Residents of Nepal's Kathmandu Valley face chronic water shortages and rely on multiple water sources to meet their daily needs. However, inconsistent operational monitoring across these sources increases the likelihood of disease outbreaks. To assess the water quality status across multiple water sources, 86 samples were collected in 2018 during the winter (n = 22) and summer (n = 64) from five source types: water tankers, jar, tap, well, and stone-spouts and screened for 22 pathogens using microfluidic quantitative Polymerase Chain Reaction (mf-qPCR). Two fecal indicator bacteria and five enteric pathogens were detected. Contamination patterns showed seasonal variations, with 95% of winter samples and 55% of summer samples testing positive for pathogens. Winter samples exhibited higher concentrations of fecal indicators than summer samples. Campylobacter jejuni appeared exclusively in summer, while Adenovirus and Giardia lamblia were detected only during winter. Nonmetric multidimensional scaling showed significant clustering by season (p < 0.001), while source type was not associated with community composition. Winter samples clustered with adv4041, ftsZ, uidA, and eaeA, showing consistently higher relative abundances whereas summer samples exhibited sporadic and sparse gene distribution. These findings highlight seasonal differences in pathogen exposure risks that should be accounted for when designing surveillance and intervention measures.

This study aimed to compare the performance of polyethylene glycol (PEG) precipitation, and Nanotrap® Microbiome magnetic particle capture workflows for recovering novel fecal marker, pBI143 from 12 wastewater samples collected across six treatment plants in Maryland, USA. Quantitative PCR (qPCR) was used to quantify marker abundance. The Nanotrap workflow yielded significantly higher concentration of pBI143 compared to PEG precipitation workflow (p < 0.05). The Nanotrap workflow used in the study utilized both magnetic nanoparticles A and B, rather than magnetic nanoparticle A alone, highlighting the necessity of optimization based on the intended targets for enhanced recovery. The extracted total nucleic acids by the Nanotrap workflow, were further analyzed to quantify other fecal markers, crAssphage, tomato brown rugose fruit virus (ToBRFV), and pepper mild mottle virus (PMMoV). No significant differences in the concentrations of pBI143, crAssphage, and ToBRFV (p > 0.05) were observed, whereas the concentration of PMMoV was significantly lower than that of the three fecal markers (p < 0.05). Based on the concentration alone, pBI143, ToBRFV, and crAssphage were found to be a better alternative to PMMoV as an endogenous fecal marker.

Digital polymerase chain reaction (dPCR) is a significant advancement in health-related water microbiology, enabling absolute quantification without standard curves. By partitioning samples into thousands of individual reactions, dPCR allows for precise quantification even in the presence of inhibitory substances common in environmental samples. This study evaluated the applicability of dPCR to detect gastroenteritis-causing enteropathogens (Salmonella spp., Campylobacter coli, Campylobacter jejuni, Clostridium perfringens, JC and BK polyomaviruses, and human adenovirus), crAssphage, and four antibiotic resistance genes (ARGs) (sul1, blaNDM-1, blaCTX-M, and intI1) in wastewater and drinking water source samples. Wastewater samples were collected in 2018 from two municipal wastewater treatment plants (WWTPs) that used an oxidation ditch system (n = 12) and a stabilization pond system (n = 10) in the Kathmandu Valley, Nepal, whereas the drinking water source samples were collected from shallow wells between 2015 and 2016 (n = 22). The enteropathogens and ARGs were analyzed using the QIAcuity dPCR System. The highest detection ratio was observed by crAssphage in wastewater (100 %, 22/22) and by sul1 and intl1 in drinking water sources (91 %, 20/22). The log10 reduction values evaluated in both WWTPs were <1 using dPCR, consistent with those obtained in previous quantitative PCR studies, and may be used to cross-validate between methods. However, this study also observed low detection ratios and concentrations of enteropathogens, likely due to factors such as low sample volumes, dead volume, thermal conditions, and the dPCR platform used. Thus, optimizing these variables is imperative to enhance the applicability of dPCR in environmental assessments.

Clinical genomic surveillance is regarded as the gold standard for monitoring SARS-CoV-2 variants globally. However, as the pandemic wanes, reduced testing poses a risk to effectively tracking the trajectory of these variants within populations. Wastewater-based genomic surveillance that estimates variant frequency based on its defining set of alleles derived from clinical genomic surveillance has been successfully implemented. This method has its challenges, and allele-specific (AS) RT-qPCR or RT-dPCR may instead be used as a complementary method for estimating variant prevalence. Demonstrating equivalent performance of these methods is a prerequisite for their continued application in current and future pandemics. Here, we compared single-allele frequency using AS-RT-qPCR, to single-allele or haplotype frequency estimations derived from amplicon-based sequencing to estimate variant prevalence in wastewater during emergent and prevalent periods of Delta, Omicron, and two sub-lineages of Omicron. We found that all three methods of frequency estimation were concordant and contained sufficient information to describe the trajectory of variant prevalence. We further confirmed the accuracy of these methods by quantifying the diagnostic performance through Youden's index. The Youden's index of AS-RT-qPCR was reduced during the low prevalence period of a particular variant while the same allele in sequencing was negatively influenced due to insufficient read depth. Youden's index of haplotype-based calls was negatively influenced when alleles were common between variants. Coupling AS-RT-qPCR with sequencing can overcome the shortcomings of either platform and provide a comprehensive picture to the stakeholders for public health responses.

An ideal fecal and normalization marker for water quality monitoring or wastewater-based epidemiological studies should be globally abundant in wastewater and exhibit minimal seasonal variation. This study investigates the occurrence of novel fecal marker plasmid pBI143 in wastewater and compares its concentration with that of crAssphage in wastewater in Baltimore, Maryland, USA. Forty-eight wastewater samples were collected from two wastewater treatment plants (WWTP) A and B in January to December 2024, concentrated using a filter membrane with 0.45 μm pore size, and subjected to quantitative polymerase chain reaction. Both pBI143 and crAssphage were detected in 100 % (48/48) of the samples. The average concentration of pBI143 was 8. 2 ± 0.7 log10 copies/L in WWTP A and 8. 1 ± 1.0 log10 copies/L in WWTP B. No significant difference between concentration of pBI143 and crAssphage was observed (paired t-test, p > 0.05). A significant correlation (ρ = 0.60, p < 0.05) was found between pBI143 and crAssphage, indicating similar characteristics between the two and the potential use of pBI143 as a fecal and normalization marker. Future research should focus on the prevalence of pBI143 in wastewater from non-industrialized countries, as well as validation of pBI143 as a human-specific fecal marker, prior to its universal application as a human-origin fecal and normalization marker.

Human Immunodeficiency Virus (HIV) is still one of the biggest global public health issues, and the disease burden is disproportionately high in areas with lower socioeconomic status. Research has demonstrated that even in patients on antiretroviral medication, HIV RNA can be excreted in urine and feces. However, the use of wastewater-based epidemiology (WBE) for HIV surveillance has not yet become widespread. The goals of this study were to detect HIV RNA in raw wastewater and analyze its spatial patterns in relation to socioeconomic levels in Baltimore City and the surrounding areas. 104 raw wastewater samples were collected from six wastewater treatment facilities across the state of Maryland from February 2024 through April 2025. Samples were concentrated using polyethylene glycol (PEG 8000), and qPCR was used to measure the levels of HIV in wastewater. Pepper mild mottle virus (PMMoV) was used as an internal process control. HIV RNA concentrations, spatial distribution, temporal volatility, and correlations with socioeconomic variables were examined and contrasted with results from earlier research. All samples had PMMoV, indicating little PCR inhibition and excellent extraction quality. HIV RNA was found in 12.5 % of samples (13 out of 104), and the majority of positive results came from 2 treatment facilities that served urban areas that were highly inhabited and socioeconomically disadvantaged. This is the first study to report the detection of HIV RNA in raw wastewater in Maryland. Cost-effective, scalable, and non-invasive, the suggested method provides a potent tool for targeted surveillance and early identification in regions most in need of public health interventions, especially considering the increased prevalence of this virus in underprivileged communities.

ADVERTISEMENT RETURN TO ISSUEPREVViewpointNEXTA Call to Wastewater Researchers to Support Phage Therapy in the Global Fight against Antibiotic ResistanceOcean Thakali*Ocean ThakaliDepartment of Civil Engineering, University of Ottawa, Ottawa, Ontario K1N 6N5, CanadaChildren's Hospital of Eastern Ontario Research Institute, Ottawa, Ontario K1H 8L1, Canada*[email protected]More by Ocean ThakaliView Biographyhttps://orcid.org/0000-0002-6649-2322, Shen WanShen WanDepartment of Civil Engineering, University of Ottawa, Ottawa, Ontario K1N 6N5, CanadaMore by Shen Wan, Md. Pervez KabirMd. Pervez KabirDepartment of Civil Engineering, University of Ottawa, Ottawa, Ontario K1N 6N5, CanadaMore by Md. Pervez Kabir, Xin TianXin TianDepartment of Civil Engineering, University of Ottawa, Ottawa, Ontario K1N 6N5, CanadaMore by Xin Tian, Patrick D'AoustPatrick D'AoustDepartment of Civil Engineering, University of Ottawa, Ottawa, Ontario K1N 6N5, CanadaMore by Patrick D'Aoust, Anand TiwariAnand TiwariExpert Microbiology Unit, Finnish Institute for Health and Welfare, 70701 Kuopio, FinlandMore by Anand Tiwari, Kyle BibbyKyle BibbyDepartment of Civil and Environmental Engineering and Earth Sciences, University of Notre Dame, Notre Dame, Indiana 46556, United StatesMore by Kyle Bibbyhttps://orcid.org/0000-0003-3142-6090, Samendra SherchanSamendra SherchanCenter of Research Excellence in Wastewater-based Epidemiology, Morgan State University, Baltimore, Maryland 21251, United StatesMore by Samendra Sherchan, Charles GerbaCharles GerbaWater & Energy Sustainable Technology Center, University of Arizona, Tucson, Arizona 85745, United StatesMore by Charles Gerba, Anthony William MaressoAnthony William MaressoTAILΦR Laboratories, Department of Molecular Virology and Microbiology, Baylor College of Medicine, Houston, Texas 77030, United StatesMore by Anthony William Maresso, Tyson GraberTyson GraberChildren's Hospital of Eastern Ontario Research Institute, Ottawa, Ontario K1H 8L1, CanadaMore by Tyson Graber, and Robert DelatollaRobert DelatollaDepartment of Civil Engineering, University of Ottawa, Ottawa, Ontario K1N 6N5, CanadaMore by Robert DelatollaCite this: ACS EST Water 2024, 4, 4, 1177–1179Publication Date (Web):February 7, 2024Publication History Received29 December 2023Accepted23 January 2024Revised20 January 2024Published online7 February 2024Published inissue 12 April 2024https://doi.org/10.1021/acsestwater.3c00844Copyright © 2024 American Chemical Society. This publication is available under these Terms of Use. Request reuse permissions This publication is free to access through this site. Learn MoreArticle Views766Altmetric-Citations-LEARN ABOUT THESE METRICSArticle Views are the COUNTER-compliant sum of full text article downloads since November 2008 (both PDF and HTML) across all institutions and individuals. These metrics are regularly updated to reflect usage leading up to the last few days.Citations are the number of other articles citing this article, calculated by Crossref and updated daily. Find more information about Crossref citation counts.The Altmetric Attention Score is a quantitative measure of the attention that a research article has received online. Clicking on the donut icon will load a page at altmetric.com with additional details about the score and the social media presence for the given article. Find more information on the Altmetric Attention Score and how the score is calculated. Share Add toView InAdd Full Text with ReferenceAdd Description ExportRISCitationCitation and abstractCitation and referencesMore Options Share onFacebookTwitterWechatLinked InRedditEmail PDF (2 MB) Get e-AlertscloseSUBJECTS:Antibiotic resistance,Bacteria,Therapeutics,Viruses,Wastewater Get e-Alerts

Rapid urbanization and population growth without the implementation of proper waste management are capable of contaminating water sources, which can lead to acute gastroenteritis. This study examined the detection and reduction of five gastroenteritis-causing enteropathogens, Salmonella, Campylobacter coli, Campylobacter jejuni, Clostridium perfringens, and genogroup IV norovirus, and one respiratory pathogen, influenza A virus, in two municipal wastewater treatment plants (WWTP) using an oxidation ditch system (WWTP A; n = 20) and a stabilization pond system (WWTP B; n = 18) in the Kathmandu Valley, Nepal, collected between August 2017 and August 2019. All enteropathogens were detected in wastewater via quantitative PCR. The concentrations of the pathogens ranged from 5.7 to 7.9 log10 copies/L in WWTP A and from 4.9 to 8.1 log10 copies/L in WWTP B. The log10 reduction values of the pathogens ranged from 0.3 to 1.0 in WWTP A and from -0.1 to 0.2 in WWTP B. The association between the pathogen concentrations and the number of clinical cases in the corresponding week could not be evaluated; however, the consistent detection of pathogens in the wastewater despite low number of case reports suggested the use of wastewater-based epidemiology (WBE) for early warning of acute gastroenteritis (AGE) in the Kathmandu Valley. The pathogens were also detected in river water at approximately 7.0 log10 copies/L and exhibited no significant difference in concentration compared to wastewater, suggesting the applicability of river water for WBE of AGE. Insufficient treatment of all pathogens in the wastewater was observed, suggesting the need for full rehabilitation of the treatment plants. However, the influent may be utilized for early detection of AGE-causing pathogens in the city, whereas the river water may serve as an alternative in areas without connection to the WWTPs.

An alternative and complementary diagnostic method of surveillance is provided by wastewater-based surveillance (WBS), particularly in low-income nations like Nepal with scant wastewater treatment facilities and clinical testing infrastructure. In this study, a total of 146 water samples collected from two hospitals (n = 63) and three housing wastewaters (n = 83) from the Kathmandu Valley over the period of March 2021-Febraury 2022 were investigated for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) using quantitative reverse transcription TaqMan PCR assays targeting the N and E genes. Of the total, 67 % (98/146) samples were positive for SARS-CoV-2 RNA either by using N- or E-gene assay, with concentrations ranging from 3.6 to 9.1 log10 copies/L. There was a significant difference found between positive ratio (Chi-square test, p < 0.05) and concentration (t-test, p = 0.009) of SARS-CoV-2 RNA detected from hospital wastewater and housing waters. Wastewater data are correlated with COVID-19 active cases, indicating significance in specific areas like the Hospital (APFH) (p < 0.05). According to the application of a bivariate linear regression model (p < 0.05), the concentrations of N gene may be used to predict the COVID-19 cases in the APFH. Remarkably, SARS-CoV-2 RNA was detected prior to, during, and following clinical case surges, implying that wastewater surveillance could serve as an early warning system for public health decisions. The significance of WBS in tracking and managing pandemics is emphasized by this study, especially in resource-constrained settings.

Wastewater surveillance (WS) has been used globally as a complementary tool to monitor the spread of coronavirus disease 2019 (COVID-19) throughout the pandemic. However, a concern about the appropriateness of WS in low- and middle-income countries (LMICs) exists due to low sewer coverage and expensive viral concentration methods. In this study, influent wastewater samples (n = 63) collected from two wastewater treatment plants (WWTPs) of the Kathmandu Valley between March 2021 and February 2022 were concentrated using the economical skimmed-milk flocculation method (SMFM). The presence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) was tested by qPCR using assays that target the nucleocapsid (N) and envelope (E) genes. Overall, 84% (53/63) of the total samples were positive for SARS-CoV-2 according to at least one of the tested assays, with concentrations ranging from 3.5 to 8.3 log10 gene copies/L, indicating the effectiveness of the SMFM. No correlation was observed between the total number of COVID-19 cases and SARS-CoV-2 RNA concentrations in wastewater collected from the two WWTPs (p > 0.05). This finding cautions the prediction of future COVID-19 waves and the estimation of the number of COVID-19 cases based on wastewater concentration in settings with low sewer coverage by WWTPs. Future studies on WS in LMICs are recommended to be conducted by downscaling to sewer drainage, targeting a limited number of houses. Overall, this study supports the notion that SMFM can be an excellent economical virus-concentrating method for WS of COVID-19 in LMICs.

Wastewater surveillance of coronavirus disease 2019 (COVID-19) commonly applies reverse transcription-quantitative polymerase chain reaction (RT-qPCR) to quantify severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) RNA concentrations in wastewater over time. In most applications worldwide, maximal sensitivity and specificity of RT-qPCR has been achieved, in part, by monitoring two or more genomic loci of SARS-CoV-2. In Ontario, Canada, the provincial Wastewater Surveillance Initiative reports the average copies of the CDC N1 and N2 loci normalized to the fecal biomarker pepper mild mottle virus. In November 2021, the emergence of the Omicron variant of concern, harboring a C28311T mutation within the CDC N1 probe region, challenged the accuracy of the consensus between the RT-qPCR measurements of the N1 and N2 loci of SARS-CoV-2. In this study, we developed and applied a novel real-time dual loci quality assurance and control framework based on the relative difference between the loci measurements to the City of Ottawa dataset to identify a loss of sensitivity of the N1 assay in the period from July 10, 2022 to January 31, 2023. Further analysis via sequencing and allele-specific RT-qPCR revealed a high proportion of mutations C28312T and A28330G during the study period, both in the City of Ottawa and across the province. It is hypothesized that nucleotide mutations in the probe region, especially A28330G, led to inefficient annealing, resulting in reduction in sensitivity and accuracy of the N1 assay. This study highlights the importance of implementing quality assurance and control criteria to continually evaluate, in near real-time, the accuracy of the signal produced in wastewater surveillance applications that rely on detection of pathogens whose genomes undergo high rates of mutation.

Prison populations are unlikely to have access to prompt, effective medical care as the general population. Therefore, vaccination and effective surveillance systems have been recommended to mitigate coronavirus disease 2019 (COVID-19) transmission in prison settings. This pilot study aimed to assess the application of wastewater-based epidemiology (WBE) in a prison to act as an early warning tool for COVID-19 transmission. In this study, weekly wastewater samples (n = 21) were collected for 21 weeks from a prison facility in New Orleans, LA, USA, and analyzed for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), and the results were compared with the number of confirmed cases during the same period. SARS-CoV-2 was concentrated using two methods and quantified via RT-qPCR using CDC N1 and N2 assays. Overall, SARS-CoV-2 was detected in eight samples (38%). An equal number of samples tested positive for SARS-CoV-2 using the two concentrating methods, indicating the effectiveness of both methods for building-scale WBE. Despite limited clinical testing in the studied prison facility, instances of SARS-CoV-2 detection in wastewater prior to the diagnosis of COVID-19 depict the potential use of wastewater surveillance in detecting the presence of early and averting outbreaks in asymptomatic COVID-19 patients.

Wastewater surveillance (WWS) of SARS-CoV-2 has become a crucial tool for monitoring COVID-19 cases and outbreaks. Previous studies have indicated that SARS-CoV-2 RNA measurement from testing solid-rich primary sludge yields better sensitivity compared to testing wastewater influent. Furthermore, measurement of pepper mild mottle virus (PMMoV) signal in wastewater allows for precise normalization of SARS-CoV-2 viral signal based on solid content, enhancing disease prevalence tracking. However, despite the widespread adoption of WWS, a knowledge gap remains regarding the impact of ferric sulfate coagulation, commonly used in enhanced primary clarification, the initial stage of wastewater treatment where solids are sedimented and removed, on SARS-CoV-2 and PMMoV quantification in wastewater-based epidemiology. This study examines the effects of ferric sulfate addition, along with the associated pH reduction, on the measurement of SARS-CoV-2 and PMMoV viral measurements in wastewater primary clarified sludge through jar testing. Results show that the addition of Fe 3+ concentrations in the conventional 0 to 60 mg/L range caused no effect on SARS-CoV-2 N1 and N2 gene region measurements in wastewater solids. However, elevated Fe 3+ concentrations were shown to be associated with a statistically significant increase in PMMoV viral measurements in wastewater solids, which consequently resulted in the underestimation of PMMoV-normalized SARS-CoV-2 viral signal measurements (N1 and N2 copies/copies of PMMoV). The observed pH reduction from coagulant addition did not contribute to the increased PMMoV measurements, suggesting that this phenomenon arises from the partitioning of PMMoV viral particles into wastewater solids.

In regions without adequate centralized wastewater treatment plants, sample collection from rivers and sewers can be an alternative sampling strategy for wastewater surveillance. This study aimed to assess the feasibility of alternative sampling strategies by testing samples collected from rivers (n = 246) and sewers (n = 244) in the Kathmandu Valley between March 2021 and February 2022. All samples were concentrated using the skimmedmilk flocculation method and severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) RNA was quantified using the nucleocapsid (N) and envelope (E) genes qPCR assays. Of the total, 75 % (371/490) of the samples tested positive using at least one qPCR assay, with concentrations ranging from 3.0 to 8.3 log10 gene copies/L. No significant correlation between concentrations of SARS-CoV-2 from both sewers and river with the number of confirmed coronavirus disease 2019 (COVID-19) cases in the Kathmandu valley was observed (p >

No single microbial source tracking (MST) marker can be applied to determine the sources of fecal pollution in all water types. This study aimed to validate a high-throughput quantitative polymerase chain reaction (HT-qPCR) method for the simultaneous detection of multiple MST markers. A total of 26 fecal-source samples that had been previously collected from human sewage (n = 6) and ruminant (n = 3), dog (n = 6), pig (n = 6), chicken (n = 3), and duck (n = 2) feces in the Kathmandu Valley, Nepal, were used to validate 10 host-specific MST markers, i.e., Bacteroidales (BacHum, gyrB, BacR, and Pig2Bac), mitochondrial DNA (mtDNA) (swine, bovine, and DogmtDNA), and viral (human adenovirus, porcine adenovirus, and chicken/turkey parvovirus) markers, via HTqPCR. Only Dog-mtDNA showed 100 % accuracy. All the tested bacterial markers showed a sensitivity of 100 %. Nine of the 10 markers were further used to identify fecal contamination in groundwater sources (n = 54), tanker filling stations (n = 14), drinking water treatment plants (n = 5), and river water samples (n = 6). The human-specific Bacteroidales marker BacHum and ruminant-specific Bacteroidales marker BacR was detected at a high ratio in river water samples (83 % and 100 %, respectively). The results of HT-qPCR were in agreement with the standard qPCR. The comparable performances of HT-qPCR and standard qPCR as well as the successful detection of MST markers in the fecal -source and water samples demonstrated the potential applicability of these markers for detecting fecal contamination sources via HT-qPCR.

The emergence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants is a major public health concern that has highlighted the need to monitor circulating strains to better understand the coronavirus disease 2019 (COVID-19) pandemic. This study was carried out to monitor SARS-CoV-2 RNA and its variant-specific mutations in wastewater using reverse transcription-quantitative polymerase chain reaction (RT-qPCR). One-step RT-qPCR using the SARS-CoV-2 Detection RT-qPCR Kit for Wastewater (Takara Bio), which amplified two N-gene regions simultaneously using CDC N1 and N2 assays with a single fluorescence dye, demonstrated better performance in detecting SARS-CoV-2 RNA (positive ratio, 66 %) compared to two-step RT-qPCR using CDC N1 or N2 assay (40 % each, and 52 % when combined), with significantly lower Ct values. The one-step RT-qPCR assay detected SARS-CoV-2 RNA in 59 % (38/64) of influent samples collected from a wastewater treatment plant in Japan between January 2021 and March 2022. The correlation between the concentration of SARS-CoV-2 RNA in the wastewater and the number of COVID-19 cases reported each day for 7 days pre- and post-sampling was significant (p < 0.05, r = 0.76 ± 0.03). Thirty-one influent samples which showed two-well positive for SARS-CoV-2 RNA were further tested by six mutations site-specific one-step RT-qPCR (E484K, L452R, N501Y, T478K, G339D, and E484A mutations). The N501Y mutation was detected between March and June 2021 but was replaced by the L452R and T478K mutations between July and October 2021, reflecting the shift from Alpha to Delta variants in the study region. The G339D and E484A mutations were identified in January 2022 and later when the incidence of the Omicron variant peaked. These findings indicate that wastewater-based epidemiology has the epidemiological potential to complement clinical tests to track the spread of COVID-19 and monitor variants circulating in communities.

Recent MPOX viral resurgences have mobilized public health agencies around the world. Recognizing the significant risk of MPOX outbreaks, large-scale human testing, and immunization campaigns have been initiated by local, national, and global public health authorities. Recently, traditional clinical surveillance campaigns for MPOX have been complemented with wastewater surveillance (WWS), building on the effectiveness of existing wastewater programs that were built to monitor SARS-CoV-2 and recently expanded to include influenza and respiratory syncytial virus surveillance in wastewaters. In the present study, we demonstrate and further support the finding that MPOX viral fragments agglomerate in the wastewater solids fraction. Furthermore, this study demonstrates that the current, most commonly used MPOX assays are equally effective at detecting low titers of MPOX viral signal in wastewaters. Finally, MPOX WWS is shown to be more effective at passively tracking outbreaks and/or resurgences of the disease than clinical testing alone in smaller communities with low human clinical case counts of MPOX.

The role of wastewater-based epidemiology (WBE), a powerful tool to complement clinical surveillance, has increased as many grassroots-level facilities, such as municipalities and cities, are actively involved in wastewater monitoring, and the clinical testing of coronavirus disease 2019 (COVID-19) is downscaled widely. This study aimed to conduct long-term wastewater surveillance of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in Yamanashi Prefecture, Japan, using one-step reverse transcription-quantitative polymerase chain reaction (RT-qPCR) assay and estimate COVID-19 cases using a cubic regression model that is simple to implement. Influent wastewater samples (n = 132) from a wastewater treatment plant were collected normally once weekly between September 2020 and January 2022 and twice weekly between February and August 2022. Viruses in wastewater samples (40 mL) were concentrated by the polyethylene glycol precipitation method, followed by RNA extraction and RT-qPCR. The K-6-fold cross-validation method was used to select the appropriate data type (SARS-CoV-2 RNA concentration and COVID-19 cases) suitable for the final model run. SARS-CoV-2 RNA was successfully detected in 67 % (88 of 132) of the samples tested during the whole surveillance period, 37 % (24 of 65) and 96 % (64 of 67) of the samples collected before and during 2022, respectively, with concentrations ranging from 3.5 to 6.3 log10 copies/L. This study applied a nonnormalized SARS-CoV-2 RNA concentration and nonstandardized data for running the final 14-day (1 to 14 days) offset models to estimate weekly average COVID-19 cases. Comparing the parameters used for a model evaluation, the best model showed that COVID-19 cases lagged 3 days behind the SARS-CoV-2 RNA concentration in wastewater samples during the Omicron variant phase (year 2022). Finally, 3- and 7-day offset models successfully predicted the trend of COVID-19 cases from September 2022 until February 2023, indicating the applicability of WBE as an early warning tool.

This study aimed to utilize wastewater surveillance for monitoring Mpox cases at a community level. Untreated wastewater samples were collected once a week from two wastewater treatment plants (A and B) in Baltimore City from July 27, 2022-September 22, 2022. The samples were concentrated via an adsorption-elution (AE) method and Polyethylene Glycol (PEG) precipitation method followed by quantitative polymerase chain reaction (qPCR). Monkeypox virus (MPXV) was detected in 89 % (8/9) samples from WWTP A and 55 % (5/9) samples from WWTP B with at least one concentration method. Higher detection rate in samples concentrated with PEG precipitation compared to AE method was observed, indicating that PEG precipitation is a more effective virus concentration method for MPXV. To our knowledge, this is the first study reporting the detection of MPXV in wastewater in Baltimore. The results highlight that wastewater surveillance could be used as a complementary early warning tool for monitoring future Mpox outbreaks.