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The search for better tools for interpreting and understanding wastewater surveillance has continued since the beginning of the coronavirus disease 2019 (COVID-19) pandemic. Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has continued to mutate, thus complicating the interpretation of surveillance results. We assessed the Omicron variants (BA.1, BA.2, and BA.5) associated with wastewater-derived SARS-CoV-2 RNA trends by estimating the effective reproduction number (Reff) using an epidemic model that integrates explicitly the SARS-CoV-2 N2 gene concentration detected in wastewater through rt-qPCR quantitative analysis. The model inferred COVID-19 cases based on wastewater data and compared them with the ones reported by clinical surveillance. The variant of the SARS-CoV-2 associated with the wastewater-derived viral RNA was monitored through wastewater whole-genome sequencing. Three major waves between January and September 2022 were associated with the Omicron subvariants (BA.1, BA.2, and BA.5). This work showed that disease trends can be monitored using estimates of the effective reproduction number which is simple and easy to understand.

The prolonged course of the COVID-19 pandemic necessitates sustained surveillance of emerging variants. This study aimed to develop a multiplex real-time polymerase chain reaction (rt-PCR) suitable for the real-time tracking of Omicron subvariants in clinical and wastewater samples. Plasmids containing variant-specific mutations were used to develop a MeltArray assay. After a comprehensive evaluation of both analytical and clinical performance, the established assay was used to detect Omicron variants in clinical and wastewater samples, and the results were compared with those of next-generation sequencing (NGS) and droplet digital PCR (ddPCR). The MeltArray assay identified 14 variant-specific mutations, enabling the detection of five Omicron sublineages (BA.2*, BA.5.2*, BA.2.75*, BQ.1*, and XBB.1*) and eight subvariants (BF.7, BN.1, BR.2, BQ.1.1, XBB.1.5, XBB.1.16, XBB.1.9, and BA.4.6). The limit of detection (LOD) of the assay was 50 copies/reaction, and no cross-reactivity was observed with 15 other respiratory viruses. Using NGS as the reference method, the clinical evaluation of 232 swab samples exhibited a clinical sensitivity of > 95.12% (95% CI 89.77–97.75%) and a specificity of > 95.21% (95% CI, 91.15–97.46%). When used to evaluate the Omicron outbreak from late 2022 to early 2023, the MeltArray assay performed on 1408 samples revealed that the epidemic was driven by BA.5.2* (883, 62.71%) and BF.7 (525, 37.29%). Additionally, the MeltArray assay demonstrated potential for estimating variant abundance in wastewater samples. The MeltArray assay is a rapid and scalable method for identifying SARS-CoV-2 variants. Integrating this approach with NGS and ddPCR will improve variant surveillance capabilities and ensure preparedness for future variants.

Sampling and analysing urban wastewater are found to be a reliable indicator of the regional spread of infectious diseases. During the COVID-19 pandemic, several research groups around the globe sampled wastewater from treatment plants or other points throughout a sewer system and tried to identify the presence of the virus. Since infected persons are found to excrete the virus in their feces and urine, urban wastewater analysis proved to be a valuable tool for the early detection of spikes in the disease. In the present study, an effort was made to investigate several fate and transport scenarios of SARS-CoV-2 in a sewer system. USEPA’s Storm Water Management Model (SWMM) was utilized for the analysis. The modelling results were then used as an input to an optimization procedure using an NSGA-II algorithm. The optimization procedure aimed to determine the appropriate number and combination of sampling points for a better assessment of the disease’s dispersion in the community. Four to six sampling points seem to offer a high likelihood of SARS-CoV-2 RNA detection in minimum time, representing the maximum population.

Wastewater-based epidemiology is being used as a tool to monitor the spread of COVID-19 and provide an early warning for the presence or increase of clinical cases in a community. The majority of wastewater-based epidemiology for COVID-19 tracking has been utilized in sewersheds that service populations in the tens-to-hundreds of thousands. Few studies have been conducted to assess the usefulness of wastewater in predicting COVID-19 clinical cases specifically in rural areas. This study collected samples from 16 locations across the Eastern Upper Peninsula of Michigan from June to December 2021. Sampling locations included 12 rural municipalities, a Tribal housing community and casino, a public university, three municipalities that also contained a prison, and a small island with heavy tourist traffic. Samples were analyzed for SARS-CoV-2 N1, N2, and variant gene copies using reverse transcriptase droplet digital polymerase chain reaction (RT-ddPCR). Wastewater N1 and N2 gene copies and clinical case counts were correlated to determine if wastewater results were predictive of clinical cases. Significant correlation between N1 and N2 gene copies and clinical cases was found for all sites (⍴= 0.89 to 0.48). N1 and N2 wastewater results were predictive of clinical case trends within 0-7 days. The Delta variant was detected in the Pickford and St. Ignace samples more than 12-days prior to the first reported Delta clinical cases in their respective counties. Locations with low correlation could be attributed to their high rates of tourism. This is further supported by the high correlation seen in the public university, which is a closed population. Long-term wastewater monitoring over a large, rural geographic area is useful for informing the public of potential outbreaks in the community regardless of asymptomatic cases and access to clinical testing.

Summary: Background: Schools are high-risk settings for SARS-CoV-2 transmission, but necessary for children's educational and social-emotional wellbeing. Previous research suggests that wastewater monitoring can detect SARS-CoV-2 infections in controlled residential settings with high levels of accuracy. However, its effective accuracy, cost, and feasibility in non-residential community settings is unknown. Methods: The objective of this study was to determine the effectiveness and accuracy of community-based passive wastewater and surface (environmental) surveillance to detect SARS-CoV-2 infection in neighborhood schools compared to weekly diagnostic (PCR) testing. We implemented an environmental surveillance system in nine elementary schools with 1700 regularly present staff and students in southern California. The system was validated from November 2020 to March 2021. Findings: In 447 data collection days across the nine sites 89 individuals tested positive for COVID-19, and SARS-CoV-2 was detected in 374 surface samples and 133 wastewater samples. Ninety-three percent of identified cases were associated with an environmental sample (95% CI: 88%–98%); 67% were associated with a positive wastewater sample (95% CI: 57%–77%), and 40% were associated with a positive surface sample (95% CI: 29%–52%). The techniques we utilized allowed for near-complete genomic sequencing of wastewater and surface samples. Interpretation: Passive environmental surveillance can detect the presence of COVID-19 cases in non-residential community school settings with a high degree of accuracy. Funding: County of San Diego, Health and Human Services Agency, National Institutes of Health, National Science Foundation, Centers for Disease Control.

ABSTRACT The adaptive evolution of SARS-CoV-2 variants is driven by selection for increased viral fitness in transmissibility and immune evasion. Understanding the dynamics of how an emergent variant sweeps across populations can better inform public health response preparedness for future variants. Here, we investigated the state-level genomic epidemiology of SARS-CoV-2 through baseline genomic sequencing surveillance of 27,071 public testing specimens and 1,125 hospital inpatient specimens diagnosed between November 1, 2021, and January 31, 2022, in Arizona. We found that the Omicron variant rapidly displaced Delta variant in December 2021, leading to an “Omicron surge” of COVID-19 cases in early 2022. Wastewater sequencing surveillance of 370 samples supported the synchronous sweep of Omicron in the community. Hospital inpatient COVID-19 cases of Omicron variant presented to three major hospitals 10.51 days after its detection from public clinical testing. Nonsynonymous mutations in nsp3, nsp12, and nsp13 genes were significantly associated with Omicron hospital cases compared to community cases. To model SARS-CoV-2 transmissions across the state population, we developed a scalable sequence network methodology and showed that the Omicron variant spread through intracounty and intercounty transmissions. Finally, we demonstrated that the temporal emergence of Omicron BA.1 to become the dominant variant (17.02 days) was 2.3 times faster than the prior Delta variant (40.70 days) or subsequent Omicron sublineages BA.2 (39.65 days) and BA.5 (35.38 days). Our results demonstrate the uniquely rapid sweep of Omicron BA.1. These findings highlight how integrated public health surveillance can be used to enhance preparedness and response to future variants. IMPORTANCE SARS-CoV-2 continues to evolve new variants throughout the pandemic. However, the temporal dynamics of how SARS-CoV-2 variants emerge to become the dominant circulating variant is not precisely known. Genomic sequencing surveillance offers unique insights into how SARS-CoV-2 spreads in communities and the lead-up to hospital cases during a surge. Specifically, baseline sequencing surveillance through random selection of positive diagnostic specimens provides a representative outlook of the virus lineages circulating in a geographic region. Here, we investigated the emergence of the Omicron variant of concern in Arizona by leveraging baseline genomic sequence surveillance of public clinical testing, hospitals, and community wastewater. We tracked the spread and evolution of the Omicron variant as it first emerged in the general public, and its rapid shift in hospital admissions in the state health system. This study demonstrates the timescale of public health preparedness needed to respond to an antigenic shift in SARS-CoV-2.

Wastewater surveillance has proven to be an effective tool to monitor the transmission and emergence of infectious agents at a community scale. Workflows for wastewater surveillance generally rely on concentration steps to increase the probability of detection of low-abundance targets, but preconcentration can substantially increase the time and cost of analyses while also introducing additional loss of target during processing. To address some of these issues, we conducted a longitudinal study implementing a simplified workflow for SARS-CoV-2 detection from wastewater, using a direct column-based extraction approach. Composite influent wastewater samples were collected weekly for 1 year between June 2020 and June 2021 in Athens-Clarke County, Georgia, USA. Bypassing any concentration step, low volumes (280 μl) of influent wastewater were extracted using a commercial kit, and immediately analyzed by RT-qPCR for the SARS-CoV-2 N1 and N2 gene targets. SARS-CoV-2 viral RNA was detected in 76% (193/254) of influent samples, and the recovery of the surrogate bovine coronavirus was 42% (IQR: 28%, 59%). N1 and N2 assay positivity, viral concentration, and flow-adjusted daily viral load correlated significantly with per-capita case reports of COVID-19 at the county-level (ρ = 0.69-0.82). To compensate for the method's high limit of detection (approximately 106-107 copies l-1 in wastewater), we extracted multiple smallvolume replicates of eachwastewater sample. With this approach, we detected as fewas five cases of COVID-19 per 100 000 individuals. These results indicate that a direct-extraction-based workflow for SARS-CoV-2 wastewater surveillance can provide informative and actionable results. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Wastewater surveillance of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has shown to be an important approach to determine early outbreaks of infections. Wastewater-based epidemiology (WBE) is regarded as a complementary tool for monitoring SARS-CoV-2 trends in communities. In this study, the changes in the SARS-CoV-2 RNA levels in wastewater during Easter holidays in 2021 and 2022 in the City of Cape Town were monitored over nine weeks. Our findings showed a statistically significant difference in the SARS-CoV-2 RNA viral load between the study weeks over the Easter period in 2021 and 2022, except for study week 1 and 4. During the Easter week, 52% of the wastewater treatment plants moved from the lower (low viral RNA) category in 2021 to the higher (medium to very high viral RNA) categories in 2022. As a result, the median SARS-CoV-2 viral loads where higher during the Easter week in 2022 than Easter week in 2021 (p = 0.0052). Mixed-effects model showed an association between the SARS-CoV-2 RNA viral loads and Easter week over the Easter period in 2021 only (p < 0.01). The study highlights the potential of WBE to track outbreaks during the holiday period. [ABSTRACT FROM AUTHOR]

There are a high number of COVID-19 cases per capita in the world that goes undetected including clinical diseases compatible with COVID-19. While the presence of the COVID-19 in untreated drinking water is possible, it is yet to be detected in the drinking-water supplies. COVID-19 viral fragments have been found in excrete, this call for wastewater monitoring and analysis (wastewater surveillance) of the potential health risk. This raises concern about the potential of the SARS-CoV-2 transmission via the water systems. The economic limits on the medical screening for the SARS-CoV-2 or COVID-19 worldwide are turning to wastewater-based epidemiology as great potential tools for assessing and management of the COVID-19 pandemic. Surveillance and tracking of the pathogens in the wastewater are key to the early warning system and public health strategy monitoring of the COVID-19. Currently, RT-qPCR assays is been developed for SARS-CoV-2 RNA specimen clinical testing and detection in the water system. Convectional wastewater treatment methods and disinfection are expected to eradicate the SAR-CoV-2. Chlorine, UV radiation, ozone, chloramine is been used to inactivate and disinfect the water treatment system against the SARS-CoV-2. Water management and design of the water infrastructure require major changes to accommodate climate change, water cycle, reimaging of digitalization, infrastructure and privacy protection. The water digital revolution, biosensors and nanoscale, contact tracing, knowledge management can accelerate with disruption of the COVID-19 outbreak (water-health-digital nexus). [ABSTRACT FROM AUTHOR]

Background. The accurate identification of SARS-CoV-2 (SC2) variants and estimation of their abundance in mixed population samples (e.g., air or wastewater) is imperative for successful surveillance of community level trends. Assessing the performance of SC2 variant composition estimators (VCEs) should improve our confidence in public health decision making. Here, we introduce a linear regression based VCE and compare its performance to four other VCEs: two re-purposed DNA sequence read classifiers (Kallisto and Kraken2), a maximum-likelihood based method (Lineage deComposition for Sars-Cov-2 pooled samples (LCS)), and a regression based method (Freyja). Methods. We simulated DNA sequence datasets of known variant composition from both Illumina and Oxford Nanopore Technologies (ONT) platforms and assessed the performance of each VCE. We also evaluated VCEs performance using publicly available empirical wastewater samples collected for SC2 surveillance efforts. Bioinformatic analyses were performed with a custom NextFlow workflow (C-WAP, CFSAN Wastewater Analysis Pipeline). Relative root mean squared error (RRMSE) was used as a measure of performance with respect to the known abundance and concordance correlation coefficient (CCC) was used to measure agreement between pairs of estimators. Results. Based on our results from simulated data, Kallisto was the most accurate estimator as it had the lowest RRMSE, followed by Freyja. Kallisto and Freyja had the most similar predictions, reflected by the highest CCC metrics. We also found that accuracy was platform and amplicon panel dependent. For example, the accuracy of Freyja was significantly higher with Illumina data compared to ONT data; performance of Kallisto was best with ARTICv4. However, when analyzing empirical data there was poor agreement among methods and variations in the number of variants detected (e.g., Freyja ARTICv4 had a mean of 2.2 variants while Kallisto ARTICv4 had a mean of 10.1 variants). Conclusion. This work provides an understanding of the differences in performance of a number of VCEs and how accurate they are in capturing the relative abundance of SC2 variants within a mixed sample (e.g., wastewater). Such information should help officials gauge the confidence they can have in such data for informing public health decisions. [ABSTRACT FROM AUTHOR]

Infectious diseases caused by antibiotic-resistant bacterial (ARB) pathogens are a serious threat to human and animal health. The active surveillance of ARB using an integrated one-health approach can help to reduce the emergence and spread of ARB, reduce the associated economic impact, and guide antimicrobial stewardship programs. Wastewater surveillance (WWS) of ARB provides composite samples for a total population, with easy access to the mixed community microbiome. This concept is emerging rapidly, but the clinical utility, sensitivity, and uniformity of WWS of ARB remain poorly understood especially in relation to clinical evidence in sewershed communities. Here, we systematically searched the literature to identify studies that have compared findings from WWS of ARB and antibiotic resistance genes (ARG) with clinical evidence in parallel, thereby evaluating how likely WWS of ARB and ARG can relate to the clinical cases in communities. Initially, 2,235 articles were obtained using the primary search keywords, and 1,219 articles remained after de-duplication. Among these, 35 articles fulfilled the search criteria, and an additional 13 relevant articles were included by searching references in the primary literature. Among the 48 included papers, 34 studies used a culture-based method, followed by 11 metagenomics, and three PCR-based methods. A total of 28 out of 48 included studies were conducted at the single sewershed level, eight studies involved several countries, seven studies were conducted at national or regional scales, and five at hospital levels. Our review revealed that the performance of WWS of ARB pathogens has been evaluated more frequently for Escherichia coli, Enterococcus spp., and other members of the family Enterobacteriaceae, but has not been uniformly tested for all ARB pathogens. Many wastewater-based ARB studies comparing the findings with clinical evidence were conducted to evaluate the public health risk but not to relate with clinical evidence and to evaluate the performance of WWS of ARB. Indeed, relating WWS of ARB with clinical evidence in a sewershed is not straightforward, as the source of ARB in wastewater cannot be only from symptomatic human individuals but can also be from asymptomatic carriers as well as from animal sources. Further, the varying fates of each bacterial species and ARG within the sewerage make the aim of connecting WWS of ARB with clinical evidence more complicated. Therefore, future studies evaluating the performance of many AMR pathogens and their genes for WWS one by one can make the process simpler and the interpretation of results easier. [ABSTRACT FROM AUTHOR]

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Wastewater surveillance for SARS-CoV-2 may serve as a useful source of data for public health departments as the virus is shed in the stool of infected individuals. However, for wastewater data to be actionable, wastewater must be collected, concentrated, and analyzed in a timely manner. This manuscript presents modifications on a skimmed milk concentration protocol to reduce processing time, increase the number of samples that can be processed at once, and enable use in resource-limited settings. Wastewater seeded with Human coronavirus OC43 (OC43) was concentrated using a skimmed milk flocculation protocol, and then pellets were directly extracted with the QIAamp Viral RNA Mini kit. This protocol has a higher average effective volume assayed (6.35 mL) than skimmed milk concentration methods, with and without Vertrel XF™, which involve resuspension of the pellets in PBS extraction prior to nucleic acid extraction (1.28 mL, 1.44 mL, respectively). OC43 was selected as a recovery control organism because both it and SARS-CoV-2 are enveloped respiratory viruses that primarily infect humans resulting in respiratory symptoms. The OC43 percent recovery for the direct extraction protocol (3.4%) is comparable to that of skimmed milk concentration with and without Vertrel XF™ extraction (4.0%, 2.6%, respectively). When comparing SARS-CoV-2 detection using McNemar's chi-square test, the pellet extraction method is not statistically different from skimmed milk concentration, with and without Vertrel XF™ extraction. This suggests that the method performs equally as well as existing methods. Added benefits include reduced time spent per sample and the ability to process more samples at a single time. Direct extraction of skimmed milk pellets is a viable method for quick turnaround of wastewater data for public health interventions. [ABSTRACT FROM AUTHOR]

The quantification and molecular characterization of the AdV genome in urban wastewater samples (WWSs) collected weekly at a wastewater treatment plant (WWTP) in Milan from 1 January 2021 (week 2021-01) to 1 May 2022 (week 2022-17) were performed. The concentration of the AdV genome was graphically compared with the AdV positive rate observed in the respiratory/gastrointestinal specimens from individuals hospitalized with acute respiratory/gastrointestinal infections collected from one of the major hospitals in Milan in the same time series. An increase in the AdV circulation in WWSs was seen from November 2021, peaking in March 2022 and overlapped with an increase in the AdV positive rate in respiratory/fecal samples from individuals hospitalized with acute respiratory/gastrointestinal infections. The molecular characterization of the hexon hypervariable region of loop 1 of AdV revealed the presence of the species F type 41 in WWSs collected from February 2022 to April 2022. The wastewater surveillance of AdV can provide crucial epidemiological characteristics regarding AdV, particularly where no clinical surveillance is ongoing. The increase in the AdV circulation in Milan both in WWSs and clinical samples temporally overlapped with the outbreak of severe acute pediatric hepatitis observed in Europe and needs to be better investigated. [ABSTRACT FROM AUTHOR]

Wastewater surveillance, also known as wastewater‐based epidemiology (WBE), has been successfully used to detect SARS‐CoV‐2 and other viruses in sewage in many locations in the United States and globally. This includes implementation of the surveillance on college and university campuses. A two‐phase study was conducted during the 2020–2021 academic year to test the feasibility of a WBE system on campus and to supplement the clinical COVID‐19 testing performed for the student, staff, and faculty body. The primary objective during the Fall 2020 semester was to monitor a large portion of the on‐campus population and to obtain an understanding of the spreading of the SARS‐CoV‐2 virus. The Spring 2021 objective was focused on selected residence halls and groups of residents on campus, as this was more efficient and relevant for an effective follow‐up response. Logistical problems and planning oversights initially occurred but were corrected with improved communication and experience. Many lessons were learned, including effective mapping, site planning, communication, personnel organization, and equipment management, and obtained along the way, thereby paving an opportune guide for future planning efforts. Practitioner Points: WBE was successful in the detection of many SARS‐CoV‐2 variants incl. Alpha, Beta, Gamma, Delta, Lambda, Mu, and Omicron.Careful planning and contingencies were essential for a successful implementation of a SARS‐CoV‐2 monitoring program.A surveillance program may be important for detection and monitoring of other public health relevant targets in wastewater incl. bacteria, viruses, fungi and viruses.Diverse lessons were learned incl. effective mapping, site planning, communication, personnel organization, and equipment management, thereby providing a guide for future planning efforts. [ABSTRACT FROM AUTHOR]

Wastewater-based epidemiology (WBE) is a surveillance approach used to examine chemical and biological targets within a population. Historically, the most common approaches to wastewater sampling include grab sampling and composite sampling, which can be performed manually or using an automated sampler. However, there are inherent flaws with these sampling methods. They can miss analytes due to fluctuation events in wastewater and can have high cost and labour implications. Alternately, passive sampling is a technique that involves a sampling medium that can stay in an aqueous matrix for extended periods of time to provide a greater temporal coverage. This literature review examines the current passive sampling devices used in wastewater surveillance and the general contaminants they are targeting. The polar organic chemical integrated sampler, Chemcatcher®, diffusive gradients in thin films sampler and semipermeable membrane devices were among the most frequently deployed samplers in wastewater matrices. Chemical contaminants and pharmaceuticals were identified as the most common targets. Passive sampling of biological targets has received recent attention due to the surveillance of SARS-CoV-2; however, overall, there is a lack of critical knowledge relating to the deployment and associated variability of passive samplers used for biological targets. Notwithstanding, the ability of passive sampling to capture temporal fluctuation of analytes in wastewater make it a useful sampling technique for the surveillance of pathogens in the community. Future research should focus on addressing the gaps in knowledge to optimise the use of these sampling devices. [ABSTRACT FROM AUTHOR]

The COVID-19 pandemic has resulted in over 340 million infection cases (as of 21 January 2022) and more than 5.57 million deaths globally. In reaction, science, technology and innovation communities across the globe have organised themselves to contribute to national responses to COVID-19 disease. A significant contribution has been from the establishment of wastewater-based epidemiological (WBE) surveillance interventions and programmes for monitoring the spread of COVID-19 in at least 55 countries. Here, we examine and share experiences and lessons learnt in establishing such surveillance programmes. We use case studies to highlight testing methods and logistics considerations associated in scaling the implementing of such programmes in South Africa, the Netherlands, Turkey and England. The four countries were selected to represent different regions of the world and the perspective based on the considerable progress made in establishing and implementing their national WBE programmes. The selected countries also represent different climatic zones, economies, and development stages, which influence the implementation of national programmes of this nature and magnitude. In addition, the four countries' programmes offer good experiences and lessons learnt since they are systematic, and cover extensive areas, disseminate knowledge locally and internationally and partnered with authorities (government). The programmes also strengthened working relations and partnerships between and among local and global organisations. This paper shares these experiences and lessons to encourage others in the water and public health sectors on the benefits and value of WBE in tackling SARS-CoV-2 and related future circumstances. HIGHLIGHTS Designing and refining methodologies, epidemiological tools and indicators.; Influencing public health decision-making through research data.; Experiences on programme design and methodology for WBE surveillance.; Partnerships strengthening communication and knowledge dissemination.; Capacity building activities among the science communities, local authorities, industry nationally and internationally.;

In 2020, the Houston Health Department (HHD) in Texas launched a citywide wastewater surveillance program, including a pilot program that monitored manholes at schools in Houston’s largest school district (prekindergarten–12th grade). By 2022, the pilot program monitored wastewater for SARS-CoV-2, influenza A and B, and respiratory syncytial virus. To ensure effective communication of wastewater surveillance results to school communities, HHD designed and implemented a text- and email-based alert system using existing City of Houston resources. This alert program informs recipients about the presence of a virus at their schools and actions to protect themselves and others against that virus. To promote alert program sign-ups, a dedicated bilingual community involvement coordinator conducted in-person outreach geared toward school nurses and student caregivers. From September 2023 through February 2024, a combined 5178 alerts for 43 schools were sent following virus detections. As a supplemental initiative, HHD offered vaccination events to pilot program schools with consistent virus detection. As wastewater surveillance becomes more common across the United States, this alert program presents a framework for other public health agencies to scale and adapt according to their resources. [ABSTRACT FROM AUTHOR]

Since the start of the COVID-19 pandemic, wastewater surveillance hasemerged as a critical tool for tracking the spread of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) virus and other pathogens in communities throughout the United States. In 2020, the Centers for Disease Control and Prevention (CDC) launched the National Wastewater Surveillance System (NWSS), which partners with state, local, tribal, and territorial health departments to develop and implement wastewater collection and analysis systems and to share data. In 2022, the CDC established the first two NWSS Centers of Excellence to lead its implementation and coordination efforts—one in Colorado (Colorado CoE) and one in Houston (Houston CoE). As the NWSS expands, it is becoming more important to support the training needs of jurisdictions at different stages of developing their wastewater surveillance infrastructure. To evaluate these needs, the Colorado CoE and Houston CoE conducted a needs assessment study of NWSS-funded public health agencies and public utilities departments located in the United States using surveys developed by the Colorado CoE. The results of the surveys showed that although some training needs were universal, it will be most beneficial to develop training modules tailored to the needs of entities that operate wastewater surveillance programs of various sizes, workforce experience levels, and at different stages in the infrastructure development process. [ABSTRACT FROM AUTHOR]

• 4 glucuronide and 4 sulfate metabolites of BPA, BPF and BPS investigated. • Only sulfate metabolites proven to be stable in wastewater. • A SPE and UHPLC-MS/MS method was optimized and fully validated. • Monosulfate metabolites of BPA, BPF and BPS were detected in wastewater. • Back-calculated human exposure to BPA would surpass tolerable daily intake. Wastewater-based epidemiology (WBE) has become an invaluable tool for tracking the evolution of use or exposure of/to numerous substances. Bisphenols, commonly utilized in manufacturing plastic goods, have been categorized as endocrine disrupting chemicals, underscoring the critical need for real-time data on their local-level exposure to safeguard public health. In this study, we have developed a novel analytical method and WBE framework for the assessment of population-level exposure to bisphenol A (BPA) and its most prominent substitutes, bisphenols F and S (BPF and BPS), through the determination their Phase II metabolites in wastewater by WBE. Stability and exclusivity tests denoted that glucuronides are not stable in sewage, whereas sulfate metabolites are good biomarkers. Therefore, a solid-phase extraction followed by liquid chromatography-tandem mass spectrometry method was developed for the bisphenols' monosulfates and BPA bissulfate. The analytical method was validated with three different wastewater matrices, providing trueness (as recovery) in the 79–112 % range with relative standard deviations < 12 %, and method quantification limits below 2 ng L−1 for monosulfates, but higher (35 ng L−1) for BPA bissulfate. Subsequently, the method was applied to 24h-composite raw wastewater samples collected over a week in 4 different locations in Spain and Portugal. BPA bissulfate was not detected, but the three monosulfate metabolites of each bisphenol were positively detected in the samples, being the metabolite of BPA the most prevalent, followed by those of BPF and BPS. Community-wide BPA intake was then estimated to be higher than the European Food Safety Agency (EFSA) tolerable daily intake (TDI) of 2 × 10−4 µg kg−1day−1 in all locations. In the case of BPF and BPS, there is not enough metabolism data or even established limit, but they would also surpass safe levels in several locations if a similar metabolism and TDI would be assumed. This innovative method could be used to a larger set of wastewater-treatment plants as an early-warning approach on human exposure to bisphenols. [Display omitted] [ABSTRACT FROM AUTHOR]

[Display omitted] The Chicago Department of Public Health tested wastewater samples for the presence of Monkeypox Virus (MPXV) from March 13 through June 26, 2023. There were persistent detections prior to reported cases. This indicated the baseline levels of MPXV prevalence might warrant routine monitoring. Detections in areas without corresponding reported clinical cases might highlight areas where cases are being under-reported by traditional surveillance. [ABSTRACT FROM AUTHOR]

• Direct injection allowed fast LC-MS/MS analysis of illicit drugs in WW. • DI presents similar LOQs and lower matrix effect than the SPE method. • Interlaboratory exercise supports the reliability of the DI approach. • Method would allow reporting data for most cities of a large monitoring campaigns. • Methodology promotes easier logistic and prompt reporting of results. The determination of illicit drugs in urban influent wastewater (IWW) enables the monitoring of spatial and temporal drug usage trends and assessment of community lifestyle habits. The increasing number of wastewater surveillance studies has emphasized the necessity for the development of rapid, high-throughput methods that maintain high quality data. This work evaluates the use of a dilute-and-shoot methodology, based on direct injection (DI) of centrifuged samples, as an alternative approach to the widely applied sample pre-treatment based on solid-phase extraction, for the liquid chromatography-tandem mass spectrometry determination of seven widely consumed illicit drugs and their metabolites in IWW (amphetamine; cocaine metabolite, benzoylecgonine; ketamine; 3,4-methylenedioxymethamphetamine (MDMA); methamphetamine; cannabis metabolite, 11-nor-9-carboxy-delta-9-tetrahydrocannabinol (THC COOH); heroin metabolite, 6-acetylmorphine (6-MAM)). Comparison of both approaches in terms of matrix effects, sensitivity and accuracy, demonstrates the DI method suitability to correctly quantify these analytes in IWW, with a limit of quantification lower than 30 ng L−1 for most compounds. After validation of the method and participation in an interlaboratory exercise, the DI method was applied to the analysis of 54 IWW samples collected from different Spanish wastewater treatment plants. Additionally, quality controls were incorporated in each analysis batch to support the DI method applicability and robustness. The use of a 10 μL-DI reduces time-consuming sample preparation, analysis time and measurement uncertainty. Moreover, it supports green chemistry by reducing the consumption of organic solvents and it facilitates logistics by collecting, transporting, and storing less sample volume. The methodology is therefore especially appropriate for monitoring illicit drugs in large wastewater-based epidemiology sampling campaigns or when fast near real-time results are needed. [Display omitted] [ABSTRACT FROM AUTHOR]

Wastewater surveillance (WWS) was developed in the early 1960s for the detection of poliovirus (PV) circulation in the population. It has been used to monitor several pathogens, including non-polio enteroviruses (NPEVs), which are increasingly recognised as causes of morbidity in children. However, when applying WWS to a new pathogen, it is important to consider the purpose of such a study as well as the suitability of the chosen methodology. With this purpose, the European Non-Polio Enterovirus Network (ENPEN) organised an expert webinar to discuss its history, methods, and applications; its evolution from a culture-based method to molecular detection; and future implementation of next generation sequencing (NGS). The first simulation experiments with PV calculated that a 400 mL sewage sample is sufficient for the detection of viral particles if 1:10,000 people excrete poliovirus in a population of 700,000 people. If the method is applied correctly, several NPEV types are detected. Despite culture-based methods remaining the gold standard for WWS, direct methods followed by molecular-based and sequence-based assays have been developed, not only for enterovirus but for several pathogens. Along with case-based sentinel and/or syndromic surveillance, WWS for NPEV and other pathogens represents an inexpensive, flexible, anonymised, reliable, population-based tool for monitoring outbreaks and the (re)emergence of these virus types/strains within the general population.

During the COVID-19 pandemic, wastewater surveillance was widely used to monitor temporal and geographical infection trends. Using this as a foundation, a statewide program for routine wastewater monitoring of gastrointestinal pathogens was established in Oklahoma. The results from 18 months of surveillance showed that wastewater concentrations of Salmonella, Campylobacter, and norovirus exhibit similar seasonal patterns to those observed in reported human cases (F = 4–29, p < 0.05) and that wastewater can serve as an early warning tool for increases in cases, offering between one- and two-weeks lead time. Approximately one third of outbreak alerts in wastewater correlated in time with confirmed outbreaks of Salmonella or Campylobacter and our results further indicated that several outbreaks are likely to go undetected through the traditional surveillance approach currently in place. Better understanding of the true distribution and burden of gastrointestinal infections ultimately facilitates better disease prevention and control and reduces the overall socioeconomic and healthcare related impact of these pathogens. In this respect, wastewater represents a unique opportunity for monitoring infections in real-time, without the need for individual human testing. With increasing demands for sustainable and low-cost disease surveillance, the usefulness of wastewater as a long-term method for tracking infectious disease transmission is likely to become even more pronounced.

The new coronavirus 2 (SARS-CoV-2) is known to be also shed through feces, which makes wastewater-based surveillance possible, independent of symptomatic cases and unbiased by any testing strategies and frequencies. We investigated the entire population of the Principality of Liechtenstein with samples from the wastewater treatment plant Bendern (serving all 39,000 inhabitants). Twenty-four-hour composite samples were taken once or twice a week over a period of 6 months from September 2020 to March 2021. Viral RNA was concentrated using the PEG centrifugation method followed by reverse transcription quantitative PCR. The aim of this research was to assess the suitability of SARS-CoV-2 fragments to relate the viral wastewater signal to the incidences and assess the impact of the emerging B.1.1.7. variant. The viral load in the wastewater peaked at almost 9 × 108 viral fragments per person equivalent (PE) and day on October 25, and showed a second peak on December 22 reaching a viral load of approximately 2 × 108 PE−1d−1. Individual testing showed a lag of 4 days and a distinct underestimation of cases at the first peak when testing frequency was low. The wastewater signal showed an immediate response to the implementation of non-pharmaceutical interventions. The new virus variant B.1.1.7. was first detected in wastewater on December 23, while it was first observed with individual testing on January 13, 2021. Further, our data indicate that the emergence of new virus variant may change the wastewater signal, probably due to different shedding patterns, which should be considered in future models. HIGHLIGHTS Wastewater-based epidemiology covering an entire country (Liechtenstein).; Lucrative lead of 4 days of SARS-CoV-2 gene copy numbers versus individual testing.; Variant of concern B.1.1.7. detected in wastewater 2 weeks prior to individual testing.; Variant of concern B.1.1.7. increased the ratio of wastewater signal per incidence.;

Background The accurate identification of SARS-CoV-2 (SC2) variants and estimation of their abundance in mixed population samples (e.g., air or wastewater) is imperative for successful surveillance of community level trends. Assessing the performance of SC2 variant composition estimators (VCEs) should improve our confidence in public health decision making. Here, we introduce a linear regression based VCE and compare its performance to four other VCEs: two re-purposed DNA sequence read classifiers (Kallisto and Kraken2), a maximum-likelihood based method (Lineage deComposition for Sars-Cov-2 pooled samples (LCS)), and a regression based method (Freyja). Methods We simulated DNA sequence datasets of known variant composition from both Illumina and Oxford Nanopore Technologies (ONT) platforms and assessed the performance of each VCE. We also evaluated VCEs performance using publicly available empirical wastewater samples collected for SC2 surveillance efforts. Bioinformatic analyses were performed with a custom NextFlow workflow (C-WAP, CFSAN Wastewater Analysis Pipeline). Relative root mean squared error (RRMSE) was used as a measure of performance with respect to the known abundance and concordance correlation coefficient (CCC) was used to measure agreement between pairs of estimators. Results Based on our results from simulated data, Kallisto was the most accurate estimator as it had the lowest RRMSE, followed by Freyja. Kallisto and Freyja had the most similar predictions, reflected by the highest CCC metrics. We also found that accuracy was platform and amplicon panel dependent. For example, the accuracy of Freyja was significantly higher with Illumina data compared to ONT data; performance of Kallisto was best with ARTICv4. However, when analyzing empirical data there was poor agreement among methods and variations in the number of variants detected (e.g., Freyja ARTICv4 had a mean of 2.2 variants while Kallisto ARTICv4 had a mean of 10.1 variants). Conclusion This work provides an understanding of the differences in performance of a number of VCEs and how accurate they are in capturing the relative abundance of SC2 variants within a mixed sample (e.g., wastewater). Such information should help officials gauge the confidence they can have in such data for informing public health decisions.

The coronavirus disease 2019 (COVID-19) pandemic has prompted a lot of questions globally regarding the range of information about the virus’s possible routes of transmission, diagnostics, and therapeutic tools. Worldwide studies have pointed out the importance of monitoring and early surveillance techniques based on the identification of viral RNA in wastewater. These studies indicated the presence of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) RNA in human feces, which is shed via excreta including mucus, feces, saliva, and sputum. Subsequently, they get dumped into wastewater, and their presence in wastewater provides a possibility of using it as a tool to help prevent and eradicate the virus. Its monitoring is still done in many regions worldwide and serves as an early “warning signal”; however, a lot of limitations of wastewater surveillance have also been identified.

Infectious diseases caused by antibiotic-resistant bacterial (ARB) pathogens are a serious threat to human and animal health. The active surveillance of ARB using an integrated one-health approach can help to reduce the emergence and spread of ARB, reduce the associated economic impact, and guide antimicrobial stewardship programs. Wastewater surveillance (WWS) of ARB provides composite samples for a total population, with easy access to the mixed community microbiome. This concept is emerging rapidly, but the clinical utility, sensitivity, and uniformity of WWS of ARB remain poorly understood especially in relation to clinical evidence in sewershed communities. Here, we systematically searched the literature to identify studies that have compared findings from WWS of ARB and antibiotic resistance genes (ARG) with clinical evidence in parallel, thereby evaluating how likely WWS of ARB and ARG can relate to the clinical cases in communities. Initially, 2,235 articles were obtained using the primary search keywords, and 1,219 articles remained after de-duplication. Among these, 35 articles fulfilled the search criteria, and an additional 13 relevant articles were included by searching references in the primary literature. Among the 48 included papers, 34 studies used a culture-based method, followed by 11 metagenomics, and three PCR-based methods. A total of 28 out of 48 included studies were conducted at the single sewershed level, eight studies involved several countries, seven studies were conducted at national or regional scales, and five at hospital levels. Our review revealed that the performance of WWS of ARB pathogens has been evaluated more frequently for Escherichia coli, Enterococcus spp., and other members of the family Enterobacteriaceae, but has not been uniformly tested for all ARB pathogens. Many wastewater-based ARB studies comparing the findings with clinical evidence were conducted to evaluate the public health risk but not to relate with clinical evidence and to evaluate the performance of WWS of ARB. Indeed, relating WWS of ARB with clinical evidence in a sewershed is not straightforward, as the source of ARB in wastewater cannot be only from symptomatic human individuals but can also be from asymptomatic carriers as well as from animal sources. Further, the varying fates of each bacterial species and ARG within the sewerage make the aim of connecting WWS of ARB with clinical evidence more complicated. Therefore, future studies evaluating the performance of many AMR pathogens and their genes for WWS one by one can make the process simpler and the interpretation of results easier.

The COVID-19 pandemic highlighted a wide range of public health system challenges for infectious disease surveillance. The discovery that the SARS-CoV-2 virus was shed in feces and can be characterized using PCR-based testing of sewage samples offers new possibilities and challenges for wastewater surveillance (WWS). However, WWS standardization of practices is needed to provide actionable data for a public health response. A workshop was convened consisting of academic, federal government, and industry stakeholders. The objective was to review WWS sampling protocols, testing methods, analyses, and data interpretation approaches for WWS employed nationally and identify opportunities for standardizing practices, including the development of documentary standards or reference materials in the case of SARS-CoV-2 surveillance. Other WWS potential future threats to public health were also discussed. Several aspects of WWS were considered and each offers the opportunity for standards development. These areas included sampling strategies, analytical methods, and data reporting practices. Each of these areas converged on a common theme, the challenge of results comparability across facilities and jurisdictions. For sampling, the consensus solution was the development of documentary standards to guide appropriate sampling practices. In contrast, the predominant opportunity for analytical methods was reference material development, such as PCR-based standards and surrogate recovery controls. For data reporting practices, the need for establishing the minimal required metadata, a metadata vocabulary, and standardizing data units of measure including measurement threshold definitions was discussed. Beyond SARS-CoV-2 testing, there was general agreement that the WWS platform will continue to be a valuable tool for a wide range of public health threats and that future cross-sector engagements are needed to guide an enduring WWS capability.

There are only a few established methods to determine the concentration of encapsulated viruses, such as SARS-CoV-2, in water matrices, limiting the application of wastewater-based epidemiology (WBE)—an important tool for public health research. The present study compared four methods that are commonly used to concentrate non-encapsulated enteric viruses for determining SARS-CoV-2 concentration in wastewater and wastewater-enriched river water samples. The four methods tested were electronegative membrane with Mg+2 addition, aluminum hydroxide-based precipitation, polyethylene glycol (PEG) 8000 precipitation, and ultrafiltration (with porosity of 10 and 50 kDa). Prior to the concentration step, filtration or centrifugation was performed to remove suspended particles from the samples (pretreatment). To evaluate the recovery efficiency (%), samples of SARS-CoV-2 from nasopharyngeal swabs obtained from RT-qPCR-positive patients were used as spiked samples. The second part of the analysis involved the quantification of the SARS-CoV-2 copy number in analytes without SARS-CoV-2-spiked samples. Among the tested methods, pretreatment via centrifugation followed by ultrafiltration with a 50-kDa cut-off was found the most efficient method for wastewater samples with spiked samples (54.3 or 113.01% efficiency). For the wastewater-enriched river samples with spiked samples, pretreatment via centrifugation followed by filtration using an electronegative membrane was the most efficient method (110.8% and 95.9% for N1 and N2 markers, respectively). However, ultrafiltration of the raw river water samples using 10 or 50 kDa cut-off filters and PEG 8000 precipitation showed the best concentration efficiency based on copy number, regardless of the pretreatment approach or sample type (values ranging from 3 × 105 to 6.7 × 103). The effectiveness of the concentration method can vary depending on the type of sample and concentration method. We consider that this study will contribute to more widespread use of WBE for the environmental surveillance of SARS-CoV-2.

The presence of SARS-CoV-2 RNA has been extensively reported at the influent of wastewater treatment plants (WWTPs) worldwide, and its monitoring has been proposed as a potential surveillance tool to early alert of epidemic outbreaks. However, the fate of the SARS-CoV-2 RNA in the treatment process of WWTP has not been widely studied yet; therefore, in this study, we aimed to evaluate the efficiency of treatment processes in reducing SARS-CoV-2 RNA levels in wastewater. The treatment process of three WWTPs of the Parisian area in France was monitored on six different weeks over a period of 2 months (from April 14 to June 9, 2021). SARS-CoV-2 RNA copies were detected using digital polymerase chain reaction (dPCR). Investigation on the presence of variants of concern (Del69-70, E484K, and L452R) was also performed. Additionally, SARS-CoV-2 RNA loads in the WWTPs influents were expressed as the viral concentration in per population equivalent (PE) and showed a good correlation with French public health indicators (incidence rate). SARS-CoV-2 RNA loads were notably reduced along the water treatment lines of the three WWTPs studied (2.5–3.4 log reduction). Finally, very low SARS-CoV-2 RNA loads were detected in effluents (non-detected in over half of the samples) which indicated that the potential risk of the release of wastewater effluents to the environment is probably insignificant, in the case of WWTPs enabling an efficient biological removal of nitrogen. [ABSTRACT FROM AUTHOR]

Evaluations of analytical performance through interlaboratory comparisons and proficiency tests are underway globally for biomolecular-based methods [e.g., reverse-transcription quantitative polymerase chain reaction (RT-qPCR)] used in the surveillance of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in wastewater. These evaluations often rely on sharing a common reference wastewater sample that is split among participating laboratories. A known quantity of recovery surrogates can be introduced to the wastewater matrix by the coordinating laboratory as an exogenous control in a spike-and-recovery approach; however, split-sample comparisons are increasingly performed to evaluate in situ quantities of SARS-CoV-2 genetic signal native to the sample due to the lack of a universally accepted recovery surrogate of SARS-CoV-2. A reproducible procedure that minimizes the variability of SARS-CoV-2 genetic signal among split wastewater aliquots is therefore necessary to facilitate the method comparisons, especially when a large number of aliquots are required. Emerging literature has suggested that SARS-CoV-2 genetic signal in wastewater is linked to the solids fraction. Accordingly, a protocol that allows for equal distribution of solids content evenly among wastewater aliquots was also likely to facilitate even distribution of the SARS-CoV-2 genetic signal. Based on this premise, we reviewed existing sample splitting apparatus and approaches used for solids-based parameters in environmental samples. A portable batch reactor was designed, comprised of readily accessible materials and equipment. This design was validated through splitting of real wastewater samples collected from a municipal wastewater treatment facility serving a population with reported cases of COVID-19. This work applies well-established solid-liquid mixing theory and concepts that are likely unfamiliar to molecular microbiologists and laboratory analysts, providing (1) a prototype adaptable for a range of sample quantities, aliquot sizes, microbial targets, and water matrices; and (2) a pragmatic demonstration of critical considerations for design and validation of a reproducible and effective sample splitting protocol. [ABSTRACT FROM AUTHOR]

Reverse transcription-quantitative PCR (RT-qPCR) is widely used for monitoring viruses, including severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), in wastewater. Various materials, including plasmid DNA, synthetic nucleic acids, PCR amplicons, genomic DNA, and cDNA, are currently used for SARS-CoV-2 quantification by generating standard curves. We assessed three common standards on quantifying SARS-CoV-2 RNA across nine wastewater treatment plants in Finland, as part of the national wastewater surveillance effort. We pairwise compared RT-qPCR results from 148 wastewater samples, using both IDT (#10006625, IDT, USA) and CODEX standards (#SC2-RNAC-1100, CODEX DNA), and 179 samples using both IDT and EURM019 standards (#EURM-019, European Commission, Joint Research Centre) in our assessment. Amongst the tested standards, the CODEX standard consistently yielded more stable results than either the IDT or EURM019 standards. We found that SARS-CoV-2 levels were higher with the IDT standard (4.36 Log 10 GC/100 mL) compared to the CODEX standard (4.05 Log 10 GC/100 mL). Similarly, quantification using the IDT standard was higher (5.27 Log 10 GC/100 mL) than values obtained with the EURM019 (4.81 Log 10 GC/100 mL). SARS-CoV-2 RNA quantified with IDT and CODEX standards exhibited stronger concordance (Spearman's correlation rho median of 0.79) compared to those quantified with IDT and EURM019 standards (rho median of 0.59). This study highlights the significant impact of standard material selection on SARS-CoV-2 RNA quantification, emphasizing the need for harmonization in standard material., (© 2024. The Author(s).)

Most existing wastewater surveillance studies that focus on viruses have identified a large fraction of bacteriophages. Identifying bacteria by considering bacteriophage-host interactions is a novel method for detecting bacterial pathogens circulating in a community, using wastewater surveillance. This study aims to identify human-related bacterial pathogens in municipal wastewater collected in metro Detroit, using high-throughput sequencing and bioinformatics. Untreated municipal wastewater samples were collected on August 11, 2020, and bacteriophages were concentrated using the VIRus ADsorption-ELution (VIRADEL) method. Bacteriophage-related contigs in samples ranged from 15.53 % to 18.91 %, with 2477 classified and 8853 unclassified contigs. Most identified bacteriophages were from Caudoviricetes and Malgrandaviricetes classes belonging to 19 families. Hosts of bacteriophages were predicted with the PhaBOX (CHERRY) tool. The results indicated that out of the 2477 classified phages, 2373 were associated with known bacterial hosts. Also, out of 8853 unclassified bacteriophages, 8421 were associated with known bacterial hosts, and the remaining 432 were with unknown bacterial hosts. Among all bacteriophage-associated hosts, 399 were identified as pathogenic bacteria at the species level. Approximately, 85 % of the identified pathogenic bacteria are reported to be associated with human diseases. Genome quality assessments showed that 15 bacteriophages had nearly complete genomes, which were further analyzed to understand bacteriophage-bacteria interactions in wastewater. Identified hosts of these complete-genome phages included human pathogens such as Salmonella enterica, Bacillus cereus, Achromobacter xylosoxidans, and Escherichia coli. The S. enterica bacteriophage (k141&#95;1005294) genomic map was annotated, and responsible open reading frames (ORFs) were characterized to illustrate bacteriophage behavior during infection of pathogenic bacteria in untreated wastewater. To the best of our knowledge, this is the first attempt to characterize human bacterial pathogens in wastewater through bacteriophage-pathogen interactions. Novel bioinformatic approaches enhance pathogen detection and improve the understanding of community wastewater microbiomes., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this study., (Copyright © 2024 Elsevier B.V. All rights reserved.)

Wastewater-based epidemiology (WBE) requires high-quality survey methods to determine the incidence of infections in wastewater catchment areas. In this study, the wastewater survey methods necessary for comprehending the incidence of infection by WBE are clarified. This clarification is based on the correlation with the number of confirmed coronavirus disease 2019 (COVID-19) cases, considering factors such as handling non-detect data, calculation method for representative values, analytical sensitivity, analytical reproducibility, sampling frequency, and survey duration. Data collected from 15 samples per week for two and a half years using a highly accurate analysis method were regarded as gold standard data, and the correlation between severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) RNA concentrations in wastewater and confirmed COVID-19 cases was analyzed by Monte Carlo simulation under the hypothetical situation where the quality of the wastewater survey method was reduced. Regarding data handling, it was appropriate to replace non-detect data with estimates based on distribution, and to use geometric means to calculate representative values. For the analysis of SARS-CoV-2 RNA in samples, using a highly sensitive and reproducible method (non-detect rates of <40 %; ≤0.4 standard deviation) and surveying at least three samples, preferably five samples, per week were considered desirable. Furthermore, conducting the survey over a period of time that included at least 50 weeks was necessary. A WBE that meets these survey criteria is sufficient for the determination of the COVID-19 infection incidence in the catchment. Furthermore, WBE can offer additional insights into infection rates in the catchment, such as the estimated 48 % decrease in confirmed COVID-19 cases visiting a clinic following a COVID-19 legal reclassification in Japan., Competing Interests: Declaration of competing interest The authors declare the following financial interests/personal relationships which may be considered as potential competing interests:, (Copyright © 2024 The Authors. Published by Elsevier B.V. All rights reserved.)

A survey of US infectious disease physicians indicated that few regularly reviewed wastewater surveillance (WWS) data but many reported examples of how WWS has affected or could affect their clinical practice. WWS data can be useful for physicians, but increased communication between public health professionals and physicians regarding WWS could improve its utility.

We evaluated the association between wastewater concentration and weekly percent positivity of patient testing for SARS-CoV-2, influenza, and respiratory syncytial virus in Oregon, USA. We found strong, positive correlations for SARS-CoV-2 (ρ = 0.84, p<0.001), influenza (ρ = 0.73, p<0.001) and respiratory syncytial virus (ρ = 0.69, p<0.001).

During the COVID-19 pandemic, wastewater surveillance was used to monitor community transmission of SARS-CoV-2. As new genetic variants emerged, the need for timely identification of these variants in wastewater became an important focus. In response to increased reports of Omicron transmission across the United States, the Oklahoma Wastewater Surveillance team utilized allele-specific RT-qPCR assays to detect and differentiate variants, such as Omicron, from other variants found in wastewater in Oklahoma. The PCR assays showed presence of the Omicron variant in Oklahoma on average two weeks before official reports, which was confirmed through genomic sequencing of selected wastewater samples. Through continued surveillance from November 2021 to January 2022, we also demonstrated the transition from prevalence of the Delta variant to prevalence of the Omicron variant in local communities. We further assessed how this transition correlated with certain demographic factors characterizing each community. Our results highlight RT-qPCR assays as a rapid, simple, and cost-effective method for monitoring the community spread of SARS-CoV-2 genetic variants in wastewater. Additionally, they demonstrate that specific demographic factors such as ethnic composition and household income can correlate with the timing of SARS-CoV-2 variant introduction and spread., Competing Interests: The authors declare no conflicts of interest.

The SARS-CoV-2 BA.2.86 variant, also known as Pirola, has acquired over 30 amino acid changes in the Spike protein, evolving into >150 sublineages within ten months of its emergence. Among these, the JN.1, has been rapidly increasing globally becoming the most prevalent variant. To facilitate the identification of BA.2.86 sublineages, we designed the PiroMet-1 and PiroMet-2 assays in silico and validated them using BA.2.86 viral RNA and clinical samples to ascertain analytical specificity and sensitivity. Both assays resulted very specific with limit of detection of about 1-2 RNA copies/μL. The assays were then applied in a digital RT-PCR format to wastewater samples, combined with the OmMet assay (which identifies Omicron sublineages except BA.2.86 and its descendants) and the JRC-UCE.2 assay (which can universally recognize all SARS-CoV-2 variants). When used together with the OmMet and JRC-CoV-UCE.2 assays, the PiroMet assays accurately quantified BA.2.86 sublineages in wastewater samples. Our findings support the integration of these assays into routine SARS-CoV-2 wastewater surveillance as a timely and cost-effective complement to sequencing for monitoring the prevalence and spread of BA.2.86 sublineages within communities., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 The Authors. Published by Elsevier B.V. All rights reserved.)

In advanced wastewater treatment plants on pig farms, meticulous design aims to eliminate intrinsic pollutants such as organic matter, heavy metals, and biological contaminants. In our field survey across Southern China, a notable disparity in wastewater treatment procedures among various farming facilities lies in the utilization of terminal chemical oxidation post-sedimentation tank. However, recent focus in wastewater surveillance has predominantly centered on antibiotic resistance genes, leaving the efficacy of virus removal in different effluent systems largely unexplored. To profile virus composition at the effluent, assess the virus elimination efficiency of chemical oxidation at the effluent end, and the potential environmental driver of virus abundance, we deployed a meta-transcriptomics approach to first determine the total virome in effluent specimens of terminal clean water tank system (CWT) and terminal chemical oxidation system (TCO) in Southern China pig farms, respectively. From these data, 172 viruses were identified, with a median reads per million (RPM) of 27,789 in CWT and 19,982 in TCO. Through the integration of analyses encompassing the co-occurrence patterns within viral communities, the ecology of viral diversity, and a comparative assessment of average variation degrees, we have empirically demonstrated that the procedure of TCO may perturb viral communities and diminish their abundance, particularly impacting RNA viral communities. However, despite the diminished abundance, pathogenic viruses such as PEDV and PRRSV persisted in the effluent following chemical deoxidation at a moderate RPM value, indicating a substantial in situ presence at effluent. Our environmental driver modeling, employing GLM and mantel tests, substantiated the intricate nature of virus community variation within the effluent, influenced heterogeneously by diverse factors. Notably, pond temperature emerged as the foremost determinant, while fishing farming exhibited a positive correlation with virus diversity (p < 0.05). This revelation of the cryptic persistence of virus communities in wastewater effluent expands our understanding of the varied responses of different virus categories to oxidation. Such insights transcend mere virus characterization, offering valuable implications for enhancing biosafety measures in farming practices and informing wastewater-based epidemiological surveillance., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Ltd. All rights reserved.)

Background: The COVID-19 pandemic highlighted the need for pathogen surveillance systems to augment both early warning and outbreak monitoring/control efforts. Community wastewater samples provide a rapid and accurate source of environmental surveillance data to complement direct patient sampling. Due to its global presence and critical missions, the US military is a leader in global pandemic preparedness efforts. Clinical testing for COVID-19 on US Air Force (USAF) bases (AFBs) was effective but costly with respect to direct monetary costs and indirect costs due to lost time. To remain operating at peak capacity, such bases sought a more passive surveillance option and piloted wastewater surveillance (WWS) at 17 AFBs to demonstrate feasibility, safety, utility, and cost-effectiveness from May 2021 to January 2022., Objective: We model the costs of a wastewater program for pathogens of public health concern within the specific context of US military installations using assumptions based on the results of the USAF and Joint Program Executive Office for Chemical, Biological, Radiological and Nuclear Defense pilot program. The objective was to determine the cost of deploying WWS to all AFBs relative to clinical swab testing surveillance regimes., Methods: A WWS cost projection model was built based on subject matter expert input and actual costs incurred during the WWS pilot program at USAF AFBs. Several SARS-CoV-2 circulation scenarios were considered, and the costs of both WWS and clinical swab testing were projected. Analysis was conducted to determine the break-even point and how a reduction in swab testing could unlock funds to enable WWS to occur in parallel., Results: Our model confirmed that WWS is complementary and highly cost-effective when compared to existing alternative forms of biosurveillance. We found that the cost of WWS was between US $10.5-$18.5 million less expensive annually in direct costs as compared to clinical swab testing surveillance. When the indirect cost of lost work was incorporated, including lost work associated with required clinical swab testing, we estimated that over two-thirds of clinical swab testing could be maintained with no additional costs upon implementation of WWS., Conclusions: Our results support the adoption of WWS across US military installations as part of a more comprehensive and early warning system that will enable adaptive monitoring during disease outbreaks in a more cost-effective manner than swab testing alone., (© Jaleal S Sanjak, Erin M McAuley, Justin Raybern, Richard Pinkham, Jacob Tarnowski, Nicole Miko, Bridgette Rasmussen, Christian J Manalo, Michael Goodson, Blake Stamps, Bryan Necciai, Shanmuga Sozhamannan, Ezekiel J Maier. Originally published in JMIR Public Health and Surveillance (https://publichealth.jmir.org).)

Using participatory, virologic, and wastewater surveillance systems, we estimated when and to what extent reported data of adult COVID-19 cases underestimated COVID-19 incidence in Germany. We also examined how case underestimation evolved over time. Our findings highlight how community-based surveillance systems can complement official notification systems for respiratory disease dynamics.