age 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 fo r 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 cond itions. In this EA, uncertainty in these national9 Studies omitted from the alternative occurrence model ar e 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 (U SEPA 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 followi ng 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 tr eatment 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 secti on 6.4.6 and later in this chapter.

6.4.8 Alternative Cost Analysis
The Agency performed an alterna tive 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 publication 9 and so consisted only of peer-reviewed data . This cost model run parallels th e alternative benefits model run described in section 5.5.4. Compared to the primary an alysis, 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 incorpor ate the costs of rule implementation, sanitary surveys, triggered monitoring, corrective actions, and compliance mon itoring. 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 wa ter contamination. Exhibit 6.31 also presents the same information for CWSs that must take correctiv e action. Household costs tend to decrease as system size increases, due mainly to the economi es 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 s ubject to each rule requirement is divided by 2.59 people per household (U.S. Bureau of the Ce nsus, 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 priv ate and public systems and for systems of different sizes. The rate differences between systems re present the different borrowing sources each type of system has available to it, differences in risk, and e xpectations 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 correc tive actions range from $0.45 to $52.38, depending on system size. EPA estimates that, as a whole, hou seholds 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 peopl e; 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 th at these nonquantified costs are much smaller than the nonquantified benefits. These nonquantified costs r esult from uncertainties surrounding rule assumptions and from modeling assumptions. For example, EPA es timated 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 th e 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 disi nfection 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 overestim ate 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 becau se 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 cl arify the source classification. If a source is reclassified as GWUDI, the system may incu r significant additional costs to comply with the requirements (e.g., filtration) under the various regula tions 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 re gulations 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 "reali zation" is selected for them in each "uncertainty iteration" of this EA. These uncertainties then propa gate through the derivation of final estimates so the total uncertainty of those final estimates can be unde rstood. The paragraphs that follow discuss the most important of these uncertain quantities.
The Baseline Numbers of Ground Water Systems, P opulations Served, and Associated Disinfection Practice
The baseline number of systems is uncertain b ecause 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 ma y 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, SDWI S 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 uncerta inty in influencing the estimates within the GWR EA is small compared to other uncertain component s 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 monito ring 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 es timates that are consistent with the data. This uncertainty sample is an input to the probabilis tic economic analysis, where these uncertainties are combined with the uncertainties of other inputs to por tray total uncertainty in the GWR cost and benefit estimates. EPA’s occurrence model includes concentr ation differences between more and less vulnerable wells, but applies the same hit rate model to both ty pes 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 S ystems Identified as Having Significant Deficiencies, the Percent of These Deficiencies That A re Corrected, and Associated Costs and Benefits
For the sanitary survey provisions, EPA estimated the impacts associated w ith well deficiencies. EPA used data from the 1998 ASDWA survey to es timate the percent of wells with deficiencies (ASDWA, 1997). To estimate benefits, EPA assumed that if a correction of a well defect occurred at aEconomic 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 det ected 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 corr ections 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 si gnificant 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 distributi on 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 ha ve 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 a bout 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 uncerta inty sample of the relevant parameters. Again, EPA assumes no difference based on vulnerability or sensitivity.
Undisinfected wells are subjected to triggere d 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 contam ination. 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 f actors. 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 aver age 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 fo r the universe of systems. As a result, there is uncertainty inherent in these unit cost estimates si nce 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 c onditions. EPA quantifies the uncertainty in these national average unit cost factors for specific t echnologies. 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 Ar senic Rule. EPA believes that the uncertainties in capital and O&M costs for a given treatment tec hnology are independent of one another and that uncertainties across all technologies are independent.
Optional Assessment Monitoring
The Agency was not able to estimate the bene fits 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 resu lts 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 co rrective actions decisions, and recordkeeping.
Corrective Actions and Significant Deficiencies
The Agency also did not develop costs for co rrective actions for all conceivable significant deficiencies that a system may encounter. Instead, re presentative actions that span the range of low cost to expensive actions were used. The corrective ac tions that are a result of significant deficiencies identified during sanitary surveys do not include the on es performed within the treatment plant or in the distribution system due to lack of adequate data. Ex clusion 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 co sts (as well as benefits) from the correction of sanitary survey deficiencies identified in the dist ribution 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 cost s. The Agency has been careful to use the best available data, to account for uncertainty quantitativel y 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 th e 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 XEconomic 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 annua lized costs to PWSs for the final GWR at 3 and 7 percent discount rates. Exhibit 6.34 presents the tota l 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%

Lowe r (5th %ile) Uppe r (95th %ile) Lowe r (5th %ile) Uppe r (95th %ile)

2.91 $ 2.13 $ 3.69 $ 2.91 $ 2.16 $ 3.72 $ 3.61 $ 2.54 $ 4.94 $ 3.59 $ 2.60 $ 4.83 $ 1.45 $ 0.99 $ 1.98 $ 1.44 $ 1.00 $ 1.94 $ 1.96 $ 1.29 $ 2.76 $ 1.94 $ 1.30 $ 2.69 $ 2.23 $ 1.40 $ 3.26 $ 2.26 $ 1.49 $ 3.25 $ 2.85 $ 1.87 $ 4.06 $ 3.05 $ 2.05 $ 4.41 $ 1.78 $ 1.01 $ 2.73 $ 1.88 $ 1.11 $ 2.84 $ 1.89 $ 1.14 $ 2.89 $ 2.12 $ 1.31 $ 3.18 $ 0.00 $ 0.00 $ 0.00 $ 0.00 $ 0.00 $ 0.00 $ 18.67 $ 12.39 $ 26.31 $ 19.19 $ 13.03 $ 26.87 $

1.77 $ 1.34 $ 2.27 $ 1.78 $ 1.34 $ 2.26 $ 1.86 $ 1.21 $ 2.60 $ 1.83 $ 1.23 $ 2.53 $ 0.67 $ 0.43 $ 0.97 $ 0.66 $ 0.42 $ 0.94 $ 0.46 $ 0.28 $ 0.68 $ 0.46 $ 0.28 $ 0.67 $ 0.10 $ 0.05 $ 0.16 $ 0.10 $ 0.06 $ 0.17 $ 0.04 $ 0.02 $ 0.07 $ 0.04 $ 0.02 $ 0.07 $ 0.01 $ 0.00 $ 0.01 $ 0.01 $ 0.00 $ 0.01 $ 0.01 $ 0.00 $ 0.01 $ 0.01 $ 0.00 $ 0.02 $

- $ - $ - $ - $ - $ - $ 4.91 $ 3.33 $ 6.77 $ 4.89 $ 3.36 $ 6.68 $

17.74 $ 12.87 $ 23.27 $ 17.86 $ 13.11 $ 23.44 $ 7.07 $ 4.75 $ 9.95 $ 7.00 $ 4.76 $ 9.61 $ 0.98 $ 0.58 $ 1.45 $ 0.96 $ 0.59 $ 1.38 $ 0.42 $ 0.25 $ 0.63 $ 0.42 $ 0.26 $ 0.63 $ 0.13 $ 0.07 $ 0.21 $ 0.14 $ 0.07 $ 0.22 $ 0.08 $ 0.04 $ 0.14 $ 0.09 $ 0.04 $ 0.15 $ 0.01 $ 0.00 $ 0.01 $ 0.01 $ 0.00 $ 0.01 $ 0.01 $ 0.01 $ 0.02 $ 0.01 $ 0.01 $ 0.02 $

- $ - $ - $ - $ - $ - $ 26.44 $ 18.56 $ 35.68 $ 26.49 $ 18.84 $ 35.46 $ 50.02 $ 34.28 $ 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 annua l 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 fecalEconomic 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 15.3 $ 11.8 $ 19.2 $ 15.3 $ 11.9 $ 19.0 $

Alternative 2 - Risk-Targeted Approach (Final Rule) Sanitary Survey and Triggered Monitoring 61.8 $ 45.2 $ 81.4 $ 62.3 $ 46.1 $ 81.6 $ Alternative 3 - Multi-Barrier Approach Sanitary Survey, Hydrogeologic Sensitivity Assessment, Assessment Monitoring, and Triggered Monitoring 67.9 $ 49.4 $ 89.5 $ 69.4 $ 51.0 $ 90.6 $

Alternative 4 Across-the-Board Disinfection 686.4 $ 636.8 $ 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 in curred 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 estim ates for implementation and annual administration for the final regulatory alternative are presented in Exhib its 6.7a and 6.7b. These costs are estimated to be similar for Alternatives 2 and 3. States incur less bur den from oversight and administration of Alternatives 1 and 4 because these alternatives do not have mon itoring 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 allocat ed 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 num ber 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 require d 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 accordan ce 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 Cap acity Assessment as required by Section 1420(d)(3) of the 1996 Amendments to the SDWA. 5) Paperwork Reduction Act (a separate Informa tion Collection Request document contains the complete analysis). 6) Unfunded Mandates Reform Act (UMRA) of 1995. 7) Executive Order 13175 (Consultation and Coordina tion 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 Regul ations That Significantly Affect Energy Supply, Distribution, or Use).
Many of the requirements and executive orders lis ted 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 rega rding the objectives of the rule). More specifically, they are designed to assess the financial and health eff ects of the rule on sensitive, low-income, and Tribal populations as well as on small systems. The chap ter also examines how much additional capacity systems will need to meet GWR requirements and wh ether 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 independen tly owned and operated a nd is not dominant in its field.” However, the RFA also authorizes an agency to u se 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 consu lt with SBA’s Chief Council for Advocacy.

The RFA references the definition of “small bus iness” found in the Small Business Act, which authorizes the SBA to define “small business” furthe r 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 (Adminis tration 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 busin esses 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 co llected on businesses, organizations, and governmental jurisdictions in terms of the number of water cust omers they serve. Therefore, EPA chose to use an alternative definition for small entities.
For purposes of assessing the impacts of the GW R 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 usi ng this alternative definition in the Federal Register (63 FR 7620; February 13, 1998), requested public comment, consulte d with the SBA, and finalized the alternative definition for all future drinking wa ter 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 sanita ry survey requirement and a substantial number these systems will be impacted by additional requireme nts 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 S BREFA, and Section 203 of UMRA require EPA to provide small governments with an opportunity for timel y 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 Wa ter 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 Prima ry Drinking Water Regulations: Ground Water . The small entity stakeholder comments on components of the GW R 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 SB AR 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 ru le, on the need for the rule, and the potential requirements. The small entity stakeholders were ask ed to provide input on the potential impacts of the rule from their perspective. All 22 small entity st akeholders 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 Pa nel, the small entity stakeholders were invited to provide additional comments on the information provi ded. Three small entity stakeholders provided additional comments on the rule components after the teleconference.
In general, the small entity stakeholders cons ulted on the GWR were concerned about the impact of the rule on small water systems (because of th eir small staff and limited budgets), the additional monitoring that might be required, and the da ta and resources necessary to conduct a hydrogeologic sensitivity assessment (HSA) or sanitary survey. Ther e 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 provi sions and opposed mandatory disinfection acrossthe-board. Small entity stakeholders expressed s upport for existing monitoring requirements as a means of determining compliance, and some supported in creased requirements for total coliform monitoring.
Consistent with the RFA/SBREFA requireme nts, the SBAR Panel evaluated the assembled materials and small entity comments related to the el ements 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 est ablish different rule requirements for systems basedEconomic 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 ensuri ng 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 stakeholde rs’ 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 cont aminant (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 a nd treatment techniques available that would allow systems to meet the GWR requirements. EPA determ ined that ground water systems of all sizes can meet the requirements of 4-log virus inactivation by usi ng chlorine (hypochlorination or gas disinfection), which is also relatively inexpensive and si mple 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 lik ely 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 dr inking water standards. Capacity encompasses three components: technical, managerial, and financial. T echnical 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 infrastructur e, 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 a pplicable standards? Can the operators effectively implement this technical know ledge? 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 fi nancial, 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 a nd managers clearly identified? Is the system properly organized and staffed? Do personnel understand the management aspects of regulatory requirements and syst em operations? Do they have adequate expertise to manage water system operati ons? 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 comp liance with SDWA requirements. Key issues include:
• Revenue Sufficiency—Do revenues cover costs?
• Creditworthiness—Is the system financia lly healthy? Does it have access to capital through public or private sources?
• Fiscal Management and Controls—Are ade quate books and records maintained? Are appropriate budgeting, accounting, and fina ncial planning methods used? Does the system manage its revenues effectively?

7.5.1 Requirements of the Final GWR
This capacity analysis is presented only fo r the Final Rule, although EPA took similar considerations into account in the selection of the Fina l Rule over the other alternatives. This process led to the incorporation of less expensive rule featur es for systems having fewer capabilities. For example, EPA allowed flexibility in the triggered monitoring re quirements for certain small systems. Very small systems that must take four repeat samples follo wing 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 th at 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 unde r 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. Re fer 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 syst ems (Exhibits 7.1a) and for large systems (Exhibit 7.1b). This distinction is necessary becau se most large systems will face fewer challenges in implementing the rule than smaller systems. Fo r 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 October 2006Final Ground Water RuleExhibit 7.1a Estimated Impact of the GWR on Small System’s Technical, Managerial, and Financial Capacity(0 = no impact, 1 = minimal impact, and 5 = very significant impact)RequirementNumber and Percent ofSmall SystemsTechnical Capacity Managerial Capacity Financial Capacity

Source Water Adequacy Infrastructure Adequacy Technical Knowledge & Implementation Ownership Accountability Staffing & Organization Effective External Linkages Revenue Sufficiency Credit Worthiness Fiscal Mgmt. & ControlsFamiliarization with rulerequirements145,580 (100%) 0 00121111Sanitary surveys 145,580 (100%) 0 00000000Triggered monitoring 128,711 (88%) 0 00111111Corrective actions forsignificant deficiencies24,749 (17%) 4 44444444Compliance monitoring 3,685 (3%) 2 22222222Notes: (1) To analyze the impact of theserequirements on system capacity, the requirements believedto have the most and the least impact onaffected systems were analyzed first. These initial analyses werethen used as the bases againstwhich the relative impact ofthe remainingrequirements were assessed. The impact estimates developed foreach requirement were also compared to those developed for theLong Term2 Enhanced Surface Water Treatment Rule(LT2ESWTR) and the Stage 2 Disinfectants and Disinfection Byproducts Rule (Stage 2 DBPR) toensure cross-rule consistency andto enable cross-rule comparisons.(2) The scores presented above represent the worst case scenario; the requirementsof this rule are expected to have less impact on thecapacity 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 previous regulations based onthe cost and number of systems/plants that require additional capacity to complywith each requirement, as described in section7.5.4.Economic Analysis for the 7-8 October 2006Final Ground Water RuleExhibit 7.1b Estimated Impact of the GWR on LargeSystem’s Technical, Managerial, and Financial Capacity(0 = no impact, 1 = minimal impact, and 5 = very significant impact)RequirementNumber andPercent of LargeSystemsTechnical Capacity Managerial Capacity Financial Capacity

Source Water Adequacy Infrastructure Adequacy Technical Knowledge & Implementation Ownership Accountability Staffing & Organization Effective External Linkages Revenue Sufficiency Credit Worthiness Fiscal Mgmt. & ControlsFamiliarization with rulerequirements1,750 (100%) 1 11111111Sanitary surveys 1,750 (100%) 0 00000000Triggered monitoring 964 (55%) 0 00000000Corrective actions for significantdeficiencies298 (17%) 3 33333333Compliance monitoring 123 (7%) 2 22222222Notes: (1) To analyze the impact of theserequirements on system capacity, the requirements believedto have the most and the least impact onaffected systems were analyzed first. These initial analyses werethen used as the bases againstwhich the relative impact ofthe remainingrequirements were assessed. The impact estimates developed foreach requirement were also compared to those developed for theLT2ESWTR and the Stage 2 DBPR to ensure cross-ruleconsistency and to enable cross-rule comparisons.(2) The scores presented above represent the worst case scenario; the requirementsof this rule are expected to have less impact on thecapacity 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 previous regulations based onthe cost and number of systems/plants that require additional capacity to complywith each requirement, as described in section7.5.4.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 PW Ss to which the regulation applies.
2. List all of the requirements of the regulation.
3. Determine the type and number of PW Ss 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 co st and technical information contained in SDWIS, EAs developed for other rules, information collec tion requests, and other supporting documentation for the rule. These data sources are also used to deve lop 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 inExhibit 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. Afte r 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 comp arisons, 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 requireme nts 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 accu rately 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 th e 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 themsel ves 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 cap acity 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 systemsEconomic 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, e liminating 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 pe ople or fewer and using disinfection can conduct daily grab samples to measure disinfection levels inst ead of installing more costly continuous monitoring equipment. However, this may also require the syst em 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 correc tive action are expected to experience the most significant financial challenge since many correc tive actions consist of a large, one-time capital expenditure to resolve the problem. Changes in tr eatment 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 familia rize 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 signifi cant challenge meeting the technical, managerial, and financial requirements associated with corrective ac tion. 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 a llow the States/Primacy Agencies and EPA to determine appropriate requirements for specific system s 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 gene rate, 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 an y 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 Agenci es 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 Pr imary Drinking Water Regulations: Final Ground Water Rule (USEPA 2006c).
The total burden associated with GWR requirement s 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. Th e 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 Prim ary 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 Account ability and Reform,” are relevant to the GWR and are discussed in this section. Title II, Sec tion 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 identif y and consider a reasonable number of regulatory alternatives and adopt the least costly, most cost-eff ective, or least burdensome alternative that achieves the objectives of the rule before promulgating a ru le 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 alterna tive 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 r esult in expenditures of $100 million or more for State, Local, and Tribal governments, in the aggreg ate 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, St ate, 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 Cost s from GWR Cost Model Output.

Although the GWR is not subject to the requi rements 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 di sproportionate budgetary effects (Chapter 6, section 7.7.2)

• Macroeconomic effects (section 7.7.3)
• A summary of EPA’s consultation with Stat e, 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 regulat ory alternatives and the selection of the least costly, most cost-effective, or least burdens ome 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 exposur e 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 becau se it does not include the pain and discomfort associated with the illness. Mortaliti es were valued using a value of statistical life estimate consistentEconomic 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. Th e 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 bacteria lly 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 analys is of nonquantified benefits from avoided bacterial illnesses and deaths is presented in section 5.4. This ru le 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, cal culating regulatory compliance costs, and estimating any disproportionate impacts. Chapter 6 of this doc ument details the cost analysis performed for the GWR. Under the Preferred Alternative, the likely compliance scenario is exp ected 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 th e range of annualized costs and benefits for each regulatory alternative.



### Exhibit 7.4 Mean Total Annualized Benefi ts and Costs of Regulatory Alternatives ($Millions, 2003$)

Source: Benefits from Exhibit 5. 31. Costs from Exhibit 6.35.

Various Federal programs exist to provide fi nancial 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 responsib ility 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/Pr imacy Agencies may use PWSS Grants to set up and administer a State program that includes such activ ities 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 contai ning. . . (3) estimates by the agency, if and to the extent that the agency determines that accurate estimat es 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 comm unities, or particular segmen ts of the private sector...”

Economic Analysis for the 7-15 October 2006 Final Ground Water Rule Additional funding is available from other progr ams 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 Progr am, 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 infrast ructure needed to achieve or maintain compliance with SDWA requirements. Each State has considerab le flexibility to determine the design of its DWSRF Program and to direct funding toward its most pr essing 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 transf er a portion of funds from their Clean Water State Revolving Fund accounts to their DWSRF accounts.
A State/Primacy Agency can use the financial r esources 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 u sed to provide technical assistance to small systems. In addition, up to 14 percent of the State/Primacy Ag ency’s grant may be used to provide TMF assistance to all system sizes. For small systems that ar e disadvantaged, up to 30 percent of a State/Primacy Agency’s DWSRF may be used for increased loan subs idies. 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, repa ir, 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 program s. 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 popula tions 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 gr ants 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 Stat e, Local, and Tribal governments of Federal mandates that are not accompanied by adequate Fe deral funding. Section 202 of UMRA requires an analysis of possible disproportionate budgetary eff ects of certain classes of rules, in which the GWR falls. 1 EPA believes that the cost estimates presente d in Exhibit 7.5 accurately characterize future compliance costs of the GWR. EPA explored possibl e disproportionate impacts of the GWR on particular geographic areas and groups of customers. In gene ral, the costs that a PWS, whether publicly- or privately-owned, will incur to comply with this ru le will depend on many factors that are not generallyEconomic 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 Cate g or y 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 la rge 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 co mparatively more ground water systems. However, costs are not expected to be highly focused on a pa rticularly 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 imp act 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 syst ems 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 ar e 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 Tri bal 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 sm all 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
≤ 100 226 $ 187 $ 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 sy stems is the total cost to privately-owned water systems compared to that incurred by publicly-o wned 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 fro m 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 cost s of the rule, but it does not expect cost per system to differ systematically with ownership. Most importan tly, 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 productiv ity, 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 ha ve a measurable effect. A regulation with a smaller aggregate effect is unlikely to have any measura ble impact, unless it is highly focused on a particular geographic region or economic sector. The GWR shoul d not have a measurable effect on the national economy; the total annualized costs for the rule ra nge 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 co st 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 governme nts, 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 a ffected 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 government s 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 th ese 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 stak eholders 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 Associa tion, the Ground Water Foundation, the National Ground Water Association, the National Rural Water Associa tion, and the National League of Cities. Twelve State drinking water representatives also par ticipated in the Agency’s GWR workgroup.

In addition to these consultations, EPA circulat ed 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 ove r 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 fro m Federal government agencies, and 4 from other people/organizations. No comments were receive d from Tribal governments. EPA reviewed the comments and carefully considered their merit. Th e 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 conci sely 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 cons idered several regulatory alternatives and numerous methods that would reduce microbial cont amination 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 th at achieves the rule’s objec tive 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 th e 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 de velopment process through the SBREFA process, public stakeholder meetings, and Tribal meetings. Re presentatives of small governments took part in the SBREFA process for this rulemaking and attended pub lic stakeholder meetings. Through participation and exchange in the SBREFA process and various mee tings, 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 i nput 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 E xhibit 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), re quires 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 th at is not required by statute, unless the Federal government provides the funds necessary to pay th e direct compliance costs incurred by Tribal governments, or EPA consults with Tribal offici als 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 complian ce costs on Tribal governments, and the FederalEconomic 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. Accord ingly, 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 extensiv e 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 H ealth 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 imp act 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 theFinal Ground Water Rule 7-21 October 2006% 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 P Q = A * PPrimarily Disinfecting Ground Water CWSs≤100171 100% 171 100% 171 0% 0 76% 130 0% 0 24% 42 31% 53 226$ 38,686$101-500 223 100% 223 100% 223 0% 0 62% 138 0% 0 24% 53 45% 100 251$ 56,084$501-1,000 69 100% 69 100% 69 0% 0 61% 42 0% 0 24% 16 46% 32 312$ 21,562$1,001-3,300 69 100% 69 100% 69 0% 0 63% 43 0% 0 22% 15 42% 29 331$ 22,851$3,301-10,000 21 100% 21 100% 21 0% 0 62% 13 0% 0 24% 5 45% 9 773$ 16,230$10,001-50,000 3 NA NA NA NA NA NA NA NA NA NA NA NA NA NA -$ -$50,001-100,000 0 NA NA NA NA NA NA NA NA NA NA NA NA NA NA -$ -$100,001-1 Million 0 NA NA NA NA NA NA NA NA NA NA NA NA NA NA -$ -$> 1 Million 0 NA NA NA NA NA NA NA NA NA NA NA NA NA NA -$ -$Subtotal556 553 553 0 367 0 132 224 155,413$Primarily Disinfecting Ground Water NTNCWSs≤10034 100% 34 100% 34 0% 0 91% 31 0% 0 24% 8 16% 6 187$ 6,371$101-500 28 100% 28 100% 28 0% 0 91% 25 0% 0 25% 7 17% 5 275$ 7,689$501-1,000 13 100% 13 100% 13 0% 0 91% 12 0% 0 25% 3 17% 2 354$ 4,607$1,001-3,300 21 100% 21 100% 21 0% 0 91% 19 0% 0 29% 6 21% 4 646$ 13,568$3,301-10,000 2 100% 2 100% 2 0% 0 91% 2 0% 0 31% 1 23% 0 1,361$ -$10,001-50,000 0 100% 0 100% 0 0% 0 91% 0 0% 0 33% 0 25% 0 3,769$ -$50,001-100,000 0 NA NA NA NA NA NA NA NA NA NA NA NA NA NA -$ -$100,001-1 Million 0 NA NA NA NA NA NA NA NA NA NA NA NA NA NA -$ -$> 1 Million 0 NA NA NA NA NA NA NA NA NA NA NA NA NA NA -$ -$Subtotal98 98 98 0 89 0 25 17 32,235$Primarily Disinfecting Ground Water TNCWSs≤10057 100% 57 100% 57 0% 0 98% 56 0% 0 28% 16 13% 7 275$ 15,688$101-500 11 100% 11 100% 11 0% 0 98% 11 0% 0 28% 3 12% 1 372$ 4,096$501-1,000 3 100% 3 100% 3 0% 0 98% 3 0% 0 28% 1 13% 0 506$ 1,517$1,001-3,300 1 100% 1 100% 1 0% 0 98% 1 0% 0 30% 0 15% 0 721$ 721$3,301-10,000 1 NA NA NA NA NA NA NA NA NA NA NA NA NA NA -$ -$10,001-50,000 0 100% 0 100% 0 0% 0 98% 0 0% 0 35% 0 20% 0 4,127$ -$50,001-100,000 0 NA NA NA NA NA NA NA NA NA NA NA NA NA NA -$ -$100,001-1 Million 0 NA NA NA NA NA NA NA NA NA NA NA NA NA NA -$ -$> 1 Million 0 NA NA NA NA NA NA NA NA NA NA NA NA NA NA -$ -$Subtotal73 72 72 0 71 0 20 9 22,022$TOTALS727 723 723 0 527 0 177 250209,670$SystemsConductingAssessmentMonitoringSystemSize/TypeNumber ofSystemsAffectedbyGWRMeanAnnualizedCost perSystemEstimatedTotal TribalCostsSystemsConductingImplementationActivitiesSystemsConductingSantitarySurveysSystemsConductingHSAsSystemsConductingTriggeredMonitoringSytems TakingCorrectiveActionSystemsConductingComplianceMonitoringExhibit 7.7 Annual Cost of Compliance for Tribal Systems by SystemType 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 sy stems 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 co sts 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 cost s for various rule activities. Second, the average cost of each rule requirement is multiplied by the num ber of Tribal systems expected to incur costs. Exhibit 7.7 shows the percentage of systems expect ed to incur costs for va rious 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 consid ered 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 populati on. These sensitive subpopulations include the young, elderly (especially those weakened by other cond itions), 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, indivi duals with Lupus or cys tic 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 in creased risk from enteric viruses as well as act as a source of infection for neonates. Infection duri ng 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 fo r 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 e xplicitly 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 bot h 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 Enviro nmental Health Risks and Safety Risks
Executive Order 13045 (62 FR 19885; April 23, 1997) a pplies to any rule initiated after April 21, 1998, that (1) is determined to be “economica lly significant” as defined under Executive Order 12866; and (2) concerns an environmental, health, or safet y risk that EPA has reason to believe may have a disproportionate effect on children. If the regulator y action meets both criteria, EPA must evaluate the environmental, health, or safety effects of the pl anned rule on children, a nd explain why the planned regulation is preferable to other potentially effec tive 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 in fection 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 hea lth 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-o f-illness associated with viral illnesses avoided in young children. In other words, the analysis suggests th at the viral and bacterial illnesses of concern to the GWR disproportionately affect children, and ther efore, 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 missi ons by directing agencies to identify and address disproportionately high adverse human health or envi ronmental effects of its programs, policies, and activities on minority and low-income populations. Th e 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 or der 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 ove rall 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 expos ure 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 co mmunities 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 variousEconomic Analysis for the 7-24 October 2006 Final Ground Water Rule components of pending drinking wate r regulations and how they might impact sensitive subpopulations, minority populations, and low-income populations. Th is 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 benef its, data quality, health effects, and the regulatory process. Participants were national, State, Tr ibal, 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 c oncerning 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 ar e 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 protec tion 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 di fferences. Thus, the GWR meets the intent of Federal policy requiring incorpora tion 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 bacter ia 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 tim ely input by State and Local officials in the development of regulatory policies that have Federalis m 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 am ong the various levels of government.”

Under Section 6(b) Executive Order 13132, EPA ma y not issue a regulation that has Federalism implications, that imposes substantial direct complian ce 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 a nd 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 thei r 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 officialsEconomic 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 mu st 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 Stat e 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 ASDW A. 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 th e incidence of fecally contaminated drinking water supplies by requiring corrective actions for fecally c ontaminated 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 discu ssions with State and Local elected officials regarding the implications of the rule during th e public comment period and took their recommendations under consideration during the developm ent 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 “signi ficant 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 Admi nistrator 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 woul d adversely affect the supply of energy. The GWR does not regulate power generation, either direc tly 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 a dversely affect the supply of energy.
In response to the GWR, some water utilities are e xpected 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 dist ribution. 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 th at 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 woul d 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 re quires 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 th e 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 2004a 2 ). The energy use per plant for each flow range and technology or correctiv e action is then multiplied by the number of plants3 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 ClO 2 

### 39 11,928 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 electri city 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 ta ken from Exhibits 6.5b and 6.21b. [B] ClO 2 , 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 Chlo rination, 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 num bers 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 2004b 3 ). 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 0.004 12,857 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 0.004 8,606 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 0.003 63,288 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 (ClO 2 

### 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 ch lorine dioxide taken from Exhibit 6.21b [D] Energy cost per entry point inte rpolated 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 signi ficantly 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 a nd 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 2004b 4 ). 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 plan t 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 an alysis reflects the effect of the rule on national energy supply, distribution, and use. While certa in 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 averag e use and conditions of peak power demand).
The total increase in energy usage by water syst ems 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 adve rse 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 quantif ied 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 nonqua ntified benefits. In particular, EPA estimates that the nonquantified benefits associated with bacteria l illness would increase total benefits to about five times the quantified benefits associated with vira l 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 al so accrue but are not quantified.
The following sections present summary results fro m the quantified economic analysis, followed by a discussion of the results based on evaluation of the total benefits, both qua ntified 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 illn ess attributable to consumption of drinking water from the PWSs affected by the rule. The quantifie d acute viral illnesses are those associated with Type A (represented by data from rotavirus) and Type B (repr esented by data from enterovirus and echovirus) and are a subset of the total illnesses, both acute and ch ronic, 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 Traditiona l 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 appr oach and the discount rate used.

There are substantial benefits attributable to th e 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-hea lth benefits. Nonquantifie d 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 b acterial 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 av erting 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

Mean Mean System Type 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 subs tantial 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 E xhibit 8.3. The nonquantified benefits result from multiple factors. First, the quantified bene fits 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 uncer tainty ranges in the benefit analysis. This EA, where applicable, discusses alternative assumptions. For example, the enterovirus morbidity fractions are, by assumption, not determined using coxsackievi rus (an enterovirus) data although the enterovirus severity data use all enterovirus data. If coxsackievi rus 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 incr ease 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 discu ssed 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 gastroenter itis illness and fatal dehydration associated with that illness are monetized. Norovirus disease is not cons idered. For the enteroviruses, all acute disease endpoints are considered, but the prevalence of sever e 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, e ither 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 explic itly on what has been directly measured in PWS wells, yet there is great difficulty in identifying a nd 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 contamin ation scenarios are thoroughly documented in the ground water contamination and outbreak scientific literatu re. However, these scenar ios, 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 ep idemic disease (outbreaks). If epidemic illnesses and the avoided non-health-related costs of ground wa terborne disease outbreaks were included, the quantified benefits would increase.
In summary, this EA quantifies a subset of the to tal health and non-health related benefits. In a sample calculation, discussed in Section 5.4.3.2, EPA es timated that the total benefits could increase by a factor of five by only accounting for additional d eaths and hospitalizations caused by bacterial illness being avoided. While EPA recognizes that this estim ate includes substantial uncertainty, given all the other nonquantified factors described above, EPA believ es 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 quantifiedEconomic 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 fro m 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 milli on 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 bene fits with estimated costs. Based on the comparison of these values, the estimated quantified be nefits of the rule range from approximately onethird to about one-seventh of the value of the co sts, 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 par ticular avoided bacterial illnesses and deaths, which would significantly increase the net benefits of the final GWR. E xhibit 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 bac terial 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 person al 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 Cate g or y Benefits 3% 7% Quantified Benefits (ECOI) 19.7 $ 16.8 $ Bacterial Illness and Death Avoidance Benefits 98.6 $ 83.8 $ Total 118.3 $ 100.6 $ Costs 61.8 $ 62.3 $ Net Benefits 56.5 $ 38.3 $ 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 uncerta inties 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 distri bution 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 de termined by statistical models that allowed the data to inform the distribution. Choice of statisti cal models were based on examining the data combined with use of scientific principles. Alternative assump tions were tested and described in alternative analyses. The EA also includes detailed discussi on of the additional uncertainty associated with nonquantified factors and untested assumptions.
The quantified GWR benefits are calculated us ing 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 thr oughout 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 qua ntified 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 to tal mean benefits are expected to be several times greater than the quantified mean benefits and are lik ely 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 be nefits 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 identif ied 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. Exclus ion 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 fo r correction of treatment or distribution system significant deficiencies is minimal since data limitati ons also exclude quantifying any benefits that may be realized for correcting these significant deficiencies.
There is uncertainty in the cost analysis that c ould 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 nationa l costs. The greatest uncertainties affecting the costs of the GWR are in the per centages used to estimate complia nce and costs for each regulatory alternative. However, by using a Monte-Carlo anal ysis, 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 co sts are much smaller than the nonquantified benefits and the estimates of the national net be nefits are conservative. Detailed discussion of nonquantified benefits and costs are presente d in chapters 5 and 6, respectively.



### 8.3 Breakeven Analysis
In the face of uncertainties, it is helpful to eval uate the range over which the regulation meets the critical test of benefits exceeding costs. Thus, th e number of illnesses or deaths that would have to be avoided annually to compensate for costs, or for th e 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 a pproach. 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) avoi ded by the final GWR. To “break even” using deaths avoided as a measure, approximately 8 deaths w ould have to be avoided for either a three or seven percent discount rate. Although this number of d eaths 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 bacteria l 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 w as 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 Even 1
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 thi s 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 in cluded 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 mon itoring, 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 regulat ory 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 pr esentations 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 Quanti fied Viral Illnesses and Deaths Avoided Regulatory AlternativesEconomic 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 expect ed 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 moneti zed 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 bene fits far exceed those that EPA was able to quantify, and their incorporation into the quantified analysis would resu lt 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 th e enhanced COI and are very close to positive using the traditional COI. Based on consideration of th e large number of nonquantifie d benefits, EPA believes that this level of additional nonqua ntified benefits in relation to quantified benefits will be easily achieved. Therefore, consideration of these nonquan tified 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 Bene fits 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 E xhibits 8.11a and 8.11b, the test is to see if any alternative falls to the right a nd 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 altern atives 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 o ffer 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)

A lt 3 A lt 4

A l t 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)

A lt 3 A lt 4

A lt 1 Final Rule 

### Exhibit 8.11a Mean Annualized Costs at Mean Benefit Level, Enhanced COI, by Regulatory AlternativeEconomic 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)

A l t 3 A lt 4

A lt 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)

A lt 3 A lt 4

A lt 1 Final Rule 

### Exhibit 8.11b Mean Annualized Costs at Mean Benefit Level, Traditional COI, by Regulatory AlternativeEconomic 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 ev aluating the alternatives, the lower the cost per case or death avoided, the more cost-effective the altern ative is believed to be. Exhibit 8.12 presents the average cost per case of viral illness and deat h 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 consider ed. Thus, the Final GWR is the most efficient alternative by this measure. Given the substantia l nonquantified benefits of the final GWR as described in Chapter 5, the actual cost per case is lo wer 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 incr emental 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 opti on 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 quantif ied 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 alterna tives 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 benef its 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 A nnual Costs A nnual Benefits Incremental Costs Incremental Benefits Incremental Net Benefits A B C D E=D-C

Alternative 1: Sanitary Survey and Corrective Action 15.3 $ 3.6 $ 15.3 $ 3.6 $ (11.7) $

Alternative 2 (Final Rule): Risk Targeted Approach 61.8 $ 19.7 $ 46.5 $ 16.1 $ (30.4) $

Alternative 3: Multi-Barrier Approach 67.9 $ 21.3 $ 6.1 $ 1.6 $ (4.5) $

Alternative 4: Across-the-board Disinfection 686.4 $ 70.2 $ 618.5 $ 48.9 $ (569.6) $

Alternative 1: Sanitary Survey and Corrective Action 15.3 $ 2.9 $ 15.3 $ 2.9 $ (12.4) $

Alternative 2 (Final Rule): Risk Targeted Approach 62.3 $ 16.8 $ 47.0 $ 13.9 $ (33.1) $

Alternative 3: Multi-Barrier Approach 69.4 $ 18.2 $ 7.1 $ 1.4 $ (5.7) $

Alternative 4: Across-the-board Disinfection 665.3 $ 61.9 $ 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 hous ehold production). The Enhanced COI also factors in valuations for lost personal time (non-work ti me) such as childcare and homemaking (to the extent not covered b y 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 quantif iable benefits of the GWR. The unquantified benefits are expect ed 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 in crease 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 w ould 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-mone tized benefits would be unlikely to compensate. However, comparisons betw een Alternative 4 and the other alternatives may be between two separate sets of benefits, in the sense th at they may be distributed to somewhat different populations. However, based on cons ideration 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 altern atives 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 term s 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 15.3 $ 1.9 $ 15.3 $ 1.9 $ (13.5) $

Alternative 2 (Final Rule): Risk Targeted Approach 61.8 $ 10.0 $ 46.5 $ 8.2 $ (38.3) $

Alternative 3: Multi-Barrier Approach 67.9 $ 10.8 $ 6.1 $ 0.8 $ (5.3) $

Alternative 4: Across-the-board Disinfection 686.4 $ 35.5 $ 618.5 $ 24.7 $ (593.8) $

Alternative 1: Sanitary Survey and Corrective Action 15.3 $ 1.5 $ 15.3 $ 1.5 $ (13.8) $

Alternative 2 (Final Rule): Risk Targeted Approach 62.3 $ 8.6 $ 47.0 $ 7.1 $ (39.9) $

Alternative 3: Multi-Barrier Approach 69.4 $ 9.3 $ 7.1 $ 0.7 $ (6.4) $

Alternative 4: Across-the-board Disinfection 665.3 $ 31.5 $ 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 house hold 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 b y 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 quanti fiable benefits of the GWR. The unquantified benefits are expect ed 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 Quantifi ed 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 an alyses related to the final rule. This process included an analysis of net benefits, as well as cost e ffectiveness 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. Th e following is a summary of these analyses.
The GWR likely passes economic threshold criteria:
• The GWR has positive net benefits when bot h quantified and nonquan tified benefits are considered. For the Enhanced COI approach, th e 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 appear s likely that the final GWR would have positive net benefits regardless of the discount rate or co st 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 inEconomic Analysis for the 8-20 October 2006 Final Ground Water Rule total benefits that are five times the primary be nefits). 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 GW R would be positive using the Enhanced COI approach. Total net benefits would still be slightly negative using the Traditional COI approach, however, other nonquantified benef its 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 term s. 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 th e same cost or the same benefits at lower cost (Exhibit 8.11).

Final GWR determinations:

C The economic analysis for this rule, cons idering quantified and nonquantified benefits, supports the basis for selecting the final GW R 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 sen sitive (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 logi cal outgrowth of the proposed rule, that it is supported by comments, and that it provides pub lic 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 attri butable to fecally contaminated ground water. EPA also believes that the GWR will provide a desi red level of protection from ground water pathogen contamination at a justifiable cost.Economic Analysis for the R-1 October 2006 Final Ground Water Rule References

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