Wastewater Surveillance Research Articles

Population infection estimation from wastewater surveillance for SARS-CoV-2 in Nagpur, India during the second pandemic wave.

Wastewater-based epidemiology (WBE) has emerged as an effective environmental surveillance tool for predicting severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) disease outbreaks in high-income countries (HICs) with centralized sewage infrastructure. However, few studies have applied WBE alongside epidemic disease modelling to estimate the prevalence of SARS-CoV-2 in low-resource settings. This study aimed to explore the feasibility of collecting untreated wastewater samples from rural and urban catchment areas of Nagpur district, to detect and quantify SARS-CoV-2 using real-time qPCR, to compare geographic differences in viral loads, and to integrate the wastewater data into a modified Susceptible-Exposed-Infectious-Confirmed Positives-Recovered (SEIPR) model. Of the 983 wastewater samples analyzed for SARS-CoV-2 RNA, we detected significantly higher sample positivity rates, 43.7% (95% confidence interval (CI) 40.1, 47.4) and 30.4% (95% CI 24.66, 36.66), and higher viral loads for the urban compared with rural samples, respectively. The Basic reproductive number, R0, positively correlated with population density and negatively correlated with humidity, a proxy for rainfall and dilution of waste in the sewers. The SEIPR model estimated the rate of unreported coronavirus disease 2019 (COVID-19) cases at the start of the wave as 13.97 [95% CI (10.17, 17.0)] times that of confirmed cases, representing a material difference in cases and healthcare resource burden. Wastewater surveillance might prove to be a more reliable way to prepare for surges in COVID-19 cases during future waves for authorities.

Crykey: Rapid identification of SARS-CoV-2 cryptic mutations in wastewater

Wastewater surveillance for SARS-CoV-2 provides early warnings of emerging variants of concerns and can be used to screen for novel cryptic linked-read mutations, which are co-occurring single nucleotide mutations that are rare, or entirely missing, in existing SARS-CoV-2 databases. While previous approaches have focused on specific regions of the SARS-CoV-2 genome, there is a need for computational tools capable of efficiently tracking cryptic mutations across the entire genome and investigating their potential origin. We present Crykey, a tool for rapidly identifying rare linked-read mutations across the genome of SARS-CoV-2. We evaluated the utility of Crykey on over 3,000 wastewater and over 22,000 clinical samples; our findings are three-fold: i) we identify hundreds of cryptic mutations that cover the entire SARS-CoV-2 genome, ii) we track the presence of these cryptic mutations across multiple wastewater treatment plants and over three years of sampling in Houston, and iii) we find a handful of cryptic mutations in wastewater mirror cryptic mutations in clinical samples and investigate their potential to represent real cryptic lineages. In summary, Crykey enables large-scale detection of cryptic mutations in wastewater that represent potential circulating cryptic lineages, serving as a new computational tool for wastewater surveillance of SARS-CoV-2.

Long-term wastewater monitoring of SARS-CoV-2 viral loads and variants at the major international passenger hub Amsterdam Schiphol Airport: A valuable addition to COVID-19 surveillance

Wastewater-based epidemiological surveillance at municipal wastewater treatment plants has proven to play an important role in COVID-19 surveillance. Considering international passenger hubs contribute extensively to global transmission of viruses, wastewater surveillance at this type of location may be of added value as well. The aim of this study is to explore the potential of long-term wastewater surveillance at a large passenger hub as an additional tool for public health surveillance during different stages of a pandemic. Here, we present an analysis of SARS-CoV-2 viral loads in airport wastewater by reverse-transcription quantitative polymerase chain reaction (RT-qPCR) from the beginning of the COVID-19 pandemic in Feb 2020, and an analysis of SARS-CoV-2 variants by whole-genome next-generation sequencing from Sep 2020, both until Sep 2022, in the Netherlands. Results are contextualized using (inter)national measures and data sources such as passenger numbers, clinical surveillance data and national wastewater surveillance data. Our findings show that wastewater surveillance was possible throughout the study period, irrespective of measures, as viral loads were detected and quantified in 98.6 % (273/277) of samples. Emergence of SARS-CoV-2 variants, identified in 91.0 % (161/177) of sequenced samples, coincided with increases in viral loads. Furthermore, trends in viral load and variant detection in airport wastewater closely followed, and in some cases preceded, trends in national daily average viral load in wastewater and variants detected in clinical surveillance. Wastewater-based epidemiology at a large international airport is a valuable addition to classical COVID-19 surveillance and the developed expertise can be applied in pandemic preparedness plans for other (emerging) pathogens in the future.

Efficient wastewater sample filtration improves the detection of SARS-CoV-2 variants: An extensive analysis based on sequencing parameters.

During the SARS-CoV-2 pandemic, many countries established wastewater (WW) surveillance to objectively monitor the level of infection within the population. As new variants continue to emerge, it has become clear that WW surveillance is an essential tool for the early detection of variants. The EU Commission published a recommendation suggesting an approach to establish surveillance of SARS-CoV-2 and its variants in WW, besides specifying the methodology for WW concentration and RNA extraction. Therefore, different groups have approached the issue with different strategies, mainly focusing on WW concentration methods, but only a few groups highlighted the importance of prefiltering WW samples and/or purification of RNA samples. Aiming to obtain high-quality sequencing data allowing variants detection, we compared four experimental conditions generated from the treatment of: i) WW samples by WW filtration and ii) the extracted RNA by DNase treatment, purification and concentration of the extracted RNA. To evaluate the best condition, the results were assessed by focusing on several sequencing parameters, as the outcome of SARS-CoV-2 sequencing from WW is crucial for variant detection. Overall, the best sequencing result was obtained by filtering the WW sample. Moreover, the present study provides an overview of some sequencing parameters to consider when optimizing a method for monitoring SARS-CoV-2 variants from WW samples, which can also be applied to any sample preparation methodology.

Cold-chain free nucleic acid preservation using porous super-absorbent polymer (PSAP) beads to facilitate wastewater surveillance

The instability of viral targets including SARS-CoV-2 in sewage is an important challenge in wastewater monitoring projects. The unrecognized interruptions in the ‘cold-chain’ transport from the sample collection to RNA quantification in the laboratory may undermine the accurate quantification of the virus. In this study, bovine serum albumin (BSA)-modified porous superabsorbent polymer (PSAP) beads were applied to absorb raw sewage samples as a simple method for viral RNA preservation. The preservation efficiency for SARS-CoV-2 and pepper mild mottle virus (PMMoV) RNA were examined during storage for 14 days at 4 °C or room temperature against the control (no beads applied). While a non-significant difference was observed at 4 °C (∼80 % retention for both control and PSAP-treated sewage), the reduction of SARS-CoV-2 RNA concentrations was significantly lower in sewage retrieved from PSAP beads (25–40 % reduction) compared to control (>60 % reduction) at room temperature. On the other hand, the recovery of PMMoV, known for its high persistence in raw sewage, from PSAP beads or controls were consistently above 85 %, regardless of the storage temperature. Our results demonstrate the applicability of PSAP beads to wastewater-based epidemiology (WBE) projects for preservation of SARS-CoV-2 RNA in sewage, especially in remote settings with no refrigeration capabilities.

Using wastewater surveillance for mpox as a complement to traditional case-based reporting – Chicago, March–June 2023

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.

Wastewater surveillance together with metaviromic data revealed the unusual resurgence of infectious diseases after the first wave of the COVID-19 outbreak

How to address public health priorities after COVID-19 is becoming a critical task. To this end, we conducted wastewater surveillance for six leading pathogens, namely, SARS-CoV-2, norovirus, rotavirus, influenza A virus (IAV), enteroviruses and respiratory syncytial virus (RSV), in Nanchang city from January to April 2023. Metaviromic sequencing was conducted at the 1st, 4th, 7th, 9th, 12th and 14th weeks to reveal the dynamics of viral pathogens that were not covered by qPCR. Amplicon sequencing of the conserved region of norovirus GI and GII and the rotavirus and region encoding nonstructural protein of RSV was also conducted weekly. The results showed that after a rapid decrease in SARS-CoV-2 sewage concentrations occurred in January 2023, surges of norovirus, rotavirus, IAV and RSV started at the 6th, 7th, 8th and 11th weeks, respectively. The dynamics of the sewage concentrations of norovirus, rotavirus, IAV and RSV were consistent with the off-season resurgence of the above infectious diseases. Notably, peak sewage concentrations of norovirus GI, GII, rotavirus, IAV and RSV were found at the 6th, 3rd, 7th, 7th and 8th weeks, respectively. Astroviruses also resurge after the 7th week, as revealed by metaviromic data, suggesting that wastewater surveillance together with metaviromic data provides an essential early warning tool for revealing patterns of infectious disease resurgence.

The role of catchment population size, data normalization, and chronology of public health interventions on wastewater-based COVID-19 viral trends

The severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) pandemic presented the most challenging global crisis in recent times. A pandemic caused by a novel pathogen such as SARS-CoV-2 necessitated the development of innovative techniques for the monitoring and surveillance of COVID-19 infections within communities. Wastewater surveillance (WWS) is recognized as a non-invasive, cost-effective, and valuable epidemiological tool to monitor the prevalence of COVID-19 infections in communities. Seven municipal wastewater sampling sites representing distinct sewershed communities were selected for the surveillance of the SARS-CoV-2 virus in Durham Region, Ontario, Canada over 8 months from March 2021 to October 2021. Viral RNA fragments of SARS-CoV-2 and the normalization target pepper mild mottle virus (PMMoV) were concentrated from wastewater influent using the PEG/NaCl superspeed centrifugation method and quantified using RT-qPCR. Strong significant correlations (Spearman's rs = 0.749 to 0.862, P < 0.001) were observed between SARS-CoV-2 gene copies/mL of wastewater and clinical cases reported in each delineated sewershed by onset date. Although raw wastewater offered higher correlation coefficients with clinical cases by onset date compared to PMMoV normalized data, only one site had a statistically significantly higher Spearman's correlation coefficient value for raw data than normalized data. Implementation of community stay-at-home orders and vaccinations over the course of the study period in 2021 were found to strongly correspond to decreasing SARS-CoV-2 wastewater trends in the wastewater treatment plants and upstream pumping stations.

Encrypted data-sharing for preserving privacy in wastewater-based epidemiology

The rapidly expanding use of wastewater for public health surveillance requires new strategies to protect privacy rights, while data are collected at increasingly discrete geospatial scales, i.e., city, neighborhood, campus, and building-level. Data collected at high geospatial resolution can inform on labile, short-lived biomarkers, thereby making wastewater-derived data both more actionable and more likely to cause privacy concerns and stigmatization of subpopulations. Additionally, data sharing restrictions among neighboring cities and communities can complicate efforts to balance public health protections with citizens' privacy. Here, we have created an encrypted framework that facilitates the sharing of sensitive population health data among entities that lack trust for one another (e.g., between adjacent municipalities with different governance of health monitoring and data sharing). We demonstrate the utility of this approach with two real-world cases. Our results show the feasibility of sharing encrypted data between two municipalities and a laboratory, while performing secure private computations for wastewater-based epidemiology (WBE) with high precision, fast speeds, and low data costs. This framework is amenable to other computations used by WBE researchers including population normalized mass loads, fecal indicator normalizations, and quality control measures. The Centers for Disease Control and Prevention's National Wastewater Surveillance System shows ∼8 % of the records attributed to collection before the wastewater treatment plant, illustrating an opportunity to further expand currently limited community-level sampling and public health surveillance through security and responsible data-sharing as outlined here.

Incursion of SARS-CoV-2 BA.2.86.1 variant into Israel: National-scale wastewater surveillance using a novel quantitative real-time PCR assay

The emergence of the SARS-CoV-2 variant BA.2.86.1 raised a considerable concern, due to the large number of potentially virulent mutations. In this study, we developed a novel assay that specifically detects variant BA.2.86.1, and used it to screen environmental samples from wastewater treatment sites across Israel. By using a multiplex assay that included a general SARS-CoV-2 reaction, together with the BA.2.86.1-specific reaction and a control reaction, we quantified the absolute number of viral copies in each sample and its relative abundance, compared with the total copy number of circulating SARS-CoV-2.Evaluation of the new reactions showed that they are both sensitive and specific, detecting down to four copies per reaction, and maintain specificity in the presence of Omicron variants BA.1, 2 and 4 RNA. Examination of 279 samples from 30 wastewater collection sites during August–September 2023 showed that 35 samples (12.5 %) were positive, from 18 sites. Quantitative analysis of the samples showed that the relative abundance of variant BA.2.86.1 with respect to the total viral load of SARS-CoV-2 was very low and consisted between 0.01 % and 0.6 % of the total SARS-CoV-2 circulation.This study demonstrates the importance of combining wastewater surveillance with the development of specialized diagnostic assays, when clinical testing is insufficient. This approach may be useful for timely response by public health authorities in future outbreaks.

Seasonality of respiratory, enteric, and urinary viruses revealed by wastewater genomic surveillance.

Wastewater surveillance can reveal population-level infectious disease burden and emergent public health threats can be reliably assessed through wastewater surveillance. While molecular methods for wastewater monitoring of microorganisms have traditionally relied on PCR-based approaches, next-generation sequencing (NGS) can provide deeper insights via genomic analyses of multiple diverse pathogens. We conducted a year-long sequencing surveillance of 1,408 composite wastewater samples collected from 12 neighborhood-level access points in the greater Tempe area, Arizona, USA, and show that variation in wastewater viruses is driven by seasonal time and location. The temporal dynamics of viruses in wastewater were influenced cyclically, with the most dissimilarity between samples 23 weeks apart (i.e., winter vs summer, spring vs fall). We identified diverse urinary and enteric viruses including polyomaviruses, astroviruses, and noroviruses, and showed that their genotypes/subtypes shifted across seasons. We show that while wastewater data of certain respiratory viruses like severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) strongly correlate with clinical case rates, laboratory-reported case incidences were discordant with surges of high viral load in wastewater for other viruses like human coronavirus 229E. These results demonstrate the utility of wastewater sequencing for informing decision-making in public health.IMPORTANCEWastewater surveillance can provide insights into the spread of pathogens in communities. Advances in next-generation sequencing (NGS) methodologies allow for more precise detection of viruses in wastewater. Long-term wastewater surveillance of viruses is an important tool for public health preparedness. This system can act as a public health observatory that gives real-time early warning for infectious disease outbreaks and improved response times.

Leveraging wastewater: Validating the national-scale SARS-CoV-2 surveillance system in Cyprus for elevated public health surveillance and enhanced epidemiological insight

The validation of a cross-country, national-scale SARS-CoV-2 wastewater surveillance system for the monitoring of public health in the Republic of Cyprus, took place during October 2021-September 2022. The chronicle of SARS-CoV-2 genetic marker concentrations and prevailing Variants of Concern (VoCs) in all large Wastewater Treatment Plants (WWTPs) of Cyprus for a continuous period of 1 year, was recorded through an integrated, multi-disciplinary sewage-based surveillance system set up to track, visualize and make the collected information and statistical analysis outcomes, publicly available. Composite sampling and physicochemical parameter normalization of Population Equivalents (PE) and SARS-CoV-2 genetic marker concentration loads were utilized.Chemical Oxygen Demand (COD) was selected for normalization of genetic fragment loads. The selection of a normalization method should be tailored according to the characteristics of each individual city/WWTP population structure, flows and wastewater origin. Metagenomic sequencing showed the transition of the SARS-CoV-2 genome from the Delta to the Omicron variant prevalence, in agreement with changes in wastewater gene concentrations. Differences in the early detection of SARS-CoV-2 genetic markers were found among cities. The established system was able to track and monitor the trend of SARS-CoV-2, even in times of absence of other public health measures such as tracing of confirmed COVID-19 cases, showing the capacity of the wastewater system to quickly capture shifts in infections.The work done herein, confirmed the ability of the national-scale system to timely observe pandemic trends, evaluate effects of control measures implemented and monitor the burden of infected patients that shed SARS-CoV-2 fragments.

Detection of thermotolerant coliforms and SARS-CoV-2 RNA in sewage and recreational waters in the Ecuadorian coast: A call for improving water quality regulation.

Wastewater surveillance represents an alternative approach to regulating contamination and the early detection of infectious agents and outbreaks of diseases of public health importance. This study evaluated domestic wastewater effects on recreational waters in estuarine and seawater bodies in Guayas and Santa Elena provinces in Ecuador, South America. Fecal indicator bacteria (thermotolerant coliforms) served as key indicators for evaluation. Physical, chemical, and microbiological quality markers following the Ecuadorian environmental quality standard and the discharge of effluents to the water resource were analyzed. Samples were collected from 44 coastal sites and 2 oxidation lagoons during the dry and rainy seasons of 2020 and 2021, respectively. SARS-CoV-2 RNA was detected in samples with higher E. coli concentrations using reverse transcription quantitative PCR to detect the genes N and ORF1ab. All samples analyzed for SARS-CoV-2 showed Ct ˂ 40 for at least one gene. Four samples showed at least 20 genome copies of gene N per reaction. These were at an artisanal fishing port, an estuarine area (Palmar), a recreational bay, and an oxidation lagoon. A moderate correlation was found between SARS-CoV-2 RNA, thermotolerant coliform and E. coli (p-value ≤ 0.0037), and a strong and positive correlation between thermotolerant coliform and E. coli. (p-value ≤ 0.00001), highlighting the utility of these established parameters as a proxy of the virus. Significant differences were found in the concentrations of thermotolerant coliforms between seasons (p-value = 0.016) and sites (p-value = 0.005). The highest levels of coliforms were found in the dry season (63000 MPN/100 mL) in Anconcito and during the rainy season (14000 MPN/100 mL) at Esterillo in Playas County. It is recommended that the decentralized autonomous governments of the surveyed provinces in Ecuador implement urgent corrective actions and establish medium-term mechanisms to minimize a potential contamination route. Additional parameters must be included in the monitoring, such as Enterococcus and intestinal parasites, due to their public health implications. In the oxidation lagoons, maintenance actions must be carried out, including the dissolution of sediments, an increase in water retention times, and in situ treatment of the sludge, to improve the system's performance.

SARS-CoV-2 wastewater surveillance at two university campuses: lessons learned and insights on intervention strategies for public health guidance.

Wastewater surveillance has been a tool for public health officials throughout the COVID-19 pandemic. Universities established pandemic response committees to facilitate safe learning for students, faculty, and staff. These committees met to analyze both wastewater and clinical data to propose mitigation strategies to limit the spread of COVID-19. This paper reviews the initial efforts of utilizing campus data inclusive of wastewater surveillance for SARS-CoV-2 RNA concentrations, clinical case data from university response teams, and mitigation strategies from Grand Valley State University in West Michigan (population 21,648 students) and Oakland University in East Michigan (population 18,552 students) from November 2020 to April 2022. Wastewater positivity rates for both universities ranged from 32.8 to 46.8%. Peak viral signals for both universities directly corresponded to variant points of entry within the campus populations from 2021 to 2022. It was found that the organization of clinical case data and variability of wastewater testing data were large barriers for both universities to effectively understand disease dynamics within the university population. We review the initial efforts of onboarding wastewater surveillance and provide direction for structuring ongoing surveillance workflows and future epidemic response strategies based on those that led to reduced viral signals in campus wastewater.

Target and Nontarget Screening to Support Capacity Scaling for Substance Use Assessment through a Statewide Wastewater Surveillance Network in New York.

Wastewater-based epidemiology (WBE) has been widely implemented around the world as a complementary tool to conventional surveillance techniques to inform and improve public health responses. Currently, wastewater surveillance programs in the U.S. are evaluating integrated approaches to address public health challenges across multiple domains, including substance abuse. In this work, we demonstrated the potential of online solid-phase extraction coupled with liquid chromatography-high-resolution mass spectrometry to support targeted quantification and nontargeted analysis of psychoactive and lifestyle substances as a step toward understanding the operational feasibility of a statewide wastewater surveillance program for substance use assessment in New York. Target screening confirmed 39 substances in influent samples collected from 10 wastewater treatment plants with varying sewershed characteristics and is anticipated to meet the throughput demands as the statewide program scales up to full capacity. Nontarget screening prioritized additional compounds for identification at three confidence levels, including psychoactive substances, such as opioid analgesics, phenethylamines, and cathinone derivatives. Consumption rates of 12 target substances detected in over 80% of wastewater samples were similar to those reported by previous U.S.-based WBE studies despite the uncertainty associated with back-calculations. For selected substances, the relative bias in consumption estimates was sensitive to variations in monitoring frequency, and factors beyond human excretion (e.g., as indicated by the parent-to-metabolite ratios) might also contribute to their prevalence at the sewershed scale. Overall, our study marks the initial phase of refining analytical workflows and data interpretation in preparation for the incorporation of substance use assessment into the statewide wastewater surveillance program in New York.

Innovations in public health surveillance: An overview of novel use of data and analytic methods.

Innovative data sources and methods for public health surveillance (PHS) have evolved rapidly over the past 10 years, suggesting the need for a closer look at the scientific maturity, feasibility, and utility of use in real-world situations. This article provides an overview of recent innovations in PHS, including data from social media, internet search engines, the Internet of Things (IoT), wastewater surveillance, participatory surveillance, artificial intelligence (AI), and nowcasting. Examples identified suggest that novel data sources and analytic methods have the potential to strengthen PHS by improving disease estimates, promoting early warning for disease outbreaks, and generating additional and/or more timely information for public health action. For example, wastewater surveillance has re-emerged as a practical tool for early detection of the coronavirus disease 2019 (COVID-19) and other pathogens, and AI is increasingly used to process large amounts of digital data. Challenges to implementing novel methods include lack of scientific maturity, limited examples of implementation in real-world public health settings, privacy and security risks, and health equity implications. Improving data governance, developing clear policies for the use of AI technologies, and public health workforce development are important next steps towards advancing the use of innovation in PHS.

Wastewater surveillance of antibiotic resistance and class 1 integron-integrase genes: Potential impact of wastewater characteristics on genes profile

Antibiotic resistance (AR) is a major global health concern, but current surveillance efforts primarily focus on healthcare settings, leaving a lack of understanding about AR across all sectors of the One Health approach. To bridge this gap, wastewater surveillance provides a cost-effective and efficient method for monitoring AR within a population. In this study, we implemented a surveillance program by monitoring the wastewater effluent from two large-scale municipal treatment plants situated in Isfahan, a central region of Iran. These treatment plants covered distinct catchment regions and served a combined population about two million of residents. Furthermore, the effect of physicochemical and microbial characteristics of wastewater effluent including biological oxygen demand (BOD), chemical oxygen demand (COD), total suspended solids (TSS), temperature, total coliforms and Escherichia coli concentration on the abundance of ARGs (blaCTX-M, tetW, sul1, cmlA, and ermB) and class 1 integron-integrase gene (intI1) were investigated. Sul1 and blaCTX-M were the most and least abundant ARGs in the two WWTPs, respectively. Principal Component Analysis showed that in both of the WWTPs all ARGs and intI1 gene abundance were positively correlated with effluent temperature, but all other effluent characteristics (BOD, COD, TSS, total coliforms and E. coli) showed no significant correlation with ARGs abundance. Temperature could affect the performance of conventional activated sludge process, which in turn could affect the abundance of ARGs. The results of this study suggest that other factors than BOD, COD and TSS may affect the ARGs abundance. The predicted AR could lead to development of effective interventions and policies to combat AR in the clinical settings. However, further research is needed to determine the relationship between the AR in wastewater and clinical settings as well as the effect of other influential factors on ARGs abundance.

Application of Skimmed-Milk Flocculation Method for Wastewater Surveillance of COVID-19 in Kathmandu, Nepal.

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.

Leveraging wastewater surveillance for managing the spread of SARS-CoV-2 and concerned pathogens during FIFA World Cup Qatar 2022

Wastewater-based epidemiology (WBE) has been proven effective for the monitoring of infectious disease outbreaks during mass gathering events and for timely public health interventions. As part of Qatar's efforts to monitor and combat the spread of infectious diseases during the FIFA World Cup Qatar 2022™ (FWC’22), wastewater surveillance was used to monitor the spread of SARS-CoV-2, human enterovirus, and poliovirus. The screening covered five major wastewater treatment plants servicing the event locations between October 2022 and January 2023. Viruses were concentrated from the wastewater samples by PEG precipitation, followed by qRT-PCR to measure the viral load in the wastewater. As expected, SARS-CoV-2 and enterovirus RNA were detected in all samples, while poliovirus was not detected. The concentration of SARS-CoV-2 was correlated with population density, such as areas surrounding the World Cup venues, and with the number of reported clinical cases. Additionally, we observed temporal fluctuations in viral RNA concentrations, with peak levels coinciding with the group stage matches of the FWC’22. This study has been useful in providing public health authorities with an efficient and cost-effective surveillance system for potential infectious disease outbreaks during mega-events.

A systematic review on the incidence of influenza viruses in wastewater matrices: Implications for public health.

Influenza viruses pose a significant public health threat, necessitating comprehensive surveillance strategies to enhance early detection and preventive measures. This systematic review investigates the incidence of influenza viruses in wastewater matrices, aiming to elucidate the potential implications for public health. The study synthesizes existing literature, employing rigorous inclusion criteria to identify relevant studies conducted globally. The essence of the problem lies in the gaps of traditional surveillance methods, which often rely on clinical data and may underestimate the true prevalence of influenza within communities. Wastewater-based epidemiology offers a novel approach to supplementing these conventional methods, providing a broader and more representative assessment of viral circulation. This review systematically examines the methodologies employed in the selected studies, including virus concentration techniques and molecular detection methods, to establish a standardized framework for future research. Our findings reveal a consistent presence of influenza viruses in diverse wastewater matrices across different geographic locations and seasons. Recommendations for future research include the standardization of sampling protocols, improvement of virus concentration methods, and the integration of wastewater surveillance into existing public health frameworks. In conclusion, this systematic review contributes to the understanding of influenza dynamics in wastewater matrices, offering valuable insights for public health practitioners and policymakers. Implementation of wastewater surveillance alongside traditional methods can enhance the resilience of public health systems and better prepare communities for the challenges posed by influenza outbreaks.