Integrating quantitative PCR and Bayesian statistics in quantifying human adenoviruses in small volumes of source water

Demonstrating the reduction of enteric viruses by drinking water treatment during snowmelt episodes in urban areas

This study investigates short-term fluctuations in virus concentrations in source water and their removal by full-scale drinking water treatment processes under different source water conditions. Transient peaks in raw water faecal contamination were identified using in situ online β-d-glucuronidase activity monitoring at two urban drinking water treatment plants. During these peaks, sequential grab samples were collected at the source and throughout the treatment train to evaluate concentrations of rotavirus, adenovirus, norovirus, enterovirus, JC virus, reovirus, astrovirus and sapovirus by reverse transcription and real-time quantitative PCR. Virus infectivity was assessed through viral culture by measurement of cytopathic effect and integrated cell culture qPCR. Virus concentrations increased by approximately 0.5-log during two snowmelt/rainfall episodes and approximately 1.0-log following a planned wastewater discharge upstream of the drinking water intake and during a β-d-glucuronidase activity peak in dry weather conditions. Increases in the removal of adenovirus and rotavirus by coagulation/flocculation processes were observed during peak virus concentrations in source water, suggesting that these processes do not operate under steady-state conditions but dynamic conditions in response to source water conditions. Rotavirus and enterovirus detected in raw and treated water samples were predominantly negative in viral culture. At one site, infectious adenoviruses were detected in raw water and water treated by a combination of ballasted clarification, ozonation, GAC filtration, and UV disinfection operated at a dose of 40 mJ cm^-2. The proposed sampling strategy can inform the understanding of the dynamics associated with virus concentrations at drinking water treatment plants susceptible to de facto wastewater reuse.

Informing water distribution line rehabilitation through quantitative microbial risk assessment

Poor urban water quality has been linked to diminished source water quality, poorly functioning water treatment systems and infiltration into distribution lines after treatment resulting in microbiological contamination. With limited funding to rehabilitate distribution lines, developing nations need tools to identify the areas of greatest concern to human health so as to target cost effective remediation approaches. Herein, a case study of Hyderabad, Pakistan was used to demonstrate the efficacy of combining quantitative microbial risk assessment (QMRA) for multiple pathogens with spatial distribution system modeling to identify areas for pipe rehabilitation. Abundance of Escherichia coli, Enterococcus (enterococci), Salmonella spp., Shigella spp., Giardia intestinalis, Vibrio cholera, norovirus GI and adenovirus 40/41, were determined in 85 locations including the source water, treatment plant effluent and the city distribution lines. Bayesian statistics and Monte Carlo simulations were used in the QMRA to account for left-censored microbial abundance distributions. Bacterial and viral abundances in the distribution system samples decreased as follows: 9400 ± 19,800 norovirus gene copies/100 mL (average ± standard deviation, 100% of samples positive); 340 ± 2200 enterococci CFU/100 mL (94%), 71 ± 97 Shigella sp. CFU/100 mL (97%), 60 ± 360 E. coli CFU/100 mL (89%), 35 ± 79 adenovirus gene copies/100 mL (100%), and 21 ± 46 Salmonella sp. CFU/100 mL (76%). The QMRA revealed unacceptable probabilities of illness (>1 in 10,000 illness level) from the four exposure routes considered (drinking water, or only showering, tooth brushing, and rinsing vegetables consumed raw). Disease severity indices based on the QMRA combined with mapping the distribution system revealed areas for targeted rehabilitation. The combined intensive sampling, risk assessment and mapping can be used in low- and middle-income countries to target distribution system rehabilitation efforts and improve health outcomes.

Multi-pathway human exposure risk assessment using Bayesian modeling at the historically largest mercury mining district

The largest mercury (Hg) mining district in the world is located in Almadén (Spain), with well-known environmental impacts in the surrounding ecosystem. However, the impact of mercury on the health of the inhabitants of this area has not been documented accordingly. This study aims to carry out a probabilistic human health risk assessment using Bayesian modeling to estimate the non-carcinogenic risk related to Hg through multiple exposure pathways. Samples of vegetables, wild mushrooms, fish, soil, water, and air were analyzed, and adult residents were randomly surveyed to adjust the risk models to the specific population data. On the one hand, the results for the non-carcinogenic risk based on Hazard Quotient (HQ) showed unacceptable risk levels through ingestion of Hg-contaminated vegetables and fish, with HQ values 20 and 3 times higher, respectively, than the safe exposure threshold of 1 for the 97.5th percentile. On the other hand, ingestion of mushrooms, dermal contact with soil, ingestion of water, dermal contact with water and inhalation of air, were below the safety limit for the 97.5th percentile, and did not represent a risk to the health of residents. In addition, the probabilistic approach was compared with the conservative deterministic approach, and similar results were obtained. This is the first study conducted in Almadén, which clearly reveals the high levels of human health risk to which the population is exposed due to the legacy of two millennia of Hg mining.

Linking landscape patterns to sources of water contamination: Implications for tracking fecal contaminants with geospatial and Bayesian approaches

Microbial source tracking (MST) techniques have been designed to identify the host source of fecal contamination in water. However, current MST techniques cannot provide geographic origins of particular sources because they do not provide any spatial information beyond the points of observation. In this study, the associations between landscape patterns and the major sources of microbial contamination were examined and the application of geospatial techniques (e.g., remote sensing and geographic information systems) and Bayesian modeling was explored to track microbial sources over the landscape. The land cover information of three watersheds (the lower Dungeness Watershed, the Middle Rio Grande Watershed, and the Arroyo Burro Watershed) in the United States was obtained either by classifying high resolution satellite images or directly using land cover datasets (e.g., National Land Cover Dataset, 2006 and 2011). Then, the relationship between land use/land cover (LULC) and microbial sources from these three geographically disparate watersheds were analyzed using Bayesian hierarchical models. The results showed the predictive positive associations between human sources of fecal contamination and developed area, between dog sources and grassland, and between bird sources and water, but negative associations between human sources and forest and water areas. Furthermore, the diversity of microbial sources had positive associations with landscape fragmentation and diversity indices. This study demonstrates associations between landscape patterns and major microbial sources and offers new insight in tracking the dominant sources of fecal contamination in water using geospatial and Bayesian techniques.

Estimating virus occurrence using Bayesian modeling in multiple drinking water systems of the United States

Drinking water treatment plants rely on purification of contaminated source waters to provide communities with potable water. One group of possible contaminants are enteric viruses. Measurement of viral quantities in environmental water systems are often performed using polymerase chain reaction (PCR) or quantitative PCR (qPCR). However, true values may be underestimated due to challenges involved in a multi-step viral concentration process and due to PCR inhibition. In this study, water samples were concentrated from 25 drinking water treatment plants (DWTPs) across the US to study the occurrence of enteric viruses in source water and removal after treatment. The five different types of viruses studied were adenovirus, norovirus GI, norovirus GII, enterovirus, and polyomavirus. Quantitative PCR was performed on all samples to determine presence or absence of these viruses in each sample. Ten DWTPs showed presence of one or more viruses in source water, with four DWTPs having treated drinking water testing positive. Furthermore, PCR inhibition was assessed for each sample using an exogenous amplification control, which indicated that all of the DWTP samples, including source and treated water samples, had some level of inhibition, confirming that inhibition plays an important role in PCR-based assessments of environmental samples. PCR inhibition measurements, viral recovery, and other assessments were incorporated into a Bayesian model to more accurately determine viral load in both source and treated water. Results of the Bayesian model indicated that viruses are present in source water and treated water. By using a Bayesian framework that incorporates inhibition, as well as many other parameters that affect viral detection, this study offers an approach for more accurately estimating the occurrence of viral pathogens in environmental waters.

Exploring links between greenspace and sudden unexpected death: A spatial analysis

Greenspace has been increasingly recognized as having numerous health benefits. However, its effects are unknown concerning sudden unexpected death (SUD), commonly referred to as sudden cardiac death, which constitutes a large proportion of mortality in the United States. Because greenspace can promote physical activity, reduce stress and buffer air pollutants, it may have beneficial effects for people at risk of SUD, such as those with heart disease, hypertension, and diabetes mellitus. Using several spatial techniques, this study explored the relationship between SUD and greenspace. We adjudicated 396 SUD cases that occurred from March 2013 to February 2015 among reports from emergency medical services (EMS) that attended out-of-hospital deaths in Wake County (central North Carolina, USA). We measured multiple greenspace metrics in each census tract, including the percentages of forest, grassland, average tree canopy, tree canopy diversity, near-road tree canopy and greenway density. The associations between SUD incidence and these greenspace metrics were examined using Poisson regression (non-spatial) and Bayesian spatial models. The results from both models indicated that SUD incidence was inversely associated with both greenway density (adjusted risk ratio [RR] = 0.82, 95% credible/ confidence interval [CI]: 0.69-0.97) and the percentage of forest (adjusted RR = 0.90, 95% CI: 0.81-0.99). These results suggest that increases in greenway density by 1 km/km2 and in forest by 10% were associated with a decrease in SUD risk of 18% and 10%, respectively. The inverse relationship was not observed between SUD incidence and other metrics, including grassland, average tree canopy, near-road tree canopy and tree canopy diversity. This study implies that greenspace, specifically greenways and forest, may have beneficial effects for people at risk of SUD. Further studies are needed to investigate potential causal relationships between greenspace and SUD, and potential mechanisms such as promoting physical activity and reducing stress.

Bacteriophage removal efficiency as a validation and operational monitoring tool for virus reduction in wastewater reclamation: Review

The multiple-barrier concept is widely employed in international and domestic guidelines for wastewater reclamation and reuse for microbiological risk management, in which a wastewater reclamation system is designed to achieve guideline values of the performance target of microbe reduction. Enteric viruses are one of the pathogens for which the target reduction values are stipulated in guidelines, but frequent monitoring to validate human virus removal efficacy is challenging in a daily operation due to the cumbersome procedures for virus quantification in wastewater. Bacteriophages have been the first choice surrogate for this task, because of the well-characterized nature of strains and the presence of established protocols for quantification. Here, we performed a meta-analysis to calculate the average log₁₀ reduction values (LRVs) of somatic coliphages, F-specific phages, MS2 coliphage and T4 phage by membrane bioreactor, activated sludge, constructed wetlands, pond systems, microfiltration and ultrafiltration. The calculated LRVs of bacteriophages were then compared with reported human enteric virus LRVs. MS2 coliphage LRVs in MBR processes were shown to be lower than those of norovirus GII and enterovirus, suggesting it as a possible validation and operational monitoring tool. The other bacteriophages provided higher LRVs compared to human viruses. The data sets on LRVs of human viruses and bacteriophages are scarce except for MBR and conventional activated sludge processes, which highlights the necessity of investigating LRVs of human viruses and bacteriophages in multiple treatment unit processes.

The compartment bag test (CBT) for enumerating fecal indicator bacteria: Basis for design and interpretation of results

For the past several years, the compartment bag test (CBT) has been employed in water quality monitoring and public health protection around the world. To date, however, the statistical basis for the design and recommended procedures for enumerating fecal indicator bacteria (FIB) concentrations from CBT results have not been formally documented. Here, we provide that documentation following protocols for communicating the evolution of similar water quality testing procedures. We begin with an overview of the statistical theory behind the CBT, followed by a description of how that theory was applied to determine an optimal CBT design. We then provide recommendations for interpreting CBT results, including procedures for estimating quantiles of the FIB concentration probability distribution, and the confidence of compliance with recognized water quality guidelines. We synthesize these values in custom user-oriented 'look-up' tables similar to those developed for other FIB water quality testing methods. Modified versions of our tables are currently distributed commercially as part of the CBT testing kit.

Decay of Coliphages in Sewage-Contaminated Freshwater: Uncertainty and Seasonal Effects

Understanding the fate of enteric viruses in water is vital for protection of water quality. However, the decay of enteric viruses is not well characterized, and its uncertainty has not been examined yet. In this study, the decay of coliphages, an indicator for enteric viruses, was investigated in situ under both sunlit and shaded conditions as well as in summer and winter. The decay rates of coliphages and their uncertainties were analyzed using a Bayesian approach. The results from the summer experiments revealed that the decay rates of somatic coliphages were significantly higher in sunlight (1.29 ± 0.06 day^-1) than in shade (0.96 ± 0.04 day^-1), but the decay rates of male-specific (F+) coliphages were not significantly different between sunlight (1.09 ± 0.09 day^-1) and shaded treatments (1.11 ± 0.08 day^-1). The decay rates of both F+ coliphages (0.25 ± 0.02 day^-1) and somatic coliphages (0.12 ± 0.01 day^-1) in winter were considerably lower than those in summer. Temperature and chlorophyll a (chla) concentration varied significantly (p < 0.001) between the two seasons, suggesting that these parameters might be important contributors to the seasonal variation of coliphage decay. Additionally, the Bayesian approach provided full distributions of decay rates and reduced the uncertainty, offering useful information for comparing decay rates under different conditions.

Assessment of public health risk associated with viral contamination in harvested urban stormwater for domestic applications

Capturing stormwater is becoming a new standard for sustainable urban stormwater management, which can be used to supplement water supply portfolios in water-stressed cities. The key advantage of harvesting stormwater is to use low impact development (LID) systems for treatment to meet water quality requirement for non-potable uses. However, the lack of scientific studies to validate the safety of such practice has limited its adoption. Microbial hazards in stormwater, especially human viruses, represent the primary public health threat. Using adenovirus and norovirus as target pathogens, we investigated the viral health risk associated with a generic scenario of urban stormwater harvesting practice and its application for three non-potable uses: 1) toilet flushing, 2) showering, and 3) food-crop irrigation. The Quantitative Microbial Risk Assessment (QMRA) results showed that food-crop irrigation has the highest annual viral infection risk (median range: 6.8×10(-4)-9.7×10(-1) per-person-per-year or pppy), followed by showering (3.6×10(-7)-4.3×10(-2)pppy), and toilet flushing (1.1×10(-7)-1.3×10(-4)pppy). Disease burden of each stormwater use was ranked in the same order as its viral infection risk: food-crop irrigation>showering>toilet flushing. The median and 95th percentile risk values of toilet-flushing using treated stormwater are below U.S. EPA annual risk benchmark of ≤10(-4)pppy, whereas the disease burdens of both toilet-flushing and showering are within the WHO recommended disease burdens of ≤10(-6)DALYspppy. However, the acceptability of showering risk interpreted based on the U.S. EPA and WHO benchmarks is in disagreement. These results confirm the safety of stormwater application in toilet flushing, but call for further research to fill the data gaps in risk modeling as well as risk benchmarks.