Wastewater surveillance of SARS-CoV-2 mutational profiles at a university and its surrounding community reveals a 20G outbreak on campus

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.

Systematic SARS-CoV-2 S-gene sequencing in wastewater samples enables early lineage detection and uncovers rare mutations in Portugal

As the COVID-19 pandemic reached its peak, many countries implemented genomic surveillance systems to track the evolution and transmission of SARS-CoV-2. Transition from the pandemic to the endemic phase prioritized alternative testing strategies to maintain effective epidemic surveillance at the population level, with less intensive sequencing efforts. One such promising approach was Wastewater-Based Surveillance (WBS), which offers non-invasive, cost-effective means for analysing virus trends at the sewershed level. From 2020 onwards, wastewater has been recognized as an instrumental source of information for public health, with national and international authorities exploring options to implement national wastewater surveillance systems and increasingly relying on WBS as early warning of potential pathogen outbreaks. In Portugal, several pioneer projects joined the academia, water utilities and Public Administration around WBS. To validate WBS as an effective genomic surveillance strategy, it is crucial to collect long term performance data. In this work, we present one year of systematic SARS-CoV-2 wastewater surveillance in Portugal, representing 35 % of the mainland population. We employed two complementary methods for lineage determination - allelic discrimination by RT-PCR and S-gene sequencing. This combination allowed us to monitor variant evolution in near-real-time and identify low-frequency mutations. Over the course of this year-long study, spanning from May 2022 to April 2023, we successfully tracked the dominant Omicron sub-lineages, their progression and evolution, which aligned with concurrent clinical surveillance data. Our results underscore the effectiveness of WBS as a tracking system for virus variants, with the ability to unveil mutations undetected via massive sequencing of clinical samples from Portugal, demonstrating the ability of WBS to uncover new mutations and detect rare genetic variants. Our findings emphasize that knowledge of the genetic diversity of SARS-CoV-2 at the population level can be extended far beyond via the combination of routine clinical genomic surveillance with wastewater sequencing and genotyping.

Comparison of Nanopore and Synthesis-Based Next-Generation Sequencing Platforms for SARS-CoV-2 Variant Monitoring in Wastewater

Shortly after the beginning of the SARS-CoV-2 pandemic, many countries implemented sewage sentinel systems to monitor the circulation of the virus in the population. A fundamental part of these surveillance programs is the variant tracking through sequencing approaches to monitor and identify new variants or mutations that may be of importance. Two of the main sequencing platforms are Illumina and Oxford Nanopore Technologies. Here, we compare the performance of MiSeq (Illumina) and MinION (Oxford Nanopore Technologies), as well as two different data processing pipelines, to determine the effect they may have on the results. MiSeq showed higher sequencing coverage, lower error rate, and better capacity to detect and accurately estimate variant abundances than MinION R9.4.1 flow cell data. The use of different variant callers (LoFreq and iVar) and approaches to calculate the variant proportions had a remarkable impact on the results generated from wastewater samples. Freyja, coupled with iVar, may be more sensitive and accurate than LoFreq, especially with MinION data, but it comes at the cost of having a higher error rate. The analysis of MinION R10.4.1 flow cell data using Freyja combined with iVar narrows the gap with MiSeq performance in terms of read quality, accuracy, sensitivity, and number of detected mutations. Although MiSeq should still be considered as the standard method for SARS-CoV-2 variant tracking, MinION's versatility and rapid turnaround time may represent a clear advantage during the ongoing pandemic.

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.

Wastewater surveillance uncovers regional diversity and dynamics of SARS-CoV-2 variants across nine states in the USA

Wastewater-based epidemiology (WBE) is a non-invasive and cost-effective approach for monitoring the spread of a pathogen within a community. WBE has been adopted as one of the methods to monitor the spread and population dynamics of the SARS-CoV-2 virus, but significant challenges remain in the bioinformatic analysis of WBE-derived data. Here, we have developed a new distance metric, CoVdist, and an associated analysis tool that facilitates the application of ordination analysis to WBE data and the identification of viral population changes based on nucleotide variants. We applied these new approaches to a large-scale dataset from 18 cities in nine states of the USA using wastewater collected from July 2021 to June 2022. We found that the trends in the shift between the Delta and Omicron SARS-CoV-2 lineages were largely consistent with what was seen in clinical data, but that wastewater analysis offered the added benefit of revealing significant differences in viral population dynamics at the state, city, and even neighborhood scales. We also were able to observe the early spread of variants of concern and the presence of recombinant lineages during the transitions between variants, both of which are challenging to analyze based on clinically-derived viral genomes. The methods outlined here will be beneficial for future applications of WBE to monitor SARS-CoV-2, particularly as clinical monitoring becomes less prevalent. Additionally, these approaches are generalizable, allowing them to be applied for the monitoring and analysis of future viral outbreaks.

Wastewater monitoring for detection of public health markers during the COVID-19 pandemic: Near-source monitoring of schools in England over an academic year

BACKGROUND

Schools are high-risk settings for infectious disease transmission. Wastewater monitoring for infectious diseases has been used to identify and mitigate outbreaks in many near-source settings during the COVID-19 pandemic, including universities and hospitals but less is known about the technology when applied for school health protection. This study aimed to implement a wastewater surveillance system to detect SARS-CoV-2 and other public health markers from wastewater in schools in England.

METHODS

A total of 855 wastewater samples were collected from 16 schools (10 primary, 5 secondary and 1 post-16 and further education) over 10 months of school term time. Wastewater was analysed for SARS-CoV-2 genomic copies of N1 and E genes by RT-qPCR. A subset of wastewater samples was sent for genomic sequencing, enabling determination of the presence of SARS-CoV-2 and emergence of variant(s) contributing to COVID-19 infections within schools. In total, >280 microbial pathogens and >1200 AMR genes were screened using RT-qPCR and metagenomics to consider the utility of these additional targets to further inform on health threats within the schools.

RESULTS

We report on wastewater-based surveillance for COVID-19 within English primary, secondary and further education schools over a full academic year (October 2020 to July 2021). The highest positivity rate (80.4%) was observed in the week commencing 30th November 2020 during the emergence of the Alpha variant, indicating most schools contained people who were shedding the virus. There was high SARS-CoV-2 amplicon concentration (up to 9.2x106 GC/L) detected over the summer term (8th June - 6th July 2021) during Delta variant prevalence. The summer increase of SARS-CoV-2 in school wastewater was reflected in age-specific clinical COVID-19 cases. Alpha variant and Delta variant were identified in the wastewater by sequencing of samples collected from December to March and June to July, respectively. Lead/lag analysis between SARS-CoV-2 concentrations in school and WWTP data sets show a maximum correlation between the two-time series when school data are lagged by two weeks. Furthermore, wastewater sample enrichment coupled with metagenomic sequencing and rapid informatics enabled the detection of other clinically relevant viral and bacterial pathogens and AMR.

CONCLUSIONS

Passive wastewater monitoring surveillance in schools can identify cases of COVID-19. Samples can be sequenced to monitor for emerging and current variants of concern at the resolution of school catchments. Wastewater based monitoring for SARS-CoV-2 is a useful tool for SARS-CoV-2 passive surveillance and could be applied for case identification and containment, and mitigation in schools and other congregate settings with high risks of transmission. Wastewater monitoring enables public health authorities to develop targeted prevention and education programmes for hygiene measures within undertested communities across a broad range of use cases.

Community-Based SARS-CoV-2 Testing Using Saliva or Nasopharyngeal Swabs to Compare the Performance of Weekly COVID-19 Screening to Wastewater SARS-CoV-2 Signals

Multiple studies worldwide have confirmed that severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) RNA can be detected in wastewater. However, there is a lack of data directly comparing the wastewater SARS-CoV-2 RNA concentration with the prevalence of coronavirus disease 2019 (COVID-19) in individuals living in sewershed areas. Here, we correlate wastewater SARS-CoV-2 signals with SARS-CoV-2 positivity rates in symptomatic and asymptomatic individuals and compare positivity rates in two underserved communities in Portland, Oregon to those reported in greater Multnomah County. 403 individuals were recruited via two COVID-19 testing sites over a period of 16 weeks. The weekly SARS-CoV-2 positivity rate in our cohort ranged from 0 to 21.7% and trended higher than symptomatic positivity rates reported by Multnomah County (1.9-8.7%). Among the 362 individuals who reported symptom status, 76 were symptomatic and 286 were asymptomatic. COVID-19 was detected in 35 participants: 24 symptomatic, 9 asymptomatic, and 2 of unknown symptomatology. Wastewater testing yielded 0.33-149.9 viral RNA genomic copies/L/person and paralleled community COVID-19 positive test rates. In conclusion, wastewater sampling accurately identified increased SARS-CoV-2 within a community. Importantly, the rate of SARS-CoV-2 positivity in underserved areas is higher than positivity rates within the County as a whole, suggesting a disproportionate burden of SARS-CoV-2 in these communities.

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

To date, the COVID-19 pandemic has resulted in over 570 million cases and over 6 million deaths worldwide. Predominant clinical testing methods, though invaluable, may create an inaccurate depiction of COVID-19 prevalence due to inadequate access, testing, or most recently under-reporting because of at-home testing. These concerns have created a need for unbiased, community-level surveillance. Wastewater-based epidemiology has been used for previous public health threats, and more recently has been established as a complementary method of SARS-CoV-2 surveillance. Here we describe the application of wastewater surveillance for SARS-CoV-2 in two university campus communities located in rural Lincoln Parish, Louisiana. This cost-effective approach is especially well suited to rural areas where limited access to testing may worsen the spread of COVID-19 and quickly exhaust the capacity of local healthcare systems. Our work demonstrates that local universities can leverage scientific resources to advance public health equity in rural areas and enhance their community involvement.

Multifaceted Assessment of Wastewater-Based Epidemiology for SARS-CoV-2 in Selected Urban Communities in Davao City, Philippines: A Pilot Study

Over 60 countries have integrated wastewater-based epidemiology (WBE) in their COVID-19 surveillance programs, focusing on wastewater treatment plants (WWTP). In this paper, we piloted the assessment of SARS-CoV-2 WBE as a complementary public health surveillance method in susceptible communities in a highly urbanized city without WWTP in the Philippines by exploring the extraction and detection methods, evaluating the contribution of physico-chemical-anthropogenic factors, and attempting whole-genome sequencing (WGS). Weekly wastewater samples were collected from sewer pipes or creeks in six communities with moderate-to-high risk of COVID-19 transmission, as categorized by the City Government of Davao from November to December 2020. Physico-chemical properties of the wastewater and anthropogenic conditions of the sites were noted. Samples were concentrated using a PEG-NaCl precipitation method and analyzed by RT-PCR to detect the SARS-CoV-2 N, RdRP, and E genes. A subset of nine samples were subjected to WGS using the Minion sequencing platform. SARS-CoV-2 RNA was detected in twenty-two samples (91.7%) regardless of the presence of new cases. Cycle threshold values correlated with RNA concentration and attack rate. The lack of a sewershed map in the sampled areas highlights the need to integrate this in the WBE planning. A combined analysis of wastewater physico-chemical parameters such as flow rate, surface water temperature, salinity, dissolved oxygen, and total dissolved solids provided insights on the ideal sampling location, time, and method for WBE, and their impact on RNA recovery. The contribution of fecal matter in the wastewater may also be assessed through the coliform count and in the context of anthropogenic conditions in the area. Finally, our attempt on WGS detected single-nucleotide polymorphisms (SNPs) in wastewater which included clinically reported and newly identified mutations in the Philippines. This exploratory report provides a contextualized framework for applying WBE surveillance in low-sanitation areas.