Wastewater surveillance for COVID-19 and other pathogens has expanded globally. Rapid development and availability of various assays has facilitated swift adoption of wastewater surveillance in localities with diverse requirements. However, it presents challenges in comparing data due to methodological variations. Using surrogates for recovery control to address quantification biases has limitations as the recovery of surrogates and target pathogens often diverges significantly. Using non-spiked field-obtained wastewater samples as reference samples in an inter-lab study, this article proposes a straightforward, inexpensive, and most representative way of measuring relative quantification biases that occurs in analyzing field wastewater samples. Five labs participated in the study, testing five types of assays, resulting in a total of seven methods of lab-assay combinations. Each method quantified the concentration of SARS-CoV-2 and pepper mild mottle virus (PMMoV) RNAs in two types of reference samples. The results showed significant variations in quantification among methods, but the relative quantification biases were consistent across reference samples. This suggests that relative quantification biases measured with the reference samples are contingent on methods rather than wastewater samples, and that the once-determined method-specific factors can be used to correct for quantification biases in routine wastewater surveillance results. Subsequent data standardization was performed on year-long observational data from seven cities, serving as a preliminary validation of the proposed approach. This process demonstrated the potential for quantitative data comparison through the bias correction factors obtained in this inter-lab study.

Since the start of the COVID-19 pandemic, wastewater surveillance hasemerged as a critical tool for tracking the spread of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) virus and other pathogens in communities throughout the United States. In 2020, the Centers for Disease Control and Prevention (CDC) launched the National Wastewater Surveillance System (NWSS), which partners with state, local, tribal, and territorial health departments to develop and implement wastewater collection and analysis systems and to share data. In 2022, the CDC established the first two NWSS Centers of Excellence to lead its implementation and coordination efforts-one in Colorado (Colorado CoE) and one in Houston (Houston CoE). As the NWSS expands, it is becoming more important to support the training needs of jurisdictions at different stages of developing their wastewater surveillance infrastructure. To evaluate these needs, the Colorado CoE and Houston CoE conducted a needs assessment study of NWSS-funded public health agencies and public utilities departments located in the United States using surveys developed by the Colorado CoE. The results of the surveys showed that although some training needs were universal, it will be most beneficial to develop training modules tailored to the needs of entities that operate wastewater surveillance programs of various sizes, workforce experience levels, and at different stages in the infrastructure development process.

Knowledge of the number of people present in a catchment is fundamental for the assessment of spatio-temporal trends in wastewater-based epidemiology (WBE). Accurately estimating the number of people connected to wastewater catchments is challenging however, because populations are dynamic. Methods used to estimate population size can significantly influence the calculation and interpretation of population-normalised wastewater data (PNWD). This paper systematically reviews the reporting of population data in 339 WBE studies. Studies were evaluated based on their reporting of population size, the source of population data, the population calculation methods, and the uncertainties in population estimates. Most papers reported population size (96 %) and the source of population data (60 %). Fewer studies reported the uncertainties in their population data (50 %) and the methods used to calculate these estimates (28 %). This is relevant because different methods have unique strengths and limitations which can affect the accuracy of PNWD. Only 64 studies (19 %) reported all four components of population data. The reporting of population data has remained consistent in the past decade. Based on the findings, we recommend generalised reporting criteria for population data in WBE. As WBE is further mainstreamed and applied, the clear and comprehensive reporting of population data will only become increasingly important.

UNASSIGNED: The COVID-19 pandemic highlighted the need for pathogen surveillance systems to augment both early warning and outbreak monitoring/control efforts. Community wastewater samples provide a rapid and accurate source of environmental surveillance data to complement direct patient sampling. Due to its global presence and critical missions, the US military is a leader in global pandemic preparedness efforts. Clinical testing for COVID-19 on US Air Force (USAF) bases (AFBs) was effective but costly with respect to direct monetary costs and indirect costs due to lost time. To remain operating at peak capacity, such bases sought a more passive surveillance option and piloted wastewater surveillance (WWS) at 17 AFBs to demonstrate feasibility, safety, utility, and cost-effectiveness from May 2021 to January 2022.
UNASSIGNED: We model the costs of a wastewater program for pathogens of public health concern within the specific context of US military installations using assumptions based on the results of the USAF and Joint Program Executive Office for Chemical, Biological, Radiological and Nuclear Defense pilot program. The objective was to determine the cost of deploying WWS to all AFBs relative to clinical swab testing surveillance regimes.
UNASSIGNED: A WWS cost projection model was built based on subject matter expert input and actual costs incurred during the WWS pilot program at USAF AFBs. Several SARS-CoV-2 circulation scenarios were considered, and the costs of both WWS and clinical swab testing were projected. Analysis was conducted to determine the break-even point and how a reduction in swab testing could unlock funds to enable WWS to occur in parallel.
UNASSIGNED: Our model confirmed that WWS is complementary and highly cost-effective when compared to existing alternative forms of biosurveillance. We found that the cost of WWS was between US $10.5-$18.5 million less expensive annually in direct costs as compared to clinical swab testing surveillance. When the indirect cost of lost work was incorporated, including lost work associated with required clinical swab testing, we estimated that over two-thirds of clinical swab testing could be maintained with no additional costs upon implementation of WWS.
UNASSIGNED: Our results support the adoption of WWS across US military installations as part of a more comprehensive and early warning system that will enable adaptive monitoring during disease outbreaks in a more cost-effective manner than swab testing alone.

The COVID-19 pandemic initiated public interest in wastewater-based epidemiology (WBE). Public and private entities responded to the need to produce timely and accurate data. LuminUltra and Hach partnered to provide a rapid, field-based quantitative polymerase chain reaction (qPCR) test for detecting severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in wastewater. This study evaluates the Hach GeneCount SARS-CoV-2 Wastewater RT-qPCR Assay Kit and LuminUltra GeneCount® Q-16 RT-PCR instrument. The Hach LuminUltra methods were compared to the Promega Wizard® Enviro Total Nucleic Acid kit and Bio-Rad CFX Opus 96 Real-time PCR Detection System. Over a 12-week period, wastewater samples were collected weekly from seven locations in the Roanoke/Salem, VA sewersheds. Concentration and extraction of the viral RNA were followed by qPCR analysis. The target gene for detection was the nucleocapsid gene (N1) of the SARS-CoV-2 virus. Costs, ease of use, time to produce results, sample preparation, and data comparisons were considered. The comparison determined that the Hach LuminUltra method and instrument were more affordable, consumed less time, and required less technical expertise. While the new method was specific, it had low sensitivity. This evaluation suggests the Hach LuminUltra method should be reserved for limited situations requiring onsite field analysis where data accuracy is not essential.

Wastewater (WW)-based epidemiology is an approach for the objective surveillance of the consumption of (illicit) drugs in populations. The aims of this study were to monitor drugs of abuse, cognitive enhancers, and their metabolites as biomarkers in influent WW. Data obtained from different sampling points and mean daily loads were compared with previously published data. The prevalence of analytes was monitored in WW grab samples collected monthly over 22 months at two sampling points and 24 h composite WW samples collected over 2 weeks at a WW treatment plant in the same city. Quantification was performed using a previously validated and published method based on solid-phase extraction followed by liquid chromatography coupled with high-resolution tandem mass spectrometry. Grab samples allowed for frequent detection of ritalinic acid and sporadic detection of drugs of abuse. The daily mean loads calculated for 24 h WW composite samples were in accordance with data published in an international study. Furthermore, loads of amphetamine and methamphetamine increased compared with those observed in a previously published study from 2014. This study showed frequent quantification of ritalinic acid in the grab samples, while drugs of abuse were commonly quantified in the composite WW samples. Daily mean loads were in accordance with trends reported for Germany.

During the COVID-19 pandemic, wastewater-based epidemiology has proved to be an important tool for monitoring the spread of a disease in a population. Indeed, wastewater surveillance was successfully used as a complementary approach to support public health monitoring schemes and decision-making policies. An essential feature for the estimation of a disease transmission using wastewater data is the distribution of viral shedding rate of individuals in their personal human wastes as a function of the days of their infection. Several candidate shapes for this function have been proposed in literature for SARS-CoV-2. The purpose of the present work is to explore the proposed function shapes and examine their significance on analyzing wastewater SARS-CoV-2 shedding rate data. For this purpose, a simple model is employed applying to medical surveillance and wastewater data of the city of Thessaloniki during a period of Omicron variant domination in 2022. The distribution shapes are normalized with respect to the total virus shedding and then their basic features are investigated. Detailed analysis reveals that the main parameter determining the results of the model is the difference between the day of maximum shedding rate and the day of infection reporting. Since the latter is not part of the distribution shape, the major feature of the distribution affecting the estimation of the number of infected people is the day of maximum shedding rate with respect to the initial infection day. On the contrary, the duration of shedding (total number of disease days) as well as the exact shape of the distribution are by far less important. The incorporation of such wastewater surveillance models in conventional epidemiological models - based on recorded disease transmission data- may improve predictions for disease spread during outbreaks.

Using participatory, virologic, and wastewater surveillance systems, we estimated when and to what extent reported data of adult COVID-19 cases underestimated COVID-19 incidence in Germany. We also examined how case underestimation evolved over time. Our findings highlight how community-based surveillance systems can complement official notification systems for respiratory disease dynamics.

Many countries have applied the wastewater surveillance of the COVID-19 pandemic to their national public health monitoring measures. The most used methods for detecting SARS-CoV-2 in wastewater are quantitative reverse transcriptase-polymerase chain reaction (RT-qPCR) and reverse transcriptase-droplet digital polymerase chain reaction (RT-ddPCR). Previous comparison studies have produced conflicting results, thus more research on the subject is required.
This study aims to compare RT-qPCR and RT-ddPCR for detecting SARS-CoV-2 in wastewater. It also aimed to investigate the effect of changes in the analytical pipeline, including the RNA extraction kit, RT-PCR kit, and target gene assay, on the results. Another aim was to find a detection method for low-resource settings.
We compared 2 RT-qPCR kits, TaqMan RT-qPCR and QuantiTect RT-qPCR, and RT-ddPCR based on sensitivity, positivity rates, variability, and correlation of SARS-CoV-2 gene copy numbers in wastewater to the incidence of COVID-19. Furthermore, we compared 2 RNA extraction methods, column- and magnetic-bead-based. In addition, we assessed 2 target gene assays for RT-qPCR, N1 and N2, and 2 target gene assays for ddPCR N1 and E. Reverse transcription strand invasion-based amplification (RT-SIBA) was used to detect SARS-CoV-2 from wastewater qualitatively.
Our results indicated that the most sensitive method to detect SARS-CoV-2 in wastewater was RT-ddPCR. It had the highest positivity rate (26/30), and its limit of detection was the lowest (0.06 gene copies/µL). However, we obtained the best correlation between COVID-19 incidence and SARS-CoV-2 gene copy number in wastewater using TaqMan RT-qPCR (correlation coefficient [CC]=0.697, P<.001). We found a significant difference in sensitivity between the TaqMan RT-qPCR kit and the QuantiTect RT-qPCR kit, the first having a significantly lower limit of detection and a higher positivity rate than the latter. Furthermore, the N1 target gene assay was the most sensitive for both RT-qPCR kits, while no significant difference was found between the gene targets using RT-ddPCR. In addition, the use of different RNA extraction kits affected the result when the TaqMan RT-qPCR kit was used. RT-SIBA was able to detect SARS-CoV-2 RNA in wastewater.
As our study, as well as most of the previous studies, has shown RT-ddPCR to be more sensitive than RT-qPCR, its use in the wastewater surveillance of SARS-CoV-2 should be considered, especially if the amount of SARS-CoV-2 circulating in the population was low. All the analysis steps must be optimized for wastewater surveillance as our study showed that all the analysis steps including the compatibility of the RNA extraction, the RT-PCR kit, and the target gene assay influence the results. In addition, our study showed that RT-SIBA could be used to detect SARS-CoV-2 in wastewater if a qualitative result is sufficient.

Diverse enteric pathogens, transmitted through human and animal feces, can cause gastroenteritis. Enteric viruses, such as human Aichi virus, specifically genotype A (AiV-A), are emerging pathogens that cause illnesses even at low doses and are spreading globally. This research developed a reverse transcription quantitative polymerase chain reaction (RT-qPCR) assay targeting the 3CD junction and a reverse transcription colorimetric loop-mediated isothermal amplification (RT-cLAMP) duplex assay targeting junctions 2BC and 3CD of the AiV-A genome for rapid and sensitive detection of this virus in metropolitan and regional wastewater samples in Queensland, Australia. The performance of these assays was evaluated using control materials and by analyzing wastewater samples. In serially diluted control materials, RT-qPCR provided quantifiable data (mean 1.51 log10 GC/2 μL of nucleic acid) down to a dilution of 1 × 10-5 pg/μL. In comparison, the duplex RT-cLAMP assay detected down to 1 × 10-4 pg/μL, indicating that its sensitivity was one order of magnitude less than that of RT-qPCR. Of the 38 wastewater samples from 38 metropolitan and regional wastewater treatment plants (WWTPs) in Queensland, Australia, 21 (55.3 %) tested positive by RT-qPCR with concentrations ranging from 3.60 to 6.23 log10 GC/L. In contrast, only 15 (39.5 %) of 38 wastewater samples were positive using the duplex RT-cLAMP assay. The methods demonstrated substantial qualitative agreement (κ = 0.730), with a concordance of 86.5 %, demonstrating the reliability of RT-cLAMP for detecting AiV-A in wastewater samples. The duplex RT-cLAMP assay, despite demonstrating reduced detection sensitivity, has proven effective and holds promise as a supplementary approach, especially in settings with limited resources where rapid and affordable testing is crucial.