Sewage Surveillance Research Articles

Use of passive samplers as sewage surveillance tool to monitor a hepatitis A outbreak at a school in Amsterdam, the Netherlands, Oct 2022 – March 2023

BackgroundEnteric hepatitis A virus (HAV) infections during childhood are often asymptomatic but may cause severe illness in adults. To improve public health surveillance we assessed the applicability of sewage monitoring during an HAV outbreak at a primary school.MethodsBetween October 19 and December 27, 2022, five symptomatic HAV cases were notified to the Public Health Service Amsterdam; all attended the same primary school. Passive samplers, small absorbent tools, were deployed in sewage near the school from November 14, 2022, to March 22, 2023. The absorbents were subjected to RNA extraction, HAV PCR testing, and, if positive, sequencing. PCR and sequencing were also performed on plasma and feces samples of HAV cases.ResultsIn 22 out of 88 (25%) of sewage samples, HAV RNA was detected. All HAV-RNA-positive sewage samples until 8 February 2023 were subgenotype IB, matching the strain detected in all cases. Another strain of HAV (subgenotype IA) was detected in sewage from 15 February 2023 onwards, without associated cases.ConclusionsPassive sampler-based sewage monitoring is an effective method to rapidly detect HAV shedding linked to diagnosed cases. It detects unnoticed viral infections and allows monitoring of outbreaks. This suggests that passive sampler-based monitoring is a promising tool supporting the public health response during HAV and other outbreaks.

Unnoticed antimicrobial resistance risk in Tibetan cities unveiled by sewage metagenomic surveillance: Compared to the eastern Chinese cities

Sewage surveillance is a cost-effective tool for assessing antimicrobial resistance (AMR) in urban populations. However, research on sewage AMR in remote areas is still limited. Here, we used shotgun metagenomic sequencing to profile antibiotic resistance genes (ARGs) and ARG-carrying pathogens (APs) across 15 cities in Tibetan Plateau (TP) and the major cities in eastern China. Notable regional disparities in sewage ARG composition were found, with a significantly higher ARG abundance in TP (2.97 copies/cell). A total of 542 and 545 APs were identified in sewage from TP and the East, respectively, while more than 40 % carried mobile genetic elements (MGEs). Moreover, 65 MGEs-carrying APs were identified as World Health Organization (WHO) priority-like bacterial and fungal pathogens. Notably, a fungal zoonotic pathogen, Enterocytozoon bieneusi, was found for the first time to carry a nitroimidazole resistance gene (nimJ). Although distinct in AP compositions, the relative abundances of APs were comparable in these two regions. Furthermore, sewage in TP was found to be comparable to the cities in eastern China in terms of ARG mobility and AMR risks. These findings provide insights into ARGs and APs distribution in Chinese sewage and stress the importance of AMR surveillance and management strategies in remote regions.

Time-series sewage metagenomics distinguishes seasonal, human-derived and environmental microbial communities potentially allowing source-attributed surveillance

Sewage metagenomics has risen to prominence in urban population surveillance of pathogens and antimicrobial resistance (AMR). Unknown species with similarity to known genomes cause database bias in reference-based metagenomics. To improve surveillance, we seek to recover sewage genomes and develop a quantification and correlation workflow for these genomes and AMR over time. We use longitudinal sewage sampling in seven treatment plants from five major European cities to explore the utility of catch-all sequencing of these population-level samples. Using metagenomic assembly methods, we recover 2332 metagenome-assembled genomes (MAGs) from prokaryotic species, 1334 of which were previously undescribed. These genomes account for ~69% of sequenced DNA and provide insight into sewage microbial dynamics. Rotterdam (Netherlands) and Copenhagen (Denmark) show strong seasonal microbial community shifts, while Bologna, Rome, (Italy) and Budapest (Hungary) have occasional blooms of Pseudomonas-dominated communities, accounting for up to ~95% of sample DNA. Seasonal shifts and blooms present challenges for effective sewage surveillance. We find that bacteria of known shared origin, like human gut microbiota, form communities, suggesting the potential for source-attributing novel species and their ARGs through network community analysis. This could significantly improve AMR tracking in urban environments.

Sewerage surveillance tracking characteristics of human antibiotic resistance genes in sewer system

Sewage surveillance is widely applied to track valid human excretion information and identify public health conditions during corona virus disease 2019 (COVID-19) pandemic. This approach can be applied to monitor the antibiotic resistance level in sewers and to assess the risk of spreading antibiotic resistance in municipal wastewater systems. However, there is still little information about human antibiotic resistance occurrence characteristics in sewer system. This study conducted a field trial for whole year to advance understanding on spatial and temporal occurrence of antibiotic resistance genes (ARGs) in gravity sewerage. The spatial distribution of ARGs along the drainage pipe line (from human settlements to wastewater treatement pant (WWTP)) was insignificant, which may be affected by irregular human emission alongside the pipeline. The correlation between ARGs and antibiotics in sewage was insignificant. The temporal distribution showed that the effect of temperature on ARGs abundance was evident, the ARGs abundance in sewage was generally higher during the cold season. Metagenomic analysis revealed that the detected ARGs were mainly distributed in Proteobacteria (47.51 %) and Antinobacteria (20.11 %). Potential hosts of ARGs in sewage were mainly identified as human gut microorganisms, including human pathogenic bacteria, such as Prevotella, Kocuria, and Propionibacterium, etc. This study provides a new insight into the sewerage surveillance tracking characteristics of human ARGs in sewer system, and suggesting that the sewage-carried ARGs surveillance is a promising method for assessment and management of antibiotic resistance level on population size.

Escherichia coli novel sequence type 11873 harbours a new CTX-M-15–carrying multidrug resistance type 1/2 hybrid IncC plasmid

ObjectiveThe aim of the current study was to determine the genomic map of the resistance genes of two CTX-M-15–carrying Escherichia coli strains belonging to novel sequence type (ST) 11873. Complete, closed genome sequences of the E. coli strains were obtained by applying a combination of short-read Illumina and long-read Oxford Nanopore-based sequencing. MethodsIsolation of E. coli was performed using ECC CHROMagar and antibiotic sensitivity patterns were determined using Sensititre EUVSEC plates. Whole-genome sequencing was performed for two E. coli strains (3–338 and 5–325) using Illumina MiSeq- and Oxford Nanopore MinION-based sequencing. ResultsThe complete genome of strain 3–338 (GenBank accession no. CP130007–17) was assembled into a circular chromosome of 4.65 Mb and 10 plasmids (between 2 and 148 kb). Strain 5–325 (CP130018–27) exhibited a circular chromosome of 4.7 Mb and 9 plasmids (between 2 and 148 kb). Both strains carried an identical type 1/2 hybrid IncC plasmid (∼148 kb) harbouring multiple antibiotic resistance genes (ARGs), including blaCTX−M-15, blaOXA-1, blaTEM-1, qnrS1, sul2, aphA1, aacC2, mph(A) and floR. This plasmid also carried heavy metal resistance genes, such as chrA and arsR. Strain 5–325 carried an additional IncFIB plasmid (∼78 kb) harbouring additional ARGs, including blaTEM-1, qnrS1, tet(A), dfrA14, sul2, strA and strB. ConclusionsOur study shows the emergence of a CTX-M-15–carrying type 1/2 hybrid IncC plasmid in novel E. coli ST11873. These findings emphasise the need for population-based sewage surveillance for understanding the prevalence of antibiotic resistance in pathogens in order to mitigate the further spread of such resistance factors.

Detection of Multiple Human Viruses, including Mpox, Using a Wastewater Surveillance Approach in Brazil.

Sewage surveillance can be used as an effective complementary tool for detecting pathogens in local communities, providing insights into emerging threats and aiding in the monitoring of outbreaks. In this study using qPCR and whole genomic sewage surveillance, we detected the Mpox virus along with other viruses, in municipal and hospital wastewaters in Belo Horizonte, Brazil over a 9-month period (from July 2022 until March 2023). MPXV DNA detection rates varied in our study, with 19.6% (11 out of 56 samples) detected through the hybrid capture method of whole-genome sequencing and 20% (12 out of 60 samples) through qPCR. In hospital wastewaters, the detection rate was higher, at 40% (12 out of 30 samples) compared to 13.3% (4 out of 30 samples) in municipal wastewaters. This variation could be attributed to the relatively low number of MPXV cases reported in the city, which ranged from 106 to 341 cases during the study period, and the dilution effects, given that each of the two wastewater treatment plants (WWTP) investigated serves approximately 1.1 million inhabitants. Additionally, nine other virus families were identified in both hospitals and municipal wastewaters, including Adenoviridade, Astroviridae, Caliciviridae, Picornaviridade, Polyomaviridae, Coronaviridae (which includes SARS-CoV-2), Herspesviridae, Papillomaviridae and Flaviviridae (notably including Dengue). These findings underscore the potential of genomic sewage surveillance as a robust public health tool for monitoring a wide range of viruses circulating in both community and hospitals environments, including MPXV.

Sewage surveillance of SARS-CoV-2 in Tokyo (May 2020-June 2022): method using high-throughput, fully-automated platform.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is shed in saliva, sputum, and feces of the novel coronavirus disease 2019 (COVID-19) patients, and SARS-CoV-2 RNA has been detected in sewage. Thus, many regions worldwide have implemented the measurement of SARS-CoV-2 RNA in sewage as a monitoring tool for COVID-19 prevalence. Here, we report the monitoring of two wastewater treatment plants in Tokyo from May 2020 to June 2022 using a fully automated genetic testing method for the solid fraction of sewage. We found that SARS-CoV-2 sewage monitoring using the Panther System with the Aptima SARS-CoV-2 Assay Kit is an effective method of qualitative monitoring. Furthermore, spike gene mutations (N501Y, L452R, E484A) by real-time PCR using test residues were detected in some samples, which reflected the epidemic status. Nevertheless, our findings demonstrate that the use of a fully automated testing platform is effective for SARS-CoV-2 RNA detection in the solid fraction of sewage.

Molecular Characterization and Phylogenetic analyses of Rotaviruses Circulating in Municipal Sewage and Sewage-Polluted River Waters in Durban Area, South Africa.

Globally, rotavirus continues to be the leading etiology of severe pediatric gastroenteritis, and transmission of the disease via environmental reservoirs has become an emerging concern in developing countries. From August to October 2021, a total of 69 samples comprising 48 of raw and treated sewage, and 21 surface waters, were collected from four Durban wastewater treatment plants (DWWTP), and effluent receiving rivers, respectively. Rotaviruses recovered and identified from the samples were subjected to sequencing, genotyping, and phylogenetic analysis. Of the 65 (94.2%) rotavirus-positive samples, 33.3% were from raw sewage, 16% from activated sludge, 15.9% from final effluents, and 29.0% were from the receiving river samples. A total of 49 G and 41 P genotypes were detected in sewage while 15 G and 22 P genotypes were detected in river samples. G1 genotype predominated in sewage (24.5%) followed by G3 (22.4%), G2 (14.3%), G4 (12.2%), G12 (10.2%), G9 (8.2%), and G8 (6.1%). Similarly, G1 predominated in river water samples (33.3%) and was followed by G2, G4 (20.0% each), G3, and G12 (13.3% each). Rotavirus VP4 genotypes P[4], P[6], and P[8] accounted for 36.6%, 29.3%, and 9.8%, respectively, in sewage. Correspondingly, 45.5%, 31.8%, and 13.6% were detected in river samples. The G and P genotypes not identified by the methods used were 2.1% versus 24.3% and 0.1% versus 9.1% for sewage and river water samples, respectively. Sequence comparison studies indicated a high level of nucleotide identity in the G1, G2, G3, G4, G8 VP7, and P[4], P[6], and P[8] VP4 gene sequences between strains from the environment and those from patients in the region. This is the first environmental-based study on the G and P genotypes diversity of rotavirus in municipal wastewater and their receiving rivers in this geographical region. The high similarity between environmental and clinical rotavirus strains suggests both local circulation of the virus and potential exposure risks. In addition, it highlights the usefulness of sewage surveillance as an additional tool for an epidemiological investigation, especially in populations that include individuals with subclinical or asymptomatic infections that are precluded in case-based studies.

Advancing sanitary surveillance: Innovating a live-feed sewer monitoring framework for effective water level and chamber cover detections

Efficient sanitation system management relies on vigilant sewage surveillance to uphold environmental hygiene. The absence of robust monitoring infrastructure jeopardizes unimpeded conduit flow, leading to floods and contamination. The accumulation of harmful gases in sewer chambers, coupled with tampered lids, compounds sewer network challenges, resulting in structural damage, disruptions, and safety risks from accidents and gas inhalation. Notably, even vehicular transit is vulnerable, facing collisions due to inadequately secured manholes. The core objective of this research was to deconstruct and synthesize a prototype blueprint for a live-feed sewer monitoring framework (LSMF). This involves creating a data gathering nexus (DGN) and empirically assessing diverse wireless sensing implements (WSI) for precision. Simultaneously, a geographic information matrix (GIM) was developed with algorithms to detect sewer surges, blockages, and missing manhole covers. Three scrutinized sensors—the LiDar TF-Luna, laser TOF400 VL53L1X, and ultrasonic JSN-SR04T—were evaluated for their ability to measure water levels in sewer vaults. The results showed that the TF-Luna LiDar sensor performed favorably within the 1.0–5.0 m range, with a standard deviation of 0.44–1.15. The TOF400 laser sensor ranked second, with a more variable standard deviation of up to 104 as obstacle distance increased. In contrast, the JSN-SR04T ultrasonic sensor exhibited lower standard deviation but lacked consistency, maintaining readings of 0.22–0.23 m within the 2.0–5.0 m span. The insights from this study provide valuable guidance for sustainable solutions to sewer surveillance challenges. Moreover, employing a logarithmic function, TF-Luna Benewake exhibited reliability at approximately 84.5%, while TOF400 VL53L1X adopted an exponential equation, boasting reliability approaching approximately 89.6%. With this navigational tool, TF-Luna Benewake maintained accuracy within ±10 cm for distances ranging from 8 to 10 m, showcasing its exceptional performance.

Cost-effective sensor placement optimization for large-scale urban sewage surveillance

Early pandemic outbreak detection in cities is a crucial but challenging task. Complementary to the costly massive individual testing, urban sewage surveillance offers a rare, cost-effective solution for large-scale monitoring of pandemic spread in cities with minimal interference to people’s lives. One emerging question is how to derive a cost-effective sensor placement plan in city-scale sewage networks having complicated topologies. Inspired by remote sensing, we first provide a general multi-objective formulation of the optimal sensor placement problem on directed networks. Then, we introduce a connectivity-based objective evaluation approach and embed it into an NSGA-II algorithm to enable efficient optimization on large-scale directed graphs. The effectiveness of the proposed method is verified on a real-world sewage network in Hong Kong serving more than 500,000 urban residents. Results show that the proposed method efficiently generated optimal sensor placement plans on city-scale networks. Optimized sensor placement plans outperformed human placement heuristics by a significant margin of 102%, highlighting the necessity for data-driven decision support for large-scale urban sensing. Methodologically, this study provides a benchmark problem and datasets for network-based spatial optimization studies. Codes and datasets developed in this study are open-sourced to support future research in a real-world scenario.

The cases of tracing the source of patients infected with Omicron variant of SARS-CoV-2 based on wastewater-based epidemiology in Shenzhen

Wastewater-based epidemiology (WBE) is an emerging discipline, which has been applied to drug abuse tracking and infectious disease pathogen surveillance. During the COVID-19 epidemic, WBE has been applied to monitor the epidemic trend and SARS-CoV-2 variants etc. In order to detect hidden COVID-19 cases and prevent transmission in the community, wastewater surveillance system for monitoring SARS-CoV-2 RNA was developed in Shenzhen. The sewage sampling sites were set up in key places such as the port areas, urban villages and residential communities of Futian, Nanshan, Luohu and Yantian districts. From July 26 to November 30, 2022, a total of 369 sewage sampling sites were set up, covering 1.93 million people. Continuous sampling was carried out for 3 hours in the peak period of water use every day. Sewage virus enrichment and SARS-CoV-2 nucleic acid detection were carried out by polyethylene glycol precipitation method and RT-qPCR, and a positive water sample disposal process was molded. This article aims to introduce the case of source tracing of COVID-19 infected patients based on urban sewage in Shenzhen. The sewage monitoring of Honghu water treatment plant in Luohu District played an early warning role, and the source of infection was traced. In the disposal of positive water samples in Futian South Road, Futian District, the important experience of monitoring point layout was obtained. In the sewage monitoring of Nanshan village, Nanshan District, the existence of occult infection was revealed. Sharing the experience of tracing the source of COVID-19 patients to avoid the spread of COVID-19 in the community based on wastewater surveillance of SARS-CoV-2 RNA in Shenzhen, and summarizing the advantages and application prospects of sewage surveillance can provide new ideas for monitoring emerging or re-emerging pathogens that are known to exhibit gastrointestinal excretion in the future.

Genomic surveillance of antimicrobial-resistant Escherichia coli in fecal sludge and sewage in Uganda

The global increase of antimicrobial resistance (AMR) is a major public health concern. An effective AMR surveillance tool is needed to track the emergence and spread of AMR. Wastewater surveillance has been proposed as a resource-efficient tool for monitoring AMR carriage in the community. Here, we performed genomic surveillance of antimicrobial-resistant Escherichia coli obtained from fecal sludge and sewage in Uganda to gain insights into E. coli epidemiology and AMR burden in the underlying population. Selective media containing different antibiotic combinations (cefotaxime, ciprofloxacin, cefotaxime + ciprofloxacin + gentamicin) were used to obtain antimicrobial-resistant E. coli from fecal sludge and sewage. Short-read sequencing was performed for the obtained isolates, and a subset of isolates (selected from predominant sequence types (STs)) was also subjected to long-read sequencing. Genomic analysis of the obtained E. coli isolates (n = 181) revealed the prevalence of clonal complex 10, including ST167 (n = 43), ST10 (n = 28), ST1284 (n = 17), and ST617 (n = 4), in both fecal sludge and sewage, irrespective of antibiotics used for selection. We also detected global high-risk clones ST1193 (n = 10) and ST131 (n = 2 clade A, n = 3 subclade C1-M27, and n = 1 subclade C2). Diverse AMR determinants, including extended-spectrum β-lactamase genes (mostly blaCTX-M-15) and mutations in gyrA and parC, were identified. Analysis of the completed genomes revealed that diverse IncF plasmids and chromosomal integration were the major contributors to the spread of AMR genes in the predominant STs. This study showed that a combination of sewage surveillance (or fecal sludge surveillance) and whole-genome sequencing can be a powerful tool for monitoring AMR carriage in the underlying population.

PCR standard curve quantification in an extensive wastewater surveillance program: results from the Dutch SARS-CoV-2 wastewater surveillance.

Since the start of the COVID-19 pandemic in 2020, wastewater surveillance programs were established, or upscaled, in many countries around the world and have proven to be a cost-effective way of monitoring infectious disease pathogens. Many of these programs use RT-qPCR, and quantify the viral concentrations in samples based on standard curves, by including preparations of a reference material with known nucleic acid or virus concentrations in the RT-qPCR analyses. In high-throughput monitoring programs it is possible to combine data from multiple previous runs, circumventing the need for duplication and resulting in decreased costs and prolonged periods during which the reference material is obtained from the same batch. However, over time, systematic shifts in standard curves are likely to occur. This would affect the reliability and usefulness of wastewater surveillance as a whole. We aim to find an optimal combination of standard curve data to compensate for run-to-run measurement variance while ensuring enough flexibility to capture systematic longitudinal shifts. Based on more than 4000 observations obtained with the CDC N1 and N2 assays, taken as a part of the National Sewage Surveillance program at the Dutch National Institute for Public Health and the Environment, we show that seasonal and long-term shifts in RT-qPCR efficiency and sensitivity occur. We find that in our setting, using five days of standard-curve data to quantify, results in the least error prone curve or best approximation. This results in differences up to 100% in quantified viral loads when averaged out over a nationwide program of >300 treatment plants. Results show that combining standard curves from a limited set of runs can be a valid approach to quantification without obscuring the trends in the viral load of interest.

Monkeypox Virus in Wastewater Samples from Santiago Metropolitan Region, Chile.

Sewage surveillance provides useful epidemiologic and public health information on viral infections at the population level. We detected monkeypox virus DNA from sewage samples covering 85% of the population in Santiago Metropolitan Region Chile. We also isolated infective viruses from those samples. Wastewater surveillance could complement clinical surveillance for monkeypox virus.

Comparison of kits for SARS-CoV-2 extraction in liquid and passive samples.

Effective extraction and detection of viral nucleic acids from sewage are fundamental components of a successful SARS-CoV-2 sewage surveillance programme. As there is no standard method employed in sewage surveillance, understanding the performance of different extraction kits in the recovery of SARS-CoV-2 and the impact that PCR inhibitors have on quantification is essential to minimize data discrepancies caused by sample extraction. Three commercial nucleic acid extraction kits: the RNeasy PowerSoil Total RNA Kit (PS), the RNeasy PowerMicrobiome Kit (PMB), and the MagMAX™ Microbiome Ultra Nucleic Acid Isolation Kit (MM), with minor modifications, were evaluated. Their efficacy in recovering viral ribonucleic acid and removal of PCR inhibitors was assessed using two South Australian wastewater matrices-one from a major metropolitan site and one from a regional centre. Both had SARS-CoV-2 present due to active COVID-19 cases in these communities. Overall, the MM kit had a higher recovery of SARS-CoV-2 from the samples tested, followed by PMB and PS. The PMB kit performance was strongly influenced by the sample matrix when compared to the MM kit. It is recommended to assess the performance of extraction kits using different local wastewater matrices to ensure the accuracy and reliability of monitoring results to avoid false reporting.

Antibiotic resistance in wastewater: Indian scenario

The surge of Antibiotic Resistant Bacteria (ARB) in the environment is poised to be the next health threat. World Health Organisation's (WHO's) Global Antimicrobial Surveillance System (GLASS) report indicates that developing countries may be at a greater risk. Among various factors, the major driver here could be untreated wastewater and poor sanitation. Bacteria are extremely adaptable to their surroundings and develop Antimicrobial Resistance (AMR) when exposed to antibiotics and other pollutants that cause microbial stress. Thus, untreated domestic wastewater drains could easily become hotspots for the occurrence of ARBs. This study reports surveillance of sewage-carrying drains across four urban cities in India and demonstrated the presence of ARBs in the bacterial community against 7 classes of antibiotics, namely, β-Lactams, Chloramphenicol, Glycopeptides, Macrolides, Tetracycline, Third Generation Cephalosporin, and Quinolones. Untreated domestic wastewater flowing in target drains was collected twice a month, for a period of six months and the microbial community was subjected to Antibiotic Susceptibility Testing (AST) by plate assays. The zone of inhibition was recorded and interpreted as per the interpretive chart of The Clinical & Laboratory Standards Institute (CLSI) & The European Committee on Antimicrobial Susceptibility Testing (EUCAST). The total number of samples showing resistance against antibiotics was used to define an Antibiotic Resistance Index (ARI), calculated for all 20 sampling sites (drains). Results demonstrated that the highest ARI was observed in Delhi and Mumbai, ranging from 0.81 to 0.92 in Delhi and 0.49–0.56 in Mumbai. This surveillance study reveals the antibiotic resistance pattern of the representative bacterial community in the drains and goes beyond few targeted bacterial species. The alarming presence of antibiotic resistant bacterial community highlights the concern of ARBs being the next looming health threat. This report aims to demonstrates the importance of considering sewage surveillance on routine basis by state authorities.

Circulation of SARS-CoV-2 Omicron sub-lineages revealed by multiplex genotyping RT-qPCR assays for sewage surveillance

Sewage surveillance has proven to be an essential complementary tool to clinical diagnosis in combating the COVID-19 pandemic by tracking the spread of the SARS-CoV-2 virus and evaluating infection levels in populations. With the striking spreading and continuous evolution of SARS-CoV-2 Omicron VOC that characterized with higher transmissibility and potential immune evasion, there is an urgent need for the rapid surveillance of this prevalent strain and its sub-lineages in sewage. In this study, based on three multiplex allele-specific (AS) RT-qPCR assays, we established a rapid and high-throughput detection workflow for the simultaneous discrimination of Omicron sub-lineages BA.2.2, BA.2.12.1, BA.4 and BA.5 (hereafter referred to as BA.4/BA.5) to track their community circulation in Hong Kong. All primer-probe sets in the multiplex assays could correctly discriminate and quantitate their target genotypes with high sensitivity and specificity, even when multiple variants co-existed in the sewage samples. Using the established multiplex assays, the trends of SARS-CoV-2 total viral load and variant dynamics in influent samples collected from 11 wastewater treatment plants (WWTPs) during June 2022 and September 2022, aligned with the clinical data, successfully unveiling the swift emergence and predominance of Omicron BA.4/BA.5 in Hong Kong. The study highlights the feasibility and applicability of multiplex RT-qPCR assays for monitoring epidemic trends and tracking variant displacement dynamics in sewage samples, providing a more rapid, high-throughput and cost-effective alternative to enhance the current sewage surveillance system.

Interactive SARS-CoV-2 dashboard for real-time geospatial visualisation of sewage and clinical surveillance data from Dhaka, Bangladesh: a tool for public health situational awareness.

Throughout the COVID-19 pandemic, many dashboards were created to visualise clinical case incidence. Other dashboards have displayed SARS-CoV-2 sewage data, largely from countries with formal sewage networks. However, very few dashboards from low-income and lower-middle-income countries integrated both clinical and sewage data sets. We created a dashboard to track in real-time both COVID-19 clinical cases and the level of SARS-CoV-2 virus in sewage in Dhaka, Bangladesh. The development of this dashboard was a collaborative iterative process with Bangladesh public health stakeholders to include specific features to address their needs. The final dashboard product provides spatiotemporal visualisations of COVID-19 cases and SARS-CoV-2 viral load at 51 sewage collection sites in 21 wards in Dhaka since 24 March 2020. Our dashboard was updated weekly for the Bangladesh COVID-19 national task force to provide supplemental data for public health stakeholders making public policy decisions on mitigation efforts. Here, we highlight the importance of working closely with public health stakeholders to create a COVID-19 dashboard for public health impact. In the future, the dashboard can be expanded to track trends of other infectious diseases as sewage surveillance is increased for other pathogens.

POTENTIAL OF SEWAGE SURVEILLANCE IN EARLY DETECTION OF COVID-19

In the prevailing pandemic, recognizing and eventually isolating infected people is the need of the hour. Present testing methods tend to take their share of time to identify positive samples, then the authorities initiate communication with infected persons, and necessary precautions are taken. This process takes time, keeping the target person to be an individual, but where we need to get a broad idea of the virus spread in a community, a suitable, effective, and efficient method should be applied, which brings us to sewage surveillance for COVID-19 spread. The concept of mass sewage surveillance for a check on epidemics supports the requirement of individual testing and suggests potential hotspots. Sewage samples taken up from a community are tested on common testing platforms, and their results can give a bigger picture of the infection in that particular community. Other infections, such as polio, have been effectively detected via sewage testing. Several studies related to this methodology have been coming up recently, making sewage samples a source of testing rather than individual testing. It saves time and effort, and eventually, we move towards better governance in public health. This review paper looks at the various studies done under sewage surveillance in different parts of the world, emphasizing their critical points.

Patterns of SARS-CoV-2 circulation revealed by a nationwide sewage surveillance programme, the Netherlands, August 2020 to February 2022.

BackgroundSurveillance of SARS-CoV-2 in wastewater offers a near real-time tool to track circulation of SARS-CoV-2 at a local scale. However, individual measurements of SARS-CoV-2 in sewage are noisy, inherently variable and can be left-censored.AimWe aimed to infer latent virus loads in a comprehensive sewage surveillance programme that includes all sewage treatment plants (STPs) in the Netherlands and covers 99.6% of the Dutch population.MethodsWe applied a multilevel Bayesian penalised spline model to estimate time- and STP-specific virus loads based on water flow-adjusted SARS-CoV-2 qRT-PCR data for one to four sewage samples per week for each of the more than 300 STPs.ResultsThe model captured the epidemic upsurges and downturns in the Netherlands, despite substantial day-to-day variation in the measurements. Estimated STP virus loads varied by more than two orders of magnitude, from ca 1012 virus particles per 100,000 persons per day in the epidemic trough in August 2020 to almost 1015 per 100,000 in many STPs in January 2022. The timing of epidemics at the local level was slightly shifted between STPs and municipalities, which resulted in less pronounced peaks and troughs at the national level.ConclusionAlthough substantial day-to-day variation is observed in virus load measurements, wastewater-based surveillance of SARS-CoV-2 that is performed at high sampling frequency can track long-term progression of an epidemic at a local scale in near real time.