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.

Monitoring SARS-CoV-2 Circulation and Diversity through Community Wastewater Sequencing, the Netherlands and Belgium.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has rapidly become a major global health problem, and public health surveillance is crucial to monitor and prevent virus spread. Wastewater-based epidemiology has been proposed as an addition to disease-based surveillance because virus is shed in the feces of ≈40% of infected persons. We used next-generation sequencing of sewage samples to evaluate the diversity of SARS-CoV-2 at the community level in the Netherlands and Belgium. Phylogenetic analysis revealed the presence of the most prevalent clades (19A, 20A, and 20B) and clustering of sewage samples with clinical samples from the same region. We distinguished multiple clades within a single sewage sample by using low-frequency variant analysis. In addition, several novel mutations in the SARS-CoV-2 genome were detected. Our results illustrate how wastewater can be used to investigate the diversity of SARS-CoV-2 viruses circulating in a community and identify new outbreaks.

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.

Changes in biofilm composition and microbial water quality in drinking water distribution systems by temperature increase induced through thermal energy recovery.

Drinking water distribution systems (DWDSs) have been thoroughly studied, but the concept of thermal energy recovery from DWDSs is very new and has been conceptualized in the past few years. Cold recovery results in a temperature increase of the drinking water. Its effects on drinking water quality and biofilm development are unclear. Hence, we studied both bulk water and biofilm phases for 232 days in two parallel pilot scale distribution systems with two temperature settings after cold recovery, 25 °C and 30 °C, and compared these with a reference pilot system without cold recovery. In all three pilot distributions systems (DSs) our results showed an initial increase in biomass (ATP) in the biofilm phase, along with occurrence of primary colonizers (Betaproteobacteriales) and subsequently a decrease in biomass and an increasing relative abundance of other microbial groups (amoeba resisting groups; Xanthobacteraceae, Legionellales), including those responsible for EPS formation in biofilms (Sphingomonadaceae). The timeline for biofilm microbial development was different for the three pilot DSs: the higher the temperature, the faster the development took place. With respect to the water phase within the three pilot DSs, major microbial contributions came from the feed water (17-100%) and unkown sources (2-80%). Random contributions of biofilm (0-70%) were seen between day 7-77. During this time period six-fold higher ATP concentration (7-11 ng/l) and two-fold higher numbers of high nucleic acid cells (5.20-5.80 × 104 cells/ml) were also observed in the effluent water from all three pilot DSs, compared to the feed water. At the end of the experimental period the microbial composition of effluent water from three pilot DSs revealed no differences, except the presence of a biofilm related microbial group (Sphingomonadaceae), within all three DSs compared to the feed water. In the biofilm phase higher temperatures initiated the growth of primary colonizing bacteria but this did not lead to differences in microbial diversity and composition at the end of the experimental period. Hence, we propose that the microbiological water quality of DWDSs with cold recovery should be monitored more frequently during the first 2-3 months of operation.

Impact of Hydrometeorological Events for the Selection of Parametric Models for Protozoan Pathogens in Drinking-Water Sources.

Temporal variations in concentrations of pathogenic microorganisms in surface waters are well known to be influenced by hydrometeorological events. Reasonable methods for accounting for microbial peaks in the quantification of drinking water treatment requirements need to be addressed. Here, we applied a novel method for data collection and model validation to explicitly account for weather events (rainfall, snowmelt) when concentrations of pathogens are estimated in source water. Online in situ ß-d-glucuronidase activity measurements were used to trigger sequential grab sampling of source water to quantify Cryptosporidium and Giardia concentrations during rainfall and snowmelt events at an urban and an agricultural drinking water treatment plant in Quebec, Canada. We then evaluate if mixed Poisson distributions fitted to monthly sampling data ( n = 30 samples) could accurately predict daily mean concentrations during these events. We found that using the gamma distribution underestimated high Cryptosporidium and Giardia concentrations measured with routine or event-based monitoring. However, the log-normal distribution accurately predicted these high concentrations. The selection of a log-normal distribution in preference to a gamma distribution increased the annual mean concentration by less than 0.1-log but increased the upper bound of the 95% credibility interval on the annual mean by about 0.5-log. Therefore, considering parametric uncertainty in an exposure assessment is essential to account for microbial peaks in risk assessment.

Importance of Distributional Forms for the Assessment of Protozoan Pathogens Concentrations in Drinking-Water Sources.

The identification of appropriately conservative statistical distributions is needed to predict microbial peak events in drinking water sources explicitly. In this study, Poisson and mixed Poisson distributions with different upper tail behaviors were used for modeling source water Cryptosporidium and Giardia data from 30 drinking water treatment plants. Small differences (<0.5-log) were found between the "best" estimates of the mean Cryptosporidium and Giardia concentrations with the Poisson-gamma and Poisson-log-normal models. However, the upper bound of the 95% credibility interval on the mean Cryptosporidium concentrations of the Poisson-log-normal model was considerably higher (>0.5-log) than that of the Poisson-gamma model at four sites. The improper choice of a model may, therefore, mislead the assessment of treatment requirements and health risks associated with the water supply. Discrimination between models using the marginal deviance information criterion (mDIC) was unachievable because differences in upper tail behaviors were not well characterized with available data sets ( n<30 ). Therefore, the gamma and the log-normal distributions fit the data equally well but may predict different risk estimates when they are used as an input distribution in an exposure assessment. The collection of event-based monitoring data and the modeling of larger routine monitoring data sets are recommended to identify appropriately conservative distributions to predict microbial peak events.

360-Degree Distribution of Biofilm Quantity and Community in an Operational Unchlorinated Drinking Water Distribution Pipe.

In the present study, triplicate rings of 360° pipe surfaces of an operational drinking water distribution pipe were swabbed. Each ring was equally divided into 16 parts for swabbing. The collected swabs were grouped into 3 sections and compared with the biofilm samples sampled by sonication of specimens from the same pipe. The results showed that the biofilm is unevenly distributed over the 16 parts and the 3 sections of the pipe surface. Both the active biomass and the number of observed OTUs increased as the measurements proceeded from the top to the bottom of the pipe. The bacterial community was dominated in all sections by Proteobacteria. At the genus level, Nitrospira spp., Terrimonas spp., and Hyphomicrobium spp. were dominant in all sections. Gaiella spp. and Vicinamibacter spp. dominated in S-I, Blastopirellula spp. and Pirellula spp. dominated in S-II, while Holophaga spp. and Phaeodactylibacter spp. dominated in S-III. When swabbing and pipe specimen sonication were compared, the results showed that the sampling strategy significantly influences the obtained biofilm bacterial community. A consistent multisectional swabbing strategy is proposed for future biofilm sampling; it involves collecting swabs from all sections and comparing the swabs from the same position/section across locations.

Effects of cold recovery technology on the microbial drinking water quality in unchlorinated distribution systems.

Drinking water distribution systems (DWDSs) are used to supply hygienically safe and biologically stable water for human consumption. The potential of thermal energy recovery from drinking water has been explored recently to provide cooling for buildings. Yet, the effects of increased water temperature induced by this "cold recovery" on the water quality in DWDSs are not known. The objective of this study was to investigate the impact of cold recovery from DWDSs on the microbiological quality of drinking water. For this purpose, three pilot distribution systems were operated in parallel for 38 weeks. System 1 has an operational heat exchanger, mimicking the cold recovery system by maintaining the water temperature at 25 °C; system 2 operated with a non-operational heat exchanger and system 3 run without heat exchanger. The results showed no significant effects on drinking water quality: cell numbers and ATP concentrations remained around 3.5 × 105 cells/ml and 4 ng ATP/l, comparable observed operational taxonomic units (OTUs) (~470-490) and similar Shannon indices (7.7-8.9). In the system with cold recovery, a higher relative abundance of Pseudomonas spp. and Chryseobacterium spp. was observed in the drinking water microbial community, but only when the cold recovery induced temperature difference (ΔT) was higher than 9 °C. In the 38 weeks' old biofilm, higher ATP concentration (475 vs. 89 pg/cm2), lower diversity (observed OTUs: 88 vs. ≥200) and a different bacterial community composition (e.g. higher relative abundance of Novosphingobium spp.) were detected, which did not influence water quality. No impacts were observed for the selected opportunisitic pathogens after introducing cold recovery. It is concluded that cold recovery does not affect bacterial water quality. Further investigation for a longer period is commended to understand the dynamic responses of biofilm to the increased temperature caused by cold recovery.

Global Cryptosporidium Loads from Livestock Manure.

Understanding the environmental pathways of Cryptosporidium is essential for effective management of human and animal cryptosporidiosis. In this paper we aim to quantify livestock Cryptosporidium spp. loads to land on a global scale using spatially explicit process-based modeling, and to explore the effect of manure storage and treatment on oocyst loads using scenario analysis. Our model GloWPa-Crypto L1 calculates a total global Cryptosporidium spp. load from livestock manure of 3.2 × 1023 oocysts per year. Cattle, especially calves, are the largest contributors, followed by chickens and pigs. Spatial differences are linked to animal spatial distributions. North America, Europe, and Oceania together account for nearly a quarter of the total oocyst load, meaning that the developing world accounts for the largest share. GloWPa-Crypto L1 is most sensitive to oocyst excretion rates, due to large variation reported in literature. We compared the current situation to four alternative management scenarios. We find that although manure storage halves oocyst loads, manure treatment, especially of cattle manure and particularly at elevated temperatures, has a larger load reduction potential than manure storage (up to 4.6 log units). Regions with high reduction potential include India, Bangladesh, western Europe, China, several countries in Africa, and New Zealand.

Source tracking of Enterococcus moraviensis and E. haemoperoxidus.

Enterococci were detected occasionally in 100 L samples of water abstracted from a shallow aquifer in a natural dune infiltration area for drinking water production. Enterococcus moraviensis was the species most frequently identified in these samples. Because there are no existing reports of faecal sources of E. moraviensis and the closely related E. hemoperoxidus, this study aimed to find such sources of these two species in the dunes. Faecal samples from various animal species living in the vicinity of abstraction wells, were analysed for enterococci on Slanetz and Bartley Agar. From these samples, enterococci isolates (1,386 in total) were subsequently identified using matrix assisted laser desorption ionization-time of flight (MALDI-TOF) mass spectrometry. E. moraviensis was found in the faeces of geese, foxes and rabbits. Also, E. haemoperoxidus was isolated from goose faeces. Using hierarchical clustering, the species composition of Enterococcus spp. isolated from abstracted water formed one cluster with the species composition found in geese droppings. A sanitary survey supported the indication that feral geese may provide a substantial faecal load in particular parts of this dune infiltration area, close to the water abstraction system. This study confirms the faecal origin of E. moraviensis and E. haemoperoxidus from specific animals, which strengthens their significance as faecal indicators.

Quantification of waterborne pathogens and associated health risks in urban water.

Citizens are exposed to microbial hazards in urban waters. To quantify health risks associated with this exposure, pathogen concentrations in an urban river, lake, rainwater sedimentation pond, a pond in a park, and a wadi, were assessed. E. coli concentrations were variable in all locations, with mean values ranging between 1.2 × 10(2) (lake) and 1.7 × 10(4) (sedimentation pond) cfu (colony forming units)/100 mL. High concentrations of Campylobacter were found, being the lowest in the lake (4.2 × 10(1) gc (genomic copies)/L) and the highest in the wadi (1.7 × 10(4) gc/L). Cryptosporidium was not found in any sample. Low levels of adenovirus 40/41 were found in some samples in the river (1.8 × 10(1) gc/L) and lake (7.2 × 10° gc/L), indicating human fecal contamination. Legionella pneumophila was found in the sedimentation pond, with higher concentrations after rain events (1.3 × 10(2) gc/L). Cyanochlorophyll-a was found in the lake (7.0 × 10(-1) µg/L), the sedimentation pond (1.1 × 10° µg/L), and the pond in the park (2.9 × 10(1) µg/L), where low levels of microcystin were found (2.1 × 10° µg/L). Campylobacter data were used to estimate gastrointestinal risks from recreational exposure. This revealed risks above the annual disease incidence of campylobacteriosis in The Netherlands, being highest in the wadi and river. Measures are proposed to reduce the health risks.

Screening-level microbial risk assessment of urban water locations: a tool for prioritization.

People in urban areas are exposed to microbial hazards in urban waters. In this study, various hazards, diseases, and water systems, where different recreation activities take place, are compared in an integrated quantitative microbial risk assessment (QMRA). The event and annual probability of gastrointestinal illness (GI) and Legionnaires'disease (LD) were analyzed in QMRA models using selected literature data. Highest mean event probabilities of GI were found for playing in pluvial flood from a combined sewer overflow (34%), swimming (18%), and rowing (13%) in the river, swimming (8.7%) and rowing (4.5%) in the lake, and playing in a water playground (3.7%) and in the pluvial flood from stormwater sewers (4.7%). At these locations, the GI probability was above the EU Bathing Water Directive threshold for excellent water quality (3%). All the annual risk medians were below the national incidence of legionellosis of 0.002%. The illness probability was most sensitive to the pathogens concentration (particularly Campylobacter, Norovirus, and Legionella) and exposure frequency. Therefore, site-specific pathogen data collection is the best next step to strengthen the certainty of the risk estimates. This study created an evidence-base that was used by water authorities to understand the health risks and set priorities for risk management.

A new Bayesian approach for managing bathing water quality at river bathing locations vulnerable to short-term pollution.

Short-term fecal pollution events are a major challenge for managing microbial safety at recreational waters. Long turn-over times of current laboratory methods for analyzing fecal indicator bacteria (FIB) delay water quality assessments. Data-driven models have been shown to be valuable approaches to enable fast water quality assessments. However, a major barrier towards the wider use of such models is the prevalent data scarcity at existing bathing waters, which questions the representativeness and thus usefulness of such datasets for model training. The present study explores the ability of five data-driven modelling approaches to predict short-term fecal pollution episodes at recreational bathing locations under data scarce situations and imbalanced datasets. The study explicitly focuses on the potential benefits of adopting an innovative modeling and risk-based assessment approach, based on state/cluster-based Bayesian updating of FIB distributions in relation to different hydrological states. The models are benchmarked against commonly applied supervised learning approaches, particularly linear regression, and random forests, as well as to a zero-model which closely resembles the current way of classifying bathing water quality in the European Union. For model-based clustering we apply a non-parametric Bayesian approach based on a Dirichlet Process Mixture Model. The study tests and demonstrates the proposed approaches at three river bathing locations in Germany, known to be influenced by short-term pollution events. At each river two modelling experiments ("longest dry period", "sequential model training") are performed to explore how the different modelling approaches react and adapt to scarce and uninformative training data, i.e., datasets that do not include event pollution information in terms of elevated FIB concentrations. We demonstrate that it is especially the proposed Bayesian approaches that are able to raise correct warnings in such situations (> 90 % true positive rate). The zero-model and random forest are shown to be unable to predict contamination episodes if pollution episodes are not present in the training data. Our research shows that the investigated Bayesian approaches reduce the risk of missed pollution events, thereby improving bathing water safety management. Additionally, the approaches provide a transparent solution for setting minimum data quality requirements under various conditions. The proposed approaches open the way for developing data-driven models for bathing water quality prediction against the reality that data scarcity is common problem at existing and prospective bathing waters.

Qualitative detection of E. coli in distributed drinking water using real-time reverse transcription PCR targeting 16S rRNA: Validation and practical experiences.

Escherichia coli (E. coli) plays a central role as an indicator for fecal contamination to predict the possible presence of microbial pathogens in drinking water. Current detection methods for E. coli are based on time-consuming culture-based techniques. There is a strong need for methods to detect fecal contamination rapidly in distributed drinking water to prevent outbreaks of waterborne disease and support water utilities to efficiently manage their operations like actions to repair or maintain distribution pipes, to minimize impact on consumers. This study describes the validation and application of a qualitative real time reverse transcription PCR (RT-PCR) method targeting 16S ribosomal RNA (rRNA) for rapid detection of E. coli in distributed drinking water. The RT-PCR assay targets 16S rRNA, a highly abundant RNA in viable cells, enabling robust detection at the required sensitivity of 1 CFU/100 ml. The validation was performed by comparing the RT-PCR method with the culture-based chromogenic reference method (CCA) using the protocol and criteria described in ISO 16,140-2:2016. The validation demonstrated that this RT-PCR method can be used to specifically detect E. coli in a broad range of drinking water samples with at least the same limit of detection as the culture method (Relative Limit Of Detection = 0.75, range 0.43-1.43). The inclusivity study showed that the RT-PCR method was able to detect a broad range of E. coli strains derived from different sources and geographic areas, including pathogenic serotype O157 strains that are not detected with the culture method. The exclusivity study determined that other bacterial genera are not detected with this RT-PCR. However, Escherichia fergusonii was detected and, based on "in silico" analysis, it is expected that also E. albertii and E. marmotae and Shigella species will be detectable using this RT-PCR. An interlaboratory study confirmed that the RT-PCR and culture method have comparable sensitivities when tested by different participants at different laboratories. The application of RT-PCR to confirm the hygienic quality of distributed drinking water after actions to repair or maintain distribution pipes was compared with the culture method on 8076 routine samples, analyzed by the drinking water laboratories in the Netherlands. This comparison study showed a 96.4 % agreement between RT-PCR and culture. In 3.3 % of the samples E. coli was detected with RT-PCR and not with the culture method and in 0.1 % of the samples E. coli was only detected by culture confirming either a higher sensitivity for RT-PCR or the detection of RNA from uncultivable cells. Finally, the application of RT-PCR was highlighted during a contamination event in Belgium where we demonstrate the potency of RT-PCR as a tool to rapidly monitor the spread of microbial contamination and to monitor the effect of measures to remove the contamination This is the first fully validated rapid nucleic based method for detection of E. coli in distributed drinking water. These results demonstrate that this RT-PCR method can be used as a rapid alternative to the culture method to monitor E. coli in distributed drinking water. However, it should be emphasized that nucleic acid based detection methods rely on highly different detection principles (detection of captured nucleic acids present in a sample) than culture base methods (presence of cells cultivable on a selective medium) resulting in occasional different analysis results. Varying treatment and disinfection steps (UV, chlorine, monochloramine, Ozone) or environmental factors (decay) can influence the results and cause differences between RT-PCR and culture methods.

Assessing environmental exposure to viruses in wastewater treatment plant and swine farm scenarios with next-generation sequencing and occupational risk approaches.

Occupational exposure to pathogens can pose health risks. This study investigates the viral exposure of workers in a wastewater treatment plant (WWTP) and a swine farm by analyzing aerosol and surfaces samples. Viral contamination was evaluated using quantitative polymerase chain reaction (qPCR) assays, and target enrichment sequencing (TES) was performed to identify the vertebrate viruses to which workers might be exposed. Additionally, Quantitative Microbial Risk Assessment (QMRA) was conducted to estimate the occupational risk associated with viral exposure for WWTP workers, choosing Human Adenovirus (HAdV) as the reference pathogen. In the swine farm, QMRA was performed as an extrapolation, considering a hypothetical zoonotic virus with characteristics similar to Porcine Adenovirus (PAdV). The modelled exposure routes included aerosol inhalation and oral ingestion through contaminated surfaces and hand-to-mouth contact. HAdV and PAdV were widespread viruses in the WWTP and the swine farm, respectively, by qPCR assays. TES identified human and other vertebrate viruses WWTP samples, including viruses from families such as Adenoviridae, Circoviridae, Orthoherpesviridae, Papillomaviridae, and Parvoviridae. In the swine farm, most of the identified vertebrate viruses were porcine viruses belonging to Adenoviridae, Astroviridae, Circoviridae, Herpesviridae, Papillomaviridae, Parvoviridae, Picornaviridae, and Retroviridae. QMRA analysis revealed noteworthy risks of viral infections for WWTP workers if safety measures are not taken. The probability of illness due to HAdV inhalation was higher in summer compared to winter, while the greatest risk from oral ingestion was observed in workspaces during winter. Swine farm QMRA simulation suggested a potential occupational risk in the case of exposure to a hypothetical zoonotic virus. This study provides valuable insights into WWTP and swine farm worker's occupational exposure to human and other vertebrate viruses. QMRA and NGS analyses conducted in this study will assist managers in making evidence-based decisions, facilitating the implementation of protection measures, and risk mitigation practices for workers.

Bacterial communities of planktonic bacteria and mature biofilm in service lines and premise plumbing of a Megacity: Composition, Diversity, and influencing factors.

Although simulated studies have provided valuable knowledge regarding the communities of planktonic bacteria and biofilms, the lack of systematic field studies have hampered the understanding of microbiology in real-world service lines and premise plumbing. In this study, the bacterial communities of water and biofilm were explored, with a special focus on the lifetime development of biofilm communities and their key influencing factors. The 16S rRNA gene sequencing results showed that both the planktonic bacteria and biofilm were dominated by Proteobacteria. Among the 15,084 observed amplicon sequence variants (ASVs), the 33 core ASVs covered 72.8 %, while the 12 shared core ASVs accounted for 62.2 % of the total sequences. Remarkably, it was found that the species richness and diversity of biofilm communities correlated with pipe age. The relative abundance of ASV2 (f_Sphingomonadaceae) was lower for pipe ages 40-50 years (7.9 %) than for pipe ages 10-20 years (59.3 %), while the relative abundance of ASV10 (f_Hyphomonadaceae) was higher for pipe ages 40-50 years (19.5 %) than its presence at pipe ages 20-30 years (1.9 %). The community of the premise plumbing biofilm had significantly higher species richness and diversity than that of the service line, while the steel-plastics composite pipe interior lined with polyethylene (S-PE) harbored significantly more diverse biofilm than the galvanized steel pipes (S-Zn). Interestingly, S-PE was enriched with ASV27 (g_Mycobacterium), while S-Zn pipes were enriched with ASV13 (g_Pseudomonas). Moreover, the network analysis showed that five rare ASVs, not core ASVs, were keystone members in biofilm communities, indicating the importance of rare members in the function and stability of biofilm communities. This manuscript provides novel insights into real-world service lines and premise plumbing microbiology, regarding lifetime dynamics (pipe age 10-50 years), and the influences of pipe types (premise plumbing vs. service line) and pipe materials (S-Zn vs. S-PE).

Enhanced virus inactivation by copper and silver ions in the presence of natural organic matter in water.

Natural organic matter (NOM) is present in water matrix that serves as a drinking water source. This study examined the effect of low and high NOM concentrations on inactivation kinetics of a model RNA virus (MS2) and a model DNA virus (PhiX 174) by copper (Cu2+) and/or silver (Ag+) ions. Cu and Ag are increasingly applied in household water treatment (HHWT) systems. However, the impact of NOM on their inactivation kinetics remains elusive despite its importance for their application. The presence of NOM in water led to faster virus inactivation by Cu2+ but slower by Ag+. The fastest inactivation kinetics of MS2 (Kobs = 4.8 h-1) were observed by Cu in water containing high NOM (20 mg C/L). Meanwhile, for PhiX 174, the fastest inactivation kinetics (av. Kobs = 3.5 h-1) were observed by Cu and Ag synergism in water containing high NOM. Altogether, it can be concluded that the combination of Cu and Ag is promising as a virus disinfectant in treatment options allowing for multiple hours of residence time such as safe water storage tanks.

New RT-PCR Assay for the Detection of Current and Future SARS-CoV-2 Variants.

Multiple lineages of SARS-CoV-2 have been identified featuring distinct sets of genetic changes that confer to the virus higher transmissibility and ability to evade existing immunity. The continuous evolution of SARS-CoV-2 may pose challenges for current treatment options and diagnostic tools. In this study, we have first evaluated the performance of the 14 WHO-recommended real-time reverse transcription (RT)-PCR assays currently in use for the detection of SARS-CoV-2 and found that only one assay has reduced performance against Omicron. We then developed a new duplex real-time RT-PCR assay based on the amplification of two ultra-conserved elements present within the SARS-CoV-2 genome. The new duplex assay successfully detects all of the tested SARS-CoV-2 variants of concern (including Omicron sub-lineages BA.4 and BA.5) from both clinical and wastewater samples with high sensitivity and specificity. The assay also functions as a one-step droplet digital RT-PCR assay. This new assay, in addition to clinical testing, could be adopted in surveillance programs for the routine monitoring of SARS-CoV-2's presence in a population in wastewater samples. Positive results with our assay in conjunction with negative results from an Omicron-specific assay may provide timely indication of the emergence of a novel SARS-CoV-2 variant in a certain community and thereby aid public health interventions.