Computational analysis of SARS-CoV-2/COVID-19 surveillance by wastewater-based epidemiology locally and globally: Feasibility, economy, opportunities and challenges

Structured Ethical Review for Wastewater-Based Testing in Support of Public Health

Wastewater-based testing (WBT) for SARS-CoV-2 has rapidly expanded over the past three years due to its ability to provide a comprehensive measurement of disease prevalence independent of clinical testing. The development and simultaneous application of WBT measured biomarkers for research activities and for the pursuit of public health goals, both areas with well-established ethical frameworks. Currently, WBT practitioners do not employ a standardized ethical review process, introducing the potential for adverse outcomes for WBT professionals and community members. To address this deficiency, an interdisciplinary workshop developed a framework for a structured ethical review of WBT. The workshop employed a consensus approach to create this framework as a set of 11 questions derived from primarily public health guidance. This study retrospectively applied these questions to SARS-CoV-2 monitoring programs covering the emergent phase of the pandemic (3/2020-2/2022 (n = 53)). Of note, 43% of answers highlight a lack of reported information to assess. Therefore, a systematic framework would at a minimum structure the communication of ethical considerations for applications of WBT. Consistent application of an ethical review will also assist in developing a practice of updating approaches and techniques to reflect the concerns held by both those practicing and those being monitored by WBT supported programs.

Economic Evaluation of Wastewater Surveillance Combined with Clinical COVID-19 Screening Tests, Japan

The COVID-19 pandemic has imposed substantial burdens on the global society. To find an optimal combination of wastewater surveillance and clinical testing for tracking COVID-19, we evaluated the economic efficiency of hypothetical screening options at a single facility in Japan. To conduct cost-benefit analyses, we developed standard decision models in which we assumed model parameters from literature and primary data, such as screening policies used at the Tokyo Olympic and Paralympic Village in 2021. We compared hypothetical 2-step screening options that used clinical PCR to diagnose COVID-19 after a positive result from primary screening using antigen tests (option 1) or wastewater surveillance (option 2). Our simulation results indicated that option 2 likely would be economically more justifiable than option 1, particularly at lower incidence levels. Our findings could help justify and promote the use of wastewater surveillance as a primary screening at a facility level for COVID-19 and other infectious diseases.

Targeting a free viral fraction enhances the early alert potential of wastewater surveillance for SARS-CoV-2: a methods comparison spanning the transition between delta and omicron variants in a large urban center

Introduction

Wastewater surveillance has proven to be a valuable approach to monitoring the spread of SARS-CoV-2, the virus that causes Coronavirus disease 2019 (COVID-19). Recognizing the benefits of wastewater surveillance as a tool to support public health in tracking SARS-CoV-2 and other respiratory pathogens, numerous wastewater virus sampling and concentration methods have been tested for appropriate applications as well as their significance for actionability by public health practices.

Methods

Here, we present a 34-week long wastewater surveillance study that covers nearly 4 million residents of the Detroit (MI, United States) metropolitan area. Three primary concentration methods were compared with respect to recovery of SARS-CoV-2 from wastewater: Virus Adsorption-Elution (VIRADEL), polyethylene glycol precipitation (PEG), and polysulfone (PES) filtration. Wastewater viral concentrations were normalized using various parameters (flow rate, population, total suspended solids) to account for variations in flow. Three analytical approaches were implemented to compare wastewater viral concentrations across the three primary concentration methods to COVID-19 clinical data for both normalized and non-normalized data: Pearson and Spearman correlations, Dynamic Time Warping (DTW), and Time Lagged Cross Correlation (TLCC) and peak synchrony.

Results

It was found that VIRADEL, which captures free and suspended virus from supernatant wastewater, was a leading indicator of COVID-19 cases within the region, whereas PEG and PES filtration, which target particle-associated virus, each lagged behind the early alert potential of VIRADEL. PEG and PES methods may potentially capture previously shed and accumulated SARS-CoV-2 resuspended from sediments in the interceptors.

Discussion

These results indicate that the VIRADEL method can be used to enhance the early-warning potential of wastewater surveillance applications although drawbacks include the need to process large volumes of wastewater to concentrate sufficiently free and suspended virus for detection. While lagging the VIRADEL method for early-alert potential, both PEG and PES filtration can be used for routine COVID-19 wastewater monitoring since they allow a large number of samples to be processed concurrently while being more cost-effective and with rapid turn-around yielding results same day as collection.

Measurement of SARS-CoV-2 RNA in wastewater: A case study of the Northern Cape, South Africa

The SARS-CoV-2 pandemic has resulted in the infection and death of many South Africans. This is in part due to a lack of testing facilities, equipment, and staff in many areas, particularly those with low population densities. The study focused on the infection dynamics of the virus in the Northern Cape province in all five municipalities investigating wastewater-based surveillance for the province. Reverse transcription was used to identify the virus, and SARS-CoV-2 RNA was detected in a batch of wastewater from four of the five areas sampled and was collected in the months that fall within the third wave of COVID as well as the winter season (May-July). The detection of the SARS-CoV-2 RNA correlated with infection statistics as well as the seasonality of the virus. This research showed a positive result in using wastewater epidemiology to track the spread of the virus but also highlighted the need for improved methodology when it comes to this surveillance. This includes sampling smaller areas and frequent sampling in multiple areas to show clear patterns within smaller, sparsely populated communities.

Evaluating the theoretical performance of aircraft wastewater monitoring as a tool for SARS-CoV-2 surveillance

Air travel plays an important role in the cross-border spread of infectious diseases. During the SARS-CoV-2 pandemic many countries introduced strict border testing protocols to monitor the incursion of the virus. However, high implementation costs and significant inconvenience to passengers have led public health authorities to consider alternative methods of disease surveillance at borders. Aircraft wastewater monitoring has been proposed as one such alternative. In this paper we assess the theoretical limits of aircraft wastewater monitoring and compare its performance to post-arrival border screening approaches. Using an infectious disease model, we simulate an unmitigated SARS-CoV-2 epidemic originating in a seed country and spreading to the United Kingdom (UK) through daily flights. We use a probabilistic approach to estimate the time of first detection in the UK in aircraft wastewater and respiratory swab screening. Across a broad range of model parameters, our analysis indicates that the median time between the first incursion and detection in wastewater would be approximately 17 days (IQR: 7-28 days), resulting in a median of 25 cumulative cases (IQR: 6-84 cases) in the UK at the point of detection. Comparisons to respiratory swab screening suggest that aircraft wastewater monitoring is as effective as random screening of 20% of passengers at the border, using a test with 95% sensitivity. For testing regimes with sensitivity of 85% or less, the required coverage to outperform wastewater monitoring increases to 30%. Analysis of other model parameters suggests that wastewater monitoring is most effective when used on long-haul flights where probability of defecation is above 30%, and when the target pathogen has high faecal shedding rates and reasonable detectability in wastewater. These results demonstrate the potential use cases of aircraft wastewater monitoring and its utility in a wider system of public health surveillance.

Stabilization of SARS-CoV-2 RNA in wastewater via rapid RNA extraction

Wastewater-based Epidemiology (WBE) has contributed to surveillance of SARS-CoV-2 in communities across the world. Both symptomatic and asymptomatic patients with COVID-19 can shed the virus through the gastrointestinal tract, enabling the quantification of the virus in stool and ultimately in wastewater (WW). Unfortunately, instability of SARS-CoV-2 RNA in wastewater limits the utility of WBE programs, particularly in remote/rural regions where reliable cold storage and/or rapid shipping may be unavailable. This study examined whether rapid SARS-CoV-2 RNA extraction on the day of sample collection could minimize degradation. Importantly, the extraction technology used in these experiments, termed exclusion-based sample preparation (ESP), is lightweight, portable, and electricity-free, making it suitable for implementation in remote settings. We demonstrated that immediate RNA extraction followed by ambient storage significantly increased the RNA half-life compared to raw wastewater samples stored at both 4 °C or ambient temperature. Given that RNA degradation negatively impacts both the sensitivity and precision of WBE measurements, efforts must be made to mitigate degradation in order to maximize the potential impact of WBE on public health.

Structured Ethical Review for Wastewater-Based Testing

Wastewater-based testing (WBT) for SARS-CoV-2 has rapidly expanded over the past three years due to its ability to provide a comprehensive measurement of disease prevalence independent of clinical testing. The development and simultaneous application of the field blurred the boundary between measuring biomarkers for research activities and for pursuit of public health goals, both areas with well-established ethical frameworks. Currently, WBT practitioners do not employ a standardized ethical review process (or associated data management safeguards), introducing the potential for adverse outcomes for WBT professionals and community members. To address this deficiency, an interdisciplinary group developed a framework for a structured ethical review of WBT. The workshop employed a consensus approach to create this framework as a set of 11-questions derived from primarily public health guidance because of the common exemption of wastewater samples to human subject research considerations. This study retrospectively applied the set of questions to peer- reviewed published reports on SARS-CoV-2 monitoring campaigns covering the emergent phase of the pandemic from March 2020 to February 2022 (n=53). Overall, 43% of the responses to the questions were unable to be assessed because of lack of reported information. It is therefore hypothesized that a systematic framework would at a minimum improve the communication of key ethical considerations for the application of WBT. Consistent application of a standardized ethical review will also assist in developing an engaged practice of critically applying and updating approaches and techniques to reflect the concerns held by both those practicing and being monitored by WBT supported campaigns.

Abstract Figure

Synopsis

Development of a structured ethical review facilitates retrospective analysis of published studies and drafted scenarios in the context of wastewater-based testing.

Prolonged viral shedding from noninfectious individuals confounds wastewater-based epidemiology

Wastewater surveillance has been widely used to track and estimate SARS-CoV-2 incidence. While both infectious and recovered individuals shed virus into wastewater, epidemiological inferences using wastewater often only consider the viral contribution from the former group. Yet, the persistent shedding in the latter group could confound wastewater-based epidemiological inference, especially during the late stage of an outbreak when the recovered population outnumbers the infectious population. To determine the impact of recovered individuals' viral shedding on the utility of wastewater surveillance, we develop a quantitative framework that incorporates population-level viral shedding dynamics, measured viral RNA in wastewater, and an epidemic dynamic model. We find that the viral shedding from the recovered population can become higher than the infectious population after the transmission peak, which leads to a decrease in the correlation between wastewater viral RNA and case report data. Furthermore, the inclusion of recovered individuals' viral shedding into the model predicts earlier transmission dynamics and slower decreasing trends in wastewater viral RNA. The prolonged viral shedding also induces a potential delay in the detection of new variants due to the time needed to generate enough new cases for a significant viral signal in an environment dominated by virus shed by the recovered population. This effect is most prominent toward the end of an outbreak and is greatly affected by both the recovered individuals' shedding rate and shedding duration. Our results suggest that the inclusion of viral shedding from non-infectious recovered individuals into wastewater surveillance research is important for precision epidemiology.

SARS-CoV-2 wastewater-based epidemiology in an enclosed compound: A 2.5-year survey to identify factors contributing to local community dissemination

Long-term (>2.5 years) surveillance of SARS-CoV-2 RNA concentrations in wastewater was conducted within an enclosed university compound. This study aims to demonstrate how coupling wastewater-based epidemiology (WBE) with meta-data can identify which factors contribute toward the dissemination of SARS-CoV-2 within a local community. Throughout the pandemic, the temporal dynamics of SARS-CoV-2 RNA concentrations were tracked by quantitative polymerase chain reaction and analyzed in the context of the number of positive swab cases, the extent of human movement, and intervention measures. Our findings suggest that during the early phase of the pandemic, when strict lockdown was imposed, the viral titer load in the wastewater remained below detection limits, with <4 positive swab cases reported over a 14-day period in the compound. After the lockdown was lifted and global travel gradually resumed, SARS-CoV-2 RNA was first detected in the wastewater on 12 August 2020 and increased in frequency thereafter, despite high vaccination rates and mandatory face-covering requirements in the community. Accompanied by a combination of the Omicron surge and significant global travel by community members, SARS-CoV-2 RNA was detected in most of the weekly wastewater samples collected in late December 2021 and January 2022. With the cease of mandatory face covering, SARS-CoV-2 was detected in at least two of the four weekly wastewater samples collected from May through August 2022. Retrospective Nanopore sequencing revealed the presence of the Omicron variant in the wastewater with a multitude of amino acid mutations, from which we could infer the likely geographical origins through bioinformatic analysis. This study demonstrated that long-term tracking of the temporal dynamics and sequencing of variants in wastewater would aid in identifying which factors contribute the most to SARS-CoV-2 dissemination within the local community, facilitating an appropriate public health response to control future outbreaks as we now live with endemic SARS-CoV-2.

Co-incidence of BA.1 and BA.2 at the start of Singapore's Omicron wave revealed by Community and University Campus wastewater surveillance

Wastewater surveillance (WWS) has been globally recognised to be a useful tool in quantifying SARS-CoV-2 RNA at the community and residential levels without biases associated with case-reporting. The emergence of variants of concern (VOCs) have given rise to an unprecedented number of infections even though populations are increasingly vaccinated. This is because VOCs have been reported to possess higher transmissibility and can evade host immune responses. The B.1.1.529 lineage (Omicron) has severely disrupted global plans to return to normalcy. In this study, we developed an allele-specific (AS) RT-qPCR assay which simultaneously targets the stretch of deletions and mutations in the spike protein from position 24-27 for quantitative detection of Omicron BA.2. Together with previous assays that detect mutations associated with Omicron BA.1 (deletion at position 69 and 70) and all Omicron (mutation at position 493 and 498), we report the validation and time series of these assays from September 2021 to May 2022 using influent samples from two wastewater treatment plants and across four University campus sites in Singapore. Viral RNA concentrations at the treatment plants corroborate with locally reported clinical cases, AS RT-qPCR assays revealed co-incidence of Omicron BA.1 and BA.2 on 12 January 2022, almost two months after initial BA.1 detection in South Africa and Botswana. BA.2 became the dominant variant by the end of January 2022 and completely displaced BA.1 by mid-March 2022. University campus sites were similarly positive for BA.1 and/or BA.2 in the same week as first detection at the treatment plants, where BA.2 became rapidly established as the dominant lineage within three weeks. These results corroborate clinical incidence of the Omicron lineages in Singapore and indicate minimal silent circulation prior to January 2022. The subsequent simultaneous spread of both variant lineages followed strategic relaxation of safe management measures upon meeting nationwide vaccination goals.

Assessment of virus concentration methods for detecting SARS-CoV-2 IN wastewater

Wastewater-based epidemiology has been described as a valuable tool for monitoring the spread of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in a community. However, there is no consensus on the best concentration method to allow reliable detection of SARS-CoV-2 in this matrix, considering different laboratory facilities. This study compares two viral concentration methods, ultracentrifugation (ULT) and skimmed-milk flocculation (SMF), for detecting SARS-CoV-2 in wastewater samples. The analytical sensitivity (limits of detection and quantification [LoD/LoQ]) of both methods was evaluated using a bovine respiratory syncytial virus (BRSV) as a surrogate. Three different approaches were conducted to establish LoD of each method based on the assays on the standard curve (ALoDsc), on the dilution of internal control (ALoDiC), and the processing steps (PLoD). For PLoD, ULT method had the lowest value (1.86 × 103 genome copy/microliter [GC/µL]) when compared to the SMF method (1.26 × 107 GC/µL). The LoQ determination showed a mean value of 1.55 × 105 GC/µL and 3.56 × 108 GC/µL to ULT and SMF, respectively. The detection of SARSCoV-2 in naturally contaminated wastewater revealed 100% (12/12) and 25% (3/12) of detection using ULT and SMF with quantification ranging from 5.2 to 7.2 log10 genome copy/liter (GC/L) and 5.06 to 5.46 log10 GC/L, respectively. The detection success rate of BRSV used as an internal control process was 100% (12/12) for ULT and 67% (8/12) for SMF, with an efficiency recovery rate ranging from 12 to 38% and 0.1 to 5%, respectively. Our data consolidates the importance of assessing the methods used; however, further analysis should be carried out to improve low-cost concentration methodologies, essential for use in low-income and developing countries.

Wastewater monitoring for detection of public health markers during the COVID-19 pandemic: Near-source monitoring of schools in England over an academic year

BACKGROUND

Schools are high-risk settings for infectious disease transmission. Wastewater monitoring for infectious diseases has been used to identify and mitigate outbreaks in many near-source settings during the COVID-19 pandemic, including universities and hospitals but less is known about the technology when applied for school health protection. This study aimed to implement a wastewater surveillance system to detect SARS-CoV-2 and other public health markers from wastewater in schools in England.

METHODS

A total of 855 wastewater samples were collected from 16 schools (10 primary, 5 secondary and 1 post-16 and further education) over 10 months of school term time. Wastewater was analysed for SARS-CoV-2 genomic copies of N1 and E genes by RT-qPCR. A subset of wastewater samples was sent for genomic sequencing, enabling determination of the presence of SARS-CoV-2 and emergence of variant(s) contributing to COVID-19 infections within schools. In total, >280 microbial pathogens and >1200 AMR genes were screened using RT-qPCR and metagenomics to consider the utility of these additional targets to further inform on health threats within the schools.

RESULTS

We report on wastewater-based surveillance for COVID-19 within English primary, secondary and further education schools over a full academic year (October 2020 to July 2021). The highest positivity rate (80.4%) was observed in the week commencing 30th November 2020 during the emergence of the Alpha variant, indicating most schools contained people who were shedding the virus. There was high SARS-CoV-2 amplicon concentration (up to 9.2x106 GC/L) detected over the summer term (8th June - 6th July 2021) during Delta variant prevalence. The summer increase of SARS-CoV-2 in school wastewater was reflected in age-specific clinical COVID-19 cases. Alpha variant and Delta variant were identified in the wastewater by sequencing of samples collected from December to March and June to July, respectively. Lead/lag analysis between SARS-CoV-2 concentrations in school and WWTP data sets show a maximum correlation between the two-time series when school data are lagged by two weeks. Furthermore, wastewater sample enrichment coupled with metagenomic sequencing and rapid informatics enabled the detection of other clinically relevant viral and bacterial pathogens and AMR.

CONCLUSIONS

Passive wastewater monitoring surveillance in schools can identify cases of COVID-19. Samples can be sequenced to monitor for emerging and current variants of concern at the resolution of school catchments. Wastewater based monitoring for SARS-CoV-2 is a useful tool for SARS-CoV-2 passive surveillance and could be applied for case identification and containment, and mitigation in schools and other congregate settings with high risks of transmission. Wastewater monitoring enables public health authorities to develop targeted prevention and education programmes for hygiene measures within undertested communities across a broad range of use cases.

Prediction of hospitalisations based on wastewater-based SARS-CoV-2 epidemiology

Wastewater-based epidemiology is widely applied in Austria since April 2020 to monitor the SARS-CoV-2 pandemic. With a steadily increasing number of monitored wastewater facilities, 123 plants covering roughly 70 % of the 9 million population were monitored as of August 2022. In this study, the SARS-CoV-2 viral concentrations in raw sewage were analysed to infer short-term hospitalisation occupancy. The temporal lead of wastewater-based epidemiological time series over hospitalisation occupancy levels facilitates the construction of forecast models. Data pre-processing techniques are presented, including the approach of comparing multiple decentralised wastewater signals with aggregated and centralised clinical data. Time‑lead quantification was performed using cross-correlation analysis and coefficient of determination optimisation approaches. Multivariate regression models were successfully applied to infer hospitalisation bed occupancy. The results show a predictive potential of viral loads in sewage towards Covid-19 hospitalisation occupancy, with an average lead time towards ICU and non-ICU bed occupancy between 14.8-17.7 days and 8.6-11.6 days, respectively. The presented procedure provides access to the trend and tipping point behaviour of pandemic dynamics and allows the prediction of short-term demand for public health services. The results showed an increase in forecast accuracy with an increase in the number of monitored wastewater treatment plants. Trained models are sensitive to changing variant types and require recalibration of model parameters, likely caused by immunity by vaccination and/or infection. The utilised approach displays a practical and rapidly implementable application of wastewater-based epidemiology to infer hospitalisation occupancy.

Detection of BK and JC polyomaviruses in sewage water of the urban areas of Lahore, Pakistan

The surveillance of sewage water has become an extremely essential tool to trace the circulation of viruses in a population and to predict the outbreak of viral diseases. Sewage monitoring is important for those viruses which cause subclinical infections since it is difficult to determine their prevalence. Polyomaviruses are ubiquitously present, circular double-stranded DNA viruses that can infect humans as well. Among all human polyomaviruses, BK polyomavirus and JC polyomavirus associated with the development of aggressive diseases in immunocompromised individuals, are highly prevalent. This study aimed to investigate the presence and the quantitative prevalence of these two disease-associated human polyomaviruses in sewage water collected from six drains of Lahore, Pakistan. The viruses present in the environmental samples were concentrated by PEG method before isolating viral nucleic acids. Conventional PCR amplifications were performed for molecular detection of BK polyomavirus and JC polyomavirus targeting their large tumor antigen genetic region. The presence of BK polyomavirus and JC polyomavirus was confirmed in the DNA extracted from concentrated sewage samples of each drain by performing both qualitative and quantitative PCR. Our data shows that the viral load ranged from 1278 to 178368 copies per µg of environmental DNA for BK polyomavirus and 5173 to 79129 copies per µg of environmental DNA for JC polyomavirus. In conclusion, here we report first time the detection of BK polyomavirus and JC polyomavirus in sewage water collected from six main drains in urban areas of Lahore, Pakistan showing the high prevalence of these viruses in the Pakistani population. This assay could be used as a proxy to determine the prevalence of these viruses in the Pakistani population.

Optimised protocol for monitoring SARS-CoV-2 in wastewater using reverse complement PCR-based whole-genome sequencing

Monitoring the spread of viral pathogens in the population during epidemics is crucial for mounting an effective public health response. Understanding the viral lineages that constitute the infections in a population can uncover the origins and transmission patterns of outbreaks and detect the emergence of novel variants that may impact the course of an epidemic. Population-level surveillance of viruses through genomic sequencing of wastewater captures unbiased lineage data, including cryptic asymptomatic and undiagnosed infections, and has been shown to detect infection outbreaks and novel variant emergence before detection in clinical samples. Here, we present an optimised protocol for quantification and sequencing of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in influent wastewater, used for high-throughput genomic surveillance in England during the COVID-19 pandemic. This protocol utilises reverse compliment PCR for library preparation, enabling tiled amplification across the whole viral genome and sequencing adapter addition in a single step to enhance efficiency. Sequencing of synthetic SARS-CoV-2 RNA provided evidence validating the efficacy of this protocol, while data from high-throughput sequencing of wastewater samples demonstrated the sensitivity of this method. We also provided guidance on the quality control steps required during library preparation and data analysis. Overall, this represents an effective method for high-throughput sequencing of SARS-CoV-2 in wastewater which can be applied to other viruses and pathogens of humans and animals.

What data counts in policymaking and programming evaluation - Relevant data sources for triangulation according to main epistemologies and philosophies within social science

Policy analysis and program evaluation quality guides how impact is measured, revisions are made, and allocations of resources is deployed. As interdisciplinary research grows in contemporary policy science, the importance of defining truth can be contentious among different social scientists. This research traces the history of triangulation to its contemporary version within the social sciences. The study examines the philosophical evolution influencing the environment in which triangulation develops including: consilience and the comparative linguistic structure of the traditions of thought; and the historical development of methods and emergence of triangulation in research. It also offers contrasting interpretations of triangulation within the various epistemologies and philosophies of science that have arisen in recent movements within social science. As research strives to address novel 21st century issues including big data, pandemics, misinformation, and globalization, there is a need for rigorous social science and policy-based research to be aware of different interpretations of empirical data and valid research methods across disciplines, examine new and old phenomena using multi-method approaches, and validate data informing policy through methods of triangulation.

SARS-CoV-2 concentration in wastewater consistently predicts trends in COVID-19 case counts by at least two days across multiple WWTP scales

Wastewater surveillance of SARS-CoV-2 has proven instrumental in mitigating the spread of COVID-19 by providing an economical and equitable approach to disease surveillance. Here, we analyze the correlation of SARS-CoV-2 RNA in influents of seven wastewater plants (WWTPs) across the state of South Carolina with corresponding daily case counts to determine whether underlying characteristics of WWTPs and sewershed populations predict stronger correlations. The populations served by these WWTPs have varying social vulnerability and represent 24% of the South Carolina population. The study spanned 15 months from April 19, 2020, to July 1, 2021, which includes the administration of the first COVID-19 vaccines. SARS-CoV-2 RNA concentrations were measured by either reverse transcription quantitative PCR (RT-qPCR) or droplet digital PCR (RT-ddPCR). Although populations served and average flow rate varied across WWTPs, the strongest correlation was identified for six of the seven WWTPs when daily case counts were lagged two days after the measured SARS-CoV-2 RNA concentration in wastewater. The weakest correlation was found for WWTP 6, which had the lowest ratio of population served to average flow rate, indicating that the SARS-CoV-2 signal was too dilute for a robust correlation. Smoothing daily case counts by a 7-day moving average improved correlation strength between case counts and SARS-CoV-2 RNA concentration in wastewater while dampening the effect of lag-time optimization. Correlation strength between cases and SARS-CoV-2 RNA was compared for cases determined at the ZIP-code and sewershed levels. The strength of correlations using ZIP-code-level versus sewershed-level cases were not statistically different across WWTPs. Results indicate that wastewater surveillance, even without normalization to fecal indicators, is a strong predictor of clinical cases by at least two days, especially when SARS-CoV-2 RNA is measured using RT-ddPCR. Furthermore, the ratio of population served to flow rate may be a useful metric to assess whether a WWTP is suitable for a surveillance program.

Degradation rates influence the ability of composite samples to represent 24-hourly means of SARS-CoV-2 and other microbiological target measures in wastewater

The utility of using severe-acute respiratory syndrome coronavirus-2 (SARS-CoV-2) RNA for assessing the prevalence of COVID-19 within communities begins with the design of the sample collection program. The objective of this study was to assess the utility of 24-hour composites as representative samples for measuring multiple microbiological targets in wastewater, and whether normalization of SARS-CoV-2 by endogenous targets can be used to decrease hour to hour variability at different watershed scales. Two sets of experiments were conducted, in tandem with the same wastewater, with samples collected at the building, cluster, and community sewershed scales. The first set of experiments focused on evaluating degradation of microbiological targets: SARS-CoV-2, Simian Immunodeficiency Virus (SIV) - a surrogate spiked into the wastewater, plus human waste indicators of Pepper Mild Mottle Virus (PMMoV), Beta-2 microglobulin (B2M), and fecal coliform bacteria (FC). The second focused on the variability of these targets from samples, collected each hour on the hour. Results show that SARS-CoV-2, PMMoV, and B2M were relatively stable, with minimal degradation over 24-h. SIV, which was spiked-in prior to analysis, degraded significantly and FC increased significantly over the course of 24 h, emphasizing the possibility for decay and growth within wastewater. Hour-to-hour variability of the source wastewater was large between each hour of sampling relative to the variability of the SARS-CoV-2 levels calculated between sewershed scales; thus, differences in SARS-CoV-2 hourly variability were not statistically significant between sewershed scales. Results further provided that the quantified representativeness of 24-h composite samples (i.e., statistical equivalency compared against hourly collected grabs) was dependent upon the molecular target measured. Overall, improvements made by normalization were minimal within this study. Degradation and multiplication for other targets should be evaluated when deciding upon whether to collect composite or grab samples in future studies.

SARS-CoV-2 Variants Detection Strategies in Wastewater Samples Collected in the Bangkok Metropolitan Region

Wastewater surveillance is considered a promising approach for COVID-19 surveillance in communities. In this study, we collected wastewater samples between November 2020 and February 2022 from twenty-three sites in the Bangkok Metropolitan Region to detect the presence of SARS-CoV-2 and its variants for comparison to standard clinical sampling. A total of 215 wastewater samples were collected and tested for SARS-CoV-2 RNA by real-time PCR with three targeted genes (N, E, and ORF1ab); 102 samples were positive (42.5%). The SARS-CoV-2 variants were determined by a multiplex PCR MassARRAY assay to distinguish four SARS-CoV-2 variants, including Alpha, Beta, Delta, and Omicron. Multiple variants of Alpha-Delta and Delta-Omicron were detected in the wastewater samples in July 2021 and January 2022, respectively. These wastewater variant results mirrored the country data from clinical specimens deposited in GISAID. Our results demonstrated that wastewater surveillance using multiple signature mutation sites for SARS-CoV-2 variant detection is an appropriate strategy to monitor the presence of SARS-CoV-2 variants in the community at a low cost and with rapid turn-around time. However, it is essential to note that sequencing surveillance of wastewater samples should be considered complementary to whole genome sequencing of clinical samples to detect novel variants.

Wastewater-based epidemiology for preventing outbreaks and epidemics in Latin America - Lessons from the past and a look to the future

Wastewater-based epidemiology (WBE) is an approach with the potential to complement clinical surveillance systems. Using WBE, it is possible to carry out an early warning of a possible outbreak, monitor spatial and temporal trends of infectious diseases, produce real-time results and generate representative epidemiological information in a territory, especially in areas of social vulnerability. Despite the historical uses of this approach, particularly in the Global Polio Eradication Initiative, and for other pathogens, it was during the COVID-19 pandemic that occurred an exponential increase in environmental surveillance programs for SARS-CoV-2 in wastewater, with many experiences and developments in the field of public health using data for decision making and prioritizing actions to control the pandemic. In Latin America, WBE was applied in heterogeneous contexts and with emphasis on populations that present many socio-environmental inequalities, a condition shared by all Latin American countries. This manuscript addresses the concepts and applications of WBE in public health actions, as well as different experiences in Latin American countries, and discusses a model to implement this surveillance system at the local or national level. We emphasize the need to implement this sentinel surveillance system in countries that want to detect the early entry and spread of new pathogens and monitor outbreaks or epidemics of infectious agents in their territories as a complement of public health surveillance systems.

Norovirus, Hepatitis A and SARS-CoV-2 surveillance within Chilean rural wastewater treatment plants based on different biological treatment typologies

During the COVID-19 pandemic, wastewater from WWTPs became an interesting source of epidemiological surveillance. However, there is uncertainty about the influence of treatment type on virus removal. The aim of this study was to assess viral surveillance within wastewater treatment plants (WWTPs) based on different biological treatments. Seasonal monitoring (autumn-winter and spring-summer) was conducted in 10 Chilean rural WWTPs, which were based on activated sludge, aerated lagoons, bio-discs, constructed wetlands, vermifilters and mixed systems. Viruses were measured (influent/effluent) by the RT-qPCR technique, using a commercial kit for SARS-CoV-2, NoV GI, NoV GII, and HAV. The detection of SARS-CoV-2 viral variants by genotyping was performed using SARS-CoV-2 Mutation Assays (ThermoFisher Scientific, USA). JC polyomavirus detection (control), as well as a qPCR technique. Results showed that SARS-CoV-2, NoV GI and GII were detected in influents at values between <5 and 462, 0 to 28, and 0 to 75 GC/mL, respectively. HAV was not detected among the studied WWTPs. The monitored WWTPs removed these viruses at percentages between 0 and 100 %. WWTPs based on activated sludge with bio-discs demonstrated to be the most efficient at removing SARS-CoV-2 (up to 98 %) and NoV GI and GII (100 %). Meanwhile, bio-discs technologies were the least efficient for viral removal, due to biofilm detachment, which could also adsorb viral aggregates. A correlation analysis established that solids, pH, and temperature are the most influential parameters in viral removal. Wastewater-based surveillance at WWTP allowed for the detection of Omicron before the Chilean health authorities notified its presence in the population. In addition, surveillance of viruses and other microorganisms could help assess the potential public health risk of wastewater recycling.

Evaluation of intra- and inter-lab variability in quantifying SARS-CoV-2 in a state-wide wastewater monitoring network

In December 2019, SARS-CoV-2, the virus that causes coronavirus disease 2019, was first reported and subsequently triggered a global pandemic. Wastewater monitoring, a strategy for quantifying viral gene concentrations from wastewater influents within a community, has served as an early warning and management tool for the spread of SARS-CoV-2 in a community. Ohio built a collaborative statewide wastewater monitoring network that is supported by eight labs (university, government, and commercial laboratories) with unique sample processing workflows. Consequently, we sought to characterize the variability in wastewater monitoring results for network labs. Across seven trials between October 2020 and November 2021, eight participating labs successfully quantified two SARS-CoV-2 RNA targets and human fecal indicator virus targets in wastewater sample aliquots with reproducible results, although recovery efficiencies of spiked surrogates ranged from 3 to 75%. When SARS-CoV-2 gene fragment concentrations were adjusted for recovery efficiency and flow, the proportion of variance between laboratories was minimized, serving as the best model to account for between-lab variance. Another adjustment factor (alone and in different combinations with the above factors) considered to account for sample and measurement variability includes fecal marker normalization. Genetic quantification variability can be attributed to many factors, including the methods, individual samples, and water quality parameters. In addition, statistically significant correlations were observed between SARS-CoV-2 RNA and COVID-19 case numbers, supporting the notion that wastewater surveillance continues to serve as an effective monitoring tool. This study serves as a real-time example of multi-laboratory collaboration for public health preparedness for infectious diseases.

Number of COVID-19 cases required in a population to detect SARS-CoV-2 RNA in wastewater in the province of Alberta, Canada: Sensitivity assessment

With a unique and large size of testing results of 1,842 samples collected from 12 wastewater treatment plants (WWTP) for 14 months through from low to high prevalence of COVID-19, the sensitivity of RT-qPCR detection of SARS-CoV-2 RNA in wastewater that correspond to the communities was computed by using Probit analysis. This study determined the number of new COVID-19 cases per 100,000 population required to detect SARS-CoV-2 RNA in wastewater at defined probabilities and provided an evidence-based framework of wastewater-based epidemiology surveillance (WBE). Input data were positive and negative test results of SARS-CoV-2 RNA in wastewater samples and the corresponding new COVID-19 case rates per 100,000 population served by each WWTP. The analyses determined that RT-qPCR-based SARS-CoV-2 RNA detection threshold at 50%, 80% and 99% probability required a median of 8 (range: 4-19), 18 (9-43), and 38 (17-97) of new COVID-19 cases /100,000, respectively. Namely, the positive detection rate at 50%, 80% and 99% probability were 0.01%, 0.02%, and 0.04% averagely for new cases in the population. This study improves understanding of the performance of WBE SARS-CoV-2 RNA detection using the large datasets and prolonged study period. Estimated COVID-19 burden at a community level that would result in a positive detection of SARS-CoV-2 in wastewater is critical to support WBE application as a supplementary warning/monitoring system for COVID-19 prevention and control.

Sewershed surveillance as a tool for smart management of a pandemic in threshold countries. Case study: Tracking SARS-CoV-2 during COVID-19 pandemic in a major urban metropolis in northwestern Argentina

Wastewater-based epidemiology is an economical and effective tool for monitoring the COVID-19 pandemic. In this study we proposed sampling campaigns that addressed spatial-temporal trends within a metropolitan area. This is a local study of detection and quantification of SARS-CoV-2 in wastewater during the onset, rise, and decline of COVID-19 cases in Salta city (Argentina) over the course of a twenty-one-week period (13 Aug to 30 Dec) in 2020. Wastewater samples were gathered from 13 sewer manholes specific to each sewershed catchment, prior to convergence or mixing with other sewer lines, resulting in samples specific to individual catchments with defined areas. The 13 sewershed catchments selected comprise 118,832 connections to the network throughout the city, representing 84.7 % (534,747 individuals) of the total population. The number of COVID19-related exposure and symptoms cases in each area were registered using an application developed for smartphones by the provincial government. Geographical coordinates provided by the devices were recorded, and consequently, it was possible to geolocalise all app-cases and track them down to which of the 13 sampling catchments belonged. RNA fragments of SARS-CoV-2 were detected in every site since the beginning of the monitoring, anticipating viral circulation in the population. Over the course of the 21-week study, the concentrations of SARS-CoV-2 ranged between 1.77 × 104 and 4.35 × 107 genome copies/L. There was a correspondence with the highest viral load in wastewater and the peak number of cases reported by the app for each catchment. The associations were evaluated with correlation analysis. The viral loads of SARS-CoV-2 in wastewater were a feasible means to describe the trends of COVID-19 infections. Surveillance at sewershed scale, provided reliable and strategic information that could be used by local health stakeholders to manage the COVID-19 pandemic.

Baseline Sequencing Surveillance of Public Clinical Testing, Hospitals, and Community Wastewater Reveals Rapid Emergence of SARS-CoV-2 Omicron Variant of Concern in Arizona, USA

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

Strategies for safe management of hospital wastewater during the COVID-19 pandemic

Management of hospital wastewater is a challenging task, particularly during the situations like coronavirus 2019 (COVID-19) pandemic. The hospital effluent streams are likely to contain many known and unknown contaminants including severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) along with a variety of pollutants arising from pharmaceuticals, life-style chemicals, drugs, radioactive species, and human excreta from the patients. The effluents are a mixed bag of contaminants with some of them capable of infecting through contact. Hence, it is essential to identify appropriate treatment strategies for hospital waste streams. In this work, various pollutants emerging in the context of COVID-19 are examined. A methodical review is conducted on the occurrence and disinfection methods of SARS-CoV-2 in wastewater. An emphasis is given to the necessity of addressing the challenges of handling hospital effluents dynamically involved during the pandemic scenario to ensure human and environmental safety. A comparative evaluation of disinfection strategies makes it evident that the non-contact methods like ultraviolet irradiation, hydrogen peroxide vapor, and preventive approaches such as the usage of antimicrobial surface coating offer promise in reducing the chance of disease transmission. These methods are also highly efficient in comparison with other strategies. Chemical disinfection strategies such as chlorination may lead to further disinfection byproducts, complicating the treatment processes. An overall analysis of various disinfection methods is presented here, including developing methods such as membrane technologies, highlighting the merits and demerits of each of these processes. Finally, the wastewater surveillance adopted during the COVID-19 outbreak is discussed.

Supplementary Information

The online version contains supplementary material available at 10.1007/s13762-023-04803-1.

Occurrence and transport of SARS-CoV-2 in wastewater streams and its detection and remediation by chemical-biological methods

This paper explains the transmission of SARS-CoV and influences of several environmental factors in the transmission process. The article highlighted several methods of collection, sampling and monitoring/estimation as well as surveillance tool for detecting SARS-CoV in wastewater streams. In this context, WBE (Wastewater based epidemiology) is found to be the most effective surveillance tool. Several methods of genomic sequencing are discussed in the paper, which are applied in WBE, like qPCR-based wastewater testing, metagenomics-based analysis, next generation sequencing etc. Additionally, several types of biosensors (colorimetric biosensor, mobile phone-based biosensors, and nanomaterials-based biosensors) showed promising results in sensing SARS-CoV in wastewater. Further, this review paper outlined the gaps in assessing the factors responsible for transmission and challenges in detection and monitoring along with the remediation and disinfection methods of this virus in wastewater. Various methods of disinfection of SARS-CoV-2 in wastewater are discussed (primary, secondary, and tertiary phases) and it is found that a suite of disinfection methods can be used for complete disinfection/removal of the virus. Application of ultraviolet light, ozone and chlorine-based disinfectants are also discussed in the context of treatment methods. This study calls for continuous efforts to gather more information about the virus through continuous monitoring and analyses and to address the existing gaps and identification of the most effective tool/ strategy to prevent SARS-CoV-2 transmission. Wastewater surveillance can be very useful in effective surveillance of future pandemics and epidemics caused by viruses, especially after development of new technologies in detecting and disinfecting viral pathogens more effectively.

Waste management beyond the COVID-19 pandemic: Bibliometric and text mining analyses

The outbreak of the COVID-19 pandemic has significantly increased the demand for personal protective equipment, in particular face masks, thus leading to a huge amount of healthcare waste generated worldwide. Consequently, such an unprecedented amount of newly emerged waste has posed significant challenges to practitioners, policy-makers, and municipal authorities involved in waste management (WM) systems. This research aims at mapping the COVID-19-related scientific production to date in the field of WM. In this vein, the performance indicators of the target literature were analyzed and discussed through conducting a bibliometric analysis. The conceptual structure of COVID-19-related WM research, including seven main research themes, were uncovered and visualized through a text mining analysis as follows: (1) household and food waste, (2) personnel safety and training for waste handling, (3) sustainability and circular economy, (4) personal protective equipment and plastic waste, (5) healthcare waste management practices, (6) wastewater management, and (7) COVID-19 transmission through infectious waste. Finally, a research agenda for WM practices and activities in the post-COVID-19 era was proposed, focusing on the following three identified research gaps: (i) developing a systemic framework to properly manage the pandemic crisis implications for WM practices as a whole, following a systems thinking approach, (ii) building a circular economy model encompassing all activities from the design stage to the implementation stage, and (iii) proposing incentives to effectively involve informal sectors and local capacity in decentralizing municipal waste management, with a specific focus on developing and less-developed countries.

Wastewater-based epidemiology approach: The learning lessons from COVID-19 pandemic and the development of novel guidelines for future pandemics

Wastewater-based epidemiology (WBE) provides a comprehensive real-time framework of population attitude and health status. This approach is attracting the interest of medical community and health authorities to monitor the prevalence of a virus (such as the severe acute respiratory syndrome coronavirus 2, SARS-CoV-2) among a community. Indeed, WBE is currently fine-tuning as environmental surveillance tool for coronavirus disease 2019 (COVID-19) pandemic. After a bibliometric analysis conducted to discover the research trends in WBE field, this work aimed to side-by-side compare the conventional method based on clinical testing with WBE approach. Furthermore, novel guidelines were developed to apply the WBE approach to a pandemic. The growing interest on WBE approach for COVID-19 pandemic is demonstrated by looking at the sharp increase in scientific papers published in the last years and at the ongoing studies on viral quantification methods and analytical procedures. The side-by-side comparison highlighted the ability of WBE to identify the hot-spot areas faster than the conventional approach, reducing the costs (e.g., rational use of available resources) and the gatherings at medical centers. Contrary to clinical testing, WBE has the surveillance capacity for preventing the virus resurgence, including asymptomatic contribution, and ensuring the preservation of medical staff health by avoiding the exposure to the virus infection during clinical testing. As extensively reported, the time in collecting epidemiological data is crucial for establishing the prevention and mitigation measures that are essential for curbing a pandemic. The developed guidelines can help to build a WBE system useful to control any future pandemic.

SARS-CoV-2 removal with a polyurethane foam composite

The pandemic of COVID-19 (SARS-CoV-2 disease) has been causing unprecedented health and economic impacts, alerting the world to the importance of basic sanitation and existing social inequalities. The risk of the spread and appearance of new diseases highlights the need for the removal of these pathogens through efficient techniques and materials. This study aimed to develop a polyurethane (PU) biofoam filled with dregs waste (leftover from the pulp and paper industry) for removal SARS-CoV-2 from the water. The biofoam was prepared by the free expansion method with the incorporation of 5wt% of dregs as a filler. For the removal assays, the all materials and its isolated phases were incubated for 24 h with an inactivated SARS-CoV-2 viral suspension. Then, the RNA was extracted and the viral load was quantified using the quantitative reverse transcription (RT-qPCR) technique. The biofoam (polyurethane/dregs) reached a great removal percentage of 91.55%, whereas the isolated dregs waste was 99.03%, commercial activated carbon was 99.64%, commercial activated carbon/polyurethane was 99.30%, and neat PU foam reached was 99.96% for this same property and without statistical difference. Those new materials endowed with low cost and high removal efficiency of SARS-CoV-2 as alternatives to conventional adsorbents.

A simple SEIR-V model to estimate COVID-19 prevalence and predict SARS-CoV-2 transmission using wastewater-based surveillance data

Wastewater-based surveillance (WBS) has been widely used as a public health tool to monitor SARS-CoV-2 transmission. However, epidemiological inference from WBS data remains understudied and limits its application. In this study, we have established a quantitative framework to estimate COVID-19 prevalence and predict SARS-CoV-2 transmission through integrating WBS data into an SEIR-V model. We conceptually divide the individual-level viral shedding course into exposed, infectious, and recovery phases as an analogy to the compartments in a population-level SEIR model. We demonstrated that the effect of temperature on viral losses in the sewer can be straightforwardly incorporated in our framework. Using WBS data from the second wave of the pandemic (Oct 02, 2020-Jan 25, 2021) in the Greater Boston area, we showed that the SEIR-V model successfully recapitulates the temporal dynamics of viral load in wastewater and predicts the true number of cases peaked earlier and higher than the number of reported cases by 6-16 days and 8.3-10.2 folds (R = 0.93). This work showcases a simple yet effective method to bridge WBS and quantitative epidemiological modeling to estimate the prevalence and transmission of SARS-CoV-2 in the sewershed, which could facilitate the application of wastewater surveillance of infectious diseases for epidemiological inference and inform public health actions.

Persistence of endogenous RNA biomarkers of SARS-CoV-2 and PMMoV in raw wastewater: Impact of temperature and implications for wastewater-based epidemiology

Understanding the persistence of SARS-CoV-2 biomarkers in wastewater should guide wastewater-based epidemiology users in selecting best RNA biomarkers for reliable detection of the virus during current and future waves of the pandemic. In the present study, the persistence of endogenous SARS-CoV-2 were assessed during one month for six different RNA biomarkers and for the pepper mild mottle virus (PMMoV) at three different temperatures (4, 12 and 20 °C) in one wastewater sample. All SARS-CoV-2 RNA biomarkers were consistently detected during 6 days at 4° and differences in signal persistence among RNA biomarkers were mostly observed at 20 °C with N biomarkers being globally more persistent than RdRP, E and ORF1ab ones. SARS-CoV-2 signal persistence further decreased in a temperature dependent manner. At 12 and 20 °C, RNA biomarker losses of 1-log10 occurred on average after 6 and 4 days, and led to a complete signal loss after 13 and 6 days, respectively. Besides the effect of temperature, SARS-CoV-2 RNA signals were more persistent in the particulate phase compared to the aqueous one. Finally, PMMoV RNA signal was highly persistent in both phases and significantly differed from that of SARS-CoV-2 biomarkers. We further provide a detailed overview of the latest literature on SARS-CoV-2 and PMMoV decay rates in sewage matrices.

Show us the data: global COVID-19 wastewater monitoring efforts, equity, and gaps

A year since the declaration of the global coronavirus disease 2019 (COVID-19) pandemic, there were over 110 million cases and 2.5 million deaths. Learning from methods to track community spread of other viruses such as poliovirus, environmental virologists and those in the wastewater-based epidemiology (WBE) field quickly adapted their existing methods to detect SARS-CoV-2 RNA in wastewater. Unlike COVID-19 case and mortality data, there was not a global dashboard to track wastewater monitoring of SARS-CoV-2 RNA worldwide. This study provides a 1-year review of the "COVIDPoops19" global dashboard of universities, sites, and countries monitoring SARS-CoV-2 RNA in wastewater. Methods to assemble the dashboard combined standard literature review, Google Form submissions, and daily, social media keyword searches. Over 200 universities, 1400 sites, and 55 countries with 59 dashboards monitored wastewater for SARS-CoV-2 RNA. However, monitoring was primarily in high-income countries (65%) with less access to this valuable tool in low- and middle-income countries (35%). Data were not widely shared publicly or accessible to researchers to further inform public health actions, perform meta-analysis, better coordinate, and determine equitable distribution of monitoring sites. For WBE to be used to its full potential during COVID-19 and beyond, show us the data.

Correlation between SARS-CoV-2 RNA concentration in wastewater and COVID-19 cases in community: A systematic review and meta-analysis

Wastewater-based epidemiology (WBE) has been considered as a promising approach for population-wide surveillance of coronavirus disease 2019 (COVID-19). Many studies have successfully quantified severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) RNA concentration in wastewater (CRNA). However, the correlation between the CRNA and the COVID-19 clinically confirmed cases in the corresponding wastewater catchments varies and the impacts of environmental and other factors remain unclear. A systematic review and meta-analysis were conducted to identify the correlation between CRNA and various types of clinically confirmed case numbers, including prevalence and incidence rates. The impacts of environmental factors, WBE sampling design, and epidemiological conditions on the correlation were assessed for the same datasets. The systematic review identified 133 correlation coefficients, ranging from -0.38 to 0.99. The correlation between CRNA and new cases (either daily new, weekly new, or future cases) was stronger than that of active cases and cumulative cases. These correlation coefficients were potentially affected by environmental and epidemiological conditions and WBE sampling design. Larger variations of air temperature and clinical testing coverage, and the increase of catchment size showed strong negative impacts on the correlation between CRNA and COVID-19 case numbers. Interestingly, the sampling technique had negligible impact although increasing the sampling frequency improved the correlation. These findings highlight the importance of viral shedding dynamics, in-sewer decay, WBE sampling design and clinical testing on the accurate back-estimation of COVID-19 case numbers through the WBE approach.

Timing and Trends for Municipal Wastewater, Lab-Confirmed Case, and Syndromic Case Surveillance of COVID-19 in Raleigh, North Carolina

Objectives. To compare 4 COVID-19 surveillance metrics in a major metropolitan area. Methods. We analyzed severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) RNA in wastewater influent and primary solids in Raleigh, North Carolina, from April 10 through December 13, 2020. We compared wastewater results with lab-confirmed COVID-19 cases and syndromic COVID-like illness (CLI) cases to answer 3 questions: (1) Did they correlate? (2) What was the temporal alignment of the different surveillance systems? (3) Did periods of significant change (i.e., trends) align? Results. In the Raleigh sewershed, wastewater influent, wastewater primary solids, lab-confirmed cases, and CLI were strongly or moderately correlated. Trends in lab-confirmed cases and wastewater influent were observed earlier, followed by CLI and, lastly, wastewater primary solids. All 4 metrics showed sustained increases in COVID-19 in June, July, and November 2020 and sustained decreases in August and September 2020. Conclusions. In a major metropolitan area in 2020, the timing of and trends in municipal wastewater, lab-confirmed case, and syndromic case surveillance of COVID-19 were in general agreement. Public Health Implications. Our results provide evidence for investment in SARS-CoV-2 wastewater and CLI surveillance to complement information provided through lab-confirmed cases. (Am J Public Health. 2023;113(1):79-88. https://doi.org/10.2105/AJPH.2022.307108).

Leveraging an established neighbourhood-level, open access wastewater monitoring network to address public health priorities: a population-based study

BACKGROUND

Before the COVID-19 pandemic, the US opioid epidemic triggered a collaborative municipal and academic effort in Tempe, Arizona, which resulted in the world's first open access dashboard featuring neighbourhood-level trends informed by wastewater-based epidemiology (WBE). This study aimed to showcase how wastewater monitoring, once established and accepted by a community, could readily be adapted to respond to newly emerging public health priorities.

METHODS

In this population-based study in Greater Tempe, Arizona, an existing opioid monitoring WBE network was modified to track SARS-CoV-2 transmission through the analysis of 11 contiguous wastewater catchments. Flow-weighted and time-weighted 24 h composite samples of untreated wastewater were collected at each sampling location within the wastewater collection system for 3 days each week (Tuesday, Thursday, and Saturday) from April 1, 2020, to March 31, 2021 (Area 7 and Tempe St Luke's Hospital were added in July, 2020). Reverse transcription quantitative PCR targeting the E gene of SARS-CoV-2 isolated from the wastewater samples was used to determine the number of genome copies in each catchment. Newly detected clinical cases of COVID-19 by zip code within the City of Tempe, Arizona were reported daily by the Arizona Department of Health Services from May 23, 2020. Maricopa County-level new positive cases, COVID-19-related hospitalisations, deaths, and long-term care facility deaths per day are publicly available and were collected from the Maricopa County Epidemic Curve Dashboard. Viral loads of SARS-CoV-2 (genome copies per day) measured in wastewater from each catchment were aggregated at the zip code level and city level and compared with the clinically reported data using root mean square error to investigate early warning capability of WBE.

FINDINGS

Between April 1, 2020, and March 31, 2021, 1556 wastewater samples were analysed. Most locations showed two waves in viral levels peaking in June, 2020, and December, 2020-January, 2021. An additional wave of viral load was seen in catchments close to Arizona State University (Areas 6 and 7) at the beginning of the fall (autumn) semester in late August, 2020. Additionally, an early infection hotspot was detected in the Town of Guadalupe, Arizona, starting the week of May 4, 2020, that was successfully mitigated through targeted interventions. A shift in early warning potential of WBE was seen, from a leading (mean of 8·5 days [SD 2·1], June, 2020) to a lagging (-2·0 days [1·4], January, 2021) indicator compared with newly reported clinical cases.

INTERPRETATION

Lessons learned from leveraging an existing neighbourhood-level WBE reporting dashboard include: (1) community buy-in is key, (2) public data sharing is effective, and (3) sub-ZIP-code (postal code) data can help to pinpoint populations at risk, track intervention success in real time, and reveal the effect of local clinical testing capacity on WBE's early warning capability. This successful demonstration of transitioning WBE efforts from opioids to COVID-19 encourages an expansion of WBE to tackle newly emerging and re-emerging threats (eg, mpox and polio).

FUNDING

National Institutes of Health's RADx-rad initiative, National Science Foundation, Virginia G Piper Charitable Trust, J M Kaplan Fund, and The Flinn Foundation.

Optimization of sewage sampling for wastewater-based epidemiology through stochastic modeling

The proliferation of the SARS-CoV-2 global pandemic has brought to attention the need for epidemiological tools that can detect diseases in specific geographical areas through non-contact means. Such methods may protect those potentially infected by facilitating early quarantine policies to prevent the spread of the disease. Sampling of municipal wastewater has been studied as a plausible solution to detect pathogen spread, even from asymptomatic patients. However, many challenges exist in wastewater-based epidemiology such as identifying a representative sample for a population, determining the appropriate sample size, and establishing the right time and place for samples. In this work, a new approach to address these questions is assessed using stochastic modeling to represent wastewater sampling given a particular community of interest. Using estimates for various process parameters, inferences on the population infected are generated with Monte Carlo simulation output. A case study at the University of Oklahoma is examined to calibrate and evaluate the model output. Finally, extensions are provided for more efficient wastewater sampling campaigns in the future. This research provides greater insight into the effects of viral load, the percentage of the population infected, and sampling time on mean SARS-CoV-2 concentration through simulation. In doing so, an earlier warning of infection for a given population may be obtained and aid in reducing the spread of viruses.

Cost of wastewater-based environmental surveillance for SARS-CoV-2: Evidence from pilot sites in Blantyre, Malawi and Kathmandu, Nepal

Environmental surveillance of rivers and wastewater for SARS-CoV-2 detection has been explored as an innovative way to surveil the pandemic. This study estimated the economic costs of conducting wastewater-based environmental surveillance for SARS-CoV-2 to inform decision making if countries consider continuing these efforts. We estimated the cost of two SARS-CoV-2 environmental surveillance pilot studies conducted in Blantyre, Malawi, and Kathmandu, Nepal. The cost estimation accounted for the consumables, equipment, and human resource time costs used for environmental surveillance from sample selection until pathogen detection and overhead costs for the projects. Costs are reported in 2021 US$ and reported as costs per month, per sample and person per year. The estimated costs for environmental surveillance range from $6,175 to $8,272 per month (Blantyre site) and $16,756 to $30,050 (Kathmandu site). The number of samples processed per month ranged from 84 to 336 at the Blantyre site and 96 to 250 at the Kathmandu site. Consumables costs are variable costs influenced by the number of samples processed and are a large share of the monthly costs for ES (ranging from 39% to 72%). The relatively higher costs per month for the Kathmandu site were attributable to the higher allocation of dedicated human resources and equipment to environmental surveillance for SARS-CoV-2 compared to the Blantyre site where these resources were shared with other activities. The average cost per sample ranged from $25 to $74 (Blantyre) and $120 to $175 (Kathmandu). There were associated economies of scale for human resources and equipment costs with increased sample processing and sharing of resources with other activities. The cost per person in the catchment area per year ranged from $0.07 to $0.10 in Blantyre and $0.07 to $0.13 in Kathmandu. Environmental surveillance may be a low-cost early warning signal for SARS-CoV-2 that can complement other SARS-CoV2 monitoring efforts.

Application of neighborhood-scale wastewater-based epidemiology in low COVID-19 incidence situations

Wastewater-based epidemiology (WBE), an emerging approach for community-wide COVID-19 surveillance, was primarily characterized at large sewersheds such as wastewater treatment plants serving a large population. Although informed public health measures can be better implemented for a small population, WBE for neighborhood-scale sewersheds is less studied and not fully understood. This study applied WBE to seven neighborhood-scale sewersheds (average population of 1471) from January to November 2021. Community testing data showed an average of 0.004 % incidence rate in these sewersheds (97 % of monitoring periods reported two or fewer daily infections). In 92 % of sewage samples, SARS-CoV-2 N gene fragments were below the limit of quantification. We statistically determined 10-2.6 as the threshold of the SARS-CoV-2 N gene concentration normalized to pepper mild mottle virus (N/PMMOV) to alert high COVID-19 incidence rate in the studied sewershed. This threshold of N/PMMOV identified neighborhood-scale outbreaks (COVID-19 incidence rate higher than 0.2 %) with 82 % sensitivity and 51 % specificity. Importantly, neighborhood-scale WBE can discern local outbreaks that would not otherwise be identified by city-scale WBE. Our findings suggest that neighborhood-scale WBE is an effective community-wide disease surveillance tool when COVID-19 incidence is maintained at a low level.

Importance of wastewater-based epidemiology for detecting and monitoring SARS-CoV-2

Coronavirus disease caused by the SARS-CoV-2 virus has emerged as a global challenge in terms of health and disease monitoring. COVID-19 infection is mainly spread through the SARS-CoV-2 infection leading to the development of mild to severe clinical manifestations. The virus binds to its cognate receptor ACE2 which is widely expressed among different tissues in the body. Notably, SARS-CoV-2 shedding in the fecal samples has been reported through the screening of sewage water across various countries. Wastewater screening for the presence of SARS-CoV-2 provides an alternative method to monitor infection threat, variant identification, and clinical evaluation to restrict the virus progression. Multiple cohort studies have reported the application of wastewater treatment approaches and epidemiological significance in terms of virus monitoring. Thus, the manuscript outlines consolidated and systematic information regarding the application of wastewater-based epidemiology in terms of monitoring and managing a viral disease outbreak like COVID-19.

Spectrum of environmental surveillance of SARS-CoV-2 fragments: Questions, quests, and conquest

This works examines the entire spectrum of 'Environmental Surveillance (EnvSurv)' of SARS-CoV-2 fragments i.e. the questions, quests, and conquests of the technology since early year 2020. The prime focus of the present work to document the journey with achieved objectives and remaining ambitions associated with the technology. Despite the EnvSurv may be regarded as the techniques, which rather achieved more than expected, will it win the struggle for its existence or lose its way once the pandemic and fear associated with it completely fades. Pertaining to this discussions, major researched topics were investigated, followed by enlisting of ten bullets of the past experiences along with corresponding challenges, and finally key targets for the techniques are enlisted. The article targets to be a simple guide of the journey of EnvSur in terms of its effectiveness for treatment, infectivity, monitoring & estimation (TIME) till date.

Socioeconomic status correlations with confirmed COVID-19 cases and SARS-CoV-2 wastewater concentrations in small-medium sized communities

Over two years into the COVID-19 pandemic, it is apparent that some populations across the world are more susceptible than others to SARS-CoV-2 infection and spread. Understanding how populations with varying demographic patterns are impacted by COVID-19 may highlight which factors are most important in targeting to combat global suffering. The first objective of this study was to investigate the association of various socioeconomic status (SES) parameters and confirmed COVID-19 cases in the state of Ohio, USA. This study examines the largest and capital city of Ohio (Columbus) and various small-medium-sized communities. The second objective was to determine the relationship between SES parameters and community-level SARS-CoV-2 concentrations using municipal wastewater samples from each city's respective wastewater treatment plants from August 2020 to January 2021. SES parameters include population size, median income, poverty, race/ethnicity, education, health care access, types of COVID-19 testing sites, and social vulnerability index. Statistical analysis results show that confirmed (normalized and/or non-normalized) COVID-19 cases were negatively associated with White percentage and registered hospitals, and positively associated with registered physicians and various COVID-19 testing sites. Wastewater viral concentrations were negatively associated with poverty, and positively associated with median income, community health centers, and onsite rapid testing locations. Additional analyses conclude that population is a significant factor in determining COVID-19 cases and SARS-CoV-2 wastewater concentrations. Results indicate that community healthcare parameters relate to a negative health outcome (COVID-19) and that demographic parameters can be associated with community-level SARS-CoV-2 wastewater concentrations. As the first study that examines the association between socioeconomic parameters and SARS-CoV-2 wastewater concentrations as well as confirmed COVID-19 cases, it is apparent that social determinants have an impact in determining the health burden of small-medium sized Ohioan cities. This study design and innovative approach are scalable and applicable for endemic and pandemic surveillance across the world.

Persistence and occurrence of SARS-CoV-2 in water and wastewater environments: a review of the current literature

As the world continues to cope with the COVID-19 pandemic, emerging evidence indicates that respiratory transmission may not the only pathway in which the virus can be spread. This review paper aims to summarize current knowledge surrounding possible fecal-oral transmission of SARS-CoV-2. It covers recent evidence of proliferation of SARS-CoV-2 in the gastrointestinal tract, as well as presence and persistence of SARS-CoV-2 in water, and suggested future directions. Research indicates that SARS-CoV-2 can actively replicate in the human gastrointestinal system and can subsequently be shed via feces. Several countries have reported SARS-CoV-2 RNA fractions in wastewater systems, and various factors such as temperature and presence of solids have been shown to affect the survival of the virus in water. The detection of RNA does not guarantee infectivity, as current methods such as RT-qPCR are not yet able to distinguish between infectious and non-infectious particles. More research is needed to determine survival time and potential infectivity, as well as to develop more accurate methods for detection and surveillance.

Challenges and Opportunities for Global Genomic Surveillance Strategies in the COVID-19 Era

Global SARS-CoV-2 genomic surveillance efforts have provided critical data on the ongoing evolution of the virus to inform best practices in clinical care and public health throughout the pandemic. Impactful genomic surveillance strategies generally follow a multi-disciplinary pipeline involving clinical sample collection, viral genotyping, metadata linkage, data reporting, and public health responses. Unfortunately, current limitations in each of these steps have compromised the overall effectiveness of these strategies. Biases from convenience-based sampling methods can obfuscate the true distribution of circulating variants. The lack of standardization in genotyping strategies and bioinformatic expertise can create bottlenecks in data processing and complicate interpretation. Limitations and inconsistencies in clinical and demographic data collection and sharing can slow the compilation and limit the utility of comprehensive datasets. This likewise can complicate data reporting, restricting the availability of timely data. Finally, gaps and delays in the implementation of genomic surveillance data in the public health sphere can prevent officials from formulating effective mitigation strategies to prevent outbreaks. In this review, we outline current SARS-CoV-2 global genomic surveillance methods and assess roadblocks at each step of the pipeline to identify potential solutions. Evaluating the current obstacles that impede effective surveillance can improve both global coordination efforts and pandemic preparedness for future outbreaks.

Diurnal Variability of SARS-CoV-2 RNA Concentrations in Hourly Grab Samples of Wastewater Influent during Low COVID-19 Incidence

Wastewater-based epidemiology (WBE) has been widely deployed during the COVID-19 pandemic, but with limited evaluation of the utility of discrete sampling for large sewersheds and low COVID-19 incidence. In this study, SARS-CoV-2 RNA was measured in 72 consecutive hourly influent grab samples collected at a wastewater treatment plant serving nearly 500 000 residents when incidence was low (approximately 20 cases per 100 000). We characterized diurnal variability and relationships between SARS-CoV-2 RNA detection and physicochemical covariates [flow rate, total ammonia nitrogen (TAN), and total solids (TS)]. The highest detection rate observed was 82% during the first peak flow, which occurred in the early afternoon (14:00). Higher detection rates were also observed when sampling above median TAN concentrations (71%; p < 0.01; median = 40.26 mg of NH4/L). SARS-CoV-2 RNA concentrations were weakly correlated with flow rate (Kendall's τ = 0.16; p < 0.01), TAN (τ = 0.19; p < 0.05), and TS (τ = 0.18; p < 0.01), suggesting generally low RNA sewer discharges as expected at low incidence. Our results elucidated sensible adjustments to maximize detection rates, including using multiple gene targets, collecting duplicate samples, and sampling during higher flow and TAN discharges. Optimizing the lower-incidence bounds of WBE can help assess its suitability for verifying COVID-19 reemergence or eradication.

Development and Validation of a Simplified Method for Analysis of SARS-CoV-2 RNA in University Dormitories

Over the course of the COVID-19 pandemic, wastewater surveillance has become a useful tool for describing SARS-CoV-2 prevalence in populations of varying size, from individual facilities (e.g., university residence halls, nursing homes, prisons) to entire municipalities. Wastewater analysis for SARS-CoV-2 RNA requires specialized equipment, expensive consumables, and expert staff, limiting its feasibility and scalability. Further, the extremely labile nature of viral RNA complicates sample transportation, especially in regions with limited access to reliable cold chains. Here, we present a new method for wastewater analysis, termed exclusion-based sample preparation (ESP), that substantially simplifies workflow (at least 70% decrease in time; 40% decrease in consumable usage compared with traditional techniques) by targeting the labor-intensive processing steps of RNA purification and concentration. To optimize and validate this method, we analyzed wastewater samples from residence halls at the University of Kentucky, of which 34% (44/129) contained detectible SARS-CoV-2 RNA. Although concurrent clinical testing was not comprehensive, student infections were identified in the 7 days following a positive wastewater detection in 68% of samples. This pilot study among university residence halls validated the performance and utility of the ESP method, laying the foundation for future studies in regions of the world where wastewater testing is not currently feasible.

Predicting COVID-19 Infected Individuals in a Defined Population from Wastewater RNA Data

Wastewater surveillance of SARS-CoV-2 RNA has become an important tool for tracking the presence of the virus and serving as an early indicator for the onset of rapid transmission. Nevertheless, wastewater data are still not commonly used to predict the number of infected individuals in a sewershed. The main objective of this study was to calibrate a susceptible-exposed-infectious-recovered (SEIR) model using RNA copy rates in sewage (i.e., gene copies per liter times flow rate) and the number of SARS-CoV-2 saliva-test-positive infected individuals in a university student population that was subject to repeated weekly testing during the Spring 2021 semester. A strong correlation was observed between the RNA copy rates and the number of infected individuals. The parameter in the SEIR model that had the largest impact on calibration was the maximum shedding rate, resulting in a mean value of 7.72 log10 genome copies per gram of feces. Regressing the saliva-test-positive infected individuals on predictions from the SEIR model based on the RNA copy rates yielded a slope of 0.87 (SE=0.11), which is statistically consistent with a 1:1 relationship between the two. These findings demonstrate that wastewater surveillance of SARS-CoV-2 can be used to estimate the number of infected individuals in a sewershed.