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

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

Comparison and Evaluation of Epidemiological Study 

Designs of Health Effects Associated with Recreational 

Water Use

U.S. Environmental Protection Agency

Office of Water

December 2010
U.S. Environmental Protection Agency

December 2010 i

DISCLAIMER

This report is intended for internal 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 reviewed 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 interpreted as 

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

December 2010 ii

ACKNOWLEDGMENTS

Questions concerning this document or its application should be addressed to the EPA Work 

Assignment Manager (WAM):

John Ravenscroft (WAM)

USEPA Headquarters 

Health and Ecological 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 Assignments 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:

Jeffrey 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 Environmental Consultants, Inc.
December 2010 iii

CONTENTS

Disclaimer........................................................................................................................................ i

Acknowledgments........................................................................................................................... ii

Contents.........................................................................................................................................iii

Tables and Figures.......................................................................................................................... v

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

1.1 Objectives......................................................................................................................... 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 that 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 Quality 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 Analyses 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 ............................................................... 36

5.4 Water Quality ................................................................................................................. 37

5.5 Population Investigated.................................................................................................. 38

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

5.7 Direct Approaches to Compare RCT and PC Results.................................................... 39
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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-1
December 2010 v

TABLES AND FIGURES

Table 1. Comparison of Major Conclusions from Three Meta-Analyses of Recreational Water 

Epidemiology 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 Category .................................................... 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. Probability 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 Gastroenteritis in Marine Water.................... 41

Figure 6. Epibathe Meta-analysis Forest Plots of Gastroenteritis in Freshwater......................... 42

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

............................................................................................................................................. A-7
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1. EXECUTIVE SUMMARY

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 epidemiology studies have 

been conducted in Europe and the United States that have estimated the risks associated with 

both marine and freshwater recreation. Two different types of study were conducted, (1)

experimental (randomized control trials [RCT]); and (2) non-experimental (prospective followup or cohort [(PC]) studies. The studies also considered different exposure measures 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 it 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 might be the better option. 

1.1 Objectives

This draft report includes the following information:

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

waters.

2. Detailed descriptions of RCTs conducted in:

• marine recreational waters in the United Kingdom (U.K.),

• fresh recreational waters in Germany,

• marine recreational waters in Florida, and

• fresh and marine recreational waters in the European Union (EU).

3. An explanation of the epidemiological bases for the 2006 EU Bathing Water Quality 

Directive and the 2003 WHO Guidelines for Safe Recreational Water Environments.

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

5. Analyses and additional data that could facilitate comparison of the reported RCT and PC 

results.

6. Prioritized recommendations to facilitate comparison of RCT and PC studies.

1.2 Key Factors Limiting Comparisons between RCT and PC Studies

There 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 significantly influence individual exposures and the observed rates of 

illness. These study characteristics include the following:
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December 2010 2

• how water quality (i.e., indicators) is assigned as an exposure variable to bathers;

• duration and/or intensity of exposure; 

• definition of illness and duration of incubation;

• regulatory conditions and 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 investigated 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 Recommended Activities

To determine if a comparison between RCT and PC studies is possible, additional analyses 

and/or data are necessary. 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 Assessment of Recreational (NEEAR) Water Study 

statistical methods and exposure/illness definitions can be applied and if so, conduct a reanalysis. This analysis will indicate whether RCT and PC results can be directly 

compared and will help to determine whether the observed differences in existing 

epidemiology studies are due to the study design or other factors. (Discussions with Dr. 

David Kay regarding Epibathe are ongoing).

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

results 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 analyses 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 ingested 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 types for 

samples collected at multiple depths. This information will help characterize the extent 

to which the method of allocating exposure to subjects influences the indicator-illness 

relationship. If indicator density is highly variable in short spatial and temporal frames, 

differences in exposure sampling prescribed for RCT versus PC based epidemiology

studies will have less influence on study results.

5. Conduct an RCT sub-study within a PC epidemiology 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-analysis of human-impacted waters for epidemiology 
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studies conducted worldwide. Otherwise, use the information to supplement the current 

report and provide an updated qualitative meta-analysis.
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2. INTRODUCTION

Epidemiological methods have estimated endemic illness risks associated with contaminated 

recreational waters. Over the past 50 years, several dozen epidemiology studies have been 

conducted around the world evaluating endemic illness risks associated with recreational waters. 

Most of these studies were conducted 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 epidemiology 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 epidemiology study 

designs have been used—prospective 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 

Environmental Assessment of Recreational (NEEAR) Water Study. Comparing the results from 

the NEEAR epidemiology 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 indicator1

(typically Escherichia coli, Enterococcus, Staphylococcus, 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 

epidemiology study design (PC vs. 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 their major conclusions regarding the use of bacterial indicators to assess 

adverse health effects resulting from exposure to sewage-contaminated marine and fresh 

recreational waters2

 1 Environmental waters, including recreational waters, may contain many potentially pathogenic microorganisms, including 

bacteria, viruses, 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 incidence 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 addition, several studies in the United 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. However, the results of these recent studies have not yet been synthesized by meta-analyses.
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Table 1. Comparison of Major Conclusions from Three Meta-Analyses of Recreational Water Epidemiology Studies

Conclusion

Prüss, 1998 Wade et al., 2003 Zmirou et al., 20031

Overall Marine Fresh Overall Marine Fresh Overall Marine Fresh

Number of studies in metaanalysis 222 15 6 27 17 10 182 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 illness symptoms 

assessed Yes Yes Yes Yes Yes Yes No No No

GI illness rates higher in 

lower age groups Yes NA NA Yes3 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 Yes Yes Yes Yes Yes4 Yes4 Yes4

Supports use of fecal 

coliforms as an indicator NA NA NA No No No Yes4 Yes4 Yes4

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 excluded 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 one 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).
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freshwater beaches), the characteristics of the study cohort 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 and 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 epidemiology studies were 

different designs are analyzed together.

Wade et al. (2003) surveyed epidemiology studies of recreational exposure to surface waters and 

developed a weighted regression model relating the log base 10 indicator level 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 and RCT sources for studies reviewed for this draft report. Their 

analyses indicated that E. coli and enterococci are useful predictors of GI illness in marine and 

freshwaters, with E. coli superior to enterococci for predicting illness in freshwaters. Sources 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 could result in different exposures), 

and whether studies focused specifically on children.

Prüss (1998) conducted a meta-analysis of epidemiology 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 indicator 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 indicator 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 recreational 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 with 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 epidemiology 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 sources 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 swimmers to nonswimmers as the dependent 

variable. Random effects variances were used when heterogeneity was observed. Data selection 
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December 2010 7

was conducted to minimize heterogeneity, resulting in the notable exclusion of data from studies 

by Cabelli et al. (1982) and U.S. EPA (1983, 1984) because those studies associated seasonaveraged indicator densities with swimmers rather than indicator density taken on the day or at 

the time of swimming. Additionally, 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, it is important to better 

understand the differences between the RCT 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 study types. To that end, this report addresses the 

following objectives: 

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

Wiedenmann et al. (2006), Fleisher et al. (2010), and the EU Epibathe program ( ECEpibathe, 2009a,b);

2. to provide 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 data;

3. to provide a discussion of additional activities which could aid in conducting valid 

comparisons between PC and RCT studies; and

4. to identify 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 epidemiology 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 presents detailed descriptions and comparisons of PC and RCT study designs, as 

well as detailed descriptions of the largest and most recent PC epidemiology studies conducted 

by EPA, in support of development of new or revised water quality criteria.
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December 2010 8

2.2.1 Comparison of PC and RCT Epidemiology 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 epidemiology study, while the PC is considered a nonexperimental epidemiology study. 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: the 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: in the RCT design, swimmers are asked to complete specific 

activities such as immersing their head a minimum number of 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: the EPA NEEAR PC studies target the entire beach 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: the 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 layout to assess average water quality over a given time/space dimension. 

• Other differences: because 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 appropriate period of 

time to compare illness incidence (e.g., GI illness) 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 causes 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 potential 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. 

The NEEAR PC marine recreational water epidemiology study (Wade et al., 2010) provides an 

example of a large PC epidemiology study. In those studies, EPA conducted surveys on 

weekends and holidays between May and September at marine beaches in Rhode Island, 

Alabama, and Mississippi. U pon arrival, beachgoers were provided a pamphlet describing the 
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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 member 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, asthma, 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 consumption. 

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 epidemiology studies (Prüss, 1998; Wade et al., 2003; 

Zmirou et al., 2003), the majority of epidemiology studies of risks associated with recreation 

conducted to date have had PC designs. PC recreational water epidemiology studies have been 

conducted in numerous locations worldwide, such as studies conducted in the United States (e.g., 

Cabelli et al., 1982; 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., Cheung et al., 

1990), New Zealand (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. 

The NEEAR Study used a PC design at fresh and marine recreational beaches impacted by 

POTWs over the past decade (Wade et al., 2006, 2008, 2010). 

2.2.1.2 Randomized Control Trials

The other major epidemiology design used for recreational waters is the RCT. The RCT is an 

epidemiological experiment in which the study subjects are randomly allocated into groups to 

receive an experimental procedure, manner, or intervention. The random allocation tends to 

prevent section bias. For recreational water exposures, the groups are bathers and nonbathers

(swimmers vs. nonswimmers3

Kay et al., 1994

). The bathers are instructed as to their time in the water and 

activities. Similar to the PC study, bathers and nonbathers must be followed for an appropriate 

time to assess illness incidence and the effect of other biases and potential confounders. 

Exposure-response analyses may be conducted. Among the purported merits 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) account for non-waterrelated risk factors ( ). The most significant limitations of RCT studies include 

sample sizes typically smaller than those for comparable PC studies, exposures not necessarily 

typical of those experienced by beach-goers, 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 report
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December 2010 10

The EU recently adopted Directive concerning the management of bathing water quality

(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 POTW- and nonpoint source (NPS)-

impacted fresh recreational 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 Studies

2.2.2.1 NEEAR Epidemiology Study Design

The objective of the NEEAR Water Study was to develop a mathematical relationship of adverse 

health effects from swimming in sewage polluted recreational waters to the quality of that water 

as measured by an indicator of human fecal contamination, using new and faster measurement 

methods. Although several different epidemiology study designs were initially considered, only 

the RCT and 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) Guidelines 

for recreational waters (see Appendix A). The RCT design was recently employed by German 

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 in the United States (personal 

communication, Tim Wade, EPA, 2008). 

The NEEAR study PC design (Wade et al., 2006, 2008, 2010) 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 design, 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 easy 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 

variability in water quality (Wade et al., 2006, 2008, 2010). 

A three-part health survey (enrollment, exit interview, and follow up telephone interview) was 

administered to agreeable adult (18 years or older) beach-goers at each of the beach study sites. 

Adults 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 10-12 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 exit 
U.S. Environmental Protection Agency

December 2010 11

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

telephone 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 interviews, 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 reaction [qPCR] CCE/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 their 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 possibility that head immersion might 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 outcome 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 accuracy 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 studies 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).
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December 2010 12

These beaches were selected because they fulfilled the following specific 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) large 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). Three 

journal articles have been published based on the NEEAR freshwater studies: 

• Haugland et al. (2005) compared qPCR and traditional culture-based Enterococcus

measurements in freshwater at two (of four total) Great Lakes recreational beaches for 

samples taken in the first year of the NEEAR Water Study;

• Wade et al. (2006) describes the associations of swimming-associated GI illness and 

water quality measures (qPCR test results of Enterococcus and Bacteroides, another 

bacterial fecal contamination indicator) taken at the same two Great Lakes’ beaches; and

• Wade et al. (2008) expanded on the results of Wade et al. (2006), adding analyses 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 days 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 number of households and individuals were roughly 

evenly-distributed between the Lake Erie and Lake Michigan beaches.

As described above, water samples were analyzed for the traditional fecal indicator bacteria, 

Enterococcus4

Wade et al., 2008

and the alternative fecal indicator Bacteroidales. 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 were

frequently below detectable limits, making results difficult to interpret. As a result, the NEEAR 

study focuses on the relationship between the qPCR Enterococcus assay and health effects 

(primarily 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 sampling 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, water samples were collected three times a day (8:00 

AM, 11:00 AM, and 3:00 PM) on weekends and holidays. For each sample event, two 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 CCE) 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 species of bacteria (see WHO, 2003 and NRC, 2004 for further 

information). 
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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. The base 10 logarithm

(log10) 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-regression 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 CCE measures and incidence 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 CCE 

was associated with GI illnesses at freshwater Great Lake Beaches impacted by point sources of 

sewage based on a definition of swimming that included body immersion. Specifically, higher

Enterococcus qPCR CCEs were positively and significantly associated with swimmingassociated GI illness; the strength of association between GI illness and qPCR CCEs 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, although EPA’s ability to make valid 

conclusions among this potentially sensitive population was limited because they swam 

infrequently and reported the lowest incidence of illness. The association between the 8:00 AM 

Enterococcus qPCR CCE average and GI illness was nearly identical to association with the 

daily average qPCR CCE. In addition, the association between Enterococcus and GI illness 

strengthened as time spent swimming in the water increased. Nonenteric illnesses were not 

consistently associated with level of Enterococcus qPCR CCEs; however, rash and earache 

occurred more frequently among swimmers than nonswimmers. Notably, Enterococcus qPCR

CCE 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 relationship between the 

density of fecal indicators 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 populations of at least 15,000. Based on historical 
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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 similar to the freshwater studies as 

summarized above (Wade et al., 2006, 2008). The health endpoints considered included GI 

illness (as defined above); upper respiratory illness (any two of sore throat, cough, runny nose, 

cold, or fever); rash; eye 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 phylum 

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 and 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 analyses 

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 

relationship 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 differences in baseline 

illness. Covariates which could plausibly affect 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

preceding 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, use of insect repellent and sunscreen, and consumption of raw or 

undercooked meat. Environmental 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 temperature; 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 eligible 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 mL) and Goddard Beach the lowest (4 
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December 2010 15

CFU/100 mL). Individual samples of Enterococcus CFU ranged from below detection to 3000 

CFU/100 mL. Overall, 142 samples (11.5%) exceeded 104 CFU/100 mL, 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 significantly associated with exposure to 

Enterococcus and Bacteroidales CCE∆∆ 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) were also significantly associated with both GI illness and diarrhea. Associations 

between GI illness and fecal Bacteroidales were generally positive but not statistically 

significant. Clostridium CCE∆∆ showed a strong statistically significant 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 significant. None 

of the associations with non-enteric illnesses were consistently 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 strengthen with more intense or 

prolonged water exposure, although results were based on few subjects. There was no evidence 

of systematic differences in the relationships between GI illness and diarrhea and Enterococcus

or Bacteroidales CCE exposure across the three beaches.

The odds of GI illness was higher among swimmers compared to nonswimmers 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/100mL compared to days when 

Enterococcus was below 35 CFU/100 mL.

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.
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December 2010 16

3. SUMMARY OF RCT WATER EPIDEMIOLOGY STUDIES

3.1 Marine RCT Studies Conducted during 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 results 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 to 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 adequately 

controlled for.” The authors indicate that these problems were overcome by use of a RCT 

epidemiology 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 for 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 epidemiology 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 recruited within several weeks before each of 

the studies were conducted from 1988 to 1992 at U.K. marine beaches. Because 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 

previous 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 heads exactly three times. 

 The water in the recreational 

area near to where the participants bathed 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 ingested by the participants is not known nor is it known if water was actually swallowed
U.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 indicators (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 indicators 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 

interviewed 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, consumption 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 

reported 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 enterococci 

measured at chest depth. Only enterococci, measured at chest depth, showed an indicator-illness 

relationship 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 significant increase in the 

occurrence of AFRI at levels at or above 60 CFU enterococci/100 mL. A significant relationship

with GI illness was identified when enterococci densities exceeded approximately 32 CFU/100 

mL. 

3.2 Freshwater RCT Studies Conducted in Germany

A series of RCT epidemiology 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, all 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 included treated and untreated 

municipal sewage, agricultural runoff (non-point source pollution), and fecal contamination from 

water fowl. 

Briefly, local volunteers, including children 4 years or older6

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 

interviewed 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.
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December 2010 18

Bathers were exposed for exactly 10 minutes in 1 of 4 roped-off zones (each divided 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 swallowed 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 stayed. 

Exposure was defined two different ways. The first definition was “10 minutes bathing 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. The minute-specific densities during which the head was immersed 

were multiplied by number 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, 

intestinal 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

cold, 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 movements 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 stomach 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 time period of 3 weeks than for a period of 1 week.

These 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 metrics 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.
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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 organisms in water.

It would be impossible to set imperative values for 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 indicate 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 authors 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 the 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 freshwaters currently 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 funded 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:
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December 2010 20

1. To add value to existing epidemiological (RCT) data sets through a new analysis that 

integrates 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 epidemiology 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 Hungary, 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 derived 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 measured 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 questionnaire 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 exposure. 

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 completed 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 methods 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 and 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 

Imperative 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), were 
U.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 and 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 in 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 on 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), the 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 with freshwaters containing similar fecal 

indicator organism densities. 

As noted previously, the 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 waters 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 nonbather 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 Spanish data 

sets combined) which have a 95th 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 “Level 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 microbe densities and reported symptoms in human subjects with randomexposure assignment and intensive individual microbial monitoring in this environment (Fleisher 
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December 2010 22

et al., 2010; Sinigalliano et al., 2010). This study was the first RCT in the United States, and the 

first RCT in (sub)tropical non-point source recreational marine waters globally. The datacollection 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. Participants 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 

consumption, 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 assigned to either the (exposed) 

bather group or the (unexposed) nonbather group.

Bathers were required to spend 15 minutes 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 

epidemiology 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 corresponding 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.

Participants randomized to be in the nonbather group were restricted to an area distant from 

water and sand exposure. Out of 1341 adult regular bathers randomly assigned to bather or 

nonbather 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 hour period. “Acute febrile 

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 nose 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, respiratory illness, and skin illness relative to nonbathers. 

After controlling for non-water-related risk factors/possible confounders for each of these 
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December 2010 23

illnesses bathers were 1.79 times more likely to report GI illness relative to nonbathers; bathers 

were 4.46 times 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 measured by membrane 

filtration and 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 individual 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 addition, there was evidence for an indicator-illness

relationship between bather exposure to increasing levels of enterococci and an increased risk of 

reporting skin illness. Perhaps the most unique feature of this study is that it is the only 

epidemiology study 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.” Thus, the basic unit of measurement was the individual bather 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 risk, 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 accurate 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 correspondences 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. 
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December 2010 24

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

Design/Issue 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 90th

and 95th percentile 

evaluation of 

enterococci and E. 

coli densities 

(FW/MW)

Based on a 95th

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 95th

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

Acceptable/

attributable risk of 

GI illness

No-observedadverse-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 

analyses for ≤ 10 

years old)

elderly (≥ 55 years 

old)

Yes (children ≥ 4 

years old)

Yes (children ≥ 4 

years old)

No
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December 2010 25

4. ANALYSIS OF STUDY DESIGNS: DIFFERENCES THAT COULD AFFECT 

COMPARABILITY

This section presents a discussion of the limitations and precautions of comparing and/or 

integrating data from RCT and PC epidemiology studies. 

4.1 Summary of Published Commentary on Epidemiological Design Comparison

The epidemiology studies that underpinned EPA’s 1986 RWQC were the most sophisticated 

studies to have been conducted 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 estimation, alternative statistical treatment of the data indicated substantially 

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

conducted.

The WHO took a different approach than EPA, in part, to address the perceived 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 Guidelines 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 Prüss 

[1998]... The dose-response relationships from these studies were plotted...and it was 

noted that the UK randomized trial results [Kay et al., 1994] showed steeper doseresponse curves than the prospective cohort studies. This was attributed to the enhanced 

control of bias facilitated by the randomized 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 quality 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 for 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 indicatorillness relationship (see Figure 1) in the U.K. RCT studies with the probability density function 

(pdf) of log10 transformed indicator densities observed at numerous sites 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 indicator-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 95th

percentile). 
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December 2010 26

Figure 1. Dose-Response Relationship Used in the Derivation 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 mathematical 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 model reported in Kay et al. (1994) 

(i.e., the curve shown in Figure 1). In this extension, they evaluated Enterococcus densities with 
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December 2010 27

means ranging from 1 to 1000 per 100 mL (note that the Kay and colleagues paper effectively 

solved the same integral for single values that resulted in one case of GI illness in 100, 20, and 

10 exposures). A detailed explanation and graphical illustrations are presented in Appendix A

The resulting curve from Wymer et al. (2005) is shown in 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 further:

...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 USEPA 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 diversity 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:
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December 2010 28

• They emphasized that exposure is a “probabilistic” event that depends on the distribution 

of enterococci in the bathing 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 epidemiologic 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 suggested that if the acquisition of “exposure” (water quality) data in epidemiology

studies 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.

• Large spatial and temporal variations 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 concluded that basing 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 concentrations 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 study approach, methods, and data analysis 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 

are the key to understanding if or how the results are comparable. Those differences are 

described below.

4.2.1 Assignment of Water Quality to Bathers

The assignment of indicator organisms as an exposure variable to the study participants is very 

different in PC 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 daily 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 a 
U.S. Environmental Protection Agency

December 2010 29

better predictor of illness among swimmers exposed later that day). Thus, in EPA’s NEEAR

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, in 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 Water Exposure

The definition of swimmer/bather varied 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.

Swimmers in the NEEAR PC studies were defined as those who self-reported immersing 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). Levels of Enterococcus CCE by qPCR

were consistently higher in the shallower water. The EPA PC results demonstrate that 

Enterococcus qPCR CCE was associated with GI illness at fresh and marine water beaches 

impacted by point sources of sewage based on a definition of swimming that included body 

immersion. Furthermore, a more stringent definition of swimming that required head immersion 

did not substantially alter the results, suggesting that head immersion is not a critical determinant 

of whether and how much water is swallowed. However, Wade et al. (2008, 2010) found that

the association between increasing levels of Enterococcus qPCR CCE and increased incidence of 

GI illness strengthened as time spent swimming in the water increased. 

Adult swimmers 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 immerse 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 below 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 an indicator-illness relationship for both GI illness and 

AFRI in marine recreational waters. The recent EU RCT studies (Epibathe) used a similar 

protocol for swimmer exposure. 

In the German RCT study (Wiedenmann et al., 2006), bathers were exposed 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, 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. Thus, it seems likely that most head immersions were in 

swimming zones with deeper water. For each minute of the trial, microbial water densities were 

calculated in both the swimmer and the nonswimmer zones. The microbial densities of each of 

the 10 minute periods were assigned to each of the bathers in their individual exposure area, 

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 immersion,” 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 head 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 minutes

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 exposure 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-minute 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 mandatory 

head immersions). Interestingly, the EPA PC studies 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 potentially significant, because the rate of water 

ingestion could vary with extent or duration of immersion. Thus, it is possible that the different 

“exposures” resulting from swimmer definitions in the PC and RCT studies resulted in 

significantly different volumes of water ingested.

4.2.3 Definition of GI Illness

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 studies (U.S. EPA, 1983, 1984) were 

principally based on “highly credible gastrointestinal symptoms” (HCGI) that included all cases 

of vomiting, instances of diarrhea that were accompanied by a fever or that were disabling, or 
U.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 initial 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 after the beach exposure (Kay et al., 1994). This 

definition was also used in the Epibathe studies (EC-Epibathe, 2009a,b). Notably, in 1-week 

post-exposure interviews, 34.3% of the GI illnesses were reported while the remaining GI 

illnesses (65.7%) manifested 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, and the crude attributable risks 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 three 

or more runny stools within a 24-hour 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” definitions 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 

studies. 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 shorter incubation periods). 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 Quality

In all of the PC and RCT recreational water studies that have been reviewed in this report, the 

recreational water body that was evaluated 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 Bathing 
U.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 that were evaluated as part of the 

NEEAR Water Study (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). The 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. Moreover, the 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). The Miami RCT study 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 

sources of domestic sewage (Fleisher et al., 2010).

4.2.5 Population Investigated

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 the RCT 

studies, or were those that independently decided (not recruited) to go to a particular beach on 

the study day.

The U.K. marine RCT studies (Kay et al., 1994; Fleisher 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 

their study. The German freshwater RCT studies (Wiedenmann et al., 2006) and the EU 

Epibathe studies recruited healthy local volunteers including those as young as 4 years old to 

participate. Children less than 4 years old were not recruited as they were considered to be 

potential sources of direct fecal contamination. 

The NEEAR fresh and marine PC studies included criteria for site selection areas that comprise 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 postexposure questionnaires for all members of the household that visited the beach.

4.2.6 Temporal Variability of Molecular and Culturable Indicator Counts

A key factor that influences the indicator-illness relationship in epidemiological investigations is 

nondifferential misclassification bias (Fleisher, 1991; Prüss, 1998; Kay et al., 2004; Kay 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 exposures. 

Nondifferential misclassification bias nearly always leads to erroneously shallow indicatorillness relationships, since it results in either high illness rates associated with low indicator 

densities or low illness rates associated with high indicator densities.
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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 epidemiology study design that minimizes these 

two kinds of imprecision therefore also minimizes misclassification bias (Wiedenmann et al., 

2006). Proponents of the RCT epidemiology study design have indicated that an RCT design 

minimizes the imprecise assignment of microbiological monitoring results relative to the PC 

design.

Recent 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 

commercial 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 trends are observed for indicator 

organisms as enumerated by qPCR or other molecular methods. If these trends are also true in 

diverse aquatic environments for Enterococcus and/or Bacteroides as enumerated by qPCR, then 

this information would be very valuable in (1) designing sampling protocols, and (2) developing 

scientifically valid water quality criteria.

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

The primary differences between the seminal recreational water PC and RCT epidemiology 

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

• populations investigated in the various epidemiology studies.

Based on the differences noted above, limitations exist with comparing and combining results 

from these two study designs. In 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.
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5. OPTIONS FOR ADDITIONAL ANALYSES TO FACILITATE COMPARING RESULTS 

ACROSS STUDY DESIGNS

This section presents activities that could be conducted to help facilitate valid comparisons of 

RCT and PC study results. The major study features that hinder comparisons between these 

types of studies were introduced and discussed in the preceding section. Thus, the focus of this 

section is to describe activities that could be undertaken to harmonize the studies and explain the 

rationale for those 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 epidemiological designs is how water quality is 

assigned to each 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 these 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 organisms in the recreational waters correspond to the overall level of fecal 

contamination and thus, with the pathogens that cause illness. Under this assumption, there 

exists some relationship between the density of the indicator organisms and the probability 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 observed in the water and the probability of 

illness is expressed in an indicator-response curve (Parkhurst et al., 2007). 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 from 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, 

and 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. 

Extensive debate exists in the literature regarding the relative merits 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 study, 

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) studies 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.
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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 EMPACT beach studies demonstrated significant variability among the 

beaches based on the sampling plans used. Recent research (Boehm, 2007) 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 samples are taken at three 

times during the day or immediately 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 an 

appropriate sampling period. More samples provide not only greater statistical power but also 

alternative statistical measures of water quality (e.g., maximum observation) 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 

fractal:

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 sample 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 organisms 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 environmental 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 studies 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. The 

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.
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December 2010 36

5.2 Swimmer Exposure to Water Quality

Another distinguishing attribute of the two epidemiological designs is the definition of 

“exposure” that is used. For 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 

(usually 10 minutes). In the PC studies, results are typically reported for subjects who selfreported “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 probable 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 are available (Dufour et al., 2006) indicate ingestion 

volumes of 37 and 16 mL for 45 minutes of unstructured activity in swimming pools for nonadults and adults, respectively. The extent to which these different epidemiological protocols 

result in exposures different than that reported by Dufour and colleagues 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 studies, 

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 results of the study. 

5.3 Definition of GI Illness and Reporting Period

There are clear differences in the definition of GI illness across the various epidemiology studies 

considered in this report. For the U.K., EU (Epibathe), and U.S. (Miami) RCT studies, 

gastroenteritis was defined as any case of vomiting or diarrhea plus any case of either indigestion

or nausea accompanied by fever (Kay et al., 1994; EC-Epibathe, 2009a,b; Fleisher et al., 2010). 

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

within 1-week post-exposure period that while the remaining GI illnesses (65.7%) manifested in 

8-21 days post-exposure. In contrast, and as noted previously, Wiedenmann et al. (2006)

concentrated their analyses on the results obtained 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 stools 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 HCGI that included all cases of vomiting, 

instances of diarrhea that were accompanied by a fever or that were disabling, or cases of nausea 
U.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 recreational 

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) then 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, most 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 curves 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) RCT 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 different because they could not be conducted at beaches that were 

deemed unacceptable in terms of microbiological water quality. Furthermore, since the 

criteria/standards for microbial water quality were different, it is possible that a confounding 

factor is present with respect to comparing the results of these 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 more common in the United 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 standards could result in different relationships between indicators 

and pathogens. These differences could manifest themselves as different rates and 

characteristics of illness caused by exposure to different pathogens at POTW-impacted 

recreational water sites (Soller et al., 2010). 
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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 

retrospective 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 exclude data 

collected on days when the U.S. criteria for enterococci was exceeded (U.S. EPA, 1986). The 

analysis could be considered a sensitivity analysis to determine whether different conclusions 

would be reached if the studies had not been conducted on the days that U.S. criteria were 

exceeded. Such a retrospective analysis could partially address the possible biases due to 

exposure differences due to different water quality standards. However, this approach would not 

address the potential effects of the different standards on the differences in the ratios and 

pathogens that result from different types 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 epidemiology study is the population (or subpopulation) 

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, this difference has been at least partially resolved (Wiedenmann et al., 2006; ECEpibathe, 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 study sites were selected to ensure the 

population in the study included a broad age range of swimmers, including children, teenagers, 

and adults (Haugland et al., 2005).

There are differences between the indicator-illness relationships in young subjects and those of 

the general population (Wade et al., 2008). In freshwater, children 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 epidemiology 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 risks to 

specific portions of the population (children in this case). 

5.6 Relationship between 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, all of the other epidemiology studies discussed in this draft report used 

culture-based methods to enumerate fecal indicator organisms and characterize water quality. 
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Ideally, these molecular method-based results would be comparable 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 non-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 use 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 analyze the results using both sets of data in a consistent manner to 

determine how to appropriately compare epidemiology studies that base their water quality 

evaluations on different microbiological 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 an RCT in Parallel with a PC Study

The importance of temporal and spatial variability of water quality was highlighted above and 

the implications for comparing results from epidemiology 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 epidemiology study by leveraging a 

carefully designed water quality 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, similar population, etc.) while simultaneously 

minimizing costs because the water quality component could serve for both components of the 

study.

5.7.2 QMRA Translation between RCT and PC

Another approach is to use a QMRA framework to translate results from an RCT to 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 more RCT study. Using the published relationship between the fecal 

indicator and adverse health effects (GI illness), predicted mean probability of illnesses would be 

computed for each individual in the study (or studies) using a predicted volume of water ingested 

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 norovirus is the primary etiologic agent of concern, provided that the RCT was conducted in 
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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 Diagram of a QMRA-based Approach to Translate RCT Results to a 

PC Paradigm

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 

samples 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 RCT 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” study vs. the geometric mean fecal indicator organism densities that which 

would be comparable to other PC studies.
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December 2010 41

5.7.3 Meta-Analysis of RCT and PC Studies

If the activities described above allow meaningful comparisons of RCT and PC studies, a metaanalysis of similar studies (e.g., studies 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 the EU meta-analysis conducted on marine and freshwaters, respectively (ECEpibathe, 2009a,b). EU marine and freshwaters suggest elevations in illness in the bather 

cohorts. However, results from freshwater studies do not display a consistent incremental 

elevation in odds ratio as the exposure increases. A similar analysis could be conducted that 

includes all similar studies from the United States and EU to provide an extremely robust dataset. 

The meta-analysis should include consideration of the setting (marine vs. Great Lakes vs. fresh 

impounded vs. fresh flowing) as well as the suspected dominant fecal pollution source(s).

Figure 5. Epibathe Meta-Analysis Forest Plots of Gastroenteritis in Marine Water
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Figure 6. Epibathe Meta-Analysis Forest Plots of Gastroenteritis in Freshwater

5.8 Interactions between 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 there 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 this 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/or 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; 
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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 corresponding relationships 

between the indicators and the pathogens, as measured by those methods.

Adding to these complexities, 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 variability include the 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 for 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 confound 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 not 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 epidemiology studies. Further, there might 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 interactions could be 

site-specific. 
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6. RECOMMENDED ACTIVITIES AND CONCLUSIONS

When the available epidemiological data are compared, significant differences are observed in 

the relationships between exposure to recreational waters and related incidence of illness. Based 

on the information described in this draft report, the extent to which the differences observed in 

the outcomes of epidemiology studies are due to differences in the study design (RCT or PC) or 

are due to other differences (e.g., inter-site variability, differences 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 

treatment, topography, flow, and/or substrate). However, some of this variability might also be 

attributable to other factors such as differences in sampling protocols, collection, and analysis, as 

well as other issues. 

Differences between study designs 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 epidemiology studies, the 

drivers in these differences are critical. Even for 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 assumed directly comparable. Further,

when attempting to directly compare the results or pool the data between studies of different

designs, it may 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 

significantly 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 different designs, a prioritization of the factors of greatest concern is 

needed. In addition, some of the observed effects during an epidemiology study could be caused 

or influenced by parameters that were not controlled for in the study. The following prioritized 

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 of an RCT study to obtain the raw data from that study 

and re-analyze the results using the statistical methods employed by Wade and colleagues 

for the NEEAR studies. Such an analysis will provide an indication of whether or not 

results from RCTs and PCs can be compared directly and will help to answer the question 

of whether the differences observed in existing epidemiology studies are due to the study 

design or other factors. In this regard, initial contact has been made with Dr. David Kay.
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2. Use a QMRA framework to translate results from an RCT study to a comparable PC 

study. 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 ingested is a critical 

component, conduct 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. Extend the work reported by Boehm (2007) using both culture- 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 influences 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 epidemiology studies will not have a large 

influence on study results.

5. To verify the results of the above activities, conduct 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 Conclusions

The following information has been compiled in this draft report:

1. Detailed descriptions of the 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 studies in the United 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 compare the reported results from 

RCT and PC studies. 

5. Prioritized recommendations for activities to help compare the reported results from RCT 

and PC studies. 

Based on this information, we conclude that with the information and techniques currently 

available it would be extremely difficult and dubious to directly compare relationships between 

indicator density and incidence of illness from previously conducted RCT and PC studies 

without additional analyses or collection of additional information. Further, we conclude that in 
U.S. Environmental Protection Agency

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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 

analyses using data from both RCT and PC studies.
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Escherichia Coli. EPA 821R97004, U.S. Environmental Protection Agency, Office of Water, Washington, DC.

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Recreational Waters. EPA 600/R-04/023. U.S. Environmental Protection Agency, Office of Research and 

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their Use in Criteria Development. U.S Environmental Protetion Agency, Health and Ecological Criteria Division, 

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Wade, T.J., Calderon, R.L., Sams, E., Beach, M., Brenner, K.P., Williams, A.H., and Dufour, A.P. (2006) Rapidly 

measured indicators of recreational water quality are predictive of swimming-associated gastrointestinal illness. 

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Wade, T.J., Calderon, R.L., Brenner, K.P., Sams, E., Beach, M., Haugland, R. et al. (2008) High sensitivity of 

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APPENDIX A. OVERVIEW OF EU AND WHO GUIDELINES FOR RECREATIONAL 

WATERS 

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 recreational 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 grounds (see Zmirou et al., 2003) and were 

not based on epidemiology 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 epidemiology studies should be undertaken urgently concerning 

the health risks associated with bathing, particularly in fresh water.” As noted previously, the 

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 consultations 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) enterococci

(CFU/100 mL) 100* 200* 200**

E. coli (CFU/100 mL) 250* 500* 500**

Source: Adapted from EP/CEU (2006).

Notes: * = Based on a 95th percentile evaluation; ** = Based on a 90th 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 vs. good microbiological 

water quality. 

Unlike the 1976 Directive (CEC, 1976), in which bathing waters either conform 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 quality 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. coli presented in 

Annex I of the Directive are based on epidemiology studies and on either a 90th or 95th percentile 

basis of the last set of bathing water quality data (i.e., generally the last four bathing seasons). 

This method of determining the microbiological water quality assessment classification of a 

particular recreational area by densities of indicators is similar to that recommended in the latest 
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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 Recreational Water 

Environments Volume 1: Coastal and Fresh Waters. This extensive report builds and expands 

on several previous related reports, most notably including 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 associated 

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 sanitary 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” beaches 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 conclude 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 

several symptoms or symptom groups was significantly related to the count of fecal indicator 

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 fecal 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 

established. 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 waters 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 flattened indicator-response curves due to random 
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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 

and 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 recreational 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 based 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 presented in the 2003 WHO Guidelines, it is provided 

in detail in Kay et al. (2004) and is summarized below. 

 8 “Misclassification” 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 underestimation of the illness rate (WHO, 2003).
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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 organisms. 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

(gastroenteritis) (1 ) 0.0866 1

= − − − −b P e [1]
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where 

( )

 ( ) 







− − >

− − ≤ ≤ = 0.20102 158 32 2.3561 1580.20102 32 2.3561 32 158

ent

ent ent

C

C C b [2]

and Cent is Enterococcus 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 

gastrointestinal illness above the background level. A plot of what is referred to as the doseresponse curve (indicator-illness curve) corresponding to equations 1 and 2 is shown in Figure 1. 

The solid line corresponds to the dose-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 indicator densities vary greatly in recreational waters, and their distribution at a particular 

site is often modeled as log-normal, given mathematically as 

( ) ( )

2 2

10 log / 2

2

1 C m s

ent

ent e

s

p C − − = π

[3]

where m and s are the median and standard deviation of the log-transformed 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|Cent) × p(Cent) ) 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 the 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 combined 

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 becoming 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 

95th percentile value given the knowledge of the standard deviation of log10 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 risk 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 curve 
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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 indicatorilnness (referred to as “dose-response” by Kay and colleagues) curve into an area of “no data,” as 

predicted by the mathematical form in the upper region of Figure 1. It was, therefore, assumed 

that the excess illness probability remained constant at just under 40%, at densities 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 exposures, (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 95th percentile 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. (1994) 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 95th

percentile value was chosen as an appropriate 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 1and 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. Epidemiology studies that have focused on children have generally found that 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 and 

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-term (increasing 

pollution abatement measures).

 9 As can be seen in Figure 2, a 5% risk of GI illness is associated with a pdf 95th percentile value of 185, which was 

subsequently rounded up to 200 enterococci per 100 mL by WHO expert advisors.
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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 derived 

above from the two marine recreational water studies are specifically allowed to apply to 

freshwaters. In this regard, the 2003 WHO Guidelines concluded 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 suitable 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 freshwater. 

This would result in more pathogens in marine water than in freshwater when indicator organism 

densities are identical, which in turn would logically lead to a higher swimming-associated GI 

illness rate in marine recreational water swimmers (WHO, 2003). Interestingly, the metaanalysis 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 waters? 

...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 weak 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 given compliance location (and at what time), if separate marine 

and freshwater guideline values were to be specified.