MINI-REVIEW Open Access [620644]

MINI-REVIEW Open Access
Contamination of water resources by pathogenic
bacteria
Pramod K Pandey1*, Philip H Kass1, Michelle L Soupir2, Sagor Biswas1and Vijay P Singh3
Abstract
Water-borne pathogen contamination in water resources and related diseases are a major water quality concern
throughout the world. Increasing interest in controlling water-borne pathogens in water resources evidenced by a
large number of recent publications clearly attests to the need for studies that synthesize knowledge from multiplefields covering comparative aspects of pathogen contamination, and unify them in a single place in order to present
and address the problem as a whole. Providing a broader perceptive of pathogen contamination in freshwater (rivers,
lakes, reservoirs, groundwater) and saline water (estuaries and coastal waters) resources, this review paper attempts todevelop the first comprehensive single source of existing information on pathogen contamination in multiple
types of water resources. In addition, a comprehensive dis cussion describes the challenges associated with using
indicator organisms. Potential impacts of water resources development on pathogen contamination as well aschallenges that lie ahead for addressing pa thogen contamination are also discussed.
Keywords: Pathogens; Contamination; Water resources; Watershed; Pathogens transport
Introduction
Water-borne pathogen contamination in ambient water
bodies and related diseases are a major water qualityconcern throughout the world. Pathogen contamination is
a serious issue for almost all types of ambient water bodies,
making its recognition and understanding essential (U.S.EPA 2012a). The United Nations identified improving
water quality as one of the eight Millennium Development
Goals (MDGs). Its target is to reduce the number ofpeople without access to safe water by 50% by 2015
(WHO 2011). Because of the overwhelming scientific
evidence for climate change (IPCC 2007), it is also im-portant to understand how perturbations in weather
patterns can potentially impact pathogen levels in
water resources. To meet future demands of water forfood, energy, and ecosystems, increasing water storage
structures (i.e., dams) must be a component of long-range
planning (World Bank 2010). However, such new struc-tures can potentially degrade water quality and exacerbate
public health risk.While several review papers are currently available
(Bradford et al. 2013; Pachepsky and Shelton 2011; Pang
2009; Jin and Flury 2002; John and Rose 2005; Jamiesonet al. 2004; Jamieson et al. 2002; Arnone and Walling
2007; Kay et al. 2007), there is a manifest need for add-
itional transdisciplinary studies that assimilate knowledgegained from multi-research endeavors studying pathogen
contamination, and provide a comprehensive synopsis in
order to comprehend the entirety of the problem. There-fore, the goal of this review is to present a broad research
scope assessment of pathogen contamination of water
resources and the associated challenges it presents. Wesynthesize the potential health risks imposed by pathogens
in water resources by providing existing knowledge that
covers surface water, groundwater, fresh water, and salinewater. Further, the impact of water resources development
on pathogen contamination, fu ture challenges, and recom-
mendations are summarized. In addition, we provide a briefdiscussion describing water-borne pathogen footprints and
potential challenges associated with the use of indicator
organisms for assessing water quality.
Health risk
Water-borne diseases (i.e., diar rhea, gastrointestinal illness)
caused by various bacteria, vir uses, and protozoa have been* Correspondence: pkpandey@ucdavis.edu
1Department of Population Health and Reproduction, University of California,
Davis, California, USAFull list of author information is available at the end of the article
© 2014 Pandey et al.; licensee Springer. This is an Open Access article distributed under the terms of the Creative Commons
Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproductionin any medium, provided the original work is properly credited.Pandey et al. AMB Express 2014, 4:51
http://www.amb-express.com/content/4/1/51

the causes of many outbreaks (Craun et al. 2006). In de-
veloping countries, such as those in Africa, water-borne
diseases infect millions (Fenwick 2006). According toWorld Health Organization (WHO), each year 3.4 million
people, mostly children, die from water-related diseases
(WHO 2014). According to United Nations Children ’s
Fund (UNICEF) assessment, 4000 children die each day as
a result of contaminated water (UNICEF 2014). WHO
(2010) reports that over 2.6 billion people lack access toclean water, which is responsible for about 2.2 million
deaths annually, of which 1.4 million are in children.
Improving water quality can reduce the global diseaseburden by approximately 4% (WHO 2010).
Although water-associated diseases in developing coun-
tries are prevalent, they are also a serious challenge ind e v e l o p e dc o u n t r i e s .As t u d yb yA r n o n ea n dW a l l i n g
(2007), who compiled data of outbreaks in the U.S.
(1986 –2000), reported 5,905 cases and 95 outbreaks
associated with recreational water. Gastrointestinal Illness
(GI) caused by variety of different microbes and germs,
which causes symptoms, such as diarrhea, nausea,vomiting, fever, abdominal pain, was responsible for
about 29.53% cases. More than 27% of cases were
caused by Shigella spp . In addition, 10.99%, 10.08%, and
6.59% of the cases were caused by Cryptosporidium
parvum , Adenovirus 3, and Leptospira, respectively.
Nearly 23% and 21% of the outbreaks were caused byGI and Shigella spp , respectively. In addition, 16.84%,
12.63%, and 7.37% of the outbreaks were caused by
Naegleria fowleri ,E. coli 0157:H7, and Schistosoma spp. ,
respectively. Besides acute gastroenteritis, major etio-
logical agents such as Giarida ,Cryptosporadium ,E. coli
0157:H7, V. cholera ,a n d Salmonella were the agents re-
sponsible for many outbreaks (Craun et al. 2006). During
the same period 437,082 cases and 48 outbreaks were
caused by contaminated drinking water, of which about95.89% of the cases were caused by Cryptosporidium par-
vum. Nearly 42% and 31% of the outbreaks were caused
byGiardia lamblia and GI, respectively. Reporting statis-
tics on water-borne outbreaks in the U.S., Craun et al.
(2006) found that at least 1870 outbreaks (23 per year) oc-
curred between 1920 and 2002. These reported outbreaks
and their reported incidence of illnesses are likely to be
an underestimation of actual numbers because of non-reported cases and missing exposure information. To
protect public health, the U.S. EPA ’s National Primary
Drinking Water Regulations (NPDWRs) contain standardsdescribing the Maximum Contaminant Level (MCL) –the
highest level of a contaminate allowable in drinking water.
The U.S. EPA has defined the MCL of various microor-ganisms, such as Cryptosporidium ,Giardia lamblia ,
Legionella , and Total Coliforms (including fecal coliform
andE. coli ), and viruses (U.S. EPA 2012b). The Maximum
Contaminant Level Goal (MCLG) –the level of acontaminant in drinking water below which there is no
known risk to public health, has also been proposed by
t h eU . S .E P A .T h eM C L Cl e v e l sf o r Cryptosporidium ,
Giardia lamblia ,Legionella ,a n dT o t a lC o l i f o r m sa r e
zero. The EPA requires 99% removal of Cryptosporidium
in drinking water, and the removal percentages of Giardia
lamblia and viruses are 99.9 and 99.99%, respectively. Al-
though there is no limit for
Legionella , EPA believes that if
Giardia lamblia and viruses are removed/inactivated, then
drinking water likely to be free of Legionella. The U.S.
EPA requires routine sampling of drinking water for test-
ing total coliform and E. coli , and if a routine sample is
positive, then repeat samples are required. If, in any repeat
sample, total coliform or E. coli is detected then the drink-
ing water has an acute MCL violation. For a drinkingwater system that collects fewer than 40 routine samples
per month, no more than one sample can be total
coliform-positive per month. For a system that collectsmore than 40 routine samples, no more than 5% of
samples total coliform-positive in a month is allowed
(U.S. EPA 2012b).
Each year approximately 42,000 cases of salmonellosis
are reported in the U.S. (CDC 2014). Schistosomiasis is
not reported in the U.S. because it is not endemic;however, 200 million people are infected worldwide. In
2011, about 1,060 cases of Guinea worm disease, caused
by the parasite Dracunculus medinensis , were reported
in many remote parts of Africa that do not have safe
drinking water. Malaria, a protozoal disease of the
Genus Plasmodium transmitted by mosquitos breedingin contaminated water, affects 300 –500 million people,
and causes over one million deaths each year (more
than 90% of deaths in Africa). Overall the morbidityand mortality caused by contaminated water are enormous
and need to be controlled by improving the security of safe
water (i.e., recreational as well as drinking water) in bothdeveloping and developed countries.
Historical perspective of water-borne diseases
Water contamination has a long presence in human
history, with descriptions in the Sushruta Samshita
about water-borne diseases resembling cholera in anIndian text written in Sanskrit as early as 500 –400 B.C.
(Colwell 1996). Although cholera infections have not
been reported in recent years in developed countriesmainly due to improved sanitation, millions of people
each year continue to get infected by Vibrio cholera in
developing countries (Nelson et al. 2009). The WorldHealth Organization reports about 3 –5 million cholera
cases and 10,000 –120,000 deaths, mainly in developing
countries, due to cholera every year. Over time, cholerahas caused millions of deaths in developing as well as
developed countries (Colwell 1996; Okun 1996). For
instance, a major outbreak of cholera was reported inPandey et al. AMB Express 2014, 4:51 Page 2 of 16
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London in 1849. Dr. John Snow, a physician to Queen
Victoria, showed a relationship between people in-
fected by cholera and contaminated water (Snow 1854;Colwell 1996). Jordan et al. (1904), Ruediger (1911),
Simons et al. (1922), and Rudolfs et al. (1950) provide
excellent reviews on incidents during the early 19thcentury. Colwell (1996) reported that in the mid and
late 18th century, cholera infected millions of people
all over the world. The worst outbreak in recent memoryoccurred in Haiti following the devastating earthquake
affecting the capital and surrounding regions, with al-
most a half a million cases, killing thousands of people(CDC 2011).
Water-borne pathogen footprints and challenges
Indicator organisms are commonly used to assess the
levels of pathogens in water resources; i.e., water-borne
pathogen footprints of water resources. Monitoring thelevels of indicator organisms (such as fecal coliforms,
E. coli ) (Figure 1) is a common approach for quantifying
the potential pathogen loads in ambient water bodies. Fordecades, public health officials/scientists have evaluated
w a t e rq u a l i t yb ye n u m e r a t i n gf e c a lc o l i f o r m sa n d E. coli
levels in rivers, lakes, estuaries, and coastal waters (Malakoff2002; Pandey et al. 2012a; Pandey et al. 2012b; Pandey and
Soupir 2013). There is, however, much debate regarding
current indicator organisms a nd their ability to representthe potential presence of path ogenic bacteria. In addition,
identifying the source of pathogens (e.g., human waste,
animal waste, wildlife excreta, and waterfowl droppings)(Figure 2) is challenging (Malakoff 2002; Dickerson et al.
2007). There is potential to use a relatively new approach
such as microbial source tracking (MST) to trace the ori-gin of fecal coliform (Scott et al. 2002; Grave et al. 2007;
Dickerson et al. 2007; Ibekwe et al. 2011; Ma et al. 2014).
In the past, the MST method was exploited by antibioticresistance analysis to assess the impact of cattle on water
quality on a watershed scale (Grave et al. 2007). The
authors suggested that host-origin libraries, based on aphenotypic method, are useful for tracking the pathogen
sources. Many MST methods, however, rely on the as-
sumption that some strains of bacteria are found onlywithin a single kind or group of animals. This assumption
can be debatable when it comes to the common fecal bac-
teria E. coli (Malakoff 2002). Therefore, caution is needed
while using E. coli for source tracking (Gordon 2001). Fur-
ther, the cost to develop libraries, implement extensive
sampling programs needed for verifying the MST method,and calculate uncertainties associated with the method are
legitimate issues, which requires attention before exploit-
ing the MST method at watershed scale.
Currently, public health officials/scientists rely on ex-
posure limits for assessing pathogen levels in water re-
sources, which have been established to protect human
Figure 1 Transmission electron micrograph of E. coli (0157:H7; ATCC: 35150).Pandey et al. AMB Express 2014, 4:51 Page 3 of 16
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health. The EPA defines acceptable recreational limits as
those that will result in eight or fewer swimming-related
gastrointestinal (GI) illnesses out of every 1,000 swimmers(U.S. EPA 1986). The current U.S. EPA fresh water quality
criteria for E. coli is a geometric mean not exceeding
126 CFU/100 ml, or no samples exceeding a single samplemaximum of 235 CFU/100 ml (U.S. EPA 2001). Criteria
were developed based on the U.S. EPA measurements
of total and Highly Credible Gastrointestinal Illnesses
(HCGI), which correlated with E. coli densities (r =0.804)
in fresh recreational waters (Dufour 1984). Multiple stud-ies have identified trends between indicator organisms in
water and GI illness in humans, including vomiting, diar-
rhea, and fever (Cabelli 1983; Wade et al. 2006). Recentwork by Edge et al. (2010) detected water-borne E. coli
in 80% of water samples with E. coli levels of less than
100 CFU/100 ml. Another study by Wade et al. (2006)reported significant positive trends between increased GI
illness and indicator organisms at the Lake Michigan
beach, and a positive trend with indicators such as E. coli
at a Lake Erie beach. Recently, the use of indicatororganisms (e.g., fecal coliforms, E. coli ) for assessing
pathogen levels has been debated more often than ever;
however, the use of indicator organisms is likely tocontinue for assessing pathogen levels in water resources
potentially because of the lack of an alternative reliable
solution.
Pathogen contamination in water resources
The U.S. EPA, which monitors water quality of variousambient water bodies, estimated that pathogens impair
more than 480,000 km of rivers and shorelines and
2 million ha of lakes in the U.S. (U.S. EnvironmentalProtection Agency 2010a). According to EPA estimates,
pathogens are the leading cause of impairment for 303 (d)
listed waters (i.e., list of impaired and threatened watersthat the Clean Water Act requires all states to submit for
EPA approval) (Figure 3) (U.S. EPA 2014a, 2014b, 2014c).
A total of 71,917 causes of impairment have been re-ported, and the top five causes of impairment are shown
in Figure 3. Pathogen contamination clearly dominates the
causes of impairment (U.S. EPA 2014a, 2014b, 2014c).
Figure 2 Challenges in identifying enteric pathogen sources (source: Malakoff, 2002).Pandey et al. AMB Express 2014, 4:51 Page 4 of 16
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Studies by Diffey (1991), Brookes et al. (2004), Jamieson
et al. (2004), Gerba and Smith (2005), Gerba and McLeod
(1976), Hipsey et al. (2008), Pachepsky and Shelton (2011)reviewed the current studies of water-borne pathogen
transport, with particular reference to freshwater and
estuarine sediments. In addition, many current reviewsfocus on specific aspects of water resources, for in-
stance, John and Rose (2005) focused on groundwater,
Brookes et al. (2004) focused on reservoirs and lakes,Jamieson et al. (2004) focused on agricultural watersheds,
and Kay et al. (2007) reviewed catchment microbial dy-
namics. The review study presented here uses a relativelybroader approach for understanding how water-borne
pathogens can potentially impact public health and vari-
ous ambient water bodies. In addition, existing challenges,while assessing pathogen levels in water resources are
discussed.
Coastal and estuarine environments
In the U.S., elevated pathogen levels are a leading cause
of impairments of coastal environments (U.S. EPA2014a, 2014b, 2014c). Urban runoff and sewers have been
identified as the primary source of coastal water impair-
ments. Rippey (1994) reported about 400 outbreaks and14,000 cases caused by pathogen contaminated coastal
water since the late 1800s in the U.S. Impairments of
coastal environments have major economic impacts onthe U.S. For example, losses caused by pathogen con-
tamination in Massachusetts are more than $75 million
each year (Weiskel et al. 1996). The studies, which elabor-ate various pathogens in coastal environment and their
survival mechanism, are summarized in Table 1.
The sources of coastal water contamination are: point
discharges of treated and untreated sewage from shoreline
outfalls, and non-point discharges. The non-point sources,
such as runoff from naturally vegetated areas, dischargepathogens into coastal waters. Besides runoff from vege-
tated areas, the storm water runoff from urban, commer-
cial, and industrial lands also discharges pathogens intocoastal waters. In addition, other sources, such as malfunc-
tioning or poorly sited septic s ystems, can also introduce
significant amounts of pathogens (Sayler et al. 1975; Howeet al. 2002). Weiskel et al. (1996) reported that direct
deposition of waterfowl feces was a considerable source
of pathogens. Fayer and Trout (2005) summarized thetransport of various pathogens, such as Giardia ,Toxo-
plasma ,a n d Cryptosporidium (zoonotic parasites) in
the coastal environment. Moreover, the presence ofsediment in seawater can also increase the survival
chance of fecal coliforms, such as E. coli (Gerba nd
McLeod 1976; Goyal et al. 1977). Solo-Gabriele et al.(2000) showed that the location and timing of storms of
the coastal area in tropical and subtropical environ-
ments are also important factors that can potentiallyinfluence coastal water quality.
Previous studies have shown that the direct discharge
of storm water runoff into coastal waters through stormdrain systems can cause pathogen contamination, even
where separate storm and sanitary sewer systems are in
place. For instance, Weiskel et al. (1996) found that about
16% of the total fecal coliform inputs were caused by
storm water entering Butter milk Bay in Massachusetts.
In addition, coastal rivers draining largely undeveloped
watersheds with extensive riparian wetlands can be a
natural source of fecal pathogens to coastal waters(Viau et al. 2011; Staley et al. 2014; Roberts et al. 2013;
Liang et al. 2013; Wilkes et al. 2014). On-site septic
systems can also contribute significant amounts offecal pathogens to coastal waters in low-lying fine-
grained geological settings where saturated soils en-
hance pathogen growth. Weis kel et al. (1996) reported
that shoreline wrack deposits could act as a reservoir02,0004,0006,0008,00010,00012,000
Pathogens Metals (other than
Mercury)Nutrients Organic
enrichment/oxygen
depletionSedimentsrebmuntnemriapmidetropeR
Causes of impariment
Figure 3 Causes of impairment in the U.S. (data source: U.S. EPA (2014a, 2014b, 2014c)).Pandey et al. AMB Express 2014, 4:51 Page 5 of 16
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of fecal bacteria, and the removal of wrack deposits
from inter-tidal zones can improve the water quality of
adjacent coastal waters.
Similar to the coastal environment, increasing water-
borne pathogen levels in estuaries are a serious threat to
public health. Human activities can impact estuary patho-
gen levels when they are adjacent to populated areas, andoften provide a means of transportation and substantial
recreation (Schriewer et al. 2010; Pachepsky and Shelton
2011). The most common pathogens, previously identifiedin estuaries by Rhodes and Kator (1990), were Vibrio
cholerae ,Giardia ,Cryptosporidium ,Salmonella ,a n d
Campylobacter spp. As shown in Table 1, the presence
of various pathogens (e.g., E. coli, C. perfringens,Clostridium, Salmonella ) has been reported in many
previous studies. Municipal point sources are the pri-
mary cause of pathogen contamination in estuaries.
Urban water disposed through combined sewer outflowsis the cause of approximately 12% of estuary impairments
in the U.S. (Arnone and Walling 2007). Pathogens, includ-
ingVibrio vulnificus which carries the highest fatality rate
of any food-borne pathogen in the U.S., were detected in
the Gulf of Mexico Estuary (Lipp et al. 2001; Baker-Austin
et al. 2009). Several studies discovered that bed sedimentplays a vital role (i.e., with the release of particle-attached
pathogens from bed sediment to a water column through
a resuspension process) for the persistence and transportof pathogens in the estuaries (Smith et al. 1978; DesmaraisTable 1 Studies describing pathogen contamination in saline water (coastal and estuary environments)
Author(s) year Organisms Results Study remarks
Coastal water
Gerba and McLeod ( 1976 ) E. coli , fecal coliform Longer survival in the sediment
presence in seawaterSediment influence on pathogen
survival
Goyal et al. ( 1977 ) Total coliform, fecal coliform Sediments of shallow canal can
act as a reservoirPathogens distribution in water
and sediment
Kapuscinski and Mitchell ( 1983 ) E. coli , bacteriophages E. coli survives longer than
bacteriophagesSurvival of pathogens in sunlight
Rao et al. ( 1984 ) Enteroviruses (Polio and Rota) Abundance viruses were attached
with sedimentViruses distribution in water and
sediment
Weiskel et al. ( 1996 ) Fecal coliform Waterfowl major source of fecal
coliform inputsPathogen source and transport
pathways
Sinton et al. ( 1999 ) Bacteria and Fecal bacteriophages Somatic coliphages shown
prolonged survivalSunlight influence on sewage-polluted
seawater
Solo-Gabriele et al. ( 2000 ) E. coli Riverbanks as the primary
pathogen sourceSources of pathogens on subtropical
environment
Nasser et al. ( 2003 ) Cryptosporidium, viruses, E. coli E. coli die-off was faster than
other pathogensComparative survival of various
pathogens
Schriewer et al. ( 2010 ) Bacteroidales, fecal indicator,
protozoa, bacteriaBacteroidales have shown higher
predictive skill than fecal indicatorsBacteroidales as a predictor of
pathogens in coastal water
EstuariesKetchum et al. ( 1952 ) Coliform, zooplankton Sactericidal and predation
caused coliform die-offProcesses responsible for pathogens
decrease
Smith et al. ( 1978 ) Echovirus 1, coxsackieviruses Sediment prolonged viruses
survivalPersistence of pathogen viruses
Rhodes and Kator ( 1990 ) E. coli Mortality rises in sunlight Indigenous microbiota and sunlight
influence
White et al. ( 1998 ) Perkinsus marinus Use of Kriging analysis for
disease prevalenceUse of GIS in pathogen distribution
analysis
Lipp et al. ( 2001 ) Vibrio vulnificus Salinity controls the distribution
of pathogensDistribution of human pathogens
Desmarais et al. ( 2002 ) E. coli, C. perfringens Pathogens re-grown with tides
and sterile sedimentInfluence of soil on fecal indicator
in tidally influenced environment
Frias-Lopez et al. ( 2002 ) Clostridium ,Campylobacter ,
ArobacterPathogen partitioning was found
in surface and overlying waterBacterial communities partitioning
between sea water, dead coral surface
Chandran and
Hatha ( 2005 )E. coli, Salmonella E. coli shows better survival
capacity than SalmonellaRelative survival in microcosm studies
Baker-Austin et al. ( 2009 ) Vibrio vulnificus Prevalence of antibiotic
resistance in a human pathogenMulti-site analysis shows widespread
antibiotic resistance in pathogensPandey et al. AMB Express 2014, 4:51 Page 6 of 16
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et al. 2002). Previous studies have shown that pathogen
growth and decay are influenced by environmental condi-
tions. For instance, a study by Chandran and Hatha (2005)revealed that sunlight is a major factor that influences
survival of pathogens like E. coli and S. typhimurium in
the estuarine water.
Groundwater
Groundwater is heavily used all over the world as theprimary source of domestic drinking water supplies, and
contaminated groundwater certainly enhances risk to
public health. Nationally, 40% of the U.S. domestic watersupply originates from groundwater, and over 40 million
people use groundwater as their drinking water via private
wells (Alley et al. 1999). Groundwater pathogen contamin-ation has led to numerous disease outbreaks in the U.S.;
for example, at least 46 outbreaks of disease occurred be-
tween 1992 and 1999, resulting in 2,739 cases of illnessand several deaths (John and Rose 2005). These are re-
ported cases; due to underdiagnosis and underreporting,
the actual morbidity is almost certainly higher.
Several studies have shown that microbial pathogens,
such as Salmonella ,E. coli ,S. faecalis , and enteroviruses
are relatively stable in groundwater (Bittion et al. 1983;Schijven and Hassanizadeh 2000; Pang et al. 2004) (Table 2).
Controlling groundwater pathogen contamination has
recently been emphasized in many countries, as patho-gens can survive up to 400 days depending on the soil
temperature (Nevecherya et al. 2005; Filip and Demnerova
2009). For example, identifying sources of groundwaterpathogen contamination has received significant attention
in France (Grisey et al. 2010). Many studies reported that
health risks caused by chlorine-resistant protozoans, suchasCryptosporidium spp. (Ferguson et al. 2003; Kay et al.
2007; Kay et al. 2008), are considerable. One of the major
concerns is that wetlands without lining might causepathogen contamination of groundwater (Kay et al. 2007).
Similar concerns have been expressed in the United
Kingdom by water regulators. The European Union(EU) has also emphasized protecting groundwater from
pathogen contamination. Pathogen-contaminated ground-
water can cause pollution in coastal environments. Forexample, a study of Buttermilk Bay has shown that
groundwater is capable of transporting a large quantity
of pathogens from surface to sub-surface water eitherby direct discharge or by discharge to rivers flowing into
the bay (Moog 1987; Weiskel et al. 1996). The risk of
contaminating groundwater particularly increases inareas where shallow aquifers exist. In these situations it
is more likely that contaminated surface water or water
from septic tanks can reach groundwater (Weiskel et al.1996). Precipitation events are likely to increase ground-
water pathogen contamination because of contaminated
ground water recharge.Pathogen contamination (e.g., bacteria, protozoa, and
viruses) poses a serious risk in water resources. The
transport of pathogens from surface water to ground-water increases the vulnerability of groundwater (Jin and
Flury 2002). These authors reported that 70% of the
water-borne microbial illness outbreaks in the UnitedStates have been associated with ground water. Pathogens
such as viruses are much smaller than bacteria and proto-
zoa, and many can potentially reach groundwater throughporous soil matrices. Jin and Flury (2002) reviewed the
fate and transport of viruses in porous media to under-
stand mechanisms and modeling of virus sorption, andconcluded that factors such as solution chemistry, virus
properties, soil properties, temperature, and association
with solid particle influences virus survival, transport, andsorption in porous media. Pang (2009) studied microbial
removal rates in subsurface media, and reported that soil
types considerably influence microbial removal rates. Forinstance, volcanic soils, pumice sand, fine sand, and highly
weathered aquifer rocks showed high removal rates. The
author found that microbial removal rates were inverselycorrelated with infiltration rates and transport velocity.
Considerable work recently has been done towards
understanding pathogen transport in the vadose zone(Wang et al. 2014a; 2014b; Unc and Goss 2004; Darnault
et al. 2004). Groundwater can be contaminated by seepage
and percolation of contaminated water from the vadosezone (Darnault et al. 2004). The macropores of agricul-
t u r a ll a n da r ea l s ok n o w nt op l a yac o n s i d e r a b l er o l ei n
polluting groundwater, particularly from fields wheremanure is applied (Jamieson et al. 2002). Unc and Goss
(2004) evaluated the influence of manure on the trans-
port of bacteria from land receiving manure to waterresources. These authors reported that manure appli-
cation in the land influences pathogen transport in the
vadose zone. The presence of straw and coarse organicmatter influences the persistence of bacteria, and manure
application changes the physical configuration of soil, the
soil chemistry, and the properties of the microbial cells,which control the survival and persistence of bacteria in
soils. Another recent study by Wang et al. (2014) assessed
the transport of E. coli in soils with preferential flow. The
authors reported that a decrease in macropore length re-
sulted in a decreased apparent saturated hydraulic con-ductivity of the macropore and an increase in the mass
transfer. Wang et al. (2014a; 2014b) concluded that
macropore length has a considerable influence on pref-erential transport of E. coli .
Reservoirs and lakes
Previous studies have shown the presence of many path-
ogens in lakes and reservoirs (Table 2), and that these
pathogens can pose risks to human health. In many
countries surface reservoirs serve as the main sourcePandey et al. AMB Express 2014, 4:51 Page 7 of 16
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of drinking water, and these surface water bodies are
often vulnerable to pathogen contamination (Kistemannet al. 2002). In the developed world, although there is
increased awareness of water treatment for pathogen con-
tamination and water quality, outbreaks of water-bornedisease via public water supplies continue to be reported
(Gibson et al. 1998; Howe et al. 2002; Brookes et al. 2004).
In the past, more than 403,000 residents of the greater
Milwaukee, Wisconsin area experienced gastrointestinal ill-
nesses due to infection with the parasite CryptosporidiumTable 2 Pathogen contamination in freshwater environment (ground water, rivers and lakes and reservoirs)
Author(s) year Organisms Results Study remarks
Groundwater
Bitton et al. ( 1983 ) Salmonella, E. coli, S. faecalis,
enterovirusesS. faecalis decay rate was similar
to virusesSurvival of pathogens in groundwater
Schijven and Hassanizadeh ( 2000 ) Viruses Viruses attachment with soil was
influenced by pH, and favorable
sitesSoil passage impacts on virus removal
at field-scale
Pang et al. ( 2004 ) E. coli and F-RNA phages Pathogens were sorbed in aquifer
materialTransport of E. coli and F-RNA phages
Nevecherya et al. ( 2005 ) Salmonella , viruses, E. coli,
shigellosMathematical model was derived
for temperature depends inactivation
ratePathogenic bacteria and viruses survival
in groundwater
Filip and Demnerova ( 2009 ) Bacillus megaterium and
StaphylococcusPathogens survived 10 to 100 days Pathogens survival in groundwater; FT-IR
characterization
Grisey et al. ( 2010 ) Total coliforms, E. coli,
Enterococci, Pseudomonas
aeruginosa, Salmonella and
Staphylococcus aureusBacterial density monitoring coupled
with artificial trace experiments proved
useful in locating pathogens sourcesPathogens survival in groundwater and
landfill leachate
Rivers
Chin ( 2010 ) Fecal coliform Summer and rainfall raises pathogens Urban areas impacts on stream pathogens
Smith et al. ( 1973 ) Salmonella , fecal coliforms,
streptococciSalmonella decline was close to fecal
coliformUsefulness of indicators organisms
Burton et al. ( 1987 ) Pseudomonas aeruginosa,
Salmonella newport, E. coliClay in sediments improves E. coli
survivalSurvival of pathogens in fresh water
sediments
Smith et al. ( 1987 ) E. coli , Fecal bacteria U.S. rivers shows decline in fecal
indicatorWater quality assessment from 1974 to 1981
Terzieva and McFeters ( 1991 ) E. coli, Campylobacter jejuni,
Yersinia enterocoliticaTemperate zone surface water serve
as a rersisitent verhicle in transimsisionof bacteria between animals and
humansSurvival and injury study of bacteria in
agricultural surface water
Terzieva and McFeters (
1991 ) Yersinia enterocolitica and
E. coliExperimental design and environmental
play major role in pathogens survivalSurvival in stream water, comparison
between field and lab studies
Fraser et al. ( 1998 ) Fecal coliform Model predicted pathogens Modelling non-point source pollution
Lakes and reservoirsBeaver and Crisman ( 1989 ) Ciliates Grazing habits of ciliates are discussed Predators roles in fresh water
Rubentschik et al. ( 1936 ) Serratia marcescens Adsorption of bacteria could be
questionableAdsorption of bacteria in salt lakes
Mac Kenzie et al. ( 1994 ) Cryptosporidium C. oocysts study passes through the
filtration system of water supplyContaminated water from Milwaukee
lake caused outbreak
Wcislo and Chrost ( 2000 ) E. coli Predators controlled pathogen levels Survival of pathogens in man-made
reservoir
Kistemann et al. ( 2002 ) E. coli , coliform, fecal
streptococcal, and Clostridium
perfringensMost of the pathogens increases during
extreme runoff eventsMicrobial load in drinking water reservoir
during rainfall events
Howe et al. ( 2002 ) Cryptosporidium oocysts Animal feces was a major source of
pathogensWater supply ’s oocysts caused outbreak
in northern England
Ishii et al. ( 2006 ) E. coli E. coli survived longer in soil Presence and growth of E. coli in Lake
superior watershedPandey et al. AMB Express 2014, 4:51 Page 8 of 16
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parvum following contamination of the city ’sw a t e rs u p p l y ,
which was associated with inadequate filtration of contami-
nated water from Lake Michigan (Mac Kenzie et al. 1994;Cicirello et al. 1997). In the 1990s, Cryptosporidiosis be-
came the most common cause of outbreaks associated
with public drinking water supplies in the UnitedKingdom (Howe et al. 2002). In developing countries,
diseases such as diarrhea and cholera are the leading
cause of morbidity (Nelson et al. 2009). Overall, diarrheaassociated with drinking cont aminated water is responsible
for 2 to 2.5 million deaths annually (Fenwick 2006). In lakes
and reservoirs, increased pathogens are often associatedwith storm events, and the st ream inflow is considered to
be the major source of pathogens during storm events.
Elevated flows in rivers most likely agitate bed sediment,which causes enhancement of pathogen levels of the water
column (Jamieson et al. 2005a; Jamieson et al. 2005b;
Pandey and Soupir 2013; Bai and Lung 2005). During ther a i n ys e a s o n ,t h ei n f l u xo fc o n t a m i n a t e dw a t e rf r o mr i v e r s
to lakes and reservoirs can substantially increase pathogen
levels (Kistemann et al. 2002). The quantity of pathogen in-fluxes from tributaries of lak es and reservoirs during the
rainy season is of particular importance in determining
pathogen transport and distribution (Brookes et al. 2004).
Rivers
Pathogen contamination is a major cause of stream im-pairments. The sources of impairment and health risks
induced by water-borne pathog ens are extensively reported
(Table 2). In the U.S. pathogen contamination is the leading
cause of stream water pollution. The EPA ’s National Water
Quality Inventory Report su ggests that about 53% of the
assessed rivers are impaired, and a majority of them arecontaminated by pathogens (U.S. EPA 2012a). The cost to
implement the total maximum daily load (TMDL) plans to
improve stream water is estimated as $0.9 to $4.3 billionper year (U.S. EPA 2010b).
Pathogen influxes into rivers from agricultural lands
(Figure 4) are the main cause of stream impairments(Chin 2010; U.S. EPA 2012a). A weak understanding of
pathogen transport from agricultural lands to rivers is
considered to be a major challenge in implementing andderiving suitable land management practices capable of
improving stream water quali ty. For instance, despite
common knowledge that agricultural land ’sn o n – p o i n t
source pollution is a leading cause of stream impairment,
it is difficult to identify points of origin of pathogens and
the pathways by which they enter streams. As an example,pathogens are likely to enter rivers from many potential
sources, including lateral inputs from pastures and ripar-
ian zones, influx of pathogen-contaminated groundwater,direct deposit of fecal matter from livestock and wildlife,
discharge of contaminated sanitary sewer flows, and
wastewater treatment plant effluents. In rainy events,pathogens in rivers are influenced by fresh input from
watersheds as well as sub-surface flow. In addition, the
resuspension of legacy pathogens from bed sedimentscan considerably increase pathogen levels (Cho et al.
2010; Droppo et al. 2009; Jamieson et al. 2005b; Kiefer
et al. 2012; Nagels et al. 2002; Muirhead et al. 2004;Kim et al. 2010; Smith et al. 2008).
Controlling pathogen contamination from livestock/
wildlife to streams is challenging (Terzieva and McFeters1991). For example, it is doubtful that pathogen contam-
ination can be prevented by fencing off riparian buffers,
and even if buffers are useful in controlling stream waterpathogens, it is not certain what their width must be
(Nagels et al. 2002). There are review studies that elabor-
ate on stream water pathogen contamination (Fraser et al.1998; Jamieson et al. 2004; Pachepsky et al. 2006).
Many studies have emphasized the use of mathematical
models to understand pathogen transport from agricul-tural land to rivers (Kim et al. 2010; Muirhead et al. 2004;
Jamieson et al. 2005a; Jamieson et al. 2005b). Previous
studies (Gerba and Smith 2005; Pandey et al. 2012b;Pandey and Soupir 2013; Pachepsky and Shelton 2011;
Martinez et al. 2014) have emphasized the need to im-
prove existing models for calculating the fate andtransport of pathogens at the watershed scale. Cur-
rently, empirical as well as mechanistic models are
being used to calculate micr obial fate and transport
(Muirhead and Monaghan 2012). Numerous studies
are available for exploiting watershed scale models such as
WATFLOOD (Dorner et al. 2006), the Soil and WaterAssessment Tool (SWAT) (Neitsch et al. 2005), the
Spatially Explicit Deliver Model (SEDMOD) (Fraser
1999), and KINEROS/STWIR (Guber et al. 2011) forpredicting pathogen transport. Though numerous water-
shed scale models are available, which can be exploited for
calculating pathogen transport at watershed scale, consid-erable difficulties exist while using the models (Pandey
et al. 2012b; Pandey and Soupir 2013). For instance,
correctly identifying the model input parameter valuesis a daunting task. Recently, considerable emphasis has
been given to understand the sensitivity of the input
parameters to the model output (Martinez et al. 2014;
Parajuli et al. 2009).
When implementing watershed scale models for
predicting pathogen transport, difficulties related to
the selection of model input parameters are common
(Martinez et al. 2014). A study by Parajuli et al. (2009)evaluated the sensitivity of fecal coliform bacteria loads
modeled with SWAT, and the authors reported that
many of the parameters (e.g., bacterial die-off rates, thetemperature adjustment fact or) were insensitive to the
model output. Similarly, Coffey et al. (2010) reported that
initial concentration of E. coli and the bacterial partition
coefficient parameters of the SWAT model were overlyPandey et al. AMB Express 2014, 4:51 Page 9 of 16
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sensitive in affecting the model ’s output. Another recent
study by Martinez et al. (2014) evaluated the KINEROS/
STWIF model input parameter sensitivities to the output.
These authors reported that environmental controls suchas soil saturation, rainfall duration, and rainfall intensity
had the most sensitivity, while parameters such as soil and
manure properties were the least sensitive in affectingmodel output. Many previous studies (Pandey and Soupir
2012a, 2012b; Kim et al. 2010; Martinez et al. 2014; Parajuli
et al. 2009) reported that identification and selection
of model input parameters are major challenges when
implementing the model for predicting fate and transportof pathogens at the watershed scale.
Blooming of cyanobacteria
While water-borne pathogens are a serious concern,excessive algal bloom (Figure 5) in water resources can
potentially limit their uses for recreation activities as
well as for drinking water. Cyanobacteria (blue-greenalgae) have unique roles in oxygenation of the atmosphere
(Hofer 2013); however, their excessive growth or dense
algal bloom in water resources diminishes the quality andquantity of light in the water column (U.S. EPA 2014b).
When blooms are excessive, the risk of toxin contamin-
ation (released by harmful algal bloom (HABs)) is likely to
be elevated. The HAB includes many types of algal taxasuch as dinoflagellates, di atoms, and cyanobacteria.
Eutrophication caused by excessive algal bloom can
cause fish kills and reduce the diversity of aquatic life(U.S. EPA 2014b). In hypoxic water, dissolved oxygen
levels can be less than 2 –3 ppm (U.S. EPA 2014c). For
example, in the hypoxic zone in the northern Gulf of
Mexico, an area along the Louisiana-Texas coast, less
than 2 ppm of dissolved oxygen concentration has beenreported. This is believed to be caused by excess nutrients
delivered from the Mississippi River, in combination with
seasonal stratification of Gulf waters (U.S.G.S., 2014). Thelargest U.S. hypoxic zone, which occurred in 2002 in the
Gulf of Mexico, was about 13,518 square kilometers (U.S.
G.S. 2012).
Freshwater cyanobacterial b looms produce highly po-
tent cyanotoxins and cyanobacterial HABs, which can
affect the liver, nervous system, and skin (U.S. EPA 2014b).Cyanobacterial blooms can be potentially detrimental to
Figure 4 Simplified path of animal waste pathogen transport from agricultural land to rivers.Pandey et al. AMB Express 2014, 4:51 Page 10 of 16
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human and animal health, aquatic habitats, and aquaculture
industries (Kaloudis et al. 2013; Carmichael 2001; Falconer
2005; Codd et al. 1999). Previous studies (Mackintosh et al.
1990; Yoshizawa et al. 1990) have shown that microcystins(i.e., cynotoxins) are hepatotoxic and act as tumor pro-
moters through the inhibition of protein phosphatases,
which play a key role in cellular regulation. Eutrophicwater conditions combined with warm surface water
temperatures (15 –30°C) can potentially enhance cyano-
bacterial blooms in water (Oikonomou et al. 2012; Vareliet al. 2009). Currently more than 400 hypoxic zones exist
in the world affecting 245,000 square kilometers (Diaz and
Rosenberg 2008). These dead zones in coastal waters havespread exponentially since the 1960s and have consider-
ably impacted ecosystems. The increase in these dead
zones is likely to be influenced by climate change. Variousfactors such as how climate change affects water-column
stratification and how nutrient runoff affects organic mat-
ter production will determine further expansion of thedead zones (Diaz and Rosenberg 2008). For instance, cli-
mate predictions of the Mississippi River basin indicate a
20% increase in river discharge, which will enhance nutri-ent loading and result in expansion of the oxygen depleted
area (IPCC 2007). Considering the importance of fresh
water, estuarine, and marine environment to public
health and aquatic life, identifying approaches capable
of controlling excessive algal blooms is required beforethese dead zones spread globally.
Impact of water resources development
Water resources development involves altering the naturalflow path of rivers and lakes, as well as designing irrigation
schemes and dams. These activities have been alleged to
be responsible for causing new diseases and enhancinghealth risks (Fenwick 2006; Steinmann et al. 2006).
The influence of water resources development in
spreading diseases, such as schistosomiasis, a parasiticdisease which is ranked second only to malaria with
regard to the number of people infected, has been
reported extensively; one e stimate says that about 103
million out of 779 million infected people live in closeproximity to large reservoirs and irrigation schemes
(Steinmann et al. 2006).
Designing dams and irrigation schemes in tropical and
subtropical climate zones has often resulted in disease
outbreaks caused by water-borne pathogens. Consider,
for example, the Sennar Dam on the Blue Nile River andSudan ’s Gezira Scheme, the world ’s largest irrigation
project. Because of the dam ’s commercial success, irriga-
tion in the region has doubled from the 1940s and 1950s.After the 1950s, infections from malaria and schistosomia-
sis increased significantly, becoming the subject of the first
integrated disease-control program, the Blue Nile HealthProject, implemented from 1978 to 1990. The project
failed to have any impact in controlling the prevalence
of schistosomiasis (Eltoum et al. 1993; Fenwick 2006;Steinmann et al. 2006). Another example is China ’s
Three Gorges Dam, built across the Yangtze River and
completed in 2009, which created a 50,700 km
2reservoir
and submerged more than 220 counties. Hotez et al.
(1997) reported that the reservoir would produce environ-
mental changes that could lead to the transmission of
schistosomiasis in the area served by the dam. A recent
study by Schrader et al. (2013) found major high risk areasfor schistosomiasis occurrence in the large lakes and flood
plain regions of the Yangtze River. Another study by Gray
et al. (2012) reported that the Three Gorges Dam willlikely to impact the transmission of schistosomiasis in
China.
In the U.S., because of increasing concern for produce
safety, pathogen-free irriga tion water is attracting con-
siderable attention (Martinez et al. 2014). Painter et al.
(2013) reported that produce accounted for nearly halfof food-borne illnesses in the U.S. between 1998 and
Figure 5 Algal bloom in Squaw Creek, Iowa, U.S.Pandey et al. AMB Express 2014, 4:51 Page 11 of 16
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2008. Growing concern about the safety of food and
water will likely help in developing improved strategies
while planning and designing large dams for irrigation
purposes.
Challenges and recommendations
Infectious diseases caused by pathogens are the third
leading cause of death in the United States, and the lead-
ing cause in the world (Binder et al. 1999). The past twodecades have seen the emergence of many new pathogenic
infectious diseases (Daszak et al. 2000). Many of these are
caused by anthropogenic changes, such as water resourcesdevelopment, climate warming, and interactions between
humans and animals, both domestic and wild (Krause
1994; Epstein 2001; Woolhouse 2002; Fenwick 2006;Schriewer et al. 2010).
Multidisciplinary knowledge about how ambient water
bodies, wildlife, domestic animals, and human populationsinteract with and impact each other are crucial in dealing
with future challenges. Generally, domestic animals,
wildlife, and humans are considered to be major sourcesof water-borne pathogens; however, finding the specific
culprit —the primary pathogen source —is challenging
(Malakoff 2002). A watershed, for example, can havemany pathogen sources, such as agricultural land, riparian
areas, agricultural feeding operations, livestock, wildlife,
and humans.
Developing models that are reliable in predicting
pathogen survival and transport at the watershed scale
can be helpful in implementing/evaluating the strategiesfor mitigating ambient water body pathogen levels.
Evaluating the impacts of various environmental factors
on pathogen survival in water resources is crucial. Variouspublications (i.e., Dorner et al. 2006; Kim et al. 2010;
Rehmann and Soupir 2009; Droppo et al., 2011; Cho et al.
2010; Pandey et al. 2012b; Pandey and Soupir 2013) areavailable describing models capable of predicting pathogen
contamination levels in ambient water bodies; however,
further work is required to improve model predictions.The evaluation of predictions by existing models clearly
demonstrates the need for improvement. Many pathogen
transport models use only temperature-induced mortalityand growth, and do not include interactions among other
environmental factors (e.g., pH, nutrients, DO, solar radi-
ation); future inclusion of these environmental factors willlikely to improve the model predictions.
Typically most studies have relied on E. coli and other
indicator bacteria to indicate pathogen levels in water.Although widely used in monitoring contamination levels,
E. coli alone can lead to mercurial and misleading infor-
mation (Gordon 2001). Schriewer et al. (2010) suggestedthat with improved pathogen detection technology (i.e.,
PCR-based detection) an indicator organism, such as E.
coli, can be sufficiently accurate in most cases. Overall,improving technology to identify causative agents more
accurately, creating standard epidemiological data for
diseased populations, and enhancing the knowledge ofdisease dynamics can improve the understanding of
risks caused by interactions among various populations
(Harvell et al. 1999; Daszak et al. 2000; Harvell et al.2002).
In the past, a number of studies on pathogen con-
tamination have been conducted on a scale where theconditions of ambient water bodies were simulated in
laboratories. These studies ar e helpful in understanding
pathogen behavior only up to a point. For enhancing theunderstanding of pathogen int eractions in the environment,
more emphasis should be given to field-scale studies.
Conclusions
This review examines studies from various disciplinesto understand pathogen contamination in ambient water
bodies. The worldwide prevalence of pathogen contam-ination is a serious concern, and enhancing the under-
standing of major pathogen sources and their significant
impacts on water resources is crucial. A considerablenumber of studies on pathogen contamination have
been conducted on a laboratory-scale; more emphasis
should be given to field-scale studies for enhancing theunderstanding of pathogen interactions in the environ-
ment. Developing new models, and improving existing
modeling approaches commonly used for predictingwater-borne pathogen levels will likely to help in assessing
pathogen contamination at watershed-scale. Considering
the limited ability of existing models to predict pathogencontamination, improvement and development of new
models are needed so that pathogen levels can be predicted
more accurately. Integrating kn owledge from multiple fields
(e.g., hydrology, microbiology, and ecology) would increase
the understanding of pollution levels and potential causes
of pollution, and can also help de vise long-term strategies
to improve water quality.
Competing interest
The authors declare that they have no competing interests.
Acknowledgment
The authors thank the Division of Agriculture and Natural Resources andVeterinary Medicine Extension, University of California, Davis, and National
Science Foundation (award No. CBET-0967845) for supporting this work.
Author details
1Department of Population Health and Reproduction, University of California,
Davis, California, USA.2Department of Agricultural and Biosystems
Engineering, Iowa State University, Ames, Iowa, USA.3Department of
Biological and Agricultural Engineering & Zachry Department of CivilEngineering, Texas A & M University, College Station, Texas, USA.
Received: 3 May 2014 Accepted: 27 May 2014
Pandey et al. AMB Express 2014, 4:51 Page 12 of 16
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