Stabilization of SARS-CoV-2 RNA in wastewater via rapid RNA extraction

Cryptic transmission of a SARS-CoV-2 variant detected by wastewater surveillance in Panama

The COVID-19 pandemic highlighted the critical role of viral genomic surveillance, prompting numerous countries to enhance their monitoring systems for acute respiratory infections (ARIs), especially influenza-like illnesses (ILIs). Given the significance of asymptomatic cases in severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) transmission, cases often undetected by the ILI surveillance, a more comprehensive approach was essential to track the circulation of SARS-CoV-2 variants in the population. In response, many countries swiftly adopted wastewater surveillance, which allowed the early detection of SARS-CoV-2 variants before they were identified through molecular characterization from confirmed clinical cases. In this report, we detail the implementation of SARS-CoV-2 wastewater genomic surveillance in Panama during the first half of 2024. Wastewater samples were collected monthly in duplicate at two collection points from three districts of Panama city metropolitan area for testing by SARS-CoV-2 RT-qPCR, and positive samples were analyzed by next-generation sequencing to identify sublineages. A total of 36 wastewater samples and 822 samples obtained through the clinical surveillance were analyzed for molecular detection and sequencing. Sublineages detected by wastewater surveillance were compared to those detected by clinical surveillance for the same period of time. Wastewater surveillance allowed the identification of the Omicron sublineage JN.1.16.1 in the capital city and its surroundings, which was not detected by the clinical surveillance in the country, despite its global circulation. This highlights the critical need to sustain both genomic surveillance programs beyond the pandemic in countries like Panama that serve as pivotal exchange hubs.

Bringing Pandemic Science to the Classroom: Building Public Health Capacity at a Rural Kentucky High School

In response to the COVID-19 pandemic, a multidisciplinary team at the University of Kentucky developed an interdisciplinary science, technology, engineering, and mathematics and environmental health unit-the Wastewater Assessment for Coronavirus in Kentucky: Implementing Enhanced Surveillance Technology (WACKIEST) Unit-for high school students in summer 2022. This case study outlines the WACKIEST Unit, which focused on wastewater surveillance and COVID-19, the obstacles faced during development and recruitment, and implementation of the WACKIEST Unit in conjunction with a rural wastewater surveillance initiative. The unit was implemented in spring 2023 at a rural high school in Kentucky, spanning 12 days and engaging 190 students. Lessons emphasized the importance of wastewater testing in public health decision-making, particularly in the context of COVID-19. A mobile laboratory provided students with hands-on experience in conducting preliminary analyses of wastewater, and a field trip to the local wastewater treatment plant allowed them to observe real-world wastewater management practices. At the unit's conclusion, students created a public health report aligned with the Evidence-Informed Decision Making in Public Health model, reinforcing the goal of fostering community health resilience. The initiative's success-measured by the unit's completion and positive feedback from students and teachers-supports the creation of online modules for broader dissemination. This case study demonstrates how adaptable interdisciplinary approaches can integrate real-world scientific issues into secondary education, offering valuable insights for future efforts in public health education.

Sewer transport conditions and their role in the decay of endogenous SARS-CoV-2 and pepper mild mottle virus from source to collection

This study presents a comprehensive analysis of the decay patterns of endogenous SARS-CoV-2 and Pepper mild mottle virus (PMMoV) within wastewaters spiked with stool from infected patients expressing COVID-19 symptoms, and hence explores the decay of endogenous SARS-CoV-2 and PMMoV targets in wastewaters from source to collection of the sample. Stool samples from infected patients were used as endogenous viral material to more accurately mirror real-world decay processes compared to more traditionally used lab-propagated spike-ins. As such, this study includes data on early decay stages of endogenous viral targets in wastewaters that are typically overlooked when performing decay studies on wastewaters harvested from wastewater treatment plants that contain already-degraded endogenous material. The two distinct sewer transport conditions of dynamic suspended sewer transport and bed and near-bed sewer transport were simulated in this study at temperatures of 4 °C, 12 °C and 20 °C to elucidate decay under these two dominant transport conditions within wastewater infrastructure. The dynamic suspended sewer transport was simulated over 35 h, representing typical flow conditions, whereas bed and near-bed transport extended to 60 days to reflect the prolonged settling of solids in sewer systems during reduced flow periods. In dynamic suspended sewer transport, no decay was observed for SARS-CoV-2, PMMoV, or total RNA over the 35-h period, and temperature ranging from 4 °C to 20 °C had no noticeable effect. Conversely, experiments simulating bed and near-bed transport conditions revealed significant decreases in SARS-CoV-2 and total RNA concentrations by day 2, and PMMoV concentrations by day 3. Only PMMoV exhibited a clear trend of increasing decay constant with higher temperatures, suggesting that while temperature influences decay dynamics, its impact may be less significant than previously assumed, particularly for endogenous RNA that is bound to dissolved organic matter in wastewater. First order decay models were inadequate for accurately fitting decay curves of SARS-CoV-2, PMMoV, and total RNA in bed and near-bed transport conditions. F-tests confirmed the superior fit of the two-phase decay model compared to first order decay models across temperatures of 4 °C-20 °C. Finally, and most importantly, total RNA normalization emerged as an appropriate approach for correcting the time decay of SARS-CoV-2 exposed to bed and near-bed transport conditions. These findings highlight the importance of considering decay from the point of entry in the sewers, sewer transport conditions, and normalization strategies when assessing and modelling the impact of viral decay rates in wastewater systems. This study also emphasizes the need for ongoing research into the diverse and multifaceted factors that influence these decay rates, which is crucial for accurate public health monitoring and response strategies.

Assessment of environmental factors influencing SARS-CoV-2 in Vietnam's surface water across two years of clinical data

Wastewater-based epidemiology (WBE) is an effective, non-invasive method for monitoring the spread of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) by tracking viral prevalence in water. This study aimed to investigate the presence of SARS-CoV-2 in surface water in Vietnam over two years. One-step quantitative reverse transcription polymerase chain reaction (qRT-PCR) assays were employed to quantify SARS-CoV-2 and its variant-specific mutation sites (G339D/E484A) and pepper mild mottle virus (PMMoV) from a total of 315 samples (105 samples per site) to compare with reported Coronavirus disease 2019 (COVID-19) cases and environmental factors. SARS-CoV-2 was detected in 38 % (40/105), 43 % (45/105), and 39 % (41/105) of water samples from Sites A, B, and C, respectively, with concentrations of 3.0-5.6 log10 copies/L. PMMoV concentrations were 5.1-8.9 log10 copies/L. SARS-CoV-2 levels were higher in winter compared with summer. There was a strong positive association between the mutant type and SARS-CoV-2 concentrations (Spearman's rho = 0.77, p < 0.01). The mean concentrations of mutant and nonmutant types were 2.3 and 1.8 log10 copies/L, respectively. Peaks in SARS-CoV-2 concentrations preceded reported COVID-19 cases by 2-4 weeks, with the highest association observed at a 4-week delay (Pearson's correlation coefficient: 0.46-0.53). Environmental factors, including temperature, pH, and electrical conductivity, correlated negatively with SARS-CoV-2 (Spearman's rho = -0.21, -0.28, and -0.21, respectively, p < 0.05), whereas average rainfall, humidity, and dissolved oxygen correlated positively (Spearman's rho = 0.20, 0.27, and 0.51, respectively, p < 0.05). These correlations highlight the significance of environmental variables in understanding viral prevalence in water. Our findings confirmed the utility of WBE as an early warning system for long-term monitoring. Future research should incorporate environmental factors to improve prediction accuracy for clinical cases and other waterborne diseases.

Extraction of redox extracellular vesicles using exclusion-based sample preparation

Studying specific subpopulations of cancer-derived extracellular vesicles (EVs) could help reveal their role in cancer progression. In cancer, an increase in reactive oxygen species (ROS) happens which results in lipid peroxidation with a major product of 4-hydroxynonenal (HNE). Adduction by HNE causes alteration to the structure of proteins, leading to loss of function. Blebbing of EVs carrying these HNE-adducted proteins as a cargo or carrying HNE-adducted on EV membrane are methods for clearing these molecules by the cells. We have referred to these EVs as Redox EVs. Here, we utilize a surface tension-mediated extraction process, termed exclusion-based sample preparation (ESP), for the rapid and efficient isolation of intact Redox EVs, from a mixed population of EVs derived from human glioblastoma cell line LN18. After optimizing different parameters, two populations of EVs were analyzed, those isolated from the sample (Redox EVs) and those remaining in the original sample (Remaining EVs). Electron microscopic imaging was used to confirm the presence of HNE adducts on the outer leaflet of Redox EVs. Moreover, the population of HNE-adducted Redox EVs shows significantly different characteristics to those of Remaining EVs including smaller size EVs and a more negative zeta potential EVs. We further treated glioblastoma cells (LN18), radiation-resistant glioblastoma cells (RR-LN18), and normal human astrocytes (NHA) with both Remaining and Redox EV populations. Our results indicate that Redox EVs promote the growth of glioblastoma cells, likely through the production of H2O2, and cause injury to normal astrocytes. In contrast, Remaining EVs have minimal impact on the viability of both glioblastoma cells and NHA cells. Thus, isolating a subpopulation of EVs employing ESP-based immunoaffinity could pave the way for a deeper mechanistic understanding of how subtypes of EVs, such as those containing HNE-adducted proteins, induce biological changes in the cells that take up these EVs.

Wastewater surveillance for viral pathogens: A tool for public health

A focus on water quality has intensified globally, considering its critical role in sustaining life and ecosystems. Wastewater, reflecting societal development, profoundly impacts public health. Wastewater-based epidemiology (WBE) has emerged as a surveillance tool for detecting outbreaks early, monitoring infectious disease trends, and providing real-time insights, particularly in vulnerable communities. WBE aids in tracking pathogens, including viruses, in sewage, offering a comprehensive understanding of community health and lifestyle habits. With the rise in global COVID-19 cases, WBE has gained prominence, aiding in monitoring SARS-CoV-2 levels worldwide. Despite advancements in water treatment, poorly treated wastewater discharge remains a threat, amplifying the spread of water-, sanitation-, and hygiene (WaSH)-related diseases. WBE, serving as complementary surveillance, is pivotal for monitoring community-level viral infections. However, there is untapped potential for WBE to expand its role in public health surveillance. This review emphasizes the importance of WBE in understanding the link between viral surveillance in wastewater and public health, highlighting the need for its further integration into public health management.

Fate-and-transport modeling of SARS-CoV-2 for rural wastewater-based epidemiology application benefit

Wastewater-based epidemiology (WBE) for the detection of agents of concern such as severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) has been prevalent in literature since 2020. The majority of reported research focuses on large urban centers with few references to rural communities. In this research the EPA-Storm Water Management Model (EPA-SWMM) software was used to describe a small sewershed and identify the effects of temperature, temperature-affected decay rate, flow rate, flush time, fecal shedding rate, and historical infection rates during the spread of the Omicron variant of the SARS-CoV-2 virus within the sewershed. Due to the sewershed's relative isolation from the rest of the city, its wastewater quality behavior is similar to a rural sewershed. The model was used to assess city wastewater sampling campaigns to best appropriate field and or lab equipment when sampling wastewater. An important aspect of the assessment was the comparison of SARS-CoV-2 quantification methods with specifically between a traditional microbiological lab (practical quantitation limit, PQL, 1 GC/mL) versus what can be known from a field method (PQL 10 GC/mL). Understanding these monitoring choices will help rural communities make decisions on how to best implement the collection and testing for WBE agents of concern. An important outcome of this work is the knowledge that it is possible to simulate a WBE agent of concern with reasonable precision, if uncertainties are incorporated into model sensitivity. These ideas could form the basis for future mixed monitoring-modeling studies that will enhance its application and therefore adoption of WBE techniques in communities of many sizes and financial means.

Simple SARS-CoV-2 concentration methods for wastewater surveillance in low resource settings

Wastewater-based epidemiology (WBE) measures pathogens in wastewater to monitor infectious disease prevalence in communities. Due to the high dilution of pathogens in sewage, a concentration method is often required to achieve reliable biomarker signals. However, most of the current concentration methods rely on expensive equipment and labor-intensive processes, which limits the application of WBE in low-resource settings. Here, we compared the performance of four inexpensive and simple concentration methods to detect SARS-CoV-2 in wastewater samples: Solid Fraction, Porcine Gastric Mucin-conjugated Magnetic Beads, Calcium Flocculation-Citrate Dissolution (CFCD), and Nanotrap® Magnetic Beads (NMBs). The NMBs and CFCD methods yielded the highest concentration performance for SARS-CoV-2 (∼16-fold concentration and ∼ 41 % recovery) and require <45 min processing time. CFCD has a relatively low consumable cost (<$2 per four sample replicates). All methods can be performed with basic laboratory equipment and minimal electricity usage which enables further application of WBE in remote areas and low resource settings.

20-Month monitoring of SARS-CoV-2 in wastewater of Curitiba, in Southern Brazil

The COVID-19 pandemic resulted in the collapse of healthcare systems and led to the development and application of several approaches of wastewater-based epidemiology to monitor infected populations. The main objective of this study was to carry out a SARS-CoV-2 wastewater based surveillance in Curitiba, Southern Brazil Sewage samples were collected weekly for 20 months at the entrance of five treatment plants representing the entire city and quantified by qPCR using the N1 marker. The viral loads were correlated with epidemiological data. The correlation by sampling points showed that the relationship between the viral loads and the number of reported cases was best described by a cross-correlation function, indicating a lag between 7 and 14 days amidst the variables, whereas the data for the entire city presented a higher correlation (0.84) with the number of positive tests at lag 0 (sampling day). The results also suggest that the Omicron VOC resulted in higher titers than the Delta VOC. Overall, our results showed that the approach used was robust as an early warning system, even with the use of different epidemiological indicators or changes in the virus variants in circulation. Therefore, it can contribute to public decision-makers and health interventions, especially in vulnerable and low-income regions with limited clinical testing capacity. Looking toward the future, this approach will contribute to a new look at environmental sanitation and should even induce an increase in sewage coverage rates in emerging countries.