Pathogens in water: value and limits of correlation with microbial indicators

Examination of the natural mineral water quality in the Kesserwan region, Lebanon

Introduction

Water is an essential element for life, especially the water that we drink. The water is consumable for humans as soon as it meets certain quality requirements. Any chemical, physical, or biological change in water quality may lead to harmful effects on health.

Objective

This study presents the updated situation of some spring water from groundwater in Lebanon, specifically in the Kesserwan region.

Method

To assess the quality of the water, certain physico-chemical parameters such as total dissolved solids, temperature, pH, and microbiological indicators were monitored on 15 sampling sources covering the Kesserwan region. All the parameters were studied during the winter period.

Results

The results identified multiple contaminated sources in Kesserwan. Consequently, groundwater cannot be consumed directly without treatment. Out of the 15 sources tested, only 8 were found to be microbiologically safe, while the remaining 7 were contaminated and required treatment before consumption or use.

Conclusion

Each municipality in the region should be responsible for protecting and maintaining the cleanliness of the areas surrounding the spring water. Additionally, regular, systematic testing of the spring water must be conducted to ensure its suitability for drinking by confirming the absence of contaminants.

The escalating threat of human-associated infectious bacteria in surface aquatic resources: Insights into prevalence, antibiotic resistance, survival mechanisms, detection, and prevention strategies

Anthropogenic activities and climate change profoundly impact water quality, leading to a concerning increase in the prevalence and abundance of bacterial pathogens across diverse aquatic environments. This rise has resulted in a growing challenge concerning the safety of water sources, particularly surface waters and marine environments. This comprehensive review delves into the multifaceted challenges presented by bacterial pathogens, emphasizing threads to human health within ground and surface waters, including marine ecosystems. The exploration encompasses the intricate survival mechanisms employed by bacterial pathogens and the proliferation of antimicrobial resistance, largely driven by human-generated antibiotic contamination in aquatic systems. The review further addresses prevalent pathogenic bacteria, elucidating associated risk factors, exploring their eco-physiology, and discussing the production of potent toxins. The spectrum of detection techniques, ranging from conventional to cutting-edge molecular approaches, is thoroughly examined to underscore their significance in identifying and understanding waterborne bacterial pathogens. A critical aspect highlighted in this review is the imperative for real-time monitoring of biomarkers associated with waterborne bacterial pathogens. This monitoring serves as an early warning system, facilitating the swift implementation of action plans to preserve and protect global water resources. In conclusion, this comprehensive review provides fresh insights and perspectives, emphasizing the paramount importance of preserving the quality of aquatic resources to safeguard human health on a global scale.

Municipal separate storm sewer system (MS4) dry weather flows and potential flow sources as assessed by conventional and advanced bacterial analyses

Municipal separate storm sewer systems (MS4s) function in urbanized areas to convey flows during both wet weather (i.e., stormwater) and dry weather (i.e., urban runoff as well as subsurface sources of flow) to receiving waters. While urban stormwater is known to contain microbial and chemical pollutants, MS4 dry weather flows, or non-stormwater discharges (NSWDs), are much less studied, although they are also known to contain pollutants, especially when these flows include raw sewage. In addition, some natural NSWDs (e.g., from groundwater infiltrating MS4 pipes) are critical for aquatic habitat protection. Thus, it is important to distinguish NSWD sources to prevent non-natural flows while retaining natural waters (i.e., groundwater). Here, MS4 dry weather flows were assessed by analyzing water samples from MS4 outfalls across multiple watersheds and water provider service areas in south Orange County, CA; potential NSWD sources including sewage, recycled water, potable water, and groundwater were sampled and analyzed for their likely contributions to overall NSWDs. Geochemical and microbiological water quality indicators, as well as bacterial communities, differed across NSWDs, yet water quality within most locations did not vary significantly diurnally or by sampling date. Meanwhile, NSWD source waters had distinctly different bacterial taxa abundances and specific bacterial genera. Shared geochemical and microbial characteristics of certain sources and outfall flows suggested the contributions of sources to outfall flows. The average proportions by sources contributing to MS4 outfalls were further estimated by SourceTracker and FEAST, respectively. The results of this study highlight the use of multiple tools when assessing chemical and microbiological water quality to predict sources of NSWDs contributing to urban MS4 flows during dry weather. This information can be used to support management actions to reduce unnatural and high risk sources of dry weather drainage while preserving natural sources important to environmental health in downstream receiving waters.

Enhanced detection of viruses for improved water safety

Human viruses pose a significant health risk in freshwater environments, but current monitoring methods are inadequate for detecting viral presence efficiently. We evaluated a novel passive in-situ concentration method using granular activated carbon (GAC). This study detected and quantified eight enteric and non-enteric, pathogenic viruses in a freshwater recreational lake in paired grab and GAC passive samples. The results found that GAC passive sampling had a higher detection rate for all viruses compared to grab samples, with adenovirus found to be the most prevalent virus, followed by respiratory syncytial virus, norovirus, enterovirus, influenza A, SARS-CoV-2, and rotavirus. GAC in-situ concentration allowed for the capture and recovery of viral gene copy targets that ranged from one to three orders of magnitude higher than conventional ex-situ concentration methods used in viral monitoring. This simple and affordable sampling method may have far-reaching implications for reducing barriers associated with viral monitoring across various environmental contexts.

Occurrence of human pathogenic viruses in drinking water and in its sources: A review

Since many waterborne diseases are caused by human pathogenic viruses, virus monitoring of drinking water (DW) and DW sources is crucial for public health. Therefore, the aim of this review was to describe the occurrence of human pathogenic viruses in DW and DW sources; the occurrence of two viruses proposed as novel indicators of human faecal contamination (Pepper mild mottle virus and Tobacco mosaic virus) was also reported. This research was focused on articles that assessed viral occurrence using molecular methods in the surface water used for DW production (SW-D), groundwater used for DW production (GW-D), DW and bottled-DW (BW). A total of 1544 studies published in the last 10 years were analysed, and 79 were ultimately included. In considering the detection methods, filtration is the most common concentration technique, while quantitative polymerase chain reaction is the most common quantification technique. Regarding virus occurrence in SW-D, GW-D, and DW, high percentages of positive samples were reported for adenovirus, polyomavirus and Pepper mild mottle virus. Viral genomes were frequently detected in SW-D and rarely in GW-D, suggesting that GW-D may be a safe DW source. Viral genomes were also detected in DW, posing a possible threat to human health. The lowest percentages of positive samples were found in Europe, while the highest were found in Asia and South America. Only three articles assessed viral occurrence in BW. This review highlights the lack of method standardization and the need for legislation updates.

Improvement of crAssphage detection/quantification method and its extensive application for food safety

Water-borne diseases are usually caused by the fecal-oral transmission of human fecal pathogens. Traditionally, coliforms and enterococci are widely used as indicator bacteria, but they do not allow to differentiate between human and animal fecal contamination. Owing to its presence only in the human gut environment, crAssphage has been suggested as an alternative indicator of human fecal contamination to overcome the above challenges. In this study, 139 human and 89 animal fecal samples (e.g., chicken, cow, dog, pig, pigeon, and mouse) were collected. For the rapid detection of human crAssphage in fecal samples, quantitative real-time PCR (qPCR) was performed using five different oligonucleotide primer/probe combinations. These included three previously reported oligonucleotide primer/probe combinations (RQ, CPQ056, and CrAssBP) and two newly developed combinations (ORF00018-targeting CrAssPFL1 and ORF00044-targeting CrAssPFL2). The detection rate (crAssphage-positive rate) in human fecal samples were 23.0, 30.2, 28.8, 20.1, and 30.9%, respectively, suggesting CrAssPFL2 showed the highest detection rate. Furthermore, the lowest copy numbers (436.16 copy numbers) could be detected using the CrAssPFL2 combination. Interestingly, no difference in crAssphage detection rates was found between healthy people and intestinal inflammatory patients. As expected, no crAssphage was detected in any animal fecal samples, indicating its human specificity. Furthermore, qPCR analysis of sewage samples collected from five different sewage treatment plants revealed that they were all contaminated with 10^5.71 copy numbers/mL of crAssphage on average. The simulation test of crAssphage-contaminated food samples also confirmed that the detection limit was from 10^7.55 copy numbers of crAssphage in foods. Therefore, the newly developed and optimized qPCR would be useful for the sensitive detection of crAssphage while identifying the source of human fecal contamination.

Flushing Temporarily Improves Microbiological Water Quality for Buildings Supplied with Chloraminated Surface Water but Has Little Effect for Groundwater Supplies

Microbial communities in premise plumbing systems were investigated after more than 2 months of long-term stagnation, during a subsequent flushing event, and during post-flush stagnation. Water samples were collected from showers in buildings supplied with chlorinated groundwater, untreated groundwater, and chloraminated surface water. The building supplied with chlorinated groundwater generally had the lowest bacterial concentrations across all sites (ranging from below quantification limit to 5.2 log copies/L). For buildings supplied with untreated groundwater, bacterial concentrations (5.0 to 7.6 log copies/L) and microbial community diversity index (ACE) values were consistent throughout sampling. Nontuberculous mycobacteria (NTM) and Legionella pneumophila were not detected in any groundwater-supplied buildings. Total bacteria, Legionella spp., and NTM were abundant in the surface water-supplied buildings following long-term stagnation (up to 7.6, 6.2, and 7.6 log copies/L, respectively). Flushing decreased these concentrations by ∼1 to >4 log units and reduced microbial community diversity, but the communities largely recovered within a week of post-flush stagnation. The results suggest that buildings supplied with disinfected surface water are more likely than buildings supplied with treated or untreated groundwater to experience deleterious changes in microbiological water quality during stagnation and that the water quality improvements from flushing with chloraminated water, while substantial, are short-lived.

Applicability of crAssphage as a performance indicator for viral reduction during activated sludge wastewater treatment

A major threat to water quality is the discharge of human-derived wastewater, which can cause waterborne illnesses associated with enteric viruses. A poor association exists between fecal indicator bacteria and virus fate in the environment, especially during wastewater treatment. In the current study, the potential of using a novel human gut bacteriophage crAssphage as a wastewater treatment process indicator was evaluated. Using qPCR, influent and effluent wastewater samples of two wastewater treatment plants were analyzed for crAssphage and human viruses including human bocavirus (HBoV), human adenovirus (HAdV), and human polyomavirus (HPyV). All samples were positive for crAssphage. The annual crAssphage concentrations varied between 1.45E + 04 and 2.39E + 08 gc/l in influent samples and from 1.25E + 04 to 7.88E + 06 gc/l in effluent samples. Human viruses concentrations were some orders of magnitude lower than that of crAssphage. Data demonstrated a significant correlation between crAssphage, HAdV, and HPyV during the wastewater treatment process, suggesting that crAssphage and human viral pathogens have similar removal mechanisms. Ultimately, this work concludes that crAssphage could be a performance indicator for viral reduction in the wastewater treatment process.

Conditional Forest Models Built Using Metagenomic Data Accurately Predicted Salmonella Contamination in Northeastern Streams

The use of water contaminated with Salmonella for produce production contributes to foodborne disease burden. To reduce human health risks, there is a need for novel, targeted approaches for assessing the pathogen status of agricultural water. We investigated the utility of water microbiome data for predicting Salmonella contamination of streams used to source water for produce production. Grab samples were collected from 60 New York streams in 2018 and tested for Salmonella. Separately, DNA was extracted from the samples and used for Illumina shotgun metagenomic sequencing. Reads were trimmed and used to assign taxonomy with Kraken2. Conditional forest (CF), regularized random forest (RRF), and support vector machine (SVM) models were implemented to predict Salmonella contamination. Model performance was assessed using 10-fold cross-validation repeated 10 times to quantify area under the curve (AUC) and Kappa score. CF models outperformed the other two algorithms based on AUC (0.86, CF; 0.81, RRF; 0.65, SVM) and Kappa score (0.53, CF; 0.41, RRF; 0.12, SVM). The taxa that were most informative for accurately predicting Salmonella contamination based on CF were compared to taxa identified by ALDEx2 as being differentially abundant between Salmonella-positive and -negative samples. CF and differential abundance tests both identified Aeromonas salmonicida (variable importance [VI] = 0.012) and Aeromonas sp. strain CA23 (VI = 0.025) as the two most informative taxa for predicting Salmonella contamination. Our findings suggest that microbiome-based models may provide an alternative to or complement existing water monitoring strategies. Similarly, the informative taxa identified in this study warrant further investigation as potential indicators of Salmonella contamination of agricultural water. IMPORTANCE Understanding the associations between surface water microbiome composition and the presence of foodborne pathogens, such as Salmonella, can facilitate the identification of novel indicators of Salmonella contamination. This study assessed the utility of microbiome data and three machine learning algorithms for predicting Salmonella contamination of Northeastern streams. The research reported here both expanded the knowledge on the microbiome composition of surface waters and identified putative novel indicators (i.e., Aeromonas species) for Salmonella in Northeastern streams. These putative indicators warrant further research to assess whether they are consistent indicators of Salmonella contamination across regions, waterways, and years not represented in the data set used in this study. Validated indicators identified using microbiome data may be used as targets in the development of rapid (e.g., PCR-based) detection assays for the assessment of microbial safety of agricultural surface waters.

Effects of water, sanitation, and hygiene interventions on detection of enteropathogens and host-specific faecal markers in the environment: a systematic review and individual participant data meta-analysis

BACKGROUND

Water, sanitation, and hygiene (WASH) improvements are promoted to reduce diarrhoea in low-income countries. However, trials from the past 5 years have found mixed effects of household-level and community-level WASH interventions on child health. Measuring pathogens and host-specific faecal markers in the environment can help investigate causal pathways between WASH and health by quantifying whether and by how much interventions reduce environmental exposure to enteric pathogens and faecal contamination from human and different animal sources. We aimed to assess the effects of WASH interventions on enteropathogens and microbial source tracking (MST) markers in environmental samples.

METHODS

We did a systematic review and individual participant data meta-analysis, which included searches from Jan 1, 2000, to Jan 5, 2023, from PubMed, Embase, CAB Direct Global Health, Agricultural and Environmental Science Database, Web of Science, and Scopus, of prospective studies with water, sanitation, or hygiene interventions and concurrent control group that measured pathogens or MST markers in environmental samples and measured child anthropometry, diarrhoea, or pathogen-specific infections. We used covariate-adjusted regression models with robust standard errors to estimate study-specific intervention effects and pooled effect estimates across studies using random-effects models.

FINDINGS

Few trials have measured the effect of sanitation interventions on pathogens and MST markers in the environment and they mostly focused on onsite sanitation. We extracted individual participant data on nine environmental assessments from five eligible trials. Environmental sampling included drinking water, hand rinses, soil, and flies. Interventions were consistently associated with reduced pathogen detection in the environment but effect estimates in most individual studies could not be distinguished from chance. Pooled across studies, we found a small reduction in the prevalence of any pathogen in any sample type (pooled prevalence ratio [PR] 0·94 [95% CI 0·90-0·99]). Interventions had no effect on the prevalence of MST markers from humans (pooled PR 1·00 [95% CI 0·88-1·13]) or animals (pooled PR 1·00 [95% CI 0·97-1·03]).

INTERPRETATION

The small effect of these sanitation interventions on pathogen detection and absence of effects on human or animal faecal markers are consistent with the small or null health effects previously reported in these trials. Our findings suggest that the basic sanitation interventions implemented in these studies did not contain human waste and did not adequately reduce exposure to enteropathogens in the environment.

FUNDING

Bill and Melinda Gates Foundation and the UK Foreign and Commonwealth Development Office.

Temporal stability of Salmonella enterica and Listeria monocytogenes in surface waters used for irrigation in the Mid-Atlantic United States

Enteric bacterial pathogen levels can influence the suitability of irrigation water sources for fruits and vegetables. We hypothesize that stable spatial patterns of Salmonella enterica and Listeria monocytogenes levels may exist across surface water sources in the Mid-Atlantic U.S. Water samples were collected at four streams and two pond sites in the mid-Atlantic U.S. over 2 years, biweekly during the fruit and vegetable growing seasons, and once a month during nongrowing seasons. Two stream sites and one pond site had significantly different mean concentrations in growing and nongrowing seasons. Stable spatial patterns were determined for relative differences between the site concentrations and average concentration of both pathogens across the study area. Mean relative differences were significantly different from zero at four of the six sites for S. enterica and three of six sites for L. monocytogenes. There was a similarity between the mean relative difference distribution between sites over growing season, nongrowing season, and the entire observation period. Mean relative differences were determined for temperature, oxidation-reduction potential, specific electrical conductance, pH, dissolved oxygen, turbidity, and cumulative rainfall. A moderate-to-strong Spearman correlation (r_s > 0.657) was found between spatial patterns of S. enterica and 7-day rainfall, and between relative difference patterns of L. monocytogenes and temperature (r_s = 0.885) and dissolved oxygen (r_s = -0.885). Persistence in ranking sampling sites by the concentrations of the two pathogens was also observed. Finding spatially stable patterns in pathogen concentrations highlights spatiotemporal dynamics of these microorganisms across the study area can facilitate the design of an effective microbial water quality monitoring program for surface irrigation water.

Biosensors for the detection of disease outbreaks through wastewater-based epidemiology

Wastewater-Based Epidemiology (WBE) is a novel community-wide monitoring tool that provides comprehensive real-time data of the public and environmental health status and can contribute to public health interventions, including those related to infectious disease outbreaks (e.g., the ongoing COVID-19 pandemic). Nonetheless, municipalities without centralized laboratories are likely still not able to process WBE samples. Biosensors are a potentially cost-effective solution to monitor the development of diseases through WBE to prevent local outbreaks. This review discusses the economic and technical feasibility of eighteen recently developed biosensors for the detection and monitoring of infectious disease agents in wastewater, prospecting the prevention of future pandemics.

A preliminary evaluation of microbial water quality in the irrigation pond

This study aimed to determine the microbial water quality of Imrahor Pond by enumerating the coliform bacteria levels in the area. Water samples were collected biweekly from the surface and bottom waters at seven points in the pond. Samples were analyzed for total coliforms, Escherichia coli, physicochemical parameters (water temperature, conductivity, pH, turbidity, dissolved oxygen, nitrate) and 1-day rainfall. The average values of TC and E. coli were 1487.4 and 36.3 MPN/100 ml, respectively. TC concentrations/physicochemical parameters were met at least 2nd class water quality class and E. coli results were met "guideline value" (E. coli < 250 MPN/100 ml) of national regulation. Overall, among measured physicochemical parameters, rainfall had the strongest positive correlation (r = 0.377 for total coliforms and r = 0.466 for E. coli, p < 0.05) with both indicators, indicted that surface runoff due to rainfall is the main factor which effects microbial water quality in the study area. This study demonstrated the preliminary microbial water quality results (TC and E. coli) in the Imrahor Pond and can serve as a basis for developing more precise water quality monitoring and management studies in the future. PRACTITIONER POINTS: Prevalence of TC and E. coli in the surface and bottom waters of Imrahor Pond were investigated for the first time. Imrahor Pond was met guideline value of national regulations based on E. coli concentrations, in the study period. Surface runoff after rainfall was the main environmental factor which influenced the microbial water quality of the pond.

Microbiomes in drinking water treatment and distribution: A meta-analysis from source to tap

A meta-analysis of existing and available Illumina 16S rRNA datasets from drinking water source, treatment and drinking water distribution systems (DWDS) were collated to compare changes in abundance and diversity throughout. Samples from bulk water and biofilm were used to assess principles governing microbial community assembly and the value of amplicon sequencing to water utilities. Individual phyla relationships were explored to identify competitive or synergistic factors governing DWDS microbiomes. The relative importance of stochasticity in the assembly of the DWDS microbiome was considered to identify the significance of source and treatment in determining communities in DWDS. Treatment of water significantly reduces overall species abundance and richness, with chlorination of water providing the most impact to individual taxa relationships. The assembly of microbial communities in the bulk water of the source, primary treatment process and DWDS is governed by more stochastic processes, as is the DWDS biofilm. DWDS biofilm is significantly different from bulk water in terms of local contribution to beta diversity, type and abundance of taxa present. Water immediately post chlorination has a more deterministic microbial assembly, highlighting the significance of this process in changing the microbiome, although elevated levels of stochasticity in DWDS samples suggest that this may not be the case at customer taps. 16S rRNA sequencing is becoming more routine, and may have several uses for water utilities, including: detection and risk assessment of potential pathogens such as those within the genera of Legionella and Mycobacterium; assessing the risk of nitrification in DWDS; providing improved indicators of process performance and monitoring for significant changes in the microbial community to detect contamination. Combining this with quantitative methods like flow cytometry will allow a greater depth of understanding of the DWDS microbiome.

Modeling Exposure to Fecal Contamination in Drinking Water due to Multiple Water Source Use

The Joint Monitoring Programme estimated that 71% of people globally had access to "safely managed" drinking water in 2017. However, typical data collection practices focus only on a household's primary water source, yet some households in low- and middle-income countries (LMICs) engage in multiple water source use, including supplementing improved water supplies with unimproved water throughout the year. Monte Carlo simulations and previously published data were used to simulate exposure to fecal contamination (as measured by E. coli) along a range of supplemental unimproved source use rates (e.g., 0-100% improved water use, with the remainder made up with unimproved water). The model results revealed a statistically significant increase in annual exposure to E. coli when individuals supplement their improved water with unimproved water just 2 days annually. Additionally, our analysis identified scenarios-realistic for the data set study setting-where supplementing with unimproved water counterintuitively decreases exposure to E. coli. These results highlight the need for evaluating the temporal dynamics in water quality and availability of drinking water sources in LMICs as well as capturing the use of multiple water sources for monitoring global access to safe drinking water.

Incidence of human associated HF183 Bacteroides marker and E. coli levels in New Orleans Canals

With a focus on five sites in an impaired, densely populated area in the New Orleans area, we investigated the temporal and spatial variability of standard FIB and a marker of human-associated pollution (Bacteroides HF183). With all sites combined, only a weak positive correlation (r = 0.345; p = 0.001) was observed between E. coli and HF183. Also, specific conductivity (r = - 0.374; p < 0.0001) and dissolved oxygen (r = - 0.390; p < 0.0001) were observed to show a weak moderate correlation with E. coli. These correlations increased to moderately negative when HF183 was correlated with specific conductivity (r = - 0.448; p < 0.0001) and dissolved oxygen (r = - 0.455; p < 0.0001). E. coli contamination was generally highest at the sites in the canal that are situated in the most densely populated part of the watershed while HF183 was frequently detected across all sites. E. coli concentrations were significantly higher (p < 0.05) when HF183 was present. HF183 was detected at significantly higher concentrations in samples that exceeded the EPA water quality standard (WQS) than those that did not (p < 0.05). Dissolved oxygen and specific conductivity were significantly lower when E. coli WQS was exceeded or when HF183 was present (p < 0.05). Rainfall impacted E. coli concentrations and HF183 differently at the study sites. While HF183 and E. coli concentrations levels were significantly higher (p < 0.05) if the days prior to sampling had been wet, the frequency of detection of HF183 was unimpacted, as comparable detection rates were recorded during wet and dry weather conditions. Without testing for HF183, it would have been assumed, based on testing for E. coli alone, that human fecal pollution was only associated with densely populated areas and rainfall events. E. coli alone may not be an effective indicator of sewage pollution at the study sites across all weather conditions and may need to be complemented with HF183 enumeration to optimize human fecal pollution identification and management at the watershed level.

Spatial and temporal dynamics and potential pathogenicity of fecal coliforms in coastal shallow groundwater wells

Access to water through shallow groundwater wells is a common practice in coastal settlements. This, coupled with a lack of planning for wastewater disposal promotes fecal contamination of groundwater and poses a threat to human health. Here, the spatial and temporal dynamics of groundwater fecal contamination was evaluated during summer and winter (2013 and 2014) in a coastal protected area having a high touristic relevance (Cabo Polonio, Uruguay). Fecal coliforms (FC) abundance in groundwater was significantly higher during summer, related to an influx of ~ 1000 tourists per day. A significant spatial autocorrelation was found in 2014, when the abundance of FC in a well was influenced by its three nearest wells (Moran and Geary tests). The applied statistical models (mixed models) indicated that total phosphorus and organic matter were the variables significantly explaining FC abundance. The risk for human health was estimated using groundwater-extracted DNA and qPCR of genes encoding for E. coli virulence factors (stx1, stx2, and eae). Potential Shiga toxin-producing enteropathogenic and enterohemorrhagic pathotypes were detected, even at FC abundances ≤ 1 CFU (100 mL^-1). Moreover, we found that contaminated groundwater reached the beach, being the presence of FC in sand detected even in winter and showing its highest frequency nearby groundwater wells consistently having high FC abundance (hot spots). Altogether, the results show that fecal contamination of shallow groundwater in Cabo Polonio involves a risk for human health that intensifies during summer (associated to a significant increase of tourists). This contamination also impacts the beach, where FC can remain through the whole year.

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.

Occurrence of male-specific and somatic coliphages and relationship with rainfall in privately-owned wells from peri‑urban and rural households

Privately-owned drinking water wells serving fewer than 25 people (private wells) are prevalent and understudied across most of the US. Private wells primarily serve rural households located outside of municipal drinking water and sewerage service coverage areas. These wells are not regulated by United States Environmental Protection Agency (EPA) under the Safe Drinking Water Act, are not regularly monitored by any public agency or utility, and generally do not undergo disinfection treatment. Coliphages are a group of viruses that infect coliform bacteria and are useful viral surrogates for fecal contamination in water systems in much the same way that fecal indicator bacteria (FIB), such as E. coli and to a lesser extent total coliforms, are used to quantify fecal contamination. Coliphages are approved by the EPA for regulatory monitoring in groundwater wells in the USA, but are not routinely used for this purpose. The present study characterizes the occurrence of male-specific and somatic coliphages, along with FIB, in private wells (n = 122) across two different counties in North Carolina. While occurrences of E. coli were rare and frequency of total coliform was generally low (~20%), male-specific and somatic coliphages were detectable in 66% and 54% of samples, respectively. Concentrations of male-specific coliphages were higher than somatics at each county and on a monthly basis. Rainfall appears to be partly influencing higher coliphage concentrations in December, January and February. This research underscores the need for increased surveillance in private wells and consideration of using coliphages in order to better characterize occurrence of fecal contamination at the time of sampling, especially during rainier months.

Longitudinal Effects of a Sanitation Intervention on Environmental Fecal Contamination in a Cluster-Randomized Controlled Trial in Rural Bangladesh

Household latrine access generally is not associated with reduced fecal contamination in the environment, but its long-term effectiveness has not been measured. We conducted an environmental assessment nested within the WASH Benefits Bangladesh randomized controlled trial (NCT01590095). We quantified E. coli and fecal coliforms in samples of stored drinking water, child hands, mother hands, soil, and food among a random sample of households from the sanitation and control arms of the trial. Samples were collected during eight quarterly visits approximately 1-3.5 years after intervention initiation. Overall, there were no substantial differences in environmental fecal contamination between households enrolled in the sanitation and control arms. Statistically significant reductions were found in stored water and child hands after pooling across sampling rounds, but the effects were small and not consistent across rounds. In addition, we assessed potential effect modification of intervention effects by follow-up time, season, wealth, community-level latrine density and coverage, population density, and domestic animal ownership. While the intervention had statistically significant effects within some subgroups, there were no consistent patterns of effect modification. Our findings support a growing consensus that on-site latrines are insufficient to prevent fecal contamination in the rural household environment.

Removal of Pathogens in Onsite Wastewater Treatment Systems: A Review of Design Considerations and Influencing Factors

Conventional onsite wastewater treatment systems (OWTSs) could potentially contribute to the transmission of infectious diseases caused by waterborne pathogenic microorganisms and become an important human health concern, especially in the areas where OWTSs are used as the major wastewater treatment units. Although previous studies suggested the OWTSs could reduce chemical pollutants as well as effectively reducing microbial contaminants from onsite wastewater, the microbiological quality of effluents and the factors potentially affecting the removal are still understudied. Therefore, the design and optimization of pathogen removal performance necessitate a better mechanistic understanding of the hydrological, geochemical, and biological processes controlling the water quality in OWTSs. To fill the knowledge gaps, the sources of pathogens and common pathogenic indicators, along with their major removal mechanisms in OWTSs were discussed. This review evaluated the effectiveness of pathogen removal in state-of-art OWTSs and investigated the contributing factors for efficient pathogen removal (e.g., system configurations, filter materials, environmental and operational conditions), with the aim to guide the future design for optimized treatment performance.

Salmonella Genomics and Population Analyses Reveal High Inter- and Intraserovar Diversity in Freshwater

Freshwater can support the survival of the enteric pathogen Salmonella, though temporal Salmonella diversity in a large watershed has not been assessed. At 28 locations within the Susquehanna River basin, 10-liter samples were assessed in spring and summer over 2 years. Salmonella prevalence was 49%, and increased river discharge was the main driver of Salmonella presence. The amplicon-based sequencing tool, CRISPR-SeroSeq, was used to determine serovar population diversity and detected 25 different Salmonella serovars, including up to 10 serovars from a single water sample. On average, there were three serovars per sample, and 80% of Salmonella-positive samples contained more than one serovar. Serovars Give, Typhimurium, Thompson, and Infantis were identified throughout the watershed and over multiple collections. Seasonal differences were evident: serovar Give was abundant in the spring, whereas serovar Infantis was more frequently identified in the summer. Eight of the ten serovars most commonly associated with human illness were detected in this study. Crucially, six of these serovars often existed in the background, where they were masked by a more abundant serovar(s) in a sample. Serovars Enteritidis and Typhimurium, especially, were masked in 71 and 78% of samples where they were detected, respectively. Whole-genome sequencing-based phylogeny demonstrated that strains within the same serovar collected throughout the watershed were also very diverse. The Susquehanna River basin is the largest system where Salmonella prevalence and serovar diversity have been temporally and spatially investigated, and this study reveals an extraordinary level of inter- and intraserovar diversity.IMPORTANCESalmonella is a leading cause of bacterial foodborne illness in the United States, and outbreaks linked to fresh produce are increasing. Understanding Salmonella ecology in freshwater is of importance, especially where irrigation practices or recreational use occur. As the third largest river in the United States east of the Mississippi, the Susquehanna River is the largest freshwater contributor to the Chesapeake Bay, and it is the largest river system where Salmonella diversity has been studied. Rainfall and subsequent high river discharge rates were the greatest indicators of Salmonella presence in the Susquehanna and its tributaries. Several Salmonella serovars were identified, including eight commonly associated with foodborne illness. Many clinically important serovars were present at a low frequency within individual samples and so could not be detected by conventional culture methods. The technologies employed here reveal an average of three serovars in a 10-liter sample of water and up to 10 serovars in a single sample.

Aptamers and Aptamer-Coupled Biosensors to Detect Water-Borne Pathogens

Aptamers can serve as efficient bioreceptors for the development of biosensing detection platforms. Aptamers are short DNA or RNA oligonucleotides that fold into specific structures, which enable them to selectively bind to target analytes. The method used to identify aptamers is Systematic Evolution of Ligands through Exponential Enrichment (SELEX). Target properties can have an impact on aptamer efficiencies. Therefore, characteristics of water-borne microbial targets must be carefully considered during SELEX for optimal aptamer development. Several aptamers have been described for key water-borne pathogens. Here, we provide an exhaustive overview of these aptamers and discuss important microbial aspects to consider when developing such aptamers.

Predictive Models May Complement or Provide an Alternative to Existing Strategies for Assessing the Enteric Pathogen Contamination Status of Northeastern Streams Used to Provide Water for Produce Production

While the Food Safety Modernization Act established standards for the use of surface water for produce production, water quality is known to vary over space and time. Targeted approaches for identifying hazards in water that account for this variation may improve growers’ ability to address pre-harvest food safety risks. Models that utilize publicly-available data (e.g., land-use, real-time weather) may be useful for developing these approaches. The objective of this study was to use pre-existing datasets collected in 2017 (N = 181 samples) and 2018 (N = 191 samples) to train and test models that predict the likelihood of detecting Salmonella and pathogenic E. coli markers (eaeA, stx) in agricultural water. Four types of features were used to train the models: microbial, physicochemical, spatial and weather. “Full models” were built using all four features types, while “nested models” were built using between one and three types. Twenty learners were used to develop separate full models for each pathogen. Separately, to assess information gain associated with using different feature types, six learners were randomly selected and used to develop nine, nested models each. Performance measures for each model were then calculated and compared against baseline models where E. coli concentration was the sole covariate. In the methods, we outline the advantages and disadvantages of each learner. Overall, full models built using ensemble (e.g., Node Harvest) and “black-box” (e.g., SVMs) learners out-performed full models built using more interpretable learners (e.g., tree- and rule-based learners) for both outcomes. However, nested eaeA-stx models built using interpretable learners and microbial data performed almost as well as these full models. While none of the nested Salmonella models performed as well as the full models, nested models built using spatial data consistently out-performed models that excluded spatial data. These findings demonstrate that machine learning approaches can be used to predict when and where pathogens are likely to be present in agricultural water. This study serves as a proof-of-concept that can be built upon once larger datasets become available and provides guidance on the learner-data combinations that should be the foci of future efforts (e.g., tree-based microbial models for pathogenic E. coli).

Fecal Indicator Bacteria Transport from Watersheds with Differing Wastewater Technologies and Septic System Densities

Wastewater contains elevated concentrations of fecal indicator bacteria (FIB). The type of wastewater treatment technology and septic system density may influence the FIB concentration and exports at the watershed scale. The goal of this study was to gain a better understanding of FIB concentrations and exports from watersheds served by conventional septic (CS) systems, sand filter (SF) septic systems, and a municipal sewer (SEW) system. Seven watersheds (3 CS, 3 SF, and 1 SEW) were monitored to quantify FIB concentration and export monthly from April 2015 to March 2016. The type of wastewater treatment did not yield significant differences in FIB concentration or exports when pooling watersheds using similar wastewater treatment. Watersheds with the highest septic densities (approximately 0.4 systems ha−1) contained greater FIB concentrations and exports than watersheds with the lowest (approximately 0.1–0.2 systems ha−1), but only FIB concentrations significantly differed. These findings suggest that when the septic system density exceeds 0.4 systems ha−1, water quality degradation from septic leachate may be observable at the watershed scale, especially in watersheds dominated by residential development. More research is recommended to determine if this density threshold is similar for other water pollutants and/or in watersheds with differing hydrogeological, land use, and wastewater characteristics.

Stochastic determination of the spatial variation of potentially pathogenic bacteria communities in a large subtropical river

Understanding the composition and assembly mechanism of waterborne pathogen is essential for preventing the pathogenic infection and protecting the human health. Here, based on 16S rRNA sequencing, we investigated the composition and spatial variation of potentially pathogenic bacteria from different sections of the Pearl River, the most important source of water for human in Southern China. The results showed that the potential pathogen communities consisted of 6 phyla and 64 genera, covering 11 categories of potential pathogens mainly involving animal parasites or symbionts (AniP), human pathogens all (HumPA), and intracellular parasites (IntCelP). Proteobacteria (75.87%) and Chlamydiae (20.56%) were dominant at the phylum level, and Acinetobacter (35.01%) and Roseomonas (8.24%) were dominant at the genus level. Multivariate analysis showed that the potential pathogenic bacterial community was significantly different among the four sections in the Pearl River. Both physicochemical factors (e.g., NO₃-N, and suspended solids) and land use (e.g., urban land and forest) significantly shaped the pathogen community structure. However, spatial effects contributed more to the variation of pathogen community based on variation partitioning and path analysis. Null model based normalized stochasticity ratio analysis further indicated that the stochastic process rather than deterministic process dominated the assembly mechanisms by controlling the spatial patterns of potential pathogens. In conclusion, high-throughput sequencing shows great potential for monitoring the potential pathogens, and provided more comprehensive information on the potentially pathogenic community. Our study highlighted the importance of considering the influences of dispersal-related processes in future risk assessments for the prevention and control of pathogenic bacteria.

The Composition of Microbial Communities in Six Streams, and Its Association With Environmental Conditions, and Foodborne Pathogen Isolation

Surface water used for produce production is a potential source of pre-harvest contamination with foodborne pathogens. Decisions on how to mitigate food safety risks associated with pre-harvest water use currently rely on generic Escherichia coli-based water quality tests, although multiple studies have suggested that E. coli levels are not a suitable indicator of the food safety risks under all relevant environmental conditions. Hence, improved understanding of spatiotemporal variability in surface water microbiota composition is needed to facilitate identification of alternative or supplementary indicators that co-occur with pathogens. To this end, we aimed to characterize the composition of bacterial and fungal communities in the sediment and water fractions of 68 agricultural water samples collected from six New York streams. We investigated potential associations between the composition of microbial communities, environmental factors and Salmonella and/or Listeria monocytogenes isolation. We found significantly different composition of fungal and bacterial communities among sampled streams and among water fractions of collected samples. This indicates that geography and the amount of sediment in a collected water sample may affect its microbial composition, which was further supported by identified associations between the flow rate, turbidity, pH and conductivity, and microbial community composition. Lastly, we identified specific microbial families that were weakly associated with the presence of Salmonella or Listeria monocytogenes, however, further studies on samples from additional streams are needed to assess whether identified families may be used as indicators of pathogen presence.

Pathogen infection risk to recreational water users, associated with surface waters impacted by de facto and indirect potable reuse activities

Water deficit, exacerbated by global population increases and climate change, necessitates the investigation of alternative non-traditional water sources to augment existing supplies. Indirect potable reuse (IPR) represents a promising alternative water source in water-stressed regions. Of high concern is the presence of pathogenic microorganisms in wastewater, such as enteric viruses, protozoa and bacteria. Therefore, a greater understanding of the potential impact to human health is required. The aim of this research was to use a quantitative microbial risk assessment (QMRA) approach to calculate the probability of potential pathogen infection risk to the public in surface waters used for a range of recreational activities under scenarios: 1) existing de facto wastewater reuse conditions; 2) after augmentation with conventionally treated wastewater; and 3) after augmentation with reclaimed wastewater from proposed IPR schemes. Forty-four 31 l samples were collected from river sites and a coastal wastewater treatment works from July 2016-May 2017. Concentrations of faecal indicator organisms (enterococci, faecal coliforms, somatic coliphages and Bacteroides phages) determined using culture-based approaches and selected pathogens (adenovirus, Salmonella and Cryptosporidium) determined using molecular approaches (qPCR) were used to inform QMRA. The mean probability of infection from adenovirus under de facto conditions was high (>0.90) for all recreational activities, per single event. The risk of adenovirus and Cryptosporidium infection increased under augmentation scenario (2) (mean probability 0.95-1.00 and 0.01-0.06 per single event, respectively). Adenovirus and Cryptosporidium infection risk decreased under reclaimed water augmentation scenario (3) (mean probability <0.79, excluding swimming, which remained 1.00 and <0.01 per single event, respectively). Pathogen reduction after reclaimed water augmentation in surface waters impacted by de facto reuse, provides important evidence for alternative water supply option selection. As such, this evidence may inform water managers and the public of the potential benefits of IPR and improve acceptance of such practices in the future.

Gastroenteric Viruses Detection in a Drinking Water Distribution-to-Consumption System in a Low-Income Community in Rio de Janeiro

The availability of drinking water is one of the main determinants of quality of life, disease prevention and the promotion of health. Viruses are important agents of waterborne diseases and have been described as important markers of human faecal contamination. This study aimed to investigate viruses' presence as an indicator of drinking water quality in low-income communities in the Manguinhos area, Rio de Janeiro, Brazil. Three hundred and four drinking water samples (2L/each) were collected along the drinking water distribution-to-consumption pathway in households, as well as healthcare and school units. Water samples were collected both directly from the water supply prior to distribution and after storage in tanks and filtration units. Using qPCR, viruses were detected 50 times in 45 water samples (15%), 19 of these being human adenovirus, 17 rotavirus A and 14 norovirus GII. Viral loads recovered ranged from 5E+10 to 8.7E+10⁶ genome copies/Liter. Co-detection was observed in five household water samples and there was no difference regarding virus detection across sampling sites. Precarious and inadequate environmental conditions characterized by the lack of local infrastructure regarding basic sanitation and waste collection in the territory, as well as negligent hygiene habits, could explain viral detection in drinking water in regions with a water supply system.

A critical analysis of recreational water guidelines developed from temperate climate data and applied to the tropics

Recreational water epidemiology studies are rare in settings with minimal wastewater treatment where risk may be highest, and in tropical settings where warmer temperature influences the ecology of fecal indicator bacteria commonly used to monitor recreational waters. One exception is a 1999 study conducted in São Paulo Brazil. We compared the risk and exposure characteristics of these data with those conducted in the United Kingdom (UK) in the early 1990s that are the basis of the World Health Organization's (WHO) guidelines on recreational water risks. We then developed adjusted risk difference models (excess gastrointestinal illness per swimming event) for children (<10 years of age) and non-children (≥10 years of age) across five Brazil beaches. We used these models along with beach water quality data from 2004 to 2015 to assess spatial and temporal trends in water quality and human risk. Risk models indicate that children in Brazil have as much as two times the risk of gastrointestinal illness than non-children. In Brazil, 11.8% of the weekly water samples from 2004 to 2015 exceeded 158 enterococci CFU/100 ml, the highest level of fecal streptococci concentration measured in the UK study. Risks associated with these elevated levels equated to median NEEAR-Gastrointestinal Illness (NGI) risks of 53 and 96 excess cases per 1000 swimmers in non-children and children, respectively. Two of the five beaches appear to drive the overall elevated NGI risks seen during this study. Distinct enteric pathogen profiles that exist in tropical settings as well as in settings with minimal wastewater treatment highlight the importance of regionally specific guideline development.

Integration of weather conditions for predicting microbial water quality using Bayesian Belief Networks

Levels of fecal indicator bacteria (FIB) provide a surrogate measure of the microbial quality of water used for a wide range of applications. Despite the common use of these measures, a significant limitation is a delay in results due to the time required for cultivation and enumeration of FIB. Testing requires at least 18-24 h, and therefore, FIB cannot be used to identify current or real-time microbial water quality. An approach of nowcasting or empirical modelling approaches that incorporate water quality, environmental, and weather variables to predict FIB levels in real-time has been developed with some success. However, FIB levels are dependent on a complex interaction of numerous variables, which can be challenging to model with ordinary linear regression or classification methods most commonly applied. In this study, novel use of Bayesian Belief Networks (BBNs) that allow for a probabilistic representation of complex variable interactions is investigated for real-time modelling of FIB levels surface waters. In particular, the integration of both water quality measures and current/historical weather for prediction of fecal coliforms and Escherichia coli levels is achieved using BBNs. For 4-bin classification of fecal coliform levels, BBNs increased prediction accuracy by 25%-54% compared to other previously used techniques including logistic regression, Naïve Bayes, and random forests. Binary prediction of E. coli levels exceeding a threshold of 20 CFU/100 mL was also significantly improved using BBNs with prediction accuracies >90% for all monitoring sites. Advantages of the BBN approach are also demonstrated identifying the ability to make predictions from incomplete monitoring data as well as probabilistic inference of variable importance in FIB levels. In particular, the results indicate that water quality surrogates such as conductivity are essential to real-time prediction of FIB. The results and models described in this work can be readily utilized to provide accurate and real-time assessments of FIB levels in surface waters utilizing commonly monitored parameters.

Complex Interactions Between Weather, and Microbial and Physicochemical Water Quality Impact the Likelihood of Detecting Foodborne Pathogens in Agricultural Water

Agricultural water is an important source of foodborne pathogens on produce farms. Managing water-associated risks does not lend itself to one-size-fits-all approaches due to the heterogeneous nature of freshwater environments. To improve our ability to develop location-specific risk management practices, a study was conducted in two produce-growing regions to (i) characterize the relationship between Escherichia coli levels and pathogen presence in agricultural water, and (ii) identify environmental factors associated with pathogen detection. Three AZ and six NY waterways were sampled longitudinally using 10-L grab samples (GS) and 24-h Moore swabs (MS). Regression showed that the likelihood of Salmonella detection (Odds Ratio [OR] = 2.18), and eaeA-stx codetection (OR = 6.49) was significantly greater for MS compared to GS, while the likelihood of detecting L. monocytogenes was not. Regression also showed that eaeA-stx codetection in AZ (OR = 50.2) and NY (OR = 18.4), and Salmonella detection in AZ (OR = 4.4) were significantly associated with E. coli levels, while Salmonella detection in NY was not. Random forest analysis indicated that interactions between environmental factors (e.g., rainfall, temperature, turbidity) (i) were associated with likelihood of pathogen detection and (ii) mediated the relationship between E. coli levels and likelihood of pathogen detection. Our findings suggest that (i) environmental heterogeneity, including interactions between factors, affects microbial water quality, and (ii) E. coli levels alone may not be a suitable indicator of food safety risks. Instead, targeted methods that utilize environmental and microbial data (e.g., models that use turbidity and E. coli levels to predict when there is a high or low risk of surface water being contaminated by pathogens) are needed to assess and mitigate the food safety risks associated with preharvest water use. By identifying environmental factors associated with an increased likelihood of detecting pathogens in agricultural water, this study provides information that (i) can be used to assess when pathogen contamination of agricultural water is likely to occur, and (ii) facilitate development of targeted interventions for individual water sources, providing an alternative to existing one-size-fits-all approaches.

Strengths of correlations with formation of chlorination disinfection byproducts: effects of predictor type and other factors

Measurements of the UV-Vis absorbance (Abs) and intensity of fluorescence emission (Fluor), as well as of concentrations of total or dissolved organic carbon (OC) in aqueous samples are commonly used to estimate the potential for disinfection byproducts (DBPs) formation during water chlorination. In this work, based on 574 linear associations collected from 70 experimental research papers published over the period of 1997-2019, the strengths of the correlations of Abs, Fluor, and OC with DBPs concentrations are compared. The correlations were expressed as approximately normally distributed Z-scores using Fisher variance-stabilizing transformation. The effects of specific prediction method, chlorination agent, water source, and DBPs type, with consideration of possible effects due to the presence of bromide, are examined against Z-scores by ANOVA, testing main effects and some variables interactions. The performed analysis is a first attempt to expose differences and patterns in correlation strengths associated with DBPs formation, based on systematically covered broad existing literature. Abs and OC concentration of water samples tend to demonstrate the strongest correlations with DBPs formation as compared with specific UV absorbance (SUVA) or intensity of fluorescence emission. Correlations of DBPs formation during chloramination demonstrated weaker strengths as compared with other chlorination agents, suggesting more caution in predicting DBPs concentrations, based on simple descriptors such as Abs, OC, and Fluor. In a series of different water types, the correlations with DBPs formation are expected to be enhanced, when wastewater is chlorinated. Non-fluorescent matter may be an important contributor to DBPs formation during water chlorination. When fluorescence intensity is considered as a predicting tool, choosing humic-like rather than proteinaceous fluorescence may enhance the strengths of the correlations with DBPs formation. Different performances of Abs, OC, and Fluor in correlating with DBPs formation may be beneficial for their concurrent use helping to optimize removal of different DBPs precursors.

Landscape, Water Quality, and Weather Factors Associated With an Increased Likelihood of Foodborne Pathogen Contamination of New York Streams Used to Source Water for Produce Production

There is a need for science-based tools to (i) help manage microbial produce safety hazards associated with preharvest surface water use, and (ii) facilitate comanagement of agroecosystems for competing stakeholder aims. To develop these tools an improved understanding of foodborne pathogen ecology in freshwater systems is needed. The purpose of this study was to identify (i) sources of potential food safety hazards, and (ii) combinations of factors associated with an increased likelihood of pathogen contamination of agricultural water Sixty-eight streams were sampled between April and October 2018 (196 samples). At each sampling event separate 10-L grab samples (GS) were collected and tested for Listeria, Salmonella, and the stx and eaeA genes. A 1-L GS was also collected and used for Escherichia coli enumeration and detection of four host-associated fecal source-tracking markers (FST). Regression analysis was used to identify individual factors that were significantly associated with pathogen detection. We found that eaeA-stx codetection [Odds Ratio (OR) = 4.2; 95% Confidence Interval (CI) = 1.3, 13.4] and Salmonella isolation (OR = 1.8; CI = 0.9, 3.5) were strongly associated with detection of ruminant and human FST markers, respectively, while Listeria spp. (excluding Listeria monocytogenes) was negatively associated with log10 E. coli levels (OR = 0.50; CI = 0.26, 0.96). L. monocytogenes isolation was not associated with the detection of any fecal indicators. This observation supports the current understanding that, unlike enteric pathogens, Listeria is not fecally-associated and instead originates from other environmental sources. Separately, conditional inference trees were used to identify scenarios associated with an elevated or reduced risk of pathogen contamination. Interestingly, while the likelihood of isolating L. monocytogenes appears to be driven by complex interactions between environmental factors, the likelihood of Salmonella isolation and eaeA-stx codetection were driven by physicochemical water quality (e.g., dissolved oxygen) and temperature, respectively. Overall, these models identify environmental conditions associated with an enhanced risk of pathogen presence in agricultural water (e.g., rain events were associated with L. monocytogenes isolation from samples collected downstream of dairy farms; P = 0.002). The information presented here will enable growers to comanage their operations to mitigate the produce safety risks associated with preharvest surface water use.

Decay of infectious adenovirus and coliphages in freshwater habitats is differentially affected by ambient sunlight and the presence of indigenous protozoa communities

BACKGROUND

Sanitary quality of recreational waters worldwide is assessed using fecal indicator bacteria (FIB), such as Escherichia coli and enterococci. However, fate and transport characteristics of FIB in aquatic habitats can differ from those of viral pathogens which have been identified as main etiologic agents of recreational waterborne illness. Coliphages (bacteriophages infecting E. coli) are an attractive alternative to FIB because of their many morphological and structural similarities to viral pathogens.

METHODS

In this in situ field study, we used a submersible aquatic mesocosm to compare decay characteristics of somatic and F+ coliphages to those of infectious human adenovirus 2 in a freshwater lake. In addition, we also evaluated the effect of ambient sunlight (and associated UV irradiation) and indigenous protozoan communities on decay of somatic and F+ coliphage, as well as infectious adenovirus.

RESULTS

Our results show that decay of coliphages and adenovirus was similar (p = 0.0794), indicating that both of these bacteriophage groups are adequate surrogates for decay of human adenoviruses. Overall, after 8 days the greatest log10 reductions were observed when viruses were exposed to a combination of biotic and abiotic factors (2.92 ± 0.39, 4.48 ± 0.38, 3.40 ± 0.19 for somatic coliphages, F+ coliphages and adenovirus, respectively). Both, indigenous protozoa and ambient sunlight, were important contributors to decay of all three viruses, although the magnitude of that effect differed over time and across viral targets.

CONCLUSIONS

While all viruses studied decayed significantly faster (p < 0.0001) when exposed to ambient sunlight, somatic coliphages were particularly susceptible to sunlight irradiation suggesting a potentially different mechanism of UV damage compared to F+ coliphages and adenoviruses. Presence of indigenous protozoan communities was also a significant contributor (p value range: 0.0016 to < 0.0001) to decay of coliphages and adenovirus suggesting that this rarely studied biotic factor is an important driver of viral reductions in freshwater aquatic habitats.

Bathing Activities and Microbiological River Water Quality in the Paris Area: A Long-Term Perspective

This chapter presents the historical aspects regarding swimming in rivers in the Paris region since the seventeenth century, including the concept of fecal contamination indicator bacteria (FIBs) developed at the very beginning of the twentieth century, and historical contamination data covering more than one century in the Paris agglomeration. The sources of microbiological contamination of river waters are quantified, showing the importance of rain events. The present contamination levels are presented with reference to the European Directive for bathing water quality. FIB levels show that the sufficient quality for bathing is not reached yet in any of the monitored stations. A comprehensive data set regarding waterborne pathogens (viruses, Giardia, Cryptosporidium) in the Seine and Marne rivers is presented as a necessary complement to the regulatory FIB data to better evaluate health risks. The last section concludes on the actions to be conducted to improve the rivers’ microbiological quality in the coming years.

A Comprehensive Review of Microfluidic Water Quality Monitoring Sensors

Water crisis is a global issue due to water contamination and extremely restricted sources of fresh water. Water contamination induces severe diseases which put human lives at risk. Hence, water quality monitoring has become a prime activity worldwide. The available monitoring procedures are inadequate as most of them require expensive instrumentation, longer processing time, tedious processes, and skilled lab technicians. Therefore, a portable, sensitive, and selective sensor with in situ and continuous water quality monitoring is the current necessity. In this context, microfluidics is the promising technology to fulfill this need due to its advantages such as faster reaction times, better process control, reduced waste generation, system compactness and parallelization, reduced cost, and disposability. This paper presents a review on the latest enhancements of microfluidic-based electrochemical and optical sensors for water quality monitoring and discusses the relative merits and shortcomings of the methods.

Evaluation of Occurrence, Concentration, and Removal of Pathogenic Parasites and Fecal Coliforms in Three Waste Stabilization Pond Systems in Tanzania

In Tanzania, waste stabilization ponds (WSPs) are employed to treat wastewater, and effluents are used for urban agricultural activities. The use of untreated or partially treated wastewater poses risks of disease transmission, including parasitic and bacterial infections, to exposed communities. Little is known about the occurrence, concentration, and removal of parasites and fecal coliform (FC) bacteria in WSPs in Tanzania. This study evaluates the occurrence and concentration of parasites and FCs in wastewater, the efficiency of WSPs in removing parasites and FCs, and the validity of using FCs as an indicator of parasites. This was a cross-sectional study conducted between February and August 2018. Wastewater samples were collected from three WSPs located in the Morogoro, Mwanza, and Iringa regions. APHA methods were used to test physicochemical parameters. The modified Bailenger method and Ziehl–Neelsen stain were used to analyse parasites. Membrane filtration method was used to analyse FCs. Data were analysed using IBM SPSS version 20. Helminth egg removal ranged from 80.8% to 100%. Protozoan (oo)cyst removal ranged from 98.8% to 99.9%. The Mwanza WSP showed the highest FC reduction (3.8 log units (100 mL)⁻¹). Both the parasites and FCs detected in the effluents of assessed WSPs were of higher concentrations than World Health Organization and Tanzania Bureau of Standards limits, except for helminths in the Morogoro WSP and FCs in the Mwanza WSP. FCs were significantly correlated with protozoa (p < 0.01) and predicted protozoa occurrence well (p=0.011). There were correlations between physicochemical parameters, parasites, and FC bacteria in the WSP systems. Inadequate performance of these systems may be due to lack of regular maintenance and/or systems operating beyond their capacity. FC indicators were observed to be a good alternative for protozoa monitoring, but not for helminths. Therefore, during wastewater quality monitoring, helminths should be surveyed independently.

Overview of Monitoring Techniques for Evaluating Water Quality at Potable Reuse Treatment Facilities

Needless to say, the safety of treated water for potable reuse must be definitively ensured. Numerous methods are available for assessing water quality; it's important to understand their challenges and limitations.

Quantitative microbial risk assessment and its applications in small water systems: A review

Quantitative microbial risk assessment (QMRA) has been mainstreamed in many large municipal water systems as part of a paradigm shift in the drinking water industry towards water safety planning and risk-based system assessment. Small water systems (SWSs) are generally more vulnerable to typical water system hazards, and consequently have a higher risk of waterborne disease outbreak. In this paper, a review of experiences in implementing QMRA in SWSs helps elaborate the sources of risks and highlights some of the challenges facing SWSs in developed countries. A critical review of the important elements for practical implementation of QMRA was conducted. The investigation focuses on aspects related to challenges in identifying relevant hazards to SWSs to create failure scenarios, acquiring monitoring data for pathogens' concentrations in source water, estimating treatment efficiencies of typical small system technologies, and access to software tools to support successful implementation. The review helped outline ways through which SWSs can overcome the identified challenges in implementing QMRA. An adjusted framework for implementing QMRA for small water systems was formulated and discussed.

Quality of water used in Palestinian hemodialysis centers

OBJECTIVES

Worldwide, hemodialysis (HD) patients are increasing every year, including Palestine. Dialysis fluid contamination due to the use of unpurified water is a common problem worldwide. Chemical and microbiological contaminants in the dialysis fluid could cross the dialyzer membrane and cause harm to dialysis patients. The objectives of this study were to evaluate the water quality used in centers in the West Bank, Palestine. The outcomes of this study will reflect the water purification system situation and come up with valuable recommendations to health decision makers.

STUDY DESIGN

This is a laboratory-based study that covered all dialysis centers in the West Bank, Palestine.

METHODS

Water samples were collected from all dialysis centers, and the samples were tested chemically and microbiologically according to the standard international and pharmacopeial methods.

RESULTS

The results showed that the water quality in most dialysis centers did not comply with the minimum requirements of HD water. Microbiological contamination was detected in 12.5% of the dialysis centers. The test for chloride failed in 87% of the dialysis centers. Moreover, tests for conductivity, total organic carbon (TOC), and lead were not within the allowed limits in all the dialysis centers.

CONCLUSIONS

Our study revealed evidence of chemical and bacterial contamination in the dialysis centers in Palestine. The outcomes of this study showed an urgent need for immediate steps to be taken by the concerned authorities to improve the water quality used in Palestinian HD centers.

Determination of Removal Efficiencies for Escherichia coli, Clostridial Spores, and F-Specific Coliphages in Unit Processes of Surface Waterworks for QMRA Applications

The removal efficiencies of bacteria, bacterial spores, and viruses after a change in source water and water pH in coagulation were studied at pilot scale in coagulation with flotation, rapid sand filtration, and disinfection with UV and chlorine. The results were compared to the treatment efficiencies of full-scale waterworks and data from literature. A quantitative microbial risk assessment (QMRA)-method was applied to estimate the numbers of illness cases caused by Campylobacter and norovirus after simulation of six operational malfunction scenarios. Coagulation with flotation and disinfection were more efficient in removing Clostridium spp. spores and MS2 coliphages than sand filtration in the pilot scale experiments (p < 0.001–0.008). The removal of E. coli was more efficient in sand filtration and in disinfection compared to coagulation with flotation (p = 0.006 and 0.01). Source water or pH change in coagulation had not significant effects on the removal efficiency of microbes. In QMRA, when disinfection was not in use, an increase in the number of illness cases compared to the normal situation was noticed. The variability in the number of illness cases demonstrated the importance of site-specific data in QMRA. This study provides new information on applying QMRA in both pilot and full-scale waterworks.

Tracking enteric viruses in green vegetables from central Argentina: potential association with viral contamination of irrigation waters

Consumption of green vegetable products is commonly viewed as a potential risk factor for infection with enteric viruses. The link between vegetable crops and fecally contaminated irrigation water establishes an environmental scenario that can result in a risk to human health. The aim of this work was to analyze the enteric viral quality in leafy green vegetables from Córdoba (Argentina) and its potential association with viral contamination of irrigation waters. During July-December 2012, vegetables were collected from peri-urban green farms (n = 19) and its corresponding urban river irrigation waters (n = 12). Also, urban sewage samples (n = 6) were collected to analyze the viral variants circulating in the community. Viruses were eluted and concentrated by polyethylene glycol precipitation and then were subject to Reverse Transcription Polymerase Chain Reaction to assess the genome presence of norovirus, rotavirus and human astrovirus. The concentrates were also inoculated in HEp-2 (Human Epidermoid carcinoma strain #2) cells to monitor the occurrence of infective enterovirus. The frequency of detection of the viral groups in sewage, irrigation water and crops was: norovirus 100%, 67% and 58%, rotavirus 100%, 75% and 5%, astrovirus 83%, 75% and 32% and infective enterovirus 50%, 33% and 79%, respectively. A similar profile in sewage, irrigation water and green vegetables was observed for norovirus genogroups (I and II) distribution as well as for rotavirus and astrovirus G-types. These results provide the first data for Argentina pointing out that green leafy vegetables are contaminated with a broad range of enteric viruses and that the irrigation water would be a source of contamination. The presence of viral genomes and infective particles in food that in general suffer minimal treatment before consumption underlines that green crops can act as potential sources of enteric virus transmission. Public intervention in the use of the river waters as irrigation source is needed.

Evaluation of Bacterial Contamination as an Indicator of Viral Contamination in a Sedimentary Aquifer in Uruguay

In Uruguay, groundwater is frequently used for agricultural activities, as well as for human consumption in urban and rural areas. As in many countries worldwide, drinking water microbiological quality is evaluated only according to bacteriological standards and virological analyses are not mentioned in the legislation. In this work, the incidence of human viral (Rotavirus A, Norovirus GII, and human Adenovirus) and bacterial (total and thermotolerant coliform and Pseudomonas aeruginosa) contamination in groundwater in the Salto district, Uruguay, as well as the possible correlation between these groups of microorganisms, was studied. From a total of 134 groundwater samples, 42 (32.1%) were positive for Rotavirus, only 1 (0.7%) for both Rotavirus and Adenovirus, and 96 (72.6%) samples were positive for bacterial indicators. Results also show that Rotavirus presence was not associated with changes in chemical composition of the aquifer water. Bacteriological indicators were not adequate to predict the presence of viruses in individual groundwater samples (well scale), but a deeper spatial-temporal analysis showed that they are promising candidates to assess the viral contamination degree at aquifer scale, since from the number of wells with bacterial contamination the number of wells with viral contamination could be estimated.

Comparative predictive modelling of the occurrence of faecal indicator bacteria in a drinking water source in Norway

Presently, concentrations of fecal indicator bacteria (FIB) in raw water sources are not known before water undergoes treatment, since analysis takes approximately 24h to produce results. Using data on water quality and environmental variables, models can be used to predict real time concentrations of FIB in raw water. This study evaluates the potentials of zero-inflated regression models (ZI), Random Forest regression model (RF) and adaptive neuro-fuzzy inference system (ANFIS) to predict the concentration of FIB in the raw water source of a water treatment plant in Norway. The ZI, RF and ANFIS faecal indicator bacteria predictive models were built using physico-chemical (pH, temperature, electrical conductivity, turbidity, color, and alkalinity) and catchment precipitation data from 2009 to 2015. The study revealed that pH, temperature, turbidity, and electrical conductivity in the raw water were the most significant factors associated with the concentration of FIB in the raw water source. Compared to the other models, the ANFIS model was superior (Mean Square Error=39.49, 0.35, 0.09, 0.23CFU/100ml respectively for coliform bacteria, E. coli, Intestinal enterococci and Clostridium perfringens) in predicting the variations of FIB in the raw water during model testing. However, the model was not capable of predicting low counts of FIB during both training and testing stages of the models. The ZI and RF models were more consistent when applied to testing data, and they predicted FIB concentrations that characterized the observed FIB concentrations. While these models might need further improvement, results of this study indicate that ZI and RF regression models have high prospects as tools for the real-time prediction of FIB in raw water sources for proactive microbial risk management in water treatment plants.