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.

Onsite Nonpotable Water Systems Pathogen Treatment Targets: A Comparison of Infection and Disability-Adjusted Life Years (DALYs) Risk Benchmark Approaches.

Pathogen log10 reduction targets for onsite nonpotable water systems were calculated using both annual infection (LRTINF) and disability-adjusted life year (LRTDALY) benchmarks. The DALY is a measure of the health burden of a disease, accounting for both the severity and duration of illness. Results were evaluated to identify if treatment requirements change when accounting for the likelihood, duration, and severity of illness in addition to the likelihood of infection. The benchmarks of 10-4 infections per person per year (ppy) and 10-6 DALYs ppy were adopted along with multilevel dose-response models for Norovirus and Campylobacter jejuni, which characterize the probability of illness given infection (Pill|inf) as dose-dependent using challenge or outbreak data. We found differences between treatment requirements, LRTINF - LRTDALY, for some pathogens, driven by the likelihood of illness, rather than the severity of illness. For pathogens with dose-independent Pill|inf characterizations, such as Cryptosporidium spp., Giardia, and Salmonella enterica, the difference, LRTINF - LRTDALY, was identical across reuse scenarios (

Characterizing Spatial Information Loss for Wastewater Surveillance Using crAssphage: Effect of Decay, Temperature, and Population Mobility.

Populations contribute information about their health status to wastewater. Characterizing how that information degrades in transit to wastewater sampling locations (e.g., wastewater treatment plants and pumping stations) is critical to interpret wastewater responses. In this work, we statistically estimate the loss of information about fecal contributions to wastewater from spatially distributed populations at the census block group resolution. This was accomplished with a hydrologically and hydraulically influenced spatial statistical approach applied to crAssphage (Carjivirus communis) load measured from the influent of four wastewater treatment plants in Hamilton County, Ohio. We find that we would expect to observe a 90% loss of information about fecal contributions from a given census block group over a travel time of 10.3 h. This work demonstrates that a challenge to interpreting wastewater responses (e.g., during wastewater surveillance) is distinguishing between a distal but large cluster of contributions and a near but small contribution. This work demonstrates new modeling approaches to improve measurement interpretation depending on sewer network and wastewater characteristics (e.g., geospatial layout, temperature variability, population distribution, and mobility). This modeling can be integrated into standard wastewater surveillance methods and help to optimize sewer sampling locations to ensure that different populations (e.g., vulnerable and susceptible) are appropriately represented.

Ohio Coronavirus Wastewater Monitoring Network: Implementation of Statewide Monitoring for Protecting Public Health.

CONTEXT: Prior to the COVID-19 pandemic, wastewater influent monitoring for tracking disease burden in sewered communities was not performed in Ohio, and this field was only on the periphery of the state academic research community. PROGRAM: Because of the urgency of the pandemic and extensive state-level support for this new technology to detect levels of community infection to aid in public health response, the Ohio Water Resources Center established relationships and support of various stakeholders. This enabled Ohio to develop a statewide wastewater SARS-CoV-2 (severe acute respiratory syndrome coronavirus 2) monitoring network in 2 months starting in July 2020. IMPLEMENTATION: The current Ohio Coronavirus Wastewater Monitoring Network (OCWMN) monitors more than 70 unique locations twice per week, and publicly available data are updated weekly on the public dashboard. EVALUATION: This article describes the process and decisions that were made during network initiation, the network progression, and data applications, which can inform ongoing and future pandemic response and wastewater monitoring. DISCUSSION: Overall, the OCWMN established wastewater monitoring infrastructure and provided a useful tool for public health professionals responding to the pandemic.

Geospatial Patterns of Antimicrobial Resistance Genes in the US EPA National Rivers and Streams Assessment Survey.

Antimicrobial resistance (AR) is a serious global problem due to the overuse of antimicrobials in human, animal, and agriculture sectors. There is intense research to control the dissemination of AR, but little is known regarding the environmental drivers influencing its spread. Although AR genes (ARGs) are detected in many different environments, the risk associated with the spread of these genes to microbial pathogens is unknown. Recreational microbial exposure risks are likely to be greater in water bodies receiving discharge from human and animal waste in comparison to less disturbed aquatic environments. Given this scenario, research practitioners are encouraged to consider an ecological context to assess the effect of environmental ARGs on public health. Here, we use a stratified, probabilistic survey of nearly 2000 sites to determine national patterns of the anthropogenic indicator class I integron Integrase gene (intI1) and several ARGs in 1.2 million kilometers of United States (US) rivers and streams. Gene concentrations were greater in eastern than in western regions and in rivers and streams in poor condition. These first of their kind findings on the national distribution of intI1 and ARGs provide new information to aid risk assessment and implement mitigation strategies to protect public health.

Quantitative Microbial Risk Assessment of Antimicrobial Resistant and Susceptible Staphylococcus aureus in Reclaimed Wastewaters.

The annual risks of colonization, skin infection, bloodstream infection (BSI), and disease burden from exposures to antibiotic-resistant and susceptible Staphylococcus aureus (S. aureus) were estimated using quantitative microbial risk assessment (QMRA). We estimated the probability of nasal colonization after immersion in wastewater (WW) or greywater (GW) treated across a range of treatment alternatives and subsequent infection. Horizontal gene transfer was incorporated into the treatment model but had little effect on the predicted risk. The cumulative annual probability of infection (resulting from self-inoculation) was most sensitive to the treatment log10 reduction value (LRV), S. aureus concentration, and the newly calculated morbidity ratios and was below the health benchmark of 10-4 infections per person per year (ppy) given a treatment LRV of roughly 3.0. The predicted annual disability-adjusted life years (DALYs), which were dominated by BSI, were below the health benchmark of 10-6 DALYs ppy for resistant and susceptible S. aureus, given LRVs of 4.5 and 3.5, respectively. Thus, the estimated infection risks and disease burdens resulting from nasal colonization are below the relevant health benchmarks for risk-based, nonpotable, or potable reuse systems but possibly above for immersion in minimally treated GW or WW. Strain-specific data to characterize dose-response and concentration in WW are needed to substantiate the QMRA.

A risk-based evaluation of onsite, non-potable reuse systems developed in compliance with conventional water quality measures.

Water quality standards (WQSs) based on water quality measures (e.g., fecal indicator bacteria (FIB)) have been used by regulatory agencies to assess onsite, non-potable water reuse systems. A risk-based approach, based on quantitative microbial risk assessment, was developed to define treatment requirements that achieve benchmark levels of risk. This work compared these approaches using the predicted annual infection risks for non-potable reuse systems that comply with WQSs along with the benchmark risk levels achieved by the risk-based systems. The systems include a recirculating synthetic sand filter or an aerobic membrane bioreactor (MBR) combined with disinfection. The greywater MBR system had predicted risks in the range of the selected benchmark levels. However, wastewater reuse with systems that comply with WQSs had uncertain and potentially high predicted risks (i.e., >10-2 infections per person per year) in residential applications, due to exposures to viruses and protozoa. The predicted risks illustrate that WQSs based on FIB treatment performance do not ensure adequate treatment removal of viruses and protozoa. We present risk-based log10 pathogen reduction targets for intermediate-sized non-potable systems, which are 0.5 log10 less than those previously proposed for district-sized systems. Still, pathogen treatment performance data are required to better manage non-potable reuse risk.

Life cycle assessment of a rainwater harvesting system compared with an AC condensate harvesting system.

This study presents a life cycle assessment (LCA) of a rainwater harvesting (RWH) system and an air-conditioning condensate harvesting (ACH) system for non-potable water reuse. U.S. commercial buildings were reviewed to design rooftop RWH and ACH systems for one to multi-story buildings' non-potable water demand. A life cycle inventory was compiled from the U.S. EPA's database. Nine scenarios were analyzed, including baseline RWH system, ACH system, and combinations of the two systems adapted to 4-story and 19-story commercial buildings in San Francisco and a 4-story building in Washington, DC. Normalization of 11 life cycle impact assessment categories showed that RWH systems in 4-story buildings at both locations outperformed ACH systems (45-80% of ACH impacts) except equivalent in Evaporative Water Consumption. However, San Francisco's ACH system in 19-story building outperformed the RWH system (51-83% of RWH impacts) due to the larger volume of ACH collection, except equivalent in Evaporative Water Consumption. For all three buildings, the combined system preformed equivalently to the better-performing option (≤4-8% impact difference compared to the maximum system). Sensitivity analysis of the volume of water supply and building occupancy showed impact-specific results. Local climatic conditions, rainfall, humidity, water collections and demands are important when designing building-scale RWH and ACH systems. LCA models are transferrable to other locations with variable climatic conditions for decision-making when developing and implementing on-site non-potable water systems.

Bioaerosol Deposition to Food Crops near Manure Application: Quantitative Microbial Risk Assessment.

Production of both livestock and food crops are central priorities of agriculture; however, food safety concerns arise where these practices intersect. In this study, we investigated the public health risks associated with potential bioaerosol deposition to crops grown in the vicinity of manure application sites. A field sampling campaign at dairy manure application sites supported the emission, transport, and deposition modeling of bioaerosols emitted from these lands following application activities. Results were coupled with a quantitative microbial risk assessment model to estimate the infection risk due to consumption of leafy green vegetable crops grown at various distances downwind from the application area. Inactivation of pathogens ( spp., spp., and O157:H7) on both the manure-amended field and on crops was considered to determine the maximum loading of pathogens to plants with time following application. Overall median one-time infection risks at the time of maximum loading decreased from 1:1300 at 0 m directly downwind from the field to 1:6700 at 100 m and 1:92,000 at 1000 m; peak risks (95th percentiles) were considerably greater (1:18, 1:89, and 1:1200, respectively). Median risk was below 1:10,000 at >160 m downwind. As such, it is recommended that a 160-m setback distance is provided between manure application and nearby leafy green crop production. Additional distance or delay before harvest will provide further protection of public health.

Emission and Dispersion of Bioaerosols from Dairy Manure Application Sites: Human Health Risk Assessment.

In this study, we report the human health risk of gastrointestinal infection associated with inhalation exposure to airborne zoonotic pathogens emitted following application of dairy cattle manure to land. Inverse dispersion modeling with the USEPA's AERMOD dispersion model was used to determine bioaerosol emission rates based on edge-of-field bioaerosol and source material samples analyzed by real-time quantitative polymerase chain reaction (qPCR). Bioaerosol emissions and transport simulated with AERMOD, previously reported viable manure pathogen contents, relevant exposure pathways, and pathogen-specific dose-response relationships were then used to estimate potential downwind risks with a quantitative microbial risk assessment (QMRA) approach. Median 8-h infection risks decreased exponentially with distance from a median of 1:2700 at edge-of-field to 1:13 000 at 100 m and 1:200 000 at 1000 m; peak risks were considerably greater (1:33, 1:170, and 1:2500, respectively). These results indicate that bioaerosols emitted from manure application sites following manure application may present significant public health risks to downwind receptors. Manure management practices should consider improved controls for bioaerosols in order to reduce the risk of disease transmission.

Hierarchal clustering yields insight into multidrug-resistant bacteria isolated from a cattle feedlot wastewater treatment system.

Forty-two percent of Escherichia coli and 58% of Enterococcus spp. isolated from cattle feedlot runoff and associated infiltration basin and constructed wetland treatment system were resistant to at least one antibiotic of clinical importance; a high level of multidrug resistance (22% of E. coli and 37% of Enterococcus spp.) was observed. Hierarchical clustering revealed a closely associated resistance cluster among drug-resistant E. coli isolates that included cephalosporins (ceftiofur, cefoxitin, and ceftriaxone), aminoglycosides (gentamycin, kanamycin, and amikacin), and quinolone nalidixic acid; antibiotics from these classes were used at the study site, and cross-resistance may be associated with transferrable multiple-resistance elements. For Enterococcus spp., co-resistance among vancomycin, linezolid, and daptomycin was common; these antibiotics are reserved for complicated clinical infections and have not been approved for animal use. Vancomycin resistance (n = 49) only occurred when isolates were resistant to linezolid, daptomycin, and all four of the MLSB (macrolide-lincosamide-streptogramin B) antibiotics tested (tylosin, erythromycin, lincomycin, and quinipristin/dalfopristin). This suggests that developing co-resistance to MLSB antibiotics along with cyclic lipopeptides and oxazolidinones may result in resistance to vancomycin as well. Effects of the treatment system on antibiotic resistance were pronounced during periods of no rainfall and low flow (long residence time). Increased hydraulic loading (short residence time) under the influence of rain caused antibiotic-resistant bacteria to be flushed through the treatment system. This presents concern for environmental discharge of multidrug-resistant organisms relevant to public health.

A unit process log reduction database for water reuse practitioners.

Pathogen reduction for the purpose of human health protection is a critical function provided by water reuse systems. Pathogen reduction performance potential is dependent on a wide range of design and operational parameters. Poor understanding of pathogen reduction performance has important consequences-under treatment can jeopardize human health, while over treatment can lead to unnecessary costs and environmental impacts. Documented pathogen reduction potential of the unit processes that make up water reuse treatment trains is based on a highly dispersed and unstructured literature, creating an impediment to practitioners looking to design, model or simply better understand these systems. This review presents a database of compiled log reduction values (LRVs) and log reduction credits (LRCs) for unit processes capable of providing some level of pathogen reduction, with a focus on processes suitable for onsite non-potable water reuse systems. Where reported, we have also compiled all relevant design and operational factors associated with the LRVs and LRCs. Overall, we compiled over 1100 individual LRV data entries for 31 unit processes, and LRCs for 8 unit processes. Results show very inconsistent reporting of influencing parameters, representing a limitation to the use of some of the data. As a standalone resource, the database (included as Supplemental Information) provides water reuse practitioners with easy access to LRV and LRC data. The database is also part of a longer-term effort to optimize the balance between human health protection, potential environmental impacts and cost of water reuse treatment trains.

Non-targeted analysis and toxicity prediction for evaluation of photocatalytic membrane distillation removing organic contaminants from hypersaline oil and gas field-produced water.

Membrane distillation (MD) has received ample recognition for treating complex wastewater, including hypersaline oil and gas (O&G) produced water (PW). Rigorous water quality assessment is critical in evaluating PW treatment because PW consists of numerous contaminants beyond the targets listed in general discharge and reuse standards. This study evaluated a novel photocatalytic membrane distillation (PMD) process, with and without a UV light source, against a standard vacuum membrane distillation (VMD) process for treating PW, utilizing targeted analyses and a non-targeted chemical identification workflow coupled with toxicity predictions. PMD with UV light resulted in better removals of dissolved organic carbon, ammoniacal nitrogen, and conductivity. Targeted organic analyses identified only trace amounts of acetone and 2-butanone in distillates. According to non-targeted analysis, the number of suspects reduced from 65 in feed to 25-30 across all distillate samples. Certain physicochemical properties of compounds influenced contaminant rejection in different MD configurations. According to preliminary toxicity predictions, VMD, PMD with and without UV distillate samples, respectively contained 21, 22, and 23 suspects associated with critical toxicity concerns. Overall, non-targeted analysis together with toxicity prediction provides a competent supportive tool to assess treatment efficiency and potential impacts on public health and the environment during PW reuse.

A one health approach for monitoring antimicrobial resistance: developing a national freshwater pilot effort.

Antimicrobial resistance (AMR) is a world-wide public health threat that is projected to lead to 10 million annual deaths globally by 2050. The AMR public health issue has led to the development of action plans to combat AMR, including improved antimicrobial stewardship, development of new antimicrobials, and advanced monitoring. The National Antimicrobial Resistance Monitoring System (NARMS) led by the United States (U.S) Food and Drug Administration along with the U.S. Centers for Disease Control and U.S. Department of Agriculture has monitored antimicrobial resistant bacteria in retail meats, humans, and food animals since the mid 1990's. NARMS is currently exploring an integrated One Health monitoring model recognizing that human, animal, plant, and environmental systems are linked to public health. Since 2020, the U.S. Environmental Protection Agency has led an interagency NARMS environmental working group (EWG) to implement a surface water AMR monitoring program (SWAM) at watershed and national scales. The NARMS EWG divided the development of the environmental monitoring effort into five areas: (i) defining objectives and questions, (ii) designing study/sampling design, (iii) selecting AMR indicators, (iv) establishing analytical methods, and (v) developing data management/analytics/metadata plans. For each of these areas, the consensus among the scientific community and literature was reviewed and carefully considered prior to the development of this environmental monitoring program. The data produced from the SWAM effort will help develop robust surface water monitoring programs with the goal of assessing public health risks associated with AMR pathogens in surface water (e.g., recreational water exposures), provide a comprehensive picture of how resistant strains are related spatially and temporally within a watershed, and help assess how anthropogenic drivers and intervention strategies impact the transmission of AMR within human, animal, and environmental systems.

Enteric pathogen reduction targets for onsite non-potable water systems: A critical evaluation.

Onsite non-potable water systems (ONWS) collect and treat local source waters for non-potable end uses such as toilet flushing and irrigation. Quantitative microbial risk assessment (QMRA) has been used to set pathogen log10-reduction targets (LRTs) for ONWS to achieve the risk benchmark of 10-4 infections per person per year (ppy) in a series of two efforts completed in 2017 and 2021. In this work, we compare and synthesize the ONWS LRT efforts to inform the selection of pathogen LRTs. For onsite wastewater, greywater, and stormwater, LRTs for human enteric viruses and parasitic protozoa were within 1.5-log10 units between 2017 and 2021 efforts, despite differences in approaches used to characterize pathogens in these waters. For onsite wastewater and greywater, the 2017 effort used an epidemiology-based model to simulate pathogen concentrations contributed exclusively from onsite waste and selected Norovirus as the viral reference pathogen; the 2021 effort used municipal wastewater pathogen data and cultivable adenoviruses as the reference viral pathogen. Across source waters, the greatest differences occurred for viruses in stormwater, given the newly available municipal wastewater characterizations used for modeling sewage contributions in 2021 and the different selection of reference pathogens (Norovirus vs. adenoviruses). The roof runoff LRTs support the need for protozoa treatment, but these remain difficult to characterize due to the pathogen variability in roof runoff across space and time. The comparison highlights adaptability of the risk-based approach, allowing for updated LRTs as site specific or improved information becomes available. Future research efforts should focus on data collection of onsite water sources.

Water, Water Everywhere, but Every Drop Unique: Challenges in the Science to Understand the Role of Contaminants of Emerging Concern in the Management of Drinking Water Supplies.

The protection and management of water resources continues to be challenged by multiple and ongoing factors such as shifts in demographic, social, economic, and public health requirements. Physical limitations placed on access to potable supplies include natural and human-caused factors such as aquifer depletion, aging infrastructure, saltwater intrusion, floods, and drought. These factors, although varying in magnitude, spatial extent, and timing, can exacerbate the potential for contaminants of concern (CECs) to be present in sources of drinking water, infrastructure, premise plumbing and associated tap water. This monograph examines how current and emerging scientific efforts and technologies increase our understanding of the range of CECs and drinking water issues facing current and future populations. It is not intended to be read in one sitting, but is instead a starting point for scientists wanting to learn more about the issues surrounding CECs. This text discusses the topical evolution CECs over time (Section 1), improvements in measuring chemical and microbial CECs, through both analysis of concentration and toxicity (Section 2) and modeling CEC exposure and fate (Section 3), forms of treatment effective at removing chemical and microbial CECs (Section 4), and potential for human health impacts from exposure to CECs (Section 5). The paper concludes with how changes to water quantity, both scarcity and surpluses, could affect water quality (Section 6). Taken together, these sections document the past 25 years of CEC research and the regulatory response to these contaminants, the current work to identify and monitor CECs and mitigate exposure, and the challenges facing the future.

Characterization of roof runoff microbial quality in four U.S. cities with varying climate and land use characteristics.

Roof runoff has the potential to serve as an important local water source in regions with growing populations and limited water supply. Given the scarcity of guidance regulating the use of roof runoff, a need exists to characterize the microbial quality of roof runoff. The objective of this 2-year research effort was to examine roof runoff microbial quality in four U.S. cities: Fort Collins, CO; Tucson, AZ; Baltimore, MD; and Miami, FL. Seven participants, i.e., homeowners and schools, were recruited in each city to collect roof runoff samples across 13 precipitation events. Sample collection was done as part of a citizen science approach. The presence and concentrations of indicator organisms and potentially human-infectious pathogens in roof runoff were determined using culture methods and digital droplet polymerase chain reaction (ddPCR), respectively. The analyzed pathogens included Salmonella spp., Campylobacter spp., Giardia duodenalis, and Cryptosporidium parvum. Several factors were evaluated to study their influence on the presence of potentially human-infectious pathogens including the physicochemical characteristics (total suspended solids, volatile suspended solids, total dissolved solids, chemical oxygen demand, and turbidity) of roof runoff, concentrations of indicator organisms, presence/absence of trees, storm properties (rainfall depth and antecedent dry period), percent of impervious cover surrounding each sampling location, seasonality, and geographical location. E. coli and enterococci were detected in 73.4% and 96.2% of the analyzed samples, respectively. Concentrations of both E. coli and enterococci ranged from <0 log10 to >3.38 log10 MPN/100 mL. Salmonella spp. invA, Campylobacter spp. ceuE, and G. duodenalis ß - giardin gene targets were detected in 8.9%, 2.5%, and 5.1% of the analyzed samples, respectively. Campylobacter spp. mapA and C. parvum 18S rRNA gene targets were not detected in any of the analyzed samples. The detection of Salmonella spp. invA was influenced by the geographical location of the sampling site (Chi-square p-value < 0.001) as well as the number of antecedent dry days prior to a rain event (p-value = 0.002, negative correlation). The antecedent dry period was negatively correlated with the occurrence of Campylobacter spp. ceuE as well (p-value = 0.07). On the other hand, the presence of G. duodenalis ß-giardin in roof runoff was positively correlated with rainfall depth (p-value = 0.05). While physicochemical parameters and impervious area were not found to be correlated with the presence/absence of potentially human-infectious pathogens, significant correlations were found between meteorological parameters and the presence/absence of potentially human-infectious pathogens. Additionally, a weak, yet significant positive correlation, was found only between the concentrations of E. coli and those of Giardia duodenalis ß-giardin. This dataset represents the largest-scale study to date of enteric pathogens in U.S. roof runoff collections and will inform treatment targets for different non-potable end uses for roof runoff. However, the dataset is limited by the low percent detection of bacterial and protozoan pathogens, an issue that is likely to persist challenging the characterization of roof runoff microbial quality given sampling limitations related to the volume and number of samples.

Onsite Non-potable Reuse for Large Buildings: Environmental and Economic Suitability as a Function of Building Characteristics and Location.

Onsite non-potable reuse (NPR) is a way for buildings to conserve water using onsite sources for uses like toilet flushing, laundry and irrigation. Although early case study results are promising, aspects like system suitability, cost and environmental performance remain difficult to quantify and compare across broad geographic contexts and variable system configurations. In this study, we evaluate four NPR system types - rainwater harvesting (RWH), air-conditioning condensate harvesting (ACH), and source-separated graywater and mixed wastewater membrane bioreactors (GWMBR, WWMBR) - in terms of their ability to satisfy onsite non-potable demand, their environmental impacts and their economic cost. As part of the analysis, we developed the Non-potable Environmental and Economic Water Reuse Calculator (NEWR), a publicly available U.S. EPA web application that allows users to generate planning-level estimates of system cost and environmental performance using location and basic building characteristics as inputs. By running NEWR for a range of scenarios, we find that, across the U.S., rainfall and air-conditioner condensate are only able to satisfy a fraction of the non-potable demand typical of large buildings even under favorable climate conditions. Environmental impacts of RWH and ACH systems depend on local climate and were comparable to the ones of MBR systems where annual rainfall exceeds approximately 10 in/yr or annual condensate potential exceeds approximately 3 gal/cfm. MBR systems can meet all non-potable demands but their environmental impacts depend more on the composition of the local energy grid, owing to their greater reliance on electricity inputs. Incorporation of thermal recovery to offset building hot water heating requirements amplifies the influence of the local grid mix on environmental impacts, with mixed results depending on grid composition and whether thermal recovery offsets natural gas or electricity consumption. Additional environmental benefits are realized when NPR systems are implemented in water scarce regions with diverse topography and regions relying on groundwater sources, which increases the benefits of reducing reliance on centralized drinking water services. In terms of cost, WWMBRs were found to have the lowest cost under the largest range of building characteristics and locations, achieving cost parity with local drinking water rates when those rates were more than $7 per 1000 gallons, which occurred in 19% of surveyed cities.

Standardizing data reporting in the research community to enhance the utility of open data for SARS-CoV-2 wastewater surveillance.

SARS-CoV-2 RNA detection in wastewater is being rapidly developed and adopted as a public health monitoring tool worldwide. With wastewater surveillance programs being implemented across many different scales and by many different stakeholders, it is critical that data collected and shared are accompanied by an appropriate minimal amount of metainformation to enable meaningful interpretation and use of this new information source and intercomparison across datasets. While some databases are being developed for specific surveillance programs locally, regionally, nationally, and internationally, common globally-adopted data standards have not yet been established within the research community. Establishing such standards will require national and international consensus on what metainformation should accompany SARS-CoV-2 wastewater measurements. To establish a recommendation on minimum information to accompany reporting of SARS-CoV-2 occurrence in wastewater for the research community, the United States National Science Foundation (NSF) Research Coordination Network on Wastewater Surveillance for SARS-CoV-2 hosted a workshop in February 2021 with participants from academia, government agencies, private companies, wastewater utilities, public health laboratories, and research institutes. This report presents the primary two outcomes of the workshop: (i) a recommendation on the set of minimum meta-information that is needed to confidently interpret wastewater SARS-CoV-2 data, and (ii) insights from workshop discussions on how to improve standardization of data reporting.