Detection of SARS-CoV-2 RNA throughout wastewater treatment plants and a modeling approach to understand COVID-19 infection dynamics in Winnipeg, Canada

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

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

A mass balance approach for quantifying the role of natural decay and fate mechanisms on SARS-CoV-2 genetic marker removal during water reclamation

The recent SARS-CoV-2 outbreak yielded substantial data regarding virus fate and prevalence at water reclamation facilities (WRFs), identifying influential factors as natural decay, adsorption, light, pH, salinity, and antagonistic microorganisms. However, no studies have quantified the impact of these factors in full scale WRFs. Utilizing a mass balance approach, we assessed the impact of natural decay and other fate mechanisms on genetic marker removal during water reclamation, through the use of sludge and wastewater genetic marker loading estimates. Results indicated negligible removal of genetic markers during P/PT (primary effluent (PE) p value: 0.267; preliminary and primary treatment (P/PT) accumulation p value: 0.904; and thickened primary sludge (TPS) p value: 0.076) indicating no contribution of natural decay and other fate mechanisms toward removal in P/PT. Comparably, adsorption and decomposition was found to be the dominant pathway for genetic marker removal (thickened waste activated sludge (TWAS) log loading 9.75 log10 GC/day); however, no estimation of log genetic marker accumulation could be carried out due to high detections in TWAS. PRACTITIONER POINTS: The mass balance approach suggested that the contribution of natural decay and other fate mechanisms to virus removal during wastewater treatment are negligible compared with adsorption and decomposition in P/PT (p value: 0.904). During (P/PT), a higher viral load remained in the (PE) (14.16 log10 GC/day) compared with TPS (13.83 log10 GC/day); however, no statistical difference was observed (p value: 0.280) indicting that adsorption/decomposition most probably did not occur. In secondary treatment (ST), viral genetic markers in TWAS were consistently detected (13.41 log10 GC/day) compared with secondary effluent (SE), indicating that longer HRT and the potential presence of extracellular polymeric substance-containing enriched biomass enabled adsorption/decomposition. Estimations of total solids and volatile solids for TPS and TWAS indicated that adsorption affinity was different between solids sampling locations (p value: <0.0001).

Wastewater-based Epidemiology for COVID-19 Surveillance: A Survey

The pandemic of COVID-19 has imposed tremendous pressure on public health systems and social economic ecosystems over the past years. To alleviate its social impact, it is important to proactively track the prevalence of COVID-19 within communities. The traditional way to estimate the disease prevalence is to estimate from reported clinical test data or surveys. However, the coverage of clinical tests is often limited and the tests can be labor-intensive, requires reliable and timely results, and consistent diagnostic and reporting criteria. Recent studies revealed that patients who are diagnosed with COVID-19 often undergo fecal shedding of SARS-CoV-2 virus into wastewater, which makes wastewater-based epidemiology (WBE) for COVID-19 surveillance a promising approach to complement traditional clinical testing. In this paper, we survey the existing literature regarding WBE for COVID-19 surveillance and summarize the current advances in the area. Specifically, we have covered the key aspects of wastewater sampling, sample testing, and presented a comprehensive and organized summary of wastewater data analytical methods. Finally, we provide the open challenges on current wastewater-based COVID-19 surveillance studies, aiming to encourage new ideas to advance the development of effective wastewater-based surveillance systems for general infectious diseases.

COVID-19 cases, vaccination, and SARS-CoV-2 in wastewater: insights from a Brazilian municipality

Vaccines combatting COVID-19 demonstrate the ability to protect against disease and hospitalization, and reduce the likelihood of death caused by SARS-CoV-2. In addition, monitoring viral loads in sewage emerges as another crucial strategy in the epidemiological context, enabling early and collective detection of outbreaks. The study aimed to monitor the viral concentration of SARS-CoV-2 in untreated sewage in a Brazilian municipality. Also, it attempted to correlate these measurements with the number of clinical cases and deaths resulting from COVID-19 between July 2021 and July 2022. SARS-CoV-2 viral RNA was quantified by RT-qPCR. Pearson's correlation was performed to analyze the variables' relationship using the number of cases, deaths, vaccinated individuals, and viral concentration of SARS-CoV-2. The results revealed a significant negative correlation (p < 0.05) between the number of vaccinated individuals and the viral concentration of SARS-CoV-2, suggesting that after vaccination, the RNA viral load concentration was reduced in the sample population by the circulating concentration of wastewater. Consequently, wastewater monitoring, in addition to functioning as an early warning system for the circulation of SARS-CoV-2 and other pathogens, can offer a novel perspective that enhances decision-making, strengthens vaccination campaigns, and contributes to authorities establishing systematic networks for monitoring SARS-CoV-2.

Impact of coagulation on SARS-CoV-2 and PMMoV viral signal in wastewater solids

Wastewater surveillance (WWS) of SARS-CoV-2 has become a crucial tool for monitoring COVID-19 cases and outbreaks. Previous studies have indicated that SARS-CoV-2 RNA measurement from testing solid-rich primary sludge yields better sensitivity compared to testing wastewater influent. Furthermore, measurement of pepper mild mottle virus (PMMoV) signal in wastewater allows for precise normalization of SARS-CoV-2 viral signal based on solid content, enhancing disease prevalence tracking. However, despite the widespread adoption of WWS, a knowledge gap remains regarding the impact of ferric sulfate coagulation, commonly used in enhanced primary clarification, the initial stage of wastewater treatment where solids are sedimented and removed, on SARS-CoV-2 and PMMoV quantification in wastewater-based epidemiology. This study examines the effects of ferric sulfate addition, along with the associated pH reduction, on the measurement of SARS-CoV-2 and PMMoV viral measurements in wastewater primary clarified sludge through jar testing. Results show that the addition of Fe3+ concentrations in the conventional 0 to 60 mg/L range caused no effect on SARS-CoV-2 N1 and N2 gene region measurements in wastewater solids. However, elevated Fe3+ concentrations were shown to be associated with a statistically significant increase in PMMoV viral measurements in wastewater solids, which consequently resulted in the underestimation of PMMoV-normalized SARS-CoV-2 viral signal measurements (N1 and N2 copies/copies of PMMoV). The observed pH reduction from coagulant addition did not contribute to the increased PMMoV measurements, suggesting that this phenomenon arises from the partitioning of PMMoV viral particles into wastewater solids.

Effectiveness of environmental surveillance of SARS-CoV-2 as an early-warning system: Update of a systematic review during the second year of the pandemic

The aim of this updated systematic review was to offer an overview of the effectiveness of environmental surveillance (ES) of SARS-CoV-2 as a potential early-warning system (EWS) for COVID-19 and new variants of concerns (VOCs) during the second year of the pandemic. An updated literature search was conducted to evaluate the added value of ES of SARS-CoV-2 for public health decisions. The search for studies published between June 2021 and July 2022 resulted in 1,588 publications, identifying 331 articles for full-text screening. A total of 151 publications met our inclusion criteria for the assessment of the effectiveness of ES as an EWS and early detection of SARS-CoV-2 variants. We identified a further 30 publications among the grey literature. ES confirms its usefulness as an EWS for detecting new waves of SARS-CoV-2 infection with an average lead time of 1-2 weeks for most of the publication. ES could function as an EWS for new VOCs in areas with no registered cases or limited clinical capacity. Challenges in data harmonization and variant detection require standardized approaches and innovations for improved public health decision-making. ES confirms its potential to support public health decision-making and resource allocation in future outbreaks.

Surveillance of COVID-19 and influenza A(H1N1) prevalence in China via medicine-based wastewater biomarkers

The simultaneous monitoring of individual or multiple diseases can be achieved by selecting therapeutic medicines used to treat the primary symptoms of the condition as biomarkers in wastewater. This study proposes a novel approach to monitor the prevalence of COVID-19 and influenza A (H1N1) by selecting nine medicines to serve as biomarkers, including three antipyretics, three antivirals, and three cough suppressants. To verify our approach, wastewater samples were collected from seventeen urban and five rural wastewater treatment plants (WWTPs) in a Chinese city over a period of one year. The use of antipyretics increased notably during the COVID-19 pandemic, while the consumption of antivirals for influenza A (H1N1) rose in the post-COVID-19 pandemic period, indicating a minor spike in the occurrence of influenza A (H1N1) after the COVID-19 pandemic. Fever is a significant symptom of COVID-19 and can serve as a reliable indicator of disease prevalence. Our research found that the prevalence of COVID-19 in urban areas was significantly higher (at 78.5 %, 95 % CI: 73.4 % - 83.9 %) than in rural areas (with a prevalence of 48.1 %, 95 % CI: 42.4 % - 53.8 %). The prevalence of COVID-19 in urban areas in this study was consistent with the data reported by the Chinese center for Disease Control and Prevention (82.4 %). Continuous monitoring of WWTPs in urban areas with fluctuating populations and complex demographics can provide early disease warning. Our results demonstrate the feasibility of evaluating community disease prevalence by selecting major therapeutic medicines as biomarkers in wastewater.

Recent progress on wastewater-based epidemiology for COVID-19 surveillance: A systematic review of analytical procedures and epidemiological modeling

On March 11, 2020, the World Health Organization declared the coronavirus disease 2019 (COVID-19), whose causative agent is the Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2), a pandemic. This virus is predominantly transmitted via respiratory droplets and shed via sputum, saliva, urine, and stool. Wastewater-based epidemiology (WBE) has been able to monitor the circulation of viral pathogens in the population. This tool demands both in-lab and computational work to be meaningful for, among other purposes, the prediction of outbreaks. In this context, we present a systematic review that organizes and discusses laboratory procedures for SARS-CoV-2 RNA quantification from a wastewater matrix, along with modeling techniques applied to the development of WBE for COVID-19 surveillance. The goal of this review is to present the current panorama of WBE operational aspects as well as to identify current challenges related to it. Our review was conducted in a reproducible manner by following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines for systematic reviews. We identified a lack of standardization in wastewater analytical procedures. Regardless, the reverse transcription-quantitative polymerase chain reaction (RT-qPCR) approach was the most reported technique employed to detect and quantify viral RNA in wastewater samples. As a more convenient sample matrix, we suggest the solid portion of wastewater to be considered in future investigations due to its higher viral load compared to the liquid fraction. Regarding the epidemiological modeling, the data-driven approach was consistently used for the prediction of variables associated with outbreaks. Future efforts should also be directed toward the development of rapid, more economical, portable, and accurate detection devices.

Wastewater early warning system for SARS-CoV-2 outbreaks and variants in a Coruña, Spain

Wastewater-based epidemiology has been widely used as a cost-effective method for tracking the COVID-19 pandemic at the community level. Here we describe COVIDBENS, a wastewater surveillance program running from June 2020 to March 2022 in the wastewater treatment plant of Bens in A Coruña (Spain). The main goal of this work was to provide an effective early warning tool based in wastewater epidemiology to help in decision-making at both the social and public health levels. RT-qPCR procedures and Illumina sequencing were used to weekly monitor the viral load and to detect SARS-CoV-2 mutations in wastewater, respectively. In addition, own statistical models were applied to estimate the real number of infected people and the frequency of each emerging variant circulating in the community, which considerable improved the surveillance strategy. Our analysis detected 6 viral load waves in A Coruña with concentrations between 10³ and 10⁶ SARS-CoV-2 RNA copies/L. Our system was able to anticipate community outbreaks during the pandemic with 8-36 days in advance with respect to clinical reports and, to detect the emergence of new SARS-CoV-2 variants in A Coruña such as Alpha (B.1.1.7), Delta (B.1.617.2), and Omicron (B.1.1.529 and BA.2) in wastewater with 42, 30, and 27 days, respectively, before the health system did. Data generated here helped local authorities and health managers to give a faster and more efficient response to the pandemic situation, and also allowed important industrial companies to adapt their production to each situation. The wastewater-based epidemiology program developed in our metropolitan area of A Coruña (Spain) during the SARS-CoV-2 pandemic served as a powerful early warning system combining statistical models with mutations and viral load monitoring in wastewater over time.

Early warning of emerging infectious diseases based on multimodal data

The coronavirus disease 2019 (COVID-19) pandemic has dramatically increased the awareness of emerging infectious diseases. The advancement of multiomics analysis technology has resulted in the development of several databases containing virus information. Several scientists have integrated existing data on viruses to construct phylogenetic trees and predict virus mutation and transmission in different ways, providing prospective technical support for epidemic prevention and control. This review summarized the databases of known emerging infectious viruses and techniques focusing on virus variant forecasting and early warning. It focuses on the multi-dimensional information integration and database construction of emerging infectious viruses, virus mutation spectrum construction and variant forecast model, analysis of the affinity between mutation antigen and the receptor, propagation model of virus dynamic evolution, and monitoring and early warning for variants. As people have suffered from COVID-19 and repeated flu outbreaks, we focused on the research results of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and influenza viruses. This review comprehensively viewed the latest virus research and provided a reference for future virus prevention and control research.

Detecting SARS-CoV-2 in sludge samples: A systematic review

AIMS

This paper aims to review the main sludge concentration methods used for SARS-CoV-2 detection in sewage sludge samples, discussing the main methods and sample volume related to increased viral load. In addition, we aim to evaluate the countries associated with increased positivity rates for SARS-CoV-2 in sludge samples.

METHODS

This systematic methodology was registered in PROSPERO and followed the PRISMA guidelines. The search was carried out in the SciELO, PubMed/MEDLINE, Lilacs, and Google Scholar databases in January-March 2022. Quantitative studies with conclusive results were included in this review. Concentration methods (polyethylene glycol (PEG), PEG + NaCl, gravity thickening, skimmed milk flocculation, ultrafiltration, filtration using charged filters, primary sedimentation, and anaerobic digestion), as well as detection methods (RTqPCR and reverse transcription droplet digital PCR assay) were evaluated in this review. The SPSS v23 software program was used for statistical analysis.

RESULTS

PEG (with or without NaCl addition) and gravity thickening were the most used sludge concentration methods to detect SARS-CoV-2. The main method associated with increased viral load (>2,02 × 10^4 copies/mL) was PEG + NaCl (p < 0.05, Mann-Whitney test). The average positivity rate for SARS-CoV-2 in sludge samples was 61 %, and a correlation was found between the sludge volume and the viral load (ro 0.559, p = 0.03, Spearman correlation).

CONCLUSION

The sludge volume may influence the SARS-CoV-2 load since the virus can adhere to solid particles in these samples. Other factors may be associated with SARS-CoV-2 load, including the methods used; especially PEG + NaCl may result in a high viral load detected in sludge, and may provide a suitable pH for SARS-CoV-2 recovery.

The first detection of SARS-CoV-2 RNA in urban wastewater in Giza, Egypt

The new coronavirus (SARS-CoV-2) is a respiratory virus causing coronavirus disease (COVID-19). Individuals with COVID-19 can shed the viral genome in their feces, even if they do not have symptoms, and the virus can be detected in wastewater. The current study provides the first surveillance of SARS-CoV-2 RNA genome in the wastewater in Egypt. To study this aim, untreated influent (n = 48) and treated effluent (n = 48) samples were collected between January and December 2021 from the wastewater treatment plant in Giza. The viral RNA genome was determined by reverse transcription-polymerase chain reaction (RT-PCR) (S, E, and N target regions) and real-time quantitative reverse transcription-PCR (RT-qPCR) (N1 and N2 target regions). The RT-PCR assay failed to detect SARS-CoV-2 RNA in all samples analyzed, whereas RT-qPCR succeeded in the detection of N gene of SARS-CoV-2 in 62.5% of untreated influent samples. The RT-qPCR Ct values of those samples tested positive ranged from 19.9 to 30.1 with a mean of 23. The treated effluent samples were negative for viral RNA detected by both RT-PCR and RT-qPCR, indicating the efficiency of the sewage treatment plant in degrading SARS-CoV-2. Our preliminary findings provide evidence for the value of wastewater epidemiology approach for the surveillance of SARS-CoV-2 in the population to assist in the responses of public health to COVID-19 outbreak.