### Appendix B. 2 : Comparison and Evaluation of Epidemiological Study Designs

of Health Effects Associated with Recreational Water UseU.S. Environmental Protection Agency



## Comparison a nd Evaluation o f Epidemiological Study Designs o f Health Effects Associated w ith Recreational
Water Use

U

. S

. Environmental Protection Agency

Office of Water

December 2010U.S. Environmental Protection Agency

December 2010 i 

## D ISCLAIMER

This report i s intended for inte rnal use by the U.S. Environmental Protection Agency ( EPA ) to support the development of new or revised recreational water quality criteria

.

This document has been through a full QAPP (quality assurance project plan) review process but has not yet been re viewed in accordance with EPA and approved for publication and distribution.

Mention of commercial products, trade names, or services in this document or in the references and/or endnotes cited in this document does not convey, and should not be interpre ted as conveying

, official EPA approval, endorsement, or recommendation.U.S. Environmental Protection Agency

December 2010 ii 

## A CKNOWLEDGMENTS

Questions concerning this document or its application should be addressed to the EPA Work Assignment Manager (WAM) :

John Ravenscroft (WAM) USEPA Headquarters
He alth and Eco logical Criteria Division Office of Science and Technology, Office of Water 1200 Pennsylvania Avenue, NW
Mail Code 4304T Washington, DC 20460
Phone: 202

- 566

- 1101
Email: ravenscroft.john@epa.gov

This draft report was managed under Work Assignment s B

- 06 , 1

- 06, and 3

- 06 of EPA Contract
EP

- C

- 07

- 036 to Clancy Environmental Consulting, Inc. , a Tetra Tech Company. The following individuals contributed to the development of the draft report:

Jeffre y Soller (Technical Lead) Soller Environmental , LLC Timothy Bartrand Clancy Environmental Consultants , Inc. Gunther Craun Gunther F. Craun & Associates
Mark Gibson Clancy Environmental Consultants , Inc.
Michael LePuil Tetra Tech Jeffrey Rosen Clancy Enviro nmental Consultants , Inc.December 2010 iii 

## C ONTENTS

Disclaimer

................................ ................................ ................................ ................................ ........ i Acknowledgments

................................ ................................ ................................ ........................... ii
Contents

................................ ................................ ................................ ................................ ......... iii Tables and Figures

................................ ................................ ................................ .......................... v 1. Executive Summary

................................ ................................ ................................ ................ 1
1.1 O bjectives

................................ ................................ ................................ ......................... 1
1.2 Key Factors Limiting Comparisons between RCT and PC Studies

................................ . 1
1.3 Summary of Recommended Activities

................................ ................................ ............ 2
2. Introduction

................................ ................................ ................................ ............................. 4
2.1 Purpose

................................ ................................ ................................ ............................. 7
2.2 Background

................................ ................................ ................................ ...................... 7 2.2.1 Comparison of PC and RCT Epidemiology Study Designs

................................ .......... 8
2.2.1.1 Prospective Cohort Studies

................................ ................................ ................ 8
2.2.1.2 Randomized Control Trials

................................ ................................ ............... 9 2.2.2 EPA NEEAR Water Studies

................................ ................................ ........................ 10
2.2.2.1 NEEAR Epidemiology Study Design

................................ .............................. 10
2.2.2.2 NEEAR Freshwater Results

................................ ................................ ............ 11
2.2.2.3 NEEAR Marine Water Results

................................ ................................ ........ 13
3. Summary of RCT Water Epidemiology Studies

................................ ................................ ... 16
3.1 Marine RCT Studies Conducted during the 1980s and 1990s in the U.K.

.................... 16
3.2 Freshwater RCT Studies Conducted in Germany

................................ .......................... 17
3.3 Epibathe RCT and Related Studies

................................ ................................ ................ 19
3.4 Miami, Florida RCT Study

................................ ................................ ............................. 21
3.5 Planned Tampa Bay, Florida RCT Study

................................ ................................ ....... 23
3.6 Summary Table of Reviewed Recreational Water Quality Studies

............................... 23
4. Analysis of Study Designs: Differences t hat Could Affect Comparability

.......................... 25
4.1 Summary of Published Commentary on Epidemiological Design Comparison

............ 25
4.2 Differences in the PC and RCT Studies that Can Potentially Affect Comparability of
Data 28 4.2.1 Assignment of Water Qualit y to Bathers

................................ ................................ ..... 28 4.2.2 Swimmer Water Exposure

................................ ................................ ........................... 29
4.2.3 Definition of GI Illness

................................ ................................ ................................ 30 4.2.4 Water Quality

................................ ................................ ................................ ............... 31 4.2.5 Population Investigated

................................ ................................ ................................ 32 4.2.6 Temporal Variability of Molecular and Culturable Indicator Counts

......................... 32
4.3 Summary of Issues on Integrating the Results from RCT with PC Studies

................... 33
5. Options for Additional Anal yses to Facilitate Comparing Results Across Study Designs

.. 34
5.1 Water Quality Metric

................................ ................................ ................................ ..... 34
5.2 Swimmer Exposure to Water Quality

................................ ................................ ............ 36
5.3 Definition of GI Illness and Reporting Period

................................ ............................... 3 6 5.4 Water Quality

................................ ................................ ................................ ................. 37
5.5 Population Investigated

................................ ................................ ................................ .. 38
5.6 Relationship between Culture Methods and Rapid Methods

................................ ......... 38
5.7 Direct Approaches t o Compare RCT and PC Results

................................ .................... 39December 2010 iv 5.7.1 Conduct an RCT in Parallel with a PC Study

................................ .............................. 39 5.7.2 QMRA Translation between RCT and PC

................................ ................................ ... 39
5.7.3 Meta

- Analysis of RCT and PC Studies

................................ ................................ ....... 41
5.8 Interactions between Previously Identified Factors

................................ ....................... 42
6. Recommended Activities and Conclusions

................................ ................................ .......... 44
6.1 Summary of Recommended Activities

................................ ................................ .......... 44
6. 2 Conclusions

................................ ................................ ................................ .................... 45
7. References

................................ ................................ ................................ ............................. 47 Appendix A. Overview of EU and WHO Guidelines for Recreational Waters

.......................... A

- 1December 2010 v 

## T ABLES AND 

## F IGURES

Table 1. Comparison of Major Conclusions from Three Meta

- Analyses of Recreational Water Epidemiolog y Studies

................................ ................................ ................................ ............. 5 Table 2. Summary of Select Recreational Water Quality Approaches, Reports, and Studies

..... 24 Table 3. Current EU Bathing Water Directive Requirements for Microbiological Water Quality Assessment Classification by Indicator Density

................................ ................................ . A

- 1 Table 4. Who Classification Matrix for Integrating Microbial Water Quality as Measured by Enterococci Density with Sanitary Inspection Cate gory

................................ .................... A

- 3 Table 5. WHO Guidelines Values for Microbial Water Quality of Recreational Waters Using the 95th Percentile of Enterococci Density

................................ ................................ ............... A

- 4

Figure 1. Dose

- Response Relationship Used in the Derivation of WHO Numerical Microbiological Criteria for Recreational Waters.

................................ ............................... 26 Figure 2. Proba bility Density Function for Enterococcus , Excess Probability of Gastroenteritis from WHO (2003).

................................ ................................ ................................ ................ 26 Figure 3. Wymer et al. (2005) Extension of the WHO Risk Curve.

................................ ............ 27 Figure 4. Schematic Diagram of a QMRA

- based Approach to Translate RCT Results to a PC Paradigm

................................ ................................ ................................ ............................... 40 Figure 5. Epibathe Meta

- analysis Forest Plots of Gast roenteritis in Marine Water

.................... 41 Figure 6. Epibathe Meta

- analysis Forest Plots of Gastroenteritis in Freshwater

......................... 42 Figure 7. Wat er Quality and Illness Relations for WHO Recreational Water Guideline Values.

...

................................ ................................ ................................ ................................ ............. A

- 7U.S. Environmental Protection Agency

December 2010 1 

### 1. E XECUTIVE 

### S UMMARY

The Beaches Environmental Assessment and Coastal Health Act of 2000 (BEACH Act) requires EPA to publish new or revised Recreational Water Quality Criteria ( RWQC) by October 2012. Since the 1986 guidelines were formulated, a number of prospective epidemiolog y studies have been conducted in Europe and the United States that have estimated the risks associated with
both mari ne and freshwater recreation. Two different types of study were conducted

, (1) experimental ( randomized control trial s [ RCT ]); and (2) non

- experimental ( prospective follow

up or cohort [ (PC ] ) studies. The studies also considered different exposure measur es and illness

outcomes. To support the development and implementation of RWQC, this report considers whether it is possible to compare the results from these PC and RCT studies in a qualitative or quantitative meta

- analysis . Based on the information in this report, additional analyses and/or
data are needed before considering whether i t is possible to integrate the results or pool the data to identify overall trends (i.e., water quality indicator

- illness relationships). This draft report provides a list of activities to fill data gaps and facilitate comparison of the RCT and PC epidemiology study results. However, it is important to note that even with additional data

, a qualitative meta

- analysis m ight be the better option.

1.1 Objectives

This draft re port includes t he following information:

1. A summary of EPA PC studies conducted in temperate US fresh and marine recreational

waters

. 2. D etailed descriptions of RCTs conducted in :

**•** marine recreational waters in the U nited K ingdom (U

. K

. )

,

**•** fresh recreational wa ters in Germany,

**•** marine recreational waters in Florida

, and

**•** fresh and marine recreational waters in the E uropean U nion (EU)

. 3. An explanation of the epidemiological bas e s for the 2006 EU Bathing Water Quality
Directive and the 2003 WHO Guidelines for Safe Re creational Water Environments

. 4. K ey differences in the RCT and PC studies that can affect comparability

. 5. Analyses and additional data that could facilitate compar ison of t he reported RCT and PC
results

.
6. Prioritized r ecommendations to facilitate compar ison o f RCT and PC studies

. 1.2 Key F actors L imit ing C omparisons b etween RCT and PC S tudies

T here is substantial variation in the water quality indicator

- illness curves from epidemiology studies conducted over the last fifty years ( Prüss, 1998 ) . The diversity of results suggests that the resultant curves may depend not only on intrinsic between

- site differences, but on key study
characteristics that can significant ly influence individual exposures and the observed rates of
illn ess. The se study characteristics include the following :U.S. Environmental Protection Agency

December 2010 2 **•** how water quality (i.e., indicators) is assigned as a n exposure variable to bathers;

**•** duration and/or intensity of exposur e ;

**•** definition of illness and duration of incubation;

**•** regulatory conditions an d resulting water quality at the beaches under study;

**•** susceptibility, age , and make

- up of the participants included in the studies ;

**•** source and fate of pathogens and indicators in the i nvestigated water;

**•** temporal and/or spatial variability of pathogens and indicators and their relationships
with each other ; and

**•** analytical methods used to enumerate the indicators.

1.3 Summary of R ecommended A ctivities

To determine if a comparison between RCT and PC studies is possible, additional analyses
and/or data are necess ary. The following is a prioritized list of activities to fill data gaps and facilitate comparison of RCT and PC epidemiology study results:

1. Evaluate the raw data from an RCT study to determine whether EPA’s National Epidemiological and Environmental Asse ssment of Recreational (NEEAR) Water Study
statistical methods and exposure/illness definitions can be applied and if so, conduct a re

analysis . This analysis will indicat e whether RCT and PC results can be directly compared and will help to determine wh ether the observed differences in existing epidemiology studies are due to the study design or other factors. ( Discussion s with Dr. David Kay regarding Epibathe are ongoing )

. 2. Use a quantitative microbial risk assessment ( QMRA ) framework to translate RCT

r esults to a metric that is directly comparable to PC results . Conduct sensitivity analyses to identify model parameters that most strongly influence the results. Compare these results to the results of the analysis recommended above.

3. If the sensitivity a nalyses indicate that the volume of water ingested is a critical component, conduct a pilot study similar to that reported by Dufour et al. (2006)

, using the exposure protocol specified by RCT epidemiology studies to characterize the volume of water ingest ed during the RCT epidemiology studies.

4. Extend the work reported by Boehm ( 2007 ) by using culturable and molecular methods for the indicators of highest interest in several disparate recreational waterbody ty pes for samples collected at multiple depths . This information will help characterize the extent to which the method of allocating exposure to subjects influences the in dicator

- illness relationship . If indicator densit y is highly variable in short spatial and temporal frames, differences in exposure sampling prescribed for RCT versus PC based epidemiolog y studies will have l ess influence on study results.

5. C onduct a n RCT sub

- study within a PC epidemiolog y study ( without additional water quality data ) to verify the results of the above activities

.
6. If the activities described above provide a mechanism to compare RCT and PC study
results , conduct a quantitative meta

- analys i s of human

- impacted waters for epidemiologyU.S. Environmental Protection Agency

December 2010 3 studies conducted world wide

. Otherwise, use the information to supplement the current report and provide a n updated qualit ative meta

- analysis.U.S. Environmental Protection Agency

December 2010 4 

### 2. I NTRODUCTION

Epidemiological methods have estimate d endemic illne ss risks associated with contaminated
recreational waters. Over the past 50 years, several dozen epidemiolog y studies have been
conducted around the world evaluating endemic illness risks associated with recreational waters

. M ost of these studies were con ducted at beaches that were impacted by point sources of human
fecal contamination (effluent from one or more sewage treatment facilities)

. The studies were designed with different objectives and for a variety of local conditions and consequently employed different epidemiolog y study designs ( Rothman, 1986 )

, such as metrics for characterizing water quality, illness definitions, and exposure scenarios

. To address endemic illness risks associated with recreational waters, variations of two basic epidemiolog y study designs have been used

— pros pective cohort (PC) and randomized control trial (RCT ; also called prospective randomized exposure studies [Fleisher et al., 2010] ) studies. Recently, EPA conducted studies using the PC design as part of the EPA’s National Epidemiological and
Environmenta l Assessment of Recreational (NEEAR) Water Study. Comparing the results from the NEEAR epidemiolog y studies to results from past or concurrent studies would be helpful in use of the NEEAR study results in formulation or assessment of new or revised water quality
criteria.

The primary goal of most of the studies conducted of risks due to exposure to surface waters during recreation was to evaluate associations between a quantitative microbial indicator 1 (typically E scherichia coli

, Enterococcus

, Staphyloco ccus , fecal coliforms

, or total coliforms) of water quality and swimming

- associated illness ( typically some form of gastrointestinal [GI] illness)

. These studies comprise a heterogeneous set, with differences in the choice of fecal indicator organism, the range of fecal indicator organism densities encountered during the study, the age range of study participants, the success rate and time period of follow

- up, whether or not
illnesses were self

- reported, the illness endpoints considered, whether they were conducted in fresh or marine waters, how background illness rate was quantified and accounted for, and epidemiolog y study design (PC v s . RCT). Thus, even among epidemiology studies with the same design, heterogeneity among studies is present and should be accounted for in any collective analysis of the studies or a subset of the studies.

Collectively, the studies conducted prior to 2003 are reviewed in the meta

- analyses/systematic
reviews of Prüss ( 1998 ) , Wade et al. ( 2003 ) , and Zmirou et al. ( 2003 )

. Table 1 summarizes and compares some of the ir major conclusions regarding the use of bacterial indicators to assess
advers e health effects resulting from exposure to sewage

- contaminated marine and fresh
recreational waters 2

1 Environmental waters, including recreational waters, may contain many potentially pathogenic microorganisms, including bacteria, viru ses, and protozoa. Because testing for all potential pathogens is infeasible, monitoring of such waters usually relies on indicator microorganisms that are commonly associated with human (and sometimes animal) fecal contamination ( NRC, 2004)

. . All three studies noted a relationship between GI illness and exposure during recreation . However, the relationship between indicator density and incid ence of illness was dependent upon factors in addition to the indicator density. Those factors include the type of study (PC or RCT), the setting (particularly whether the study was conducted at marine or

2 In additio n, several studies in the U nited States (Colford et al., 2007 ; Wade et al., 2006, 2008, 2010 ; Fleisher et al.

, 2010) and studies in Europe (Wiedenmann et al

. , 2006 ; EC

- Epibathe, 2009a,b ) have been completed recently and are described in this report. Howev er, the results of these recent studies have not yet been synthesized by meta

- analyses.U.S. Environmental Protection Agency

December 2010 5 Table 1

. Comparison of M ajor Conclusions from Three Meta

- Analyses of Recreational Water Epidemiolog y S tudies

Conclusion Prüss, 1998 Wade et al., 2003 Zmirou et al., 2003 1

Overall Marine Fresh Overall Marine Fresh Overall Marine Fresh Number of studies in meta

analysis 22 2 15 6 27 17 10 18 2 12 5
Supports use of bacterial indicators to assess/predict adverse health effects Yes Yes Yes Yes Yes Yes Yes Yes Yes

Causal relationship between GI illness and recreational water exposure Yes Yes Yes Yes Yes Yes Yes Yes Yes

Non

- GI illne ss symptoms assessed Yes Yes Yes Yes Yes Yes No No No

GI illness rates higher in lower age groups Yes NA NA Yes 3 NA NA NA NA NA

Supports use of enterococci as an indicator Yes Yes Yes

− Yes No Yes Yes Yes

Supports use of E. coli as an indicator

− No Y es Yes Yes Yes Yes 4 Yes 4 Yes 4

Supports use of fecal coliforms as an indicator NA NA NA No No No Yes 4 Yes 4 Yes 4

Supports use of total coliforms as an indicator NA NA NA No No No No No No

Notes: NA = not specifically assessed or reported; 1 = study exclud ed data from the U.S. EPA ( 1983, 1984) epidemiology studies because swimmers were associated with annual mean indicator density in those studies rather than indicator density associated with the day on which swimming occurred; 2 = meta

- analysis included on e study that assessed both marine and fresh recreational waters; 3 = increased risk for children using enterococci and comparing children only studies versus studies of adults or studies of all ages; 4 = fecal coliforms and E. coli were assessed together.

For more details about these studies, refer to Review of Published Studies to Characterize Relative Risks from Different Sources of Fecal Contamination in Recreational Water ( U.S. EPA, 2009 )

.U.S. Environmental Protection Agency

December 2010 6 freshwater beaches), the characteristics of the study coho rt and particularly whether or not children were included)

, and others. As noted in the brief summaries of the three meta

- analyses
that follow Table 1

, all of the meta

- analyses noted that differences in exposure a nd association of indicator density with illness were potential important sources of heterogeneity and likely sources of bias and should be explicitly considered when results from epidemiolog y studies were different designs are analyzed together.

Wade et al. ( 2003 ) surveyed epidemiolog y studies of recreational exposure to surface waters and developed a weighted regression model relating the log base 10 indicator lev el to relative risk. Sources of variability among studies were evaluated via a random effects meta

- regression model. The variability sources considered were water type ; geographic location ; whether the control group was swimmers or nonswimmers ; swimming definition ; adjustment for covariates ; age of study population ; method of exposure measurement (self

- report, direct observation, or event participation) ; length of follow

- up period ; and study location. Most of these sources of variability differ for PC an d RCT sources for studies reviewed for this draft report. Their analyses indicated that E. coli and e nterococci are useful predictors of GI illness in marine and freshwaters, with E. coli superior to e nterococci for predicting illness in fresh waters. Sou rces of heterogeneity among studies that appeared to impact the relationship between fecal indicator density and illness were whether or not nonswimming controls were used, whether studies were conducted for athletic events (when more rigorous activity cou ld result in different exposures), and whether studies focused specifically on children.

Prüss ( 1998 ) conducted a meta

- analysis of epidemiolog y studies with the intents of establishing a
dose

- response relationship between bathing water quality and illness, determining whether threshold indicator densities are associated with the specific health outcomes, and whether the severity of illness is relate to indica tor density. Prüss’ approach is more qualitative than that of
Wade et al. ( 2003 ) ; factors likely to make the studies heterogeneous were not fully described and

were not assessed quantitatively. Qualitative observations made by Prüss based on comparison of studies selected for analysis are that symptom rates were frequently reported to be higher for younger age groups and that the majority of associations between ind icator organisms and
illnesses were for GI illness. Similar to Wade et al. ( 2003 ) , Prüss (1998) found that there is a causal relationship between GI illness and rec reational water quality ,as measured by fecal
indicator bacteria. Prüss (1998) asserts that enterococci/fecal streptococci and E. coli are the fecal indicator organisms correlating best with GI illness for marine waters and that E. coli
correlated best wi th GI illness for freshwaters

— though the basis for this latter claim is not stated explicitly. In assessing the validity of meta

- analysis of the epidemiology studies, Prüss notes that major sources of bias in epidemiolog y studies are ( 1 ) the use of fecal indicator organisms for assessing water quality (particularly given the poor correlation between the densities of fecal indicator bacteria and viruses) ; and ( 2 ) differences in exposure, with emphasis on whether or not
head immersion occurred. Minor source s of bias were described as self

- reporting of illness symptoms, low response rates, and recruitment method.

Zmirou et al. ( 2003 ) conducted a quantitative meta

- analysis of recreational water epidemiology studies using weighted multiple linear regression with indicator densities as the independent variable and the natural log of relative risk of swi mmers to nonswimmers as the dependent
variable . R andom effects variances were used when heterogeneity was observed . Data selectionU.S. Environmental Protection Agency

December 2010 7 was conducted to minimize heterogeneity, resulting in the notable exclusion of data from studies by Cabelli et al. ( 198 2 ) and U.S. EPA ( 1983, 1984 ) because those studies associated season

averaged indicator densities with swimmers rather than indicator density taken on the day or at the time of swimming. Additio nally, studies were assigned a semi

- quantitative “quality” index which was used as a covariate in the regression model. As part of their regression models

, Zmirou et al. ( 2003 ) grouped fecal coliforms with E. coli and enterococci with fecal streptococci. Grouping fecal coliforms with E. coli appears at odds with the observations of both Wade et al

. ( 2003 ) and Prüss ( 1998 ) , who assessed that fecal coliforms were not sufficiently specific and performed poorly as indicators fecal pollution and human health risk. However, Similar to Wade
et al. ( 2003 ) and Prüss ( 1998 ) , Zmirou et al. ( 2003 ) found an association between indicator density and incidence of GI illness and identified exposure differences between studies as a major potential source of bias.

2.1 Purpose

To support the development of new or revised RWQC by 2012, i t is important to better
understand the differences between the R CT and PC study designs as part of an attempt to better interpret the results of PC and RCT studies and determine whether a quantitative meta

- analysis may be conducted using results from both stu dy types

. To that end, this report address es the following objectives:

1. to d escribe the RCT studies conducted by Kay et al. ( 1994 ) , Fleisher et al. ( 1996 )

, Wiedenmann et al. ( 2006 )

, Fleisher et al. ( 2010 )

, a nd the EU Epibathe program ( EC

Epibathe , 2009a,b) ;

2. to p rovide an analysis of the two types (PC and RCT) of study designs applied at various
international sites and assess key differences in the study designs and how those differences can potentially affect comparability of d ata ;

3. to p rovide a discussion of additional activities which could aid in conducting valid comparisons between PC and RCT studies ; and

4. to i dentify and if possible, analyze an RCT epidemiology dataset by applying the exposure metric as an average exposure to the study participants and to compare results from this approach to the typical RCT approach of assigning water quality data to
individual bathers

. Although it is not an objective of this study, development of techniques for identifying and quantifying heterogeneity among epidemiolog y studies of the same type (either all PC or all RCT) is an important component of any quantitative or qualitative meta

- analyses. Those techniques could be based on qualitative or quantitative analysis of aggregate measures from studies (e.g., relative risks for indicator density ranges) or analysis of raw (individual

- level) data
from the studies ( Thompson and Sharp, 1999 )

.

2.2 Background

This section pres ents detailed descriptions and comparisons of PC and RCT study designs

, as well as detailed descriptions of the largest and most recent PC epidemiolog y studies conducted by EPA

, in support of development of new or revised water quality criteria.U.S. Environmental Protection Agency

December 2010 8 2.2.1 Comparison of PC and RCT Epidemiolog y Study Designs

Salient features of the PC and RCT designs are summarized below (Sections 3 .2.1 and 3 .2.2)

. The RCT is considered an experimental epidemiolog y study, while the PC is considered a non

experimental epidemiolog y stud y. Both are widely accepted methods of determining risks associated with the putative cause or exposure . Note that the selection of a specific study design is at the discretion of the investigator (s) and is typically made in consideration of the specific study objectives and the local conditions anticipated at the study site(s). PC and RCT study designs for the recreational water studies differ in the following important ways :

**•** Swimmer/nonswimmer assignment: t he RCT design assigns swimming and nonswimming status by randomly assigning participants to each exposure group. The PC design uses self

- reported swimming status.

**•** Swimming exposure: i n the RCT design, swimmers are asked to complete specific activities such as immersing their head a minimum number o f times and/or staying in the
water for a minimum or selected amount of time at a designated position. In the PC design, locations and swimming are assessed by interviewer and self

- report.

**•** Target population: t he EPA NEEAR PC studies target the entire beac h going population at a particular beach as their target population of interest. RCT studies recruit subjects from nearby communities. Due to ethical considerations , many RCT studies restrict their
enrollment to adults of age 18 and over.

**•** Water quality assessment and exposure assignment: t he RCT studies usually assign individual exposures by characterizing the water quality where an individual swimmer is exposed. Water quality in a PC study is usually characterized by collecting samples in a fixed layou t to assess average water quality over a given time/space dimension.

**•** Other differences: b ecause the PC design is less intensive with regard to resources and investigator involvement on a per

- subject basis , usually more subjects are enrolled over a greater number of days and environmental conditions.

2.2.1.1 Prospective Cohort Studies

A PC epidemiology study identifies a group of non

- ill people (the cohort) who may be exposed to the factor of interest (e.g., recreational water) and follows them for an appropriat e period of time to compare illness incidence (e.g., GI ill n ess) among the exposed (e.g., swimmers) and unexposed. The study can also include exposure

- response analyses if varying degrees of exposure (e.g., water quality data) are present. Information on confounders ( i.e., factors that are associated with other potential cause s of the illness or differences in the population and susceptibilities to infection and may be associated with exposure) is also collected and evaluated

, as are other sources of pote ntial bias Merits of PC studies include diversity in the pool of participants (particularly in comparison with RCT studies), exposures typical of those experienced by swimmers, and relatively large sample sizes.

T he NEEAR PC marine recreational water ep idemiology study ( Wade et al., 2010 ) provides an example of a large PC epidemiolog y study. In those studies, EPA conducted surveys on weekends and holidays between May and September at marine beaches in Rho de Island, Alabama, and Missi ssi ppi . U pon arrival

, beachgoers were provided a pamphlet describing theU.S. Environmental Protection Agency

December 2010 9 study. After reviewing the pamphlet, interviewers approached the household group or individual and offered them the opportunity to enroll in the study. On most days, all beachgoers arriving between approximately 11 :00 AM and 4 :00 PM were offered enrollment. Respondents were ineligible if they had completed the study in the previous 30 days, or if there was no adult (18 years of age or older) household mem ber present. Households provided verbal consent and completed an enrollment questionnaire consisting of demographic information, swimming exposures in the previous two weeks, and the presence of underlying health conditions, such as chronic diarrhea, asth ma, or skin conditions. As they left the beach for the day, participants completed a questionnaire to ascertain the extent and duration of their contact with water and other activities during their visit to the beach such as contact with sand and food con sumption. Ten to twelve days following the beach visit, EPA telephoned participants and asked about the occurrence of new gastrointestinal, skin, respiratory, eye, or ear symptoms ( Wade et al., 2010 )

.

As noted in the three meta

- analyses of epidemiolog y studies ( Prüss, 1998 ; Wade et al., 2003 ; Zmirou et al., 2003 ) , the majority of epidemiolog y studies of risks associated with recreation conducted to date have had PC designs. PC recreational water epidemiology studies have been
conducted in numerous locations worldwid e , such as studies conducted in the U nited States (e.g.,
Cabelli et al. , 198 2 ; U.S. EPA, 1983, 1984; Calderon et al., 1991 ; Haile et al., 1999 ; Wade et al.,
2006 ; Colford et al., 2007 ; Wade et al., 2010 )

, Canada (e.g., Seyfried et al., 1985 ; Lightfoot,
1989 ) , Europe (e.g., Ferley et al., 1989 ; Medema et al., 1995 ) , Hong Kong ( e.g., Che ung et al.,
1990 ) , New Ze a land ( McBride et al., 1998 )

, and other countries or regions

. EPA ’s current (1986) RWQC are based on results of PC studies that were conducted in the 1970s and 1980s.
T he NEEAR Study used a PC design at fresh and marine recreational beaches impacted by
POTWs over th e past decade ( Wade et al., 2006

, 2008

, 2010 )

.

2.2.1.2 Randomized C ontrol Trials

The other major epidemiology design used for recreational waters is the RCT. The RCT is an epidemiologic al experiment in which the study subjects are randomly allocated into groups to receive an experimental procedure, man n er, or interventi on. The random allocation tends to prevent section bias. For recreational water exposures, the groups are bathers and nonbathers (swimmers vs. nonswimmers 3

Kay et al., 1994 )

. The bathers are instructed as to their time in the water and
activities. Similar t o the PC stud y, bathers and non bathers must be followed for an appropriate
time to assess illness incidence and the effect of other biases and potential confounders

. E xposure

- response analyses may be conducted. Among the purported m erits of RCT study designs are that they ( 1 ) better account for the possibility that those who do not bathe choose not to do so based on factors other than water quality, ( 2 ) associate individuals and the incidence of
illness with the water quality at the time and place of bathing, and ( 3 ) a ccount for non

- water

related risk factors ( )

. The most significant l imitations of RCT studies include sample sizes typically smaller than those for comparable PC studies, exposures not necessarily typical of those experienced by beach

- go ers, and no certainty that water is actually swallowed during prescribed exposures.

3 The terms swimmers and nonswimmers and bathers and nonbathers are equivalent (the latter two are used widely in U.K., EU, and WHO studies and reports on recreational/ bathing water quality), and for convenience, they are used synonymously throughout this reportU.S. Environmental Protection Agency

December 2010 10 The EU recently adopted Directive c oncerning the m anagement of bathing w ater q uality (EP/CEU, 2006) is based on U.K. marine recreational water RCT studies ( Kay et al., 1994 ; Fleisher et al., 1996 ) and a recent RCT study of both P OTW

- and nonpoint source (NPS)

- impacted fresh recreati onal waters in Germany ( Wiedenmann et al., 2006 )

. The WHO Guidelines for Safe Recreational Water Environments ( WHO, 2003 ) are applied to both fresh
and recreational waters and are based on RCT studies conducted in the late 1980s and early
1990s at POTW

- impacted marine recreational beaches in the U.K. ( Kay et al., 1994 ; Fleisher et al., 1996 ) . The Directive and WHO Guidelines are both summarized in Appendix A )

.

2.2.2 EPA NEEAR Water Stud ies

2.2.2.1 NEEAR Epidemiology Stud y Design

The objective of the NEEAR Water Study was to develop a mathematical relationship of adverse
health effect s from swimming in sewag e polluted recreational waters to the quality of that water as measured by a n indicator of human fecal contamination , using new and faster measurement
methods

. Although several different epidemiolog y study designs were initially considered, only
the RCT a nd PC designs were deemed able to meet the specific goals of the NEEAR Water Study. As noted previously, the RCT design was used in marine recreational water studies
conducted in the U.K. ( Kay et al., 1994 ; Fleisher et al., 1996 ) , which were subsequently used to derive the numeric criteria component of the currently recommended WHO ( 2003 ) G uidelines for recreational waters ( see Appendix A ). The RCT design was recently employed by G erman investigators in a series of freshwater recreational water studies by Wiedenmann et al. ( 2006 )

, which combined with the U.K. RCT studies described above, were used to develop the current (2006) EU bathing water quality criteria. However, the PC design was determined to be better suited for EPA’s need to update recreational water quality criteria i n the United States ( p ersonal communication, Tim Wade, EPA, 2008)

.

The NEEAR study PC design ( Wade et al., 2006

, 2008

, 2 010 ) was a substantially enhanced
version of the epidemiological design employed previously by EPA researchers ( e.g., Cabelli et al., 1982 ; U.S. EPA, 1983, 1984 )

. Many of the enhancements included in this design were based on advisory group recommendations and results of pilot studies. The PC design has several advantages compared to an RCT epidemiology des ign, including: (1) the studied population of
beach

- goers represents an appropriate target population of beach

- goers, including potentially sensitive groups who use the beach, such as children, the elderly and the immunocompromised; (2) it is relatively ea sy to recruit a large cohort of swimmers and nonswimmers; and (3) the studies can be conducted over an entire swimming season, capturing day to day and seasonal
variabili ty in water quality ( Wade et al., 2006

, 2008

, 2010 )

.

A three

- part health survey (enrollment, exit interview, and follow up telephone interview) w as administered to agreeable adult (18 years or older) beach

- goers at each of the beach study sit es

. A dult s agreeing to participate in the study answered questions for other household members ( especially for children ) . At the exit interview, information was collected regarding the day’s activities, food and water consumption, water exposure (extent, time, duration, and location) and several potential confounders (e.g., other swimming events in the previous 48 hours). A telephone interview was conducted 1 0

- 12 days (the time period was based on pilot study results) after the beach visit with an adult (not necessarily the same person who was administered the exitU.S. Environmental Protection Agency

December 2010 11 interview) who answered all questions for other household members who visited the beach. The

te lephone interview included several questions about health symptoms experienced since the beach visit. Information regarding economic and physical burdens experienced as a result of each illness was also obtained (e .g., days missed from work). During inte rviews

, respondents were asked about other swimming or water

- related activities, contact with animals, or consumption of high

- risk foods between the beach visit and the interview ( Wade et al., 2006 )

.

The primary exposure factors of interest consisted of two parts, (1) contact with water and associated swimming characteristics, and (2) water quality as measured by indicator organisms ( quantitative polymerase chain re action [ q PCR ] C CE/100 mL). Additional data were collected to help interpret the results, including demographic information and information about environmental conditions (e.g., air and water temperature, rainfall, bather density, number of animals/birds, pH, turbidity). “Swimmers” were defined as those who reported immersing their body to their waist or higher because immersion to the waist showed a pattern of risk similar to
head immersion ( Wade et al., 2006 )

. Nonswimmers were defined as those who reported no contact with water while those entering the water not up to their waist were classified as
“waders.” Participants were also asked whether they immersed thei r heads, though sub

- analyses of the participants immersing their heads and not immersing their heads showed similar risks

. The lack of difference in risks for those who submerged their heads and those who did not is important because it raises the possibi lity that head immersion m ight not be the important

exposure and allows assessment of the different exposures undertaken in PC and RCT studies.

GI illness was defined as any of the following: (a) diarrhea (3 or more loose stools in a 24

- hour period) ; (b) vomiting, nausea and stomachache ; or (c) nausea or stomachache. These criteria were selected as the benchmark health effect because GI illness is the most frequently reported health outcome associated with recreational water exposure and is also the outco me most frequently associated with (adverse) water quality ( Prüss, 1998 ; Zmirou et al., 2003 ) . However, several other health effects that may be related to recreational water exposure were also considered, including: (1) upper respiratory illness (URI), defined as any two of sore throat, cough, runny nose, cold, fever; (2) rash (rash or itchy skin); (3) eye ailment (defined as either eye infection or watery eye); and (4) earache (earache, ear infection, or runny ears). Consistent with other recreational water epidemiology studies ( Colford et al., 2007 ) , URI and GI illness were not restricted to persons with fever, since infections can produce these illnesses without fever and
because EPA researchers were also concerned about the acc uracy of self

- reported low

- grade
fever ( Wade et al., 2008 )

.

2.2.2.2 NEEAR Freshwater Results

Wade et al ( 2006

, 2008 ) summarize the results of epidemiologic studie s of beach

- goers conducted during three summer seasons (2002 to 2004), including one pilot study (2002) and
four full

- scale studies conducted at the following freshwater (Great Lakes) beaches:

**•** West Beach, Indiana Dunes National Lakeshore, Porter, Indiana ( Lake Michigan);

**•** Huntington Beach, Bay Village, Ohio (Lake Erie);

**•** Silver Beach, St. Joseph, Michigan (Lake Michigan); and

**•** Washington Park Beach, Michigan City, Indiana (Lake Michigan).U.S. Environmental Protection Agency

December 2010 12 These beaches were selected because they fulfilled the following spec ific criteria: (1) officially designated recreational area located near a large population center; (2) generally meeting the state or local water quality standards; (3) potential for contamination by a human source of pollution (i.e., POTW

- impacted) ; (4) l arge attendance (e.g., 300

- 400 swimmers/day) with a broad range of ages; and (5) swimming season of at least 90 days ( Haugland et al., 2005 )

. T hree journal articles have been published based on the NEEAR freshwater s tudies :

**•** Haugland et al. ( 2005 ) compare d q PCR and traditional culture

- based Enterococcus measurements in freshwater at two (of four total) Great Lakes recreational beaches for samples taken in the fir st year of the NEEAR Water Study;

**•** Wade et al. ( 2006 ) describes the associations of swimming

- associated GI illness and water quality measures ( q PCR test results of E nterococcus and Bacteroides , another bacterial fecal contamination indicator) taken at the same two Great Lakes’ beaches ; and

**•** Wade et al. ( 2008 ) expand ed on the results of Wade et al. ( 2006 ) , adding analy ses of the remaining two freshwater Great Lakes beaches, an assessment of nonenteric illnesses (upper respiratory illness [URI], rash, eye irritations, and earaches), and separate analyses by age.
The freshwater water studies included a total of 33 study d ays at the 2 beaches

— 1 on Lake Michigan and 1 on Lake Erie . A total of 5796 household interview attempts were conducted and
the household

- level response to interview attempts was 56%. This yielded data for 3221 households, and 5717 individuals. The numb er of households and individuals were roughly evenly

- distributed between the Lake Erie and Lake Michigan beaches

.

As described above, w ater samples were analyzed for the traditional fecal indicator bacteria,
Enterococcus 4

Wade et al., 2008 and the alternative fecal indicat or Bacteroid al es . Several commercially

- available rapid test methods or validated or experimental research method protocols were considered and/or evaluated for use in the NEEAR Water Study, but only the qPCR method was included in
the NEEAR study . Of the two indicators tested with qPCR

, Bacteroides densities w ere frequently below detectable limits, making results difficult to interpret. As a result, the NEEAR study focus es on the relationship between the qPCR Enterococcus assay and health effects (primar ily GI illness). However, in addition to qPCR , EPA Method 1600 for culturable bacteria (measured as CFU per 100 mL) was included in the study as a reference method for
Enterococcus (see Haugland et al., 2005) and because it is currently recommended by the EPA for recreational freshwater monitoring ( )

.

The water sa mpling plan was designed as an “ ecological ” exposure for the swimmers during that day and thus, was intended provide a method of estimating risks that could be used to develop water quality guidelines. For all beaches, w ater samples were collected three times a day (8:00 AM, 11:00 AM, and 3:00 PM) on weekends and holiday s

. For each sample event, t wo water samples were collected along each of three transects perpendicular to the beach shorelines, one
from waist

- deep water (1 m deep) and one in shin

- deep water (0.3 m deep). Results are reported
in qPCR calibrator cell equivalents ( qPCR C CE) per 100 mL

. EPA researchers focused the

4 The terms fecal streptococci, enterococci, intestinal enterococci, and Enterococcus are often used to refer to essentially the same environmental and fecal spe cies of bacteria (see WHO, 2003 and NRC, 2004 for further information).U.S. Environmental Protection Agency

December 2010 13 sample analyses primarily on two summary measures, (1) the daily average of all samples, and (2) the average of the 8:00 AM samples

. EPA researchers created two variables to represent exposure to indicator organisms, (1) an average of all measures collected by day, and (2) an average of measures specific to day and reported swimming location

. Th e base 10 log arithm (log 10 ) of the geometric mean was used for averaging results

. The daily average represented average water quality at a beach on a particular day while the 8:00 AM average was used to determine if morning water quality was predictive of illness among swimmers exposed later that day

— an important consideration for assessing the utility of a rapid method such as qPCR for recreational water quality monitoring. Analyses using depth

- specific averages were also
conducted.

Generalized linear

- r egression models were used to determine the strength and the significance of the relationship between water quality and health effects. Logistic regression models were used

to determine the strength of the association between the qPCR C CE measures and inc idence of illness among swimmers

. The cohort sample size was very large (>21,000 interviews), allowing thorough analyses of sensitive subpopulations ( such as children and the elderly ) and adults of various ages ( Wade et al., 2008 )

.

The NEEAR Study results ( Wade et al., 2006

, 2008 ) demonstrate that Enterococcus qPCR C CE was associated with GI illnesses at freshwater Great Lake Beaches impacted by point sou rces of sewage based on a definition of swimming that included body immersion. Specifically, higher
Enterococcus qPCR C CEs were positively and significantly associated with swimming

associated GI illness; the strength of association between GI illness and qPCR C CEs was greater among children aged 10 years and below. In contrast, no statistically valid evidence of increased GI illness among those aged 55 and older was observed, al though EPA’s ability to make valid conclusions among this potentially sensiti ve population was limited because they swam infrequently and reported the lowest incidence of illness

. The association between the 8:00 AM
Enterococcus qPCR C CE average and GI illness was nearly identical to association with the daily average qPCR C CE

. I n addition, the association between Enterococcus and GI illness strengthened as time spent swimming in the water increased

. N onenteric illnesses were not consistently associated with level of Enterococcus qPCR C CEs ; however, rash and earache
occurred more frequently among swimmers than nonswimmers

. Notably, Enterococcus qPCR
C CE exposure was more strongly associated with GI illness than culturable Enterococcus measured by membrane filtration. As with the previous analysis ( Wade et al., 2006 ) , a more stringent definition of swimming with head immersion did not substantially alter the results.

Collectively, the freshwater NEEAR results support a quantifiable relatio nship between the density of fecal indicator s in the water at the various beaches investigated and the human health
risks associated with the recreational use of water ( Wade et al., 2006 ; 2008 )

.

2.2.2.3 NEEAR Marine Water Results

EPA conducted studies at three marine beaches affected by treated sewage discharge from nearby POTW effluent. EPA studied Edgewater Beach in Biloxi, Mississippi in 2005, and Goddard Beach in West Warwick, Rhode Island and Fairhope Municipal Beach in Fairhope,
Alabama in 2007. Each beach site was located within 7 miles or less of a treated sewage discharge outfall from facilities that served po pulations of at least 15,000. Based on historicalU.S. Environmental Protection Agency

December 2010 14 records, each beach site showed variability in water quality, but were generally in compliance with local and federal water quality guidelines.

Data collection procedures for the health survey were simila r to the freshwater studies as
summarized above ( Wade et al., 2006

, 2008 )

. The health endpoints considered inclu ded GI illness (as defined above) ; u pper respiratory illness (any two of sore throat, cough, runny nose, cold, or fever) ; r ash ; e ye irritation ; and earache.

Protocols for water sample collection were also as described for the freshwater studies. Water samples were tested for the genus Enterococcus ( Haugland et al., 2005 ) and the p hylum
Bacteroidetes ( Siefring et al., 2008 ) by qPCR, qPCR subgroups of Bacteroides ( Converse et al.,
2009 ) and Clostridium spp. ( Rinttila et al., 2004 ) , male specific coliphage ( Love and Sobsey,
2007 ) , and Enterococcus using EPA method 1600 ( U.S. EPA, 2000 )

. Samples for EPA Method 1600 and qPCR analysis were filtered within 6 hours of collection. The filters were held at

- 20 ° C and shipped overnight to EMSL Analytical (Westmount , New Jersey ) on dry ice where DNA
extraction an d qPCR analyses for Enterococcus

, Bacteroidales

, and fecal Bacteroides were conducted. Frozen DNA extracts were sent from EMSL Analytical to EPA in Cincinnati , Ohio where qPCR analysis was conducted for Clostridium . Details of the microbiological analyse s and quantitation of fecal indicator bacteria are described by Wade et al. ( 2010 )

.

Swimming exposure was defined as immersion to the waist or higher, consistent with the
freshwater studies. Nonswimmers were those who reported no water contact. Water quality data were reduced in the same manner as described above for the freshwater studies (daily average,
8 :00 AM average). The researchers used logistic regression models to quantify and describe the
rel ationship between estimates of fecal indicator organisms and the risk of illness among swimmers. The predictor of interest was the estimate of fecal indicator organisms. Factor variables representing “beach ” were included in all models to control for diffe rences in baseline
illness. Covariates which could plausibly a ff ect the relationship between water quality and illness, or those which were associated with health outcomes were considered for inclusion in regression models. These included age, sex, race, contact with animals, other swimming in the

p receding 1

- week, contact with other persons with diarrhea, distance traveled to the beach, frequency of visits to the beach under study, any other chronic illnesses (GI illness , skin, asthma), digging in sand, u se of insect repellent and sunscreen, and consumption of raw or
undercooked meat. E nvironmental measures included were precipitation since 3:00 PM the previous day ; bather density ; presence of dogs, birds

, and other animals on the beach ; air and water temp erature ; wind speed ; tide stage ; wave height ; cloud cover ; wind direction ; and boat density

. Air, water temperature, wave height, windspeed and precipitation were included as
covariates in the regression models.

The marine water studies included a total of 70 study days at the three beaches. A total of 9069
beach

- goers were offered enrollment. Of these, 1715 (19%) refused to participate or were ineligible. Of those who agreed to participate, 6350 (78%) completed the telephone interview and were eligibl e for analysis.

EPA collected and tested a total of 1,242 water samples on study days . Fairhope Beach had the highest geometric mean Enterococcus CFU (21 CFU /100 m L ) and Goddard Beach the lowest (4U.S. Environmental Protection Agency

December 2010 15 CFU /100 m L ). Individual samples of Enterococcus CFU r anged from below detection to 3000
CFU /100 m L . Overall, 142 samples (11.5%) exceeded 104 CFU /100 m L , the EPA
recommended single sample maximum for marine beaches ( U.S. EPA, 1986 )

. Individual samples most frequently exceeded the single sample maximum at Fairhope Beach (99 samples, 23%), followed by Edgewater Beach (32, 8.5%) and Goddard Beach (11 samples, 3%).
Enterococcus CCE estimated by qPCR were higher than Enterococcus CFU

. For all indicators measured by qPCR, estimates of CCE **∆ ∆**  were higher than CCE **∆**

. Bacteroidales CCE were highest among the indicators. Similar comparisons are not reported for the NEEAR freshwater
studies.

Fifty

- six percent (100/222) of samples at Fairhope Beach and 65% (203/425) of samples at
Goddard Beach were positive for F+ coliphage by the 24 hour SPOT test. Fewer samples were positive for F+ coliphage by the CLAT assay. At Fairhope Beach, 4% (8/228) and 14% (14/224) of samples indicated the presence of F+ RNA and F+ DNA coliphage, respectively. At Goddard Beach, 8% (31/425) and 9% (37/423) of samples tested indicated the presence of F+ RNA and F+ DNA coliphage, respectively.

The risks of both GI illness and diarrhea were signifi cantly associated with exposure to

Enterococcus and Bacteroidales C CE **∆ ∆**  and CCE **∆**

. A log10 increase in the daily average of
Enterococcus and Bacteroidales CCE was associated with an approximate doubling or greater in
the risk of GI illness . Morning estimates of Bacteroidales and Enterococcus CCE (8:00 and/or
11:00 AM) wer e also signi fi cantly associated with both GI illness and diarrhea. Associations
between GI illness and fecal Bacteroidales were generally positive but not statistically signi fi cant. Clostridium CCE **∆ ∆**  show ed a strong statistically signifi cant association with GI illness but the relationship with Clostridium CCE **∆** was weaker. Enterococcus CFU were also positively associated with GI illness, but the associations were not statistically signi fi cant. None of the associations with non

- enteric illnesses were co nsistently positive. Children 10 years of age and under were examined separately but there was no evidence of an increased susceptibility to illness with exposure to fecal indicator bacteria.

Associations between GI illness and qPCR CCE appeared to stre ngthen with more intense or prolonged water exposure, although results were based on few subjects. There was no evidence of systematic di ff erences in the relationships between GI illness and diarrhea and Enterococcus

or Bacteroidales CCE exposure across t he three beaches.

The odds of GI illness was higher among swimmers compared to non swimmers on days when F+ DNA or F+ RNA coliphage was detected by the CLAT assay or F+ coliphage was detected by the SPOT assay. For all categories of illness, there were no differences in the odds of illness among swimmers on days when Enterococcus exceeded 35 CFU/100m L compared to days when
Enterococcus was below 35 CFU/100 m L

.

These marine water study results are consistent with but even stronger than previous findings at the freshwater beaches and provide further evidence that fecal indicators estimated by qPCR are a sensitive marker of poor water quality and subsequent health effects among swimmers at beach sites impacted by treated sewage discharge.U.S. Environmental Protection Agency

December 2010 16 

### 3. S UMMARY OF 

### RCT W AT ER 

### E PIDEMIOLOGY 

### S TUDIES

3.1 Marine RCT Studies Conducted d uring the 1980s and 1990s in the U.K.

Kay et al. ( 1994 ) and Fleisher et al. ( 1996 ) report a series of marine RCT studies conducted at
four different U.K. domestic sewage

- impacted, coastal recreational beaches in the late 1980s and early 1990s. The former study reports on gastroenteritis (GI illness) associated swimming while the latter study reports re sults for nonenteric health effects.

Kay et al. ( 1994 ) suggested that epidemiology studies (prior to 1994) “suffered from three methodological flaws: (1) those who bathed and those who did not selected themselves and may have differed in respect t o factors other than the quality of the bathing water to which they were exposed, (2) the microbiological quality of water was not assigned to each bather at the time and place of bathing, and (3) non

- water

- related risk factors were not measured or adequat ely
controlled for.” Th e authors indicate that these problems were overcome by use of a RCT epidemiolog y study design, the use of which was also suggested by the WHO. In a critical assessment of these three perceived flaws, we note that the selection of bathers in a RCT study may introduce bias and that self

- selection for swimming provides exposures that may be more typical of those undertaken by bathers than the prescribed exposures employed in RCT studies.
We also note that NEEAR PC studies accounted f or non

- water

- related risk factors and that PC studies, in general, can account for non

- water

- related risk factors. At the time of the study by Kay et al. ( 1994 ) , the largest U

. S

. EPA epidemiolog y studies of recreational exposures ( U.S. EPA, 1983, 1984 ) associated season

- averaged indicator densities with individual swimmers. As described above, in the NEEAR studies swimmer water quality is taken as the geometric mean of
the indicator densities taken at multiple locations on a beach at multiple times during a day. The second concern raised by Kay et al. (1994) appears far more important for the earlier PC studies
than more recent studies.

In brief, 548 adult volunteers in urban centers were recrui ted within several weeks before each of
the studies were conducted from 1988 to 1992 at U.K. marine beaches . B ecause children and unhealthy persons were excluded from the study

, the volunteers may not represent the actual population at a beach as well as did participants in earlier PC studies ( U.S. EPA, 1983, 1984 )

. Although the studied beaches were impacted by domestic sewage (POTW effluent), they passed the existing EU “imperative” bacteriological standards ( CEC , 1976 ) of 10,000 CFU /100 mL and
2000 CFU /100 mL for total and fecal coliforms , respectively

, for bathing waters during the

prev ious summer. All volunteers reported to an initial interview and medical examination 1

- 3 days before reporting to a beach . At the beach, volunteers were randomly assigned into the bather or nonbather group to reduce the potential “self

- selection” bias. Bathers were lead by a supervisor to a section of beach where they bathed for a minimum period of 10 minutes and were required to immerse their heads at least 3 times during that period

. 5

5 Note that Kay et al. (1994) states that participants had to immerse their heads at least three times while Fleisher et al. (1996) states that participants had to immerse their hea ds exactly three times. The water in the recreational

area near to where the participants b athed was sampled every 30 minutes during the swimming period at 20 m intervals, allowing for a unique water quality to be assigned to each bather . This sampling scheme was adopted to reduce “misclassification” bias. However, the actual volume of
water i ngested by the participants is not known nor is it known if water was actually swallowedU.S. Environmental Protection Agency

December 2010 17 as this question does not appear to have been asked, though participants were asked to describe
their water contact

.

A total of four candidate bacterial fecal indicat ors (total and fecal coliforms, fecal streptococci [enterococci], and Pseudomonas aeruginosa ) were sampled at all four sites while total staphylococci was sampled at three study sites. All samples were collected at three depths

— surf; mid (1 m depth, 30 cm below surface); and chest (1.3 to 1.4 m depth, 30 cm below surface)

. Bacterial i ndicators in the samples were enumerated by standard (culture

- based) methods. The chest depth was the location at which head immersion took place. All volunteers were
interv iewed on the day of exposure, 1 week post

- exposure, and completed a follow

- up postal questionnaire 3 weeks post

- exposure. These questionnaires collected data on an extensive range of potential confounding factors (e.g., consumption of seafood, raw milk, c onsumption of laxatives) that were considered in subsequent analyses.

Gastroenteritis was defined as any case of vomiting or diarrhea (three or more loose bowel movements per day), plus any case of either indigestion or nausea accompanied by fever

rep orted at either the 1 or 3 week post

- exposure interview.

The U.K. studies found GI illness rates in the bather group were predicted by ente rococci measured at chest depth . Only enterococci, me asured at chest depth, showed an indicator

- illness
relationshi p for both GI illness ( Kay et al., 1994 ) and acute febrile respiratory illness ( AFRI ) ( Fleisher et al., 1996 ) in marine waters. Bathers had a statistically si gnificant increase in the
occurrence of AFRI at levels at or above 60 CFU enterococci/100 mL. A significant relation ship
with GI illness was identified when enterococci densities exceeded approximately 32 CFU /100
mL.

3.2 Freshwater RCT Stud ies Conducted in German y

A series of RCT epidemiolog y studies were conducted in Germany to establish the association of illness with recreational use of designated fresh recreational waters (four lakes and one river) ( Wiedenmann et al., 2006 )

. At the study outset, a ll study sites had complied with the European
standards ( CEC , 1976 ) for total and fecal coliforms for at least the three previous bathing
seasons. Sources of fecal contamination at the study sites include d treated and untreated municipal sewage, agricultural runoff (non

- point source pollu tion), and fecal contamination from
water fowl.

Briefly, local volunteers, including children 4 years or older 6 Kay et al., 1994 were randomized into bathers and nonbathers, as in the U.K. studies described above ( ; Fleisher et al., 1996 ) . This RCT was the first to study a cohort that includes children and teenagers, who usually comprise a considerable percentage of the visitors at public bathing sites. Two

- to

- three days before exposure, the participants were interviewed in person, and all participants underwent a short medical examination by physicians. One week following exposure, all participants were
intervi ewed again in person and underwent a medical inspection of the throat, eyes, and ears. Three weeks following exposure, the participants received a last questionnaire by mail.

6 Children less than 4 years old were not recruited as they were considered to be potential sources of direct fecal
contamination.U.S. Environmental Protection Agency

December 2010 18 Bathers were exposed for exactly 10 minutes in 1 of 4 roped

- off zones (each d ivided into swimmer zones and shallow nonswimmer [wader] areas) and bathers had to immerse their head
at least 3 times

. 7 Although bathers were asked to stay inside the designated swimming zones with deeper water, bathers were not excluded if they remained in the nonswimmer (shallower) zones provided they immersed their head at least 3 times and stayed in the water for exactly 10
minutes . The actual ingestion of water was not required or quantified , though swimmers were asked if they had accidently swallow ed water . For each minute of trial duration (between 220 and 240 minutes, depending on the number of participants per site), microbial water densities

were estimated by arithmetic interpolation. The microbial densities for each of the 10 minutes of

water contact were assigned to each of the bathers in their individual exposure area, including nonswimmer and/or the swimmer zones, depending on where the participant stay ed

.

Exposure was defined two different ways. The first definition was “10 minutes bat hing with at least three head immersions,” which is equivalent to the instructions that the participants had received from the study organizers

. For this definition

, the arithmetic mean of the 10 densities
that had been estimated and assigned was used as the mean exposure for every individual bather.
The second , (referred to as “single head immersion” ) was used to assess the influence of the
number of head immersions. T he minute

- specific densities during which the head was immersed were multiplied by num ber of head immersions (nominally 3) and added . These calculations
resulted in a theoretical equivalent of a single head immersion at that indicator density

.

The researchers analyzed the water samples for the following six microorganisms : E

. coli

, intes tinal enterococci (enterococci), Clostridium perfringens , somatic coliphages, aeromonads, and pyocyanine

- positive Pseudomonas aeruginosa

. As in the U.K. RCT studies, sufficient water samples (every 20 minutes from the center of all swimmer and nonswimmer zones/areas) were collected to assign individual water quality exposure data to each bather. Water samples were
taken in both the swimmer and nonswimmer zones.

The researchers analyzed data for the following diseases as outcome variables: AFRI, common

co ld, ear inflammation, eye inflammation, skin infections or cutireactions, and urinary tract infections. Three definitions of gastroenteritis (GI illness) were also assessed : (1) “GE_UK” according to Kay et al. (1994) (diarrhea AND three or more bowel move ments per day) OR vomiting OR (nausea AND fever) OR (indigestion AND fever); (2) “GE_UK

- wf” according to their study (diarrhea OR vomiting OR [nausea AND fever] OR [indigestion AND fever]); and ( 3 ) definition “GE_NL

- 2” (diarrhea OR nausea OR vomiting OR st omach pains). Results were primarily based on health outcomes reported after 1 week because virtually all episodes of bathing

- associated gastroenteritis occurred within an incubation period of 1 week and symptoms were less likely to be remembered for a ti me period of 3 weeks than for a period of 1 week.

T hese researchers are of the opinion that recreational water standards should be based on rates of compliance with no

- observed

- adverse

- effect levels (NOAELs) rather than attributable risks (the primary met rics used in the NEEAR studies) because attributable risks depend mainly on the unpredictable susceptibility of the cohorts , though attributable risks are also presented ( Wiedenmann et al., 2006 )

. To this point, they stated the following :

7 Compared to at least 10 minutes and at least 3 head immersions in the U.K. RCT studies.U.S. Environmental Protection Agency

December 2010 19 ...the assumption that the risk of acquiring gastrointestinal illness from exposure to certain concentrations of fecal indicator organisms is predictable...may be true only for a defined population under the condition of a constant degree of endemicity of always the same kinds of pathogens. It would not, however, be a sufficient basis for the derivation of generally applicable microbiological standards for fecal indicator organis ms in water.

It would be impossible to set imperative values f or German freshwater bathing sites
based on the results of the present study

... guide values for compliance at 95th percentile
levels of monitoring results for intestinal enterococci would range from approximately
200 to approximately 4,000/100 mL depending on nothing else but different cohort susceptibilities in the German and the U.K. trials and on different definitions of gastroenteritis.

Based on this point of view and their results, they ind icate that “ Current [2003] WHO recommendations and the concept used to derive bathing water standards in the European Union should be reconsidered in light of the results and conclusions from this
randomized trial

. ”

In all, indicator

- illness effects with NOAELs were demonstrated for all three definitions of GI
illness and four fecal indicator organisms. Calculated NOAELs for nonenteric diseases (including AFRI) were either nonexistent or nondetectable. Based on the generated NOAELs for GI illness, the a uthors recommended the following guideline values for fresh recreational water quality : 100 CFU /100 mL E. coli , 25 CFU /100 mL ( intestinal) enterococci, 10 somatic coliphages/100 mL, or 10 Clostridium perfringens CFU /100 mL. The NOAELs depended mainly on t he definition of exposure, with significantly higher values for exposure definition “single head immersion,” as well as on the microbiological parameter

. They did not, however, depend on the definition of GI illness. The authors noted that the values for enterococci and E. coli are in accordance with current EPA ( 1986 ) recreational water quality criteria as assessed and (for the most part) supported by the Wade et al. ( 2003 ) meta

- analysis. The results of these RCTs in German freshwaters are also in accordance with the ratio of roughly 1:4 between the guideline
values for enterococci density to E. coli density in fresh waters curren tly required for Great Lake states and coastal states ( U.S. EPA, 1986, 2004). Wiedenmann et al. ( 2006 ) note that the ratios
between enterococci and E. coli in the EU Directive ( see Appendix A ) are much less, being closer to 1:2.5, thus implying that the recently adopted EU criteria for E. coli could be more stringent than is necessary.

3.3 Epibathe RCT and Related Studies

Epibathe was fun ded under EU Framework Programme 6 to produce “ science support for policy .” It was commenced in December 2005 and completed in March 2009. The imperative for this research effort was the relative paucity of EU data describing the health effects of bathing in EU freshwaters and Mediterranean marine waters. Both aquatic environments provide important recreational resources throughout the EU ( EC

- Epibathe, 2009b)

.

The three primary objectives of Epibathe were as follows :U.S. Environmental Protection Agency

December 2010 20 1. To add value to existing epidemiological (RCT) data sets through a new analysis that integrate s existing data and clearly define the principal data gaps that require further epidemiological investigation.
2. To fill these gaps by designing and implementing accordingly targeted epidemiological investigations, using an agreed to and harmonized epidemiological protocol (i.e., RCT) at key EC waters. 3. Using the information derived from these epidemiolog y studies, combined where appropriate with existing data, to facilitate a quantitative risk assessment as outlined in
WHO ( 2003 )

. Epibathe is comprised of a series of marine and fresh recreational water epidemiology studies conducted in 2006 and 2007 in Spain and H ungary, respectively. Four riverine recreational sites were assessed in Hungary and four coastal (Mediterranean) sites were assessed in Spain.

The study design and methodology/ protocol ( EC

- Epibathe, 2009a,b ) are d erive d from the U.K.
marine water trials ( Kay et al., 1994 ; Fleisher et al., 1996 ) that formed the basis of the 2003
WHO Guideline values

. Enterococci and E. coli were me asured using membrane filtration ( CFU /100 mL) and microtitre (most probable number [MPN]/100 mL) methods

, while somatic coliphage were measured by a pour

- plate method (plaque forming units [pfu]/100 mL). As in the German RCT study ( Wiedenmann et al., 2006 )

, 2

- 3 days before exposure the participants completed a 4

- part questionnaire in person and underwent a brief medical examination by physicians. The questionn aire concerned their overall health status, the presence of a variety of symptoms (e.g., rash, earache, vomiting, diarrhea) and potential confounders, such as contact with farm or companion animals and consumption of seafood after recreational water exposu re. Again, EPA’s NEEAR studies and prior RCT studies ( e.g., Kay et al., 1994 ) collected similar data on potential confounders. The participants completed the questionnaire in person at the beach. One week following exposure, all participants again com pleted the questionnaire and underwent a medical inspection of the throat, eyes, and ears. Three weeks following exposure, the participants received a last questionnaire by mail. The same definition of GI illness and AFRI as used in Kay et al. ( 1994 ) (“GE_UK” in Wiedenmann et al., 2006) were used.

The new information generated by the Epibathe research ( i.e.

, on EU fresh and Mediterranean

waters ) has been analyzed separately and also combined with existing data acquired using the
same research met hods in Germany and the United Kingdom. This meta

- analysis of the larger data set includes data on over 7,000 volunteers who participated in these RCT studies between
1989 and 2007.

Water quality at each field site, was measured in each of 6 marked swim zones at 20 minute
intervals. Bathers were asked to remain in the water for a minimum of 10 minutes and the water quality experienced at the time and place of bathing was attributed to each bather. This provided a range of “ exposures ” ( i.e.

, over time an d space, both between sites and within each 3

- hour exposure period )

.

Water quality encountered during the new Hungarian and Spanish investigations was relatively

“ clean ” as would be expected from the choice of sites which were in compliance with the Imp erative standard of the EU bathing Water Directive ( CEC , 1976 ) . However, elevations in symptom reporting in the bather group(s ), i.e. when compared to the nonbather group(s), wereU.S. Environmental Protection Agency

December 2010 21 observed. It was also notable that the background rates of most symptoms, principally GI symptoms, was lower in the Epibathe studies than in previous RCT studies in the U

. K

. and Germany. These temporal differences could be due to improvements in effluent treatment and the general health status of the European population over the 20

- year period spanned by these investigations

Five separate analyses were completed to examine the following relationships a nd associations

, ( 1) risk of gastroenteritis from recreational bathing water based on an analysis of Epibathe data from Hungary and Spain; ( 2) risk of gastroenteritis from recreational bathing water based on a

meta

- analysis of randomized exposure trials i n four European countries; ( 3) risk of gastroenteritis in European fresh bathing waters using E. coli as indicator organism; ( 4) risks of

non

- enteric diseases from European recreational bathing water; and ( 5) the effects of non

- water related risk factors o n gastroenteritis.

For EU marine waters (Spain and the U

. K . RCT studies ), the clearest trend in increasing risk of illness with decreasing water quality was evident using enterococci as indicator of water quality. For freshwaters (German and Hungary), th e clearest indicator

- illness relationship between GI symptoms and water quality was seen with E. coli . Both analyses (fresh and marine waters) suggest elevations in GI illness in the bather cohorts. However, results from freshwater studies do not display a consistent incremental elevation in odds ratio as the exposure increase. The
evidence

- base created by this analysis suggests that exposure to marine recreational waters presents approximately twice the risk associated w ith fresh waters containing simila r fecal indicator organism densities.

As noted previously, t he original risk assessment that underpinned the 2003 WHO Guidelines
was derived from the U

. K

. RCT studies. This assumed a simple linear relationship between
enterococci density in marine water s and rates of gastroenteritis in bathers. However, the assumption of a single linear relationship becomes questionable where several individual studies are combined spanning different regions and time periods. This may result in the rates of illness
in the non bather groups exhibiting variability between sites and times, which is normal for gastroenteritis in the community. It was for this reason that a “ meta

- analysis ” approach, was used. Using a stochastic modeling approach ( Wyer et al., 1999 ; Kay et al., 2004 ) , the risk of gastroenteritis attributable to bathing in EU marine waters (i.e.

, using the U

. K

. and Spani sh data sets combined) which have a 95 th percentile water quality of 200 enterococci per 100 mL was calculated at 4.5%. This value is comparable with an attributable illness probability of 5%, calculated using the original WHO analysis which underpins the WHO “ Le vel B ” and EU

“ Good ” criteria for this parameter

. Thus, the Epibathe empirical field studies and combined data analysis do not suggest that a change in the water quality standards suggested by either the WHO
or the EU (see Appendix A ) are in need of revision.

3.4 Miami, Florida RCT Study

The objectives of this study were to evaluate the risk to humans from exposure to subtropical
recreational marine waters with no known point source of fecal contamination , and the possible relationship between microb e densities and reported symptoms in human subjects with random

exposure assignment and intensive individual microbial monitoring in this environment ( FleisherU.S. Environmental Protection Agency

December 2010 22 et al., 2010 ; Sinigalliano et al., 2010 )

. This study was the first RCT in the U nited S tates , and the
first RCT in ( sub ) tropical non

- point source recreational marine waters globally. The data

colle ction activities were conducted over 15 individual study days beginning in December 2007
and concluding in June 2008.

Local adult residents (>18 years of age) who reported regularly bathing in recreational waters were recruited to participate. Participant s were screened for current illness and symptoms, possible alternative risk factors for the study illnesses, and a health history. On the day of their beach exposure, participants were again interviewed about any current illnesses, symptoms, food consumpti on, and beach exposure since the baseline recruitment interview.

The study site had been well characterized by the investigators previously in terms of the indicator organisms in the water and sediments as being a non

- point source subtropical beach
with periodic use by people, dogs and birds as well as seasonal heavy rains ( Fleming et al., 2008 ; Solo

- Gabriele et al., 2008 )

. Study subjects were then randomly assi gned to either the (exposed)
bath er group or the (unexposed) non bather group.

Bathers were required to spend 15 min utes in knee

- deep water and to immerse their head 3 times completely under water. Note that both the depth of exposure and time of exposure differ from
those used in the (non

- United States) RCT studies described above. Each subject collected their own environmental water sample from the demarcated bathing lanes. All samples were collected in the morning between 8 :00 AM and 12 :00 PM on each sampling day concomitant with the epidemiolog y study. Water samples were collected in knee

- deep water by each study participant using 5 L sterilized plastic containers; sampling points from the shoreline ranged from 10 to 40 m depending on tidal stage cor responding with the knee height. Samples collected by each study participant were assayed for enterococci and S. aureus by membrane filtration , for additional enterococci analyses (by chromogenic substrate and two qPCR methods), for Bacteroidales analyses ( two human markers and one dog marker by qPCR), and for one seagull marker analysis ( Catellicoccus marimammalium ) by qPCR

.

Participa nts randomized to be in the non bather group were restricted to an area distant from water and sand exposure. Out of 1341 adult regular bathers ran domly assigned to bather or

non bather groups, 1303 (i.e.

, 97% follow

- up) individuals completed the subsequent follow

- up telephone interviews for reported illness after 7 days following the beach exposure.

“Gastrointestinal illness ” was defined as the report of the following symptoms: all cases of vomiting or diarrhea, or all reported cases of indigestion or nausea accompanied by a fever

. “Diarrhea” was defined as having 3 or more runny stools within a 24 h our period . “Acute febril e respiratory illness” was defined as report of at least one of each of the symptoms listed in each of the following 3 categories: (1) fever; (2) headache and/or body

- aches and/or unusual fatigue
and/or loss of appetite; and, (3) sore throat and/or runny n ose and/or dry or productive cough

. “Skin illness” was defined as report of at least one of the following symptoms: (1) skin rash; (2) skin ulcer/sore; or (3) itching/irritation on the follow

- up questionnaire.

Bathers reported more GI illness, respirator y illness, a nd skin illness relative to non bathers. After controlling for non

- water

- related risk factors/possible confounders for each of theseU.S. Environmental Protection Agency

December 2010 23 illnesses bathers were 1.79 times more likely to report GI illness re lative to non bathers; bathers
were 4.46 ti mes more likely to report AFRI ; and bathers were 5.31 times more likely to report
skin illness. No differences between bathers and nonbathers for ear and eye illnesses were
observed.

With the exception of the positive association between enterococci meas ured by membrane
filtration a nd the report of skin illness , there were no significant dose

- response relationships between any other indicator organisms and the report of human illness.

In summary, this study was the first RCT study of bathers with individ ual exposure assessment
in ( sub ) tropical recreational marine waters with no known point source of domestic sewage. The results demonstrated bathers to be at increased risk of reported GI illness

, AFRI, and skin
illnesses relative to nonbathers. In additi on, there was evidence for a n indicator

- illness relationship between bather exposure to increasing levels of enterococci and an increased risk of reporting skin illness. Perhaps t he most unique feature of this study is that it is the only epidemiology stu dy in which the association of microbial water contamination and subsequent
illnesses was established using water quality samples collected by bathers at the same time they were being “ exposed .” T hus, the basic unit of measurement was the individual bathe r rather than the average rates of illness among many bathers on different study days.

Finally, the authors indicate that “in a regulatory context, the results can be transformed into the probability of illness, attributable risk and other measures of r isk, thus avoiding the use of rates as the basic unit of measurement published in previous prospective cohort designs, which inevitably introduce misclassification of exposure. Thus, the methods used in this study will supply the regulator with more accur ate estimates of risk upon which to build criteria in the
future.”

3.5 Planned Tampa Bay , Florida RCT Study

There is a planned RCT study of both freshwater (lake) and coastal recreational waters in and near Tampa Bay, Florida. Based on numerous corresponden ces to the Principal Investigator and other individuals who are knowledgeable about Florida recreational waters , the study appears to be on an extended hold pending additional funding.

3.6 Summary Table of Reviewed Recreational Water Quality Studies

Table 2 summarizes the NEEAR Water Study ( Wade et al., 2006

, 2008

, 2010 ) ; the 2003 WHO Guidelines; the EU Directive (EP/CEU, 2006); and the Epibathe and Miami RCT studies.U.S. Environmental Protection Agency

Decembe r 2010 24 Table 2 . Summary of Select Recreational Water Quality Approaches, Reports, and Studies

Design/Iss u e EU **Directive** WHO Guidelines EPA NEEAR German RCT Epibathe RCT Florida RCT Study or studies conducted in fresh (FW) or marine (MW) recreational
waters FW/MW MW FW/ MW FW FW/MW MW

Epidemiological design on which guidelines/ standards are based RCT RCT PC RCT RCT RCT

Provides numeric values of indicator densities for FW and/or MW Based on a 90 th

and 95 th percentile evaluation of enterococci and E. coli densities (FW/MW) Based on a 95 th percentile evaluation of enterococci (FW/MW) Not currently . To be developed by 2012 No, but provides single guideline values for E. coli

, enterococci, somatic coliphages, and C. perfringens from which (FW) standards could be
set Based on a 95 th percentile evaluation of enterococci (FW/MW) No relation between GI illness and fecal indicator bacteria

Epidemiological and statistical basis of numeric values Not specified

, generally same as WHO 2003, policy modified Acceptable/ attributable risk of GI illness and AFRI A cceptable/ attributable risk of GI illness No

- observed

adverse

- effect

- level (NOAEL) for GI illness Acceptable/ attributable risk of GI illness and AFRI Relation between exposure and enterococci for skin illness Number of participants in study Not specified, MW: see Kay et al. (1994) and Fleisher et al. (1996 );
FW : see Wiedenmann et al. (2006) FW: 1216 (Kay et al., 1994)
MW : 1216 (Fleisher et al., 1996) FW : 21,015 MW : 6350 FW: 1981 FW : 2368 MW : 2042 MW : >1300

Included children and other sensitive populations No (adult volunteers only) No Yes ( separate anal yses for ≤ 10 years old) elderly ( ≥ 55 years old) Yes (children ≥ 4 years old ) Yes (children ≥ 4 years old) NoU.S. Environmental Protection Agency

December 2010 25 

### 4. A NALYSIS O F 

### S TUDY 

### D ESIGNS 

### : D IFFERENCES T HAT 

### C OULD 

### A FFECT 

### C OMPARABILITY

This section presents a discussion of the limitations and precautions o f comparing and/or integrating data from RCT and PC epidemiology studies.

4.1 Summary of Published Commentary on Epidemiological Design Comparison

The ep idemiolog y studies that underpinned EPA’ s 1986 RWQC were the most sophisticated
studies to have been co nducted in recreational waters at the time . However, the analysis and interpretation of these studies were subsequently criticized in a detailed statistical re

- analysis by
Fleisher ( 1991 )

. Fleisher’s critique questioned the scientific rationale behind the U.S. standards
because , in his es t imati on, alternative statistical treatment of the data indicated substantially
different indicator

- illness relationships at each of the three sites where the field studies were
conducted

.

T he WHO took a different approach than EPA, in part, to address the per ceived shortcomings identified in the EPA PC studies, and based their 2003 Guidelines on data from the RCT studies
conducted in the U.K

. ( see Appendix A for further information ) . Their rationale is described
below from Kay et al. ( 2004 ) :

The WHO seeks to define Guideline s for environmental quality, based solely on the best available epidemiological and public health information... To acquire and evaluate the existing data, a WHO review of epidemiological evidence was published by Pr ü ss [1998]... The dose

- response relationsh ips from these studies were plotted...and it was noted that the UK randomized trial results [Kay et al., 1994] showed steeper dose

response curves than the prospective cohort studies. This was attributed to the enhanced control of bias facilitated by the ra ndomized trial design. Put simply, the more precise measure of exposure facilitated by measurement of water quality close to the time and place of bathing by a healthy adult volunteer limited the misclassification bias produced when a daily mean water qua lity is attributed to large groups of people participating in a prospective cohort study. The latter approach masks the considerable “ within

- day ” variability of faecal indicator concentrations, which produces both high and low actual

“ exposure ” values fo r some individuals who are falsely attributed the lower daily mean
indicator value and vise versa. This misclassification of individuals, with both high and low exposures, tends to reduce the slope of the dose

- response curve.

Mathematically, the 2003 WHO guidelines are derived by combining the observed indicator

illness relationship ( see Figure 1 ) in the U

. K

. RCT studies with the probability density function (pdf) of log 10 transformed indicator densities observed at numerous site s across Europe (as
shown in Figure 2 ). WHO decided that ( 1) the new Guidelines should employ the pdf disease
burden estimation method to calculate the risk of illness from exposure ; ( 2) the calculations
would be based on the ind icator

- illness curve derived from Kay et al. ( 1994 ) ; and ( 3) the Guidelines would employ a single value or parameter to characterize the pdf (i.e.

, its 95 th percentile).U.S. Environmental Protection Agency

December 2010 26 Figure 1 . Dose

- Response Relationship Used in the D erivation of WHO Numerical Microbiological Criteria for Recreational Waters

Figure 2

. Probability Density Function for **Enterococcus**
, Excess Probability of Gastroenteritis from WHO (2003)

Wymer et al. ( 2005 ) commented on the mathematica l methodology described in Kay et al. ( 2004 ) and extended those calculations. Their extension indicated that the slope of the comparable “ecologic” risk curve closely resembles that of the EPA’s and is likewise considerably less steep than that of the personal exposure mo del reported in Kay et al. ( 1994 ) ( i.e., the curve shown in Figure 1 ). In this extension, they evaluated Enterococcus densities withU.S. Environmental Protection Agency

December 2010 27 means ranging from 1 to 1000 per 100 mL (note that the Kay and colleagues paper effectively
solv ed the same integral for single values that resulted in one case of GI illness in 100, 20, and 10 exposures )

. A detailed explanation and g raphical illustrations are presented in Appendix A The resulting curve from Wymer et al. ( 2005 ) is shown i n Figure 3 (extracted Figure 1 from Wymer et al., 2005) and compared to the (approximately) analogous 1986 EPA curves for
marine waters.

Figure 3 . Wymer et al. (2005) Extension of the WHO Risk Curve

Wymer et al. ( 2005 ) stated fu rther :

... measurement of an individual swimmer

- specific exposure (as was done in the UK RCTs) will result in a more accurate risk assessment for that individual. However, it has not been the intent of most observational studies, in general, and of the USE PA studies in particular, to be used in the context of knowing an individual’s specific exposure. Marine and freshwater studies that have been conducted by the USEPA were designed to predict expected incidence of illness given monitoring results that are available in practice, i.e. mean indicator levels based on sampling [emphasis added]

. When the research design utilizes these same water sampling techniques and involves health surveys on the target modeling is simplified. Such prospective cohort studies reduce the number and types of assumptions that must be made in order to derive the relationship and permit straightforward evaluation of confidence bounds. ...In the final analysis, health data obtained through epidemiological studies must represent a div ersity of water
environments. In this regard, it is likely that the general variability encountered at beaches will be the driving factor in deriving guidelines that are protective of human
health.

Kay et al. ( 2006 ) subsequently responded to the comments of Wymer et al. ( 2005 ) . Highlights from their reply included the following:U.S. Environmental Protection Agency

December 2010 28 **•** They emphasized that exposure is a “ probabilistic ” event that depends on the distribution
of enterococci in the bath ing water and that this approach also facilitates calculation of a
disease burden.

**•** They emphasized that the studies that underpin the 2003 WHO Guidelines sought to maximize precision of the epidem iologic data by (1) measuring “exposure” (i.e., water quality) as close to the actual individual bather as possible, and (2) using a randomized volunteer protocol.

**•** They suggest ed that if the acquisition of “exposure” (water quality) data in epidemiolog y
st udies was to mirror the regime for regulatory samples (e.g., possibly five samples taken over a month for regulatory compliance assessment), it would have significant negative implications for the scientific quality of the evidence

- based approach.

**•** L arge sp atial and temporal variation s in fecal indicators during any bathing day makes average density on a study day a very imprecise measure of bather exposure with which to calibrate either a logistic or least

- squares regression model.

**•** They conclude d that basin g the sampling regime for any epidemiologic study in this area on the approach used for regulatory data acquisition will always produce very imprecise

“ exposure ” measures in any environment where spatial and temporal variability in fecal
indicator concentr ations is the norm. This makes model calibration difficult and produces bias towards the “ no effect ” conclusion.
Finally, it is the opinion of the principal scientists conducting the NEEAR studies (EPA Office of Research and Development) that most of the deficiencies that were noted in the epidemiology
studies conducted in the 1970s and 1980s have been addressed in the current EPA study design. Changes in the current design are documented by Wade et al. ( 2006

, 2008 , 2010 )

. In addition,
the previous perceived deficiencies were considered during the external peer review of the study,
and the overall s tudy approach, m ethods , and data analys is approach were reviewed and approved.

4.2 Differences in the PC and RCT Studies that Can Potentially Affect Comparability of
Data

A review of the studies described above indicates that several critical differences in these studies

ar e the key to understanding if or how the results are comparable. Those differences are
described below.

4.2.1 Assignment of W ater Q uality to B athers

The assignment of indicator organisms as an exposure variable to the study participants is very
different in P C and RCT studies.

In the NEEAR PC studies ( Wade et al., 2006

, 2008

, 2010 )

, water samples were collected three times a day (8:00 AM, 11:00 AM, and 3:00 PM) at three beach locations (transects), at two depths (waist and shin) for a total of 18 samples per day . Swimmer exposure was characterized using both the dai ly average (which was assumed to represent average water quality at a beach on a particular day ) and the 8:00 AM average ( used to determine if morning water quality was aU.S. Environmental Protection Agency

December 2010 29 better predictor of illness among swimmers exposed later that day ) . Thus, in EPA’s N EEAR studies, water quality measures were not applied to individual bathers but rather to all bathers on a particular beach on a particular day using the daily and morning average.

In contrast, i n the U.K. marine ( Kay et al., 1994 ; Fleisher et al., 1996 )

, German freshwater ( Wiedenmann et al., 2006 ) , and EU fresh and marine ( Epibathe ) RCT studies ( EC

- Epibathe, 2009a,b ) , the water in the designated swimmer areas was sampled every 20

- 30 minutes during
the exposure period (usually about 3 hours per trial day ) at 20 m intervals, allowing for a unique water quality to be assigned to each (previously randomized) bather . In the U.S. (Miami) RCT
studies ( Fleisher et al., 2010 ; Sinigalliano et al., 2010 ) , study participants collected their own waters samples at the same time they were being “exposed”

.

4.2.2 Swimmer W ater E xposure

The definition of swimmer/bather varie d greatly between the PC and RCT epidemiology studies

. In general, definitions and swimmer exposure in RCT studies have been more controlled compared to self

- reported activities of beachgoers in PC studies.

S wimmers in the NEEAR PC studies were defined as those who self

- reported immers ing their body to their waist or higher ( Wade et al., 2006

, 2008

, 2010 )

. Nonswimmers were defined as those who reported no contact with water while those entering the water not up to their waist
were classified as “waders.” In the EPA PC studies, water samples were taken from waist

- deep water (1 m deep) and in shin

- deep water (0.3 m deep) . L evels of Enterococcus C CE by qPCR were consistently higher in the shallower water. The EPA PC results demonstrate that
Enterococcus qPCR C CE was associated with GI illness at fresh and marine water b eaches impacted by point sou rces of sewage based on a definition of swimming that included body
immersion . F urthermore, a more stringent definition of swimming that required head immersion did not substantially alter the results , suggesting that head immersion is not a critical dete rminant
of whether and how much water is swallowed

. However, Wade et al. ( 2008

, 2010 ) found that
the association between increasing levels of Enterococcus qPCR C CE and increased incidence of GI illness strengthened as time spent swimming in the water increased

.

Adult s wimmers in the U.K. RCT studies ( Kay et al., 1994 ; Fleisher et al., 1996 ) were taken by a supervisor to a designated section of beach where they bathed for a minimum period of 10 minutes and were required to i mmerse their heads at least 3 times during that period. More specifically, Kay et al. ( 1994 ) state that participants had to immerse their heads at least three times, whereas, Fleisher et al. ( 1996 ) state that participants had to immerse their heads exactly
three times. Although water samples were collected at three depths

— surf; mid (1 m depth, 30 cm below surface); and chest (1.3 to 1.4 m depth, 30 cm belo w surface)

— the chest depth was the location at which immersion took place. Only enterococci, measured at chest depth, where the required immersions took place, showed a n indicator

- illness relationship for both GI illness and
AFRI in marine recreational wa ters. The recent EU RCT studies (Epibathe) used a similar protocol for swimmer exposure.

I n the German RCT study ( Wiedenmann et al., 2006 ) , bathers were exp osed for exactly 10
minutes in a designated zone (each divided into swimmer zones and shallow nonswimmer areas)U.S. Environmental Protection Agency

December 2010 30 and had to immerse their head at least 3 times. Although bathers were asked to stay inside the designated swimming zones with deeper water, bat hers were not excluded if they remained in the nonswimmer (shallower) zones provided they immersed their head at least 3 times and stayed in the water for exactly 10 minutes. Thus, it seems likely that most head immersions were in swimming zones with deep er water. F or each minute of the trial, microbial water densities were calculated in both the s wimmer and the nonswimmer zones . The microbial densities of each of
the 10 minute period s were assigned to each of the bathers in their individual exposure are a, including nonswimmer and/or swimmer zones , depending on their location per minute

. Exposure was defined two different ways. The first definition was “10 minutes bathing with at
least three head immersions

. ” The second was called “single head immersio n,” which was considered to be the theoretical equivalent of a single head immersion. The authors found that
the NOAELs for GI illness depended mainly on the definition of exposure, with significantly higher NOAEL values for exposure definition “single he ad immersion” than for the aggregate 10

- minute exposure definition.

In the recent U.S. RCT studies ( Fleisher et al., 2010 ) , bathers were required to spend 15 min utes in knee

- deep water (due to the relative shallowness of the study site), and to immerse their head
3 times completely under water. Using ropes, a 30 to 40 m stretch of beach was subdivided into
5

- m intervals forming 6 to 8 bathing expos ure zones, with exposure of any individual bather
restricted to their own individual swim zone that was 5 m wide. Each subject was instructed to take their own water sample at 5

- min ute intervals near the surface before their head immersion.
No bather was allowed to enter the water more than once during the actual study exposure.

As indicated above , the definition of swimmer exposure in PC studies varies markedly from the much more precise definition of swimmer exposure used in RCT studies (inclusive of m andatory
head immersions )

. Interestingly , the EPA PC stud ies found that a more stringent definition of swimming that required head immersion did not substantially alter the results (Wade et al. 2006, 2008, 2010)

. This difference in definition is potentia lly significant, because the rate of water ingestion could vary with extent or duration of immersion. Thus, i t is possible that the different “exposures” resulting from swimmer definitions in the PC and RCT studies resulted in significantly diffe rent volu mes of water ingested.

4.2.3 Definition of GI I llness

A variety of different definitions of GI illness (gastroenteritis) have been used by researchers in
the PC and RCT epidemiology studies discussed above.

For the NEEAR PC protocol, GI illness was defined as any of the following “diarrhea (three or more loose stools in a 24 hour period), vomiting, nausea and stomach ache, and nausea or stomach ache that affect regular activity” measured during the period up to 10

- 12 days after beach exposure ( Wade et al., 2006 ) . Notably, fever was not a requirement for GI illness, since infections can produce these illnesses without fever ( Payment et al., 1997 ; Colford et al., 2007 ) and because EPA researchers were also concerned about the accuracy of self

- reported low

- grade
fever ( Wade et al., 2008 )

. Previous EPA epidemiology studi es ( U.S. EPA, 1983, 1984 ) were principally based on “ highly credible gastrointestinal symptoms ” (HCGI) that inclu ded all cases of vomiting, instances of diarrhea that were accompanied by a fever or that were disabling, orU.S. Environmental Protection Agency

December 2010 31 cases of nausea or stomachache that were accompanied by a fever. During these earlier studies, participants were interviewed 8

- 10 days after the i nitial beach interview.

For the U.K. RCT studies, gastroenteritis was defined as : “...any case of vomiting or diarrhea plus any case of either indigestion or nausea accompanied by fever reported at either post exposure interview” measured after 3 weeks af ter the beach exposure ( Kay et al., 1994 )

. This
definitio n was also used in the Epibathe studies ( EC

- Epibathe, 2009a, b )

. Notably, in 1

- week post

- exposure interviews

, 34.3% of the GI il lnesses were reported while the remaining GI illnesses (65.7%) manifest ed in days 8 to 21 post

- exposure ( Kay et al., 1994 )

.

In the German freshwater RCT study, three separate definitions of GI illness were used, (1) “GE_UK” (GI illness definition used by Kay et al., 1994); (2) “GE_UK

- wf” (diarrhea OR vomiting OR [nausea AND fever] OR [indigestion AND fever]); and ( 3 ) “GE_NL

- 2” (diarrhea OR nausea OR vomiting OR stomach pains)

. In contrast to the U.K. marine studies, the German freshwater RCT reported the following ( Wiedenmann et al., 2006 ) :

Initially, we compared the crude incidence rates of disease among bathers and nonbathers, the crude relative risks , a nd the crude attributable risk s after the 1

- week
evaluation interval with those after the 3

- week interval. After it became obvious from this comparison that there was no additional scientific benefit from using the 3

- week interval, all subsequent analyses concentrated on the results obtained within a period of 1
week.

In the U.S. marine RCT studies ( Fleisher et al., 2010 ; Sinigalliano et al., 2010 )

, GI illness was defined as a report of the following symptoms: all cases of vomiting or diarrhoea, or all reported cases of indigestion or nausea accompanied by a fever; where “diarrhea” defined as having th ree or more runny stools within a 24

- h our period. The researchers indicate that these illness definitions were compatible with past studies carried out by the investigators in Europe, and are roughly compatible with the “ highly creditable illness ” definit ions used in the majority of the US
recreational water cohort studies.

Based on the information summarized above, it is clear that different health endpoints and
different follow

- up periods have been used by the various recreational water epidemiology

stu dies. These differences in follow

- up period are important in light of the differences in incubation periods for common causes of GI illness

, such as Giardia (associated with longer incubation periods) and norovirus (associated with shorte r incubation peri ods )

. Furthermore, it is not known if or how the inclusion of fever as a requirement for GI illness impacts the relationship between water quality and observed health effects.

4.2.4 Water Q uality

In all o f the PC and RCT recreational water studies that have been reviewed in this report , the recreational water body that was evaluate d met (at least usually) the applicable U.S. criteria ( U.S. EPA, 1986 or local/state standard) or EU standards ( CEC , 1976 ) that were in place at the time of the study. However, these EPA criteria and EU standards are substantially different from each
other

. Notably, the “ imperative indicator maximums ” of the recently repealed 1976 BathingU.S. Environmental Protection Agency

December 2010 32 Water Quality Directive ( CEC , 1976 ) were not based on or developed from epidemiology
studies

.

The predominant sources of fecal contamination at each of the studies sites are also noteworthy. Point sources of treated human sewage were the (reported) predominant sources of fecal
contamination at the fresh and marine recreational water sites tha t were evaluated as part of the
NEEAR Water Stu dy ( Wade et al., 2006

, 2008

, 2010 ) , the U.K. marine RCT studies ( Kay et al.,
1994 ; Fleisher et al., 1996 )

, and the EU fresh and marine water RCT studies ( EC

- Epibathe, 2009a,b ) . T he fact that the applicable standards were/are different could mean that various

wastewater treatment processes could have been used and there could have been differential indicator/pathogen relationships in those waters. M oreover, th e German freshwater sites were impacted by fecal contamination from treated and untreated municipal sewage, agricultural runoff (non

- point source pollution), and contamination from water fowl ( Wiedenmann et al.,
2006 )

. T he Miami RCT stud y site is described as a non

- point source (sub) tropical beach with periodic use by people, dogs, and birds, as well as seasonal heavy rains with no known point

sour ce s of domestic sewage ( Fleisher et al., 2010 )

.

4.2.5 Population I nvestigated

There are two primary differences between the populations that have been investigated in RCT and PC studies. The first is inclusion or exclusion of children. The second is whether subjects were specifically recruited from the population (and then randomized) as used by th e RCT
studies

, or were those that independently decide d (not r ecruit ed ) to go to a particular beach on the study day.

The U.K. marine RCT studies ( Kay et al., 1994 ; Fle isher et al., 1996 ) and the U.S. marine water
RCT studies ( Fleisher et al., 2010 ) specifically excluded subjects less than 18 years of age from
the ir study. T he German fresh water RCT st udies ( Wiedenmann et al., 2006 ) and the EU Epibathe studies recruited healthy local volunteers including those as young as 4 year s old to participate . C hildren less than 4 years old were not recruited as they were considered to be potential sources of direct fecal contamination.

T he NEEAR fresh and marine PC studies included criteria for site selection areas that compri se a broad age range of swimmers, including children and teenagers. In the EPA PC studies, agreeable adult (18 years or older) beach

- goers were recruited to complete on

- site and post

exposure questionnaires for all members of the household that visited th e beach.

4.2.6 Temporal V ariability of M olecular and C ulturable I ndicator C ounts

A key factor that influences the indicator

- illness relationship in epidemiological investigations is
nondifferential misclassification bias ( Fleisher, 1991 ; Prüss, 1998 ; Kay et al., 2004 ; Ka y et al.,
2006 ; Wiedenmann et al., 2006 )

. Non

- differential misclassification bias occurs if the outcome variable is erroneously and randomly assigned to false high or false low exposure s

. Nondiffe rential misclassification bias nearly always lead s to erroneously shallow indicator

illness relationships , since it results in either high illness rates associated with low indicator densities or low illness rates associated with high indicator densities

.U.S. Environmental Protection Agency

December 2010 33 The two main phenomena contributing to exposure misclassification are the imprecise assignment of microbiological monitoring results to certain exposed individuals and the imprecision of microbiological methods. An epidemiolog y study design that minimiz es these two kinds of imprecision therefore also minimizes misclassification bias ( Wiedenmann et al.,
2006 ) . Proponents of the RCT epidemiolog y study design h ave indicated that an RCT design minimizes the imprecise assignment of microbiological monitoring results relative to the PC design.

R ecent research has the potential for profound implications with respect to interpretation of the epidemiological results because they call into question whether or not the RCT study design does in fact provide a “more precise measure of exposure...by measurement of water quality close to the time and place of bathing.” For example, enterococci time series (measured using a

co mmercial 24

- hour chromogenic substrate assay ) have no associated characteristic time scale for samples collected at ankle depth from marine sites ( Boehm, 2007 )

. Thus, the degree to
which misclassification bias is reduced by collecting water samples close in time and space to an “exposure event” appears to be in question.

Currently , data do not exist to evaluate whether similar tre nds are observed for indicator organisms as enumerated by qPCR or other molecular methods . If the se trends are also true in diverse aquatic environments for Enterococcus and/or Bacteroides as enumerated by qPCR , then this information would be very valuabl e in (1) designing sampling protocol s , and (2) developing scientifically valid water quality criteria.

4.3 Summary of I ssues on I ntegrating the R esults from RCT with PC S tudies

The primary differences between the seminal recreational water PC and RCT epidemi ology studies include both subtle and not so subtle differences. The key differences include the following:

**•** assignment of water quality and subsequent use of either personal or ecologic measures of exposure to swimmers;

**•** exposures experienced by swimmers (and thus the volume of water ingested);

**•** definitions of GI illness, especially the presence or absence of fever;

**•** water quality regulations in place ; and

**•** population s investigated in the various epidemiology studies

. Based on the differences noted above, li mitations exist with comparing and combining results from these two study designs. I n the following section, suggestions are provided for additional analyses to help resolve potential issues related to comparing results from studies using these
different epidemiology designs.U.S. Environmental Protection Agency

December 2010 3 4 

### 5. O PTIONS F OR 

### A DDITIONAL 

### A NALYSES TO 

### F ACILITATE 

### C OMPARING 

### R ESULTS 

### A CROSS 

### S TUDY 

### D ESIGNS

This section presents activities that could be conducted to help facilitate valid comparisons of RCT and PC study results . The major study featur es that hinder comparisons between these types of studies were introduced and discussed in the preceding section . T hus, the focus of this
section is to describe activities that could be undertaken to harmonize the studies and explain the
rationale for tho se activities

. Based on a prioritization of these activities, specific recommended activities are provided in Section 6

.

5.1 Water Quality Metric

An important distinguishing attribute of the two epidemiolog ical designs is how water quality is assigned to ea ch subject in those studies. The approaches employed have been well documented
in the literature and discussed in this report ( Kay et al., 1994 ; Fleisher et al., 1996 ; Wade et al.,
2006

, 2008

, 2010 ) . In all of the se epidemiology studies, the objective is to express the probability of a subject getting ill (usually GI illness) when exposed to recreational water containing a specific level of indicator organisms. There is an inherent assumption that the
indicator or ganisms in the recreational waters correspond to the overall level of fecal contamination and thus, w ith the pathogens that caus e illness. Under this assumption, there
exists some relationship between the density of the indicator organisms and the probabi lity of developing symptoms of illness in subjects exposed to the water. The relationship may be typical of a particular site type or general to all sites with similar fecal pollution sources. The relationship of the number of indicator organisms observe d in the water and the probability of
illness i s expressed in an indicator

- response curve ( Parkhurst et al., 2 007 ) . For these curves to accurately represent the relationships between exposure and probability of illness, it is important
to characterize both the density of indicators to which each subject in the study was exposed and the fecal pollution source fr om which the indicators originated. As indicated previously, imprecise (or biased) estimates of exposure can impact the inferred relationships between curves generated in studies of different designs ( Kay et al., 2004 ) and even between studies using the same design ( Wyer et al., 1999 )

.

The NEEAR PC studies characterize the densities of indicators with the geometric mean of a number of samples periodically over the course of an entire day (e.g., at multiple areas, depths,

a nd times of day as reported in Wade et al., 2006). RCT studies typically characterize the density of indicators based on samples collected in the immediate vicinity of each test subject.
E xtensive debate exists in the literature regarding the relative me rits of these two approaches ( Kay et al., 1994 ; Fleisher et al., 1996

, 2004 ; Wymer et al., 2005

, 2006 )

. The RCT studies may offer a better estimate of the personal exposure associated with the individual in the stud y, although the relationship between the indicator level and the fecal pollution to which an individual is exposed in uncertain, given the wide variability in indicator density observed at all relevant time and space scales. In contrast , the NEEAR (PC) stu dies offer an ecological or group exposure and likely a better estimate of an appropriate guideline measure considering the range of exposures at a recreation site.U.S. Environmental Protection Agency

December 2010 35 Many studies have demonstrated extreme variability in indicator densities at recreational areas. For example, Kay et al. ( 1994 ) observed “significant spatial and temporal variability in indicator organism concentrations at each site throughout the 3 hour period of sea water sampling during which the bathers were exposed.” EPA conducted an extensive study to characterize fecal indicator distributions within the bathing areas of beaches in its 2000 EMPACT ( Environmental Monitoring for Public Access and Community Tracking ) study ( U.S. EPA, 2005 )

. That study found extensive variability in both the spatial and temporal components at individual beaches. More importantly, the EMPAC T beach studies demonstrated significant variability among the beaches based on the sampling plans used. Recent research ( Boehm, 200 7 ) indicates that the
distribution of Enterococcus is fractal variability is unchanged regardless of the temporal/spatial scale of the sampling. This finding implies that regardless of whether sampl es are taken at three times during the day or immediat ely adjacent to the subject , the variability and the uncertainty of the results will be the same (i.e., uncertainty can only be reduced by increased number of samples). If these observations hold for a wide range of enumeration techniques , then the “ best ” estimate is likely to be the one that is based on the most samples over the course of a n appropriate sampling period. More samples provide not only greater statistical power but also alternative statistical measures of water quality (e.g., maximum observ ation) for use in
correlation with observed health effects.

To address the issue of assigning water quality to bathers, the following activities could be
conducted :

1. Validate and extend the research that indicates that the distribution of Enterococcus is
f ractal:

a. Use the existing EMPACT and NEEAR study data to evaluate whether water quality at the beaches studied demonstrate fractal behavior is noted. Of particular interest is the behavior of qPCR indicator densities. These evaluations would be
done for s ample collection depths greater than ankle depth

. b. If the EMPACT and NEEAR study data are inadequate for this purpose , then a new monitoring study based on multiple locations should be considered using culturable and molecular methods for the indicator orga nisms of greatest interest ( Enterococcus

, Bacteroides , and others to be determined) in several diverse waterbody types of interest (e.g., fresh and marine recreational waters)

. If the fractal nature of Enterococcus and/or other fecal indicators in environm ental water
is confirmed, the results would be invaluable for informing the type of sampling that is required to best characterize the water quality component during epidemiology studies.

2. Reanalyze the water quality data from one or more RCT study or stu dies in a manner that is parallel to the NEEAR PC studies. That is, combine all of the water quality data from a given day into a geometric mean value and then reanalyze the health

- based data. T he resulting indicator

- illness functions from the RCT and PC studies would be directly comparable . This concept was suggested during 2009 EPA Recreational Waters
Research Forum that was held at the Southern California Coastal Water Research Program office.U.S. Environmental Protection Agency

December 2010 36 5.2 Swimmer E xposure to W ater Quality

Another distinguishin g attribute of the two epidemiological designs is the definition of “exposure” that is used. F or RCTs, the study participants were most commonly instructed and observed to fully immerse their heads at least three times during a specified period of time (u sually 10 minutes) . I n the PC studies, results are typically reported for subjects who self

reported “body contact” with the water (typically defined as immersion up to their chest).
Because the route of exposure is assumed to be ingestion, it is probabl e that these different definitions of exposure relate to different levels of ingested water (and thus, risk of illness).

Little data are currently available to quantify the distribution of water ingestion during
recreational activities. The data that a re available ( Dufour et al., 2006 ) indicate ingestio n volumes of 37 and 16 mL for 45 minutes of unstructured activity in swimming pools for non

adults and adults, respectively. The extent to which these different epidemiological protocols result in exposures different than that reported by Dufour and colle agues is unknown. To our knowledge, data for characterizing the distribution of ingestion volumes typical of exposures
undertaken in RCT studies are unknown.

To address potential misclassification in interpreting the results from the epidemiology studi es, one possibility would be to conduct a pilot scale study similar to that reported by Dufour et al. ( 2006 ) using the exposure protocol specified by the RCT epidemiology studies (i.e., participants would be required to immerse their head a specific number of times within a specified period of time). All other protocols would be the same as those in the original Dufour and colleagues

. The results could then be compared to those reported by Dufour et al. (2006) to determine if the effects of the body immersion protocols have a significant effect on the res ults of the study.

5.3 Definition of GI I llness and R eporting P eriod

There are clear differences in the definition of GI illness across the various epidemiology studies considered in this report. F or the U.K. , EU ( Epibathe ), and U.S. (Miami) RCT studies, gastroenteritis was defined as a ny case of vomiting or diarrhea plus any case of either indigestion or nausea accompanied by fever ( Kay et al., 1994 ; EC

- Epibathe, 2009 a,b ; Fleisher et al., 2010 )

. Notably, Kay and colleagues ( 1994 ) indicated that 34.3% of the GI illnesses were reported
with in 1

- week post

- exposure period that while the remaining GI illnesses (6 5.7%) manifest ed in
8

- 21 days post

- exposure. In contrast, and as noted previously, Wiedenmann et al. ( 2006 )
concentrated their analyses on the results obtaine d within a period of 1 week following exposure after it became clear that there was no additional scientific benefit from using the 3

- week
interval.

For the NEEAR PC protocol, GI illness was defined as any of the following “diarrhea (three or
more loose s tools in a 24 hour period), vomiting, nausea and stomach ache, and nausea or stomach ache that affect regular activity” measured after 10

- 12 days after beach exposure ( Wade et al., 2006

, 2008

, 2010 ) This definition of GI illness is consistent with definitions used in other
PC studies ( Payment et al., 1997 ; Colford et al., 2007 ) . Previous EPA epidemiology studies ( U.S. EPA, 1983, 1984 ) were based principally on H CGI that included all cases of vomiting, instances of diarrhea that were accompanied by a fever or that were disabling, or cases of nauseaU.S. Environmental Protection Agency

December 2010 37 or stomachache that were accompanied by a fever. During these earlier studies, participants
were interviewed 8

- 10 days after the initial beach interview.

Thus, the definition of GI illness has and continues to vary between PC and RCT r ecreational
water studies

, in that recent and ongoing PC studies generally omit the requirement for fever

, while fever remains part of the definition in ongoing RCT studies. Retrospective analysis of the epidemiological data might allow for the comparison of effects of the illness definition. If the symptoms and dates were reported (and are available for analysis) for both swimmers and nonswimmers (to allow estimation of background incidence of GI illness consistent with different illness definitions) the n comparisons of results using the different end points for illness might be possible. Comparisons could then be made between the same data sets to see the
effects of the different definitions of illness.

It is likely that for human impacted waters, mos t swimming associated illnesses occur within the time period evaluated in both types of studies ( Soller et al., 2010 ) . Confirming this hypothesis depends on the availability of detailed data on the dates of illness for the subjects from the U.K. RCTs and earlier EPA studies. If the original questionnaire data are available from those studies and include documentation of the specific days that illness was observed for each subject, then these data could be used to develop alternative indicator

- illness relationships that could provide more of an “apples to apples” comparison to the current EPA PC epidemiology studies. If this approach is possible, the resultant cur ves could be compared for each time interval. This approach could possible answer the following two questions : ( 1) are the results of the studies are similar for a one week reporting interval ?; and ( 2) are there are significant increases in illnesses
that could be related to recreational exposure as the reporting periods extend from one week to
three weeks ?

5.4 Water Quality

In the previous section, the required regulatory water quality criteria/standards were reviewed for
the U.K. , EU, and U.S. (Miami) R CT studies, as well as EPA ’s PC studies. It is noteworthy that
these criteria/ standards were/are substantially different. Thus, the starting point of the various epidemiology studies was differ ent because the y could not be conducted at beaches that were deemed unacceptable in terms of microbiological water quality

. Furthermore, s ince the
criteria/ standards for microbial water quality w ere different

, it is possible that a confound ing
factor i s present with respect to compari ng the results of the se studies

.

The noted differences in the water quality standards extend further to differences in discharge regulations and the types of wastewater treatment that are applied in different geographic regions (e.g., chlorination of wastewater continues to be mor e com mon in the U nited States than in Europe )

. Because beach monitoring is dependent on somewhat consistent relationships between
the measured indicator densities and pathogen distributions, differences in wastewater treatment practices and water quality stand ards could result in different relationships be tween indicators and pathogens. These differences could manifest themselves as different rates and
characteristics of illness caused b y exposure to different pathogens at POTW

- impacted
recreational water site s ( Soller et al., 2010 )

.U.S. Environmental Protection Agency

December 2010 38 The potential differences noted above in the various epidemiology studies will be difficult

, if not impossible

, to quantify because the effects are embedded in the results and few definitive

retro spective analyses are possible. One feasible option is to reanalyze the raw data from the
U

. K

. marine recreational water studies ( Kay et al., 1994 ; Fleisher et al., 1996 ) and exclud e data collected on days when the U

. S . criteria for enterococci was exceeded ( U.S. EPA, 1986 )

. The analysis c ould be considered a sensitivity analysis to determine whether different conclusions
would be reached if the studies had not be en conducted on the days t hat U.S. criteria were
exceeded. Such a retrospective analysis c ould partially address the possible biases due to

exposure differences due to different water quality standards. However, t his approach would not
address the potential effects of the different standards on the differences in the ratios and pathogens that result from different t ypes and levels of wastewater treatment , and may be a function of what pathogen predominated in the water for any given swimming exposure period

.

5.5 Population Investigated

Another distinguishing attribute of an epidemiolog y study is the population (or subp opulation) that is studied. As noted previously, until recently, RCTs excluded subjects younger than 18

years (likely because of potential ethical issues and/or concerns ) . In the most recent RCTs in Europe, th is difference has been at least par tially res olved ( Wiedenmann et al., 2006 ; EC

Epibathe, 2009a,b )

. Because PC studies recruit subjects who have come to beaches which meet regulatory requirements

, these studies typically include individuals of a wide range of ages and subpopulations. In fact, the NEEAR freshwater stud y sites were selected to ensure the population in the study included a broad age range of swimmers

, including children, teenagers,
and adul ts ( Haugland et al., 2005 )

.

T here are differences between the indicator

- illness relationships in young subjects and those of the general population ( Wade et al., 2008 )

. In freshwater, c hildren below the age of 10 showed a higher gradient of risk for developing illness. Therefore, studies that exclude children could underestimate risk because a segment of the population with a known higher susceptibility to
illness when exposed to fecal

- contaminated water is excluded from the study group. With respect to comparability of results between epidemiolog y studies, exclusion of children could be expected to result in lower observed incidence of illness , since children are expected to swallow more water than adults as they participate in more vigorous activities for longer durations

.

The NEEAR freshwater studies provide adjusted odds ratios for participants below 10 years of

age, ages 11

- 54, over 55, and for all ages . They also provide swimming

- associated GI illness

rates among all subjects and among children aged 10 years and below

. These results could be
used to construct an analysis to estimate if the combined Epibathe results underestimate risk s to specific portion s of the pop ulation (children in this case)

.

5.6 Relationship b etween Culture Methods and Rapid Methods

Wade and colleagues reported that the odds of swimmer illness increased significantly with
increased densities of Enterococcus and Bacteroides measured by qPCR ( Wade et al., 2006

, 2008

, 2010 )

. Notably, a ll of the other epidemiology studies discussed in this draft report used
cultur e

- based methods to enumerate fecal indicator organisms and characterize water quality.U.S. Environmental Protection Agency

December 2010 39 Ideally, these molecular method

- based results would be co mparable to those estimated by
culturable methods.

The distributions of indicator densities in recreational waters may vary with the microbiological methods employed for several reasons, including ( 1) qPCR counts genetic material from both
viable and no n

- viable indicators and are typically higher, sometimes by orders of magnitude, in fecal pollution

, and is not dependent on cell viability ; and ( 2) it is possible that pathogens
densities in sewage may be reduced substantially in wastewater treatment under conditions that do not substantially reduce indicator densities as measured by qPCR.

To address the relationship between water quality estimated by culture and molecular methods,
the increased simultaneous us e of both culture

- and molecular

- based methods in future epidemiology studies ( Wade et al., 2006

, 2008

, 2010 ) could be a priority

. With these data, it would be possible to a nalyze the results using both sets of data in a consistent manner to determine how to appropriately compare epidemiology studies that base their wa ter quality
evaluations on different microb iological methods. EPA has also recently investigated numerical approaches for evaluating the relationships between culture and molecular

- based results ( U.S. EPA, 2010 ) . The recommendations from that report should also be carefully considered within
this context.

5.7 Direct Approaches to Compare RCT and PC Results

5.7.1 Conduct a n RCT in P arallel with a PC S tudy

T he importance of temporal and spatial variability of water quality was highlighted above and
the implications for comparing results from epidemiolog y studies of various designs were discussed. Depending on the extent and magnitude of fecal indicator variability

, it may be possible to conduct a small scale RCT in parallel with a PC epidemiolog y study by lev erag ing a carefully designed water qu ality collection program to minimize additional study costs over that of the PC study

. This type of study could allow the most direct possible comparison of the two study designs ( same time

, same location , simila r population, etc.) while simultaneously minimizing costs because the water quality component could serve for both components of the study.

5.7.2 QMRA T ranslation between RCT and PC

Another approach is to use a QMRA framework to translate results from an RCT t o one that is comparable to a PC study. A preliminary schematic diagram of the proposed QRMA approach is presented below ( Figure 4 )

. Briefly, the analysis would begin with the water quality (fecal indicator) data from one or mor e RCT study. Using the published relationship between the fecal indicator and adverse health effects (GI illness) , predic ted mean probability of illnesses w ould be computed for each individual in the study (or studies) using a predicted volume of water in gested during the RCT study and the published norovirus dose response relationship from a volunteer exposure study ( Teunis et al., 2008 ) . These illness values could be used to estimate pathogen densities in the recreational water. Based on recent research, it would be reasonable to assume
that norovi rus is the primary etiologic agent of concern, provided that the RCT was conducted inU.S. Environmental Protection Agency

December 2010 40 RCT water quality data

for each individual Predicted mean probability of Illness for
each individual

RCT relationship between water quality
and illness Predicted volume of water ingested Dose response for
norovirus Predicted density of
Norovirus in each water quality sample

Empirical distributions of
norovirus and indicator in beach from RCT study Sample with replacement (Paried data: indicator and norovirus densities)

Sample water quality for a simulated PC study Predicted geometric mean norovirus density per day of simulated PC study RCT volume

PC volume

Predicted mean illness per day of simulated PC study

Predicted geometric mean indicator density per day of simulated PC study Plot of illness vs. indicator for equivalent PC study

Figure 4 . Schematic D iagram of a QMRA

- based A pproach to Translate RCT R esults to a PC P aradigm
a water that was impacted by POTW effluent ( Soller et al., 2010 ) . This assumption could be assessed via a retrospective QMRA analysis of RCT study data similar to that conducted for PC data by Soller et al. ( 2010 ) . If norovirus is again found to be the primary etiological agent, these norovirus densities could be paired (for use later in the analysis) with the fecal indicator densities that were used to generate them.

The norovirus (and fecal indicator) densities could then be randomly sampled in a manner that would simulate a PC epidemiology study. To do this, we would assume that the water quality

sam ples from the RCT study are representative of the waterbody that was studied. Typically, in a PC study, 18 samples are taken on each day, and a geometric mean value of those samples is used to represent the water quality on that particular day. Here, we would randomly generate 18 samples from the computed norovirus densities and compute geometric mean norovirus and fecal indicator densities. Using a predicted volume of water ingested during the PC study (which may or may not be the same as that for the R CT study) and the published norovirus dose response relationship, the predicted mean illness on each day of a “simulated PC” study would be generated. Finally, a plot could be generated showing the predicted mean illness on each day of
a “simulated PC” st udy vs. the geometric mean fecal indicator organism densities that which would be comparable to other PC studies.U.S. Environmental Protection Agency

December 2010 41 5.7.3 Meta

- A nalysis of RCT and PC S tudies

If the activities described above allow meaningful comparisons of RCT and PC studies, a meta

analysis o f similar studies (e.g. , s tudies conducted on POTW

- impacted waters) could be highly
informative . This is the approach that was taken in the EU to compare the results of the recent Epibathe studies to those conducted previously in U

. K

. marine water ( Kay et al., 1994 ; Fleisher et al., 1996 ) and German freshwaters ( Wiedenmann et al., 2006 )

. Figure 5 and Figure 6 illustrate
the results of th e EU meta

- analysis conducted on marine and freshwaters, respectively ( EC

Epibathe, 2009a,b )

. EU marine and freshwaters suggest elevations in illness in the bather
cohorts. However, results from fresh water studies do not display a consistent incremental elevation in odds ratio as the exposure increase s . A similar analysis could be conducted that
includes all similar studies from the U nited States and EU to provide an extremely robust dataset.
The meta

- analysis should include consideration of the setting (marine v s . Great Lakes v s . fresh impounded v s . fresh flowing) as well as the suspected dominant fecal pollution source(s).

Figure 5 . Epibathe M eta

- A nalysis F orest P lots of G astroenteritis in M arine WaterU.S. Environmental Protection Agency

December 2010 42 Figure 6 . Epibathe M eta

- A nalysis F orest P lots of G astroenteritis in Freshwater

5.8 Interactions betw een Previously Identified Factors

In the preceding sections, additional activities were identified that could facilitate comparisons between epidemiology studies that are based on different approaches. The epidemiology literature clearly indicates that t here is substantial variation in the resulting indicator

- illness curves from the epidemiology studies that have been conducted over the last fifty years ( Prüss,
1998 ) . The diversity of results suggests that the resultant curves may depend on a number of key elements that can have significant influence over both individual exposures and their subsequent manifestations of illness. The key factors that contribute to thi s variability and cause complexity in directly comparing the results of epidemiology studies of various designs include the following:

**•** the manner in which water quality is assigned to bathers;

**•** the specific exposure that bathers experience (duration

, and/o r intensity of exposure ) ;

**•** the definition of illness and the duration of incubation that is considered;

**•** the regulatory conditions under which the study was conducted , and thus, the water quality at the beaches under study ;

**•** the susceptibility, age , and make

- up of the subject pool;U.S. Environmental Protection Agency

December 2010 43 **•** the source and fate of pathogens and indicators in the investigated water, the distribution of those pathogens, and temporal/spatial variability of those distributions; and

**•** the methods used to enumerate the indicators and the corr esponding relationships between the indicators and the pathogens, as measured by those methods.
Adding to these complexit ies , the EMPACT study report ( U.S. EPA, 2005 ) describes other sources of variability that may play a part in the observations made

, regardless of the epidemiological protocol used. These other sources of var iability include th e following:

**•** weather ;

**•** terrain (both of the land and of the bathymetry in the water) ;

**•** flows from rivers and outfalls ;

**•** time of day of sampling ;

**•** winds ;

**•** tides ;

**•** bather densities ;

**•** local (fecal) contamination ; and

**•** water depth.
In addition, it is important fo r epidemiology investigators to assess confounding factors that may be responsible for the associations observed. Confounders are factors that are related both to the exposure in question and the illness. Each study will have a questionnaire that is used to obtain
information about these factors. Confounding can be controlled either as part of the study design or in the analyses. For example, sources of exposure other than the recreational water exposure being studied can cause GI illness and can confou nd the risk association and indicator

- response relationship if these exposures are also associated with swimmers. An example is increased swimming activities other than on the day being studied. The study can control for this by requiring participants no t to conduct additional swimming or collection information about additional swimming for use in the risk analyses.

Based on the potential influence of each of these factors, any additional activities that are
undertaken will need to consider the potential for multiple factors to be simultaneously important. Because of the complexity associated with accounting for multiple factors, it may not be feasible or possible to control for all of the potentially important factors between recreational water epidemi ology studies. Further, there m ight be interactions between multiple factors that will be difficult to separate. Such interactions could result in either dampening or amplification of effects that could confound the interpretation of the data. Finally, such in teractions could be
site

- specific.U.S. Environmental Protection Agency

December 2010 44 

### 6. R ECOMMENDED 

### A CTIVITIES AND 

### C ONCLUSIONS

When the available epidemiological data are compared, significant differences are observed in the relationships between exposure to recreational waters and related inciden ce of illness. Based
on the information described in this draft report, t he extent to which the differences observed in the outcomes of epidemiolog y studies are due to differences in the study design (RCT or PC) or are due to other differences ( e.g ., inter

- site variability, difference s in sampling protocols) is
unknown

.

Wymer et al. (2005) opine that differences in outcomes from diverse locations are expected due to the many possible inter

- site differences (e.g., water quality, water matrices, waste water

t reatment, topography, flow, and/or substrate). However, some of this variability m ight also be attributable to other factors such as differences in sampling protocols, collection, and analysis, as
well as other issues.

D ifferences between study d esigns could significantly influence the relationship between exposure and illness observed in different studies. When considering the appropriateness of directly comparing results or combining data collected from different epidemiolog y studies, the
drive rs in these differences are critical. Even f or studies conducted using the same design ( either PC or RCT), it may not be possible to assume that differences in outcomes are mostly driven by factors other than nuances in the methodologies and analysis. For example, RCT studies with significantly different experimental exposures cannot be assume d directly comparable. Further

, when attempti ng to directly compare the results or pool the data between studies of differen t design s , it m ay be difficult to ascertain whether variability in results is due to differences between sites, or if the underlying data are fundamentally different. If the observed results are signific antly different from one another and the differences are due to significant differences in the underlying design

, then it would not be appropriate to directly compare the data. If, on the other hand, the observed differences are due to variability arising from the different study sites

, then comparing or combining the data may be reasonable.

6.1 Summary of Recommended Activities

In identifying additional activities that could be undertaken to enable valid comparisons between epidemiology studies of differe nt designs , a prioritization of the factors of greatest concern is
needed . In addition, some of the observed effects during an epidemiolog y study could be caused or influenced by parameters that were not controlled for in the study

. The following priorit ized list of activities represents a starting point for activities that could fill data gaps toward the desired end of combining results from RCT and PC epidemiology studies:

1. Coordinate with the investigators o f an RCT study to obtain the raw data from tha t study
and re

- analyze the results using the statistical methods employed by Wade and colleagues
for the NEEAR studies. Such an analysis will pro vide an indication of whether or not results from RCTs and PCs can be compared directly and will help to answe r the question of whether the differences observed in existing epidemiology studies are due to the study design or other factors. In this regard, i nitial contact has been made with Dr. David Kay.U.S. Environmental Protection Agency

December 2010 45 2. Use a QMRA framework to translate results from an RCT study to a comparable PC

s tudy. Conduct sensitivity analyses to identify the model parameters that most strongly influence the results. Compare the results with those from activity #1 above

. 3. If the sensitivity analyses indicate that the volume of water ingest ed is a critical component, c onduct a pilot scale study similar to that reported by Dufour et al. (2006) using the exposure protocol specified by the RCT epidemiology studies

. Such a study
will be able determine if the volume of water ingested during the RCT epidemiology studies are likely to differ substantially from those that are generally used to characterize exposure volumes.

4. E xtend the work reported by Boehm ( 2007 ) using both cultur e

- and molecular

- based methods for the indicators of highest interest in several disparate recreational waterbody types of interest. This information would help to characterize the extent to which the method of allocating exposure to the subjects influence s the results. If the density of indicators is highly variable in short spatial and temporal frames, differences in exposure sampling prescribed for RCT

- vs

. PC

- based epidemiolog y studies w ill not have a large influence on study results.

5. To verify the results of the above activities, c onduct a small RCT component without additional water quality data within a PC study.

6. If the activities described above are successful so that it is possible to compare the results from RCT and PC studies, conduct a meta

- analysis of POTW impacted waters for epidemiology studies conducted around the world

. 6.2 Conclusion s

The following information has been compiled in this draft report :

1. D etailed descriptions of th e RCTs conducted in marine recreational waters in the U.K.; RCT studies conducted in fresh recreational waters in Germany; RCT studies conducted
in Florida ; RCT studies conducted in fresh and marine recreational waters in the EU ; and
EPA ’s completed PC stu dies in the U nited States in temperate fresh and marine
recreational waters.

2. Detailed summaries of the RCT epidemiological bases of the 2006 EU Directive and the
2003 WHO Guidelines

. 3. A summary of the key differences in the two types of epidemiology studies that can potentially affect comparability of data.

4. A discussion of additional activities that could help compar e the reported results from
RCT and PC studies

. 5. Prioritized r ecommendations f or activities to help compare the reported results from RCT
and PC studies

.

Based on this information, we conclude that w ith the information an d techniques currently
available it would be extremely difficult and dubious to directly compare r elationships between
indicator density and incidence of illness from previously conducted RCT and PC studies
without additional analyses or collection of additio nal information. Further, we conclude that inU.S. Environmental Protection Agency

December 2010 46 some instances studies of the same type may not be directly comparable, as in the case of RCT studies with significantly different experimental exposures. Modeling activities and quantitative or qualitative meta

- analyses are frameworks that can be explored for developing meaningful

an alyses using data from both RCT and PC studies.U.S. Environmental Protection Agency

December 2010 47 

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December 2010 A

- 1 

### A PPENDIX 

### A

. O VERVIEW OF 

### EU AND 

### WHO G UIDELINES FOR 

### R ECREATIONAL 

### W ATERS

2006 EU Bathing Water Quality Directive

The meta

- analysis of Zmirou et al. (2003) was conducted to provide a scientific basis for the establishment of new standards for the microbial quality of marine and fresh recrea tional waters (EP/CEU, 2006) to replace the recently rescinded EU bathing water quality guidelines that apply equally to fresh and marine recreational waters ( CEC , 1976). The former guidelines had been criticized on technical, scientific, and management g rounds (see Zmirou et al., 2003) and were not based on epidemiolog y studies. The new EU bathing water guidelines were adopted in early 2006 with a new Directive (2006/7/EC) that “...should use scientific evidence in implementing
the most reliable indicator parameters for predicting microbiological health risk and to achieve a high level of protection. Further epidemiolog y studies should be undertaken urgently concerning the health risks associated with bathing, particularly in fresh water.” As noted previo usly, t he new guidelines are based on several marine (Kay et al., 1994; Fleisher et al., 1996) and freshwater (Wiedenmann et al., 2006) RCT epidemiology studies (see more below)

— although the final numeric standards were developed through a series of consul tations and negotiations with EU member states (see Table 3 ).

Table 3 . Current EU Bathing Water Directive Requirements for Microbiological Water Quality Assessment Classification by Indicator Density

Inland (Fresh) Waters
Indicator Excellent Good Sufficient (Intestinal) enterococci ( CFU /100 mL) 200 * 400 * 360 **

E. coli ( CFU /100 mL) 500 * 1000 * 900 ** Coastal and Transitional (Marine) Waters
Indicator Excellent Good Sufficient (Intestinal) enterococc i ( CFU /100 mL) 100 * 200 * 200 **

E. coli ( CFU /100 mL) 250 * 500 * 500 ** Source: Adapted from EP/CEU ( 2006 )

. Notes: * = Based on a 95 th percentile evaluation; ** = Based on a 90 th percentile evaluation to reduce the risk of statistical anomalies when using a small data set, which also allows lower limit values for enterococci and E. coli densities in inland waters to be classified as sufficient v s. good microbiological water quality.

Unlike the 1976 Directive ( CEC , 1976), in which bathing waters either conf orm or do not to the relevant microbiological quality parameters, the proposed Directive (EP/CEU, 2006) requires a bathing water quality assessment that classifies a particular bathing water as “poor” (does not meet sufficient or better microbiological qua lity parameters), “sufficient,” “good,” or “excellent” quality, based in large part on the results of long

- term monitoring of bacterial indicator organisms (see Table 3 ). The numeric values for (intestinal) enterococci and E. col i presented in Annex I of the Directive are based on epidemiolog y studies and on either a 90 th or 95 th percentile basis of the last set of bathing water quality data (i.e., generally the last four bathing seasons). This method of determining the microbiol ogical water quality assessment classification of a particular recreational area by densities of indicators is similar to that recommended in the latestU.S. Environmental Protection Agency

December 2010 A

- 2 (2003) WHO guidelines (see more below). There are distinct limit values for inland and coastal

waters.

WHO Guidelines for Safe Recreational Water Environments

The WHO has been concerned with health issues associated with recreational water environments for many years and has published many reports, workshop proceedings, and other documents concerning the safety of the water environment and its importance for human health. This report focuses on the recent WHO (2003) report, Guidelines for Safe Recreationa l Water
Environments Volume 1: Coastal and Fresh Waters . This extensive report builds and expands

on several previous related reports, most notably i ncluding Health

- Based Monitoring of Recreational Waters: The Feasibility of a New Approach (The “Annapolis Protocol”) (WHO, 1999), and provides a comprehensive review and assessment of the health hazards ass ociated with recreational use of coastal (including estuarine/transitional waters) and (inland) freshwater
environments.

According to the Annapolis Protocol (WHO

, 1999), recreational water safety or quality is best described by a combination of a sanita ry inspection and a microbial water quality assessment using enterococci (see Table 4 ; extracted Table 4.12 from the 2003 WHO Guidelines). This approach considers possible sources of pollution in a recreational water, as well as actual (observed) levels of fecal pollution as measured by bacterial (enterococci) indicators, and
combines them into a 5

- level classification scheme for recreational water environments. Among other uses, the classification system can be used to “grade” b eaches and provide an assessment of regulatory compliance. Follow

- up analyses are recommended when the enterococci counts are high, but the sanitary inspection suggests low sanitary impact, or vice versa (see Table 4 ). Following initial classification, the 2003 WHO Guidelines propose that all recreational waters be subjected to an annual sanitary inspection to determine whether pollution sources have changed, and continued water quality monitoring.

The 2003 WHO Guidelines conc lude that there is consistency in the overall body of evidence concerning adverse health effects resulting from exposure to fecally polluted recreational waters. In 19 of the 22 studies examined in Prüss’ (1998; WHO

- supported) meta

- analysis, the rate of

s everal symptoms or symptom groups was significantly related to the count of fecal ind icator
bacteria or bacterial pathogens in recreational water. Consistent with other governmental reports
and the two other meta

- analyses discussed previously (Wade et al. , 2003; Zmirou et al., 2003), the WHO report states that the most frequent and consistent adverse health outcome associated with exposure to fecally contaminated recreational water is gastroenteritis (or GI illness). In addition, an association between fe cal or bather

- derived pollution and AFRI

— a more severe health outcome than self

- limiting GI illness

— has also been reported (Fleisher et al., 1996 )

. More specifically, a significant indicator

- illness relationship between AFRI and enterococci was
establishe d. However, when compared with GI illness, the probability of contracting AFRI is generally lower and the threshold at which illness is observed is higher. Also, according to Prüss (1998) and the 2003 WHO Guidelines, the RCT studies conducted in marine w aters in the U.K. (Fleisher et al., 1996; Kay et al., 1994) provide a more precise measure of exposure, water quality, and illness. Compared to RCT studies, those authors hypothesize that observational studies result in artificially low threshold and flat tened indicator

- response curves due to randomU.S. Environmental Protection Agency

December 2010 A

- 3 Table 4 . Who Classification Matrix for Integrating Microbial Water Quality as Measured by Enterococci Density with Sanitary Inspection Category

misclassification and self

- selection bias. 8 In this regard, the WHO expert advisors concluded
that

In view of the probably higher accuracy of their reported dose

- response relationships as compared to observational studies, it was decided to use the results of the randomized trials reported by Kay et al. [1994] and Fleisher et al. [1996] to underpin the [2003 WHO] guideline design process. Furthermore, a WHO expert group meeting in 2001 supported the application of the intestinal enterococci... as a suitable health criterion for both marine

an d freshwater environments

.

Thus, these U.K. RCT marine water trials, and especially the dose

- response curve for excess probability of GI illness and measured level of enterococci (see Table 5 and Figure 1 ), are the key studies used in the WHO report for derivation of numeric guideline values (see more below) for use, along with the results of a sanitary inspection (see Table 4 ), in assessing the microbiological quality of recre ational waters. These two related articles are summarized together below.

The 2003 WHO Guidelines include numerical microbiological criteria for enterococci (see Table
5 ; extracted Table 4.7 from WHO, 2003) that are explicitly b ased on the U.K. marine recreational water studies of Kay et al. (1994) and Fleisher et al. (1996) and were developed using a novel approach to disease burden assessment. Although the scientific rationale and mathematical basis for this approach is not pr esented in the 2003 WHO Guidelines, it is provided in detail in Kay et al. (2004) and is summarized below.

8 “Miscl assification” bias (e.g., attributing a daily mean water quality to all bathers) and “self

- selection” bias (e.g., the exposed bathers may have been more healthy and thus likely to bathe than those that did not) would be expected
to lead to an underestimati on of the illness rate (WHO, 2003).U.S. Environmental Protection Agency

December 2010 A

- 4 Table 5 . WHO Guidelines Values for Microbial Water Quality of Recreational Waters Using the 95th Percentile of Enterococci Density

The risk of GI illness following recreational exposure to surface waters is presumed to increase with increasing levels of indicator organism s . This does not imply that the indicator organisms cause illness; rather, it implies that presence of the indicators is consistent with conditions under which infections may be acquired. In their analysis of data from their RCT study of GI illness arising from recreational activities, Kay et al. (1994) used logistic regression to establish a model
for GI illness for bathers exposed to enterococci . For bathers exposed to waters with densities greater than 32 enterococci /100 mL, the probability of gastroenteritis is given by



## ( **)** 

# ( **)** 0866

. 0 1 ritis gastroente 1

**− −**  **= −** 

**−** b e P [1]U.S. Environmental Protection Agency

December 2010 A

- 5 where



## ( **) (**  **) **  ** **  ** ** 

**>**

**− −**  **≤ ≤** 

**− −** 

**=** 158 3561

. 2 32 158 20102

. 0 158 32 3561

. 2 32 20102

. 0

ent ent ent C C C b [2]

and C ent is E nte rococcus density (enterococci/100 mL). The value 158/100 mL corresponds to
the maximum density observed during the course of the study of Kay et al. and the value 32/100
mL is the estimate of the density below which bathers did not have an incidence of

ga strointestinal illness above the background level. A plot of what is referred to as the dose

response curve ( indicator

- illness curve ) corresponding to equations 1 and 2 is shown in Figure 1

. The solid line corresponds to the dos e

- response without the limiting value of 158/100 mL and
the dashed line is the dose

- response curve suggested by the authors in which the maximum response is set equal to that predicted for the maximum enterococcus density measured in the study.

Fecal indi cator densities vary greatly in recreational waters, and the ir distribution at a particular site is often modeled as log

- normal, given mathematically as



## ( **) (**  **)** 2 2
10 2 / log 2 1

s m C

ent ent e

s C p **− −**  **=**
**π** [3]

where m and s are the median and standard deviation of the log

- transform ed densities . For a large database of bathing water quality, Kay et al. (2004) estimated that m = 0.934 and s = 0.810. The corresponding distribution is plotted in Figure 2 , along with the proportion of bathers expected to have GI illness ( p (Gastoenteritis| C ent ) × p ( C ent ) ) and the dose

- response model described by equations 1 and 2.

In assessing the forgoing methodology for estimating risk of GI illness associated with bathing in surface waters, Kay et al. (2004) concluded t he following:

The pdf (probability density function) provides a simple means of assessing the probability of exposure to bacterial concentrations greater than and less than, for example, a threshold of effect or some upper limit value or standard. When c ombined with an appropriate dose

- response curve, the pdf facilitates the calculation of the population percentage getting ill at each increment of water quality above any threshold level and, through integration, the proportion of the exposed population be coming ill
overall.

Using this approach, it is possible for policy makers to specify an acceptable excess probability of illness and then to define the parameters of the pdf required (i.e., a geometric mean value or a
95 th percentile value given the knowl edge of the standard deviation of log 10 transformed
enterococci densities ) to limit the likely symptom incidence to the specified level or lower.

In developing the numeric criteria of the 2003 WHO Guidelines, it was decided to employ the pdf disease ris k assessment method described above to calculate the risk of GI illness and AFRI from exposure to recreational waters. The calculations were based on the dose

- response curveU.S. Environmental Protection Agency

December 2010 A

- 6 (see Figure 1 ) provided in Kay et al. (1994). Because the highest recorded enterococci exposure in that study was 158 CFU per 100 mL, the decision was made to not extrapolate the indicator

ilnness (referred to as “dose

- response” by Kay and colleagues ) curve into an area of “no data,” as predicted by the mathe matical form in the upper region of Figure 1 . It was, therefore, assumed that the excess illness probability remained constant at just under 40%, at de n sities exceeding 158 enterococci per 100 mL (see dotted line of Figure 1 ).

As can be seen in Table 5 , the WHO expert advisory group decided on a banded system, where the band divisions are equivalent to a risk of acquiring GI illness for (A) <1 in 100 exposures, (B) <1 in 20 expo sures, (C) <1 in 10 exposures, and (D) >1 in 10 exposures. Table 5 also includes equivalent risk levels for AFRI. As illustrated in Figure 7 , these risk levels are equivalent to approximately the 95 th p ercentile enterococci densities of <40, <200

, 9 and <500 enterococci per 100 mL, respectively, and are intended to represent “readily understood” levels of risk based on the exposure conditions of the key marine recreational water studies of Kay et al. (199 4) and Fleisher et al. (1996).

This basis for determining the microbiological quality of a recreational water is similar to that provided in the previously discussed proposed EU Directive (EP/CEU, 2006). The 95 th percentile value was chosen as an appro priate descriptor of the PDF because it describes the probability of encountering polluted water and focuses on water quality that is likely to cause illness (i.e., the upper part of the indicator distribution; see Figure 1 and Figure 2 ) (Kay et al., 2004).

The 2003 WHO Guidelines emphasize that these studies are primarily indicative of risks for healthy adult populations in sewage

- impacted marine waters in temperate climates. Studies that reported higher thresholds and case rate values for adult populations or populations of countries with higher rates of endemic waterborne disease suggest greater immunity in the adult population. Epidemiolog y studies that have focused on children have generally found th at GI illness (symptom) rates are higher in lower age groups (see Table 1 ). Because the U.K. studies did not assess children for ethical reasons, the 2003 WHO Guidelines may systematically underestimate risks to children (either because children may be more likely to become ill from a given exposure or because they may ingest more water than adults during recreation). Other population groups that may be at higher risk of disease than is indicated by the model of Kay et
al. (1994) include the elderly, immunocompromised persons, and non

- residents (who may be more susceptible to local endemic disease). If such groups are significant water users (bathers), the 2003 WHO Guidelines recommend considering them in local risk assessment a nd management efforts. As for the recent EU Directive (EP/CEU, 2006), management action in response to a recreational water environment classification indicating unacceptable fecal contamination can be both immediate (issuing health advisories) and long

- t erm (increasing pollution abatement measures).

9 As can be seen in Figure 2 , a 5% risk of GI illness is associated with a pdf 95 th percentile value of 185, which was subsequently rounded up to 200 enterococci per 100 mL by WHO expert advisors.U.S. Environmental Protection Agency

December 2010 A

- 7 3 2 1 0 1 2 3 4 0 0.1 0.2 0.3 0.4 0.5

0 0.1 0.2 0.3 0.4 0.5 95th Percentile = 40cfu/100mL, Proportion ill = 0.01

Log10 enterococci (per 100mL)Curve height

3 2 1 0 1 2 3 4 0 0.1 0.2 0.3 0.4 0.5

0 0.1 0.2 0.3 0.4 0.5 95th Percentile = 200cfu/100mL, Proportion ill = 0.05

Log10 enterococci (per 100mL)Curve height

3 2 1 0 1 2 3 4 0 0.1 0.2 0.3 0.4 0.5

0 0.1 0.2 0.3 0.4 0.5

Proportion ill Enterococci density 95th Percentile = 500cfu/100mL, Proportion ill = 0.10

Log10 enterococci (per 100mL)Curve height

Figure 7 . Water Quality and Illness Relations for WHO Recreational Water Guideline Values
As noted previously, it is important to emphasize that the 2003 WHO guideline values derive d above from the two marine recreational water studies are specifically allowed to apply to freshwaters. In this regard, the 2003 WHO Guidelines conclude d the following :

There is inadequate evidence with which to directly derive a water quality guideline value for fresh water. Application of the guideline values derived for seawaters to fresh waters would be likely to result in a lower illness rate in freshwater swimmers, providing a conservative [i.e., more protective] guideline in the absence of suitab le epidemiological
data for fresh waters.

This is because GI illness rates in marine recreational waters are consistently higher than in fresh recreational waters (e.g., U.S. EPA, 1986). This difference may be due to the more rapid die

- off
of indicator bacteria than pathogens (especially viruses) in seawater compared with fresh water. This would result in more pathogen s in marine water than in fresh water when indicator organism densities are identical, which in turn would logically lead to a higher swim ming

- associated GI illness rate in marine recreational water swimmers (WHO, 2003). Interestingly, the meta

analysis of Zmirou et al. (2003) reached the opposite conclusion:U.S. Environmental Protection Agency

December 2010 A

- 8 ...should standards be set at the same level for marine and [fresh] recreational wat ers? ...our analysis revealed that the risk associated with the same concentration of enterococci is greater in fresh water than marine water

— a result that might point out the differences between saline and nonsaline water. However, the evidence is still w eak and warrants further study.

The 2003 WHO guideline values also apply to estuaries (transitional waters) where salinity is highly variable. For example, it would be difficult to decide whether a freshwater or marine standard should be applied to a gi ven compliance location (and at what time), if separate marine and freshwater guideline values were to be specified.