Future perspectives of wastewater-based epidemiology: Monitoring infectious disease spread and resistance to the community level

Quantification of infectious Human mastadenovirus in environmental matrices using PMAxx-qPCR

Molecular methodologies providing data on viral concentration and infectivity have been successfully used in environmental virology, supporting quantitative risk assessment studies. The present study aimed to assess human mastadenovirus (HAdV) intact particles using a derivative of propidium monoazide associated with qPCR (PMAxx-qPCR) in aquatic matrices. Initially, different concentrations of PMAxx were evaluated to establish an optimal protocol for treating different naturally contaminated matrices, using 10 min incubation in the dark at 200 rpm at room temperature and 15 min of photoactivation in the PMA-Lite™ LED photolysis device. There was no significant reduction in the quantification of infectious HAdV with increasing concentration of PMAxx used (20 μM, 50 μM, and 100 μM), except for sewage samples. In this matrix, a reduction of 5.01 log of genomic copies (GC)/L was observed from the concentration of 50 μM and revealed 100% HAdV particles with damaged capsids. On the other hand, the mean reduction of 0.51 log in stool samples using the same concentration mentioned above demonstrated 83% of damaged particles eliminated in the stool. Following, 50 μM PMAxx-qPCR protocol revealed a log reduction of 0.91, 0.67, and 1.05 in other samples of raw sewage, brackish, and seawater where HAdV concentration reached 1.47 × 10⁴, 6.81 × 10², and 2.33 × 10² GC/L, respectively. Fifty micrometers of PMAxx protocol helped screen intact viruses from different matrices, including sea and brackish water.

Sheet, Surveillance, Strategy, Salvage and Shield in global biodefense system to protect the public health and tackle the incoming pandemics

The pandemic of COVID-19 challenges the global health system and raises our concerns on the next waves of other emerging infectious diseases. Considering the lessons from the failure of world's pandemic warning system against COVID-19, many scientists and politicians have mentioned different strategies to improve global biodefense system, among which Sheet, Surveillance, Strategy, Salvage and Shield (5S) are frequently discussed. Nevertheless, the current focus is mainly on the optimization and management of individual strategy, and there are limited attempts to combine the five strategies as an integral global biodefense system. Sheet represents the biosafety datasheet for biohazards in natural environment and human society, which helps our deeper understanding on the geographical pattern, transmission routes and infection mechanism of pathogens. Online surveillance and prognostication network is an environmental Surveillance tool for monitoring the outbreak of pandemic diseases and alarming the risks to take emergency actions, targeting aerosols, waters, soils and animals. Strategy is policies and legislations for social distancing, lockdown and personal protective equipment to block the spread of infectious diseases in communities. Clinical measures are Salvage on patients by innovating appropriate medicines and therapies. The ultimate defensive Shield is vaccine development to protect healthy crowds from infection. Fighting against COVID-19 and other emerging infectious diseases is a long rocky journey, requiring the common endeavors of scientists and politicians from all countries around the world. 5S in global biodefense system bring a ray of light to the current darkest and future road from environmental and geographical perspectives.

Detection and quantification of SARS-CoV-2 RNA in wastewater influent in relation to reported COVID-19 incidence in Finland

Wastewater-based surveillance is a cost-effective concept for monitoring COVID-19 pandemics at a population level. Here, SARS-CoV-2 RNA was monitored from a total of 693 wastewater (WW) influent samples from 28 wastewater treatment plants (WWTP, N = 21-42 samples per WWTP) in Finland from August 2020 to May 2021, covering WW of ca. 3.3 million inhabitants (∼ 60% of the Finnish population). Quantity of SARS-CoV-2 RNA fragments in 24 h-composite samples was determined by using the ultrafiltration method followed by nucleic acid extraction and CDC N2 RT-qPCR assay. SARS-CoV-2 RNA signals at each WWTP were compared over time to the numbers of confirmed COVID-19 cases (14-day case incidence rate) in the sewer network area. Over the 10-month surveillance period with an extensive total number of samples, the detection rate of SARS-CoV-2 RNA in WW was 79% (including 6% uncertain results, i.e., amplified only in one out of four, two original and two ten-fold diluted replicates), while only 24% of all samples exhibited gene copy numbers above the quantification limit. The range of the SARS-CoV-2 detection rate in WW varied from 33% (including 10% uncertain results) in Pietarsaari to 100% in Espoo. Only six out of 693 WW samples were positive with SARS-COV-2 RNA when the reported COVID-19 case number from the preceding 14 days was zero. Overall, the 14-day COVID-19 incidence was 7.0, 18, and 36 cases per 100 000 persons within the sewer network area when the probability to detect SARS-CoV-2 RNA in wastewater samples was 50%, 75% and 95%, respectively. The quantification of SARS-CoV-2 RNA required significantly more COVID-19 cases: the quantification rate was 50%, 75%, and 95% when the 14-day incidence was 110, 152, and 223 COVID-19 cases, respectively, per 100 000 persons. Multiple linear regression confirmed the relationship between the COVID-19 incidence and the SARS-CoV-2 RNA quantified in WW at 15 out of 28 WWTPs (overall R² = 0.36, p < 0.001). At four of the 13 WWTPs where a significant relationship was not found, the SARS-CoV-2 RNA remained below the quantification limit during the whole study period. In the five other WWTPs, the sewer coverage was less than 80% of the total population in the area and thus the COVID-19 cases may have been inhabitants from the areas not covered. Based on the results obtained, WW-based surveillance of SARS-CoV-2 could be used as an indicator for local and national COVID-19 incidence trends. Importantly, the determination of SARS-CoV-2 RNA fragments from WW is a powerful and non-invasive public health surveillance measure, independent of possible changes in the clinical testing strategies or in the willingness of individuals to be tested for COVID-19.

Emergence of SARS-CoV-2 Alpha lineage and its correlation with quantitative wastewater-based epidemiology data

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) gave rise to an international public health emergency in 3 months after its emergence in Wuhan, China. Typically for an RNA virus, random mutations occur constantly leading to new lineages, incidental with a higher transmissibility. The highly infective alpha lineage, firstly discovered in the UK, led to elevated mortality and morbidity rates as a consequence of Covid-19, worldwide. Wastewater surveillance proved to be a powerful tool for early detection and subsequent monitoring of the dynamics of SARS-CoV-2 and its variants in a defined catchment. Using a combination of sequencing and RT-qPCR approaches, we investigated the total SARS-CoV-2 concentration and the emergence of the alpha lineage in wastewater samples in Vienna, Austria linking it to clinical data. Based on a non-linear regression model and occurrence of signature mutations, we conclude that the alpha variant was present in Vienna sewage samples already in December 2020, even one month before the first clinical case was officially confirmed and reported by the health authorities. This provides evidence that a well-designed wastewater monitoring approach can provide a fast snapshot and may detect the circulating lineages in wastewater weeks before they are detectable in the clinical samples. Furthermore, declining 14 days prevalence data with simultaneously increasing SARS-CoV-2 total concentration in wastewater indicate a different shedding behavior for the alpha variant. Overall, our results support wastewater surveillance to be a suitable approach to spot early circulating SARS-CoV-2 lineages based on whole genome sequencing and signature mutations analysis.

Comparison of high-frequency in-pipe SARS-CoV-2 wastewater-based surveillance to concurrent COVID-19 random clinical testing on a public U.S. university campus

Wastewater-based epidemiology (WBE) is utilized globally as a tool for quantifying the amount of Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) within communities, yet the efficacy of community-level wastewater monitoring has yet to be directly compared to random Coronavirus Disease of 2019 (COVID-19) clinical testing; the best-supported method of virus surveillance within a single population. This study evaluated the relationship between SARS-CoV-2 RNA in raw wastewater and random COVID-19 clinical testing on a large university campus in the Southwestern United States during the Fall 2020 semester. Daily composites of wastewater (24-hour samples) were collected three times per week at two campus locations from 16 August 2020 to 1 January 2021 (n = 95) and analyzed by reverse transcriptase-quantitative polymerase chain reaction (RT-qPCR) targeting the SARS-CoV-2 E gene. Campus populations were estimated using campus resident information and anonymized, unique user Wi-Fi connections. Resultant trends of SARS-CoV-2 RNA levels in wastewater were consistent with local and nationwide pandemic trends showing peaks in infections at the start of the Fall semester in mid-August 2020 and mid-to-late December 2020. A strong positive correlation (r = 0.71 (p < 0.01); n = 15) was identified between random COVID-19 clinical testing and WBE surveillance methods, suggesting that wastewater surveillance has a predictive power similar to that of random clinical testing. Additionally, a comparative cost analysis between wastewater and clinical methods conducted here show that WBE was more cost effective, providing data at 1.7% of the total cost of clinical testing ($6042 versus $338,000, respectively). We conclude that wastewater monitoring of SARS-CoV-2 performed in tandem with random clinical testing can strengthen campus health surveillance, and its economic advantages are maximized when performed routinely as a primary surveillance method, with random clinical testing reserved for an active outbreak situation.

Improved methods for the detection and quantification of SARS-CoV-2 RNA in wastewater

Since the start of the COVID-19 pandemic, different methods have been used to detect the presence of genetic material of SARS-CoV-2 in wastewater. The use of wastewater for SARS-CoV-2 RNA detection and quantification showed different problems, associated to the complexity of the matrix and the lack of standard methods used to analyze the presence of an enveloped virus, such as coronavirus. Different strategies for the concentration process were selected to carry out the detection and quantification of SARS-CoV-2 RNA in wastewater: (a) aluminum hydroxide adsorption-precipitation, (b) pre-treatment with glycine buffer and precipitation with polyethylene-glycol (PEG) and (c) ultrafiltration (Centricon). Our results showed that the reduction of organic matter, using the pre-treatment with glycine buffer before the concentration with Centricon or aluminum hydroxide adsorption-precipitation, improved the recovery percentage of the control virus, Mengovirus (MgV) (8.37% ± 5.88 n = 43; 6.97% ± 6.51 n = 20, respectively), and the detection of SARS-CoV-2 in comparison with the same methodology without a pre-treatment. For the concentration with Centricon, the use of 100 mL of wastewater, instead of 200 mL, increased the MgV recovery, and allowed a positive detection of SARS-CoV-2 with N1 and N2 targets. The quantity of SARS-CoV-2 RNA detected in wastewater did not show a direct correlation with the number of confirmed cases, but the study of its upwards or downwards trend over time enabled the detection of an increase of epidemiological data produced in September 2020, January 2021 and April 2021.

Opportunities and limits of wastewater-based epidemiology for tracking global health and attainment of UN sustainable development goals

Wastewater-based epidemiology (WBE) emerged as a powerful, actionable health management tool during the COVID-19 pandemic. Hypothesizing future uses, we explored its potential for real-time, tracking of progress in attaining United Nations Sustainable Development Goals (SDGs) globally as a non-expensive method using existing infrastructure. We inventoried (i) literature-documented sewerage infrastructure, (ii) demographics of populations served, and (iii) WBE markers informative of 9 SDGs. Among the 17 different sustainable development goals listed by the UN 2030 agenda, more than half of these may be monitored by using WBE monitoring at centralized treatment infrastructure as tabulated in this study. Driven mainly by COVID-19, WBE currently is practiced in at least 55 countries, reaching about 300 million people. Expansion of WBE to 109,000 + treatment plants inventoried in 129 countries would increase global coverage 9-fold to 34.7% or 2.7 billion, leaving out 5 billion people not served by centralized sewerage systems. Associations between population demographics and present-day infrastructure are explored, and geospatial regions particularly vulnerable to infectious disease outbreaks are identified. The results suggest that difference in the differential outcomes in well-being is an outcome of the sanitation infrastructure inequalities and lack of sanitation infrastructure creates doubly disadvantaged populations at risk of poor hygiene and cut off from the early-warning benefits of conventional WBE. This is the first study to explore the feasibility and potential barriers to the use of WBE for tracking the attainment of SDGs globally with at least 9 out of 17 SDGs.

Decay of four enteric pathogens and implications to wastewater-based epidemiology: Effects of temperature and wastewater dilutions

Measurement of pathogens in raw wastewater from a population within certain sewer catchments can provide quantitative information on public health status within the sampled urban area. This so-called wastewater-based epidemiology (WBE) approach has the potential of becoming a powerful tool to monitor pathogen circulation and support timely intervention during outbreaks. However, many WBE studies failed to account for the pathogen decay during wastewater transportation in back calculating the disease prevalence. Various sewer process factors, including water temperature and infiltration/inflow, can lead to the variation of pathogen decay rates. This paper firstly reviewed the effects of temperature and types of water, i.e., wastewater, freshwater, and saline water, on the decay of four selected enteric pathogens, i.e., Campylobacter, Salmonella, Norovirus, and Adenovirus. To elucidate the importance of the pathogen decay rates (measured by culture and molecular methods) to WBE, a sensitivity analysis was conducted on the back-calculation equation for infection prevalence with decay rates collected from published literature. It was found that WBE back-calculation is more sensitive to decay rates under the condition of high wastewater temperature (i.e., over 25 °C) or if wastewater is diluted by saline water (i.e., sewer infiltration or use of seawater as an alternative source of freshwater constituting around 1/3 household water demand in some cities). Stormwater dilution of domestic wastewater (i.e., sewer inflow might achieve 10 times volumetric dilution) was shown to play a role in increasing the sensitivity of WBE back-calculation to bacterial pathogens, but not viral pathogens. Hence, WBE back-calculation in real sewers should account for in-sewer decay of specific pathogen species under different wastewater temperatures and dilutions. Overall, this review contributes to a better understanding of pathogen decay in wastewater which can lead to improved accuracy of WBE back-calculation.

Changes in Sewage Sludge Chemical Signatures During a COVID-19 Community Lockdown, Part 2: Nontargeted Analysis of Sludge and Evaluation with COVID-19 Metrics

Sewage sludge and wastewater include urine and feces from an entire community, and it is highly likely that this mixture contains chemicals whose presence is dependent on levels of SARS-CoV-2 in the community. We analyzed primary sewage sludge samples collected in New Haven, Connecticut, USA, during the initial wave of the COVID-19 pandemic using liquid chromatography coupled with high-resolution mass spectrometry and performed an exploratory investigation of correlations between chemical features and COVID-19 metrics including concentrations of severe acute respiratory syndrome-coronavirus 2 (SARS-CoV-2) RNA in the sludge and local COVID-19 case numbers and hospital admissions. Inclusion of all chemical features in this analysis is key for discovering potential indicator compounds for COVID-19, whose structures may not be known. We found correlations with COVID-19 metrics for several identified chemicals as well as many unidentified features in the data, including three potential indicator molecules that are recommended for prioritization in future studies on COVID-19 in wastewater and sludge. These features have molecular weights of 108.0935, 318.1214, and 331.1374. While it is not possible to achieve prediction of COVID-19 epidemiological metrics from the one data set used in the present study, advances in this research area are important to share as scientists worldwide work on discovering efficient methods for tracking SARS-CoV-2 in wastewater and the environment. Environ Toxicol Chem 2022;41:1193-1201. © 2021 SETAC.

Passive Samplers, an Important Tool for Continuous Monitoring of the COVID-19 Pandemic

The global pandemic caused by COVID-19 has resulted in major costs around the world, costs with dimensions in every aspect, from peoples' daily living to the global economy. As the pandemic progresses, the virus evolves, and more vaccines become available, and the 'battle against the virus' continues. As part of the battle, Wastewater-Based Epidemiology (WBE) technologies are being widely deployed in essential roles for SARS-CoV-2 detection and monitoring. While focusing on demonstrating the advantages of passive samplers as a tool in WBE, this review provides a holistic view of the current WBE applications in monitoring SARS-CoV-2 with the integration of the most up-to-date data. A novel scenario example based on a recent Nanjing (China) outbreak in July 2021 is used to illustrate the potential benefits of using passive samplers to monitor COVID-19 and to facilitate effective control of future major outbreaks. The presented contents and how the application of passive samplers indicates that this technology can be beneficial at different levels, varying from building to community to regional. Countries and regions that have the pandemic well under control or have low positive case occurrences have the potential to significantly benefit from deploying passive samplers as a measure to identify and suppress outbreaks.

High Sensitivity and Specificity of Dormitory-Level Wastewater Surveillance for COVID-19 during Fall Semester 2020 at Syracuse University, New York

A residential building’s wastewater presents a potential non-invasive method of surveilling numerous infectious diseases, including SARS-CoV-2. We analyzed wastewater from 16 different residential locations at Syracuse University (Syracuse, NY, USA) during fall semester 2020, testing for SARS-CoV-2 RNA twice weekly and compared the presence of clinical COVID-19 cases to detection of the viral RNA in wastewater. The sensitivity of wastewater surveillance to correctly identify dormitories with a case of COVID-19 ranged from 95% (95% confidence interval [CI] = 76–100%) on the same day as the case was diagnosed to 73% (95% CI = 53–92%), with 7 days lead time of wastewater. The positive predictive value ranged from 20% (95% CI = 13–30%) on the same day as the case was diagnosed to 50% (95% CI = 40–60%) with 7 days lead time. The specificity of wastewater surveillance to correctly identify dormitories without a case of COVID-19 ranged from 60% (95% CI = 52–67%) on the day of the wastewater sample to 67% (95% CI = 58–74%) with 7 days lead time. The negative predictive value ranged from 99% (95% CI = 95–100%) on the day of the wastewater sample to 84% (95% CI = 77–91%) with 7 days lead time. Wastewater surveillance for SARS-CoV-2 at the building level is highly accurate in determining if residents have a COVID-19 infection. Particular benefit is derived from negative wastewater results that can confirm a building is COVID-19 free.

Successful application of wastewater-based epidemiology in prediction and monitoring of the second wave of COVID-19 with fragmented sewerage systems-a case study of Jaipur (India)

The present study tracked the city-wide dynamics of severe acute respiratory syndrome-corona virus 2 ribonucleic acids (SARS-CoV-2 RNA) in the wastewater from nine different wastewater treatment plants (WWTPs) in Jaipur during the second wave of COVID-19 out-break in India. A total of 164 samples were collected weekly between February 19th and June 8th, 2021. SARS-CoV-2 was detected in 47.2% (52/110) influent samples and 37% (20/54) effluent samples. The increasing percentage of positive influent samples correlated with the city's increasing active clinical cases during the second wave of COVID-19 in Jaipur. Furthermore, wastewater-based epidemiology (WBE) evidence clearly showed early detection of about 20 days (9/9 samples reported positive on April 20th, 2021) before the maximum cases and maximum deaths reported in the city on May 8th, 2021. The present study further observed the presence of SARS-CoV-2 RNA in treated effluents at the time window of maximum active cases in the city even after tertiary disinfection treatments of ultraviolet (UV) and chlorine (Cl₂) disinfection. The average genome concentration in the effluents and removal efficacy of six commonly used treatments, activated sludge process + chlorine disinfection (ASP + Cl₂), moving bed biofilm reactor (MBBR) with ultraviolet radiations disinfection (MBBR + UV), MBBR + chlorine (Cl₂), sequencing batch reactor (SBR), and SBR + Cl₂, were compared with removal efficacy of SBR + Cl₂ (81.2%) > MBBR + UV (68.8%) > SBR (57.1%) > ASP (50%) > MBBR + Cl₂ (36.4%). The study observed the trends and prevalence of four genes (E, RdRp, N, and ORF1ab gene) based on two different kits and found that prevalence of N > ORF1ab > RdRp > E gene suggested that the effective genome concentration should be calculated based on the presence/absence of multiple genes. Hence, it is imperative to say that using a combination of different detection genes (E, N, RdRp, & ORF1ab genes) increases the sensitivity in WBE.

Water-sanitation-health nexus in the Indus-Ganga-Brahmaputra River Basin: need for wastewater surveillance of SARS-CoV-2 for preparedness during the future waves of pandemic

The Indus-Ganga-Brahmaputra River Basin (IGBRB) is a trans-boundary river basin flowing through four major countries in South Asia viz., India, Pakistan, Bangladesh, and Nepal. Contamination of surface water by untreated or inadequately treated wastewater has been a huge problem for pathogenic microorganisms in economies in transition. Recent studies have reported that sewage surveillance can provide prior information of the outbreak data, because faeces can contain the novel coronavirus (SARS-CoV-2) shed by infected humans. Hence, in this study we geo-spatially mapped the COVID-19 hotspots during the peak time in the first and second wave of pandemic to demonstrate the need and usefulness of wastewater surveillance strategy in IGBRB during ongoing pandemic. Further we discussed the status of sanitation, health and hand-hygiene in the IGBRB along with characterization of the challenges posed by the pandemic in achieving the United Nations Sustainable Development Goals (UN-SDGs). Monthly Geographical Information System (GIS) mapping of COVID-19 hotspots in the IGBRB showed an increase in the spread along the direct sewage discharge points. The social inequalities expose the vulnerabilities of the urban poor in terms of the burden, risks and access to Water, Sanitation, and Hygiene (WASH) needs. Such an evidence-based image of the actual SARS-CoV-2 viral load in the community along the IGBRB can provide valuable insights and recommendations to deal with the future waves of COVID-19 pandemic in this region that can go a long way in achieving the UN-SDGs.

Unlocking capacities of genomics for the COVID-19 response and future pandemics

During the COVID-19 pandemic, genomics and bioinformatics have emerged as essential public health tools. The genomic data acquired using these methods have supported the global health response, facilitated development of testing methods, and allowed timely tracking of novel SARS-CoV-2 variants. Yet the virtually unlimited potential for rapid generation and analysis of genomic data is also coupled with unique technical, scientific, and organizational challenges. Here, we discuss the application of genomic and computational methods for the efficient data driven COVID-19 response, advantages of democratization of viral sequencing around the world, and challenges associated with viral genome data collection and processing.

Toward smart diagnosis of pandemic infectious diseases using wastewater-based epidemiology

COVID-19 outbreak revealed fundamental weaknesses of current diagnostic systems, particularly in prediction and subsequently prevention of pandemic infectious diseases (PIDs). Among PIDs detection methods, wastewater-based epidemiology (WBE) has been demonstrated to be a favorable mean for estimation of community-wide health. Besides, by going beyond purely sensing usages of WBE, it can be efficiently exploited in Healthcare 4.0/5.0 for surveillance, monitoring, control, and above all prediction and prevention, thereby, resulting in smart sensing and management of potential outbreaks/epidemics/pandemics. Herein, an overview of WBE sensors for PIDs is presented. The philosophy behind the smart diagnosis of PIDs using WBE with the help of digital technologies is then discussed, as well as their characteristics to be met. Analytical techniques that are pushing the frontiers of smart sensing and have a high potential to be used in the smart diagnosis of PIDs via WBE are surveyed. In this context, we underscore key challenges ahead and provide recommendations for implementing and moving faster toward smart diagnostics.

Efficacy of SARS-CoV-2 wastewater surveillance for detection of COVID-19 at a residential private college

Many colleges and universities utilized wastewater surveillance testing for SARS-CoV-2 RNA as a tool to help monitor and mitigate the COVID-19 pandemic on campuses across the United States during the 2020-2021 academic year. We sought to assess the efficacy of one such program by analyzing data on relative wastewater RNA levels from residential buildings in relation to SARS-CoV-2 cases identified through individual surveillance testing, conducted largely independent of wastewater results. Almost 80% of the cases on campus were associated with positive wastewater tests, resulting in an overall positive predictive value of 79% (Chi square 48.1, Df = 1, p &lt; 0.001). However, half of the positive wastewater samples occurred in the two weeks following the return of a student to the residence hall following the 10-day isolation period, and therefore were not useful in predicting new infections. When these samples were excluded, the positive predictive value of a positive wastewater sample was 54%. Overall, we conclude that the continued shedding of viral RNA by patients past the time of potential transmission confounds the identification of new cases using wastewater surveillance, and decreases its effectiveness in managing SARS-CoV-2 infections on a residential college campus.

Insight into prognostics, diagnostics, and management strategies for SARS CoV-2

The foremost challenge in countering infectious diseases is the shortage of effective therapeutics. The emergence of coronavirus disease (COVID-19) outbreak has posed a great menace to the public health system globally, prompting unprecedented endeavors to contain the virus. Many countries have organized research programs for therapeutics and management development. However, the longstanding process has forced authorities to implement widespread infrastructures for detailed prognostic and diagnostics study of severe acute respiratory syndrome (SARS CoV-2). This review discussed nearly all the globally developed diagnostic methodologies reported for SARS CoV-2 detection. We have highlighted in detail the approaches for evaluating COVID-19 biomarkers along with the most employed nucleic acid- and protein-based detection methodologies and the causes of their severe downfall and rejection. As the variable variants of SARS CoV-2 came into the picture, we captured the breadth of newly integrated digital sensing prototypes comprised of plasmonic and field-effect transistor-based sensors along with commercially available food and drug administration (FDA) approved detection kits. However, more efforts are required to exploit the available resources to manufacture cheap and robust diagnostic methodologies. Likewise, the visualization and characterization tools along with the current challenges associated with waste-water surveillance, food security, contact tracing, and their role during this intense period of the pandemic have also been discussed. We expect that the integrated data will be supportive and aid in the evaluation of sensing technologies not only in current but also future pandemics.

Review and Meta‐Analysis: SARS‐CoV‐2 and Enveloped Virus Detection in Feces and Wastewater

Detection and quantification of viruses supplies key information on their spread and allows risk assessment for public health. In wastewater, existing detection methods have been focusing on non‐enveloped enteric viruses due to enveloped virus transmission, such as coronaviruses, by the fecal‐oral route being less likely. Since the beginning of the SARS‐CoV‐2 pandemic, interest and importance of enveloped virus detection in wastewater has increased. Here, quantitative studies on SARS‐CoV‐2 occurrence in feces and raw wastewater and other enveloped viruses via quantitative real‐time reverse transcription polymerase chain reaction (RT‐qPCR) during the early stage of the pandemic until April 2021 are reviewed, including statistical evaluation of the positive detection rate and efficiency throughout the detection process involving concentration, extraction, and amplification stages. Optimized and aligned sampling protocols and concentration methods for enveloped viruses, along with SARS‐CoV‐2 surrogates, in wastewater environments may improve low and variable recovery rates providing increased detection efficiency and comparable data on viral load measured across different studies.

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

SARS-CoV-2 presence in wastewater has been reported in several studies and has received widespread attention among the Wastewater-based epidemiology (WBE) community. Such studies can potentially be used as a proxy for early warning of potential COVID-19 outbreak, or as a mitigation measure for potential virus transmission via contaminated water. In this review, we summarized the latest understanding on the detection, concentration, and evaluation of SARS-CoV-2 in wastewater. Importantly, we discuss factors affecting the quality of wastewater surveillance ranging from temperature, pH, starting concentration, as well as the presence of chemical pollutants. These factors greatly affect the reliability and comparability of studies reported by various communities across the world. Overall, this review provides a broadly encompassing guidance for epidemiological study using wastewater surveillance.

Wastewater-based epidemiology in hazard forecasting and early-warning systems for global health risks

With the advent of the SARS-CoV-2 pandemic, Wastewater-Based Epidemiology (WBE) has been applied to track community infection in cities worldwide and has proven succesful as an early warning system for identification of hotspots and changingprevalence of infections (both symptomatic and asymptomatic) at a city or sub-city level. Wastewater is only one of environmental compartments that requires consideration. In this manuscript, we have critically evaluated the knowledge-base and preparedness for building early warning systems in a rapidly urbanising world, with particular attention to Africa, which experiences rapid population growth and urbanisation. We have proposed a Digital Urban Environment Fingerprinting Platform (DUEF) - a new approach in hazard forecasting and early-warning systems for global health risks and an extension to the existing concept of smart cities. The urban environment (especially wastewater) contains a complex mixture of substances including toxic chemicals, infectious biological agents and human excretion products. DUEF assumes that these specific endo- and exogenous residues, anonymously pooled by communities' wastewater, are indicative of community-wide exposure and the resulting effects. DUEF postulates that the measurement of the substances continuously and anonymously pooled by the receiving environment (sewage, surface water, soils and air), can provide near real-time dynamic information about the quantity and type of physical, biological or chemical stressors to which the surveyed systems are exposed, and can create a risk profile on the potential effects of these exposures. Successful development and utilisation of a DUEF globally requires a tiered approach including: Stage I: network building, capacity building, stakeholder engagement as well as a conceptual model, followed by Stage II: DUEF development, Stage III: implementation, and Stage IV: management and utilization. We have identified four key pillars required for the establishment of a DUEF framework: (1) Environmental fingerprints, (2) Socioeconomic fingerprints, (3) Statistics and modelling and (4) Information systems. This manuscript critically evaluates the current knowledge base within each pillar and provides recommendations for further developments with an aim of laying grounds for successful development of global DUEF platforms.

Sensitivity of wastewater-based epidemiology for detection of SARS-CoV-2 RNA in a low prevalence setting

To assist public health responses to COVID-19, wastewater-based epidemiology (WBE) is being utilised internationally to monitor SARS-CoV-2 infections at the community level. However, questions remain regarding the sensitivity of WBE and its use in low prevalence settings. In this study, we estimated the total number of COVID-19 cases required for detection of SARS-CoV-2 RNA in wastewater. To do this, we leveraged a unique situation where, over a 4-month period, all symptomatic and asymptomatic cases, in a population of approximately 120,000, were precisely known and mainly located in a single managed isolation and quarantine facility (MIQF) building. From 9 July to 6 November 2020, 24-hr composite wastewater samples (n = 113) were collected daily from the sewer outside the MIQF, and from the municipal wastewater treatment plant (WWTP) located 5 km downstream. New daily COVID-19 cases at the MIQF ranged from 0 to 17, and for most of the study period there were no cases outside the MIQF identified. SARS-CoV-2 RNA was detected in 54.0% (61/113) at the WWTP, compared to 95.6% (108/113) at the MIQF. We used logistic regression to estimate the shedding of SARS-CoV-2 RNA into wastewater based on four infectious shedding models. With a total of 5 and 10 COVID-19 infectious cases per 100,000 population (0.005% and 0.01% prevalence) the predicated probability of SARS-CoV-2 RNA detection at the WWTP was estimated to be 28 and 41%, respectively. When a proportional shedding model was used, this increased to 58% and 87% for 5 and 10 cases, respectively. In other words, when 10 individuals were actively shedding SARS-CoV-2 RNA in a catchment of 100,000 individuals, there was a high likelihood of detecting viral RNA in wastewater. SARS-CoV-2 RNA detections at the WWTP were associated with increasing COVID-19 cases. Our results show that WBE provides a reliable and sensitive platform for detecting infections at the community scale, even when case prevalence is low, and can be of use as an early warning system for community outbreaks.

Molecular surveillance of tuberculosis-causing mycobacteria in wastewater

The surveillance of tuberculosis infections has largely depended on clinical diagnostics and hospitalization data. The advancement in molecular methods creates an opportunity for the adoption of alternative surveillance systems, such as wastewater-based epidemiology. This study presents the use of conventional and advanced polymerase chain reaction techniques (droplet digital PCR) to determine the occurrence and concentration of total mycobacteria and members of the Mycobacterium tuberculosis complex (MTBC) in treated and untreated wastewater. Wastewater samples were taken from three wastewater treatment plants (WWTPs) in the city of Durban, South Africa, known for a high burden of TB/MDR-TB due to HIV infections. All untreated wastewater samples contained total mycobacteria and MTBC at varying percentages per WWTP studied. Other members of the MTBC related to tuberculosis infection in animals, M. bovis and M. caprae were also detected. The highest median concentration detected in untreated wastewater was up to 4.9 (±0.2) Log10 copies/ml for total mycobacteria, 4.0 (±0.85) Log10 copies/ml for MTBC, 3.9 (±0.54) Log10 copies/ml for M. tuberculosis, 2.7 (±0.42) Log10 copies/ml for M. africanum, 4.0 (±0.29) Log10 copies/ml for M. bovis and 4.5 (±0.52) Log10 copies/ml for M. caprae. Lower concentrations were detected in the treated wastewater, with a statistically significant difference (P-value ≤ 0.05) in concentrations observed. The log reduction achieved for these bacteria in the respective WWTPs was not statistically different, indicating that the treatment configuration did not have an impact on their removal. The detection of M. africanum in wastewater from South Africa shows that it is possible that some of the TB infections in the community could be caused by this mycobacterium. This study, therefore, highlights the potential of wastewater-based epidemiology for monitoring tuberculosis infections.

Understanding and managing uncertainty and variability for wastewater monitoring beyond the pandemic: Lessons learned from the United Kingdom national COVID-19 surveillance programmes

The COVID-19 pandemic has put unprecedented pressure on public health resources around the world. From adversity, opportunities have arisen to measure the state and dynamics of human disease at a scale not seen before. In the United Kingdom, the evidence that wastewater could be used to monitor the SARS-CoV-2 virus prompted the development of National wastewater surveillance programmes. The scale and pace of this work has proven to be unique in monitoring of virus dynamics at a national level, demonstrating the importance of wastewater-based epidemiology (WBE) for public health protection. Beyond COVID-19, it can provide additional value for monitoring and informing on a range of biological and chemical markers of human health. A discussion of measurement uncertainty associated with surveillance of wastewater, focusing on lessons-learned from the UK programmes monitoring COVID-19 is presented, showing that sources of uncertainty impacting measurement quality and interpretation of data for public health decision-making, are varied and complex. While some factors remain poorly understood, we present approaches taken by the UK programmes to manage and mitigate the more tractable sources of uncertainty. This work provides a platform to integrate uncertainty management into WBE activities as part of global One Health initiatives beyond the pandemic.

COVID-19 case prediction via wastewater surveillance in a low-prevalence urban community: a modeling approach

Estimating and predicting the epidemic size from wastewater surveillance results remains challenging for the practical implementation of wastewater-based epidemiology (WBE). In this study, by employing a highly sensitive detection method, we documented the time series of SARS-CoV-2 RNA occurrence in the wastewater influent from an urban community with a 360,000 population in Japan, from August 2020 to February 2021. The detection frequency of the viral RNA increased during the outbreak events of COVID-19 and the highest viral RNA concentration was recorded at the beginning of January 2021, amid the most serious outbreak event during the study period. We found that: (1) direct back-calculation still suffers from great uncertainty dominated by inconsistent detection and the varying gap between the observed wastewater viral load and the estimated patient viral load, and (2) the detection frequency correlated well with reported cases and the prediction of the latter can be carried out via data-driven modeling methods. Our results indicate that wastewater virus occurrence can contribute to epidemic surveillance in ways more than back-calculation, which may spawn future wastewater surveillance implementations.

Building knowledge of university campus population dynamics to enhance near-to-source sewage surveillance for SARS-CoV-2 detection

Wastewater surveillance has been widely implemented for monitoring of SARS-CoV-2 during the global COVID-19 pandemic, and near-to-source monitoring is of particular interest for outbreak management in discrete populations. However, variation in population size poses a challenge to the triggering of public health interventions using wastewater SARS-CoV-2 concentrations. This is especially important for near-to-source sites that are subject to significant daily variability in upstream populations. Focusing on a university campus in England, this study investigates methods to account for variation in upstream populations at a site with highly transient footfall and provides a better understanding of the impact of variable populations on the SARS-CoV-2 trends provided by wastewater-based epidemiology. The potential for complementary data to help direct response activities within the near-to-source population is also explored, and potential concerns arising due to the presence of heavily diluted samples during wet weather are addressed. Using wastewater biomarkers, it is demonstrated that population normalisation can reveal significant differences between days where SARS-CoV-2 concentrations are very similar. Confidence in the trends identified is strongest when samples are collected during dry weather periods; however, wet weather samples can still provide valuable information. It is also shown that building-level occupancy estimates based on complementary data aid identification of potential sources of SARS-CoV-2 and can enable targeted actions to be taken to identify and manage potential sources of pathogen transmission in localised communities.

SARS-CoV-2 RNA in urban wastewater samples to monitor the COVID-19 pandemic in Lombardy, Italy (March-June 2020)

Wastewater-based viral surveillance was proposed as a promising approach to monitor the circulation of SARS-CoV-2 in the general population. The aim of this study was to develop an analytical method to detect SARS-CoV-2 RNA in urban wastewater, and apply it to follow the trends of epidemic in the framework of a surveillance network in the Lombardy region (Northern Italy). This area was the first hotspot of COVID-19 in Europe and was severely affected. Composite 24 h samples were collected weekly in eight cities from end-March to mid-June 2020 (first peak of the pandemic). The method developed and optimized, involved virus concentration using PEG centrifugation, and one-step real-time RT-PCR for analysis. SARS-CoV-2 RNA was identified in 65 (61%) out of 107 samples, and the viral concentrations (up to 2.1 E + 05 copies/L) were highest in March-April. By mid-June, wastewater samples tested negative in all the cities corresponding to the very low number of cases recorded in the same period. Viral loads were calculated considering the wastewater daily flow rate and the population served by each wastewater treatment plant, and were used for inter- city comparison. The highest viral loads were found in Brembate, Ranica and Lodi corresponding to the hotspots of the first peak of pandemic. The pattern of decrease of SARS-CoV-2 in wastewater was closely comparable to the decline of active COVID-19 cases in the population, reflecting the effect of lock-down. This study tested wastewater surveillance of SARS-CoV-2 to follow the pandemic trends in one of most affected areas worldwide, demonstrating that it can integrate ongoing virological surveillance of COVID-19, providing information from both symptomatic and asymptomatic individuals, and monitoring the effect of health interventions.

SARS-CoV-2 variant detection from wastewater: rapid spread of B.1.1.7 lineage in Hungary

Wastewater-based epidemiology (WBE) is a recognised tool for tracking community transmission of COVID-19. From the second half of 2020, the emergence of new, highly infective, more pathogenic or vaccine-escape SARS-CoV-2 variants is the major public health concern. Variant analysis in sewage might assist the early detection of new mutations. Weekly raw sewage samples from 22 wastewater treatment plants (WWTPs) in Hungary (representing 40% of the population) were analysed between December 2020 and March 2021 for signature mutations N501Y and del H69/V70 of B.1.1.7 lineage by melting point genotyping and RT-digital droplet PCR (RT-ddPCR). The latter method proved to be more efficient in parallel detection of different variants and also provides quantitative information. Wastewater surveillance indicated that the B.1.1.7 variant first emerged in Budapest in early January 2021 and rapidly became dominant in the entire country. Results are in close agreement with the available clinical data (Pearson's correlation coefficient, R = 0.9153). RT-ddPCR was confirmed to be a reliable tool for tracking emerging variant ratios in wastewaters. It is a rapid and cost-effective method compared to whole-genome sequencing, but only applicable for the detection of known mutations. Efficient variant surveillance might require the combination of multiple methods.

SARS-CoV-2 RNA concentrations in wastewater foreshadow dynamics and clinical presentation of new COVID-19 cases

Current estimates of COVID-19 prevalence are largely based on symptomatic, clinically diagnosed cases. The existence of a large number of undiagnosed infections hampers population-wide investigation of viral circulation. Here, we quantify the SARS-CoV-2 concentration and track its dynamics in wastewater at a major urban wastewater treatment facility in Massachusetts, between early January and May 2020. SARS-CoV-2 was first detected in wastewater on March 3. SARS-CoV-2 RNA concentrations in wastewater correlated with clinically diagnosed new COVID-19 cases, with the trends appearing 4-10 days earlier in wastewater than in clinical data. We inferred viral shedding dynamics by modeling wastewater viral load as a convolution of back-dated new clinical cases with the average population-level viral shedding function. The inferred viral shedding function showed an early peak, likely before symptom onset and clinical diagnosis, consistent with emerging clinical and experimental evidence. This finding suggests that SARS-CoV-2 concentrations in wastewater may be primarily driven by viral shedding early in infection. This work shows that longitudinal wastewater analysis can be used to identify trends in disease transmission in advance of clinical case reporting, and infer early viral shedding dynamics for newly infected individuals, which are difficult to capture in clinical investigations.

The source and fate of Mycobacterium tuberculosis complex in wastewater and possible routes of transmission

BACKGROUND

The Mycobacterium tuberculosis complex (MTBC) consists of causative agents of both human and animal tuberculosis and is responsible for over 10 million annual infections globally. Infections occur mainly through airborne transmission, however, there are possible indirect transmissions through a faecal-oral route which is poorly reported. This faecal-oral transmission could be through the occurrence of the microbe in environments such as wastewater. This manuscript, therefore, reviews the source and fate of MTBC in the wastewater environment, including the current methods in use and the possible risks of infections.

RESULTS

The reviewed literature indicates that about 20% of patients with pulmonary TB may have extra-pulmonary manifestations such as GITB, resulting in shedding in feaces and urine. This could potentially be the reason for the detection of MTBC in wastewater. MTBC concentrations of up to 5.5 × 105 (±3.9 × 105) copies/L of untreated wastewater have been reported. Studies have indicated that wastewater may provide these bacteria with the required nutrients for their growth and could potentially result in environmental transmission. However, 98.6 (± 2.7) %, removal during wastewater treatment, through physical-chemical decantation (primary treatment) and biofiltration (secondary treatment) has been reported. Despite these reports, several studies observed the presence of MTBC in treated wastewater via both culture-dependent and molecular techniques.

CONCLUSION

The detection of viable MTBC cells in either treated or untreated wastewater, highlights the potential risks of infection for wastewater workers and communities close to these wastewater treatment plants. The generation of aerosols during wastewater treatment could be the main route of transmission. Additionally, direct exposure to the wastewater containing MTBC could potentially contribute to indirect transmissions which may lead to pulmonary or extra-pulmonary infections. This calls for the implementation of risk reduction measures aimed at protecting the exposed populations.

Wastewater surveillance to infer COVID-19 transmission: A systematic review

Successful detection of SARS-COV-2 in wastewater suggests the potential utility of wastewater-based epidemiology (WBE) for COVID-19 community surveillance. This systematic review aims to assess the performance of wastewater surveillance as early warning system of COVID-19 community transmission. A systematic search was conducted in PubMed, Medline, Embase and the WBE Consortium Registry according to PRISMA guidelines for relevant articles published until 31st July 2021. Relevant data were extracted and summarized. Quality of each paper was assessed using an assessment tool adapted from Bilotta et al.'s tool for environmental science. Of 763 studies identified, 92 studies distributed across 34 countries were shortlisted for qualitative synthesis. A total of 26,197 samples were collected between January 2020 and May 2021 from various locations serving population ranging from 321 to 11,400,000 inhabitants. Overall sample positivity was moderate at 29.2% in all examined settings with the spike (S) gene having maximum rate of positive detections and nucleocapsid (N) gene being the most targeted. Wastewater signals preceded confirmed cases by up to 63 days, with 13 studies reporting sample positivity before the first cases were detected in the community. At least 50 studies reported an association of viral load with community cases. While wastewater surveillance cannot replace large-scale diagnostic testing, it can complement clinical surveillance by providing early signs of potential transmission for more active public health responses. However, more studies using standardized and validated methods are required along with risk analysis and modelling to understand the dynamics of viral outbreaks.

Environmental spreading of clinically relevant carbapenem-resistant gram-negative bacilli: the occurrence of blaKPC-or-NDM strains relates to local hospital activities

Background

Aquatic matrices impacted by sewage may shelter carbapenem-resistant (CR) Gram-negative bacilli (GNB) harboring resistance genes of public health concern. In this study, sewage treatment plants (STPs) servicing well-defined catchment areas were surveyed for the presence of CR-GNB bearing carbapenemase genes (bla_KPC or bla_NDM).

Results

A total of 325 CR-GNB were recovered from raw (RS) and treated (TS) sewage samples as well as from water body spots upstream (UW) and downstream (DW) from STPs. Klebsiella-Enterobacter (KE) group amounted to 116 isolates (35.7%). CR-KE isolates were recovered from TS, DW (35.7%) and RS samples (44.2%) (p = 0.001); but not from UW samples. KE isolates represented 65.8% of all bla_KPC or bla_NDM positive strains. The frequency of bla_KPC-or-NDM strains was positively associated with the occurrence of district hospitals located near STPs, as well as with the number of hospitalizations and of sewer connections serviced by the STPs. bla_KPC-or-NDM strains were recovered from ST samples in 7 out of 14 STPs, including four tertiary-level STPs; and from 6 out of 13 DW spots whose RS samples also had bla_KPC-or-NDM strains.

Conclusions

Clinically relevant GNB bearing bla_KPC-or-NDM resist sewage treatments and spread into environmental aquatic matrices mainly from STPs impacted by hospital activities.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12866-021-02400-1.

Environmental Biofilms as Reservoirs for Antimicrobial Resistance

Characterizing the response of microbial communities to a range of antibiotic concentrations is one of the strategies used to understand the impact of antibiotic resistance. Many studies have described the occurrence and prevalence of antibiotic resistance in microbial communities from reservoirs such as hospitals, sewage, and farm feedlots, where bacteria are often exposed to high and/or constant concentrations of antibiotics. Outside of these sources, antibiotics generally occur at lower, sub-minimum inhibitory concentrations (sub-MICs). The constant exposure to low concentrations of antibiotics may serve as a chemical "cue" that drives development of antibiotic resistance. Low concentrations of antibiotics have not yet been broadly described in reservoirs outside of the aforementioned environments, nor is the transfer and dissemination of antibiotic resistant bacteria and genes within natural microbial communities fully understood. This review will thus focus on low antibiotic-concentration environmental reservoirs and mechanisms that are important in the dissemination of antibiotic resistance to help identify key knowledge gaps concerning the environmental resistome.

Identification of sampling points for the detection of SARS-CoV-2 in the sewage system

A suitable tool for monitoring the spread of SARS-CoV-2 is to identify potential sampling points in the wastewater collection system that can be used to monitor the distribution of COVID-19 disease affected clusters within a city. The applicability of the developed methodology is presented through the description of the 72,837 population equivalent wastewater collection system of the city of Nagykanizsa, Hungary and the results of the analytical and epidemiological measurements of the wastewater samples. The wastewater sampling was conducted during the 3rd wave of the COVID-19 epidemic. It was found that the overlap between the road system and the wastewater network is high, it is 82 %. It was showed that the proposed methodological approach, using the tools of network science, determines confidently the zones of the wastewater collection system and provides the ideal monitoring points in order to provide the best sampling resolution in urban areas. The strength of the presented approach is that it estimates the network based on publicly available information. It was concluded that the number of zones or sampling points can be chosen based on relevant epidemiological intervention and mitigation strategies. The algorithm allows for continuous effective monitoring of the population infected by SARS-CoV-2 in small-sized cities.

Wastewater SARS-CoV-2 monitoring as a community-level COVID-19 trend tracker and variants in Ohio, United States

The global pandemic caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has resulted in more than 129 million confirm cases. Many health authorities around the world have implemented wastewater-based epidemiology as a rapid and complementary tool for the COVID-19 surveillance system and more recently for variants of concern emergence tracking. In this study, three SARS-CoV-2 target genes (N1 and N2 gene regions, and E gene) were quantified from wastewater influent samples (n = 250) obtained from the capital city and 7 other cities in various size in central Ohio from July 2020 to January 2021. To determine human-specific fecal strength in wastewater samples more accurately, two human fecal viruses (PMMoV and crAssphage) were quantified to normalize the SARS-CoV-2 gene concentrations in wastewater. To estimate the trend of new case numbers from SARS-CoV-2 gene levels, different statistical models were built and evaluated. From the longitudinal data, SARS-CoV-2 gene concentrations in wastewater strongly correlated with daily new confirmed COVID-19 cases (average Spearman's r = 0.70, p < 0.05), with the N2 gene region being the best predictor of the trend of confirmed cases. Moreover, average daily case numbers can help reduce the noise and variation from the clinical data. Among the models tested, the quadratic polynomial model performed best in correlating and predicting COVID-19 cases from the wastewater surveillance data, which can be used to track the effectiveness of vaccination in the later stage of the pandemic. Interestingly, neither of the normalization methods using PMMoV or crAssphage significantly enhanced the correlation with new case numbers, nor improved the estimation models. Viral sequencing showed that shifts in strain-defining variants of SARS-CoV-2 in wastewater samples matched those in clinical isolates from the same time periods. The findings from this study support that wastewater surveillance is effective in COVID-19 trend tracking and provide sentinel warning of variant emergence and transmission within various types of communities.

COVID-19 wastewater surveillance in rural communities: Comparison of lagoon and pumping station samples

Wastewater-based epidemiology/wastewater surveillance has been a topic of significant interest over the last year due to its application in SARS-CoV-2 surveillance to track prevalence of COVID-19 in communities. Although SARS-CoV-2 surveillance has been applied in more than 50 countries to date, the application of this surveillance has been largely focused on relatively affluent urban and peri-urban communities. As such, there is a knowledge gap regarding the implementation of reliable wastewater surveillance in small and rural communities for the purpose of tracking rates of incidence of COVID-19 and other pathogens or biomarkers. This study examines the relationships existing between SARS-CoV-2 viral signal from wastewater samples harvested from an upstream pumping station and from an access port at a downstream wastewater treatment lagoon with the community's COVID-19 rate of incidence (measured as percent test positivity) in a small, rural community in Canada. Real-time quantitative polymerase chain reaction (RT-qPCR) targeting the N1 and N2 genes of SARS-CoV-2 demonstrate that all 24-h composite samples harvested from the pumping station over a period of 5.5 weeks had strong viral signal, while all samples 24-h composite samples harvested from the lagoon over the same period were below the limit of quantification. RNA concentrations and integrity of samples harvested from the lagoon were both lower and more variable than from samples from the upstream pumping station collected on the same date, indicating a higher overall stability of SARS-CoV-2 RNA upstream of the lagoon. Additionally, measurements of PMMoV signal in wastewater allowed normalizing SARS-CoV-2 viral signal for fecal matter content, permitting the detection of actual changes in community prevalence with a high level of granularity. As a result, in sewered small and rural communities or low-income regions operating wastewater lagoons, samples for wastewater surveillance should be harvested from pumping stations or the sewershed as opposed to lagoons.

Wastewater SARS-CoV-2 monitoring as a community-level COVID-19 trend tracker and variants in Ohio, United States

The global pandemic caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has resulted in more than 129 million confirm cases. Many health authorities around the world have implemented wastewater-based epidemiology as a rapid and complementary tool for the COVID-19 surveillance system and more recently for variants of concern emergence tracking. In this study, three SARS-CoV-2 target genes (N1 and N2 gene regions, and E gene) were quantified from wastewater influent samples (n = 250) obtained from the capital city and 7 other cities in various size in central Ohio from July 2020 to January 2021. To determine human-specific fecal strength in wastewater samples more accurately, two human fecal viruses (PMMoV and crAssphage) were quantified to normalize the SARS-CoV-2 gene concentrations in wastewater. To estimate the trend of new case numbers from SARS-CoV-2 gene levels, different statistical models were built and evaluated. From the longitudinal data, SARS-CoV-2 gene concentrations in wastewater strongly correlated with daily new confirmed COVID-19 cases (average Spearman's r = 0.70, p < 0.05), with the N2 gene region being the best predictor of the trend of confirmed cases. Moreover, average daily case numbers can help reduce the noise and variation from the clinical data. Among the models tested, the quadratic polynomial model performed best in correlating and predicting COVID-19 cases from the wastewater surveillance data, which can be used to track the effectiveness of vaccination in the later stage of the pandemic. Interestingly, neither of the normalization methods using PMMoV or crAssphage significantly enhanced the correlation with new case numbers, nor improved the estimation models. Viral sequencing showed that shifts in strain-defining variants of SARS-CoV-2 in wastewater samples matched those in clinical isolates from the same time periods. The findings from this study support that wastewater surveillance is effective in COVID-19 trend tracking and provide sentinel warning of variant emergence and transmission within various types of communities.

Molecular Methods for Pathogenic Bacteria Detection and Recent Advances in Wastewater Analysis

With increasing concerns about public health and the development of molecular techniques, new detection tools and the combination of existing approaches have increased the abilities of pathogenic bacteria monitoring by exploring new biomarkers, increasing the sensitivity and accuracy of detection, quantification, and analyzing various genes such as functional genes and antimicrobial resistance genes (ARG). Molecular methods are gradually emerging as the most popular detection approach for pathogens, in addition to the conventional culture-based plate enumeration methods. The analysis of pathogens in wastewater and the back-estimation of infections in the community, also known as wastewater-based epidemiology (WBE), is an emerging methodology and has a great potential to supplement current surveillance systems for the monitoring of infectious diseases and the early warning of outbreaks. However, as a complex matrix, wastewater largely challenges the analytical performance of molecular methods. This review synthesized the literature of typical pathogenic bacteria in wastewater, types of biomarkers, molecular methods for bacterial analysis, and their recent advances in wastewater analysis. The advantages and limitation of these molecular methods were evaluated, and their prospects in WBE were discussed to provide insight for future development.

Challenges and emerging perspectives of an international SARS-CoV-2 epidemiological surveillance in wastewater

SARS-CoV-2 is a new type of coronavirus capable to infect humans and cause the severe acute respiratory syndrome COVID-19, a disease that has been causing huge impacts across the Earth. COVID-19 patients, including mild, pre-symptomatic and asymptomatic cases, were often seen to contain infectious fragments of SARS-CoV-2 in feces and urine samples. Therefore, studies to detect the new coronavirus in wastewater, which collect and concentrate human excreta, have been extremely useful as a viral tracking tool in communities. This type of monitoring, in addition to serve as a non-invasive early warning of COVID-19 outbreaks, would provide better predictions about the SARS-CoV-2 spread and strongly contribute to maintenance the global health. Although current methods to detect viruses in wastewater, based on molecular RT-PCR and RT-qPCR techniques, were considered as reliable and provided accurate qualitative and quantitative results, they have been facing considerable challenges concerning the SARS-CoV-2 surveillance. In this review, the methods used to detect the SARS-CoV-2 in wastewater and the challenges to implement an international viral monitoring network were described. The article also addressed the emerging perspectives associated with the SARS-CoV-2 epidemiological surveillance in this environment and the importance of a worldwide collaboration to generate and disseminate the detection results.

Proposed approaches for coronaviruses elimination from wastewater: Membrane techniques and nanotechnology solutions

Since the beginning of the third Millennium, specifically during the last 18 years, three outbreaks of diseases have been recorded caused by coronaviruses (CoVs). The latest outbreak of these diseases was Coronavirus Disease 2019 (COVID-19), which has been declared by the World Health Organization (WHO) as a pandemic. For this reason, current efforts of the environmental, epidemiology scientists, engineers, and water sector professionals are ongoing to detect CoV in environmental components, especially water, and assess the relative risk of exposure to these systems and any measures needed to protect the public health, workers, and public, in general. This review presents a brief overview of CoV in water, wastewater, and surface water based on a literature search providing different solutions to keep water protected from CoV. Membrane techniques are very attractive solutions for virus elimination in water. In addition, another essential solution is nanotechnology and its applications in the detection and protection of human and water systems.

SARS-CoV-2 in a stream running through an underprivileged, underserved, urban settlement in São Paulo, Brazil: A 7-month follow-up

COVID-19 pandemic has led to concerns on the circulation of SARS-CoV-2 in the environment, its infectivity from the environment and, the relevance of transmission via environmental compartments. During 31 weeks, water samples were collected from a heavily contaminated stream going through an urban, underprivileged community without sewage collection. Our results showed a statistically significant correlation between cases of COVID-19 and SARS in the community, and SARS-CoV-2 concentrations in the water. Based on the model, if the concentrations of SARS-CoV-RNA (N1 and N2 target regions) increase 10 times, there is an expected increase of 104% [95%CI: (62-157%)] and 92% [95%CI: (51-143%)], respectively, in the number of cases of COVID-19 and SARS. We believe that differences in concentration of the virus in the environment reflect the epidemiological status in the community, which may be important information for surveillance and controlling dissemination in areas with vulnerable populations and poor sanitation. None of the samples were found infectious based cultures. Our results may be applicable globally as similar communities exist worldwide.

Lessons learned from SARS-CoV-2 measurements in wastewater

Standardized protocols for wastewater-based surveillance (WBS) for the RNA of SARS-CoV-2, the virus responsible for the current COVID-19 pandemic, are being developed and refined worldwide for early detection of disease outbreaks. We report here on lessons learned from establishing a WBS program for SARS-CoV-2 integrated with a human surveillance program for COVID-19. We have established WBS at three campuses of a university, including student residential dormitories and a hospital that treats COVID-19 patients. Lessons learned from this WBS program address the variability of water quality, new detection technologies, the range of detectable viral loads in wastewater, and the predictive value of integrating environmental and human surveillance data. Data from our WBS program indicated that water quality was statistically different between sewer sampling sites, with more variability observed in wastewater coming from individual buildings compared to clusters of buildings. A new detection technology was developed based upon the use of a novel polymerase called V2G. Detectable levels of SARS-CoV-2 in wastewater varied from 10² to 10⁶ genomic copies (gc) per liter of raw wastewater (L). Integration of environmental and human surveillance data indicate that WBS detection of 100 gc/L of SARS-CoV-2 RNA in wastewater was associated with a positivity rate of 4% as detected by human surveillance in the wastewater catchment area, though confidence intervals were wide (β ~ 8.99 ∗ ln(100); 95% CI = 0.90-17.08; p < 0.05). Our data also suggest that early detection of COVID-19 surges based on correlations between viral load in wastewater and human disease incidence could benefit by increasing the wastewater sample collection frequency from weekly to daily. Coupling simpler and faster detection technology with more frequent sampling has the potential to improve the predictive potential of using WBS of SARS-CoV-2 for early detection of the onset of COVID-19.

Hepatitis A Outbreaks and Environmental Circulation of Genotype IA Strains in the São Paulo City, 2017-2018

Hepatitis A virus (HAV) is the major cause of enterically transmitted infectious hepatitis. Between 2016 and 2017, the number of confirmed cases of hepatitis A virus (HAV) increased from 64 to 786 in São Paulo affecting mainly adults aged between 18 and 39 years (80%) and males (88%). To support epidemiological surveillance, the present study monitored the presence of HAV in urban sewage samples collected bimonthly for 1 year (November 2017-November 2018) in the central region of the city, where most of cases were detected. Sewage samples were concentrated by polyethylene glycol precipitation and HAV RNA was quantified by RT-qPCR. Nucleotide sequencing targeting the VP1/2A junction region was carried out to genotype the HAV strains. HAV was detected in 76.9% (40/52) of the samples, with a geometric mean viral load of 5.09 × 10⁴ (± SD 4.51 × 10⁵) genome copies (GC/L) (Mauá Street) and 5.27 × 10⁴ (± SD 1.26 × 10⁶) GC/L (Prestes Maia Avenue). Of the 40 positive samples, 8 were typed as HAV subgenotype IA [100% nucleotide (nt) identity with HAV strain VRD_521_2016]. Highest homology was obtained with sequences from European countries (Italy, Spain) and Israel, all of which had reported recent HAV outbreaks associated with men who have sex with men. Our results highlight that wastewater surveillance is a useful tool to support investigating HAV outbreaks in the community, including circulating genotypes.

Surveillance of SARS-CoV-2 in extensive monitoring of municipal wastewater: key issues to yield reliable results

Several studies have detected SARS-CoV-2 in the stool of infected people as in urban wastewater. The quantification of SARS-CoV-2 in wastewater appears today as a powerful tool that can help in wastewater-based epidemiology (WBE). The goal is to improve the prediction of new waves of COVID-19 outbreaks and provide an early warning of the evolution of the infection. In this research, we highlighted some practical and scientific aspects that emerged during an extensive ongoing monitoring campaign carried out on a large number of wastewater treatment plants located in the province of Trento (North Italy) and aimed at the detection of SARS-CoV-2 in raw municipal wastewater. The open issues underline are related to the collection and storage (sampling protocol, storage and heat treatment), to the molecular analysis (enrichment phase), and to the mathematical calculation of SARS-CoV-2 load in wastewater, suitable for WBE (standard curve to obtain the concentration of genomic units and flow rate measurements). This study provides some insights that can help in the implementation of surveillance plans in other regions.

A Novel Multidrug Resistant, Non-Tn4401 Genetic Element-Bearing, Strain of Klebsiella pneumoniae Isolated From an Urban Lake With Drinking and Recreational Water Reuse

Antimicrobial resistance (AMR) is an increasing and urgent issue for human health worldwide, as it leads to the reduction of available antibiotics to treat bacterial infections, in turn increasing hospital stays and lethality. Therefore, the study and genomic surveillance of bacterial carriers of resistance in and outside of clinical settings is of utter importance. A colony of multidrug resistant (MDR) bacteria identified as Klebsiella spp., by 16S rDNA amplicon sequencing, has been isolated from an urban lake in Brazil, during a drug-degrading bacterial prospection. Genomic analyses revealed the bacteria as Klebsiella pneumoniae species. Furthermore, the in silico Multilocus Sequence Typing (MLST) identified the genome as a new sequence type, ST5236. The search for antimicrobial resistance genes (ARGs) detected the presence of genes against beta-lactams, fosfomycin, acriflavine and efflux pumps, as well as genes for heavy metal resistance. Of particular note, an extended-spectrum beta-lactamase gene (blaCTX-M-15) has been detected in close proximity to siphoviridae genes, while a carbapenemase gene (KPC-2) has been found in an extrachromosomal contig, within a novel non-Tn4401 genetic element (NTEKPC). An extrachromosomal contig found in the V3 isolate is identical to a contig of a K. pneumoniae isolate from a nearby hospital, which indicates a putative gene flow from the hospital network into Paranoá lake. The discovery of a MDR isolate in this lake is worrisome, as the region has recently undergone periods of water scarcity causing the lake, which receives treated wastewater effluent, and is already used for recreational purposes, to be used as an environmental buffer for drinking water reuse. Altogether, our results indicate an underrepresentation of environmental K. pneumoniae among available genomes, which may hamper the understanding of the population dynamics of the species in the environment and its consequences in the spread of ARGs and virulence genes.

Mass Spectrometry in Wastewater-Based Epidemiology for the Determination of Small and Large Molecules as Biomarkers of Exposure: Toward a Global View of Environment and Human Health under the COVID-19 Outbreak

Wastewater-based epidemiology (WBE) estimates collective consumption or exposure to chemicals or pathogens by monitoring the substances excreted in the population's wastewater. Advances in mass spectrometry (MS) and the application of some clinical diagnostic tools and proteomics to wastewater fingerprinting have been linked to the discovery of new biomarkers and indicators of population health and are broadening the scope of WBE that nowadays cover not only small molecule biomarkers but also genetic biomarkers, large molecules, viruses, infection diseases, resistance, etc. This mini-review highlights recent WBE advances using MS and how this progress can create a fingerprint of a city's health hazards, habits, and lifestyle, which is gaining in public health emphasis.

Prevalence of SARS-CoV-2 genes in water reclamation facilities: From influent to anaerobic digester

Several treatment plants were sampled for influent, primary clarifier sludge, return activated sludge (RAS), and anaerobically digested sludge throughout nine weeks during the summer of the COVID-19 pandemic. Primary clarifier sludge had a significantly higher number of SARS-CoV-2 gene copy number per liter (GC/L) than other sludge samples, within a range from 1.0 × 10⁵ to 1.0 × 10⁶ GC/L. Gene copy numbers in raw influent significantly correlated with gene copy numbers in RAS in Silver Creek (p-value = 0.007, R² = 0.681) and East Canyon (p-value = 0.009, R² = 0.775) WRFs; both of which lack primary clarifiers or industrial pretreatment processes. This data indicates that SARS-CoV-2 gene copies tend to partition into primary clarifier sludges, at which point a significant portion of them are removed through sedimentation. Furthermore, it was found that East Canyon WRF gene copy numbers in influent were a significant predictor of daily cases (p-value = 0.0322, R² = 0.561), and gene copy numbers in RAS were a significant predictor of weekly cases (p-value = 0.0597, R² = 0.449). However, gene copy numbers found in primary sludge samples from other plants significantly predicted the number of COVID-19 cases for the following week (t = 2.279) and the week after that (t = 2.122) respectively. These data indicate that SARS-CoV-2 extracted from WRF biosolids may better suit epidemiological monitoring that exhibits a time lag. It also supports the observation that primary sludge removes a significant portion of SARS-CoV-2 marker genes. In its absence, RAS can also be used to predict the number of COVID-19 cases due to direct flow through from influent. This research represents the first of its kind to thoroughly examine SARS-CoV-2 gene copy numbers in biosolids throughout the wastewater treatment process and the relationship between primary, return activated, and anaerobically digested sludge and reported positive COVID-19 cases.

A direct capture method for purification and detection of viral nucleic acid enables epidemiological surveillance of SARS-CoV-2

Studies have demonstrated that SARS-CoV-2 RNA can be detected in the feces of infected individuals. This finding spurred investigation into using wastewater-based epidemiology (WBE) to monitor SARS-CoV-2 RNA and track the appearance and spread of COVID-19 in communities. SARS-CoV-2 is present at low levels in wastewater, making sample concentration a prerequisite for sensitive detection and utility in WBE. Whereas common methods for isolating viral genetic material are biased toward intact virus isolation, it is likely that a relatively low percentage of the total SARS-CoV-2 RNA genome in wastewater is contained within intact virions. Therefore, we hypothesized that a direct unbiased total nucleic acid(TNA) extraction method could overcome the cumbersome protocols, variability and low recovery rates associated with the former methods. This led to development of a simple, rapid, and modular alternative to existing purification methods. In an initial concentration step, chaotropic agents are added to raw sewage allowing binding of nucleic acid from free nucleoprotein complexes, partially intact, and intact virions to a silica matrix. The eluted nucleic acid is then purified using manual or semi-automated methods. RT-qPCR enzyme mixes were formulated that demonstrate substantial inhibitor resistance. In addition, multiplexed probe-based RT-qPCR assays detecting the N1, N2 (nucleocapsid) and E (envelope) gene fragments of SARS-CoV-2 were developed. The RT-qPCR assays also contain primers and probes to detect Pepper Mild Mottle Virus (PMMoV), a fecal indicator RNA virus present in wastewater, and an exogenous control RNA to measure effects of RT-qPCR inhibitors. Using this workflow, we monitored wastewater samples from three wastewater treatment plants (WWTP) in Dane County, Wisconsin. We also successfully sequenced a subset of samples to ensure compatibility with a SARS-CoV-2 amplicon panel and demonstrated the potential for SARS-CoV-2 variant detection. Data obtained here underscore the potential for wastewater surveillance of SARS-CoV-2 and other infectious agents in communities.

A direct capture method for purification and detection of viral nucleic acid enables epidemiological surveillance of SARS-CoV-2

Studies have demonstrated that SARS-CoV-2 RNA can be detected in the feces of infected individuals. This finding spurred investigation into using wastewater-based epidemiology (WBE) to monitor SARS-CoV-2 RNA and track the appearance and spread of COVID-19 in communities. SARS-CoV-2 is present at low levels in wastewater, making sample concentration a prerequisite for sensitive detection and utility in WBE. Whereas common methods for isolating viral genetic material are biased toward intact virus isolation, it is likely that a relatively low percentage of the total SARS-CoV-2 RNA genome in wastewater is contained within intact virions. Therefore, we hypothesized that a direct unbiased total nucleic acid(TNA) extraction method could overcome the cumbersome protocols, variability and low recovery rates associated with the former methods. This led to development of a simple, rapid, and modular alternative to existing purification methods. In an initial concentration step, chaotropic agents are added to raw sewage allowing binding of nucleic acid from free nucleoprotein complexes, partially intact, and intact virions to a silica matrix. The eluted nucleic acid is then purified using manual or semi-automated methods. RT-qPCR enzyme mixes were formulated that demonstrate substantial inhibitor resistance. In addition, multiplexed probe-based RT-qPCR assays detecting the N1, N2 (nucleocapsid) and E (envelope) gene fragments of SARS-CoV-2 were developed. The RT-qPCR assays also contain primers and probes to detect Pepper Mild Mottle Virus (PMMoV), a fecal indicator RNA virus present in wastewater, and an exogenous control RNA to measure effects of RT-qPCR inhibitors. Using this workflow, we monitored wastewater samples from three wastewater treatment plants (WWTP) in Dane County, Wisconsin. We also successfully sequenced a subset of samples to ensure compatibility with a SARS-CoV-2 amplicon panel and demonstrated the potential for SARS-CoV-2 variant detection. Data obtained here underscore the potential for wastewater surveillance of SARS-CoV-2 and other infectious agents in communities.

RNA Viromics of Southern California Wastewater and Detection of SARS-CoV-2 Single-Nucleotide Variants

Municipal wastewater provides an integrated sample of a diversity of human-associated microbes across a sewershed, including viruses. Wastewater-based epidemiology (WBE) is a promising strategy to detect pathogens and may serve as an early warning system for disease outbreaks. Notably, WBE has garnered substantial interest during the coronavirus disease 2019 (COVID-19) pandemic to track disease burden through analyses of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) RNA. Throughout the COVID-19 outbreak, tracking SARS-CoV-2 in wastewater has been an important tool for understanding the spread of the virus. Unlike traditional sequencing of SARS-CoV-2 isolated from clinical samples, which adds testing burden to the health care system, in this study, metatranscriptomics was used to sequence virus directly from wastewater. Here, we present a study in which we explored RNA viral diversity through sequencing 94 wastewater influent samples across seven wastewater treatment plants (WTPs), collected from August 2020 to January 2021, representing approximately 16 million people in Southern California. Enriched viral libraries identified a wide diversity of RNA viruses that differed between WTPs and over time, with detected viruses including coronaviruses, influenza A, and noroviruses. Furthermore, single-nucleotide variants (SNVs) of SARS-CoV-2 were identified in wastewater, and we measured proportions of overall virus and SNVs across several months. We detected several SNVs that are markers for clinically important SARS-CoV-2 variants along with SNVs of unknown function, prevalence, or epidemiological consequence. Our study shows the potential of WBE to detect viruses in wastewater and to track the diversity and spread of viral variants in urban and suburban locations, which may aid public health efforts to monitor disease outbreaks. IMPORTANCE Wastewater-based epidemiology (WBE) can detect pathogens across sewersheds, which represents the collective waste of human populations. As there is a wide diversity of RNA viruses in wastewater, monitoring the presence of these viruses is useful for public health, industry, and ecological studies. Specific to public health, WBE has proven valuable during the coronavirus disease 2019 (COVID-19) pandemic to track the spread of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) without adding burden to health care systems. In this study, we used metatranscriptomics and reverse transcription-droplet digital PCR (RT-ddPCR) to assay RNA viruses across Southern California wastewater from August 2020 to January 2021, representing approximately 16 million people from Los Angeles, Orange, and San Diego counties. We found that SARS-CoV-2 quantification in wastewater correlates well with county-wide COVID-19 case data, and that we can detect SARS-CoV-2 single-nucleotide variants through sequencing. Likewise, wastewater treatment plants (WTPs) harbored different viromes, and we detected other human pathogens, such as noroviruses and adenoviruses, furthering our understanding of wastewater viral ecology.