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.

Association between the number of symptomatic mpox cases and the detection of mpox virus DNA in wastewater in Switzerland: an observational surveillance study.

AIM OF THE STUDY: The COVID-19 pandemic has drawn attention to the benefit of wastewater-based epidemiology, particularly when case numbers are underreported. Underreporting may be an issue with mpox, where biological reasons and stigma may prevent patients from getting tested. Therefore, we aimed to assess the validity of wastewater surveillance for monitoring mpox virus DNA in wastewater of a Central European city and its association with official case numbers. METHODS: Wastewater samples were collected between 1 July and 28 August 2022 in the catchment area of Basel, Switzerland, and the number of mpox virus genome copies they contained was determined by real-time quantitative PCR. Logistic regression analyses were used to determine the odds of detectability of mpox virus DNA in wastewater, categorised as detectable or undetectable. Mann-Whitney U tests were used to determine associations between samples that tested positive for the mpox virus and officially reported cases and patients' recorded symptomatic phases. RESULTS: Mpox virus DNA was detected in 15 of 39 wastewater samples. The number of positive wastewater samples was associated with the number of symptomatic cases (odds ratio [OR] = 2.18, 95% confidence interval (CI) = 1.38-3.43, p = 0.001). The number of symptomatic cases differed significantly between days with positive versus negative wastewater results (median = 11 and 8, respectively, p = 0.0024). CONCLUSION: Mpox virus DNA was detectable in wastewater, even when officially reported case numbers were low (0-3 newly reported mpox cases corresponding to 6-12 symptomatic patients). Detectability in wastewater was significantly associated with the number of symptomatic patients within the catchment area. These findings illustrate the value of wastewater-based surveillance systems when assessing the prevalence of emerging and circulating infectious diseases.

Monitoring ESBL-Escherichia coli in Swiss wastewater between November 2021 and November 2022: insights into population carriage.

Antimicrobial resistance (AMR) poses a global health threat, causing millions of deaths annually, with expectations of increased impact in the future. Wastewater surveillance offers a cost-effective, non-invasive tool to understand AMR carriage trends within a population. We monitored extended-spectrum ß-lactamase producing Escherichia coli (ESBL-E. coli) weekly in influent wastewater from six wastewater treatment plants (WWTPs) in Switzerland (November 2021 to November 2022) to investigate spatio-temporal variations, explore correlations with environmental variables, develop a predictive model for ESBL-E. coli carriage in the community, and detect the most prevalent ESBL-genes. We cultured total and ESBL-E. coli in 300 wastewater samples to quantify daily loads and percentage of ESBL-E. coli. Additionally, we screened 234 ESBL-E. coli isolates using molecular methods for the presence of 18 ESBL-gene families. We found a population-weighted mean percentage of ESBL-E. coli of 1.9% (95% confidence interval: 1.8-2%) across all sites and weeks, which can inform ESBL-E. coli carriage. Concentrations of ESBL-E. coli varied across WWTPs and time, with higher values observed in WWTPs serving larger populations. Recent precipitations (previous 24/96 h) showed no significant association with ESBL-E. coli, while temperature occasionally had a moderate impact (P < 0.05, correlation coefficients approximately 0.40) in some locations. We identified blaCTX-M-1, blaCTX-M-9, and blaTEM as the predominant ESBL-gene families. Our study demonstrates that wastewater-based surveillance of culturable ESBL-E. coli provides insights into AMR trends in Switzerland and may also inform resistance. These findings establish a foundation for long term, nationally established monitoring protocols and provide information that may help inform targeted public health interventions. IMPORTANCE: Antimicrobial resistance (AMR) is a global health threat and is commonly monitored in clinical settings, given its association with the risk of antimicrobial-resistant infections. Nevertheless, tracking AMR within a community proves challenging due to the substantial sample size required for a representative population, along with high associated costs and privacy concerns. By investigating high resolution temporal and geographic trends in extended-spectrum beta-lactamase producing Escherichia coli in wastewater, we provide an alternative approach to monitor AMR dynamics, distinct from the conventional clinical settings focus. Through this approach, we develop a mechanistic model, shedding light on the relationship between wastewater indicators and AMR carriage in the population. This perspective contributes valuable insights into trends of AMR carriage, emphasizing the importance of wastewater surveillance in informing effective public health interventions.

Influenza transmission dynamics quantified from RNA in wastewater in Switzerland.

INTRODUCTION: Influenza infections are challenging to monitor at the population level due to many mild and asymptomatic cases and similar symptoms to other common circulating respiratory diseases, including COVID-19. Methods for tracking cases outside of typical reporting infrastructure could improve monitoring of influenza transmission dynamics. Influenza shedding into wastewater represents a promising source of information where quantification is unbiased by testing or treatment-seeking behaviours. METHODS: We quantified influenza A and B virus loads from influent at Switzerland's three largest wastewater treatment plants, serving about 14% of the Swiss population (1.2 million individuals). We estimated trends in infection incidence and the effective reproductive number (Re) in these catchments during a 2021/22 epidemic and compared our estimates to typical influenza surveillance data. RESULTS: Wastewater data captured the same overall trends in infection incidence as laboratory-confirmed case data at the catchment level. However, the wastewater data were more sensitive in capturing a transient peak in incidence in December 2021 than the case data. The Re estimated from the wastewater data was roughly at or below the epidemic threshold of 1 during work-from-home measures in December 2021 but increased to at or above the epidemic threshold in two of the three catchments after the relaxation of these measures. The third catchment yielded qualitatively the same results but with wider confidence intervals. The confirmed case data at the catchment level yielded comparatively less precise R_e estimates before and during the work-from-home period, with confidence intervals that included one before and during the work-from-home period. DISCUSSION: Overall, we show that influenza RNA in wastewater can help monitor nationwide influenza transmission dynamics. Based on this research, we developed an online dashboard for ongoing wastewater-based influenza surveillance in Switzerland.

Portable BLAST-like algorithm library and its implementations for command line, Python, and R.

Basic local-alignment search tool (BLAST) is a versatile and commonly used sequence analysis tool in bioinformatics. BLAST permits fast and flexible sequence similarity searches across nucleotide and amino acid sequences, leading to diverse applications such as protein domain identification, orthology searches, and phylogenetic annotation. Most BLAST implementations are command line tools which produce output as comma-separated values files. However, a portable, modular and embeddable implementation of a BLAST-like algorithm, is still missing from our toolbox. Here we present nsearch, a command line tool and C++11 library which provides BLAST-like functionality that can easily be embedded in any application. As an example of this portability we present Blaster which leverages nsearch to provide native BLAST-like functionality for the R programming language, as well as npysearch which provides similar functionality for Python. These packages permit embedding BLAST-like functionality into larger frameworks such as Shiny or Django applications. Benchmarks show that nsearch, npysearch, and Blaster are comparable in speed and accuracy to other commonly used modern BLAST implementations such as VSEARCH and BLAST+. We envision similar implementations of nsearch for other languages commonly used in data science such as Julia to facilitate sequence similarity comparisons. Nsearch, Blaster and npysearch are free to use under the BSD 3.0 license and available on Github Conda, CRAN (Blaster) and PyPi (npysearch).

Correction: Effects of chronic exposure to arsenic on the fecal carriage of antibiotic-resistant Escherichia coli among people in rural Bangladesh.

[This corrects the article DOI: 10.1371/journal.ppat.1010952.].

Sensor setpoints that ensure compliance with microbial water quality targets for membrane bioreactor and chlorination treatment in on-site water reuse systems.

Widespread implementation of on-site water reuse systems is hindered by the limited ability to ensure the level of treatment and protection of human health during operation. In this study, we tested the ability of five commercially available online sensors (free chlorine (FC), oxidation-reduction potential (ORP), pH, turbidity, UV absorbance at 254 nm) to predict the microbial water quality in membrane bioreactors followed by chlorination using logistic regression-based and mechanism-based models. The microbial water quality was assessed in terms of removal of enteric bacteria from the wastewater, removal of enteric viruses, and regrowth of bacteria in the treated water. We found that FC and ORP alone could predict the microbial water quality well, with ORP-based models generally performing better. We further observed that prediction accuracy did not increase when data from multiple sensors were integrated. We propose a methodology to link online sensor measurements to risk-based water quality targets, providing operation setpoints protective of human health for specific combinations of wastewaters and reuse applications. For instance, we recommend a minimum ORP of 705 mV to ensure a virus log-removal of 5, and an ORP of 765 mV for a log-removal of 6. These setpoints were selected to ensure that the percentage of events where the water is predicted to meet the quality target but it does not remains below 5%. Such a systematic approach to set sensor setpoints could be used in the development of water reuse guidelines and regulations that aim to cover a range of reuse applications with differential risks to human health.

Defining Risk-Based Monitoring Frequencies to Verify the Performance of Water Treatment Barriers.

Preventing failures of water treatment barriers can play an important role in meeting the increasing demand for microbiologically safe water. The development and integration of failure prevention strategies into quantitative microbial risk assessment (QMRA) offer opportunities to support the design and operation of treatment trains. This study presents existing failure models and extends them to guide the development of risk-based operational monitoring strategies. For barriers with rapid performance loss, results show that a failure of 15 s should be reliably detected to verify a log reduction value (LRV) of 6.0; thus, detecting and remediating these failures may be beyond current technology. For chemical disinfection with a residual, failure durations in order of minutes should be reliably detected to verify a LRV of 6.0. Short-term failures are buffered because the disinfectant residual concentration sustains a partial reduction performance. Therefore, increasing the contact time and hydraulic mixing reduces the impact of failures. These findings demonstrate the importance of defining precise frequencies to monitor barrier performances during operation. Overall, this study highlights the utility of process-specific models for developing failure prevention strategies for water safety management.

Legionnaires' disease in Switzerland: rationale and study protocol of a prospective national case-control and molecular source attribution study (SwissLEGIO).

Switzerland has one of the highest annual Legionnaires' disease (LD) notification rates in Europe (7.8 cases/100,000 population in 2021). The main sources of infection and the cause for this high rate remain largely unknown. This hampers the implementation of targeted Legionella spp. control efforts. The SwissLEGIO national case-control and molecular source attribution study investigates risk factors and infection sources for community-acquired LD in Switzerland. Over the duration of one year, the study is recruiting 205 newly diagnosed LD patients through a network of 20 university and cantonal hospitals. Healthy controls matched for age, sex, and residence at district level are recruited from the general population. Risk factors for LD are assessed in questionnaire-based interviews. Clinical and environmental Legionella spp. isolates are compared using whole genome sequencing (WGS). Direct comparison of sero- and sequence types (ST), core genome multilocus sequencing types (cgMLST), and single nucleotide polymorphisms (SNPs) between clinical and environmental isolates are used to investigate the infection sources and the prevalence and virulence of different Legionella spp. strains detected across Switzerland. The SwissLEGIO study innovates in combining case-control and molecular typing approaches for source attribution on a national level outside an outbreak setting. The study provides a unique platform for national Legionellosis and Legionella research and is conducted in an inter- and transdisciplinary, co-production approach involving various national governmental and national research stakeholders.

Waterborne virus transport and the associated risks in a large lake.

Waterborne enteric viruses in lakes, especially at recreational water sites, may have a negative impact on human health. However, their fate and transport in lakes are poorly understood. In this study, we propose a coupled water quality and quantitative microbial risk assessment (QMRA) model to study the transport, fate and infection risk of four common waterborne viruses (adenovirus, enterovirus, norovirus and rotavirus), using Lake Geneva as a study site. The measured virus load in raw sewage entering the lake was used as the source term in the water quality simulations for a hypothetical scenario of discharging raw wastewater at the lake surface. After discharge into the lake, virus inactivation was modeled as a function of water temperature and solar irradiance that varied both spatially and temporally during transport throughout the lake. Finally, the probability of infection, while swimming at a popular beach, was quantified and compared among the four viruses. Norovirus was found to be the most abundant virus that causes an infection probability that is at least 10 times greater than the other viruses studied. Furthermore, environmental inactivation was found to be an essential determinant in the infection risks posed by viruses to recreational water users. We determined that infection risks by enterovirus and rotavirus could be up to 1000 times lower when virus inactivation by environmental stressors was accounted for compared with the scenarios considering hydrodynamic transport only. Finally, the model highlighted the role of the wind field in conveying the contamination plume and hence in determining infection probability. Our simulations revealed that for beaches located west of the sewage discharge, the infection probability under eastward wind was 43% lower than that under westward wind conditions. This study highlights the potential of combining water quality simulation and virus-specific risk assessment for a safe water resources usage and management.

Effects of chronic exposure to arsenic on the fecal carriage of antibiotic-resistant Escherichia coli among people in rural Bangladesh.

Antibiotic resistance is a leading cause of hospitalization and death worldwide. Heavy metals such as arsenic have been shown to drive co-selection of antibiotic resistance, suggesting arsenic-contaminated drinking water is a risk factor for antibiotic resistance carriage. This study aimed to determine the prevalence and abundance of antibiotic-resistant Escherichia coli (AR-Ec) among people and drinking water in high (Hajiganj, >100 µg/L) and low arsenic-contaminated (Matlab, <20 µg/L) areas in Bangladesh. Drinking water and stool from mothers and their children (<1 year) were collected from 50 households per area. AR-Ec was detected via selective culture plating and isolates were tested for antibiotic resistance, arsenic resistance, and diarrheagenic genes by PCR. Whole-genome sequencing (WGS) analysis was done for 30 E. coli isolates from 10 households. Prevalence of AR-Ec was significantly higher in water in Hajiganj (48%) compared to water in Matlab (22%, p <0.05) and among children in Hajiganj (94%) compared to children in Matlab (76%, p <0.05), but not among mothers. A significantly higher proportion of E. coli isolates from Hajiganj were multidrug-resistant (83%) compared to isolates from Matlab (71%, p <0.05). Co-resistance to arsenic and multiple antibiotics (MAR index >0.2) was observed in a higher proportion of water (78%) and child stool (100%) isolates in Hajiganj than in water (57%) and children (89%) in Matlab (p <0.05). The odds of arsenic-resistant bacteria being resistant to third-generation cephalosporin antibiotics were higher compared to arsenic-sensitive bacteria (odds ratios, OR 1.2-7.0, p <0.01). WGS-based phylogenetic analysis of E. coli isolates did not reveal any clustering based on arsenic exposure and no significant difference in resistome was found among the isolates between the two areas. The positive association detected between arsenic exposure and antibiotic resistance carriage among children in arsenic-affected areas in Bangladesh is an important public health concern that warrants redoubling efforts to reduce arsenic exposure.

Wastewater Reveals the Spatiotemporal Spread of SARS-CoV-2 in the Canton of Ticino (Switzerland) during the Onset of the COVID-19 Pandemic.

Wastewater-based epidemiology (WBE) has emerged as an effective tool for monitoring SARS-CoV-2 dynamics during the COVID-19 pandemic. Here, we add a spatial component to WBE and use it to investigate SARS-CoV-2 spread in the canton of Ticino during the onset of the pandemic in Switzerland (end of February 2020 to beginning of March 2020). Ticino is located at the border to Northern Italy, where a large COVID-19 outbreak occurred in February 2020. Not surprisingly, Ticino was the site of the first clinically confirmed COVID-19 case in Switzerland. We retrospectively analyzed daily influent samples from nine wastewater treatment plants in Ticino that jointly cover an area of 20 km × 60 km and 351,000 people (>99% of the population). Our result is a fine-grained view of the spatiotemporal evolution of the COVID-19 pandemic in this canton. The wastewater analysis revealed that by February 29, 2020, SARS-CoV-2 had already spread to all catchments. At the same time, only four individual cases had been clinically confirmed across the region served by the treatment plants investigated. Our results demonstrate that WBE could serve as a versatile tool to monitor the introduction and spread of an infectious agent on a regional scale. To fully exploit its utility, WBE should be implemented in real time and become an integral part of future disease surveillance efforts.

Early detection and surveillance of SARS-CoV-2 genomic variants in wastewater using COJAC.

The continuing emergence of SARS-CoV-2 variants of concern and variants of interest emphasizes the need for early detection and epidemiological surveillance of novel variants. We used genomic sequencing of 122 wastewater samples from three locations in Switzerland to monitor the local spread of B.1.1.7 (Alpha), B.1.351 (Beta) and P.1 (Gamma) variants of SARS-CoV-2 at a population level. We devised a bioinformatics method named COJAC (Co-Occurrence adJusted Analysis and Calling) that uses read pairs carrying multiple variant-specific signature mutations as a robust indicator of low-frequency variants. Application of COJAC revealed that a local outbreak of the Alpha variant in two Swiss cities was observable in wastewater up to 13 d before being first reported in clinical samples. We further confirmed the ability of COJAC to detect emerging variants early for the Delta variant by analysing an additional 1,339 wastewater samples. While sequencing data of single wastewater samples provide limited precision for the quantification of relative prevalence of a variant, we show that replicate and close-meshed longitudinal sequencing allow for robust estimation not only of the local prevalence but also of the transmission fitness advantage of any variant. We conclude that genomic sequencing and our computational analysis can provide population-level estimates of prevalence and fitness of emerging variants from wastewater samples earlier and on the basis of substantially fewer samples than from clinical samples. Our framework is being routinely used in large national projects in Switzerland and the UK.

Prider: multiplexed primer design using linearly scaling approximation of set coverage.

BACKGROUND: Designing oligonucleotide primers and probes is one of the key steps of various laboratory experiments such as multiplexed PCR or digital multiplexed ligation assays. When designing multiplexed primers and probes to complex, heterogeneous DNA data sets, an optimization problem can arise where the smallest number of oligonucleotides covering the largest diversity of the input dataset needs to be identified. Tools that provide this optimization in an efficient manner for large input data are currently lacking. RESULTS: Here we present Prider, an R package for designing primers and probes with a nearly optimal coverage for complex and large sequence sets. Prider initially prepares a full primer coverage of the input sequences, the complexity of which is subsequently reduced by removing components of high redundancy or narrow coverage. The primers from the resulting near-optimal coverage are easily accessible as data frames and their coverage across the input sequences can be visualised as heatmaps using Prider's plotting function. Prider permits efficient design of primers to large DNA datasets by scaling linearly to increasing sequence data, regardless of the diversity of the dataset. CONCLUSIONS: Prider solves a recalcitrant problem in molecular diagnostics: how to cover a maximal sequence diversity with a minimal number of oligonucleotide primers or probes. The combination of Prider with highly scalable molecular quantification techniques will permit an unprecedented molecular screening capability with immediate applicability in fields such as clinical microbiology, epidemic virus surveillance or antimicrobial resistance surveillance.

Wastewater-Based Estimation of the Effective Reproductive Number of SARS-CoV-2.

BACKGROUND: The effective reproductive number, Re, is a critical indicator to monitor disease dynamics, inform regional and national policies, and estimate the effectiveness of interventions. It describes the average number of new infections caused by a single infectious person through time. To date, Re estimates are based on clinical data such as observed cases, hospitalizations, and/or deaths. These estimates are temporarily biased when clinical testing or reporting strategies change. OBJECTIVES: We show that the dynamics of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) RNA in wastewater can be used to estimate Re in near real time, independent of clinical data and without the associated biases. METHODS: We collected longitudinal measurements of SARS-CoV-2 RNA in wastewater in Zurich, Switzerland, and San Jose, California, USA. We combined this data with information on the temporal dynamics of shedding (the shedding load distribution) to estimate a time series proportional to the daily COVID-19 infection incidence. We estimated a wastewater-based Re from this incidence. RESULTS: The method to estimate Re from wastewater worked robustly on data from two different countries and two wastewater matrices. The resulting estimates were as similar to the Re estimates from case report data as Re estimates based on observed cases, hospitalizations, and deaths are among each other. We further provide details on the effect of sampling frequency and the shedding load distribution on the ability to infer Re. DISCUSSION: To our knowledge, this is the first time Re has been estimated from wastewater. This method provides a low-cost, rapid, and independent way to inform SARS-CoV-2 monitoring during the ongoing pandemic and is applicable to future wastewater-based epidemiology targeting other pathogens. https://doi.org/10.1289/EHP10050.

Identifying the Sources of Intestinal Colonization With Extended-Spectrum ß-Lactamase-Producing Escherichia coli in Healthy Infants in the Community.

The prevalence of fecal colonization with extended-spectrum ß-lactamase-producing Escherichia coli (ESBL-Ec) among children in low- and middle-income countries is alarmingly high. This study aimed to identify the sources of ESBL-Ec colonization in children < 1 year old through comparative analysis of E. coli isolates from child stool, child's mother stool, and point-of-use drinking water from 46 rural households in Bangladesh. The pairwise similarity in antibiotic susceptibility of E. coli from all three sources was evaluated, followed by phylogenetic clustering using enterobacterial repetitive intergenic consensus polymerase chain reaction and whole-genome sequence analysis of the isolates. Matching antibiotic susceptibility and enterobacterial repetitive intergenic consensus polymerase chain reaction patterns were found among ESBL-Ec isolates from child-mother dyads of 24 and 11 households, respectively, from child-water dyads of 5 and 4 households, respectively, and from child-mother-water triads of 3 and 4 households, respectively. Whole-genome sequence analysis of 30 isolates from 10 households revealed that ESBL-Ec from children in five households (50%) was clonally related to ESBL-Ec either from their mothers (2 households), drinking water sources (2 households), or both mother and drinking-water sources (1 household) based on serotype, phylogroup, sequence type, antibiotic resistance genes, mobile genetic elements, core single-nucleotide polymorphisms, and whole-genome multilocus sequence typing. Overall, this study provides empirical evidence that ESBL-Ec colonization in children is linked to the colonization status of mothers and exposure to the household environments contaminated with ESBL-Ec. Interventions such as improved hygiene practices and a safe drinking water supply may help reduce the transmission of ESBL-Ec at the household level.

Drinking water chlorination has minor effects on the intestinal flora and resistomes of Bangladeshi children.

Healthy development of the gut microbiome provides long-term health benefits. Children raised in countries with high infectious disease burdens are frequently exposed to diarrhoeal pathogens and antibiotics, which perturb gut microbiome assembly. A recent cluster-randomized trial leveraging >4,000 child observations in Dhaka, Bangladesh, found that automated water chlorination of shared taps effectively reduced child diarrhoea and antibiotic use. In this substudy, we leveraged stool samples collected from 130 children 1 year after chlorine doser installation to examine differences between treatment and control children's gut microbiota. Water chlorination was associated with increased abundance of several bacterial genera previously linked to improved gut health; however, we observed no effects on the overall richness or diversity of taxa. Several clinically relevant antibiotic resistance genes were relatively more abundant in the gut microbiome of treatment children, possibly due to increases in Enterobacteriaceae. While further studies on the long-term health impacts of drinking chlorinated water would be valuable, we conclude that access to chlorinated water did not substantially impact child gut microbiome development in this setting, supporting the use of chlorination to increase global access to safe drinking water.

Inferring transmission fitness advantage of SARS-CoV-2 variants of concern from wastewater samples using digital PCR, Switzerland, December 2020 through March 2021.

BackgroundThroughout the COVID-19 pandemic, SARS-CoV-2 genetic variants of concern (VOCs) have repeatedly and independently arisen. VOCs are characterised by increased transmissibility, increased virulence or reduced neutralisation by antibodies obtained from prior infection or vaccination. Tracking the introduction and transmission of VOCs relies on sequencing, typically whole genome sequencing of clinical samples. Wastewater surveillance is increasingly used to track the introduction and spread of SARS-CoV-2 variants through sequencing approaches.AimHere, we adapt and apply a rapid, high-throughput method for detection and quantification of the relative frequency of two deletions characteristic of the Alpha, Beta, and Gamma VOCs in wastewater.MethodsWe developed drop-off RT-dPCR assays and an associated statistical approach implemented in the R package WWdPCR to analyse temporal dynamics of SARS-CoV-2 signature mutations (spike Δ69-70 and ORF1a Δ3675-3677) in wastewater and quantify transmission fitness advantage of the Alpha VOC.ResultsBased on analysis of Zurich wastewater samples, the estimated transmission fitness advantage of SARS-CoV-2 Alpha based on the spike Δ69-70 was 0.34 (95% confidence interval (CI): 0.30-0.39) and based on ORF1a Δ3675-3677 was 0.53 (95% CI: 0.49-0.57), aligning with the transmission fitness advantage of Alpha estimated by clinical sample sequencing in the surrounding canton of 0.49 (95% CI: 0.38-0.61).ConclusionDigital PCR assays targeting signature mutations in wastewater offer near real-time monitoring of SARS-CoV-2 VOCs and potentially earlier detection and inference on transmission fitness advantage than clinical sequencing.

Bacteriophage Treatment before Chemical Disinfection Can Enhance Removal of Plastic-Surface-Associated Pseudomonas aeruginosa.

Opportunistic pathogens can linger on surfaces in hospital and building plumbing environments, leading to infections in at-risk populations. Furthermore, biofilm-associated bacteria are protected from removal and inactivation protocols such as disinfection. Bacteriophages show promise as tools to treat antibiotic-resistant infections. As such, phages may also be useful in environmental applications to prevent newly acquired infections. In the current study, the potential of synergies between bacteriophage and chemical disinfection against the opportunistic pathogen Pseudomonas aeruginosa was assessed under various conditions. Specifically, surface-associated P. aeruginosa was treated with various concentrations of phages (P1 or JG004), chemical disinfectants (sodium hypochlorite or benzalkonium chloride), or combined sequential treatments under three distinct attachment models (spot inoculations, dry biofilms, and wet biofilms). Phages were very effective at removing bacteria in spot inoculations (>3.2 log10 removal) and wet biofilms (up to 2.6 log10 removal), while phages prevented the regrowth of dry biofilms in the application time. In addition, phage treatment followed by chemical disinfection inactivated P. aeruginosa cells under wet biofilm conditions better than either treatment alone. This effect was hindered when chemical disinfection was applied first, followed by phage treatment, suggesting that the additive benefits of combination treatments are lost when phage is applied last. Furthermore, we confirm previous evidence of greater phage tolerance to benzalkonium chloride than to sodium hypochlorite, informing choices for combination phage-disinfectant approaches. Overall, this paper further supports the potential of using combination phage and chemical disinfectant treatments to improve the inactivation of surface-associated P. aeruginosa. IMPORTANCE Phages are already utilized in the health care industry to treat antibiotic-resistant infections, such as those on implant-associated biofilms and in compassionate-care cases. Phage treatment could also be a promising new tool to control pathogens in the built environment, preventing infections from occurring. This study shows that phages can be combined effectively with chemical disinfectants to improve the removal of wet biofilms and bacteria spotted onto surfaces while preventing regrowth in dry biofilms. This has the potential to improve pathogen containment within the built environment and drinking water infrastructure to prevent infections by opportunistic pathogens.