Wastewater surveillance in smaller college communities may aid future public health initiatives

Monitoring Influenza A (H1N1, H3N2), RSV, and SARS-CoV-2 Using Wastewater-Based Epidemiology: A 2-Year Longitudinal Study in an Indian Megacity Covering Omicron and Post-Omicron Phases

The bourgeoning field of wastewater-based epidemiology (WBE) for the surveillance of several respiratory viruses which includes Influenza A, H1N1pdm09, H3N2, respiratory syncytial viruses (RSV), and severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is of interest for public health concerns. However, there are few long-term monitoring studies globally. In this study, respiratory viruses were detected and quantified from 11 sewer sheds by utilizing reverse transcription-quantitative polymerase chain reaction analysis in Pune city, India, from Jan 2022 to Dec 2023. The RNA fragments of respiratory viruses were detected in sewage samples before clinical cases were reported, underscoring the potential of WBE for early detection and monitoring within the population. The Spearman correlation of wastewater viral copies was positively and significantly correlated with the clinically positive case of H1N1pdm09 (ρ = 0.55, p = 1.4 × 10-9), H3N2 (ρ = 0.25, p = 9.9 × 10-3), and SARS-CoV-2 (ρ = 0.43, p = 4.1 × 10-6). The impact of public health interventions on the circulation of infectious respiratory diseases showed a significant difference in the viral load during the period when many preventing measures were carried out against the COVID-19 pandemic (restriction phase), compared to the period when no such preventive measures are followed (no-restriction phase) for Influenza A, H1N1pdm09, H3N2, and RSV with p-value < 0.05, which indicates the influence of health policy implementation in controlling disease spread. The present study provides an effective approach to detecting multiple respiratory viruses from wastewater and provides insights into the epidemiology of respiratory illnesses. The WBE aids in providing information on the spread of pathogens (viruses) in the community, offering a proactive strategy for public health management, allowing for timely interventions and implementing targeted measures to mitigate the spread of these viruses under one health approach.

Small-scale wastewater-based epidemiology (WBE) for infectious diseases and antibiotic resistance: A scoping review

Wastewater analysis can serve as a source of public health information. In recent years, wastewater-based epidemiology (WBE) has emerged and proven useful for the detection of infectious diseases. However, insights from the wastewater treatment plant do not allow for the small-scale differentiation within the sewer system that is needed to analyze the target population under study in more detail. Small-scale WBE offers several advantages, but there has been no systematic overview of its application. The aim of this scoping review is to provide a comprehensive overview of the current state of knowledge on small-scale WBE for infectious diseases, including methodological considerations for its application. A systematic database search was conducted, considering only peer-reviewed articles. Data analyses included quantitative summary and qualitative narrative synthesis. Of 2130 articles, we included 278, most of which were published since 2020. The studies analyzed wastewater at the building level (n = 203), especially healthcare (n = 110) and educational facilities (n = 80), and at the neighborhood scale (n = 86). The main analytical parameters were viruses (n = 178), notably SARS-CoV-2 (n = 161), and antibiotic resistance (ABR) biomarkers (n = 99), often analyzed by polymerase chain reaction (PCR), with DNA sequencing techniques being less common. In terms of sampling techniques, active sampling dominated. The frequent lack of detailed information on the specification of selection criteria and the characterization of the small-scale sampling sites was identified as a concern. In conclusion, based on the large number of studies, we identified several methodological considerations and overarching strategic aspects for small-scale WBE. An enabling environment for small-scale WBE requires inter- and transdisciplinary knowledge sharing across countries. Promoting the adoption of small-scale WBE will benefit from a common international conceptualization of the approach, including standardized and internationally accepted terminology. In particular, the development of good WBE practices for different aspects of small-scale WBE is warranted. This includes the establishment of guidelines for a comprehensive characterization of the local sewer system and its sub-sewersheds, and transparent reporting to ensure comparability of small-scale WBE results.

Wastewater based epidemiology as a surveillance tool during the current COVID-19 pandemic on a college campus (East Carolina University) and its accuracy in predicting SARS-CoV-2 outbreaks in dormitories

The COVID-19 outbreak led governmental officials to close many businesses and schools, including colleges and universities. Thus, the ability to resume normal campus operation required adoption of safety measures to monitor and respond to COVID-19. The objective of this study was to determine the efficacy of wastewater-based epidemiology as a surveillance method in monitoring COVID-19 on a college campus. The use of wastewater monitoring as part of a surveillance program to control COVID-19 outbreaks at East Carolina University was evaluated. During the Spring and Fall 2021 semesters, wastewater samples (N = 830) were collected every Monday, Wednesday, and Friday from the sewer pipes exiting the dormitories on campus. Samples were analyzed for SARS-CoV-2 and viral quantification was determined using qRT-PCR. During the Spring 2021 semester, there was a significant difference in SARS-CoV-2 virus copies in wastewater when comparing dorms with the highest number student cases of COVID-19 and those with the lowest number of student cases, (p = 0.002). Additionally, during the Fall 2021 semester it was observed that when weekly virus concentrations exceeded 20 copies per ml, there were new confirmed COVID-19 cases 85% of the time during the following week. Increases in wastewater viral concentration spurred COVID-19 swab testing for students residing in dormitories, aiding university officials in effectively applying COVID testing policies. This study showed wastewater-based epidemiology can be a cost-effective surveillance tool to guide other surveilling methods (e.g., contact tracing, nasal/salvia testing, etc.) to identify and isolate afflicted individuals to reduce the spread of pathogens and potential outbreaks within a community.

Wastewater based surveillance can be used to reduce clinical testing intensity on a university campus

Clinical testing has been a vital part of the response to and suppression of the COVID-19 pandemic; however, testing imposes significant burdens on a population. College students had to contend with clinical testing while simultaneously dealing with health risks and the academic pressures brought on by quarantines, changes to virtual platforms, and other disruptions to daily life. The objective of this study was to analyze whether wastewater surveillance can be used to decrease the intensity of clinical testing while maintaining reliable measurements of diseases incidence on campus. Twelve months of human health and wastewater surveillance data for eight residential buildings on a university campus were analyzed to establish how SARS-CoV-2 levels in the wastewater can be used to minimize clinical testing burden on students. Wastewater SARS-CoV-2 levels were used to create multiple scenarios, each with differing levels of testing intensity, which were compared to the actual testing volumes implemented by the university. We found that scenarios in which testing intensity fluctuations matched rise and falls in SARS-CoV-2 wastewater levels had stronger correlations between SARS-CoV-2 levels and recorded clinical positives. In addition to stronger correlations, most scenarios resulted in overall fewer weekly clinical tests performed. We suggest the use of wastewater surveillance to guide COVID-19 testing as it can significantly increase the efficacy of COVID-19 surveillance while reducing the burden placed on college students during a pandemic. Future efforts should be made to integrate wastewater surveillance into clinical testing strategies implemented on college campuses.

Evaluating various composite sampling modes for detecting pathogenic SARS-CoV-2 virus in raw sewage

Inadequate sampling approaches to wastewater analyses can introduce biases, leading to inaccurate results such as false negatives and significant over- or underestimation of average daily viral concentrations, due to the sporadic nature of viral input. To address this challenge, we conducted a field trial within the University of Tennessee residence halls, employing different composite sampling modes that encompassed different time intervals (1 h, 2 h, 4 h, 6 h, and 24 h) across various time windows (morning, afternoon, evening, and late-night). Our primary objective was to identify the optimal approach for generating representative composite samples of SARS-CoV-2 from raw wastewater. Utilizing reverse transcription-quantitative polymerase chain reaction, we quantified the levels of SARS-CoV-2 RNA and pepper mild mottle virus (PMMoV) RNA in raw sewage. Our findings consistently demonstrated that PMMoV RNA, an indicator virus of human fecal contamination in water environment, exhibited higher abundance and lower variability compared to pathogenic SARS-CoV-2 RNA. Significantly, both SARS-CoV-2 and PMMoV RNA exhibited greater variability in 1 h individual composite samples throughout the entire sampling period, contrasting with the stability observed in other time-based composite samples. Through a comprehensive analysis of various composite sampling modes using the Quade Nonparametric ANCOVA test with date, PMMoV concentration and site as covariates, we concluded that employing a composite sampler during a focused 6 h morning window for pathogenic SARS-CoV-2 RNA is a pragmatic and cost-effective strategy for achieving representative composite samples within a single day in wastewater-based epidemiology applications. This method has the potential to significantly enhance the accuracy and reliability of data collected at the community level, thereby contributing to more informed public health decision-making during a pandemic.

SARS-CoV-2 wastewater-based epidemiology in an enclosed compound: A 2.5-year survey to identify factors contributing to local community dissemination

Long-term (>2.5 years) surveillance of SARS-CoV-2 RNA concentrations in wastewater was conducted within an enclosed university compound. This study aims to demonstrate how coupling wastewater-based epidemiology (WBE) with meta-data can identify which factors contribute toward the dissemination of SARS-CoV-2 within a local community. Throughout the pandemic, the temporal dynamics of SARS-CoV-2 RNA concentrations were tracked by quantitative polymerase chain reaction and analyzed in the context of the number of positive swab cases, the extent of human movement, and intervention measures. Our findings suggest that during the early phase of the pandemic, when strict lockdown was imposed, the viral titer load in the wastewater remained below detection limits, with <4 positive swab cases reported over a 14-day period in the compound. After the lockdown was lifted and global travel gradually resumed, SARS-CoV-2 RNA was first detected in the wastewater on 12 August 2020 and increased in frequency thereafter, despite high vaccination rates and mandatory face-covering requirements in the community. Accompanied by a combination of the Omicron surge and significant global travel by community members, SARS-CoV-2 RNA was detected in most of the weekly wastewater samples collected in late December 2021 and January 2022. With the cease of mandatory face covering, SARS-CoV-2 was detected in at least two of the four weekly wastewater samples collected from May through August 2022. Retrospective Nanopore sequencing revealed the presence of the Omicron variant in the wastewater with a multitude of amino acid mutations, from which we could infer the likely geographical origins through bioinformatic analysis. This study demonstrated that long-term tracking of the temporal dynamics and sequencing of variants in wastewater would aid in identifying which factors contribute the most to SARS-CoV-2 dissemination within the local community, facilitating an appropriate public health response to control future outbreaks as we now live with endemic SARS-CoV-2.