Fecal Indicator Bacteria Concentrations Research Articles

Total Maximum Daily Loads and Escherichia coli Trends in Texas Freshwater Streams

AbstractFecal indicator bacteria are routinely used to assess surface water sanitary quality. The State of Texas uses Total Maximum Daily Loads to address water bodies that exceed the allowable fecal indicator bacteria criteria. The effectiveness of these processes in decreasing the fecal indicator bacteria concentrations has been debated due to the diversity and nature of fecal indicator bacteria sources. We assessed actual and flow‐adjusted trends in measured Escherichia coli (E. coli) concentrations at 721 freshwater stream sites from 2001 through 2021. We also compared odds of statistical improvement of E. coli concentrations at sites before and after the adoption of Total Maximum Daily Loads (adopted from 2008 through 2014). Results indicate non‐significant differences in the odds of statistically detected improvements in E. coli concentration between pre‐Total Maximum Daily Load and post‐Total Maximum Daily Load sites. Although the State of Texas and numerous watershed stakeholders have made efforts to address water quality impairments, these results join a body of evidence that water quality improvements are stagnating in the state. Furthermore, this study leverages water quality data used for state water quality standards assessment purposes and highlights that robust monitoring program design is needed to effectively assess the progress of water quality planning efforts.

Tracking SARS-CoV-2 in rivers as a tool for epidemiological surveillance

The aim of this work was to evaluate if rivers could be used for SARS-CoV-2 surveillance. Five sampling points from three rivers (AR-1 and AR-2 in Arenales River, MR-1 and MR-2 in Mojotoro River, and CR in La Caldera River) from Salta (Argentina), two of them receiving discharges from wastewater plants (WWTP), were monitored from July to December 2020. Fifteen water samples from each point (75 in total) were collected and characterized physico-chemically and microbiologically and SARS-CoV-2 was quantified by RT-qPCR. Also, two targets linked to human contributions, human polyomavirus (HPyV) and RNase P, were quantified and used to normalize SARS-CoV-2 concentration, which was compared to reported COVID-19 cases. Statistical analyses allowed us to verify the correlation between SARS-CoV-2 and the concentration of fecal indicator bacteria (FIB), as well as to find similarities and differences between sampling points. La Caldera River showed the best water quality; FIBs were within acceptable limits for recreational activities. Mojotoro River's water quality was not affected by the northern WWTP of the city. Instead, Arenales River presented the poorest water quality; at AR-2 was negatively affected by the discharges of the southern WWTP, which contributed to significant increase of fecal contamination. SARS-CoV-2 was found in about half of samples in low concentrations in La Caldera and Mojotoro Rivers, while it was high and persistent in Arenales River. No human tracers were detected in CR, only HPyV was found in MR-1, MR-2 and AR-1, and both were quantified in AR-2. The experimental and normalized viral concentrations strongly correlated with reported COVID-19 cases; thus, Arenales River at AR-2 reflected the epidemiological situation of the city. This is the first study showing the dynamic of SARS-CoV-2 concentration in an urban river highly impacted by wastewater and proved that can be used for SARS-CoV-2 surveillance to support health authorities.

A comparison of soil Staphylococcus aureus and fecal indicator bacteria concentrations across land uses in a Hawaiian watershed.

Staphylococcus aureus, methicillin-resistant S. aureus (MRSA), and fecal indicator bacteria (FIB; Enterococcus spp., Clostridium perfringens) concentrations increase in Hawaiian streams and estuaries following storms and pose a health threat to recreational water users. To reduce this risk, watershed bacteria sources need to be identified for management actions. This study's goals were to identify soil bacteria sources among different land uses and to determine if their concentrations were associated with different soil properties. Soil samples were collected three times on 24 d between October 2017 and November 2018 at urban, agriculture, and native-forest land uses in the Hilo Bay watershed, Hawai'i Island, Hawai'i. Soil bacteria concentrations were quantified using culturing techniques with selective media. Staphylococcus aureus, MRSA, and FIB were present in soil from all land uses. Bacteria concentrations were highest in urban soils and lowest in native-forest soils, with up to three orders of magnitude differences among land uses. Staphylococcus aureus, MRSA, and FIB soil concentrations were positively correlated with each other and with soil temperature and pH, but inversely correlated with soil moisture and organic matter content. Our results demonstrate that soils are a watershed bacteria source and that some soil properties affect their concentrations. Identifying these sources is critical for implementing management actions to reduce pathogen loads to estuaries and transmission to recreational water users.

Observations and Correlations from a 3-Year Study of Fecal Indicator Bacteria in the Mohawk River in Upstate NY

Fecal indicator bacteria (FIB), such as E. coli and Enterococci, are used to indicate the potential of fecal contamination in waterways. One known source of FIB in urbanized areas is the occurrence of combined sewer overflows (CSOs). To explore the impact of CSOs on local water quality and FIB presence, sampling was conducted during the summers of 2017–2019 of two cities, one with CSOs and one without, on the Mohawk River in upstate New York, USA. Sampling included in situ physiochemical parameters of pH, temperature, and dissolved oxygen and laboratory tests for E. coli, Enterococci, nitrates, and total organic carbon (TOC). Correlations between parameters were explored using the Wilcoxon rank sum test and Spearman’s Rank correlation with and without considerations of site and city location. Overall, positive correlations between FIB and rainfall were identified in one city but were less significant in the other, suggesting a buffering of FIB concentrations likely due to inflow contributions from a reservoir. Samples collected downstream from an active CSO reached the detection limit of the FIB tests, demonstrating a 2-log or greater increase in FIB concentrations from dry weather conditions. The city with CSOs demonstrated greater FIB concentrations, which are likely a combination of greater urban runoff, CSOs, and the potential resuspension of sediment during high flow events. Due to the widespread presence of FIB in the region, future research includes utilizing microbial source tracking to identify the sources of contamination in the region.

Quantification of human adenovirus in irrigation water-soil-crop continuum: are consumers of wastewater-irrigated vegetables at risk?

Because of health concerns regarding the presence of enteric viruses in wastewater effluents, this study was designed to investigate the occurrence of human adenovirus (HAdV) in the irrigation water-soil-crop continuum.Viral particles were extracted from wastewater and wastewater- or water-irrigated soil and crop samples and analyzed using real-time PCR. Concentration of fecal indicator bacteria (FIB) were also determined. Quantitative microbial risk assessment was performed to determine the HAdV illness risk associated with the consumption of wastewater-irrigated vegetables. HAdV-F was detected in 74% of wastewater effluent samples with a mean concentration of 38 Genomic Copy (GC)/mL. HAdV was also detected in wastewater-irrigated soil (2 × 102 GC/g) and crop (< 10 GC/g) samples, with no statistically significant difference in concentrations between wastewater- and freshwater-irrigated samples. The results showed no correlation between concentrations of FIB and HAdV in the analyzed samples. Mean probability of illness risk from consumption of wastewater-irrigated vegetables was 4 × 10-1 per person per year (pppy) which was about two orders of magnitude higher than the proposed value by WHO (10-3 pppy) for safe reuse of wastewater. This finding suggests that the wastewater reuse for irrigation of vegetables eaten raw could pose a threat to human health with respect to the risk of viral illness, signifying stricter management of wastewater reuse. However, because of uncertainties in the QMRA model, particularly the ratio of infectious to non-infectious virus particles, more data is required to validate the predicted risk. This information is especially important in arid and semi-arid regions where high temperatures, UV radiation intensity, and desiccation can efficiently inactivate microorganisms in the environment.

Estimating statistical power for detecting long term trends in surface water Escherichia coli concentrations

Water quality monitoring programs commonly use the Mann-Kendall test or linear regression to identify statistically significant monotonic trends in fecal indicator bacteria concentrations (typically Escherichia coli [E. coli]). The statistical power of these tests to detect trends of different magnitudes (effect size) is rarely communicated to stakeholders, and it is unlikely they are considered when designing monitoring schedules. The statistical power for detecting trends in surface water E. coli bacteria concentrations using Mann-Kendall and linear regression at water quality monitoring sites across Texas was estimated using Monte Carlo simulation. The probability that an individual water quality monitoring site in Texas had adequate statistical power was also estimated using logistic regression.Mann-Kendall and linear regression trend tests show similar statistical power. Both tests are unlikely to achieve adequate statistical power when E. coli concentrations decrease by 20% or less over 7 years under most sampling frequencies. To adequately detect concentration decreases of 30% to 40% over 7 years, monthly sampling is required. Because many sites across Texas are sampled quarterly, monotonic trends tests will not be powerful enough to detect trends of moderate magnitudes. To better facilitate stakeholder decision-making, it is important to communicate the relative power of statistical tests and detectible magnitudes of changes. I suggest data analysts conduct power analyses to improve monitoring program designs and improve communication of trend test limitations. Software and training for water quality analysts could facilitate communication of power and effect sizes. Alternative trend assessment methods may be more reliable for describing changes in fecal indicator bacteria concentrations.

Development of Predictive Models for "Very Poor" Beach Water Quality Gradings Using Class-Imbalance Learning.

Statistical water quality forecast models are useful tools to assist with beach management. In particular, multiple linear regression (MLR) models have been successfully developed for prediction of fecal indicator bacteria concentrations for beaches in river, lake, and marine environments. Nevertheless, an unresolved challenging issue is the reliable prediction of infrequent events of high bacterial concentrations to inform beach closure decisions to protect public health. The number of field data available for the infrequent events is typically an order of magnitude less than that for days when the water quality criterion is met-MLR models often perform poorly in predicting bacterial concentrations on days when the beaches should be closed. For beach management in Hong Kong, MLR models have been developed to predict beach water quality indices in terms of four gradings (BWQI-1 to 4) based on Escherichia coli (E. coli) concentrations. In this study, we propose an artificial intelligence (AI)-based binary classification (EasyEnsemble) model using class-imbalance learning to predict "very poor" occasions (BWQI-4)-when E. coli concentration exceeds 610 counts/100 mL. Models are developed for three marine beaches with different hydrographic and pollution characteristics using a 30 year data set spanning three periods with different water quality status. The model-data comparison over a wide range of conditions shows that the proposed method results in a significant improvement in the prediction of "very poor" water quality. The proposed class-imbalance method for predicting rare events has an F-score of 0.84, and it significantly outperforms MLR and classification tree (CT) models with corresponding F-scores of 0.39 and 0.69. A robust beach water quality forecast system can hence be developed using hybrid MLR-binary classification modeling.

Systematic review of the relative concentrations of noroviruses and fecal indicator bacteria in wastewater: considerations for use in quantitative microbial risk assessment.

Human noroviruses are a leading cause of food- and water-borne disease, which has led to an interest in quantifying norovirus health risks using quantitative microbial risk assessment (QMRA). Given the limited availability of quantitative norovirus data to input to QMRA models, some studies have applied a conversion factor to estimate norovirus exposure based on measured fecal indicator bacteria (FIB) concentrations. We conducted a review of peer-reviewed publications to identify the concentrations of noroviruses and FIB in raw, secondary-treated, and disinfected wastewater. A meta-analysis was performed to determine the ratios of norovirus-FIB pairs in each wastewater matrix and the variables that significantly impact these ratios. Norovirus-to-FIB ratios were found to be significantly impacted by the norovirus genotype, month of sample collection, geographic location, and the extent of wastewater treatment. Additionally, we evaluated the impact of using a FIB-to-virus conversion factor in QMRA and found that the choice of conversion ratio has a great impact on estimated health risks. For example, the use of a conversion ratio previously used in the World Health Organization Guidelines for the Safe Use of Wastewater, Excreta and Greywater predicted health risks that were significantly lower than those estimated with measured norovirus concentrations used as inputs. This work emphasizes the gold standard of using measured pathogen concentrations directly as inputs to exposure assessment in QMRA. While not encouraged, if one must use a FIB-to-virus conversion ratio to estimate norovirus dose, the ratio should be chosen carefully based on the target microorganisms (i.e., strain, genotype, or class), prevalence of disease, and extent of wastewater treatment.

Spatial and temporal variations of faecal indicator bacteria in Lake Bunyonyi, South-Western Uganda

Background Microbial water quality serves to indicate health risks associated with the consumption of contaminated water. Nevertheless, little is known about the microbiological characteristics of water in Lake Bunyonyi. This study was therefore undertaken to examine the spatial and temporal variations of faecal indicator bacteria (FIB) in relation to physicochemical parameters in Lake Bunyonyi. Result The FIB concentration was consistently measured during sampling months and correlated with each other showing the presumed human faecal pollution in the lake. The highest concentration values for E. coli (64.7 ± 47.3 CFU/100 mL) and enterococci (24.6 ± 32.4 CFU/100 mL were obtained in the station close to the Mugyera trading centre. On a temporal basis, the maximum values were recorded during the rainy season in October 2019 (70.7 ± 56.5 CFU/100 mL for E. coli and 38.44 ± 31.8 CFU/100 mL for enterococci. FIB did not differ significantly among the study stations (p > 0.05) but showed significant temporal variations among the months (p < 0.05) with concentrations being significantly high in wet season than dry season (U = 794, p < 0.0001 for E. coli; U = 993.5, p = 0.008 for enterococci). Spearman’s rank correlation revealed that FIB concentrations were significantly positively correlated with turbidity and DO concentration levels (p < 0.05). Approximately 97.2% of the water samples had E. coli and enterococci concentrations levels below USEPA threshold for recreational waters. Likewise, 98.1 and 90.7% of samples recorded E. coli and enterococci counts exceeding the UNBS, APHA, WHO and EU threshold values for drinking water. Conclusion The FIB counts show that the Lake Bunyonyi water is bacteriologically unsuitable for drinking unless it is treated since the FIB pose health risks to consumers. Besides, the water can be used for recreational purposes.

An inverse approach to estimate bacterial loading into an estuary by using field observations and residence time

Pathogen, whose abundance is often measured by the concentration of fecal indicator bacteria, is listed as the top cause of waterbody impairments in the US. An accurate estimation of the bacterial loading from watershed is thus fundamentally important for water quality management. Despite advances in watershed modeling, accurate estimation of bacterial load is still very challenging due to large uncertainties associated with bacterial sources, accumulation, and removal in the watershed. We introduce an inverse method using field-measured bacterial concentrations and numerical model-calculated residence time to estimate the bacterial loading from the drainage basin. In this method, an estuary is divided into multiple segments. Water and bacterial fluxes between neighboring segments are computed from a set of linear equations derived based on mass balance equation and the relationship between residence time and water fluxes. Loading to each segment can then be estimated by combining the computed water fluxes and observed bacterial concentrations. The approach accounts for seasonal and interannual variations in hydrodynamics due to tide, river discharge, and estuarine circulations. The method was applied to Nassawadox Creek, a sub-estuary of Chesapeake Bay, where Fecal Coliform concentrations at 46 stations were continuously monitored. The method is verified by the high consistency between estimated loadings and presumably known input loadings in numerical experiments with either constant or time-varying input loadings. With sparse observational data, the inversely estimated loadings agree well with the loadings from a previously calibrated watershed model, demonstrating the reliability of the method. The inverse approach can be used to cross-check the result of watershed models and assess changes in watershed condition. The method is also readily applicable to other types of materials, such as inorganic nutrients.

Evaluating the impacts of foreshore sand and birds on microbiological contamination at a freshwater beach

Beaches along the Great Lakes shorelines are important recreational and economic resources. However, contamination at the beaches can threaten their usage during the swimming season, potentially resulting in beach closures and/or advisories. Thus, understanding the dynamics that control nearshore water quality is integral to effective beach management. There have been significant improvements in this effort, including incorporating modeling (empirical, mechanistic) in recent years. Mechanistic modeling frameworks can contribute to this understanding of dynamics by determining sources and interactions that substantially impact fecal indicator bacteria concentrations, an index routinely used in water quality monitoring programs. To simulate E. coli concentrations at Jeorse Park beaches in southwest Lake Michigan, a coupled hydrodynamic and wave–current interaction model was developed that progressively added contaminant sources from river inputs, avian presence, bacteria–sediment interactions, and bacteria–sand–sediment interactions. Results indicated that riverine inputs affected E. coli concentrations at Jeorse Park beaches only marginally, while avian, shoreline sand, and sediment sources were much more substantial drivers of E. coli contamination at the beach. By including avian and riverine inputs, as well as bacteria–sand–sediment interactions at the beach, models can reasonably capture the variability in observed E. coli concentrations in nearshore water and bed sediments at Jeorse Park beaches. Consequently, it will be crucial to consider avian contamination sources and water-sand-sediment interactions in effective management of the beach for public health and as a recreational resource and to extend these findings to similar beaches affected by shoreline embayment.

Inactivation of Hepatovirus A in wastewater by 254 nm ultraviolet-C irradiation

Hepatovirus A is known as a waterborne and foodborne virus that can be transmitted from one person to another through contaminated water and raw food. Therefore, it is necessary to survey the circulation of this type of enteric virus in the wastewater to prevent prospective outbreaks. Wastewater samples collected from WWTP El Menzeh I and Charguia I have been the subject for physicochemical, bacteriological (MPN) and virological analyses. Hepatovirus A (HAV) detection was carried out using the standard reverse transcription-polymerase chain reaction (RT-PCR). Hepatovirus A was detected respectively in 62% (63/102) and 66% (92/140) of the collected wastewater samples at El Menzeh I and Charguia I WWTPs. The treated effluent by natural oxidizing lagoon procedure was characterized by a poor physical-chemical and virological qualities but with excellent bacteriological quality. Consequently, this effluent is not suitable to be recycled and reused in agriculture or even dismissed in the environment. The treated sewage by activated sludge and rotating biodisk procedures turned out to be of a very good physical-chemical quality but with a poor bacteriological and virological quality. After tertiary UV-C254 nm irradiation, the faecal indicator bacteria concentration was mostly reduced and removed. These findings confirmed the need for improvement and upgrade of the treatment processes used in these two studied sewage purification plants and the necessity of implementation and establishment of a proper national virological standard to control the circulation rates of enteric viruses in Tunisian municipal wastewater.

Occurrence of a human-associated microbial source tracking marker and its relationship with faecal indicator bacteria in an urban estuary.

One of the main impacts of urban sprawl in rapidly growing countries has been contamination of coastal environments by waterborne pathogens, posing a critical risk to ecosystem and human health. Microbial source tracking (MST) has been a robust tool to identify the origin of these pathogens globally. This study compared the occurrence of a human-associated Bacteroides marker (BT-α) with faecal indicator bacteria (FIB) in an urban estuary (Golden Horn, Istanbul, Turkey). Faecal coliform (culture method), enterococci (both culture and qPCR method) concentrations and physicochemical variables were compared with the BT-α concentrations in monthly collected samples for a year (n=108). Enterococci concentrations detected by culture and qPCR were positively correlated (r=0·86, P<0·01) suggesting that qPCR can be an alternative method for monitoring. BT-α marker was positive for 30% of the samples and positively correlated with enterococci (r=0·61 and r=0·64 for culture and qPCR methods respectively, P<0·01). Rainfall had a moderate positive correlation with all faecal/MST indicators suggesting combined sewer overflows also severely impacted estuarine water quality. The high FIB and BT-α concentrations at upper estuary suggested that faecal pollution mainly originated from the peri-urban settlements around two creeks entering the estuary.

What Environmental Factors Influence the Concentration of Fecal Indicator Bacteria in Groundwater? Insights from Explanatory Modeling in Uganda and Bangladesh.

Information about microbial water quality is critical for managing water safety and protecting public health. In low-income countries, monitoring all drinking water supplies is impractical because financial resources and capacity are insufficient. Data sets derived from satellite imagery, census, and hydrological models provide an opportunity to examine relationships between a suite of environmental risk factors and microbial water quality over large geographical scales. We investigated the relationships between groundwater fecal contamination and different environmental parameters in Uganda and Bangladesh. In Uganda, groundwater contamination was associated with high population density (p < 0.001; OR = 1.27), high cropland coverage (p < 0.001; OR = 1.47), high average monthly precipitation (p < 0.001; OR = 1.14), and high surface runoff (p < 0.001; OR = 1.37), while low groundwater contamination was more likely in areas further from cities (p < 0.001; OR = 0.66) and with higher forest coverage (p < 0.001; OR = 0.70). In Bangladesh, contamination was associated with higher weekly precipitation (p < 0.001; OR = 1.44) and higher livestock density (p = 0.05; OR = 1.11), while low contamination was associated with low forest coverage (p < 0.001; OR = 1.23) and high cropland coverage (p < 0.001; OR = 0.80). We developed a groundwater contamination index for each country to help decision-makers identify areas where groundwater is most prone to fecal contamination and prioritize monitoring activities. Our approach demonstrates how to harness satellite-derived data to guide water safety management.

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.

Faecal contamination of the environment and child health: a systematic review and individual participant data meta-analysis

SummaryBackgroundExposure to faecal contamination is believed to be associated with child diarrhoea and possibly stunting; however, few studies have explicitly measured the association between faecal contamination and health. We aimed to assess individual participant data (IPD) across multiple trials and observational studies to quantify the relationship for common faecal–oral transmission pathways.MethodsWe did a systematic review and meta-analysis of IPD from studies identified in an electronic search of PubMed, Web of Science, and Embase on May 21, 2018. The search was done in English, but full texts published in French, Portuguese, and Spanish were also reviewed. Eligible studies quantified (1) household-level faecal indicator bacteria concentrations along common faecal-oral transmission pathways of drinking water, soil, or food, on children's hands or fomites, or fly densities in food preparation areas; and (2) individual-level diarrhoea or linear growth measures for children younger than 5 years in low-income and middle-income countries. For the diarrhoea analysis, all definitions of diarrhoea were eligible but studies were excluded if they used a recall period longer than 7 days. For the linear growth analysis (using height-for-age Z scores [HAZ]), cross-sectional studies were excluded, because of the absence of longitudinal environmental contamination data measured before the growth outcomes. We used multilevel generalised mixed-effects models to estimate the odds ratio (OR) for diarrhoea and the difference in HAZ scores for individual studies associated with a 1-log10 higher measure of faecal contamination. Estimates from each study were combined under a random-effects meta-analysis framework. The study protocol was pre-registered with PROSPERO (CRD42018102114).FindingsFrom 72 eligible studies, we included IPD for 20 studies in the meta-analyses, totalling 54 225 diarrhoea or linear growth observations matched to faecal indicator bacteria concentrations in drinking water, and a further 35 010 observations with faecal contamination data for the other transmission pathways. Child diarrhoea was associated with 1-log10 higher faecal indicator bacteria concentrations in drinking water (OR 1·09, 95% CI 1·04 to 1·13; p=0·0002, I2=34%, 95% CI 0 to 62) and on children's hands (1·11, 1·02 to 1·22; p=0·021, I2=0%, 0 to 71). Lower HAZ scores were associated with 1-log10 higher median faecal indicator bacteria concentrations in drinking water (HAZ −0·04, 95% CI −0·06 to −0·01; p=0·0054; I2=19%, 95% CI 0 to 63) and on fomites (–0·06, −0·12 to 0·00; p=0·044, I2=57%, 0 to 90).InterpretationAlthough summary measures from individual studies often report little or no effect of measured faecal contamination on child health, this multi-study IPD analysis indicates that household faecal indicator bacteria concentrations are associated with important adverse health outcomes in young children. Improved direct measures of exposure and enteric pathogens could help to better characterise the relationship and inform intervention design in future studies.FundingNone.

Fecal indicator bacteria, direct pathogen detection, and microbial community analysis provide different microbiological water quality assessment of a tropical urban marine estuary

Urban marine estuaries are often impacted by microbiological contamination that impairs use and affects human health acutely, while limited is known about microbiological water quality in urban marine estuaries in the absence of reported sewage spills. This study used a tropical urban marine estuary, the Ala Wai Canal in Honolulu, Hawaii, as the model system to compare fecal indicator bacteria (FIB) concentrations, bacterial pathogen profiles, and microbial community structures. The FIB Escherichia coli exhibited higher geometric mean 132 CFU/100mL (n=28) than those of enterococci (18 CFU/100mL) and Clostridium perfringens (21 CFU/100mL). Amongst the four pathogens targeted by cultivation methods (Salmonella, Campylobacter, Listeria monocytogenes and Vibrio parahaemolyticus), only was V. parahaemolyticus detected and was detected at high frequency. Microbial community analysis through 16S rRNA gene amplicon sequencing also indicated the high prevalence of Vibrio in the water. The pathogen detection patterns and microbial community structure showed no significant correlation with FIB concentration profiles. Together, the results highlight the limitation of using traditional FIB in assessing water microbiological quality in the tropical urban marine estuary environment, indicating the need for more comprehensive microbial risk assessment approaches such as direct detection of pathogens.

Elucidating fecal pollution patterns in alluvial water resources by linking standard fecal indicator bacteria to river connectivity and genetic microbial source tracking

A novel concept for fecal pollution analysis was applied at alluvial water resources to substantially extend the information provided by fecal indicator bacteria (FIB). FIB data were linked to river connectivity and genetic microbial source tracking (MST). The concept was demonstrated at the Danube River and its associated backwater area downstream of the city of Vienna, using a comprehensive 3-year data set (10 selected sites, n = 317 samples). Enumeration of Escherichia coli (ISO 16649-2), intestinal enterococci (ISO 7899-2) and Clostridium perfringens (ISO 14189) revealed a patchy distribution for the investigation area. Based on these parameters alone a clear interpretation of the observed fecal contamination patterns was not possible. Comparison of FIB concentrations to river connectivity allowed defining sites with dominating versus rare fecal pollution influence from the River Danube. A strong connectivity gradient at the selected backwater sites became obvious by 2D hydrodynamic surface water modeling, ranging from 278 days (25%) down to 5 days (<1%) of hydraulic connectivity to the River Danube within the 3-year study period. Human sewage pollution could be identified as the dominating fecal source at the highly connected sites by adding information from MST analysis. In contrast, animal fecal pollution proofed to be dominating in areas with low river connectivity. The selection of genetic MST markers was focusing on potentially important pollution sources in the backwater area, using human (BacHum, HF183II), ruminant (BacR) and pig (Pig2Bac) -associated quantitative PCR assays. The presented approach is assumed to be useful to characterize alluvial water resources for water safety management throughout the globe, by allocating fecal pollution to autochthonous, allochthonous, human or animal contamination components. The established river connectivity metric is not limited to bacterial fecal pollution, but can be applied to any type of chemical and microbiological contamination.

Microbial Water Quality Conditions Associated with Livestock Grazing, Recreation, and Rural Residences in Mixed-Use Landscapes

Contamination of surface waters with microbial pollutants from fecal sources is a significant human health issue. Identification of relative fecal inputs from the mosaic of potential sources common in rural watersheds is essential to effectively develop and deploy mitigation strategies. We conducted a cross-sectional longitudinal survey of fecal indicator bacteria (FIB) concentrations associated with extensive livestock grazing, recreation, and rural residences in three rural, mountainous watersheds in California, USA during critical summer flow conditions. Overall, we found that 86% to 87% of 77 stream sample sites across the study area were below contemporary Escherichia coli-based microbial water quality standards. FIB concentrations were lowest at recreation sites, followed closely by extensive livestock grazing sites. Elevated concentrations and exceedance of water quality standards were highest at sites associated with rural residences, and at intermittently flowing stream sites. Compared to national and state recommended E. coli-based water quality standards, antiquated rural regional policies based on fecal coliform concentrations overestimated potential fecal contamination by as much as four orders of magnitude in this landscape, hindering the identification of the most likely fecal sources and thus the efficient targeting of mitigation practices to address them.

Exposure measurement error and the characterization of child exposure to fecal contamination in drinking water

Characterizing fecal contamination exposure from drinking water can introduce exposure measurement errors, i.e., differences between the observed and true exposure. These errors can mask the true relationship between fecal contamination exposure and waterborne diseases. We present a framework to quantify the impact of measurement errors on exposure–outcome health effect estimates introduced by variability in measured drinking water fecal contamination levels and household versus community sampling strategies. We matched fecal indicator bacteria (FIB) data for >37,000 drinking water samples to children aged 0–72 months from 19 studies in low- and middle-income countries and took two complementary analytical approaches. We found that household-level exposure assessments may attenuate effect estimates of FIB concentrations in drinking water on diarrhea, and single water samples may attenuate health effect estimates of FIB concentrations on linear growth. To understand the health effects of fecal contamination exposure, measurement error frameworks can be used to estimate more biologically relevant exposures.