Wastewater-Based Epidemiology for Managing the COVID-19 Pandemic

Real-Time On-Site Monitoring of Viruses in Wastewater Using Nanotrap® Particles and RICCA Technologies

Wastewater-based epidemiology (WBE) is an effective and efficient tool for the early detection of infectious disease outbreaks in a community. However, currently available methods are laborious, costly, and time-consuming due to the low concentration of viruses and the presence of matrix chemicals in wastewater that may interfere with molecular analyses. In the present study, we designed a highly sensitive "Quick Poop (wastewater with fecal waste) Sensor" (termed, QPsor) using a joint approach of Nanotrap microbiome particles and RICCA (RNA Isothermal Co-Assisted and Coupled Amplification). Using QPsor, the WBE study showed a strong correlation with standard PEG concentrations and the qPCR technique. Using a closed format for a paper-based lateral flow assay, we were able to demonstrate the potential of our assay as a real-time, point-of-care test by detecting the heat-inactivated SARS-CoV-2 virus in wastewater at concentrations of 100 copies/mL and within one hour. As a proof-of-concept demonstration, we analyzed the presence of viral RNA of the SARS-CoV-2 virus and PMMoV in raw wastewater samples from wastewater treatment plants on-site and within 60 min. The results show that the QPsor method can be an effective tool for disease outbreak detection by combining an AI-enabled case detection model with real-time on-site viral RNA extraction and amplification, especially in the absence of intensive clinical laboratory facilities. The lab-free, lab-quality test capabilities of QPsor for viral prevalence and transmission in the community can contribute to the efficient management of pandemic situations.

Early warning of statewide COVID-19 Omicron wave by sentineled urbanized sewer network monitoring using digital PCR in a province capital city, of Gujarat, India

Wastewater-based epidemiology (WBE) has been implemented globally. However, there remains confusion about the number and frequency of samples to be collected, as well as which types of treatment systems can provide reliable specific details about the virus prevalence in specific areas or communities, enabling prompt management and intervention measures. More research is necessary to fully comprehend the possibility of deploying sentinel locations in sewer networks in larger geographic areas. The present study introduces the first report on wastewater-based surveillance in Gandhinagar City using digital PCR (d-PCR) as a SARS-Cov-2 quantification tool, which describes the viral load from five pumping stations in Gandhinagar from October 2021 to March 2022. Raw wastewater samples (n = 119) were received and analyzed weekly to detect SARS-CoV-2 RNA, 109 of which were positive for N1 or N2 genes. The monthly variation analysis in viral genome copies depicted the highest concentrations in January 2022 and February 2022 (p < 0.05; Wilcoxon signed rank test) coincided with the Omicron wave, which contributed mainly from Vavol and Jaspur pumping stations. Cross-correlation analysis indicated that WBE from five stations in Gandhinagar, i.e., capital city sewer networks, provided two-week lead times to the citywide and statewide active cases (time-series cross-correlation function [CCF]; 0.666 and 0.648, respectively), mainly from individual contributions of the urbanized Kudasan and Vavol stations (CCF; 0.729 and 0.647, respectively). These findings suggest that sewer pumping stations in urbanized neighborhoods can be used as sentinel sites for statewide clinical surveillance and that WBE surveillance using digital PCR can be an efficient monitoring and management tool.

A phenomenological neural network powered by the National Wastewater Surveillance System for estimation of silent COVID-19 infections

Although wastewater-based epidemiology (WBE) has emerged as an inexpensive and non-intrusive method in contrast to clinical testing to track public health at community levels, there is a lack of structured interpretative criteria to translate the SARS-CoV-2 concentrations in wastewater to COVID-19 infection cases. The difficulties lie in the uncertainties of the amount of virus shed by an infected individual to wastewater as documented in clinical studies. This situation is even worse considering the existence of a population of silent infections and many other confounding factors. In this research, a quantitative framework of a phenomenological neural network (PNN) was developed to compute silent infections. The PNN was trained using the WBE data from the National Wastewater Surveillance System (NWSS) - a program launched by the CDC of the United States in 2020. It is found that the PNN excelled with superior interpretability and reduced overfitting. A big-data perspective on virus shedding by an infected population revealed more deterministic virus-shedding dynamics compared to the clinical studies perspective on virus shedding by an infected individual. With such characteristics employed as the theoretical basis for the estimation of the silent infections, a ratio of silent to reported infections was found to be 5.7 as the national median during the studied period. The study also noted the influence of temperature, sewershed population, and per-capita flow rates on the computation of silent infections. It is expected that the proposed framework in this work would facilitate public health actions guided by the SARS-CoV-2 concentrations in wastewater. In case of a new wave emergence or a new virus disease outbreak like COVID-19, the PNN powered by the NWSS would outline consolidated and systematic information that would enable rapid deployment of public health actions.

Diurnal changes in pathogenic and indicator virus concentrations in wastewater

Wastewater-based epidemiology (WBE) has been commonly used for monitoring SARS-CoV-2 outbreaks. As sampling times and methods (i.e. grab vs composite) may vary, diurnal changes of viral concentrations in sewage should be better understood. In this study, we collected untreated wastewater samples hourly for 4 days at two wastewater treatment plants in Wales to establish diurnal patterns in virus concentrations and the physico-chemical properties of the water. Simultaneously, we also trialled three absorbent materials as passive samples as a simple and cost-efficient alternative for the collection of composite samples. Ninety-six percent of all liquid samples (n = 74) and 88% of the passive samplers (n = 59) were positive for SARS-CoV-2, whereas 87% and 97% of the liquid and passive samples were positive for the faecal indicator virus crAssphage, respectively. We found no significant daily variations in the concentration of the target viruses, ammonium and orthophosphate, and the pH and electrical conductivity levels were also stable. Weak positive correlations were found between some physico-chemical properties and viral concentrations. More variation was observed in samples taken from the influent stream as opposed to those taken from the influent tank. Of the absorbent materials trialled as passive samples, we found that tampons provided higher viral recoveries than electronegative filter paper and cotton gauze swabs. For all materials tested, viral recovery was dependent on the virus type. Our results indicate that grab samples may provide representative alternatives to 24-h composite samples if taken from the influent tank, hence reducing the costs of sampling for WBE programmes. Tampons are also viable alternatives for cost-efficient sampling; however, viral recovery should be optimised prior to use.

Candidate biomarkers of antibiotic resistance for the monitoring of wastewater and the downstream environment

Urban wastewater treatment plants (UWTPs) are essential for reducing the pollutants load and protecting water bodies. However, wastewater catchment areas and UWTPs emit continuously antibiotic resistant bacteria (ARB) and antibiotic resistance genes (ARGs), with recognized impacts on the downstream environments. Recently, the European Commission recommended to monitor antibiotic resistance in UWTPs serving more than 100 000 population equivalents. Antibiotic resistance monitoring in environmental samples can be challenging. The expected complexity of these systems can jeopardize the interpretation capacity regarding, for instance, wastewater treatment efficiency, impacts of environmental contamination, or risks due to human exposure. Simplified monitoring frameworks will be essential for the successful implementation of analytical procedures, data analysis, and data sharing. This study aimed to test a set of biomarkers representative of ARG contamination, selected based on their frequent human association and, simultaneously, rare presence in pristine environments. In addition to the 16S rRNA gene, ten potential biomarkers (intI1, sul1, ermB, ermF, aph(3'')-Ib, qacEΔ1, uidA, mefC, tetX, and crAssphage) were monitored in DNA extracts (n = 116) from raw wastewater, activated sludge, treated wastewater, and surface water (upstream and downstream of UWTPs) samples collected in the Czech Republic, Denmark, Israel, the Netherlands, and Portugal. Each biomarker was sensitive enough to measure decreases (on average by up to 2.5 log-units gene copy/mL) from raw wastewater to surface water, with variations in the same order of magnitude as for the 16S rRNA gene. The use of the 10 biomarkers allowed the typing of water samples whose origin or quality could be predicted in a blind test. The results show that, based on appropriate biomarkers, qPCR can be used for a cost-effective and technically accessible approach to monitoring wastewater and the downstream environment.

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

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

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.

On the emergence of a health-pollutant-climate nexus in the wake of a global pandemic

COVID-19 has wreaked havoc throughout the planet within a short time frame, inducing substantial morbidity and mortality in the global population. The primary procedures commonly used to manage the pandemic can produce various environmental pollutants, primarily contaminants of emerging concern such as plastics, chemical disinfectants, and pharmaceutical waste. There is a huge influx of various environmental pollutants due to the pandemic effect. We, therefore, introduce the term "envirodemics" depicting the exacerbated surge in the amount of pandemic-induced pollutants. The general toxicity pattern of common chemical ingredients in widely used disinfectants shows negative impacts on the environment. We have identified some of the significant imprints of the pandemic on localizing the Sustainable Development Goals-environment interaction and their implications on achieving the goals in terms of environmental benefits. Climate change impacts are now widespread and have a profound effect on pollutant fluxes and distribution. The climate change signatures will impact the pandemic-induced enhanced fluxes of pollutants in the global waters, such as their transport and transformation. In this study, possible interactions and emerging pathways involving an emerging climate-health-pollutant nexus are discussed. The nexus is further elaborated by considering plastic as an example of an emerging pollutant that is produced in huge quantities as a by-product of COVID management and disaster risk reduction. Additionally, regulatory implications and future perspectives concerning the unleashed nexus are also discussed. We hope that this communication shall call for incisive investigations in the less explored realm concerning the health-pollutant-climate nexus.

Persistence of Tilapia tilapinevirus in fish rearing and environmental water and its ability to infect cell line

Tilapia tilapinevirus, or Tilapia Lake Virus (TiLV), is a RNA virus associated with mass morbidity and mortality in tilapia, leading to severe economic losses for global tilapia aquaculture. In this study, we investigated the persistence of TiLV in water by spiking sterile distilled water (SDW), freshwater collected from rearing fish tanks (FW) and natural pond water (PW) at 27°C as a representative of environmental water conditions with 0.6 ml of stock virus (3.18 × 10⁷ viral copies/ml of water). The water samples were filtered through an electronegative charge membrane and quantified using reverse transcriptase quantitative PCR at 0, 3, 5, 7, 10 and 14 days post-inoculation. The results revealed that TiLV RNA in SDW was reduced by 1.34 log₁₀ in 14 days. A similar approximately 4 log₁₀ removal of the virus in FW and PW was observed at 3 and 7 days, respectively. Moreover, the infectivity of TiLV was further studied; the virus lost its infectivity in E-11 cells after 1 day in SDW, FW and PW water samples, even though the virus was spiked 10 more times than in the viral persistence study. Taken together, the results could be applied to improving biosecurity practices in tilapia farms by disinfecting or resting reservoir water for at least three to five days prior to stocking tilapia, to limit the spread of TiLV.

Modeling the relationship between SARS-CoV-2 RNA in wastewater or sludge and COVID-19 cases in three New England regions

BACKGROUND

We aimed to compare statistical techniques estimating the association between SARS-CoV-2 RNA in untreated wastewater and sludge and reported coronavirus disease 2019 (COVID-19) cases.

METHODS

SARS-CoV-2 RNA concentrations (copies/mL) were measured from 24-h composite samples of wastewater in Massachusetts (MA) (daily; 8/19/2020-1/19/2021) and Maine (ME) (weekly; 9/1/2020-3/2/2021) and sludge samples in Connecticut (CT) (daily; 3/1/2020-6/1/2020). We fit linear, generalized additive with a cubic regression spline (GAM), Poisson, and negative binomial models to estimate the association between SARS-CoV-2 RNA concentration and reported COVID-19 cases.

RESULTS

The models that fit the data best were linear [adjusted R²=0.85 (MA), 0.16 (CT), 0.63 (ME); root-mean-square error (RMSE)=0.41 (MA), 1.14 (CT), 0.99 (ME)), GAM (adjusted R²=0.86 (MA), 0.16 (CT) 0.65 (ME); RMSE=0.39 (MA), 1.14 (CT), 0.97 (ME)], and Poisson [pseudo R²=0.84 (MA), 0.21 (CT), 0.52 (ME); RMSE=0.39 (MA), 0.67 (CT), 0.79 (ME)].

CONCLUSIONS

Linear, GAM, and Poisson models outperformed negative binomial models when relating SARS-CoV-2 RNA in wastewater or sludge to reported COVID-19 cases.

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.

Contribution of SARS-CoV-2 RNA shedding routes to RNA loads in wastewater

A portion of those infected with SARS-CoV-2 shed the virus and its genetic material in respiratory fluids, saliva, urine, and stool, thus giving the potential to monitor for infections via wastewater. Wastewater surveillance efforts to date have largely assumed that stool shedding has been the primary source of SARS-CoV-2 RNA signal; however, there are increasing questions about the possible contribution of other shedding routes, with implications for wastewater surveillance design and feasibility. In this study we used clinical SARS-CoV-2 RNA shedding data and a Monte Carlo framework to assess the relative contribution of various shedding routes on SARS-CoV-2 RNA loads in wastewater. Stool shedding dominated total SARS-CoV-2 RNA load for community-level surveillance, with mean contributions more than two orders of magnitude greater than other shedding routes. However, RNA loads were more nuanced when considering building-level monitoring efforts designed to identify a single infected individual, where any shedding route could plausibly contribute a detectable signal. The greatest source of model variability was viral load in excreta, suggesting that future modeling efforts may be improved by incorporating specific modeling scenarios with precise SARS-CoV-2 shedding data, and beyond that wastewater surveillance must continue to account for large variability during data analysis and reporting. Importantly, the findings imply that wastewater surveillance at finer spatial scales is not entirely dependent on shedding via feces for sensitive detection of infections thus enlarging the potential use cases of wastewater as a non-intrusive surveillance methodology.

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.

Absence of virological and epidemiological evidence that SARS-CoV-2 poses COVID-19 risks from environmental fecal waste, wastewater and water exposures

This review considers evidence for infectious severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) presence and COVID-19 infection and illness resulting from exposure to environmental fecal wastes and waters. There is no documented evidence that (1) infectious, replication-capable SARS-CoV-2 is present in environmental fecal wastes, wastewater or water, and (2) well-documented epidemiological evidence of COVID-19 infection, illness or death has never been reported for these exposure media. COVID-19 is transmitted mainly by direct personal contact and respiratory secretions as airborne droplets and aerosols, and less so by respiratory-secreted fomites via contact (touch) exposures. While SARS-CoV-2 often infects the gastrointestinal tract of infected people, its presence as infectious, replication-capable virus in environmental fecal wastes and waters has never been documented. There is only rare and unquantified evidence of infectious, replication-capable SARS-CoV-2 in recently shed feces of COVID-19 hospital patients. The human infectivity dose-response relationship of SARS-CoV-2 is unknown, thereby making it impossible to estimate evidence-based quantitative health effects assessments by quantitative microbial risk assessment methods requiring both known exposure assessment and health effects assessment data. The World Health Organization, Water Environment Federation, US Centers for Disease Control and Prevention and others do not consider environmental fecal wastes and waters as sources of exposure to infectious SARS-CoV-2 causing COVID-19 infection and illness.

COVID-19 Pandemic: Public Health Risk Assessment and Risk Mitigation Strategies

A newly emerged respiratory viral disease called severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) is also known as pandemic coronavirus disease (COVID-19). This pandemic has resulted an unprecedented global health crisis and devastating impact on several sectors of human lives and economies. Fortunately, the average case fatality ratio for SARS-CoV-2 is below 2%, much lower than that estimated for MERS (34%) and SARS (11%). However, COVID-19 has a much higher transmissibility rate, as evident from the constant increase in the count of infections worldwide. This article explores the reasons behind how COVID-19 was able to cause a global pandemic crisis. The current outbreak scenario and causes of rapid global spread are examined using recent developments in the literature, epidemiological features relevant to public health awareness, and critical perspective of risk assessment and mitigation strategies. Effective pandemic risk mitigation measures have been established and amended against COVID-19 diseases, but there is still much scope for upgrading execution and coordination among authorities in terms of organizational leadership's commitment and diverse range of safety measures, including administrative control measures, engineering control measures, and personal protective equipment (PPE). The significance of containment interventions against the COVID-19 pandemic is now well established; however, there is a need for its effective execution across the globe, and for the improvement of the performance of risk mitigation practices and suppression of future pandemic crises.

Wastewater Based Epidemiology Perspective as a Faster Protocol for Detecting Coronavirus RNA in Human Populations: A Review with Specific Reference to SARS-CoV-2 Virus

Wastewater-based epidemiology (WBE) has a long history of identifying a variety of viruses from poliovirus to coronaviruses, including novel Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2). The presence and detection of SARS-CoV-2 in human feces and its passage into the water bodies are significant public health challenges. Hence, the hot issue of WBE of SARS-CoV-2 in the coronavirus respiratory disease (COVID-19) pandemic is a matter of utmost importance (e.g., SARS-CoV-1). The present review discusses the background, state of the art, actual status, and prospects of WBE, as well as the detection and quantification protocols of SARS-CoV-2 in wastewater. The SARS-CoV-2 detection studies have been performed in different water matrixes such as influent and effluent of wastewater treatment plants, suburban pumping stations, hospital wastewater, and sewer networks around the globe except for Antarctica. The findings revealed that all WBE studies were in accordance with clinical and epidemiological data, which correlates the presence of SARS-CoV-2 ribonucleic acid (RNA) with the number of new daily positive cases officially reported. This last was confirmed via Reverse Transcriptase-quantitative Polymerase Chain Reaction (RT-qPCR) testing which unfortunately is not suitable for real-time surveillance. In addition, WBE concept may act as a faster protocol to alert the public health authorities to take administrative orders (possible re-emerging infections) due to the impracticality of testing all citizens in a short time with limited diagnostic facilities. A comprehensive and integrated review covering all steps starting from sampling to molecular detection of SARS-CoV-2 in wastewater has been made to guide for the development well-defined and reliable protocols.

Inferring Numbers of Wild Poliovirus Excretors Using Quantitative Environmental Surveillance

Response to and monitoring of viral outbreaks can be efficiently focused when rapid, quantitative, kinetic information provides the location and the number of infected individuals. Environmental surveillance traditionally provides information on location of populations with contagious, infected individuals since infectious poliovirus is excreted whether infections are asymptomatic or symptomatic. Here, we describe development of rapid (1 week turnaround time, TAT), quantitative RT-PCR of poliovirus RNA extracted directly from concentrated environmental surveillance samples to infer the number of infected individuals excreting poliovirus. The quantitation method was validated using data from vaccination with bivalent oral polio vaccine (bOPV). The method was then applied to infer the weekly number of excreters in a large, sustained, asymptomatic outbreak of wild type 1 poliovirus in Israel (2013) in a population where >90% of the individuals received three doses of inactivated polio vaccine (IPV). Evidence-based intervention strategies were based on the short TAT for direct quantitative detection. Furthermore, a TAT shorter than the duration of poliovirus excretion allowed resampling of infected individuals. Finally, the method documented absence of infections after successful intervention of the asymptomatic outbreak. The methodologies described here can be applied to outbreaks of other excreted viruses such as severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), where there are (1) significant numbers of asymptomatic infections; (2) long incubation times during which infectious virus is excreted; and (3) limited resources, facilities, and manpower that restrict the number of individuals who can be tested and re-tested.