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.

Informing Building Strategies to Reduce Infectious Aerosol Transmission Risk by Integrating DNA Aerosol Tracers with Quantitative Microbial Risk Assessment.

Using aerosol-based tracers to estimate risk of infectious aerosol transmission aids in the design of buildings with adequate protection against aerosol transmissible pathogens, such as SARS-CoV-2 and influenza. We propose a method for scaling a SARS-CoV-2 bulk aerosol quantitative microbial risk assessment (QMRA) model for impulse emissions, coughing or sneezing, with aerosolized synthetic DNA tracer concentration measurements. With point-of-emission ratios describing relationships between tracer and respiratory aerosol emission characteristics (i.e., volume and RNA or DNA concentrations) and accounting for aerosolized pathogen loss of infectivity over time, we scale the inhaled pathogen dose and risk of infection with time-integrated tracer concentrations measured with a filter sampler. This tracer-scaled QMRA model is evaluated through scenario testing, comparing the impact of ventilation, occupancy, masking, and layering interventions on infection risk. We apply the tracer-scaled QMRA model to measurement data from an ambulatory care room to estimate the risk reduction resulting from HEPA air cleaner operation. Using DNA tracer measurements to scale a bulk aerosol QMRA model is a relatively simple method of estimating risk in buildings and can be applied to understand the impact of risk mitigation efforts.

Towards risk assessment for antibiotic resistant pathogens in recycled water: a systematic review and summary of research needs.

Risk assessment is critical for identifying target concentrations of antibiotic resistant pathogens necessary for mitigating potential harmful exposures associated with water reuse. However, there is currently limited available data characterizing the concentrations of antibiotic resistant bacteria (ARB) and antibiotic resistance genes (ARGs) in recycled water to support robust efforts at risk assessment. The objective of this systematic review was to identify and synthesize the existing literature documenting the presence and abundance of ARB and ARGs in recycled water. In addition, this review identifies best practices and explores monitoring targets for studying ARB and ARGs in recycled water to guide future work and identifies key research needs aimed at better supporting quantitative microbial risk assessment focused on recycled water and antibiotic resistance. Future efforts to collect data about ARB and ARG prevalence in recycled water should report concentration data per unit volume. Sample metadata should also be provided, including a description of treatment approach, a description of planned water uses (e.g., potable, irrigation), methods for conveyance to the point of use, and available physicochemical water quality data. Additional research is needed aimed at identifying recommended ARB and ARG monitoring targets and for developing approaches to incorporate metagenomic data into risk assessment.

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.

Navigating Data Uncertainty and Modeling Assumptions in Quantitative Microbial Risk Assessment in an Informal Settlement in Kampala, Uganda.

Decision-makers in developing communities often lack credible data to inform decisions related to water, sanitation, and hygiene. Quantitative microbial risk assessment (QMRA), which quantifies pathogen-related health risks across exposure routes, can be informative; however, the utility of QMRA for decision-making is often undermined by data gaps. This work integrates QMRA, uncertainty and sensitivity analyses, and household surveys in Bwaise, Kampala (Uganda) to characterize the implications of censored data management, identify sources of uncertainty, and incorporate risk perceptions to improve the suitability of QMRA for informal settlements or similar settings. In Bwaise, drinking water, hand rinse, and soil samples were collected from 45 households and supplemented with data from 844 surveys. Quantified pathogen (adenovirus, Campylobacter jejuni, and Shigella spp./EIEC) concentrations were used with QMRA to model infection risks from exposure through drinking water, hand-to-mouth contact, and soil ingestion. Health risks were most sensitive to pathogen data, hand-to-mouth contact frequency, and dose-response models (particularly C. jejuni). When managing censored data, results from upper limits of detection, half of limits of detection, and uniform distributions returned similar results, which deviated from lower limits of detection and maximum likelihood estimation imputation approaches. Finally, risk perceptions (e.g., it is unsafe to drink directly from a water source) were identified to inform risk management.

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.

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.

Risk-Based Critical Concentrations of Legionella pneumophila for Indoor Residential Water Uses.

Legionella spp. is a key contributor to the United States waterborne disease burden. Despite potentially widespread exposure, human disease is relatively uncommon, except under circumstances where pathogen concentrations are high, host immunity is low, or exposure to small-diameter aerosols occurs. Water quality guidance values for Legionella are available for building managers but are generally not based on technical criteria. To address this gap, a quantitative microbial risk assessment (QMRA) was conducted using target risk values in order to calculate corresponding critical concentrations on a per-fixture and aggregate (multiple fixture exposure) basis. Showers were the driving indoor exposure risk compared to sinks and toilets. Critical concentrations depended on the dose response model (infection vs clinical severity infection, CSI), risk target used (infection risk vs disability adjusted life years [DALY] on a per-exposure or annual basis), and fixture type (conventional vs water efficient or "green"). Median critical concentrations based on exposure to a combination of toilet, faucet, and shower aerosols ranged from ∼10-2 to ∼100 CFU per L and ∼101 to ∼103 CFU per L for infection and CSI dose response models, respectively. As infection model results for critical L. pneumophila concentrations were often below a feasible detection limit for culture-based assays, the use of CSI model results for nonhealthcare water systems with a 10-6 DALY pppy target (the more conservative target) would result in an estimate of 12.3 CFU per L (arithmetic mean of samples across multiple fixtures and/or over time). Single sample critical concentrations with a per-exposure-corrected DALY target at each conventional fixture would be 1.06 × 103 CFU per L (faucets), 8.84 × 103 CFU per L (toilets), and 14.4 CFU per L (showers). Using a 10-4 annual infection risk target would give a 1.20 × 103 CFU per L mean for multiple fixtures and single sample critical concentrations of 1.02 × 105, 8.59 × 105, and 1.40 × 103 CFU per L for faucets, toilets, and showers, respectively. Annual infection risk-based target estimates are in line with most current guidance documents of less than 1000 CFU per L, while DALY-based guidance suggests lower critical concentrations might be warranted in some cases. Furthermore, approximately <10 CFU per mL L. pneumophila may be appropriate for healthcare or susceptible population settings. This analysis underscores the importance of the choice of risk target as well as sampling program considerations when choosing the most appropriate critical concentration for use in public health guidance.

Cryptosporidium and Giardia in Wastewater and Surface Water Environments.

and spp. are significant contributors to the global waterborne disease burden. Waterways used as sources of drinking water and for recreational activity can become contaminated through the introduction of fecal materials derived from humans and animals. Multiple studies have reported the occurence or concentrations of these pathogens in the environment. However, this information has not been comprehensively reviewed. Quantitative microbial risk assessment (QMRA) for and can be beneficial, but it often relies on the concentrations in environmental sources reported from the literature. A thorough literature review was conducted to develop an inventory of reported and concentrations in wastewater and surface water available in the literature. This information can be used to develop QMRA inputs. and (oo)cyst concentrations in untreated wastewater were up to 60,000 oocysts L and 100,000 cysts L, respectively. The maximum reported concentrations for and in surface water were 8400 oocysts L and 1000 cysts L, respectively. A summary of the factors for interpretation of concentration information including common quantification methods, survival and persistence, biofilm interactions, genotyping, and treatment removal is provided in this review. This information can help in identifying assumptions implicit in various QMRA parameters, thus providing the context and rationale to guide model formulation and application. Additionally, it can provide valuable information for water quality practitioners striving to meet the recreational water quality or treatment criteria. The goal is for the information provided in the current review to aid in developing source water protection and monitoring strategies that will minimize public health risks.

Seasonal Assessment of Opportunistic Premise Plumbing Pathogens in Roof-Harvested Rainwater Tanks.

A seasonal study on the occurrence of six opportunistic premise plumbing pathogens (OPPPs) in 24 roof-harvested rainwater (RHRW) tanks repeatedly sampled over six monthly sampling events (n = 144) from August 2015 to March 2016 was conducted using quantitative qPCR. Fecal indicator bacteria (FIB) Escherichia coli (E. coli) and Enterococcus spp. were enumerated using culture-based methods. All tank water samples over the six events were positive for at least one OPPP (Legionella spp., Legionella pneumophila, Mycobacterium avium, Mycobacterium intracellulare, Pseudmonas aeruginosa, or Acanthamoeba spp.) during the entire course of the study. FIB were positively but weakly correlated with P. aeruginosa (E. coli vs P. aeruginosa τ = 0.090, p = 0.027; Enterococcus spp. vs P. aeruginosa τ = 0.126, p = 0.002), but not the other OPPPs. FIBs were more prevalent during the wet season than the dry season, and L. pneumophila was only observed during the wet season. However, concentrations of Legionella spp., M. intracellulare, Acanthamoeba spp., and M. avium peaked during the dry season. Correlations were assessed between FIB and OPPPs with meteorological variables, and it was determined that P. aeruginosa was the only OPPP positively associated with an increased antecedent dry period, suggesting stagnation time may play a role for the occurrence of this OPPP in tank water. Infection risks may exceed commonly cited benchmarks for uses reported in the rainwater usage survey such as pool top-up, and warrant further exploration through quantitative microbial risk assessment (QMRA).

Incorporating Time-Dose-Response into Legionella Outbreak Models.

A novel method was used to incorporate in vivo host-pathogen dynamics into a new robust outbreak model for legionellosis. Dose-response and time-dose-response (TDR) models were generated for Legionella longbeachae exposure to mice via the intratracheal route using a maximum likelihood estimation approach. The best-fit TDR model was then incorporated into two L. pneumophila outbreak models: an outbreak that occurred at a spa in Japan, and one that occurred in a Melbourne aquarium. The best-fit TDR from the murine dosing study was the beta-Poisson with exponential-reciprocal dependency model, which had a minimized deviance of 32.9. This model was tested against other incubation distributions in the Japan outbreak, and performed consistently well, with reported deviances ranging from 32 to 35. In the case of the Melbourne outbreak, the exponential model with exponential dependency was tested against non-time-dependent distributions to explore the performance of the time-dependent model with the lowest number of parameters. This model reported low minimized deviances around 8 for the Weibull, gamma, and lognormal exposure distribution cases. This work shows that the incorporation of a time factor into outbreak distributions provides models with acceptable fits that can provide insight into the in vivo dynamics of the host-pathogen system.

Applications of Quantitative Microbial Risk Assessment to Respiratory Pathogens and Implications for Uptake in Policy: A State-of-the-Science Review.

BACKGROUND: Respiratory tract infections are major contributors to the global disease burden. Quantitative microbial risk assessment (QMRA) holds potential as a rapidly deployable framework to understand respiratory pathogen transmission and inform policy on infection control. OBJECTIVES: The goal of this paper was to evaluate, motivate, and inform further development of the use of QMRA as a rapid tool to understand the transmission of respiratory pathogens and improve the evidence base for infection control policies. METHODS: We conducted a literature review to identify peer-reviewed studies of complete QMRA frameworks on aerosol inhalation or contact transmission of respiratory pathogens. From each of the identified studies, we extracted and summarized information on the applied exposure model approaches, dose-response models, and parameter values, including risk characterization. Finally, we reviewed linkages between model outcomes and policy. RESULTS: We identified 93 studies conducted in 16 different countries with complete QMRA frameworks for diverse respiratory pathogens, including SARS-CoV-2, Legionella spp., Staphylococcus aureus, influenza, and Bacillus anthracis. Six distinct exposure models were identified across diverse and complex transmission pathways. In 57 studies, exposure model frameworks were informed by their ability to model the efficacy of potential interventions. Among interventions, masking, ventilation, social distancing, and other environmental source controls were commonly assessed. Pathogen concentration, aerosol concentration, and partitioning coefficient were influential exposure parameters as identified by sensitivity analysis. Most (84%, n=78) studies presented policy-relevant content including a) determining disease burden to call for policy intervention, b) determining risk-based threshold values for regulations, c) informing intervention and control strategies, and d) making recommendations and suggestions for QMRA application in policy. CONCLUSIONS: We identified needs to further the development of QMRA frameworks for respiratory pathogens that prioritize appropriate aerosol exposure modeling approaches, consider trade-offs between model validity and complexity, and incorporate research that strengthens confidence in QMRA results. https://doi.org/10.1289/EHP12695.

Quantitative microbial risk assessment (QMRA) tool for modelling pathogen infection risk to wastewater treatment plant workers.

Wastewater treatment plants (WWTPs) provide vital services to the public by removing contaminants from wastewater prior to environmental discharge or reuse for beneficial purposes. WWTP workers occupationally exposed to wastewater can be at risk of respiratory or gastrointestinal diseases. The study objectives were to: (1) quantify pathogens and pathogen indicators in wastewater aerosols near different WWTP processes/unit operations, (2) develop a QMRA model for multi-pathogen and multi-exposure pathway risks, and (3) create a web-based application to perform and communicate risk calculations for wastewater workers. Case studies for seven different WWTP job tasks were performed investigating infection risk across nine different enteric and respiratory pathogens. It was observed that the ingestion risk among job tasks was highest for "walking the WWTP," which involved exposure from splashing, bioaerosols, and hand-to-mouth contact from touching contaminated surfaces. There was also a notable difference in exposure risk during peak (5:00am-9:00am) and non-peak hours (9:00am- 5:00am), with risks during the peak flow hours of the early morning assumed to be 5 times greater than non-peak hours. N95 respirator usage reduced median respiratory risks by 77 %. The developed tool performs multiple QMRA calculations to estimate WWTP workers' infection risks from accidental ingestion or inhalation of wastewater from multiple pathogens and exposure scenarios, which can inform risk management strategies to protect occupational health. However, more data are needed to reduce uncertainty in model estimates, including comparative data for pathogen concentrations in wastewater during peak and non-peak hours. QMRA tools will increase accessibility of risk models for utilization in decision-making.

Site-specific risk-based threshold (RBT) concentrations for sewage-associated markers in estuarine swimming waters.

This study establishes site-specific risk-based threshold (RBT) concentrations for sewage-associated markers, including Bacteroides HF183 (HF183), Lachnospiraceae Lachno3 (Lachno3), cross-assembly phage (CrAssphage), and pepper mild mottle virus (PMMoV), utilizing quantitative microbial risk assessment (QMRA) for recreational estuarine waters (EW). The QMRA model calculates a RBT concentration corresponding to a selected target illness risk for ingestion of EW contaminated with untreated sewage. RBT concentrations were estimated considering site-specific decay rates and concentrations of markers and reference pathogen (human norovirus; HNoV), aiding in the identification of high-risk days during the swimming season. Results indicated varying RBT concentrations for fresh (Day 0) and aged (Days 1 to 10) sewage contamination scenarios over 10 days. HF183 exhibited the highest RBT concentration (26,600 gene copis (GC)/100 mL) initially but decreased rapidly with aging (2570 to 3120 GC/100 mL on Day 10) depending on the decay rates, while Lachno3 and CrAssphage remained relatively stable. PMMoV, despite lower initial RBT (3920 GC/100 mL), exhibited increased RBT (4700 to 6440 GC/100 mL) with aging due to its slower decay rate compared to HNoV. Sensitivity analysis revealed HNoV concentrations as the most influential parameter. Comparison of marker concentrations in estuarine locations with RBT concentrations showed instances of marker exceedance, suggesting days of potential higher risks. The observed discrepancies between bacterial and viral marker concentrations in EW highlight the need for optimized sample concentration method and simultaneous measurement of multiple markers for enhanced risk predictions. Future research will explore the utility of multiple markers in risk management. Overall, this study contributes to better understanding human health risks in recreational waters, aiding regulators, and water quality managers in effective decision-making for risk prioritization and mitigation strategies.

A microbial risk assessor's guide to Valley Fever (Coccidioides spp.): Case study and review of risk factors.

Valley Fever is a respiratory disease caused by inhalation of arthroconidia, a type of spore produced by fungi within the genus Coccidioides spp. which are found in dry, hot ecosystems of the Western Hemisphere. A quantitative microbial risk assessment (QMRA) for the disease has not yet been performed due to a lack of dose-response models and a scarcity of quantitative occurrence data from environmental samples. A literature review was performed to gather data on experimental animal dosing studies, environmental occurrence, human disease outbreaks, and meteorological associations. As a result, a risk framework is presented with information for parameterizing QMRA models for Coccidioides spp., with eight new dose-response models proposed. A probabilistic QMRA was conducted for a Southwestern US agricultural case study, evaluating eight scenarios related to farming occupational exposures. Median daily workday risks for developing severe Valley Fever ranged from 2.53 × 10-7 (planting by hand while wearing an N95 facemask) to 1.33 × 10-3 (machine harvesting while not wearing a facemask). The literature review and QMRA synthesis confirmed that exposure to aerosolized arthroconidia has the potential to result in high attack rates but highlighted that the mechanistic relationships between environmental conditions and disease remain poorly understood. Recommendations for Valley Fever risk assessment research needs in order to reduce disease risks are discussed, including interventions for farmers.

Mitigating risks and maximizing sustainability of treated wastewater reuse for irrigation.

Scarcity of freshwater for agriculture has led to increased utilization of treated wastewater (TWW), establishing it as a significant and reliable source of irrigation water. However, years of research indicate that if not managed adequately, TWW may deleteriously affect soil functioning and plant productivity, and pose a hazard to human and environmental health. This review leverages the experience of researchers, stakeholders, and policymakers from Israel, the United-States, and Europe to present a holistic, multidisciplinary perspective on maximizing the benefits from municipal TWW use for irrigation. We specifically draw on the extensive knowledge gained in Israel, a world leader in agricultural TWW implementation. The first two sections of the work set the foundation for understanding current challenges involved with the use of TWW, detailing known and emerging agronomic and environmental issues (such as salinity and phytotoxicity) and public health risks (such as contaminants of emerging concern and pathogens). The work then presents solutions to address these challenges, including technological and agronomic management-based solutions as well as source control policies. The concluding section presents suggestions for the path forward, emphasizing the importance of improving links between research and policy, and better outreach to the public and agricultural practitioners. We use this platform as a call for action, to form a global harmonized data system that will centralize scientific findings on agronomic, environmental and public health effects of TWW irrigation. Insights from such global collaboration will help to mitigate risks, and facilitate more sustainable use of TWW for food production in the future.

Tenets of a holistic approach to drinking water-associated pathogen research, management, and communication.

In recent years, drinking water-associated pathogens that can cause infections in immunocompromised or otherwise susceptible individuals (henceforth referred to as DWPI), sometimes referred to as opportunistic pathogens or opportunistic premise plumbing pathogens, have received considerable attention. DWPI research has largely been conducted by experts focusing on specific microorganisms or within silos of expertise. The resulting mitigation approaches optimized for a single microorganism may have unintended consequences and trade-offs for other DWPI or other interests (e.g., energy costs and conservation). For example, the ecological and epidemiological issues characteristic of Legionella pneumophila diverge from those relevant for Mycobacterium avium and other nontuberculous mycobacteria. Recent advances in understanding DWPI as part of a complex microbial ecosystem inhabiting drinking water systems continues to reveal additional challenges: namely, how can all microorganisms of concern be managed simultaneously? In order to protect public health, we must take a more holistic approach in all aspects of the field, including basic research, monitoring methods, risk-based mitigation techniques, and policy. A holistic approach will (i) target multiple microorganisms simultaneously, (ii) involve experts across several disciplines, and (iii) communicate results across disciplines and more broadly, proactively addressing source water-to-customer system management.

Quantitative microbial risk assessment of outdoor aerosolized pathogens in cities with poor sanitation.

The aeromicrobiological transmission pathway of enteric pathogens in places with unsafe sanitation services is poorly understood. In an attempt to partly fill this knowledge gap, we assessed the potential public health impact of bioaerosols near open waste canals (OWCs) using Quantitative Microbial Risk Assessment (QMRA). We used data acquired in La Paz, Bolivia to characterize the risk of disease that aerosolized enteric pathogens may pose through food, fomites and inhalation (all followed by ingestion). Three reference pathogens were selected to conduct the assessment: enterotoxigenic Escherichia coli (ETEC), Shigella flexneri, and Campylobacter jejuni. Inhalation followed by ingestion had the highest median infection risk per event i.e. 3 × 10-5 (3 infections for every 100,000 exposures), compared to contaminated food e.g. 5 × 10-6 and fomites e.g. 2 × 10-7, all for C. jejuni infections. Our sensitivity analysis showed that bacterial fluxes from the air were the most influential factor on risk. Our results suggest that fecal bacterial aerosols from OWCs present non-negligible risks of infection in La Paz, with median annual infection risks by C. jejuni being 18 (food), and 100 (inhalation) times greater than the EPA's standard for drinking water (1 × 10-4). We included two of the QMRA models presented here in a novel web application we developed for user-specified application in different contexts.

Minimizing errors in RT-PCR detection and quantification of SARS-CoV-2 RNA for wastewater surveillance.

Wastewater surveillance for pathogens using reverse transcription-polymerase chain reaction (RT-PCR) is an effective and resource-efficient tool for gathering community-level public health information, including the incidence of coronavirus disease-19 (COVID-19). Surveillance of Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2) in wastewater can potentially provide an early warning signal of COVID-19 infections in a community. The capacity of the world's environmental microbiology and virology laboratories for SARS-CoV-2 RNA characterization in wastewater is increasing rapidly. However, there are no standardized protocols or harmonized quality assurance and quality control (QA/QC) procedures for SARS-CoV-2 wastewater surveillance. This paper is a technical review of factors that can cause false-positive and false-negative errors in the surveillance of SARS-CoV-2 RNA in wastewater, culminating in recommended strategies that can be implemented to identify and mitigate some of these errors. Recommendations include stringent QA/QC measures, representative sampling approaches, effective virus concentration and efficient RNA extraction, PCR inhibition assessment, inclusion of sample processing controls, and considerations for RT-PCR assay selection and data interpretation. Clear data interpretation guidelines (e.g., determination of positive and negative samples) are critical, particularly when the incidence of SARS-CoV-2 in wastewater is low. Corrective and confirmatory actions must be in place for inconclusive results or results diverging from current trends (e.g., initial onset or reemergence of COVID-19 in a community). It is also prudent to perform interlaboratory comparisons to ensure results' reliability and interpretability for prospective and retrospective analyses. The strategies that are recommended in this review aim to improve SARS-CoV-2 characterization and detection for wastewater surveillance applications. A silver lining of the COVID-19 pandemic is that the efficacy of wastewater surveillance continues to be demonstrated during this global crisis. In the future, wastewater should also play an important role in the surveillance of a range of other communicable diseases.

Antibiotic Resistance and Sewage-Associated Marker Genes in Untreated Sewage and a River Characterized During Baseflow and Stormflow.

Since sewage is a hotspot for antibiotic resistance genes (ARGs), the identification of ARGs in environmental waters impacted by sewage, and their correlation to fecal indicators, is necessary to implement management strategies. In this study, sewage treatment plant (STP) influent samples were collected and analyzed using quantitative polymerase chain reaction (qPCR) to investigate the abundance and correlations between sewage-associated markers (i.e., Bacteroides HF183, Lachnospiraceae Lachno3, crAssphage) and ARGs indicating resistance to nine antibiotics (belonging to aminoglycosides, beta-lactams, sulfonamides, macrolides, and tetracyclines). All ARGs, except bla VIM, and sewage-associated marker genes were always detected in untreated sewage, and ermF and sul1 were detected in the greatest abundances. intl1 was also highly abundant in untreated sewage samples. Significant correlations were identified between sewage-associated marker genes, ARGs and the intl1 in untreated sewage (τ = 0.488, p = 0.0125). Of the three sewage-associated marker genes, the BIO-ENV procedure identified that HF183 alone best maximized correlations to ARGs and intl1 (τ = 0.590). Additionally, grab samples were collected from peri-urban and urban sites along the Brisbane River system during base and stormflow conditions, and analyzed for Escherichia coli, ARGs, the intl1, and sewage-associated marker genes using quantitative polymerase chain reaction (qPCR). Significant correlations were identified between E. coli, ARGs, and intl1 (τ = 0.0893, p = 0.0032), as well as with sewage-associated marker genes in water samples from the Brisbane River system (τ = 0.3229, p = 0.0001). Of the sewage-associated marker genes and E. coli, the BIO-ENV procedure identified that crAssphage alone maximized correlations with ARGs and intl1 in river samples (τ = 0.4148). Significant differences in E. coli, ARGs, intl1, and sewage-associated marker genes, and by flow condition (i.e., base vs. storm), and site types (peri-urban vs. urban) combined were identified (R = 0.3668, p = 0.0001), where percent dissimilarities between the multi-factorial groups ranged between 20.8 and 11.2%. Results from this study suggest increased levels of certain ARGs and sewage-associated marker genes in stormflow river water samples compared to base flow conditions. E. coli, HF183 and crAssphage may serve as potential indicators of sewage-derived ARGs under stormflow conditions, and this merits further investigation. Data presented in this study will be valuable to water quality managers to understand the links between sewage pollution and ARGs in urban environments.