Changes in Escherichia coli to Cryptosporidium ratios for various fecal pollution sources and drinking water intakes

Inclusion of hydrodynamic properties of bathing waters is critical in selecting faecal indicators to assess public health impacts of faecal contamination

The EU Bathing Water Directive (BWD) requires member states to assess bathing water quality according to the levels of faecal indicator bacteria (FIB) in designated bathing areas. However, this criterion has two significant limitations given that the BWD does not; (i) account for differences in hydrodynamic properties of bathing waters and, (ii) assumes that all faecal pathogens decay equally in aquatic environments. This study simulated sewage discharge events in three hypothetical aquatic environments characterised by different advection and dispersion parameters in the solute transport equation. Temporal changes in the downstream concentration of six faecal indicators were determined in simulations that utilised measured decay rates of each faecal indicator from a programme of controlled microcosm experiments in fresh and seawater environments. The results showed that the decay rates of faecal indicators are not a critical parameter in advection dominant water bodies, such as in fast-flowing rivers. Therefore, faecal indicator selection is less important in such systems and for these, FIB remains the most cost-effective faecal indicator to monitor the public health impacts of faecal contamination. In contrast, consideration of faecal indicator decay is important when assessing dispersion and advection/dispersion dominant systems, which would pertain to transitional (estuarine) and coastal waterbodies. Results suggest that the inclusion of viral indicators, such as crAssphage and PMMoV, could improve the reliability of water quality modelling and minimise the risk of waterborne illnesses from faecal contamination.

Exploration of the driving factors and distribution of fecal coliform in rivers under a traditional agro-pastoral economy in Kyrgyzstan, Central Asia

Fecal coliform (FC) in river water is one of the threats to human health. To explore the pollution status of FC in rivers of Kyrgyzstan, a mountainous country with traditional agro-pastoral economy, 184 water samples from the rivers of Kyrgyzstan in low and high river flow period were analyzed. Spatial autocorrelation and classical statistical methods were used to analyze the spatiotemporal distribution and driving factors of FC. The results showed that the surface water quality of Kyrgyz rivers was good, and the concentration range of FC was 0-23 MPN/100 mL. Temporally, the maximum FC concentration was 4 MPN/100 mL in low river flow period, while in the period of high river flow, the highest value reached to 23 MPN/100 mL. Spatially, the concentration of FC in high altitude areas was low, while that in the lowland areas was relatively high, which indicated that animal husbandry in high altitude areas contributed little to FC in rivers, and urban domestic sewage and agricultural activities in lowlands were the main pollution sources of FC in rivers. There was no correlation between FC and hardness, electrical conductivity (EC), pH and total organic carbon (TOC) in river water of Kyrgyzstan, and the distribution of FC in high river flow period was mainly driven by population and human modification of terrestrial systems. The results can provide a basis for the prevention and control of surface water FC pollution and related diseases in Kyrgyzstan.

Changes in Escherichia coli to enteric protozoa ratios in rivers: Implications for risk-based assessment of drinking water treatment requirements

Minimum treatment requirements are set in response to established or anticipated levels of enteric pathogens in the source water of drinking water treatment plants (DWTPs). For surface water, contamination can be determined directly by monitoring reference pathogens or indirectly by measuring fecal indicators such as Escherichia coli (E. coli). In the latter case, a quantitative interpretation of E. coli for estimating reference pathogen concentrations could be used to define treatment requirements. This study presents the statistical analysis of paired E. coli and reference protozoa (Cryptosporidium, Giardia) data collected monthly for two years in source water from 27 DWTPs supplied by rivers in Canada. E. coli/Cryptosporidium and E. coli/Giardia ratios in source water were modeled as the ratio of two correlated lognormal variables. To evaluate the potential of E. coli for defining protozoa treatment requirements, risk-based critical mean protozoa concentrations in source water were determined with a reverse quantitative microbial risk assessment (QMRA) model. Model assumptions were selected to be consistent with the World Health Organization (WHO) Guidelines for drinking-water quality. The sensitivity of mean E. coli concentration trigger levels to identify these critical concentrations in source water was then evaluated. Results showed no proportionalities between the log of mean E. coli concentrations and the log of mean protozoa concentrations. E. coli/protozoa ratios at DWTPs supplied by small rivers in agricultural and forested areas were typically 1.0 to 2.0-log lower than at DWTPs supplied by large rivers in urban areas. The seasonal variations analysis revealed that these differences were related to low mean E. coli concentrations during winter in small rivers. To achieve the WHO target of 10^-6 disability-adjusted life year (DALY) per person per year, a minimum reduction of 4.0-log of Cryptosporidium would be required for 20 DWTPs, and a minimum reduction of 4.0-log of Giardia would be needed for all DWTPs. A mean E. coli trigger level of 50 CFU 100 mL^-1 would be a sensitive threshold to identify critical mean concentrations for Cryptosporidium but not for Giardia. Treatment requirements higher than 3.0-log would be needed at DWTPs with mean E. coli concentrations as low as 30 CFU 100 mL^-1 for Cryptosporidium and 3 CFU 100 mL^-1 for Giardia. Therefore, an E. coli trigger level would have limited value for defining health-based treatment requirements for protozoa at DWTPs supplied by small rivers in rural areas.

Control strategies to improve the low water quality of Souk-Ahras city

This work reports control strategies of the water quality in the city of Souk-Ahras (east Algeria). With the recent development, rapid population growth, and the consequences of climate change, the capacity of water supply reserves becomes more unpredictable in the long term. This has drastically affected the distributed water quantity. A correlation between bacteriological water analysis and the analysis of pollution indicative physicochemical parameters is developed to replace the slow bacteriological analysis, which takes more than two days, by directly accessible physicochemical analysis to anticipate the case-onset of waterborne diseases. A good correlation is found between different combinations of physicochemical pollution parameters: (Turbidity, Nitrates); (Turbidity, Active chlorine) (nitrates, active chlorine); (Ammonium, Chlorine) and (Turbidity, Ammonium) with Spearman rank coefficients of 0.8657, -0.8602 and -0.8531 -0.8227 et 0.7957 respectively. Besides, long term analysis (over several years) revealed a high correlation of more than 0.92 between the analysis of pollution indicative physicochemical parameters and bacteriological analysis. The EPANET software is used to simulate the hydraulic behaviour of the network system over an extended period within pressurized and pressure-deficient conditions. The simulation results of several supply scenarios of daily drinking water pressure in the city center area show that 62% of drinking water distribution system is supplied with a steep slope (80 m), 10% with unsatisfactory pressure and only 23% with acceptable pressure (1–80 m).

Therefore, the high working pressure at the mesh, and the interruptions of the water supply are factors that can lead to the occurrence of cross-connection cases. This diagnosis of the defects in the water supply system is combined with a statistical data analysis of physicochemical parameters to set up an effective sampling strategy that takes into account the frequency of analysis and the areas at risk to prevent the risk of waterborne diseases.

Microbial risk associated with CSOs upstream of drinking water sources in a transboundary river using hydrodynamic and water quality modeling

Urban source water protection planning requires the characterization of sources of contamination upstream of drinking water intakes. Elevated pathogen concentrations following Combined Sewer Overflows (CSOs) represent a threat to human health. Quantifying peak pathogen concentrations at the intakes of drinking water plants is a challenge due to the variability of CSO occurrences and uncertainties with regards to the fate and transport mechanisms from discharge points to source water supplies. Here, a two-dimensional deterministic hydrodynamic and water quality model is used to study the fluvial contaminant transport and the impacts of the upstream CSO discharges on the downstream concentrations of Escherichia coli in the raw water supply of two drinking water plants, located on a large river. CSO dynamic loading characteristics were considered for a variety of discharges. As a result of limited Cryptosporidium data, a probability distribution of the ratio of E. coli to Cryptosporidium based on historical data was used to estimate microbial risk from simulated CSO-induced E. coli concentrations. During optimal operational performance of the plants, the daily risk target was met (based on the mean concentration during the peak) for 80% to 90% of CSO events. For suboptimal performance of the plants, these values dropped to 40% to 55%. Mean annual microbial risk following CSO discharge events was more dependent on treatment performance rather than the number of CSO occurrences. The effect of CSO-associated short term risk on the mean annual risk is largely dependent on the treatment performance as well as representativeness of the baseline condition at the intakes, demonstrating the need for assessment of treatment efficacy. The results of this study will enable water utilities and managers with a tool to investigate the potential alternatives in reducing the microbial risk associated with CSOs.

Cryptosporidium genotyping and land use mapping for hazard identification and source tracking in a small mixed rural-urban watershed in Southeastern Brazil

Cryptosporidium, faecal indicator organisms and physical and chemical water quality variables were monitored in a small mixed rural–urban watershed in southeastern Brazil. Cryptosporidium was present in 43% of 117 water samples analysed by microscopy. Concentrations varied from non-detects to 14 oocysts L−1. All samples were further analysed by nested-PCR, and Cryptosporidium spp. were detected in 24% (28) of them. Sequencing at the 18S rRNA locus gave high quality sequences in eight samples, revealing the presence of Cryptosporidium parvum. Cryptosporidium was not correlated with faecal indicator organisms (total coliforms, Escherichia coli, Enterococcus and coliphages), nor with physical and chemical water quality variables (e.g. turbidity, electrical conductivity and chemical oxygen demand), but it was with farm animal density (number of animals per ha). Land use mapping reinforced the suggestions from Cryptosporidium genotyping that both animals (livestock) and humans are potential sources to environmental contamination with oocysts within the watershed.

Cryptosporidium concentrations in rivers worldwide

Cryptosporidium is a leading cause of diarrhoea and infant mortality worldwide. A better understanding of the sources, fate and transport of Cryptosporidium via rivers is important for effective management of waterborne transmission, especially in the developing world. We present GloWPa-Crypto C1, the first global, spatially explicit model that computes Cryptosporidium concentrations in rivers, implemented on a 0.5 × 0.5° grid and monthly time step. To this end, we first modelled Cryptosporidium inputs to rivers from human faeces and animal manure. Next, we use modelled hydrology from a grid-based macroscale hydrological model (the Variable Infiltration Capacity model). Oocyst transport through the river network is modelled using a routing model, accounting for temperature- and solar radiation-dependent decay and sedimentation along the way. Monthly average oocyst concentrations are predicted to range from 10^-6 to 10² oocysts L^-1 in most places. Critical regions ('hotspots') with high concentrations include densely populated areas in India, China, Pakistan and Bangladesh, Nigeria, Algeria and South Africa, Mexico, Venezuela and some coastal areas of Brazil, several countries in Western and Eastern Europe (incl. The UK, Belgium and Macedonia), and the Middle East. Point sources (human faeces) appears to be a more dominant source of pollution than diffuse sources (mainly animal manure) in most world regions. Validation shows that GloWPa-Crypto medians are mostly within the range of observed concentrations. The model generally produces concentrations that are 1.5-2 log10 higher than the observations. This is likely predominantly due to the absence of recovery efficiency of the observations, which are therefore likely too low. Goodness of fit statistics are reasonable. Sensitivity analysis showed that the model is most sensitive to changes in input oocyst loads. GloWPa-Crypto C1 paves the way for many new opportunities at the global scale, including scenario analysis to investigate the impact of global change and management options on oocysts concentrations in rivers, and risk analysis to investigate human health risk.

Occurrence of Giardia intestinalis and Cryptosporidium sp. in wastewater samples from São Paulo State, Brazil, and Lima, Peru

The objectives of the study were to detect and genotype Cryptosporidium spp. and Giardia intestinalis in wastewater samples obtained from five cities with high transit of people in the State of São Paulo, Brazil, and at the entrance of a Wastewater Treatment Plant (WWTP) in Lima, Peru. Samples were collected and concentrated by centrifugation. The genomic DNA was extracted for molecular characterization by nested PCR for Cryptosporidium and double nested PCR for Giardia, followed by sequencing and phylogenetic analysis. G. intestinalis was found in 63.6 % of the samples, and the human assemblages A and B were identified. Cryptosporidium sp. was found in 36.4 % of the samples, and the species were corresponding to Cryptosporidium hominis, Cryptosporidium cuniculus, and Cryptosporidium muris. Results revealed the presence of human pathogenic Cryptosporidium species and G. intestinalis human pathogenic assemblages. Molecular tools highlight the importance to map the genetic diversity of these parasites, as well as to detect their epidemiological circulation pathway in the environment.

Detection of protozoa in water samples by formalin/ether concentration method

Methods to detect protozoa in water samples are expensive and laborious. We evaluated the formalin/ether concentration method to detect Giardia sp., Cryptosporidium sp. and Toxoplasma in water. In order to test the properties of the method, we spiked water samples with different amounts of each protozoa (0, 10 and 50 cysts or oocysts) in a volume of 10 L of water. Immunofluorescence assay was used for detection of Giardia and Cryptosporidium. Toxoplasma oocysts were identified by morphology. The mean percent of recovery in 10 repetitions of the entire method, in 10 samples spiked with ten parasites and read by three different observers, were for Cryptosporidium 71.3 ± 12, for Giardia 63 ± 10 and for Toxoplasma 91.6 ± 9 and the relative standard deviation of the method was of 17.5, 17.2 and 9.8, respectively. Intraobserver variation as measured by intraclass correlation coefficient, was fair for Toxoplasma, moderate for Cryptosporidium and almost perfect for Giardia. The method was then applied in 77 samples of raw and drinkable water in three different plant of water treatment. Cryptosporidium was found in 28 of 77 samples (36%) and Giardia in 31 of 77 samples (40%). Theses results identified significant differences in treatment process to reduce the presence of Giardia and Cryptosporidium. In conclusion, the formalin ether method to concentrate protozoa in water is a new alternative for low resources countries, where is urgently need to monitor and follow the presence of theses protozoa in drinkable water.

The current state of knowledge on the interaction of Escherichia coli within vegetative filter strips as a sustainable best management practice to reduce fecal pathogen loading into surface waters

Agro-pastoral operations have the potential to threaten public health with loading of diverse pathogens into surface waters through overland flow; increasing awareness of the limitations of fecal indicators has led to development of a number of advancements in detection, source tracking and predictive modeling of public health risk. These tools and techniques are beginning to be integrated into management strategies. The objective of this review was to determine the status of current knowledge and challenges of the fate and transport of Escherichia coli in overland flow and their interaction within vegetative filter strip (VFS) as one of these implemented best management practices and to critically evaluate its use in that setting as an indicator organism. With few studies directly focusing on VFS removal of E. coli from overland flow, we critically evaluated the available data on movement of E. coil from fecal source loading to retention and decay or re-release for potential contamination of water ways and pointed out potential limitations in both pathogen-specific removal and its use as an indicator organisms within overland flow and VFS. Critical areas of focus for future studies to reduce gaps in knowledge were identified, and the integration of newer approaches in source tracking, alternative indicators and the use of non-pathogenic surrogates for field testing of existing VFS models was encouraged. With VFS as a growing field of interest as an economical conservation practice and as an avenue for conservation of resources for small-scale agro-pastoral operations, management strategies to reduce initial fecal load from either applied manure constituents or shedding from free-range animals will continue to test the limits in the applications of models to overland flow and VFS management strategies. Further studies at the microscale in understanding discrepancies between low and high pathogenicity strains of E. coil and between E. coil and other fecal pathogens in the context of VFS will be critical. However, nuanced studies are needed to understand either biological or environmental differences in the fate and transport of the diverse types of fecal pathogens within these settings.

Cumulative effects of fecal contamination from combined sewer overflows: Management for source water protection

The quality of a drinking water source depends largely on upstream contaminant discharges. Sewer overflows can have a large influence on downstream drinking water intakes as they discharge untreated or partially treated wastewaters that may be contaminated with pathogens. This study focuses on the quantification of Escherichia coli discharges from combined sewer overflows (CSOs) and the dispersion and diffusion in receiving waters in order to prioritize actions for source water protection. E. coli concentrations from CSOs were estimated from monitoring data at a series of overflow structures and then applied to the 42 active overflow structures between 2009 and 2012 using a simple relationship based upon the population within the drainage network. From these estimates, a transport-dispersion model was calibrated with data from a monitoring program from both overflow structures and downstream drinking water intakes. The model was validated with 15 extreme events such as a large number of overflows (n > 8) or high concentrations at drinking water intakes. Model results demonstrated the importance of the cumulative effects of CSOs on the degradation of water quality downstream. However, permits are typically issued on a discharge point basis and do not consider cumulative effects. Source water protection plans must consider the cumulative effects of discharges and their concentrations because the simultaneous discharge of multiple overflows can lead to elevated E. coli concentrations at a drinking water intake. In addition, some CSOs have a disproportionate impact on peak concentrations at drinking water intakes. As such, it is recommended that the management of CSOs move away from frequency based permitting at the discharge point to focus on the development of comprehensive strategies to reduce cumulative and peak discharges from CSOs upstream of drinking water intakes.

The effects of combined sewer overflow events on riverine sources of drinking water

This study was set out to investigate the impacts of Combined Sewer Overflows (CSOs) on the microbiological water quality of a river used as a source of drinking water treatment plants. Escherichia coli concentrations were monitored at various stations of a river segment located in the Greater Montreal Area including two Drinking Water Intakes (DWIs) in different weather conditions (dry weather and wet weather (precipitation and snowmelt period)). Long-term monitoring data (2002-2011) at DWIs revealed good microbiological water quality with E. coli median concentrations of 20 and 30 CFU/100 mL for DWI-1 and DWI-2 respectively. However, E. coli concentration peaks reached up to 510 and 1000 CFU/100 mL for both DWIs respectively. Statistical Process Control (SPC) analysis allowed the identification of E. coli concentration peaks in almost a decade of routine monitoring data at DWIs. Almost 80% of these concentrations were linked to CSO discharges caused by precipitation exceeding 10 mm or spring snowmelt. Dry weather monitoring confirmed good microbiological water quality. Wet weather monitoring showed an increase of approximately 1.5 log of E. coli concentrations at DWIs. Cumulative impacts of CSO discharges were quantified at the river center with an increase of approximately 0.5 log of E. coli concentrations. Caffeine (CAF) was tested as a potential chemical indicator of CSO discharges in the river and CAF concentrations fell within the range of previous measurements performed for surface waters in the same area (∼20 ng/L). However, no significant differences were observed between CAF concentrations in dry and wet weather, as the dilution potential of the river was too high. CSO event based monitoring demonstrated that current bi-monthly or weekly compliance monitoring at DWIs underestimate E. coli concentrations entering DWIs and thus, should not be used to quantify the risk at DWIs. High frequency event-based monitoring is a desirable approach to establish the importance and duration of E. coli peak concentrations entering DWIs.

Estimation of concentration ratio of indicator to pathogen-related gene in environmental water based on left-censored data

A stochastic model for estimating the ratio between a fecal indicator and a pathogen based on left-censored data, which includes a substantially high number of non-detects, was constructed. River water samples were taken for 16 months at six points in a river watershed, and conventional fecal indicators (total coliforms and general Escherichia coli), genetic markers (Bacteroides spp.), and virulence genes (eaeA of enteropathogenic E. coli and ciaB of Campylobacter jejuni) were quantified. The quantification of general E. coli failed to predict the presence of the virulence gene from enteropathogenic E. coli, different from what happened with genetic markers (Total Bac and Human Bac). A Bayesian model that was adapted to left-censored data with a varying analytical quantification limit was applied to the quantitative data, and the posterior predictive distributions of the concentration ratio were predicted. When the sample size was 144, simulations conducted in this study suggested that 39 detects were enough to accurately estimate the distribution of the concentration ratio, when combined with a dataset with a positive rate higher than 99%. To evaluate the level of accuracy in the estimation, it is desirable to perform a simulation using an artificially generated left-censored dataset that has the identical number of non-detects as the actual data.

Source tracking of leaky sewers: a novel approach combining fecal indicators in water and sediments

In highly urbanized areas, surface water and groundwater are particularly vulnerable to sewer exfiltration. In this study, as an alternative to Microbial Source Tracking (MST) methods, we propose a new method combining microbial and chemical fecal indicators (Escherichia coli (E. coli)) and wastewater micropollutants (WWMPs) analysis both in water and sediment samples and under different meteorological conditions. To illustrate the use of this method, wastewater exfiltration and subsequent infiltration were identified and quantified by a three-year field study in an urban canal. The gradients of concentrations observed suggest that several sources of fecal contamination of varying intensity may be present along the canal, including feces from resident animal populations, contaminated surface run-off along the banks and under bridge crossings, release from contaminated banks, entrainment of contaminated sediments, and most importantly sewage exfiltration. Calculated exfiltration-infiltration volumes varied between 0.6 and 15.7 m(3)/d per kilometer during dry weather, and between 1.1 and 19.5 m(3)/d per kilometer during wet weather. WWMPs were mainly diluted and degraded below detection limits in water. E. coli remains the best exfiltration indicator given a large volume of dilution and a high abundance in the wastewater source. WWMPs are effective for detecting cumulated contamination in sediments from a small volume source and are particularly important because E. coli on its own does not allow source tracking.