Quantitative Microbial Risk Assessment Framework Incorporating Water Ages with Legionella pneumophila Growth Rates.

Water age in drinking water systems is often used as a proxy for water quality but is rarely used as a direct input in assessing microbial risk. This study directly linked water ages in a premise plumbing system to concentrations of Legionella pneumophila via a growth model. In turn, the L. pneumophila concentrations were used for a quantitative microbial risk assessment to calculate the associated probabilities of infection (Pinf) and clinically severe illness (Pcsi) due to showering. Risk reductions achieved by purging devices, which reduce water age, were also quantified. The median annual Pinf exceeded the commonly used 1 in 10,000 (10-4) risk benchmark in all scenarios, but the median annual Pcsi was always 1-3 orders of magnitude below 10-4. The median annual Pcsi was lower in homes with two occupants (4.7 × 10-7) than with one occupant (7.5 × 10-7) due to more frequent use of water fixtures, which reduced water ages. The median annual Pcsi for homes with one occupant was reduced by 39-43% with scheduled purging 1-2 times per day. Smart purging devices, which purge only after a certain period of nonuse, maintained these lower annual Pcsi values while reducing additional water consumption by 45-62%.

Research gaps and priorities for quantitative microbial risk assessment (QMRA).

The coronavirus disease 2019 pandemic highlighted the need for more rapid and routine application of modeling approaches such as quantitative microbial risk assessment (QMRA) for protecting public health. QMRA is a transdisciplinary science dedicated to understanding, predicting, and mitigating infectious disease risks. To better equip QMRA researchers to inform policy and public health management, an Advances in Research for QMRA workshop was held to synthesize a path forward for QMRA research. We summarize insights from 41 QMRA researchers and experts to clarify the role of QMRA in risk analysis by (1) identifying key research needs, (2) highlighting emerging applications of QMRA; and (3) describing data needs and key scientific efforts to improve the science of QMRA. Key identified research priorities included using molecular tools in QMRA, advancing dose-response methodology, addressing needed exposure assessments, harmonizing environmental monitoring for QMRA, unifying a divide between disease transmission and QMRA models, calibrating and/or validating QMRA models, modeling co-exposures and mixtures, and standardizing practices for incorporating variability and uncertainty throughout the source-to-outcome continuum. Cross-cutting needs identified were to: develop a community of research and practice, integrate QMRA with other scientific approaches, increase QMRA translation and impacts, build communication strategies, and encourage sustainable funding mechanisms. Ultimately, a vision for advancing the science of QMRA is outlined for informing national to global health assessments, controls, and policies.

Candida auris Discovery through Community Wastewater Surveillance during Healthcare Outbreak, Nevada, USA, 2022.

Candida auris transmission is steadily increasing across the United States. We report culture-based detection of C. auris in wastewater and the epidemiologic link between isolated strains and southern Nevada, USA, hospitals within the sampled sewershed. Our results illustrate the potential of wastewater surveillance for containing C. auris.

Community-Scale Wastewater Surveillance of Candida auris during an Ongoing Outbreak in Southern Nevada.

Candida auris is an opportunistic fungal pathogen and an emerging global public health threat, given its high mortality among infected individuals, antifungal resistance, and persistence in healthcare environments. This study explored the applicability of wastewater surveillance for C. auris in a metropolitan area with reported outbreaks across multiple healthcare facilities. Influent or primary effluent samples were collected over 10 weeks from seven sewersheds in Southern Nevada. Pelleted solids were analyzed using an adapted quantitative polymerase chain reaction (qPCR) assay targeting the ITS2 region of the C. auris genome. Positive detection was observed in 72 of 91 samples (79%), with higher detection frequencies in sewersheds serving healthcare facilities involved in the outbreak (94 vs 20% sample positivity). Influent wastewater concentrations ranged from 2.8 to 5.7 log10 gene copies per liter (gc/L), and primary clarification achieved an average log reduction value (LRV) of 1.24 ± 0.34. Presumptive negative surface water and wastewater controls were non-detect. These results demonstrate that wastewater surveillance may assist in tracking the spread of C. auris and serve as an early warning tool for public health action. These findings provide the foundation for future application of wastewater-based epidemiology (WBE) to community- or facility-level surveillance of C. auris and other high consequence, healthcare-associated infectious agents.

SARS-CoV-2 Wastewater Surveillance for Public Health Action.

Wastewater surveillance for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has garnered extensive public attention during the coronavirus disease pandemic as a proposed complement to existing disease surveillance systems. Over the past year, methods for detection and quantification of SARS-CoV-2 viral RNA in untreated sewage have advanced, and concentrations in wastewater have been shown to correlate with trends in reported cases. Despite the promise of wastewater surveillance, for these measurements to translate into useful public health tools, bridging the communication and knowledge gaps between researchers and public health responders is needed. We describe the key uses, barriers, and applicability of SARS-CoV-2 wastewater surveillance for supporting public health decisions and actions, including establishing ethics consideration for monitoring. Although wastewater surveillance to assess community infections is not a new idea, the coronavirus disease pandemic might be the initiating event to make this emerging public health tool a sustainable nationwide surveillance system, provided that these barriers are addressed.

Legionnaires' disease in dental offices: Quantifying aerosol risks to dental workers and patients.

Legionella pneumophila is an opportunistic bacterial respiratory pathogen that is one of the leading causes of drinking water outbreaks in the United States. Dental offices pose a potential risk for inhalation or aspiration of L. pneumophila due to the high surface area to volume ratio of dental unit water lines-a feature that is conducive to biofilm growth. This is coupled with the use of high-pressure water devices (e.g., ultrasonic scalers) that produce fine aerosols within the breathing zone. Prior research confirms that L. pneumophila occurs in dental unit water lines, but the associated human health risks have not been assessed. We aimed to: (1) synthesize the evidence for transmission and management of Legionnaires' disease in dental offices; (2) create a quantitative modeling framework for predicting associated L. pneumophila infection risk; and (3) highlight influential parameters and research gaps requiring further study. We reviewed outbreaks, management guidance, and exposure studies and used these data to parameterize a quantitative microbial risk assessment (QMRA) model for L. pneumophila in dental applications. Probabilities of infection for dental hygienists and patients were assessed on a per-exposure and annual basis. We also assessed the impact of varying ventilation rates and the use of personal protective equipment (PPE). Following an instrument purge (i.e., flush) and with a ventilation rate of 1.2 air changes per hour, the median per-exposure probability of infection for dental hygienists and patients exceeded a 1-in-10,000 infection risk benchmark. Per-exposure risks for workers during a purge and annual risks for workers wearing N95 masks did not exceed the benchmark. Increasing air change rates in the treatment room from 1.2 to 10 would achieve an ∼85% risk reduction, while utilization of N95 respirators would reduce risks by ∼95%. The concentration of L. pneumophila in dental unit water lines was a dominant parameter in the model and driver of risk. Future risk assessment efforts and refinement of microbiological control protocols would benefit from expanded occurrence datasets for L. pneumophila in dental applications.

Use of COD, TOC, and Fluorescence Spectroscopy to Estimate BOD in Wastewater.

Common to all National Pollutant Discharge Elimination System (NPDES) permits in the United States is a limit on biochemical oxygen demand (BOD). Chemical oxygen demand (COD), total organic carbon (TOC), and fluorescence spectroscopy are also capable of quantifying organic content, although the mechanisms of quantification and the organic fractions targeted differ for each test. This study explores correlations between BOD5 and these alternate test procedures using facility influent, primary effluent, and facility effluent samples from a full-scale water resource recovery facility. Relative reductions of the water quality parameters proved to be strong indicators of their suitability as surrogates for BOD5. Suitable correlations were generally limited to the combined datasets for the three sampling locations or the facility effluent alone. COD exhibited relatively strong linear correlations with BOD5 when considering the three sample points (r = 0.985) and the facility effluent alone (r = 0.914), while TOC exhibited a suitable linear correlation with BOD5 in the facility effluent (r = 0.902). Exponential regressions proved to be useful for estimating BOD5 based on TOC or fluorescence (r > 0.95).

Organic Contaminant Abatement in Reclaimed Water by UV/H2O2 and a Combined Process Consisting of O3/H2O2 Followed by UV/H2O2: Prediction of Abatement Efficiency, Energy Consumption, and Byproduct Formation.

UV/H2O2 processes can be applied to improve the quality of effluents from municipal wastewater treatment plants by attenuating trace organic contaminants (micropollutants). This study presents a kinetic model based on UV photolysis parameters, including UV absorption rate and quantum yield, and hydroxyl radical (·OH) oxidation parameters, including second-order rate constants for ·OH reactions and steady-state ·OH concentrations, that can be used to predict micropollutant abatement in wastewater. The UV/H2O2 kinetic model successfully predicted the abatement efficiencies of 16 target micropollutants in bench-scale UV and UV/H2O2 experiments in 10 secondary wastewater effluents. The model was then used to calculate the electric energies required to achieve specific levels of micropollutant abatement in several advanced wastewater treatment scenarios using various combinations of ozone, UV, and H2O2. UV/H2O2 is more energy-intensive than ozonation for abatement of most micropollutants. Nevertheless, UV/H2O2 is not limited by the formation of N-nitrosodimethylamine (NDMA) and bromate whereas ozonation may produce significant concentrations of these oxidation byproducts, as observed in some of the tested wastewater effluents. The combined process of O3/H2O2 followed by UV/H2O2, which may be warranted in some potable reuse applications, can achieve superior micropollutant abatement with reduced energy consumption compared to UV/H2O2 and reduced oxidation byproduct formation (i.e., NDMA and/or bromate) compared to conventional ozonation.

UASB reactor effluent disinfection by ozone and chlorine.

This research studied the sequential ozone and chlorine process with respect to, the inactivation of indicator bacteria and the formation of ozone disinfection byproducts in sanitary wastewater effluent. The applied ozone doses were 5, 8 and 10 mg.O3.L(-1), followed by chlorine doses of 10, 20 and 30 mg.L(-1), respectively. After the sequential ozone/chlorine process, the mean reduction in chemical oxygen demand ranged from 9 to 37%. Total coliform inactivation ranged from 1.59 to 3.73 log10, and E. coli was always <1 CFU 100 mL(-1). Ozonation resulted in the formation of aldehydes, which were not significantly impacted by the subsequent chlorine dose (P ≤ 0.05).

Sources of per- and polyfluoroalkyl substances in an arid, urban, wastewater-dominated watershed.

Per- and polyfluoroalkyl substances (PFAS) enter surface waters from various sources such as wastewater treatment plants, fire-fighting sites, and PFAS-producing and PFAS-using industries. The Las Vegas Wash in Southern Nevada of the United States (U.S.) conveys wastewater effluent from the Las Vegas metropolitan area to Lake Mead, a drinking water source for millions of people in the U.S. Southwest. PFAS have previously been detected in the Las Vegas Wash, but PFAS sources were not identified. In this study, upstream wash tributaries, wastewater treatment effluents, and shallow groundwater wells were sampled in multiple campaigns during dry-weather conditions to investigate possible PFAS sources. Out of 19 PFAS, two short-chain PFAS-perfluoropentanoic acid (48 % of the total molar concentration) and perfluorohexanoic acid (32 %)-comprised the majority of PFAS loading measured in the Las Vegas Wash, followed by perfluorooctanoic acid (9 %). On a mass loading basis, the majority of total measured PFAS (approximately 90 %) and at least 48 % of each specific PFAS in the Las Vegas Wash likely entered via municipal wastewater effluents, of which the main source was likely residential wastewater. One of the drainage areas with a major civilian airport was identified as a potential source of relatively enriched perfluorosulfonic acids to a small wash tributary and shallow groundwater samples. Nonetheless, that tributary contributed at most 15 % of any specific PFAS to the mainstem of the Las Vegas Wash. Total PFAS concentrations were relatively low for the small tributary associated with an urban smaller airport and the lack of flow in the tributary channel immediately downgradient of an Air Force base indicates the smaller airport and base were unlikely significant PFAS sources to the Las Vegas Wash. Overall, this study demonstrated effective PFAS source investigation methodology and the importance of wastewater effluent as a PFAS environmental pathway.

Spatial and Temporal Drug Usage Patterns in Wastewater Correlate with Socioeconomic and Demographic Indicators in Southern Nevada.

Evaluating drug use within populations in the United States poses significant challenges due to various social, ethical, and legal constraints, often impeding the collection of accurate and timely data. Here, we aimed to overcome these barriers by conducting a comprehensive analysis of drug consumption trends and measuring their association with socioeconomic and demographic factors. From May 2022 to April 2023, we analyzed 208 wastewater samples from eight sampling locations across six wastewater treatment plants in Southern Nevada, covering a population of 2.4 million residents with 50 million annual tourists. Using bi-weekly influent wastewater samples, we employed mass spectrometry to detect 39 analytes, including pharmaceuticals and personal care products (PPCPs) and high risk substances (HRS). Our results revealed a significant increase over time in the level of stimulants such as cocaine (pFDR=1.40×10-10) and opioids, particularly norfentanyl (pFDR =1.66×10-12), while PPCPs exhibited seasonal variation such as peak usage of DEET, an active ingredient in insect repellents, during the summer (pFDR =0.05). Wastewater from socioeconomically disadvantaged or rural areas, as determined by Area Deprivation Index (ADI) and Rural-Urban Commuting Area Codes (RUCA) scores, demonstrated distinct overall usage patterns, such as higher usage/concentration of HRS, including cocaine (p=0.05) and norfentanyl (p=1.64×10-5). Our approach offers a near real-time, comprehensive tool to assess drug consumption and personal care product usage at a community level, linking wastewater patterns to socioeconomic and demographic factors. This approach has the potential to significantly enhance public health monitoring strategies in the United States.

Environmental Surveillance of Flood Control Infrastructure Impacted by Unsheltered Individuals Leads to the Detection of SARS-CoV-2 and Novel Mutations in the Spike Gene.

In the United States, the growing number of people experiencing homelessness has become a socioeconomic crisis with public health ramifications, recently exacerbated by the COVID-19 pandemic. We hypothesized that the environmental surveillance of flood control infrastructure may be an effective approach to understand the prevalence of infectious disease. From December 2021 through July 2022, we tested for SARS-CoV-2 RNA from two flood control channels known to be impacted by unsheltered individuals residing in upstream tunnels. Using qPCR, we detected SARS-CoV-2 RNA in these environmental water samples when significant COVID-19 outbreaks were occurring in the surrounding community. We also performed whole genome sequencing to identify SARS-CoV-2 lineages. Variant compositions were consistent with those of geographically and temporally matched municipal wastewater samples and clinical specimens. However, we also detected 10 of 22 mutations specific to the Alpha variant in the environmental water samples collected during January 2022-one year after the Alpha infection peak. We also identified mutations in the spike gene that have never been identified in published reports. Our findings demonstrate that environmental surveillance of flood control infrastructure may be an effective tool to understand public health conditions among unsheltered individuals-a vulnerable population that is underrepresented in clinical surveillance data.

Early Detection of Novel SARS-CoV-2 Variants from Urban and Rural Wastewater through Genome Sequencing and Machine Learning.

Genome sequencing from wastewater has emerged as an accurate and cost-effective tool for identifying SARS-CoV-2 variants. However, existing methods for analyzing wastewater sequencing data are not designed to detect novel variants that have not been characterized in humans. Here, we present an unsupervised learning approach that clusters co-varying and time-evolving mutation patterns leading to the identification of SARS-CoV-2 variants. To build our model, we sequenced 3,659 wastewater samples collected over a span of more than two years from urban and rural locations in Southern Nevada. We then developed a multivariate independent component analysis (ICA)-based pipeline to transform mutation frequencies into independent sources with co-varying and time-evolving patterns and compared variant predictions to >5,000 SARS-CoV-2 clinical genomes isolated from Nevadans. Using the source patterns as data-driven reference "barcodes", we demonstrated the model's accuracy by successfully detecting the Delta variant in late 2021, Omicron variants in 2022, and emerging recombinant XBB variants in 2023. Our approach revealed the spatial and temporal dynamics of variants in both urban and rural regions; achieved earlier detection of most variants compared to other computational tools; and uncovered unique co-varying mutation patterns not associated with any known variant. The multivariate nature of our pipeline boosts statistical power and can support accurate and early detection of SARS-CoV-2 variants. This feature offers a unique opportunity for novel variant and pathogen detection, even in the absence of clinical testing.

Prediction of micropollutant elimination during ozonation of municipal wastewater effluents: use of kinetic and water specific information.

Ozonation is effective in improving the quality of municipal wastewater effluents by eliminating organic micropollutants. Nevertheless, ozone process design is still limited by (i) the large number of structurally diverse micropollutants and (ii) the varying quality of wastewater matrices (especially dissolved organic matter). These issues were addressed by grouping 16 micropollutants according to their ozone and hydroxyl radical ((•)OH) rate constants and normalizing the applied ozone dose to the dissolved organic carbon concentration (i.e., g O3/g DOC). Consistent elimination of micropollutants was observed in 10 secondary municipal wastewater effluents spiked with 16 micropollutants (∼2 µg/L) in the absence of ozone demand exerted by nitrite. The elimination of ozone-refractory micropollutants was well predicted by measuring the (•)OH exposure by the decrease of the probe compound p-chlorobenzoic acid. The average molar (•)OH yields (moles of (•)OH produced per mole of ozone consumed) were 21 ± 3% for g O3/g DOC = 1.0, and the average rate constant for the reaction of (•)OH with effluent organic matter was (2.1 ± 0.6) × 10(4) (mg C/L)(-1) s(-1). On the basis of these results, a DOC-normalized ozone dose, together with the rate constants for the reaction of the selected micropollutants with ozone and (•)OH, and the measurement of the (•)OH exposure are proposed as key parameters for the prediction of the elimination efficiency of micropollutants during ozonation of municipal wastewater effluents with varying water quality.

The effects of solids retention time in full-scale activated sludge basins on trace organic contaminant concentrations.

Although pharmaceuticals and personal care products (PPCPs) and endocrine disrupting compounds (EDCs) are largely unregulated, water resource recovery facilities are increasingly using advanced chemical/physical treatment technologies (e.g., advanced oxidation and reverse osmosis) to remove or destroy these trace organic contaminants (TOrCs). This can both reduce potential adverse human health effects in reuse applications and mitigate environmental effects on aquatic ecosystems. Unfortunately, advanced treatment technologies are typically energy intensive and costly to implement, operate, and maintain. The goal of this study was to determine whether optimization of solids retention time (SRT) provided sufficient benefits to warrant such operational strategies for TOrC mitigation. Specifically, SRTs of 5.5, 6, and 15 days were evaluated to determine the effects on several standard wastewater parameters (e.g., nitrite, nitrate, and ammonia concentrations) and the degradation of TOrCs. The experimental SRTs were operated simultaneously in parallel, full-scale activated sludge basins. The results indicate that it can be beneficial to implement biological process optimization strategies using existing infrastructure while reducing reliance on advanced treatment technologies. This study also identified potential operational issues that might arise in activated sludge systems operating at extended SRTs.

Wastewater-Based Surveillance Does Not Belong in a Regulatory Framework Designed to Protect Waters That Receive Treated Wastewater. Comment on Wright, T.; Adhikari, A. Utilizing a National Wastewater Monitoring Program to Address the U.S. Opioid Epidemic: A Focus on Metro Atlanta, Georgia. Int. J. Environ. Res. Public Health 2023, 20, 5282.

We read with great interest the work by Wright and Adhikari on "Utilizing a National Wastewater Monitoring Program to Address the U.S. Opioid Epidemic: A Focus on Metro Atlanta, Georgia" [...].

Detection of the Omicron BA.1 Variant of SARS-CoV-2 in Wastewater From a Las Vegas Tourist Area.

Importance: Interpretation of wastewater surveillance data is potentially confounded in communities with mobile populations, so it is important to account for this issue when conducting wastewater-based epidemiology (WBE). Objectives: To leverage spatial and temporal differences in wastewater whole-genome sequencing (WGS) data to quantify relative SARS-CoV-2 contributions from visitors to southern Nevada. Design, Setting, and Participants: This cross-sectional wastewater surveillance study was performed during the COVID-19 pandemic (March 2020 to February 2022) and included weekly influent wastewater samples that were analyzed by reverse transcription-quantitative polymerase chain reaction to quantify SARS-CoV-2 RNA and WGS for identification of variants of concern. This study was conducted in the Las Vegas, Nevada, metropolitan area, which is a semi-urban area with approximately 2.3 million residents and nearly 1 million weekly visitors. Samples were collected from 7 wastewater treatment plant (WWTP) locations that collectively serve the vast majority of southern Nevada (excluding the small number of septic systems) and 1 manhole serving the southern portion of the Las Vegas Strip. With Las Vegas tourism returning to prepandemic levels in 2021, it was hypothesized that visitors were contributing a disproportionate fraction of SARS-CoV-2 RNA to the largest WWTP in southern Nevada, potentially confounding efforts to estimate COVID-19 incidence in the local community through WBE. Main Outcomes and Measures: Relative SARS-CoV-2 load and variants from visitors vs the local population. Results: The Omicron BA.1 VOC was detected in the Las Vegas Strip manhole approximately 1 week before its detection at the WWTP locations (December 13, 2021) and by clinical testing (December 14, 2021). On December 13, Omicron-specific mutations represented a mean (SD) of 48.0% (4.2%) of all genomes from the Las Vegas Strip manhole and 4.1% (1.4%) of all genomes at facilities 2 and 3; by December 20, Omicron-specific mutations represented means (SD) of 82.0% (3.0%) of all genomes at the Las Vegas Strip manhole and 48.0% (2.8%) of all genomes at facilities 2 and 3, respectively. During this time, it was estimated that visitors contributed more than 60% of the SARS-CoV-2 load to the sewershed serving the Las Vegas Strip and that Omicron prevalence among visitors was 40% to 60% on December 13 and 80% to 100% on December 20th. Conclusions and Relevance: Wastewater surveillance is a valuable complement to clinical tools and can provide time-sensitive data for decision-makers and policy makers. This study represents a novel approach for quantifying the confounding effects of mobile populations on wastewater surveillance data, thereby allowing for modification of an existing WBE framework for estimating COVID-19 incidence in southern Nevada.

Identification of a rare SARS-CoV-2 XL hybrid variant in wastewater and the subsequent discovery of two infected individuals in Nevada.

The identification of novel SARS-CoV-2 variants can predict new patterns of COVID-19 community transmission and lead to the deployment of public health resources. However, increased access to at-home antigen tests and reduced free PCR tests have recently led to data gaps for the surveillance of evolving SARS-CoV-2 variants. To overcome such limitations, we asked whether wastewater surveillance could be leveraged to detect rare variants circulating in a community before local detection in human cases. Here, we performed whole genome sequencing (WGS) of SARS-CoV-2 from a wastewater treatment plant serving Las Vegas, Nevada in April 2022. Using metrics that exceeded 100× depth at a coverage of >90 % of the viral genome, we identified a variant profile similar to the XL recombinant lineage containing 26 mutations found in BA.1 and BA.2 and three private mutations. Prompted by the discovery of this rare lineage in wastewater, we analyzed clinical COVID-19 sequencing data from Southern Nevada and identified two cases infected with the XL lineage. Taken together, our data highlight how wastewater genome sequencing data can be used to discover rare SARS-CoV-2 lineages in a community and complement local public health surveillance.