Prevalence and Persistent Shedding of Fecal SARS-CoV-2 RNA in Patients With COVID-19 Infection: A Systematic Review and Meta-analysis

Variability of Clinical Metrics in Small Population Communities Drive Perceived Wastewater and Environmental Surveillance Data Quality: Ontario, Canada-Wide Study

The emergence of COVID-19 in Canada has led to over 4.9 million cases and 59,000 deaths by May 2024. Traditional clinical surveillance metrics (hospital admissions and clinical laboratory-positive cases) were complemented with wastewater and environmental monitoring (WEM) to monitor SARS-CoV-2 incidence. However, challenges in public health integration of WEM persist due to perceived limitations of WEM data quality, potentially driving inconsistent correlations variability and lead times. This study investigates how factors like population size, WEM measurement magnitude, site isolation status, hospital admissions, and clinical laboratory-positive cases affect WEM data correlations and variability in Ontario. The analysis uncovers a direct relationship between clinical surveillance data and the population size of the surveyed sewersheds, while WEM measurement magnitude was not directly impacted by population size. Higher variability in clinical surveillance data was observed in smaller sewersheds, likely reducing correlation strength for inferring COVID-19 incidence. Population size significantly influenced correlation quality, with thresholds identified at ∼66,000 inhabitants for strong WEM-hospital admissions correlations and ∼68,000 inhabitants for WEM-laboratory-positive cases during waned vaccination periods in Ontario (the Omicron BA.1 wave). During significant vaccination immunization (the Omicron BA.2 wave), these thresholds increased to ∼187,000 and 238,000, respectively. These findings highlight the benefit of WEM for strategic public health monitoring and interventions, especially in smaller communities. This study provides insights for enhancing public health decision making and disease monitoring through WEM, applicable to COVID-19 and potentially other diseases.

Multi-scale wastewater surveillance at a Bangkok tertiary care hospital: A potential sentinel site for real-time COVID-19 surveillance at hospital and national levels

Wastewater-based epidemiology is a valuable tool for population-level pathogen surveillance, complementing clinical methods. While most sampling focuses on municipal wastewater treatment plants, emerging evidence suggests wastewater collected from hospital settings can lead to targeted clinical interventions. To investigate wastewater pathogen surveillance in hospital settings further, we tracked the presence and concentration of SARS-CoV-2 RNA in wastewater across multi-scale sample sites within a large, public tertiary care hospital in Bangkok, Thailand. From July 2022 to May 2023, weekly wastewater samples (n=392) were collected from various sample sites including clinical and non-clinical facilities, as well as the hospital's wastewater treatment plant. Influent wastewater at the hospital's wastewater treatment center yielded the most consistent SARS-CoV-2 RNA detection across all sample sites, with detection in all 26 samples. Despite varied building usage patterns, significant moderate negative correlations were found in 90% (9/10) of sample sites between wastewater RT-PCR cycle threshold values and clinical case data from hospital and national reports. Targeting specific buildings yielded distinct data trends, indicating their potential to offer complementary insights into viral shedding and transmission among clinical and non-clinical sub-populations within a hospital campus. Our findings suggest that hospital wastewater-based epidemiology reflects broader community disease trends, which may be especially useful in regions with limited municipal wastewater treatment coverage. Large tertiary care hospitals could serve as effective and cost-efficient sentinel surveillance sites for future pathogen monitoring, guiding public health actions.

Temporal dynamics of SARS-CoV-2 shedding in feces and saliva: a longitudinal study in Norfolk, United Kingdom during the 2021-2022 COVID-19 waves

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) was originally described as a respiratory illness; however, it is now known that the infection can spread to the gastrointestinal tract, leading to shedding in feces potentially being a source of infection through wastewater. We aimed to assess the prevalence and persistence of SARS-CoV-2 in fecal and saliva samples for up to 7 weeks post-detection in a cohort of 98 participants from Norfolk, United Kingdom using RT-qPCR. Secondary goals included sequencing the viral isolates present in fecal samples and comparing the genetic sequence with isolates in the saliva of the same participant. Furthermore, we sought to identify factors associated with the presence of detectable virus in feces or saliva after a positive SARS-CoV-2 test. Saliva remained SARS-CoV-2-positive for longer periods compared to fecal samples, with all positive fecal samples occurring within 4 weeks of the initial positive test. Detectable virus in fecal samples was positively associated with the number of symptoms experienced by the individuals. Based on the genome sequencing and taxonomic classification of the virus, one donor had a distinct strain in feces compared to saliva on the same collection date, which suggests that different isolates could dominate different tissues. Our results underscore the importance of considering multiple biological samples, such as feces, in the detection and characterization of SARS-CoV-2, particularly in clinical procedures involving patient fecal material transplant. Such insights could contribute to enhancing the safety protocols surrounding the handling of patient samples and aid in devising effective strategies for mitigating the spread of coronavirus disease.

IMPORTANCE

This study provides critical insights into the dynamics of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) shedding in fecal and saliva samples, demonstrating that while viral RNA is detectable shortly after diagnosis, its prevalence declines rapidly over the course of infection. Detection was more common among individuals with more concurrent symptoms, emphasizing the potential influence of symptom burden on viral persistence. By analyzing a United Kingdom-based cohort, this study fills a significant gap in the literature, which has largely focused on Asian and North American populations, offering a geographically unique perspective on viral shedding dynamics. Our findings contribute to a globally relevant understanding of SARS-CoV-2 shedding by revealing differences in shedding durations compared to studies from other regions. These differences highlight the need for geographically diverse research to account for variations in genetic background, immune response, and healthcare practices.

Wastewater-based epidemiology framework: Collaborative modeling for sustainable disease surveillance

Many wastewater-based epidemiology (WBE) programs are being implemented worldwide due to their usefulness in monitoring residents' health. Modeling wastewater dynamics in outbreak scenarios can provide important data for designing wastewater surveillance plans. For outbreak modeling to be effective, researchers must coordinate with public health authorities and laboratory services, using frameworks to ensure that their modeling and output data are relevant for informed decision-making. However, theoretical and institutional frameworks typically omit modeling, and the connection between theoretical frameworks and models is often unrecognized. A framework that surpasses theoretical conceptualization for promoting collaboration between actors by integrating modeling can achieve the required synchrony toward sustainable wastewater surveillance plans. First, we build on an existing theoretical framework to create a collaborative framework that integrates modeling and suggests stakeholder activities for designing WBE programs. Then, we demonstrate our framework for developing a WBE plan via a COVID-19 case study where we answer when, how often, and where to sample wastewater to detect and monitor an outbreak. We evaluate the results in space and time for three outbreak phases (early detection, peak, and tail). The modeling outputs indicate the need for different sampling strategies for these outbreak phases. Our results also quantify the differences in the likelihood of capturing viral events in wastewater between the sampling hours at different disease phases for COVID-19 and various spatial locations in the sewer network. This framework lays the foundation for sustainable WBE to improve the detection efficiency of wastewater surveillance plans.

Pandemic monitoring with global aircraft-based wastewater surveillance networks

Aircraft wastewater surveillance has been proposed as a new approach to monitor the global spread of pathogens. Here we develop a computational framework providing actionable information for the design and estimation of the effectiveness of global aircraft-based wastewater surveillance networks (WWSNs). We study respiratory diseases of varying transmission potential and find that networks of 10-20 strategically placed wastewater sentinel sites can provide timely situational awareness and function effectively as an early warning system. The model identifies potential blind spots and suggests optimization strategies to increase WWSN effectiveness while minimizing resource use. Our findings indicate that increasing the number of sentinel sites beyond a critical threshold does not proportionately improve WWSN capabilities, emphasizing the importance of resource optimization. We show, through retrospective analyses, that WWSNs can notably shorten detection time for emerging pathogens. The approach presented offers a realistic analytic framework for the analysis of WWSNs at airports.

The influence of environmental factors on the detection and quantification of SARS-CoV-2 variants in dormitory wastewater at a primarily undergraduate institution

Testing for the causative agent of coronavirus disease 2019 (COVID-19), severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has been crucial in tracking disease spread and informing public health decisions. Wastewater-based epidemiology has helped to alleviate some of the strain of testing through broader, population-level surveillance, and has been applied widely on college campuses. However, questions remain about the impact of various sampling methods, target types, environmental factors, and infrastructure variables on SARS-CoV-2 detection. Here, we present a data set of over 800 wastewater samples that sheds light on the influence of a variety of these factors on SARS-CoV-2 quantification using droplet digital PCR (ddPCR) from building-specific sewage infrastructure. We consistently quantified a significantly higher number of copies of virus per liter for the target nucleocapsid 2 (N2) compared to nucleocapsid 1 (N1), regardless of the sampling method (grab vs composite). We further show some dormitory-specific differences in SARS-CoV-2 abundance, including correlations to dormitory population size. Environmental variables like precipitation and temperature show little to no impact on virus load, with the exception of higher temperatures for grab sample data. We observed significantly higher gene copy numbers of the Omicron variant than the Delta variant within ductile iron pipes but no difference in nucleocapsid abundance (N1 or N2) across the three different sewage pipe types in our data set. Our results indicate that contextual variables should be considered when interpreting wastewater-based epidemiological data.

IMPORTANCE

Testing for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the causative agent of coronavirus disease 2019 (COVID-19), has been crucial in tracking the spread of the virus and informing public health decisions. SARS-CoV-2 viral RNA is shed by symptomatic and asymptomatic infected individuals, allowing its genetic material to be detected and quantified in wastewater. Here, we used wastewater-based epidemiology to measure SARS-CoV-2 viral RNA from several dormitories on the Appalachian State University campus and examined the impact of sampling methods, target types, environmental factors, and infrastructure variables on quantification. Changes in the quantification of SARS-CoV-2 were observed based on target type, as well as trends for the quantification of the Delta and Omicron variants by sampling method. These results highlight the value of applying the data-inquiry practices used in this study to better contextualize wastewater sampling results.

Assessing the effect of selective serotonin reuptake inhibitors in the prevention of post-acute sequelae of COVID-19

Background

Post-acute sequelae of COVID-19 (PASC) produce significant morbidity, prompting evaluation of interventions that might lower risk. Selective serotonin reuptake inhibitors (SSRIs) potentially could modulate risk of PASC via their central, hypothesized immunomodulatory, and/or antiplatelet properties although clinical trial data are lacking.

Materials and Methods

This retrospective study was conducted leveraging real-world clinical data within the National COVID Cohort Collaborative (N3C) to evaluate whether SSRIs with agonist activity at the sigma-1 receptor (S1R) lower the risk of PASC, since agonism at this receptor may serve as a mechanism by which SSRIs attenuate an inflammatory response. Additionally, determine whether the potential benefit could be traced to S1R agonism. Presumed PASC was defined based on a computable PASC phenotype trained on the U09.9 ICD-10 diagnosis code.

Results

Of the 17,908 patients identified, 1521 were exposed at baseline to a S1R agonist SSRI, 1803 to a non-S1R agonist SSRI, and 14,584 to neither. Using inverse probability weighting and Poisson regression, relative risk (RR) of PASC was assessed.A 29% reduction in the RR of PASC (0.704 [95% CI, 0.58-0.85]; P = 4 ×10-4) was seen among patients who received an S1R agonist SSRI compared to SSRI unexposed patients and a 21% reduction in the RR of PASC was seen among those receiving an SSRI without S1R agonist activity (0.79 [95% CI, 0.67 - 0.93]; P = 0.005).Thus, SSRIs with and without reported agonist activity at the S1R were associated with a significant decrease in the risk of PASC.

Gastrointestinal pathophysiology in long COVID: Exploring roles of microbiota dysbiosis and serotonin dysregulation in post-infectious bowel symptoms

The emergence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) triggered an unprecedented public health crisis known as the coronavirus disease 2019 (COVID-19) pandemic. Gastrointestinal (GI) symptoms develop in patients during acute infection and persist after recovery from airway distress in a chronic form of the disease (long COVID). A high incidence of irritable bowel syndrome (IBS) manifested by severe abdominal pain and defecation pattern changes is reported in COVID patients. Although COVID is primarily considered a respiratory disease, fecal shedding of SARS-CoV-2 antigens positively correlates with bowel symptoms. Active viral infection in the GI tract was identified by human intestinal organoid studies showing SARS-CoV-2 replication in gut epithelial cells. In this review, we highlight the key findings in post-COVID bowel symptoms and explore possible mechanisms underlying the pathophysiology of the illness. These mechanisms include mucosal inflammation, gut barrier dysfunction, and microbiota dysbiosis during viral infection. Viral shedding through the GI route may be the primary factor causing the alteration of the microbiome ecosystem, particularly the virome. Recent evidence in experimental models suggested that microbiome dysbiosis could be further aggravated by epithelial barrier damage and immune activation. Moreover, altered microbiota composition has been associated with dysregulated serotonin pathways, resulting in intestinal nerve hypersensitivity. These mechanisms may explain the development of post-infectious IBS-like symptoms in long COVID. Understanding how coronavirus infection affects gut pathophysiology, including microbiome changes, would benefit the therapeutic advancement for managing post-infectious bowel symptoms.

Impact of Prolonged SARS-CoV-2 Viral Shedding on COVID-19 Disease Outcome and Viral Dynamics

This article aimed to review the current literature on the impact of continuous shedding of the COVID-19 virus in infected patients in relation to disease outcome variables and viral dynamics. Electronic databases PubMed, Google Scholar, and MedlinePlus were searched using relevant keywords, restricting the selection to thirty-two peer-reviewed articles and four gray literatures from the WHO websites. Findings from this study showed that several variables such as sex, age, immune status, treatments, and vaccines were found to affect the outcomes associated with the COVID-19 virus shedding. These findings highlight the need for further research using longitudinal whole-genome sequencing of the virus and its variants to increase the understanding.

Wastewater-based genomic surveillance of SARS-CoV-2 in vulnerable communities in Mumbai

Background & objectives The global impact of COVID-19, with over 45 million cases and 533,300 deaths in India alone, necessitates effective surveillance methods. Traditional approaches face challenges in detecting pre-symptomatic and asymptomatic cases, prompting the exploration of wastewater-based epidemiology (WBE). This study focuses on Mumbai's vulnerable slums, aiming to assess the potential of WBE as an alternative surveillance method. Methods Genomic surveillance of SARS-CoV-2 was conducted in Mumbai's vulnerable settings (slums) for 11 months (August 2022 to June 2023). Wastewater samples from open drains and sewage treatment plants were correlated with reported COVID-19 cases in the city. Early detection of emerging viral variants and seasonal variations in viral load were explored. Results Correlations were identified between wastewater samples and reported COVID-19 cases in Mumbai's vulnerable slums, with early detection occurring three weeks before clinical diagnoses, underscoring the potential utility of WBE. Genomic sequencing provided insights into the viral variants, identifying shifts in predominant variants. Seasonal variations showed higher viral concentrations in summer and monsoon, potentially associated with accelerated droplet evaporation in early summer and droplet-based transmission during mid-summer and monsoon. Interpretation & conclusions Wastewater-based epidemiology emerges as a cost-effective and rapid early warning system, providing crucial insights into virus behaviour and evolution. Particularly significant for countries like India, WBE aids in outbreak monitoring and targeted interventions. The global integration of wastewater surveillance emphasizes its importance in comprehensive pandemic monitoring, establishing it as an integral component of public health strategies worldwide.

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.

Optimization and performance analytics of global aircraft-based wastewater surveillance networks

Aircraft wastewater surveillance has been proposed as a novel approach to monitor the global spread of pathogens. Here we develop a computational framework to provide actionable information for designing and estimating the effectiveness of global aircraft-based wastewater surveillance networks (WWSNs). We study respiratory diseases of varying transmission potentials and find that networks of 10 to 20 strategically placed wastewater sentinel sites can provide timely situational awareness and function effectively as an early warning system. The model identifies potential blind spots and suggests optimization strategies to increase WWSNs effectiveness while minimizing resource use. Our findings highlight that increasing the number of sentinel sites beyond a critical threshold does not proportionately improve WWSNs capabilities, stressing the importance of resource optimization. We show through retrospective analyses that WWSNs can significantly shorten the detection time for emerging pathogens. The presented approach offers a realistic analytic framework for the analysis of WWSNs at airports.

Wastewater-Based Epidemiology for SARS-CoV-2 in Northern Italy: A Spatiotemporal Model

The study investigated the application of Wastewater-Based Epidemiology (WBE) as a tool for monitoring the SARS-CoV-2 prevalence in a city in northern Italy from October 2021 to May 2023. Based on a previously used deterministic model, this study proposed a variation to account for the population characteristics and virus biodegradation in the sewer network. The model calculated virus loads and corresponding COVID-19 cases over time in different areas of the city and was validated using healthcare data while considering viral mutations, vaccinations, and testing variability. The correlation between the predicted and reported cases was high across the three waves that occurred during the period considered, demonstrating the ability of the model to predict the relevant fluctuations in the number of cases. The population characteristics did not substantially influence the predicted and reported infection rates. Conversely, biodegradation significantly reduced the virus load reaching the wastewater treatment plant, resulting in a 30% reduction in the total virus load produced in the study area. This approach can be applied to compare the virus load values across cities with different population demographics and sewer network structures, improving the comparability of the WBE data for effective surveillance and intervention strategies.

Cross-continental comparative experiences of wastewater surveillance and a vision for the 21st century

The COVID-19 pandemic has brought the epidemiological value of monitoring wastewater into sharp focus. The challenges of implementing and optimising wastewater monitoring vary significantly from one region to another, often due to the array of different wastewater systems around the globe, as well as the availability of resources to undertake the required analyses (e.g. laboratory infrastructure and expertise). Here we reflect on the local and shared challenges of implementing a SARS-CoV-2 monitoring programme in two geographically and socio-economically distinct regions, São Paulo state (Brazil) and Wales (UK), focusing on design, laboratory methods and data analysis, and identifying potential guiding principles for wastewater surveillance fit for the 21st century. Our results highlight the historical nature of region-specific challenges to the implementation of wastewater surveillance, including previous experience of using wastewater surveillance, stakeholders involved, and nature of wastewater infrastructure. Building on those challenges, we then highlight what an ideal programme would look like if restrictions such as resource were not a constraint. Finally, we demonstrate the value of bringing multidisciplinary skills and international networks together for effective wastewater surveillance.

A modeling pipeline to relate municipal wastewater surveillance and regional public health data

As COVID-19 becomes endemic, public health departments benefit from improved passive indicators, which are independent of voluntary testing data, to estimate the prevalence of COVID-19 in local communities. Quantification of SARS-CoV-2 RNA from wastewater has the potential to be a powerful passive indicator. However, connecting measured SARS-CoV-2 RNA to community prevalence is challenging due to the high noise typical of environmental samples. We have developed a generalized pipeline using in- and out-of-sample model selection to test the ability of different correction models to reduce the variance in wastewater measurements and applied it to data collected from treatment plants in the Chicago area. We built and compared a set of multi-linear regression models, which incorporate pepper mild mottle virus (PMMoV) as a population biomarker, Bovine coronavirus (BCoV) as a recovery control, and wastewater system flow rate into a corrected estimate for SARS-CoV-2 RNA concentration. For our data, models with BCoV performed better than those with PMMoV, but the pipeline should be used to reevaluate any new data set as the sources of variance may change across locations, lab methods, and disease states. Using our best-fit model, we investigated the utility of RNA measurements in wastewater as a leading indicator of COVID-19 trends. We did this in a rolling manner for corrected wastewater data and for other prevalence indicators and statistically compared the temporal relationship between new increases in the wastewater data and those in other prevalence indicators. We found that wastewater trends often lead other COVID-19 indicators in predicting new surges.

Feasibility of wastewater-based detection of emergent pandemics through a global network of airports

Wastewater-based surveillance has been put into practice during the pandemic. Persistence of SARS-CoV-2 in faeces of infected individuals, and high volume of passengers travelling by air, make it possible to detect virus from aircraft wastewater, lending itself to the potential identification of a novel pathogen prior to clinical diagnosis. In this study, we estimated the likelihood of detecting the virus through aircraft wastewater from the probabilities of air travel, viral shedding, defecation, testing sensitivity, and sampling. We considered various hypothetical scenarios, with diverse sampling proportions of inbound flights, surveillance airports, and sources of outbreaks. Our calculations showed that the probability of detecting SARS-CoV-2 would increase exponentially against time in the early phase of the pandemic, and would be much higher if the 20 major airports in Asia, Europe, and North America cooperated to perform aircraft wastewater surveillance. We also found other contributors to early detection, including high sampling proportion of inbound flight at destination airports, small population size of the epicentre relative to the travel volume, and large volume of outbound travelers to major airports around the globe. We concluded that routine aircraft wastewater monitoring could be a feasible approach for early identification and tracking of an emerging pathogen with high faecal shedding rates, particularly when implemented through a global surveillance network of major airports.

Building Environmental and Sociological Predictive Intelligence to Understand the Seasonal Threat of SARS-CoV-2 in Human Populations

Current modeling practices for environmental and sociological modulated infectious diseases remain inadequate to forecast the risk of outbreak(s) in human populations, partly due to a lack of integration of disciplinary knowledge, limited availability of disease surveillance datasets, and overreliance on compartmental epidemiological modeling methods. Harvesting data knowledge from virus transmission (aerosols) and detection (wastewater) of SARS-CoV-2, a heuristic score-based environmental predictive intelligence system was developed that calculates the risk of COVID-19 in the human population. Seasonal validation of the algorithm was uniquely associated with wastewater surveillance of the virus, providing a lead time of 7-14 days before a county-level outbreak. Using county-scale disease prevalence data from the United States, the algorithm could predict COVID-19 risk with an overall accuracy ranging between 81% and 98%. Similarly, using wastewater surveillance data from Illinois and Maryland, the SARS-CoV-2 detection rate was greater than 80% for 75% of the locations during the same time the risk was predicted to be high. Results suggest the importance of a holistic approach across disciplinary boundaries that can potentially allow anticipatory decision-making policies of saving lives and maximizing the use of available capacity and resources.

Implementing an adaptive, two-tiered SARS-CoV-2 wastewater surveillance program on a university campus using passive sampling

Building-level wastewater-based surveillance (WBS) has been increasingly applied upstream from wastewater treatment plants to conduct targeted monitoring for SARS-CoV-2. In this study, a two-tiered, trigger-based wastewater surveillance program was developed on a university campus to monitor dormitory wastewater. The objective was to determine if passive sampling with cotton gauze as a sampling medium could be used to support institution-level public health action. Two nucleocapsid gene targets (N1 and N2) of SARS-CoV-2 as well as the endogenous fecal indicator pepper mild mottle virus (PMMoV) were quantified using RT-qPCR. >500 samples were analyzed during two contrasting surveillance periods. In the Fall of 2021 community viral burden was low and a tiered sampling network was able to isolate individual clinical cases at the building-scale. In the Winter of 2022 wastewater signals were quickly elevated by the emergence of the highly transmissible SARS-CoV-2 Omicron (B.1.1.529) variant. Prevalence of SARS-CoV-2 shifted surveillance objectives from isolating cases to monitoring trends, revealing both the benefits and limitations of a tiered surveillance design under different public health situations. Normalization of SARS-CoV-2 by PMMoV was not reflective of upstream population differences, suggesting saturation of the material occurred during the exposure period. The passive sampling method detected nearly all known clinical cases and in one instance was able to identify one pre-symptomatic individual days prior to confirmation by clinical test. Comparisons between campus samplers and municipal wastewater influent suggests that the spread of COVID-19 on the campus was similar to that of the broader community. The results demonstrate that passive sampling is an effective tool that can produce semi-quantitative data capable of tracking temporal trends to guide targeted public health decision-making at an institutional level. Practitioners of WBS can utilize these results to inform surveillance program designs that prioritize efficient resource use and rapid reporting.

Making waves: The benefits and challenges of responsibly implementing wastewater-based surveillance for rural communities

The sampling and analysis of sewage for pathogens and other biomarkers offers a powerful tool for monitoring and understanding community health trends and potentially predicting disease outbreaks. Since the early months of the COVID-19 pandemic, the use of wastewater-based testing for public health surveillance has increased markedly. However, these efforts have focused on urban and peri‑urban areas. In most rural regions of the world, healthcare service access is more limited than in urban areas, and rural public health agencies typically have less disease outcome surveillance data than their urban counterparts. The potential public health benefits of wastewater-based surveillance for rural communities are therefore substantial - though so too are the methodological and ethical challenges. For many rural communities, population dynamics and insufficient, aging, and inadequately maintained wastewater collection and treatment infrastructure present obstacles to the reliable and responsible implementation of wastewater-based surveillance. Practitioner observations and research findings indicate that for many rural systems, typical implementation approaches for wastewater-based surveillance will not yield sufficiently reliable or actionable results. We discuss key challenges and potential strategies to address them. However, to support and expand the implementation of responsible, reliable, and ethical wastewater-based surveillance for rural communities, best practice guidelines and standards are needed.

End-to-end donor screening and manufacturing controls: complementary quality-based strategies to minimize patient risk for donor-derived microbiome therapeutics

Advances in microbiome therapeutics have been motivated by a deeper understanding of the role that the gastrointestinal microbiome plays in human health and disease. The FDA approval of two stool-derived live biotherapeutic products (LBPs), REBYOTA® 150 mL enema (fecal microbiota, live-jslm; formerly RBX2660) and VOWST® oral capsules (fecal microbiota spores, live-brpk; formerly SER-109), for the prevention of recurrent CDI in adults following antibiotic treatment for recurrent CDI provides promise and insights for the development of LBPs for other diseases associated with microbiome dysfunction. Donor-derived products carry risk of disease transmission that must be mitigated through a robust donor screening program and downstream manufacturing controls. Most published recommendations for donor screening practices are prescriptive and do not include a systematic, risk-based approach for donor stool-derived products. A general framework for an end-to-end donor screening program is needed using risk management strategies for donor-derived microbiome therapeutic using a matrixed approach, combining the elements of donor screening with manufacturing controls that are designed to minimize risk to patients. A donor screening paradigm that incorporates medical history, physical examination, laboratory testing, and donor sample inspection are only the first steps in reducing risk of transmission of infectious agents. Manufacturing controls are the cornerstone of risk mitigation when screening unwittingly fails. Failure Mode and Effects Analysis (FMEA) can be used as a tool to assess for residual risk that requires further donor or manufacturing controls. Together, a well-reasoned donor program and manufacturing controls are complementary strategies that must be revisited and reexamined frequently with constant vigilance to mitigate risk to patients. In the spirit of full disclosure and informed consent, physicians should discuss any limitations in the donor screening and manufacturing processes with their patients prior to treatment with microbiome-based therapeutics.

Targeted community wastewater surveillance for SARS-CoV-2 and Mpox virus during a festival mass-gathering event

Wastewater surveillance has emerged recently as a powerful approach to understanding infectious disease dynamics in densely populated zones. Wastewater surveillance, while promising as a public health tool, is often hampered by slow turn-around times, complex analytical protocols, and resource-intensive techniques. In this study, we evaluated an affinity capture method and microfluidic digital PCR as a rapid approach to quantify severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), mpox (formerly known as monkeypox) virus, and fecal indicator, pepper mild mottle virus (PMMoV) in wastewater during a mass-gathering event. Wastewater samples (n = 131) were collected from residential and commercial manholes, pump stations, and a city's wastewater treatment plant. The use of Nanotrap® Microbiome Particles and microfluidic digital PCR produced comparable results to other established methodologies, with reduced process complexity and analytical times, providing same day results for public health preparedness and response. Using indigenous SARS-CoV-2 and PMMoV in wastewater, the average viral recovery efficiency was estimated at 10.1 %. Both SARS-CoV-2 N1 and N2 genes were consistently detected throughout the sampling period, with increased RNA concentrations mainly in wastewater samples collected from commercial area after festival mass gatherings. The mpox virus was sporadically detected in wastewater samples during the surveillance period, without distinct temporal trends. SARS-CoV-2 RNA concentrations in the city's wastewater mirrored the city's COVID-19 cases, confirming the predictive properties of wastewater surveillance. Wastewater surveillance continues to be beneficial for tracking diseases that display gastrointestinal symptoms, including SARS-CoV-2, and can be a powerful tool for sentinel surveillance. However, careful site selection and a thorough understanding of community dynamics are necessary when performing targeted surveillance during temporary mass-gathering events as potential confirmation bias may occur.

Diurnal changes in pathogenic and indicator virus concentrations in wastewater

Wastewater-based epidemiology (WBE) has been commonly used for monitoring SARS-CoV-2 outbreaks. As sampling times and methods (i.e. grab vs composite) may vary, diurnal changes of viral concentrations in sewage should be better understood. In this study, we collected untreated wastewater samples hourly for 4 days at two wastewater treatment plants in Wales to establish diurnal patterns in virus concentrations and the physico-chemical properties of the water. Simultaneously, we also trialled three absorbent materials as passive samples as a simple and cost-efficient alternative for the collection of composite samples. Ninety-six percent of all liquid samples (n = 74) and 88% of the passive samplers (n = 59) were positive for SARS-CoV-2, whereas 87% and 97% of the liquid and passive samples were positive for the faecal indicator virus crAssphage, respectively. We found no significant daily variations in the concentration of the target viruses, ammonium and orthophosphate, and the pH and electrical conductivity levels were also stable. Weak positive correlations were found between some physico-chemical properties and viral concentrations. More variation was observed in samples taken from the influent stream as opposed to those taken from the influent tank. Of the absorbent materials trialled as passive samples, we found that tampons provided higher viral recoveries than electronegative filter paper and cotton gauze swabs. For all materials tested, viral recovery was dependent on the virus type. Our results indicate that grab samples may provide representative alternatives to 24-h composite samples if taken from the influent tank, hence reducing the costs of sampling for WBE programmes. Tampons are also viable alternatives for cost-efficient sampling; however, viral recovery should be optimised prior to use.

Utility of wastewater genomic surveillance compared to clinical surveillance to track the spread of the SARS-CoV-2 Omicron variant across England

The world has moved into a new stage of managing the SARS-CoV-2 pandemic with minimal restrictions and reduced testing in the population, leading to reduced genomic surveillance of virus variants in individuals. Wastewater-based epidemiology (WBE) can provide an alternative means of tracking virus variants in the population but decision-makers require confidence that it can be applied to a national scale and is comparable to individual testing data. We analysed 19,911 samples from 524 wastewater sites across England at least twice a week between November 2021 and February 2022, capturing sewage from >70% of the English population. We used amplicon-based sequencing and the phylogeny based de-mixing tool Freyja to estimate SARS-CoV-2 variant frequencies and compared these to the variant dynamics observed in individual testing data from clinical and community settings. We show that wastewater data can reconstruct the spread of the Omicron variant across England since November 2021 in close detail and aligns closely with epidemiological estimates from individual testing data. We also show the temporal and spatial spread of Omicron within London. Our wastewater data further reliably track the transition between Omicron subvariants BA1 and BA2 in February 2022 at regional and national levels. Our demonstration that WBE can track the fast-paced dynamics of SARS-CoV-2 variant frequencies at a national scale and closely match individual testing data in time shows that WBE can reliably fill the monitoring gap left by reduced individual testing in a more affordable way.

Wastewater surveillance in the COVID-19 post-emergency pandemic period: A promising approach to monitor and predict SARS-CoV-2 surges and evolution

On May 24, 2023, approximately 3.5 years into the pandemic, the World Health Organization (WHO) declared the end of the COVID-19 global health emergency. However, as there are still ∼3000 COVID-19 deaths per day in May 2023, robust surveillance systems are still warranted to return to normalcy in times of low risk and respond appropriately in times of high risk. The different phases of the pandemic have been defined by infection numbers and variants, both of which have been determined through clinical tests that are subject to many biases. Unfortunately, the end of the COVID-19 emergency threatens to exasperate these biases, thereby warranting alternative tracking methods. We hypothesized that wastewater surveillance could be used as a more accurate and comprehensive method to track SARS-CoV-2 in the post-emergency pandemic period (PEPP). SARS-CoV-2 was quantified and sequenced from wastewater between June 2022 and March 2023 to research the anticipated 2022/23 winter surge. However, in the 2022/23 winter, there was lower-than-expected SARS-CoV-2 circulation, which was hypothesized to be due to diagnostic testing biases but was confirmed by our wastewater analysis, thereby emphasizing the unpredictable nature of SARS-CoV-2 surges while also questioning its winter seasonality. Even in times of low baseline circulation, we found wastewater surveillance to be sensitive enough to detect minor changes in circulation levels ∼30-46 days prior to diagnostic tests, suggesting that wastewater surveillance may be a more appropriate early warning system to prepare for unpredictable surges in the PEPP. Furthermore, sequencing of wastewater detected variants of concern that were positively correlated with clinical samples and also provided a method to identify mutations with a high likelihood of appearing in future variants, necessary for updating vaccines and therapeutics prior to novel variant circulation. Together, these data highlight the effectiveness of wastewater surveillance in the PEPP to limit the global health burden of SARS-CoV-2 due to increases in circulation and/or viral evolution.

The Protective Effect of Virus Capsids on RNA and DNA Virus Genomes in Wastewater

Virus concentrations measured in municipal wastewater help inform both the water treatment necessary to protect human health and wastewater-based epidemiology. Wastewater measurements are typically PCR-based, and interpreting gene copy concentrations requires an understanding of the form and stability of the nucleic acids. Here, we study the persistence of model virus genomes in wastewater, the protective effects provided by the virus capsids, and the relative decay rates of the genome and infectious viruses. In benchtop batch experiments in wastewater influent at 25 °C, extraviral (+)ssRNA and dsDNA amplicons degraded by 90% within 15-19 min and 1.6-1.9 h, respectively. When encapsidated, the T90 for MS2 (+)ssRNA increased by 424× and the T90 for T4 dsDNA increased by 52×. The (+)ssRNA decay rates were similar for a range of amplicon sizes. For our model phages MS2 and T4, the nucleic acid signal in untreated wastewater disappeared shortly after the viruses lost infectivity. Combined, these results suggest that most viral genome copies measured in wastewater are encapsidated, that measured concentrations are independent of assay amplicon sizes, and that the virus genome decay rates of nonenveloped (i.e., naked) viruses are similar to inactivation rates. These findings are valuable for the interpretation of wastewater virus measurements.

The daily updated Dutch national database on COVID-19 epidemiology, vaccination and sewage surveillance

The Dutch national open database on COVID-19 has been incrementally expanded since its start on 30 April 2020 and now includes datasets on symptoms, tests performed, individual-level positive cases and deaths, cases and deaths among vulnerable populations, settings of transmission, hospital and ICU admissions, SARS-CoV-2 variants, viral loads in sewage, vaccinations and the effective reproduction number. This data is collected by municipal health services, laboratories, hospitals, sewage treatment plants, vaccination providers and citizens and is cleaned, analysed and published, mostly daily, by the National Institute for Public Health and the Environment (RIVM) in the Netherlands, using automated scripts. Because these datasets cover the key aspects of the pandemic and are available at detailed geographical level, they are essential to gain a thorough understanding of the past and current COVID-19 epidemiology in the Netherlands. Future purposes of these datasets include country-level comparative analysis on the effect of non-pharmaceutical interventions against COVID-19 in different contexts, such as different cultural values or levels of socio-economic disparity, and studies on COVID-19 and weather factors.

Capturing the SARS-CoV-2 infection pyramid within the municipality of Rotterdam using longitudinal sewage surveillance

Despite high vaccination rates in the Netherlands, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) continues to circulate. Longitudinal sewage surveillance was implemented along with the notification of cases as two parts of the surveillance pyramid to validate the use of sewage for surveillance, as an early warning tool, and to measure the effect of interventions. Sewage samples were collected from nine neighborhoods between September 2020 and November 2021. Comparative analysis and modeling were performed to understand the correlation between wastewater and case trends. Using high resolution sampling, normalization of wastewater SARS-CoV-2 concentrations, and 'normalization' of reported positive tests for testing delay and intensity, the incidence of reported positive tests could be modeled based on sewage data, and trends in both surveillance systems coincided. The high collinearity implied that high levels of viral shedding around the onset of disease largely determined SARS-CoV-2 levels in wastewater, and that the observed relationship was independent of variants of concern and vaccination levels. Sewage surveillance alongside a large-scale testing effort where 58 % of a municipality was tested, indicated a five-fold difference in the number of SARS-CoV-2-positive individuals and reported cases through standard testing. Where trends in reported positive cases were biased due to testing delay and testing behavior, wastewater surveillance can objectively display SARS-CoV-2 dynamics for both small and large locations and is sensitive enough to measure small variations in the number of infected individuals within or between neighborhoods. With the transition to a post-acute phase of the pandemic, sewage surveillance can help to keep track of re-emergence, but continued validation studies are needed to assess the predictive value of sewage surveillance with new variants. Our findings and model aid in interpreting SARS-CoV-2 surveillance data for public health decision-making and show its potential as one of the pillars of future surveillance of (re)emerging viruses.

SARS-CoV-2 in the environment: Contamination routes, detection methods, persistence and removal in wastewater treatment plants

The present study reviewed the occurrence of SARS-CoV-2 RNA and the evaluation of virus infectivity in feces and environmental matrices. The detection of SARS-CoV-2 RNA in feces and wastewater samples, reported in several studies, has generated interest and concern regarding the possible fecal-oral route of SARS-CoV-2 transmission. To date, the presence of viable SARS-CoV-2 in feces of COVID-19 infected people is not clearly confirmed although its isolation from feces of six different patients. Further, there is no documented evidence on the infectivity of SARS-CoV-2 in wastewater, sludge and environmental water samples, although the viral genome has been detected in these matrices. Decay data revealed that SARS-CoV-2 RNA persisted longer than infectious particle in all aquatic environment, indicating that genome quantification of SARS-CoV-2 does not imply the presence of infective viral particles. In addition, this review also outlined the fate of SARS-CoV-2 RNA during the different steps in the wastewater treatment plant and focusing on the virus elimination along the sludge treatment line. Studies showed complete removal of SARS-CoV-2 during the tertiary treatment. Moreover, thermophilic sludge treatments present high efficiency in SARS-CoV-2 inactivation. Further studies are required to provide more evidence with respect to the inactivation behavior of infectious SARS-CoV-2 in different environmental matrices and to examine factors affecting SARS-CoV-2 persistence.

Acute colonic pseudo-obstruction syndrome in patients with severe COVID-19 in Buenos Aires, Argentina

BACKGROUND

Several gastrointestinal complications have been reported in patients with COVID-19, including motility disorders, such as acute colonic pseudo-obstruction (ACPO). This affection is characterized by colonic distention in the absence of mechanical obstruction. ACPO in the context of severe COVID-19 may be related to neurotropism and direct damage of SARS-CoV-2 in enterocytes.

METHOD

We conducted a retrospective study of patients who were hospitalized for critical COVID-19 and developed ACPO between March 2020 and September 2021. The diagnostic criteria to define ACPO was the presence of 2 or more of the following: abdominal distension, abdominal pain, and changes in the bowel movements, associated with distension of the colon in computed tomography. Data of sex, age, past medical history, treatment, and outcomes were collected.

RESULTS

Five patients were detected. All required admission to the Intensive Care Unit. The ACPO syndrome developed with a mean of 33.8 days from the onset of symptoms. The mean duration of the ACPO syndrome was 24.6 days. The treatment included colonic decompression with placement of rectal and nasogastric tubes, endoscopy decompression in two patients, bowel rest, fluid, and electrolytes replacement. One patient died. The remaining resolved the gastrointestinal symptoms without surgery.

CONCLUSIONS

ACPO is an infrequent complication in patients with COVID-19. It occurs especially in patients with critical condition, who require prolonged stays in intensive care and multiple pharmacological treatments. It is important to recognize its presence early and thus establish an appropriate treatment, since the risk of complications is high.

Expansion of wastewater-based disease surveillance to improve health equity in California's Central Valley: sequential shifts in case-to-wastewater and hospitalization-to-wastewater ratios

Introduction

Over a third of the communities (39%) in the Central Valley of California, a richly diverse and important agricultural region, are classified as disadvantaged-with inadequate access to healthcare, lower socio-economic status, and higher exposure to air and water pollution. The majority of racial and ethnic minorities are also at higher risk of COVID-19 infection, hospitalization, and death according to the Centers for Disease Control and Prevention. Healthy Central Valley Together established a wastewater-based disease surveillance (WDS) program that aims to achieve greater health equity in the region through partnership with Central Valley communities and the Sewer Coronavirus Alert Network. WDS offers a cost-effective strategy to monitor trends in SARS-CoV-2 community infection rates.

Methods

In this study, we evaluated correlations between public health and wastewater data (represented as SARS-CoV-2 target gene copies normalized by pepper mild mottle virus target gene copies) collected for three Central Valley communities over two periods of COVID-19 infection waves between October 2021 and September 2022. Public health data included clinical case counts at county and sewershed scales as well as COVID-19 hospitalization and intensive care unit admissions. Lag-adjusted hospitalization:wastewater ratios were also evaluated as a retrospective metric of disease severity and corollary to hospitalization:case ratios.

Results

Consistent with other studies, strong correlations were found between wastewater and public health data. However, a significant reduction in case:wastewater ratios was observed for all three communities from the first to the second wave of infections, decreasing from an average of 4.7 ± 1.4 over the first infection wave to 0.8 ± 0.4 over the second.

Discussion

The decline in case:wastewater ratios was likely due to reduced clinical testing availability and test seeking behavior, highlighting how WDS can fill data gaps associated with under-reporting of cases. Overall, the hospitalization:wastewater ratios remained more stable through the two waves of infections, averaging 0.5 ± 0.3 and 0.3 ± 0.4 over the first and second waves, respectively.

Recent progress on wastewater-based epidemiology for COVID-19 surveillance: A systematic review of analytical procedures and epidemiological modeling

On March 11, 2020, the World Health Organization declared the coronavirus disease 2019 (COVID-19), whose causative agent is the Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2), a pandemic. This virus is predominantly transmitted via respiratory droplets and shed via sputum, saliva, urine, and stool. Wastewater-based epidemiology (WBE) has been able to monitor the circulation of viral pathogens in the population. This tool demands both in-lab and computational work to be meaningful for, among other purposes, the prediction of outbreaks. In this context, we present a systematic review that organizes and discusses laboratory procedures for SARS-CoV-2 RNA quantification from a wastewater matrix, along with modeling techniques applied to the development of WBE for COVID-19 surveillance. The goal of this review is to present the current panorama of WBE operational aspects as well as to identify current challenges related to it. Our review was conducted in a reproducible manner by following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines for systematic reviews. We identified a lack of standardization in wastewater analytical procedures. Regardless, the reverse transcription-quantitative polymerase chain reaction (RT-qPCR) approach was the most reported technique employed to detect and quantify viral RNA in wastewater samples. As a more convenient sample matrix, we suggest the solid portion of wastewater to be considered in future investigations due to its higher viral load compared to the liquid fraction. Regarding the epidemiological modeling, the data-driven approach was consistently used for the prediction of variables associated with outbreaks. Future efforts should also be directed toward the development of rapid, more economical, portable, and accurate detection devices.

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

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

SARS-CoV-2 Surveillance between 2020 and 2021 of All Mammalian Species in Two Flemish Zoos (Antwerp Zoo and Planckendael Zoo)

The COVID-19 pandemic has led to millions of human infections and deaths worldwide. Several other mammal species are also susceptible to SARS-CoV-2, and multiple instances of transmission from humans to pets, farmed mink, wildlife and zoo animals have been recorded. We conducted a systematic surveillance of SARS-CoV-2 in all mammal species in two zoos in Belgium between September and December 2020 and July 2021, in four sessions, and a targeted surveillance of selected mammal enclosures following SARS-CoV-2 infection in hippopotamuses in December 2021. A total of 1523 faecal samples from 103 mammal species were tested for SARS-CoV-2 via real-time PCR. None of the samples tested positive for SARS-CoV-2. Additional surrogate virus neutralisation tests conducted on 50 routinely collected serum samples from 26 mammal species were all negative. This study is the first to our knowledge to conduct active SARS-CoV-2 surveillance for several months in all mammal species of a zoo. We conclude that at the time of our investigation, none of the screened animals were excreting SARS-CoV-2.

[Evaluation of the dynamics of detection of viable SARS-CoV-2 (Coronaviridae: Betacoronavirus: Sarbecovirus) in biological samples obtained from patients with COVID-19 in a health care setting, as one of the indicators of the infectivity of the virus]

INTRODUCTION

The study of the mechanisms of transmission of the SARS-CoV-2 virus is the basis for building a strategy for anti-epidemic measures in the context of the COVID-19 pandemic. Understanding in what time frame a patient can spread SARS-CoV-2 is just as important as knowing the transmission mechanisms themselves. This information is necessary to develop effective measures to prevent infection by breaking the chains of transmission of the virus. The aim of the work is to identify the infectious SARS-CoV-2 virus in patient samples in the course of the disease and to determine the duration of virus shedding in patients with varying severity of COVID-19.

MATERIALS AND METHODS

In patients included in the study, biomaterial (nasopharyngeal swabs) was subjected to analysis by quantitative RT-PCR and virological determination of infectivity of the virus.

RESULTS

We have determined the timeframe of maintaining the infectivity of the virus in patients hospitalized with severe and moderate COVID-19. Based on the results of the study, we made an analysis of the relationship between the amount of detected SARS-CoV-2 RNA and the infectivity of the virus in vitro in patients with COVID-19. The median time of the infectious virus shedding was 8 days. In addition, a comparative analysis of different protocols for the detection of the viral RNA in relation to the identification of the infectious virus was carried out.

CONCLUSION

The obtained data make it possible to assess the dynamics of SARS-CoV-2 detection and viral load in patients with COVID-19 and indicate the significance of these parameters for the subsequent spread of the virus and the organization of preventive measures.

Intestinal barrier dysfunction as a key driver of severe COVID-19

The intestinal lumen harbors a diverse consortium of microorganisms that participate in reciprocal crosstalk with intestinal immune cells and with epithelial and endothelial cells, forming a multi-layered barrier that enables the efficient absorption of nutrients without an excessive influx of pathogens. Despite being a lung-centered disease, severe coronavirus disease 2019 (COVID-19) affects multiple systems, including the gastrointestinal tract and the pertinent gut barrier function. Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) can inflict either direct cytopathic injury to intestinal epithelial and endothelial cells or indirect immune-mediated damage. Alternatively, SARS-CoV-2 undermines the structural integrity of the barrier by modifying the expression of tight junction proteins. In addition, SARS-CoV-2 induces profound alterations to the intestinal microflora at phylogenetic and metabolomic levels (dysbiosis) that are accompanied by disruption of local immune responses. The ensuing dysregulation of the gut-lung axis impairs the ability of the respiratory immune system to elicit robust and timely responses to restrict viral infection. The intestinal vasculature is vulnerable to SARS-CoV-2-induced endothelial injury, which simultaneously triggers the activation of the innate immune and coagulation systems, a condition referred to as “immunothrombosis” that drives severe thrombotic complications. Finally, increased intestinal permeability allows an aberrant dissemination of bacteria, fungi, and endotoxin into the systemic circulation and contributes, to a certain degree, to the over-exuberant immune responses and hyper-inflammation that dictate the severe form of COVID-19. In this review, we aim to elucidate SARS-CoV-2-mediated effects on gut barrier homeostasis and their implications on the progression of the disease.

Clinical implications of gut microbiota and cytokine responses in coronavirus disease prognosis

Objectives

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infects gut luminal cells through the angiotensin-converting enzyme-2 receptor and disrupts the gut microbiome. We investigated whether the gut microbiome in the early stage of SARS-CoV-2 infection was associated with the prognosis of coronavirus disease (COVID-19).

Methods

Thirty COVID-19 patients and 16 healthy controls were prospectively enrolled. Blood and stool samples and clinical details were collected on days 0 (enrollment), 7, 14, and 28. Participants were categorized into four groups by their clinical course.

Results

Gut microbiota composition varied during the clinical course of COVID-19 and was closely associated with cytokine levels (p=0.003). A high abundance of the genus Dialister (linear discriminant analysis [LDA] effect size: 3.97856, p=0.004), species Peptoniphilus lacrimalis (LDA effect size: 4.00551, p=0.020), and Anaerococcus prevotii (LDA effect size: 4.00885, p=0.007) was associated with a good prognosis. Starch, sucrose, and galactose metabolism was highly activated in the gut microbiota of the poor prognosis group. Glucose-lowering diets, including whole grains, were positively correlated with a good prognosis.

Conclusion

Gut microbiota may mediate the prognosis of COVID-19 by regulating cytokine responses and controlling glucose metabolism, which is implicated in the host immune response to SARS-CoV-2.

Wastewater surveillance of SARS-CoV-2 and chemical markers in campus dormitories in an evolving COVID - 19 pandemic

In this study, we report the implementation of a comprehensive wastewater surveillance testing program at a university campus in Singapore to identify Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) infected individuals and the usage of pharmaceuticals and personal care products (PPCPs) as well as other emerging contaminants (ECs). This unique co-monitoring program simultaneously measured SARS-CoV-2 with chemical markers/contaminants as the COVID-19 situation evolved from pandemic to endemic stages, following a nationwide mass vaccination drive. SARS-CoV-2 RNA concentrations in wastewater from campus dormitories were measured using real-time reverse transcription-polymerase chain reaction (RT-qPCR) and corroborated with the number of symptomatic COVID-19 cases confirmed with the antigen rapid test (ART). Consistent results were observed where the concentrations of SARS-CoV-2 RNA detected in wastewater increased proportionately with the number of COVID-19 infected individuals residing on campus. Similarly, a wide range of ECs, including disinfectants and antibiotics, were detected through sensitive liquid chromatography with tandem mass spectrometry (LC-MS/MS) techniques to establish PPCPs consumption patterns during various stages of the COVID-19 pandemic in Singapore. Statistical correlation of SARS-CoV-2 RNA was observed with few ECs belonging to disinfectants, PCPs and antibiotics. A high concentration of disinfectants and subsequent positive correlation with the number of reported cases on the university campus indicates that disinfectants could serve as a chemical marker during such unprecedented times.

The effect of variation of individual infectiousness on SARS-CoV-2 transmission in households

Quantifying variation of individual infectiousness is critical to inform disease control. Previous studies reported substantial heterogeneity in transmission of many infectious diseases including SARS-CoV-2. However, those results are difficult to interpret since the number of contacts is rarely considered in such approaches. Here, we analyze data from 17 SARS-CoV-2 household transmission studies conducted in periods dominated by ancestral strains, in which the number of contacts was known. By fitting individual-based household transmission models to these data, accounting for number of contacts and baseline transmission probabilities, the pooled estimate suggests that the 20% most infectious cases have 3.1-fold (95% confidence interval: 2.2- to 4.2-fold) higher infectiousness than average cases, which is consistent with the observed heterogeneity in viral shedding. Household data can inform the estimation of transmission heterogeneity, which is important for epidemic management.

The Inhibition and Variability of Two Different RT-qPCR Assays Used for Quantifying SARS-CoV-2 RNA in Wastewater

Faecal shedding of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and its subsequent detection in wastewater turned the spotlight onto wastewater-based epidemiology (WBE) for monitoring the coronavirus-disease 2019 (COVID-19) pandemic. WBE for SARS-CoV-2 has been deployed in 70 countries, providing insights into disease prevalence, forecasting and the spatiotemporal tracking and emergence of SARS-CoV-2 variants. Wastewater, however, is a complex sample matrix containing numerous reverse transcription quantitative PCR (RT-qPCR) inhibitors whose concentration and diversity are influenced by factors including population size, surrounding industry and agriculture and climate. Such differences in the RT-qPCR inhibitor profile are likely to impact the quality of data produced by WBE and potentially produce erroneous results.To help determine the possible impact of RT-qPCR assay on data quality, two assays employed by different laboratories within the UK's SARS-CoV-2 wastewater monitoring programme were assessed in the Cefas laboratory in Weymouth, UK. The assays were based on Fast Virus (FV) and qScript (qS) chemistries using the same primers and probes, but at different concentrations and under different cycling conditions. Bovine serum albumin and MgSO4 were also added to the FV assay reaction mixture. Two-hundred and eighty-six samples were analysed, and an external control RNA (EC RNA)-based method was used to measure RT-qPCR inhibition. Compared with qS, FV showed a 40.5% reduction in mean inhibition and a 57.0% reduction in inter-sample inhibition variability. A 4.1-fold increase in SARS-CoV-2 quantification was seen for FV relative to qS; partially due (1.5-fold) to differences in reverse transcription efficiency and the use of a dsDNA standard. Analytical variability was reduced by 51.2% using FV while qS increased the number of SARS-CoV-2 negative samples by 2.6-fold. This study indicates the importance of thorough method optimisation for RT-qPCR-based WBE which should be performed using a selection of samples which are representative of the physiochemical properties of wastewater. Furthermore, RT-qPCR inhibition, analytical variability and reverse transcription efficiency should be key considerations during assay optimisation. A standardised framework for the optimisation and validation of WBE procedures should be formed including concessions for emergency response situations that would allow flexibility in the process to address the difficult balance between the urgency of providing data and the availability of resources.

Wastewater-based prediction of COVID-19 cases using a highly sensitive SARS-CoV-2 RNA detection method combined with mathematical modeling

Wastewater-based epidemiology (WBE) has the potential to predict COVID-19 cases; however, reliable methods for tracking SARS-CoV-2 RNA concentrations (CRNA) in wastewater are lacking. In the present study, we developed a highly sensitive method (EPISENS-M) employing adsorption-extraction, followed by one-step RT-Preamp and qPCR. The EPISENS-M allowed SARS-CoV-2 RNA detection from wastewater at 50 % detection rate when newly reported COVID-19 cases exceed 0.69/100,000 inhabitants in a sewer catchment. Using the EPISENS-M, a longitudinal WBE study was conducted between 28 May 2020 and 16 June 2022 in Sapporo City, Japan, revealing a strong correlation (Pearson's r = 0.94) between CRNA and the newly COVID-19 cases reported by intensive clinical surveillance. Based on this dataset, a mathematical model was developed based on viral shedding dynamics to estimate the newly reported cases using CRNA data and recent clinical data prior to sampling day. This developed model succeeded in predicting the cumulative number of newly reported cases after 5 days of sampling day within a factor of √2 and 2 with a precision of 36 % (16/44) and 64 % (28/44), respectively. By applying this model framework, another estimation mode was developed without the recent clinical data, which successfully predicted the number of COVID-19 cases for the succeeding 5 days within a factor of √2 and 2 with a precision of 39 % (17/44) and 66 % (29/44), respectively. These results demonstrated that the EPISENS-M method combined with the mathematical model can be a powerful tool for predicting COVID-19 cases, especially in the absence of intensive clinical surveillance.

Gastrointestinal Endoscopy in Patients with Coronavirus Disease 2019: Indications, Findings, and Safety

The coronavirus disease 2019 (COVID-19) pandemic has changed the practice of gastroenterology and how we perform endoscopy. As with any new or emerging pathogen, early in the pandemic, there was limited evidence and understanding of disease transmission, limited testing capability, and resource constraints, especially availability of personal protective equipment (PPE). As the COVID-19 pandemic progressed, enhanced protocols with particular emphasis on assessing the risk status of patients and proper use of PPE have been incorporated into routine patient care. The COVID-19 pandemic has taught us important lessons for the future of gastroenterology and endoscopy.

The Effect of Acotiamide on Nausea as a Symptom of Chronic Nausea and Vomiting Syndrome after Coronavirus Disease 2019

Chronic nausea and vomiting syndrome (CNVS), one of a functional gastroduodenal disorder, was identified in an 8-year-old girl and a 13-year-old boy who had complained of nausea for more than 4 months following coronavirus disease 2019 (COVID-19) due to normality of their head computed tomography and upper gastrointestinal tract images. The patients' symptoms responded quickly to acotiamide, a medication that is effective for treating functional dyspepsia (FD). Despite being a distinct illness from FD, CNVS is also a functional gastrointestinal disorder, and acotiamide may be just as effective for CNVS following COVID-19 as for FD.

A Surgical Perspective of Gastrointestinal Manifestations and Complications of COVID-19 Infection

The coronavirus disease 2019 (COVID-19), caused by the severe acute respiratory syndrome coronavirus 2, has quickly spread over the world since December 2019. COVID-19 is a systemic disease that can affect various organs throughout the body. Gastrointestinal (GI) symptoms have been reported in 16% to 33% of all patients with COVID-19 and in 75% of critically ill patients. This chapter reviews the GI manifestations of COVID-19 as well as their diagnostic and treatment modalities.

Rapid Assessment of SARS-CoV-2 Variant-Associated Mutations in Wastewater Using Real-Time RT-PCR

Within months of the COVID-19 pandemic being declared on March 20, 2020, novel, more infectious variants of SARS-CoV-2 began to be detected in geospatially distinct regions of the world. With international travel being a lead cause of spread of the disease, the importance of rapidly identifying variants entering a country is critical. In this study, we utilized wastewater-based epidemiology (WBE) to monitor the presence of variants in wastewater generated in managed COVID-19 quarantine facilities for international air passengers entering the United Kingdom. Specifically, we developed multiplex reverse transcription quantitative PCR (RT-qPCR) assays for the identification of defining mutations associated with Beta (K417N), Gamma (K417T), Delta (156/157DEL), and Kappa (E154K) variants which were globally prevalent at the time of sampling (April to July 2021). The assays sporadically detected mutations associated with the Beta, Gamma, and Kappa variants in 0.7%, 2.3%, and 0.4% of all samples, respectively. The Delta variant was identified in 13.3% of samples, with peak detection rates and concentrations observed in May 2021 (24%), concurrent with its emergence in the United Kingdom. The RT-qPCR results correlated well with those from sequencing, suggesting that PCR-based detection is a good predictor for variant presence; although, inadequate probe binding may lead to false positive or negative results. Our findings suggest that WBE coupled with RT-qPCR may be used as a rapid, initial assessment to identify emerging variants at international borders and mass quarantining facilities. IMPORTANCE With the global spread of COVID-19, it is essential to identify emerging variants which may be more harmful or able to escape vaccines rapidly. To date, the gold standard to assess variants circulating in communities has been the sequencing of the S gene or the whole genome of SARS-CoV-2; however, that approach is time-consuming and expensive. In this study, we developed two duplex RT-qPCR assays to detect and quantify defining mutations associated with the Beta, Gamma, Delta, and Kappa variants. The assays were validated using RNA extracts derived from wastewater samples taken at quarantine facilities. The results showed good correlation with the results of sequencing and demonstrated the emergence of the Delta variant in the United Kingdom in May 2021. The assays developed here enable the assessment of variant-specific mutations within 2 h after the RNA extract was generated which is essential for outbreak rapid response.

Assessing the Effect of Selective Serotonin Reuptake Inhibitors in the Prevention of Post-Acute Sequelae of COVID-19

Importance

Post-acute sequelae of COVID-19 (PASC) produce significant morbidity, prompting evaluation of interventions that might lower risk. Selective serotonin reuptake inhibitors (SSRIs) potentially could modulate risk of PASC via their central, hypothesized immunomodulatory, and/or antiplatelet properties and therefore may be postulated to be of benefit in patients with PASC, although clinical trial data are lacking.

Objectives

The main objective was to evaluate whether SSRIs with agonist activity at the sigma-1 receptor lower the risk of PASC, since agonism at this receptor may serve as a mechanism by which SSRIs attenuate an inflammatory response. A secondary objective was to determine whether potential benefit could be traced to sigma-1 agonism by evaluating the risk of PASC among recipients of SSRIs that are not S1R agonists.

Design

Retrospective study leveraging real-world clinical data within the National COVID Cohort Collaborative (N3C), a large centralized multi-institutional de-identified EHR database. Presumed PASC was defined based on a computable PASC phenotype trained on the U09.9 ICD-10 diagnosis code to more comprehensively identify patients likely to have the condition, since the ICD code has come into wide-spread use only recently.

Setting

Population-based study at US medical centers.

Participants

Adults (≥ 18 years of age) with a confirmed COVID-19 diagnosis date between October 1, 2021 and April 7, 2022 and at least one follow up visit 45 days post-diagnosis. Of the 17 933 patients identified, 2021 were exposed at baseline to a S1R agonist SSRI, 1328 to a non-S1R agonist SSRI, and 14 584 to neither.

Exposures

Exposure at baseline (at or prior to COVID-19 diagnosis) to an SSRI with documented or presumed agonist activity at the S1R (fluvoxamine, fluoxetine, escitalopram, or citalopram), an SSRI without agonist activity at S1R (sertraline, an antagonist, or paroxetine, which does not appreciably bind to the S1R), or none of these agents.

Main Outcome and Measurement

Development of PASC based on a previously validated XGBoost-trained algorithm. Using inverse probability weighting and Poisson regression, relative risk (RR) of PASC was assessed.

Results

A 26% reduction in the RR of PASC (0.74 [95% CI, 0.63-0.88]; P = 5 × 10-4) was seen among patients who received an S1R agonist SSRI compared to SSRI unexposed patients and a 25% reduction in the RR of PASC was seen among those receiving an SSRI without S1R agonist activity (0.75 [95% CI, 0.62 - 0.90]; P = 0.003) compared to SSRI unexposed patients.

Conclusions and Relevance

SSRIs with and without reported agonist activity at the S1R were associated with a significant decrease in the risk of PASC. Future prospective studies are warranted.

When case reporting becomes untenable: Can sewer networks tell us where COVID-19 transmission occurs?

Monitoring SARS-CoV-2 in wastewater is a valuable approach to track COVID-19 transmission. Designing wastewater surveillance (WWS) with representative sampling sites and quantifiable results requires knowledge of the sewerage system and virus fate and transport. We developed a multi-level WWS system to track COVID-19 in Atlanta using an adaptive nested sampling strategy. From March 2021 to April 2022, 868 wastewater samples were collected from influent lines to wastewater treatment facilities and upstream community manholes. Variations in SARS-CoV-2 concentrations in influent line samples preceded similar variations in numbers of reported COVID-19 cases in the corresponding catchment areas. Community sites under nested sampling represented mutually-exclusive catchment areas. Community sites with high SARS-CoV-2 detection rates in wastewater covered high COVID-19 incidence areas, and adaptive sampling enabled identification and tracing of COVID-19 hotspots. This study demonstrates how a well-designed WWS provides actionable information including early warning of surges in cases and identification of disease hotspots.

Early identification of a COVID-19 outbreak detected by wastewater surveillance at a large homeless shelter in Toronto, Ontario

SETTING

Toronto (Ontario, Canada) is a large urban centre with a significant population of underhoused residents and several dozen shelters for this population with known medical and social vulnerabilities. A sizeable men's homeless shelter piloted a facility-level SARS-CoV-2 wastewater surveillance program.

INTERVENTION

Wastewater surveillance was initiated at the shelter in January 2021. One-hour composite wastewater samples were collected twice weekly from a terminal sanitary clean-out pipe. The genetic material of the SARS-CoV-2 virus was extracted from the solid phase of each sample and analyzed using real-time qPCR to estimate the viral level. Wastewater results were reported to facility managers and Toronto Public Health within 4 days.

OUTCOMES

There were 169 clients on-site at the time of the investigation. Wastewater surveillance alerted to the presence of COVID-19 activity at the site, prior to clinical detection. This notification acted as an early warning signal, which allowed for timely symptom screening and case finding for shelter managers and the local health unit, in preparation for the declaration of an outbreak.

IMPLICATIONS

Wastewater surveillance acted as an advanced notification leading to the timely deployment of enhanced testing prior to clinical presentation in a population with known vulnerabilities. Wastewater surveillance at the facility level is beneficial, particularly in high-risk congregate living settings such as shelters that house transient populations where clinical testing and vaccination can be challenging. Open communication, established individual facility response plans, and a balanced threshold for action are essential to an effective wastewater surveillance program.

Wastewater-based monitoring of SARS-CoV-2 at UK airports and its potential role in international public health surveillance

It is well established that air travel plays a key role in the global spread of many enteric and respiratory diseases, including COVID-19. Even with travel restrictions (e.g. mask wearing, negative COVID-19 test prior to departure), SARS-CoV-2 may be transmitted by asymptomatic or pre-symptomatic individuals carrying the virus. Due to the limitation of current clinical surveillance approaches, complementary methods need to be developed to allow estimation of the frequency of SARS-CoV-2 entry across international borders. Wastewater-based epidemiology (WBE) represents one such approach, allowing the unbiased sampling of SARS-CoV-2 carriage by passenger cohorts entering via airports. In this study, we monitored sewage in samples from terminals (n = 150) and aircraft (n = 32) at three major international airports in the UK for 1-3 weeks in March 2022. As the raw samples were more turbid than typical municipal wastewater, we used beef extract treatment followed by polyethylene glycol (PEG) precipitation to concentrate viruses, followed by reverse transcription quantitative PCR (RT-qPCR) for the detection of SARS-CoV-2 and a faecal indicator virus, crAssphage. All samples taken from sewers at the arrival terminals of Heathrow and Bristol airports, and 85% of samples taken from sites at Edinburgh airport, were positive for SARS-CoV-2. This suggests a high COVID-19 prevalence among passengers and/or airport staff members. Samples derived from aircraft also showed 93% SARS-CoV-2 positivity. No difference in viral prevalence was found before and after COVID-19 travel restrictions were lifted. Our results suggest that WBE is a useful tool for monitoring the global transfer rate of human pathogens and other disease-causing agents across international borders and should form part of wider international efforts to monitor and contain the spread of future disease outbreaks.

Suitability of aircraft wastewater for pathogen detection and public health surveillance

International air travel is now widely recognised as one of the primary mechanisms responsible for the transnational movement and global spread of SARS-CoV-2. Monitoring the viral load and novel lineages within human-derived wastewater collected from aircraft and at air transport hubs has been proposed as an effective way to monitor the importation frequency of viral pathogens. The success of this approach, however, is highly dependent on the bathroom and defecation habits of air passengers during their journey. In this study of UK adults (n = 2103), we quantified the likelihood of defecation prior to departure, on the aircraft and upon arrival on both short- and long-haul flights. The results were then used to assess the likelihood of capturing the signal from infected individuals at UK travel hubs. To obtain a representative cross-section of the population, the survey was stratified by geographical region, gender, age, parenting status, and social class. We found that an individual's likelihood to defecate on short-haul flights (< 6 h in duration) was low (< 13 % of the total), but was higher on long-haul flights (< 36 %; > 6 h in duration). This behaviour pattern was higher among males and younger age groups. The maximum likelihood of defecation was prior to departure (< 39 %). Based on known SARS-CoV-2 faecal shedding rates (30-60 %) and an equal probability of infected individuals being on short- (71 % of inbound flights) and long-haul flights (29 %), we estimate that aircraft wastewater is likely to capture ca. 8-14 % of SARS-CoV-2 cases entering the UK. Monte Carlo simulations predicted that SARS-CoV-2 would be present in wastewater on 14 % of short-haul flights and 62 % of long-haul flights under current pandemic conditions. We conclude that aircraft wastewater alone is insufficient to effectively monitor all the transboundary entries of faecal-borne pathogens but can form part of a wider strategy for public heath surveillance at national borders.

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.