Wastewater network infrastructure in public health: Applications and learnings from the COVID-19 pandemic

Advancing health equity in wastewater-based epidemiology: A global critical review and conceptual framework

Population health data from wastewater-based epidemiology (WBE) are being used at unprecedented scales worldwide, yet there is limited focus on how to advance health equity in the field. Addressing this gap, we conducted a critical review of published literature in PubMed, targeting studies at the intersection of WBE and health equity. Of 145 articles assessed in full-text screening, we identified 68 studies with health equity considerations. These studies spanned various spatial scales and biochemical targets, addressing domains such as study design and methodologies, ethical and social considerations, and the feasibility and implementation of WBE monitoring. We summarize and synthesize health equity-oriented considerations across the identified domains. We further propose five key considerations to advance health equity in WBE research and practice, and integrate these considerations into a conceptual framework to illustrate how they apply to major steps in the process of conducting WBE. These considerations include global inequities in WBE access, the need to prevent potential harms and stigma via data misuse (inappropriate reporting of data and potential use of WBE for criminal surveillance), and the importance of regulation and community engagement, particularly amidst the growing privatization of WBE, especially in the United States.

Wastewater-based epidemiology for COVID-19 surveillance and beyond: A survey

The pandemic of COVID-19 has imposed tremendous pressure on public health systems and social economic ecosystems over the past years. To alleviate its social impact, it is important to proactively track the prevalence of COVID-19 within communities. The traditional way to estimate the disease prevalence is to estimate from reported clinical test data or surveys. However, the coverage of clinical tests is often limited and the tests can be labor-intensive, requires reliable and timely results, and consistent diagnostic and reporting criteria. Recent studies revealed that patients who are diagnosed with COVID-19 often undergo fecal shedding of SARS-CoV-2 virus into wastewater, which makes wastewater-based epidemiology for COVID-19 surveillance a promising approach to complement traditional clinical testing. In this paper, we survey the existing literature regarding wastewater-based epidemiology for COVID-19 surveillance and summarize the current advances in the area. Specifically, we have covered the key aspects of wastewater sampling, sample testing, and presented a comprehensive and organized summary of wastewater data analytical methods. Finally, we provide the open challenges on current wastewater-based COVID-19 surveillance studies, aiming to encourage new ideas to advance the development of effective wastewater-based surveillance systems for general infectious diseases.

A low-cost homogenizing device for in-field and remote DNA and RNA extraction

Environmental monitoring of microorganisms is critical for the protection and enhancement of human and ecosystem health. Even though these molecular methods have overtaken traditional culture-based methods and become more accessible, these techniques still require expensive equipment and dedicated facilities to process samples which in the context of a global pandemic, remote sampling areas or low-income countries can be extremely challenging. Sample preparation and sample homogenisation are critical steps for molecular-based techniques, especially for the extraction of DNA and RNA. This study developed a low-cost, open-source, freely available 3D printed homogenizer for the processing of DNA and RNA extraction. The BoSL Beater 3D is a portable device that allows researcher to perform bead-beating steps commonly required for environmental sample extraction protocols in the field and without access to main's power. The BoSL Beater 3D was tested on filtered wastewater samples and passive samplers exposed to wastewater over a 24-hour period and showed similar or better performance to the traditional laboratory bead beater for both the extraction of DNA and RNA. The cost of this 3D homogeniser is roughly $18 AUD ($296 AUD with the jigsaw, which is roughly 57 times cheaper than a traditional bead beater) and has the added usability of being portable and easily adaptable to any type of jigsaw. In combination to newly developed field extraction kits as well as portable PCR machines, this 3D homogeniser could provide the tool necessary to enable access to molecular testing in remote setting as well as developing countries, which may not have access to fully equipped laboratories, but also allow for timely reporting. In addition, the BoSL Beater 3D, in combination with field extraction kit, can allow more flexibility to researchers while sampling, shipping, and processing DNA and RNA samples, whilst maintaining quality of these samples.

A Narrative Review of High Throughput Wastewater Sample Processing for Infectious Disease Surveillance: Challenges, Progress, and Future Opportunities

During the recent COVID-19 pandemic, wastewater-based epidemiological (WBE) surveillance played a crucial role in evaluating infection rates, analyzing variants, and identifying hot spots in a community. This expanded the possibilities for using wastewater to monitor the prevalence of infectious diseases. The full potential of WBE remains hindered by several factors, such as a lack of information on the survival of pathogens in sewage, heterogenicity of wastewater matrices, inconsistent sampling practices, lack of standard test methods, and variable sensitivity of analytical techniques. In this study, we review the aforementioned challenges, cost implications, process automation, and prospects of WBE for full-fledged wastewater-based community health screening. A comprehensive literature survey was conducted using relevant keywords, and peer reviewed articles pertinent to our research focus were selected for this review with the aim of serving as a reference for research related to wastewater monitoring for early epidemic detection.

Wastewater-based Epidemiology for COVID-19 Surveillance and Beyond: A Survey

The pandemic of COVID-19 has imposed tremendous pressure on public health systems and social economic ecosystems over the past years. To alleviate its social impact, it is important to proactively track the prevalence of COVID-19 within communities. The traditional way to estimate the disease prevalence is to estimate from reported clinical test data or surveys. However, the coverage of clinical tests is often limited and the tests can be labor-intensive, requires reliable and timely results, and consistent diagnostic and reporting criteria. Recent studies revealed that patients who are diagnosed with COVID-19 often undergo fecal shedding of SARS-CoV-2 virus into wastewater, which makes wastewater-based epidemiology for COVID-19 surveillance a promising approach to complement traditional clinical testing. In this paper, we survey the existing literature regarding wastewater-based epidemiology for COVID-19 surveillance and summarize the current advances in the area. Specifically, we have covered the key aspects of wastewater sampling, sample testing, and presented a comprehensive and organized summary of wastewater data analytical methods. Finally, we provide the open challenges on current wastewater-based COVID-19 surveillance studies, aiming to encourage new ideas to advance the development of effective wastewater-based surveillance systems for general infectious diseases.

Urban Wastewater-Based Surveillance of SARS-CoV-2 Virus: A Two-Year Study Conducted in City of Patras, Greece

Wastewater-based epidemiology, during the COVID-19 pandemic years, has been applied as a complementary approach, worldwide, for tracking SARS-CoV-2 virus into the community and used as an early warning of the prevalence of COVID-19 infection. The present study presents the results of the 2-year surveillance project, in the city of Patras, Greece. The purpose of the study was to monitor SARS-CoV-2 and implement WBE as an early warning method of monitoring Public Health impact. The presence of SARS-CoV-2 was determined and quantified in 310 samples using RT-qPCR assays. For the years 2022 and 2023, 93.5% and 78.7% of samples were found positive, respectively. Comparison of detection methods have been conducted to select the method with the highest recovery of the viral load. A seasonal variation of the virus was recorded, showing a recession in summer months confirming the country's epidemiological data as indicated by positive correlation of wastewater viral load with registered cases of COVID-19 infections during these years (p < 0.05) and moreover sealed with a significant negative correlation observed with Daily Average (p < 0.01) and Daily Maximum Temperature (p < 0.01). More research was carried out to elucidate a possible association of physicochemical characteristics of wastewater with viral load showing positive correlation with Chlorides (p < 0.01) advocating possible increased use of chlorine-based disinfectants and Electrical Conductivity (p < 0.01) indicates that wastewater during periods of increased infections is more heavily loaded with ions from chemical and biological pollutants. No correlation found with rainfall and physicochemical indicators, such as COD, BOD5, Total Phosphorus, Total Nitrogen, and Total Suspended Solids. According to the findings, WBE represents a useful tool in the management of epidemics based on an environmental approach and it can also shed light on the interacting parameters that capture Public Health since any infections that may lead to epidemics lead to a parallel change in the use of pharmaceuticals, antimicrobials, disinfectants, and microbial load in urban wastewater.

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.

SARS-CoV-2 wastewater surveillance at two university campuses: lessons learned and insights on intervention strategies for public health guidance

Wastewater surveillance has been a tool for public health officials throughout the COVID-19 pandemic. Universities established pandemic response committees to facilitate safe learning for students, faculty, and staff. These committees met to analyze both wastewater and clinical data to propose mitigation strategies to limit the spread of COVID-19. This paper reviews the initial efforts of utilizing campus data inclusive of wastewater surveillance for SARS-CoV-2 RNA concentrations, clinical case data from university response teams, and mitigation strategies from Grand Valley State University in West Michigan (population 21,648 students) and Oakland University in East Michigan (population 18,552 students) from November 2020 to April 2022. Wastewater positivity rates for both universities ranged from 32.8 to 46.8%. Peak viral signals for both universities directly corresponded to variant points of entry within the campus populations from 2021 to 2022. It was found that the organization of clinical case data and variability of wastewater testing data were large barriers for both universities to effectively understand disease dynamics within the university population. We review the initial efforts of onboarding wastewater surveillance and provide direction for structuring ongoing surveillance workflows and future epidemic response strategies based on those that led to reduced viral signals in campus wastewater.

Integrating socio-economic vulnerability factors improves neighborhood-scale wastewater-based epidemiology for public health applications

Wastewater Based Epidemiology (WBE) of COVID-19 is a low-cost, non-invasive, and inclusive early warning tool for disease spread. Previously studied WBE focused on sampling at wastewater treatment plant scale, limiting the level at which demographic and geographic variations in disease dynamics can be incorporated into the analysis of certain neighborhoods. This study demonstrates the integration of demographic mapping to improve the WBE of COVID-19 and associated post-COVID disease prediction (here kidney disease) at the neighborhood level using machine learning. WBE was conducted at six neighborhoods in Seattle during October 2020 - February 2022. Wastewater processing and RT-qPCR were performed to obtain SARS-CoV-2 RNA concentration. Census data, clinical data of COVID-19, as well as patient data of acute kidney injury (AKI) cases reported during the study period were collected and the distribution across the city was studied using Geographic Information System (GIS) mapping. Further, we analyzed the data set to better understand socioeconomic impacts on disease prevalence of COVID-19 and AKI per neighborhood. The heterogeneity of eleven demographic factors (such as education and age among others) was observed within neighborhoods across the city of Seattle. Dynamics of COVID-19 clinical cases and wastewater SARS-CoV-2 varied across neighborhood with different levels of demographics. Machine learning models trained with data from the earlier stages of the pandemic were able to predict both COVID-19 and AKI incidence in the later stages of the pandemic (Spearman correlation coefficient of 0·546 - 0·904), with the most predictive model trained on the combination of wastewater data and demographics. The integration of demographics strengthened machine learning models' capabilities to predict prevalence of COVID-19, and of AKI as a marker for post-COVID sequelae. Demographic-based WBE presents an effective tool to monitor and manage public health beyond COVID-19 at the neighborhood level.

Changes to Public Health Surveillance Methods Due to the COVID-19 Pandemic: Scoping Review

BACKGROUND

Public health surveillance plays a vital role in informing public health decision-making. The onset of the COVID-19 pandemic in early 2020 caused a widespread shift in public health priorities. Global efforts focused on COVID-19 monitoring and contact tracing. Existing public health programs were interrupted due to physical distancing measures and reallocation of resources. The onset of the COVID-19 pandemic intersected with advancements in technologies that have the potential to support public health surveillance efforts.

OBJECTIVE

This scoping review aims to explore emergent public health surveillance methods during the early COVID-19 pandemic to characterize the impact of the pandemic on surveillance methods.

METHODS

A scoping search was conducted in multiple databases and by scanning key government and public health organization websites from March 2020 to January 2022. Published papers and gray literature that described the application of new or revised approaches to public health surveillance were included. Papers that discussed the implications of novel public health surveillance approaches from ethical, legal, security, and equity perspectives were also included. The surveillance subject, method, location, and setting were extracted from each paper to identify trends in surveillance practices. Two public health epidemiologists were invited to provide their perspectives as peer reviewers.

RESULTS

Of the 14,238 unique papers, a total of 241 papers describing novel surveillance methods and changes to surveillance methods are included. Eighty papers were review papers and 161 were single studies. Overall, the literature heavily featured papers detailing surveillance of COVID-19 transmission (n=187). Surveillance of other infectious diseases was also described, including other pathogens (n=12). Other public health topics included vaccines (n=9), mental health (n=11), substance use (n=4), healthy nutrition (n=1), maternal and child health (n=3), antimicrobial resistance (n=2), and misinformation (n=6). The literature was dominated by applications of digital surveillance, for example, by using big data through mobility tracking and infodemiology (n=163). Wastewater surveillance was also heavily represented (n=48). Other papers described adaptations to programs or methods that existed prior to the COVID-19 pandemic (n=9). The scoping search also found 109 papers that discuss the ethical, legal, security, and equity implications of emerging surveillance methods. The peer reviewer public health epidemiologists noted that additional changes likely exist, beyond what has been reported and available for evidence syntheses.

CONCLUSIONS

The COVID-19 pandemic accelerated advancements in surveillance and the adoption of new technologies, especially for digital and wastewater surveillance methods. Given the investments in these systems, further applications for public health surveillance are likely. The literature for surveillance methods was dominated by surveillance of infectious diseases, particularly COVID-19. A substantial amount of literature on the ethical, legal, security, and equity implications of these emerging surveillance methods also points to a need for cautious consideration of potential harm.

Effectiveness of environmental surveillance of SARS-CoV-2 as an early-warning system: Update of a systematic review during the second year of the pandemic

The aim of this updated systematic review was to offer an overview of the effectiveness of environmental surveillance (ES) of SARS-CoV-2 as a potential early-warning system (EWS) for COVID-19 and new variants of concerns (VOCs) during the second year of the pandemic. An updated literature search was conducted to evaluate the added value of ES of SARS-CoV-2 for public health decisions. The search for studies published between June 2021 and July 2022 resulted in 1,588 publications, identifying 331 articles for full-text screening. A total of 151 publications met our inclusion criteria for the assessment of the effectiveness of ES as an EWS and early detection of SARS-CoV-2 variants. We identified a further 30 publications among the grey literature. ES confirms its usefulness as an EWS for detecting new waves of SARS-CoV-2 infection with an average lead time of 1-2 weeks for most of the publication. ES could function as an EWS for new VOCs in areas with no registered cases or limited clinical capacity. Challenges in data harmonization and variant detection require standardized approaches and innovations for improved public health decision-making. ES confirms its potential to support public health decision-making and resource allocation in future outbreaks.

Operationalizing an open-source dashboard for communicating results of wastewater-based surveillance

COVID-19 saw the expansion of public health tools to manage the pandemic. One tool that saw extensive use was the public health dashboard, web-based visualization tools that communicate information to users in easy-to-read graphics. Dashboards were widely used prior to the pandemic, but COVID-19 saw expanded use and development. To date, dashboards have become an important part of public health surveillance programs around the world helping decisionmakers use data to evaluate different public health metrics including caseloads, hospitalizations, and environmental surveillance results from testing wastewater. Wastewater surveillance provides community-based, spatially relevant data on disease trends within communities to assess the scale of infection in a region, which makes it an excellent candidate for dashboard development to improve public health. We developed a dashboard for New York State's wastewater surveillance program using open-source, reproducible web programming. The dashboard we developed has been used for the COVID-19 response in New York, and our methods can be adapted to other programs and pathogens. We provide:•descriptions of how the dashboard was developed and maintained•specific guidance for reproducing our dashboard in other areas and for other pathogens•fully reproducible code with step-by-step instructions for researchers and professionals to make their own data dashboards.

Public Health Interventions Guided by Houston's Wastewater Surveillance Program During the COVID-19 Pandemic

Since the start of the COVID-19 pandemic, wastewater surveillance has emerged as a powerful tool used by public health authorities to track SARS-CoV-2 infections in communities. In May 2020, the Houston Health Department began working with a coalition of municipal and academic partners to develop a wastewater monitoring and reporting system for the city of Houston, Texas. Data collected from the system are integrated with other COVID-19 surveillance data and communicated through different channels to local authorities and the general public. This information is used to shape policies and inform actions to mitigate and prevent the spread of COVID-19 at municipal, institutional, and individual levels. Based on the success of this monitoring and reporting system to drive public health protection efforts, the wastewater surveillance program is likely to become a standard part of the public health toolkit for responding to infectious diseases and, potentially, other disease-causing outbreaks.

Regional reemergence of a SARS-CoV-2 Delta lineage amid an Omicron wave detected by wastewater sequencing

The implementation and integration of wastewater-based epidemiology constitutes a valuable addition to existing pathogen surveillance systems, such as clinical surveillance for SARS-CoV-2. In the Netherlands, SARS-CoV-2 variant circulation is monitored by performing whole-genome sequencing on wastewater samples. In this manuscript, we describe the detection of an AY.43 lineage (Delta variant) amid a period of BA.5 (Omicron variant) dominance in wastewater samples from two wastewater treatment plants (WWTPs) during the months of August and September of 2022. Our results describe a temporary emergence, which was absent in samples from other WWTPs, and which coincided with peaks in viral load. We show how these lineage estimates can be traced back to lineage-specific substitution patterns. The absence of this variant from reported clinical data, but high associated viral loads suggest cryptic transmission. Our findings highlight the additional value of wastewater surveillance for generating insights into circulating pathogens.

Nonbacterial Microflora in Wastewater Treatment Plants: an Underappreciated Potential Source of Pathogens

Wastewater treatment plants (WWTPs) receive and treat large volumes of domestic, industrial, and urban wastewater containing pathogenic and nonpathogenic microorganisms, chemical compounds, heavy metals, and other potentially hazardous substances. WWTPs play an essential role in preserving human, animal, and environmental health by removing many of these toxic and infectious agents, particularly biological hazards. Wastewater contains complex consortiums of bacterial, viral, archaeal, and eukaryotic species, and while bacteria in WWTP have been extensively studied, the temporal and spatial distribution of nonbacterial microflora (viruses, archaea, and eukaryotes) is less understood. In this study, we analyzed the viral, archaeal, and eukaryotic microflora in wastewater throughout a treatment plant (raw influent, effluent, oxidation pond water, and oxidation pond sediment) in Aotearoa (New Zealand) using Illumina shotgun metagenomic sequencing. Our results suggest a similar trend across many taxa, with an increase in relative abundance in oxidation pond samples compared to influent and effluent samples, except for archaea, which had the opposite trend. Additionally, some microbial families, such as Podoviridae bacteriophages and Apicomplexa alveolates, appeared largely unaffected by the treatment process, with their relative abundance remaining stable throughout. Several groups encompassing pathogenic species, such as Leishmania, Plasmodium, Toxoplasma, Apicomplexa, Cryptococcus, Botrytis, and Ustilago, were identified. If present, these potentially pathogenic species could be a threat to human and animal health and agricultural productivity; therefore, further investigation is warranted. These nonbacterial pathogens should be considered when assessing the potential for vector transmission, distribution of biosolids to land, and discharge of treated wastewater to waterways or land. IMPORTANCE Nonbacterial microflora in wastewater remain understudied compared to their bacterial counterparts despite their importance in the wastewater treatment process. In this study, we report the temporal and spatial distributions of DNA viruses, archaea, protozoa, and fungi in raw wastewater influent, effluent, oxidation pond water, and oxidation pond sediments by using shotgun metagenomic sequencing. Our study indicated the presence of groups of nonbacterial taxa which encompass pathogenic species that may have potential to cause disease in humans, animals, and agricultural crops. We also observed higher alpha diversity in viruses, archaea, and fungi in effluent samples than in influent samples. This suggests that the resident microflora in the wastewater treatment plant may be making a greater contribution to the diversity of taxa observed in wastewater effluent than previously thought. This study provides important insights to better understand the potential human, animal, and environmental health impacts of discharged treated wastewater.

Building health system resilience and pandemic preparedness using wastewater-based epidemiology from SARS-CoV-2 monitoring in Bengaluru, India

The COVID-19 pandemic was a watershed event for wastewater-based epidemiology (WBE). It highlighted the inability of existing disease surveillance systems to provide sufficient forewarning to governments on the existing stage and scale of disease spread and underscored the need for an effective early warning signaling system. Recognizing the potentiality of environmental surveillance (ES), in May 2021, COVIDActionCollaborative launched the Precision Health platform. The idea was to leverage ES for equitable mapping of the disease spread in Bengaluru, India and provide early information regarding any inflection in the epidemiological curve of COVID-19. By sampling both networked and non-networked sewage systems in the city, the platform used ES for both equitable and comprehensive surveillance of the population to derive precise information on the existing stage of disease maturity across communities and estimate the scale of the approaching threat. This was in contrast to clinical surveillance, which during the peak of the COVID-19 pandemic in Bengaluru excluded a significant proportion of poor and vulnerable communities from its ambit of representation. The article presents the findings of a sense-making tool which the platform developed for interpreting emerging signals from wastewater data to map disease progression and identifying the inflection points in the epidemiological curve. Thus, the platform accurately generated early warning signals on disease escalation and disseminated it to the government and the general public. This information enabled concerned audiences to implement preventive measures in advance and effectively plan their next steps for improved disease management.

Citywide wastewater SARS-CoV-2 levels strongly correlated with multiple disease surveillance indicators and outcomes over three COVID-19 waves

Public health surveillance systems for COVID-19 are multifaceted and include multiple indicators reflective of different aspects of the burden and spread of the disease in a community. With the emergence of wastewater disease surveillance as a powerful tool to track infection dynamics of SARS-CoV-2, there is a need to integrate and validate wastewater information with existing disease surveillance systems and demonstrate how it can be used as a routine surveillance tool. A first step toward integration is showing how it relates to other disease surveillance indicators and outcomes, such as case positivity rates, syndromic surveillance data, and hospital bed use rates. Here, we present an 86-week long surveillance study that covers three major COVID-19 surges. City-wide SARS-CoV-2 RNA viral loads in wastewater were measured across 39 wastewater treatment plants and compared to other disease metrics for the city of Houston, TX. We show that wastewater levels are strongly correlated with positivity rate, syndromic surveillance rates of COVID-19 visits, and COVID-19-related general bed use rates at hospitals. We show that the relative timing of wastewater relative to each indicator shifted across the pandemic, likely due to a multitude of factors including testing availability, health-seeking behavior, and changes in viral variants. Next, we show that individual WWTPs led city-wide changes in SARS-CoV-2 viral loads, indicating a distributed monitoring system could be used to enhance the early-warning capability of a wastewater monitoring system. Finally, we describe how the results were used in real-time to inform public health response and resource allocation.

Wastewater surveillance of SARS-CoV-2 genomic populations on a country-wide scale through targeted sequencing

SARS-CoV-2 surveillance of viral populations in wastewater samples is recognized as a useful tool for monitoring epidemic waves and boosting health preparedness. Next generation sequencing of viral RNA isolated from wastewater is a convenient and cost-effective strategy to understand the molecular epidemiology of SARS-CoV-2 and provide insights on the population dynamics of viral variants at the community level. However, in low- and middle-income countries, isolated groups have performed wastewater monitoring and data has not been extensively shared in the scientific community. Here we report the results of monitoring the co-circulation and abundance of variants of concern (VOCs) of SARS-CoV-2 in Uruguay, a small country in Latin America, between November 2020-July 2021 using wastewater surveillance. RNA isolated from wastewater was characterized by targeted sequencing of the Receptor Binding Domain region within the spike gene. Two computational approaches were used to track the viral variants. The results of the wastewater analysis showed the transition in the overall predominance of viral variants in wastewater from No-VOCs to successive VOCs, in agreement with clinical surveillance from sequencing of nasal swabs. The mutations K417T, E484K and N501Y, that characterize the Gamma VOC, were detected as early as December 2020, several weeks before the first clinical case was reported. Interestingly, a non-synonymous mutation described in the Delta VOC, L452R, was detected at a very low frequency since April 2021 when using a recently described sequence analysis tool (SAM Refiner). Wastewater NGS-based surveillance of SARS-CoV-2 is a reliable and complementary tool for monitoring the introduction and prevalence of VOCs at a community level allowing early public health decisions. This approach allows the tracking of symptomatic and asymptomatic individuals, who are generally under-reported in countries with limited clinical testing capacity. Our results suggests that wastewater-based epidemiology can contribute to improving public health responses in low- and middle-income countries.

Contextualizing Wastewater-Based surveillance in the COVID-19 vaccination era

SARS-CoV-2 wastewater-based surveillance (WBS) offers a tool for cost-effective oversight of a population's infections. In the past two years, WBS has proven to be crucial for managing the pandemic across different geographical regions. However, the changing context of the pandemic due to high levels of COVID-19 vaccination warrants a closer examination of its implication towards SARS-CoV-2 WBS. Two main questions were raised: 1) Does vaccination cause shedding of viral signatures without infection? 2) Does vaccination affect the relationship between wastewater and clinical data? To answer, we review historical reports of shedding from viral vaccines in use prior to the COVID-19 pandemic including for polio, rotavirus, influenza and measles infection and provide a perspective on the implications of different COVID-19 vaccination strategies with regard to the potential shedding of viral signatures into the sewershed. Additionally, we reviewed studies that looked into the relationship between wastewater and clinical data and how vaccination campaigns could have affected the relationship. Finally, analyzing wastewater and clinical data from the Netherlands, we observed changes in the relationship concomitant with increasing vaccination coverage and switches in dominant variants of concern. First, that no vaccine-derived shedding is expected from the current commercial pipeline of COVID-19 vaccines that may confound interpretation of WBS data. Secondly, that breakthrough infections from vaccinated individuals contribute significantly to wastewater signals and must be interpreted in light of the changing dynamics of shedding from new variants of concern.

Cost of wastewater-based environmental surveillance for SARS-CoV-2: Evidence from pilot sites in Blantyre, Malawi and Kathmandu, Nepal

Environmental surveillance of rivers and wastewater for SARS-CoV-2 detection has been explored as an innovative way to surveil the pandemic. This study estimated the economic costs of conducting wastewater-based environmental surveillance for SARS-CoV-2 to inform decision making if countries consider continuing these efforts. We estimated the cost of two SARS-CoV-2 environmental surveillance pilot studies conducted in Blantyre, Malawi, and Kathmandu, Nepal. The cost estimation accounted for the consumables, equipment, and human resource time costs used for environmental surveillance from sample selection until pathogen detection and overhead costs for the projects. Costs are reported in 2021 US$ and reported as costs per month, per sample and person per year. The estimated costs for environmental surveillance range from $6,175 to $8,272 per month (Blantyre site) and $16,756 to $30,050 (Kathmandu site). The number of samples processed per month ranged from 84 to 336 at the Blantyre site and 96 to 250 at the Kathmandu site. Consumables costs are variable costs influenced by the number of samples processed and are a large share of the monthly costs for ES (ranging from 39% to 72%). The relatively higher costs per month for the Kathmandu site were attributable to the higher allocation of dedicated human resources and equipment to environmental surveillance for SARS-CoV-2 compared to the Blantyre site where these resources were shared with other activities. The average cost per sample ranged from $25 to $74 (Blantyre) and $120 to $175 (Kathmandu). There were associated economies of scale for human resources and equipment costs with increased sample processing and sharing of resources with other activities. The cost per person in the catchment area per year ranged from $0.07 to $0.10 in Blantyre and $0.07 to $0.13 in Kathmandu. Environmental surveillance may be a low-cost early warning signal for SARS-CoV-2 that can complement other SARS-CoV2 monitoring efforts.

Looking Forward: The Role of Academic Researchers in Building Sustainable Wastewater Surveillance Programs

BACKGROUND

In just over 2 years, tracking the COVID-19 pandemic through wastewater surveillance advanced from early reports of successful SARS-CoV-2 RNA detection in untreated wastewater to implementation of programs in at least 60 countries. Early wastewater monitoring efforts primarily originated in research laboratories and are now transitioning into more formal surveillance programs run in commercial and public health laboratories. A major challenge in this progression has been to simultaneously optimize methods and build scientific consensus while implementing surveillance programs, particularly during the rapidly changing landscape of the pandemic. Translating wastewater surveillance results for effective use by public health agencies also remains a key objective for the field.

OBJECTIVES

We examined the evolution of wastewater surveillance to identify model collaborations and effective partnerships that have created rapid and sustained success. We propose needed areas of research and key roles academic researchers can play in the framework of wastewater surveillance to aid in the transition from early monitoring efforts to more formalized programs within the public health system.

DISCUSSION

Although wastewater surveillance has rapidly developed as a useful public health tool for tracking COVID-19, there remain technical challenges and open scientific questions that academic researchers are equipped to address. This includes validating methodology and backfilling important knowledge gaps, such as fate and transport of surveillance targets and epidemiological links to wastewater concentrations. Our experience in initiating and implementing wastewater surveillance programs in the United States has allowed us to reflect on key barriers and draw useful lessons on how to promote synergy between different areas of expertise. As wastewater surveillance programs are formalized, the working relationships developed between academic researchers, commercial and public health laboratories, and data users should promote knowledge co-development. We believe active involvement of academic researchers will contribute to building robust surveillance programs that will ultimately provide new insights into population health. https://doi.org/10.1289/EHP11519.

Modeling approaches for early warning and monitoring of pandemic situations as well as decision support

The COVID-19 pandemic has highlighted the lack of preparedness of many healthcare systems against pandemic situations. In response, many population-level computational modeling approaches have been proposed for predicting outbreaks, spatiotemporally forecasting disease spread, and assessing as well as predicting the effectiveness of (non-) pharmaceutical interventions. However, in several countries, these modeling efforts have only limited impact on governmental decision-making so far. In light of this situation, the review aims to provide a critical review of existing modeling approaches and to discuss the potential for future developments.

Covid-19, an unfinished story

The Covid-19 pandemic appeared in China in December 2019 as a cluster of transmissible pneumonia caused by a new betacoronavirus. On March 11, 2020, the World Health Organization (WHO) declared it a pandemic. Covid-19 is a mild infection in 80% of cases, serious in 15% and critical in 5%. Symptomatic forms include a first phase of flu-like viral invasion, and at times a second phase, dysimmune and inflammatory, with acute respiratory distress syndrome, multiorgan failure and thromboembolic complications. Degree of severity is related to age and comorbidities. SARS-CoV-2 is the third highly pathogenic Betacoronavirus to cross the species barrier. Its genome, an RNA of 29,903 nucleotides, shows strong homogeneity with bat coronaviruses from southern China, but the conditions for its passage in humans have yet to be elucidated. Mutations can give rise to variants of concern (VOC) that are more transmissible and able to evade the host's immune response. Several VOCs have succeeded and replaced one another: Alpha in October 2020, Beta and Gamma in December 2020, Delta in spring 2021 and Omicron in November 2021. The Covid-19 pandemic has evolved in five waves of unequal amplitude and severity, with geographical disparities. Worldwide, it has caused 395,000,000 confirmed cases including 5,700,000 deaths. Epidemiological surveillance applies several indicators (incidence rate, test positivity rate, effective R and occupancy rate of intensive care beds) supplemented by genomic monitoring to detect variants by sequencing. Non-pharmacological measures, particularly face mask wearing, have been effective in preventing the transmission of SARS-CoV-2. Few currently available drugs have proven useful, with the exception of dexamethazone for patients requiring oxygen therapy. Development of SARS-CoV-2 vaccines began early on many platforms. Innovation was brought about by the Pfizer-BioNTech and Moderna messenger RNA vaccines, which claim protective efficacy of 95% and 94.1% respectively, far higher than the 70% minimum set by the WHO. Governments have hesitated between two strategies, mitigation and suppression. The second has been favored in critical periods such as April 2020, when 2.5 billion people throughout the world were confined. Vaccination campaigns got underway at the end of December 2020 and progressed without reaching sufficient herd immunity, leading some nations to consider compulsory vaccination or to require a vaccine or health pass, in order for persons to access different activities. Will the pandemic stop with Omicron and become endemic? This part of the Covid-19 story remains to be told.

Passive sampling to scale wastewater surveillance of infectious disease: Lessons learned from COVID-19

Much of what is known and theorized concerning passive sampling techniques has been developed considering chemical analytes. Yet, historically, biological analytes, such as Salmonella typhi, have been collected from wastewater via passive sampling with Moore swabs. In response to the COVID-19 pandemic, passive sampling is re-emerging as a promising technique to monitor SARS-CoV-2 RNA in wastewater. Method comparisons and disease surveillance using composite, grab, and passive sampling for SARS-CoV-2 RNA detection have found passive sampling with a variety of materials routinely produced qualitative results superior to grab samples and useful for sub-sewershed surveillance of COVID-19. Among individual studies, SARS-CoV-2 RNA concentrations derived from passive samplers demonstrated heterogeneous correlation with concentrations from paired composite samples ranging from weak (R2 = 0.27, 0.31) to moderate (R2 = 0.59) to strong (R2 = 0.76). Among passive sampler materials, electronegative membranes have shown great promise with linear uptake of SARS-CoV-2 RNA observed for exposure durations of 24 to 48 h and in several cases RNA positivity on par with composite samples. Continuing development of passive sampling methods for the surveillance of infectious diseases via diverse forms of fecal waste should focus on optimizing sampler materials for the efficient uptake and recovery of biological analytes, kit-free extraction, and resource-efficient testing methods capable of rapidly producing qualitative or quantitative data. With such refinements passive sampling could prove to be a fundamental tool for scaling wastewater surveillance of infectious disease, especially among the 1.8 billion persons living in low-resource settings served by non-traditional wastewater collection infrastructure.

Establishment of local wastewater-based surveillance programmes in response to the spread and infection of COVID-19 - case studies from South Africa, the Netherlands, Turkey and England

The COVID-19 pandemic has resulted in over 340 million infection cases (as of 21 January 2022) and more than 5.57 million deaths globally. In reaction, science, technology and innovation communities across the globe have organised themselves to contribute to national responses to COVID-19 disease. A significant contribution has been from the establishment of wastewater-based epidemiological (WBE) surveillance interventions and programmes for monitoring the spread of COVID-19 in at least 55 countries. Here, we examine and share experiences and lessons learnt in establishing such surveillance programmes. We use case studies to highlight testing methods and logistics considerations associated in scaling the implementing of such programmes in South Africa, the Netherlands, Turkey and England. The four countries were selected to represent different regions of the world and the perspective based on the considerable progress made in establishing and implementing their national WBE programmes. The selected countries also represent different climatic zones, economies, and development stages, which influence the implementation of national programmes of this nature and magnitude. In addition, the four countries' programmes offer good experiences and lessons learnt since they are systematic, and cover extensive areas, disseminate knowledge locally and internationally and partnered with authorities (government). The programmes also strengthened working relations and partnerships between and among local and global organisations. This paper shares these experiences and lessons to encourage others in the water and public health sectors on the benefits and value of WBE in tackling SARS-CoV-2 and related future circumstances.