Enhanced decay of coronaviruses in sewers with domestic wastewater

High-resolution and real-time wastewater viral surveillance by Nanopore sequencing

Wastewater genomic sequencing stands as a pivotal complementary tool for viral surveillance in populations. While long-read Nanopore sequencing is a promising platform to provide real-time genomic data, concerns over the sequencing accuracy of the earlier Nanopore versions have somewhat restrained its widespread application in wastewater analysis. Here, we evaluate the latest improved version of Nanopore sequencing (R10.4.1), using SARS-CoV-2 as the model infectious virus, to demonstrate its effectiveness in wastewater viral monitoring. By comparing amplicon lengths of 400 bp and 1200 bp, we revealed that shorter PCR amplification is more suitable for wastewater samples due to viral genome fragmentation. Utilizing mock wastewater samples, we validated the reliability of Nanopore sequencing for variant identification by comparing it with Illumina sequencing results. The strength of Nanopore sequencing in generating real-time genomic data for providing early warning signals was also showcased, indicating that as little as 0.001 Gb of data can provide accurate results for variant prevalence. Our evaluation also identified optimal alteration frequency cutoffs (>50 %) for precise mutation profiling, achieving >99 % precision in detecting single nucleotide variants (SNVs) and insertions/deletions (indels). Monitoring two major wastewater treatment plants in Hong Kong from September 2022 to April 2023, covering over 4.5 million population, we observed a transition in dominant variants from BA.5 to XBB lineages, with XBB.1.5 being the most prevalent variants. Mutation detection also highlighted the potential of wastewater Nanopore sequencing in uncovering novel mutations and revealed links between signature mutations and specific variants. This study not only reveals the environmental implications of Nanopore sequencing in SARS-CoV-2 surveillance but also underscores its potential in broader applications including environmental health monitoring of other epidemic viruses, which could significantly enhance the field of wastewater-based epidemiology.

Persistence of human respiratory viral RNA in wastewater-settled solids

Wastewater-based epidemiology has emerged as a valuable tool for monitoring respiratory viral diseases within communities by analyzing concentrations of viral nucleic-acids in wastewater. However, little is known about the fate of respiratory virus nucleic-acids in wastewater. Two important fate processes that may modulate their concentrations in wastewater as they move from household drains to the point of collection include sorption or partitioning to wastewater solids and degradation. This study investigated the decay kinetics of genomic nucleic-acids of seven human respiratory viruses, including severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), respiratory syncytial virus (RSV), human coronavirus (HCoV)-OC43, HCoV-229E, HCoV-NL63, human rhinovirus (HRV), and influenza A virus (IAV), as well as pepper mild mottle virus (PMMoV) in wastewater solids. Viruses (except for PMMoV) were spiked into wastewater solids and their concentrations were followed for 50 days at three different temperatures (4°C, 22°C, and 37°C). Viral genomic RNA decayed following first-order kinetics with decay rate constants k from 0 to 0.219 per day. Decay rate constants k were not different from 0 for all targets in solids incubated at 4°C; k values were largest at 37°C and at this temperature, k values were similar across nucleic-acid targets. Regardless of temperature, there was limited viral RNA decay, with an estimated 0% to 20% reduction, over the typical residence times of sewage in the piped systems between input and collection point (<1 day). The k values reported herein can be used directly in fate and transport models to inform the interpretation of measurements made during wastewater surveillance.IMPORTANCEUnderstanding whether or not the RNA targets quantified for wastewater-based epidemiology (WBE) efforts decay during transport between drains and the point of sample collection is critical for data interpretation. Here we show limited decay of viral RNA targets typically measured for respiratory disease WBE.

Characterizing Spatial Information Loss for Wastewater Surveillance Using crAssphage: Effect of Decay, Temperature, and Population Mobility

Populations contribute information about their health status to wastewater. Characterizing how that information degrades in transit to wastewater sampling locations (e.g., wastewater treatment plants and pumping stations) is critical to interpret wastewater responses. In this work, we statistically estimate the loss of information about fecal contributions to wastewater from spatially distributed populations at the census block group resolution. This was accomplished with a hydrologically and hydraulically influenced spatial statistical approach applied to crAssphage (Carjivirus communis) load measured from the influent of four wastewater treatment plants in Hamilton County, Ohio. We find that we would expect to observe a 90% loss of information about fecal contributions from a given census block group over a travel time of 10.3 h. This work demonstrates that a challenge to interpreting wastewater responses (e.g., during wastewater surveillance) is distinguishing between a distal but large cluster of contributions and a near but small contribution. This work demonstrates new modeling approaches to improve measurement interpretation depending on sewer network and wastewater characteristics (e.g., geospatial layout, temperature variability, population distribution, and mobility). This modeling can be integrated into standard wastewater surveillance methods and help to optimize sewer sampling locations to ensure that different populations (e.g., vulnerable and susceptible) are appropriately represented.

Wastewater-based epidemiology predicts COVID-19-induced weekly new hospital admissions in over 150 USA counties

Although the coronavirus disease (COVID-19) emergency status is easing, the COVID-19 pandemic continues to affect healthcare systems globally. It is crucial to have a reliable and population-wide prediction tool for estimating COVID-19-induced hospital admissions. We evaluated the feasibility of using wastewater-based epidemiology (WBE) to predict COVID-19-induced weekly new hospitalizations in 159 counties across 45 states in the United States of America (USA), covering a population of nearly 100 million. Using county-level weekly wastewater surveillance data (over 20 months), WBE-based models were established through the random forest algorithm. WBE-based models accurately predicted the county-level weekly new admissions, allowing a preparation window of 1-4 weeks. In real applications, periodically updated WBE-based models showed good accuracy and transferability, with mean absolute error within 4-6 patients/100k population for upcoming weekly new hospitalization numbers. Our study demonstrated the potential of using WBE as an effective method to provide early warnings for healthcare systems.

Probable Evidence of Aerosol Transmission of SARS-COV-2 in a COVID-19 Outbreak of a High-Rise Building

Although it is well established that severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) can be transmitted through aerosols, the mode of long-range aerosol transmission in high-rise buildings remains unclear. In this study, we analyzed an outbreak of coronavirus disease 2019 (COVID-19) that occurred in a high-rise building in China. Our objective was to investigate the plausibility of aerosol transmission of SARS-CoV-2 by testing relevant environmental variables and measuring the dispersion of a tracer gas in the drainage system of the building. The outbreak involved 7 infected families, of which 6 were from vertically aligned flats on different floors. Environmenìtal data revealed that 3 families' bathrooms were contaminated by SARS-CoV-2. In our tracer experiment, we injected tracer gas (CO₂) into the dry floor drains and into water-filled toilets in the index case' s bathroom. Our findings showed that the gas could travel through vertical pipes by the dry floor drains, but not through the water of the toilets. This indicates that dry floor drains might facilitate the transmission of viral aerosols through the sewage system. On the basis of circumstantial evidence, long-range aerosol transmission may have contributed to the community outbreak of COVID-19 in this high-rise building. The vertical transmission of diseases through aerosols in high-rise buildings demands urgent attention.

Intensity of sample processing methods impacts wastewater SARS-CoV-2 whole genome amplicon sequencing outcomes

Wastewater SARS-CoV-2 surveillance has been deployed since the beginning of the COVID-19 pandemic to monitor the dynamics in virus burden in local communities. Genomic surveillance of SARS-CoV-2 in wastewater, particularly efforts aimed at whole genome sequencing for variant tracking and identification, are still challenging due to low target concentration, complex microbial and chemical background, and lack of robust nucleic acid recovery experimental procedures. The intrinsic sample limitations are inherent to wastewater and are thus unavoidable. Here, we use a statistical approach that couples correlation analyses to a random forest-based machine learning algorithm to evaluate potentially important factors associated with wastewater SARS-CoV-2 whole genome amplicon sequencing outcomes, with a specific focus on the breadth of genome coverage. We collected 182 composite and grab wastewater samples from the Chicago area between November 2020 to October 2021. Samples were processed using a mixture of processing methods reflecting different homogenization intensities (HA + Zymo beads, HA + glass beads, and Nanotrap), and were sequenced using one of the two library preparation kits (the Illumina COVIDseq kit and the QIAseq DIRECT kit). Technical factors evaluated using statistical and machine learning approaches include sample types, certain sample intrinsic features, and processing and sequencing methods. The results suggested that sample processing methods could be a predominant factor affecting sequencing outcomes, and library preparation kits was considered a minor factor. A synthetic SARS-CoV-2 RNA spike-in experiment was performed to validate the impact from processing methods and suggested that the intensity of the processing methods could lead to different RNA fragmentation patterns, which could also explain the observed inconsistency between qPCR quantification and sequencing outcomes. Overall, extra attention should be paid to wastewater sample processing (i.e., concentration and homogenization) for sufficient and good quality SARS-CoV-2 RNA for downstream sequencing.

SARS-CoV-2 detection and inactivation in water and wastewater: Review on analytical methods, limitations and future research recommendations

AbstractSevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has been detected in wastewater. Wastewater-based epidemiology (WBE) is a practical and cost-effective tool for the assessment and controlling of pandemics and probably for examining SARS-CoV-2 presence. Implementation of WBE during the outbreaks is not without limitations. Temperature, suspended solids, pH, and disinfectants affect the stability of viruses in wastewater. Due to these limitations, instruments and techniques have been utilized to detect SARS-CoV-2. SARS-CoV-2 has been detected in sewage using various concentration methods and computer-aided analyzes. RT-qPCR, ddRT-PCR, multiplex PCR, RT-LAMP, and electrochemical immunosensors have been employed to detect low levels of viral contamination. Inactivation of SARS-CoV-2 is a crucial preventive measure against coronavirus disease 2019 (COVID-19). To better assess the role of wastewater as a transmission route, detection, and quantification methods need to be refined. In this paper, the latest improvements in quantification, detection, and inactivation of SARS-CoV-2 in wastewater are explained. Finally, limitations and future research recommendations are thoroughly described.

Moving forward with COVID-19: Future research prospects of wastewater-based epidemiology methodologies and applications

Wastewater-based epidemiology (WBE) has been demonstrated for its great potential in tracking of coronavirus disease 2019 (COVID-19) transmission among populations despite some inherent methodological limitations. These include non-optimized sampling approaches and analytical methods; stability of viruses in sewer systems; partitioning/retention in biofilms; and the singular and inaccurate back-calculation step to predict the number of infected individuals in the community. Future research is expected to (1) standardize best practices in wastewater sampling, analysis and data reporting protocols for the sensitive and reproducible detection of viruses in wastewater; (2) understand the in-sewer viral stability and partitioning under the impacts of dynamic wastewater flow, properties, chemicals, biofilms and sediments; and (3) achieve smart wastewater surveillance with artificial intelligence and big data models. Further specific research is essential in the monitoring of other viral pathogens with pandemic potential and subcatchment applications to maximize the benefits of WBE beyond COVID-19.

In-sewer decay and partitioning of Campylobacter jejuni and Campylobacter coli and implications for their wastewater surveillance

Campylobacter jejuni and coli are two main pathogenic species inducing diarrhoeal diseases in humans, which are responsible for the loss of 33 million lives each year. Current Campylobacter infections are mainly monitored by clinical surveillance which is often limited to individuals seeking treatment, resulting in under-reporting of disease prevalence and untimely indicators of community outbreaks. Wastewater-based epidemiology (WBE) has been developed and employed for the wastewater surveillance of pathogenic viruses and bacteria. Monitoring the temporal changes of pathogen concentration in wastewater allows the early detection of disease outbreaks in a community. However, studies investigating the WBE back-estimation of Campylobacter spp. are rare. Essential factors including the analytical recovery efficiency, the decay rate, the effect of in-sewer transport, and the correlation between the wastewater concentration and the infections in communities are lacking to support wastewater surveillance. This study carried out experiments to investigate the recovery of Campylobacter jejuni and coli from wastewater and the decay under different simulated sewer reactor conditions. It was found that the recovery of Campylobacter spp. from wastewater varied with their concentrations in wastewater and depended on the detection limit of quantification methods. The concentration reduction of Campylobacter. jejuni and coli in sewers followed a two-phase reduction model, and the faster concentration reduction during the first phase is mainly due to their partitioning onto sewer biofilms. The total decay of Campylobacter. jejuni and coli varied in different types of sewer reactors, i.e. rising main vs. gravity sewer. In addition, the sensitivity analysis for WBE back-estimation of Campylobacter suggested that the first-phase decay rate constant (k₁) and the turning time point (t₁) are determining factors and their impacts increased with the hydraulic retention time of wastewater.

Effects of sewer biofilms on the degradability of carbapenems in wastewater using laboratory scale bioreactors

Carbapenems are last-resort antibiotics used to treat bacterial infections unsuccessfully treated by most common categories of antibiotics in humans. Most of their dosage is secreted unchanged as waste, thereby making its way into the urban water system. There are two major knowledge gaps addressed in this study to gain a better understanding of the effects of their residual concentrations on the environment and environmental microbiome: development of a UHPLC-MS/MS method of detection and quantification from raw domestic wastewater via direct injection and study of their stability in sewer environment during the transportation from domestic sewers to wastewater treatment plants. The UHPLC-MS/MS method was developed for four carbapenems: meropenem, doripenem, biapenem and ertapenem, and validation was performed in the range of 0.5-10 μg/L for all analytes, with limit of detection (LOD) and limit of quantification (LOQ) values ranging from 0.2-0.5 μg/L and 0.8-1.6 μg/L respectively. Laboratory scale rising main (RM) and gravity sewer (GS) bioreactors were employed to culture mature biofilms with real wastewater as the feed. Batch tests were conducted in RM and GS sewer bioreactors fed with carbapenem-spiked wastewater to evaluate the stability of carbapenems and compared against those in a control reactor (CTL) without sewer biofilms, over a duration of 12 h. Significantly higher degradation was observed for all carbapenems in RM and GS reactors (60 - 80%) as opposed to CTL reactor (5 - 15%), which indicates that sewer biofilms play a significant role in the degradation. First order kinetics model was applied to the concentration data along with Friedman's test and Dunn's multiple comparisons analysis to establish degradation patterns and differences in the degradation observed in sewer reactors. As per Friedman's test, there was a statistically significant difference in the degradation of carbapenems observed depending on the reactor type (p = 0.0017 - 0.0289). The results from Dunn's test indicate that the degradation in the CTL reactor was statistically different from that observed in either RM (p = 0.0033 - 0.1088) or GS (p = 0.0162 - 0.1088), with the latter two showing insignificant difference in the degradation rates observed (p = 0.2850 - 0.5930). The findings contribute to the understanding about the fate of carbapenems in urban wastewater and the potential application of wastewater-based epidemiology.

Correlation between SARS-CoV-2 RNA concentration in wastewater and COVID-19 cases in community: A systematic review and meta-analysis

Wastewater-based epidemiology (WBE) has been considered as a promising approach for population-wide surveillance of coronavirus disease 2019 (COVID-19). Many studies have successfully quantified severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) RNA concentration in wastewater (CRNA). However, the correlation between the CRNA and the COVID-19 clinically confirmed cases in the corresponding wastewater catchments varies and the impacts of environmental and other factors remain unclear. A systematic review and meta-analysis were conducted to identify the correlation between CRNA and various types of clinically confirmed case numbers, including prevalence and incidence rates. The impacts of environmental factors, WBE sampling design, and epidemiological conditions on the correlation were assessed for the same datasets. The systematic review identified 133 correlation coefficients, ranging from -0.38 to 0.99. The correlation between CRNA and new cases (either daily new, weekly new, or future cases) was stronger than that of active cases and cumulative cases. These correlation coefficients were potentially affected by environmental and epidemiological conditions and WBE sampling design. Larger variations of air temperature and clinical testing coverage, and the increase of catchment size showed strong negative impacts on the correlation between CRNA and COVID-19 case numbers. Interestingly, the sampling technique had negligible impact although increasing the sampling frequency improved the correlation. These findings highlight the importance of viral shedding dynamics, in-sewer decay, WBE sampling design and clinical testing on the accurate back-estimation of COVID-19 case numbers through the WBE approach.

A Recent Progress in the Leachate Pretreatment Methods Coupled with Anaerobic Digestion for Enhanced Biogas Production: Feasibility, Trends, and Techno-Economic Evaluation

Landfill leachate (LFL) treatment is a severe challenge due to its highly viscous nature and various complex pollutants. Leachate comprises various toxic pollutants, including inorganic macro/nano components, xenobiotics, dissolved organic matter, heavy metals, and microorganisms responsible for severe environmental pollution. Various treatment procedures are available to achieve better effluent quality levels; however, most of these treatments are nondestructive, so pollutants are merely transported from one phase to another, resulting in secondary contamination. Anaerobic digestion is a promising bioconversion technology for treating leachate while producing renewable, cleaner energy. Because of its high toxicity and low biodegradability, biological approaches necessitate employing other techniques to complement and support the primary process. In this regard, pretreatment technologies have recently attracted researchers' interest in addressing leachate treatment concerns through anaerobic digestion. This review summarizes various LFL pretreatment methods, such as electrochemical, ultrasonic, alkaline, coagulation, nanofiltration, air stripping, adsorption, and photocatalysis, before the anaerobic digestion of leachate. The pretreatment could assist in converting biogas (carbon dioxide to methane) and residual volatile fatty acids to valuable chemicals and fuels and even straight to power generation. However, the selection of pretreatment is a vital step. The techno-economic analysis also suggested the high economic feasibility of integrated-anaerobic digestion. Therefore, with the incorporation of pretreatment and anaerobic digestion, the process could have high economic viability attributed to bioenergy production and cost savings through sustainable leachate management options.

A critical review of wastewater quality variation and in-sewer processes during conveyance in sewer systems

In-sewer physio-biochemical processes cause significant variations of wastewater quality during conveyance, which affects the influent to a wastewater treatment plant (WWTP) and arguably the microbial community of biological treatment units in a WWTP. In wet weather, contaminants stored in sewer deposits can be resuspended and migrate downstream or be released during combined sewer overflows to the urban water bodies, posing challenges to the treatment facilities or endangering urban water quality. Therefore, in-sewer transformation and migration of contaminants have been extensively studied. The compiled results from representative research in the past few decades showed that biochemical reactions are both cross-sectionally and longitudinally organized in the deposits and the sewage, following the redox potential as well as the sequence of macromolecule/contaminant degradation. The sewage organic contents and sewer biofilm microorganisms were found to covary but more systematic studies are required to examine the temporal stability of the feature. Besides, unique communities can be developed in the sewage phase. The enrichment of the major sewage-associated microorganisms can be explained by the availability of biodegradable organic contents in sewers. The sewer deposits, including biofilms, harbor both microorganisms and contaminants and usually can provide longer residence time for in-sewer transformation than wastewater. However, the interrelationships among contaminant transformation, microorganisms in the deposits/biofilms, and those in the sewage are largely unclear. Specifically, the formation and migration of FOG (fat, oil, and grease) deposits, generation and transport of contaminants in the sewer atmosphere (e.g., H₂S, CH₄, volatile organic compounds, bioaerosols), transport and transformation of nonconventional contaminants, such as pharmaceuticals and personal care products, and wastewater quality variation during the biofilm rehabilitation period after damages caused by rains/storms are some topics for future research. Moreover, systematic and standardized field analysis of real sewers under dynamic wastewater discharge conditions is necessary. We believe that an improved understanding of these processes would assist in sewer management and better prepare us for the challenges brought about by climate change and water shortage.

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.

Simultaneous Detection of SARS-CoV-2 and Influenza Virus in Wastewater of Two Cities in Southeastern Germany, January to May 2022

Dependent on the excretion pattern, wastewater monitoring of viruses can be a valuable approach to characterizing their circulation in the human population. Using polyethylene glycol precipitation and reverse transcription-quantitative PCR, the occurrence of RNA of SARS-CoV-2 and influenza viruses A/B in the raw wastewater of two treatment plants in Germany between January and May 2022 was investigated. Due to the relatively high incidence in both exposal areas (plant 1 and plant 2), SARS-CoV-2-specific RNA was determined in all 273 composite samples analyzed (concentration of E gene: 1.3 × 10⁴ to 3.2 × 10⁶ gc/L). Despite a nation-wide low number of confirmed infections, influenza virus A was demonstrated in 5.2% (concentration: 9.8 × 10² to 8.4 × 10⁴ gc/L; plant 1) and in 41.6% (3.6 × 10³ to 3.0 × 10⁵ gc/L; plant 2) of samples. Influenza virus B was detected in 36.0% (7.2 × 10² to 8.5 × 10⁶ gc/L; plant 1) and 57.7% (9.6 × 10³ to 2.1 × 10⁷ gc/L; plant 2) of wastewater samples. The results of the study demonstrate the frequent detection of two primary respiratory viruses in wastewater and offer the possibility to track the epidemiology of influenza by wastewater-based monitoring.

Vertical outbreak of COVID-19 in high-rise buildings: The role of sewer stacks and prevention measures

COVID-19 outbreaks in high-rise buildings suggested the transmission route of fecal-aerosol-inhalation due to the involvement of viral aerosols in sewer stacks. The vertical transmission is likely due to the failure of water traps that allow viral aerosols to spread through sewer stacks. This process can be further facilitated by the chimney effect in vent stack, extract ventilation in bathrooms, or wind-induced air pressure fluctuations. To eliminate the risk of such vertical disease spread, the installation of protective devices is highly encouraged in high-rise buildings. Although the mechanism of vertical pathogen spread through drainage pipeline has been illustrated by tracer gas or microbial experiments and numerical modeling, more research is needed to support the update of regulatory and design standards for sewerage facilities.

Effectiveness of building-level sewage surveillance during both community-spread and sporadic-infection phases of SARS-CoV-2 in a university campus population

Pathogen surveillance within wastewater rapidly progressed during the SARS-CoV-2 pandemic and informed public health management. In addition to the successful monitoring of entire sewer catchment basins at the treatment facility scale, subcatchment or building-level monitoring enabled targeted support of resource deployment. However, optimizing the temporal and spatial resolution of these monitoring programs remains complex due to population dynamics and within-sewer physical, chemical, and biological processes. To address these limitations, this study explores the advancement of the building-scale network that monitored the on-campus residential population at the University of Colorado Boulder between August 2020 and May 2021 through a daily SARS-CoV-2 surveillance campaign. During the study period, SARS-CoV-2 infection prevalence transitioned from robust community spread in Fall 2020 to sporadic infections in Spring 2021. Temporally, these distinct phases enabled investigating the effectiveness of resource commitment by exploring subsets of the original daily sampling data. Spatially, select sampling sites were installed along the flow path of the pipe network, enabling the exploration of the conservation of viral concentrations within the wastewater. Infection prevalence and resource commitment for informed action displayed an inverted relationship: higher temporal and spatial resolution surveillance is more imperative during sporadic infection phases than during high prevalence periods. This relationship was reinforced when norovirus (two minor clusters) and influenza (primarily absent) were additionally surveilled at a weekly frequency. Overall, resource commitment should scale to meet the objectives of the monitoring campaign-providing a general prevalence estimate requires fewer resources than an early-warning and targeted-action monitoring framework.

Artificial neural network-based estimation of COVID-19 case numbers and effective reproduction rate using wastewater-based epidemiology

As a cost-effective and objective population-wide surveillance tool, wastewater-based epidemiology (WBE) has been widely implemented worldwide to monitor the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) RNA concentration in wastewater. However, viral concentrations or loads in wastewater often correlate poorly with clinical case numbers. To date, there is no reliable method to back-estimate the coronavirus disease 2019 (COVID-19) case numbers from SARS-CoV-2 concentrations in wastewater. This greatly limits WBE in achieving its full potential in monitoring the unfolding pandemic. The exponentially growing SARS-CoV-2 WBE dataset, on the other hand, offers an opportunity to develop data-driven models for the estimation of COVID-19 case numbers (both incidence and prevalence) and transmission dynamics (effective reproduction rate). This study developed artificial neural network (ANN) models by innovatively expanding a conventional WBE dataset to include catchment, weather, clinical testing coverage and vaccination rate. The ANN models were trained and evaluated with a comprehensive state-wide wastewater monitoring dataset from Utah, USA during May 2020 to December 2021. In diverse sewer catchments, ANN models were found to accurately estimate the COVID-19 prevalence and incidence rates, with excellent precision for prevalence rates. Also, an ANN model was developed to estimate the effective reproduction number from both wastewater data and other pertinent factors affecting viral transmission and pandemic dynamics. The established ANN model was successfully validated for its transferability to other states or countries using the WBE dataset from Wisconsin, USA.

Reduction and discharge of SARS-CoV-2 RNA in Chicago-area water reclamation plants

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) RNA is commonly excreted in the feces and urine of infected individuals and is, therefore, detected in wastewaters where infection is present in the surrounding population. Water reclamation plants (WRPs) that treat these wastewaters commonly discharge treated effluents into the surrounding environment, yet little is known about the removal or persistence of SARS-CoV-2 RNA through wastewater treatment systems and potential for eventual release into the environment. We collected 361 24-hour composite influent and effluent samples from seven WRPs in the Greater Chicago Area in Illinois. Samples were collected over a period of 21 weeks for three large WRPs (with design max flows of 1.89-2.32 billion gallons per day and serving a combined population of 4.62 million people) and 11 weeks for four smaller WRPs (with design max flows of 96.3-186 million gallons per day and serving a combined population of >0.5 million people). A total of two of the larger WRPs implemented seasonal disinfection (using UV light or chlorination/dechlorination) for 8 weeks of this sampling period. SARS-CoV-2 RNA was quantified in the influent and effluent samples by reverse-transcription quantitative PCR (RT-qPCR) of the N1 and N2 targets of the nucleocapsid (N) gene. Although SARS-CoV-2 RNA was regularly detected in influent and effluent from all WRPs, viral RNA concentrations in the effluent samples were considerably lower, with mean effluent: influent gene copy concentration ratios ranging from 1:160 to 1:2.95 between WRPs. Samples collected while disinfection was active vs. inactive did not show any significant difference in the portion of RNA persisting through the treatment process (P > .05).