SARS-CoV-2 in wastewater: From detection to evaluation

Critical Needs for Integrated Surveillance: Wastewater-Based and Clinical Epidemiology in Evolving Scenarios with Lessons Learned from SARS-CoV-2

During the COVID-19 pandemic, wastewater-based epidemiology (WBE) and clinical surveillance have been used as tools for analyzing the circulation of SARS-CoV-2 in the community, but both approaches can be strongly influenced by some sources of variability. From the challenging perspective of integrating environmental and clinical data, we performed a correlation analysis between SARS-CoV-2 concentrations in raw sewage and incident COVID-19 cases in areas served by medium-size wastewater treatment plants (WWTPs) from 2021 to 2023. To this aim, both datasets were adjusted for several sources of variability: WBE data were adjusted for factors including the analytical protocol, sewage flow, and population size, while clinical data adjustments considered the demographic composition of the served population. Then, we addressed the impact on the correlation of differences among sewerage networks and variations in the frequency and type of swab tests due to changes in political and regulatory scenarios. Wastewater and clinical data were significantly correlated when restrictive containment measures and limited movements were in effect (ρ = 0.50) and when COVID-19 cases were confirmed exclusively through molecular testing (ρ = 0.49). Moreover, a positive (although weak) correlation arose for WWTPs located in densely populated areas (ρ = 0.37) and with shorter sewerage lengths (ρ = 0.28). This study provides methodological approaches for interpreting WBE and clinical surveillance data, which could also be useful for other infections. Data adjustments and evaluation of possible sources of bias need to be carefully considered from the perspective of integrated environmental and clinical surveillance of infections.

Rapid assays of SARS-CoV-2 virus and noble biosensors by nanomaterials

The COVID-19 outbreak caused by SARS-CoV-2 in late 2019 has spread rapidly across the world to form a global epidemic of respiratory infectious diseases. Increased investigations on diagnostic tools are currently implemented to assist rapid identification of the virus because mass and rapid diagnosis might be the best way to prevent the outbreak of the virus. This critical review discusses the detection principles, fabrication techniques, and applications on the rapid detection of SARS-CoV-2 with three categories: rapid nuclear acid augmentation test, rapid immunoassay test and biosensors. Special efforts were put on enhancement of nanomaterials on biosensors for rapid, sensitive, and low-cost diagnostics of SARS-CoV-2 virus. Future developments are suggested regarding potential candidates in hospitals, clinics and laboratories for control and prevention of large-scale epidemic.

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.

Wastewater Surveillance Data as a Complement to Emergency Department Visit Data for Tracking Incidence of Influenza A and Respiratory Syncytial Virus - Wisconsin, August 2022-March 2023

Wastewater surveillance has been used to assist public health authorities in tracking local transmission of SARS-CoV-2. The usefulness of wastewater surveillance to track community spread of other respiratory pathogens, including influenza virus and respiratory syncytial virus (RSV), is less clear. During the 2022-23 respiratory diseases season, concentrations of influenza A virus and RSV in wastewater samples in three major Wisconsin cities were compared with emergency department (ED) visits associated with these pathogens. In all three cities, higher concentrations of influenza A virus and RSV in wastewater were associated with higher numbers of associated ED visits (Kendall's tau range = 0.50-0.63 for influenza-associated illness and 0.30-0.49 for RSV-associated illness). Detections of both influenza A virus and RSV in wastewater often preceded a rise in associated ED visits for each pathogen, and virus material remained detectable in wastewater for up to 3 months after pathogen-specific ED visits declined. These results demonstrate that wastewater surveillance has the potential to complement conventional methods of influenza and RSV surveillance, detecting viral signals earlier and for a longer duration than do clinical data. Continued use of wastewater surveillance as a supplement to established surveillance systems such as ED visits might improve local understanding and response to seasonal respiratory virus outbreaks.

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.

Comparison of the methods for isolation and detection of SARS-CoV-2 RNA in municipal wastewater

Introduction

Coronavirus SARS-CoV-2 is a causative agent responsible for the current global pandemic situation known as COVID-19. Clinical manifestations of COVID-19 include a wide range of symptoms from mild (i.e., cough, fever, dyspnea) to severe pneumonia-like respiratory symptoms. SARS-CoV-2 has been demonstrated to be detectable in the stool of COVID-19 patients. Waste-based epidemiology (WBE) has been shown as a promising approach for early detection and monitoring of SARS-CoV-2 in the local population performed via collection, isolation, and detection of viral pathogens from environmental sources.

Methods

In order to select the optimal protocol for monitoring the COVID-19 epidemiological situation in region Turiec, Slovakia, we (1) compared methods for SARS-CoV-2 separation and isolation, including virus precipitation by polyethylene glycol (PEG), virus purification via ultrafiltration (Vivaspin®) and subsequent isolation by NucleoSpin RNA Virus kit (Macherey-Nagel), and direct isolation from wastewater (Zymo Environ Water RNA Kit); (2) evaluated the impact of water freezing on SARS- CoV-2 separation, isolation, and detection; (3) evaluated the role of wastewater filtration on virus stability; and (4) determined appropriate methods including reverse transcription-droplet digital PCR (RT-ddPCR) and real-time quantitative polymerase chain reaction (RT-qPCR) (targeting the same genes, i.e., RdRp and gene E) for quantitative detection of SARS-CoV-2 in wastewater samples.

Results

(1) Usage of Zymo Environ Water RNA Kit provided superior quality of isolated RNA in comparison with both ultracentrifugation and PEG precipitation. (2) Freezing of wastewater samples significantly reduces the RNA yield. (3) Filtering is counterproductive when Zymo Environ Water RNA Kit is used. (4) According to the specificity and sensitivity, the RT-ddPCR outperforms RT-qPCR.

Discussion

The results of our study suggest that WBE is a valuable early warning alert and represents a non-invasive approach to monitor viral pathogens, thus protects public health on a regional and national level. In addition, we have shown that the sensitivity of testing the samples with a nearer detection limit can be improved by selecting the appropriate combination of enrichment, isolation, and detection methods.

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.

An exploration of challenges associated with machine learning for time series forecasting of COVID-19 community spread using wastewater-based epidemiological data

Wastewater-based epidemiology (WBE) has gained increasing attention as a complementary tool to conventional surveillance methods with potential for significant resource and labour savings when used for public health monitoring. Using WBE datasets to train machine learning algorithms and develop predictive models may also facilitate early warnings for the spread of outbreaks. The challenges associated with using machine learning for the analysis of WBE datasets and timeseries forecasting of COVID-19 were explored by running Random Forest (RF) algorithms on WBE datasets across 108 sites in five regions: Scotland, Catalonia, Ohio, the Netherlands, and Switzerland. This method uses measurements of SARS-CoV-2 RNA fragment concentration in samples taken at the inlets of wastewater treatment plants, providing insight into the prevalence of infection in upstream wastewater catchment populations. RF's forecasting performance at each site was quantitatively evaluated by determining mean absolute percentage error (MAPE) values, which was used to highlight challenges affecting future implementations of RF for WBE forecasting efforts. Performance was generally poor using WBE datasets from Catalonia, Scotland, and Ohio with 'reasonable' or better forecasts constituting 0 %, 5 %, and 0 % of these regions' forecasts, respectively. RF's performance was much stronger with WBE data from the Netherlands and Switzerland, which provided 55 % and 45 % 'reasonable' or better forecasts respectively. Sampling frequency and training set size were identified as key factors contributing to accuracy, while inclusion of too many unnecessary variables (or e.g., flow data) was identified as a contributing factor to poor performance. The contribution of catchment population on forecast accuracy was more ambiguous. This study determined that the factors governing RF's forecast performance are complicated and interrelated, which presents challenges for further work in this space. A sufficiently accurate further iteration of the tool discussed within this study would provide significant but varying value for public health departments for monitoring future, or ongoing outbreaks, assisting the implementation of on-time health response measures.

Promising instrument-free detections of various analytes using smartphones with Spotxel® Reader

In consideration of the problems related to food safety, environmental pollution, and the spread of infected diseases nowadays, we urgently need testing methods that can be easily performed by common people. Smartphone-based detections are promising for general applications. However, some of these analytical strategies require a combination of accessories and instruments, such as portable electrochemical workstations, mini multi-mode microplate readers, and complex temperature control devices, etc., which are small but still expensive. Herein, we comprehensively introduce a free app (Spotxel^® Reader) that can provide accurate data analysis for microplate or parallel-format test sensors without an instrument. By simulating the optical signal of the test samples through a smartphone, the sensing results can be obtained for free. We discuss the detection strategies involved in the reported smartphone-based analyses using Spotxel^® Reader. Prospects for the development of this free app for future detection applications are presented. This review aims to popularize free analysis software, so that ordinary people may realize convenient tests.

Multifaceted Assessment of Wastewater-Based Epidemiology for SARS-CoV-2 in Selected Urban Communities in Davao City, Philippines: A Pilot Study

Over 60 countries have integrated wastewater-based epidemiology (WBE) in their COVID-19 surveillance programs, focusing on wastewater treatment plants (WWTP). In this paper, we piloted the assessment of SARS-CoV-2 WBE as a complementary public health surveillance method in susceptible communities in a highly urbanized city without WWTP in the Philippines by exploring the extraction and detection methods, evaluating the contribution of physico-chemical–anthropogenic factors, and attempting whole-genome sequencing (WGS). Weekly wastewater samples were collected from sewer pipes or creeks in six communities with moderate-to-high risk of COVID-19 transmission, as categorized by the City Government of Davao from November to December 2020. Physico-chemical properties of the wastewater and anthropogenic conditions of the sites were noted. Samples were concentrated using a PEG-NaCl precipitation method and analyzed by RT-PCR to detect the SARS-CoV-2 N, RdRP, and E genes. A subset of nine samples were subjected to WGS using the Minion sequencing platform. SARS-CoV-2 RNA was detected in twenty-two samples (91.7%) regardless of the presence of new cases. Cycle threshold values correlated with RNA concentration and attack rate. The lack of a sewershed map in the sampled areas highlights the need to integrate this in the WBE planning. A combined analysis of wastewater physico-chemical parameters such as flow rate, surface water temperature, salinity, dissolved oxygen, and total dissolved solids provided insights on the ideal sampling location, time, and method for WBE, and their impact on RNA recovery. The contribution of fecal matter in the wastewater may also be assessed through the coliform count and in the context of anthropogenic conditions in the area. Finally, our attempt on WGS detected single-nucleotide polymorphisms (SNPs) in wastewater which included clinically reported and newly identified mutations in the Philippines. This exploratory report provides a contextualized framework for applying WBE surveillance in low-sanitation areas.

Photoinactivation of Phage Phi6 as a SARS-CoV-2 Model in Wastewater: Evidence of Efficacy and Safety

The last two years have been marked by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic. This virus is found in the intestinal tract; it reaches wastewater systems and, consequently, the natural receiving water bodies. As such, inefficiently treated wastewater (WW) can be a means of contamination. The currently used methods for the disinfection of WW can lead to the formation of toxic compounds and can be expensive or inefficient. As such, new and alternative approaches must be considered, namely, photodynamic inactivation (PDI). In this work, the bacteriophage φ6 (or, simply, phage φ6), which has been used as a suitable model for enveloped RNA viruses, such as coronaviruses (CoVs), was used as a model of SARS-CoV-2. Firstly, to understand the virus's survival in the environment, phage φ6 was subjected to different laboratory-controlled environmental conditions (temperature, pH, salinity, and solar and UV-B irradiation), and its persistence over time was assessed. Second, to assess the efficiency of PDI towards the virus, assays were performed in both phosphate-buffered saline (PBS), a commonly used aqueous matrix, and a secondarily treated WW (a real WW matrix). Third, as WW is generally discharged into the marine environment after treatment, the safety of PDI-treated WW was assessed through the determination of the viability of native marine water microorganisms after their contact with the PDI-treated effluent. Overall, the results showed that, when used as a surrogate for SARS-CoV-2, phage φ6 remains viable in different environmental conditions for a considerable period. Moreover, PDI proved to be an efficient approach in the inactivation of the viruses, and the PDI-treated effluent showed no toxicity to native aquatic microorganisms under realistic dilution conditions, thus endorsing PDI as an efficient and safe tertiary WW disinfection method. Although all studies were performed with phage φ6, which is considered a suitable model of SARS-CoV-2, further studies using SARS-CoV-2 are necessary; nevertheless, the findings show the potential of PDI for controlling SARS-CoV-2 in WW.

Potential of Recycled Silicon and Silicon-Based Thermoelectrics for Power Generation

Thermoelectrics can convert waste heat to electricity and vice versa. The energy conversion efficiency depends on materials figure of merit, zT, and Carnot efficiency. Due to the higher Carnot efficiency at a higher temperature gradient, high-temperature thermoelectrics are attractive for waste heat recycling. Among high-temperature thermoelectrics, silicon-based compounds are attractive due to the confluence of light weight, high abundance, and low cost. Adding to their attractiveness is the generally defect-tolerant nature of thermoelectrics. This makes them a suitable target application for recycled silicon waste from electronic (e-waste) and solar cell waste. In this review, we summarize the usage of high-temperature thermoelectric generators (TEGs) in applications such as commercial aviation and space voyages. Special emphasis is placed on silicon-based compounds, which include some recent works on recycled silicon and their thermoelectric properties. Besides materials design, device designing considerations to further maximize the energy conversion efficiencies are also discussed. The insights derived from this review can be used to guide sustainable recycling of e-waste into thermoelectrics for power harvesting.