Shedding of SARS-CoV-2 in feces and urine and its potential role in person-to-person transmission and the environment-based spread of COVID-19

Application of wastewater-based epidemiology for monitoring COVID-19 in hospital and housing wastewaters

An alternative and complementary diagnostic method of surveillance is provided by wastewater-based surveillance (WBS), particularly in low-income nations like Nepal with scant wastewater treatment facilities and clinical testing infrastructure. In this study, a total of 146 water samples collected from two hospitals (n = 63) and three housing wastewaters (n = 83) from the Kathmandu Valley over the period of March 2021-Febraury 2022 were investigated for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) using quantitative reverse transcription TaqMan PCR assays targeting the N and E genes. Of the total, 67 % (98/146) samples were positive for SARS-CoV-2 RNA either by using N- or E-gene assay, with concentrations ranging from 3.6 to 9.1 log10 copies/L. There was a significant difference found between positive ratio (Chi-square test, p < 0.05) and concentration (t-test, p = 0.009) of SARS-CoV-2 RNA detected from hospital wastewater and housing waters. Wastewater data are correlated with COVID-19 active cases, indicating significance in specific areas like the Hospital (APFH) (p < 0.05). According to the application of a bivariate linear regression model (p < 0.05), the concentrations of N gene may be used to predict the COVID-19 cases in the APFH. Remarkably, SARS-CoV-2 RNA was detected prior to, during, and following clinical case surges, implying that wastewater surveillance could serve as an early warning system for public health decisions. The significance of WBS in tracking and managing pandemics is emphasized by this study, especially in resource-constrained settings.

SARS-CoV-2 in Captive Nonhuman Primates, Spain, 2020-2023

We conducted a serologic and molecular study to assess exposure of captive nonhuman primates (NHPs) to SARS-CoV-2 in Spain during the 2020-2023 COVID-19 pandemic. We found limited exposure of NHPs to SARS-CoV-2. Biosafety measures must be strictly maintained to avoid SARS-CoV-2 reverse-zoonotic transmission in the human-NHP interface.

Faecal shedding of SARS-CoV-2 from patients with asymptomatic and mild COVID-19 without gastrointestinal symptoms in Ghana

OBJECTIVE

In this study, we sought to determine whether faecal shedding occurs among SARS-COV-2 positive Ghanaians, as reported elsewhere. Hence we assayed for SARS-COV-2 in the stools of 48 SARS-COV-2 confirmed patients at the Ho Municipal Hospital in Ghana.

RESULTS

Of the 48 COVID-19 patients, 45 (93.8%) had positive tests for SARS-CoV-2 faecal shedding. About 60% reported no respiratory symptoms, while only 2% (1 patient) reported gastrointestinal (GI) symptoms in the form of nausea. Other symptoms reported included headache (57.9%), weakness (57.9%), cough (52.6%), blocked/runny nose (47.4%), fever (31.6%), sore throat (31.6%), and shortness of breath (21.1%). One person complained of nausea (5.3%) Semi-quantitative comparison of the SARS COV-2 viral loads in matched respiratory and faecal samples using the cycle threshold (CT) values revealed no statistical differences. Furthermore, the duration between collection of respiratory and faecal samples did not have any direct influence on the differences in the CT values. This suggests that treatment and use of sewage for environmental surveillance of SARS COV-2 could be a potential public health countermeasure.

Wastewater monitoring of SARS-CoV-2 gene for COVID-19 epidemiological surveillance in Tucumán, Argentina

Wastewater-based epidemiology provides temporal and spatial information about the health status of a population. The objective of this study was to analyze and report the epidemiological dynamics of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in the province of Tucumán, Argentina during the second and third waves of coronavirus disease 2019 (COVID-19) between April 2021 and March 2022. The study aimed to quantify SARS-CoV-2 RNA in wastewater, correlating it with clinically reported COVID-19 cases. Wastewater samples (n = 72) were collected from 16 sampling points located in three cities of Tucumán (San Miguel de Tucumán, Yerba Buena y Banda del Río Salí). Detection of viral nucleocapsid markers (N1 gene) was carried out using one-step reverse transcription-quantitative polymerase chain reaction (RT-qPCR). Viral loads were determined for each positive sample using a standard curve. A positive correlation (p < 0.05) was observed between viral load (copies/mL) and the clinically confirmed COVID-19 cases reported at specific sampling points in San Miguel de Tucumán (SP4, SP7, and SP8) in both months, May and June. Indeed, the high viral load concurred with the peaks of COVID-19 cases. This method allowed us to follow the behavior of SARS-CoV-2 infection during epidemic outbreaks. Thus, wastewater monitoring is a valuable epidemiological indicator that enables the anticipation of increases in COVID-19 cases and tracking the progress of the pandemic. SARS-CoV-2 genome-based surveillance should be implemented as a routine practice to prepare for any future surge in infections.

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

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

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

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

Polyethylenimine mediated recovery of SARS-CoV-2 and total viral RNA: Impact of aqueous conditions on behaviour and recovery

Wastewater-based epidemiology (WBE) is an emerging, practical surveillance tool for monitoring community levels of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2, SC2). However, a paucity of data exists regarding SARS-CoV-2 and viral biomarker behaviour in aqueous and wastewater environments. Therefore, there is a pressing need to develop efficient and robust methods that both improve method sensitivity and reduce time and cost. We present a novel method for SARS-CoV-2, Human Coronavirus 229E (229E), and Pepper Mild Mottle Virus (PMMoV) recovery utilizing surface charge-based attraction via the branched cationic polymer, polyethylenimine (PEI). Initially, dose-optimization experiments demonstrated that low concentrations of PEI (0.001% w/v) proved most effective at flocculating suspended viruses and viral material, including additional unbound SC2 viral fragments and/or RNA from raw wastewater. A design-of-experiments (DOE) approach was used to optimize virus and/or viral material aggregation behaviour and recovery across varying aqueous conditions, revealing pH as a major influence on recoverability in this system, combinatorially due to both a reduction in viral material surface charge and increased protonation of PEI-bound amine groups. Overall, this method has shown great promise in significantly improving quantitative viral recovery, providing a straightforward and effective augmentation to standard centrifugation techniques.

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.

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

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

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

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

Prevalence and duration of SARS-CoV-2 fecal shedding in breastfeeding dyads following maternal COVID-19 diagnosis

Background

There is a paucity of data on the presence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in feces of lactating women with coronavirus disease 2019 (COVID-19) and their breastfed infants as well as associations between fecal shedding and symptomatology.

Objective

We examined whether and to what extent SARS-CoV-2 is detectable in the feces of lactating women and their breastfed infants following maternal COVID-19 diagnosis.

Methods

This was a longitudinal study carried out from April 2020 to December 2021 involving 57 breastfeeding maternal-infant dyads: 33 dyads were enrolled within 7 d of maternal COVID-19 diagnosis, and 24 healthy dyads served as controls. Maternal/infant fecal samples were collected by participants, and surveys were administered via telephone over an 8-wk period. Feces were analyzed for SARS-CoV-2 RNA.

Results

Signs/symptoms related to ears, eyes, nose, and throat (EENT); general fatigue/malaise; and cardiopulmonary signs/symptoms were commonly reported among mothers with COVID-19. In infants of mothers with COVID-19, EENT, immunologic, and cardiopulmonary signs/symptoms were most common, but prevalence did not differ from that of infants of control mothers. SARS-CoV-2 RNA was detected in feces of 7 (25%) women with COVID-19 and 10 (30%) of their infants. Duration of fecal shedding ranged from 1-4 wk for both mothers and infants. SARS-CoV-2 RNA was sparsely detected in feces of healthy dyads, with only one mother's and two infants' fecal samples testing positive. There was no relationship between frequencies of maternal and infant SARS-CoV-2 fecal shedding (P=0.36), although presence of maternal or infant fever was related to increased likelihood (7-9 times greater, P≤0.04) of fecal shedding in infants of mothers with COVID-19.

Wastewater-based epidemiology for COVID-19 using dynamic artificial neural networks

Global efforts in vaccination have led to a decrease in COVID-19 mortality but a high circulation of SARS-CoV-2 is still observed in several countries, resulting in some cases of severe lockdowns. In this sense, wastewater-based epidemiology remains a powerful tool for supporting regional health administrations in assessing risk levels and acting accordingly. In this work, a dynamic artificial neural network (DANN) has been developed for predicting the number of COVID-19 hospitalized patients in hospitals in Valladolid (Spain). This model takes as inputs a wastewater epidemiology indicator for COVID-19 (concentration of RNA from SARS-CoV-2 N1 gene reported from Valladolid Wastewater Treatment Plant), vaccination coverage, and past data of hospitalizations. The model considered both the instantaneous values of these variables and their historical evolution. Two study periods were selected (from May 2021 until September 2022 and from September 2022 to July 2023). During the first period, accurate predictions of hospitalizations (with an overall range between 6 and 171) were favored by the correlation of this indicator with N1 concentrations in wastewater (r = 0.43, p < 0.05), showing accurate forecasting for 1 day ahead and 5 days ahead. The second period's retraining strategy maintained the overall accuracy of the model despite lower hospitalizations. Furthermore, risk levels were assigned to each 1 day ahead prediction during the first and second periods, showing agreement with the level measured and reported by regional health authorities in 95 % and 93 % of cases, respectively. These results evidenced the potential of this novel DANN model for predicting COVID-19 hospitalizations based on SARS-CoV-2 wastewater concentrations at a regional scale. The model architecture herein developed can support regional health authorities in COVID-19 risk management based on wastewater-based epidemiology.

Exploring the Interplay between COVID-19 and Gut Health: The Potential Role of Prebiotics and Probiotics in Immune Support

The COVID-19 pandemic has profoundly impacted global health, leading to extensive research focused on developing strategies to enhance outbreak response and mitigate the disease's severity. In the aftermath of the pandemic, attention has shifted towards understanding and addressing long-term health implications, particularly in individuals experiencing persistent symptoms, known as long COVID. Research into potential interventions to alleviate long COVID symptoms has intensified, with a focus on strategies to support immune function and mitigate inflammation. One area of interest is the gut microbiota, which plays a crucial role in regulating immune responses and maintaining overall health. Prebiotics and probiotics, known for their ability to modulate the gut microbiota, have emerged as potential therapeutic agents in bolstering immune function and reducing inflammation. This review delves into the intricate relationship between long COVID, the gut microbiota, and immune function, with a specific focus on the role of prebiotics and probiotics. We examine the immune response to long COVID, emphasizing the importance of inflammation and immune regulation in the persistence of symptoms. The potential of probiotics in modulating immune responses, including their mechanisms in combating viral infections such as COVID-19, is discussed in detail. Clinical evidence supporting the use of probiotics in managing long COVID symptoms is summarized, highlighting their role as adjunctive therapy in addressing various aspects of SARS-CoV-2 infection and its aftermath.

Real-Time On-Site Monitoring of Viruses in Wastewater Using Nanotrap® Particles and RICCA Technologies

Wastewater-based epidemiology (WBE) is an effective and efficient tool for the early detection of infectious disease outbreaks in a community. However, currently available methods are laborious, costly, and time-consuming due to the low concentration of viruses and the presence of matrix chemicals in wastewater that may interfere with molecular analyses. In the present study, we designed a highly sensitive "Quick Poop (wastewater with fecal waste) Sensor" (termed, QPsor) using a joint approach of Nanotrap microbiome particles and RICCA (RNA Isothermal Co-Assisted and Coupled Amplification). Using QPsor, the WBE study showed a strong correlation with standard PEG concentrations and the qPCR technique. Using a closed format for a paper-based lateral flow assay, we were able to demonstrate the potential of our assay as a real-time, point-of-care test by detecting the heat-inactivated SARS-CoV-2 virus in wastewater at concentrations of 100 copies/mL and within one hour. As a proof-of-concept demonstration, we analyzed the presence of viral RNA of the SARS-CoV-2 virus and PMMoV in raw wastewater samples from wastewater treatment plants on-site and within 60 min. The results show that the QPsor method can be an effective tool for disease outbreak detection by combining an AI-enabled case detection model with real-time on-site viral RNA extraction and amplification, especially in the absence of intensive clinical laboratory facilities. The lab-free, lab-quality test capabilities of QPsor for viral prevalence and transmission in the community can contribute to the efficient management of pandemic situations.

Reduction of acute respiratory infections in day-care by non-pharmaceutical interventions: a narrative review

Objective

Children who start in day-care have 2-4 times as many respiratory infections compared to children who are cared for at home, and day-care staff are among the employees with the highest absenteeism. The extensive new knowledge that has been generated in the COVID-19 era should be used in the prevention measures we prioritize. The purpose of this narrative review is to answer the questions: Which respiratory viruses are the most significant in day-care centers and similar indoor environments? What do we know about the transmission route of these viruses? What evidence is there for the effectiveness of different non-pharmaceutical prevention measures?

Design

Literature searches with different terms related to respiratory infections in humans, mitigation strategies, viral transmission mechanisms, and with special focus on day-care, kindergarten or child nurseries, were conducted in PubMed database and Web of Science. Searches with each of the main viruses in combination with transmission, infectivity, and infectious spread were conducted separately supplemented through the references of articles that were retrieved.

Results

Five viruses were found to be responsible for ≈95% of respiratory infections: rhinovirus, (RV), influenza virus (IV), respiratory syncytial virus (RSV), coronavirus (CoV), and adenovirus (AdV). Novel research, emerged during the COVID-19 pandemic, suggests that most respiratory viruses are primarily transmitted in an airborne manner carried by aerosols (microdroplets).

Conclusion

Since airborne transmission is dominant for the most common respiratory viruses, the most important preventive measures consist of better indoor air quality that reduces viral concentrations and viability by appropriate ventilation strategies. Furthermore, control of the relative humidity and temperature, which ensures optimal respiratory functionality and, together with low resident density (or mask use) and increased time outdoors, can reduce the occurrence of respiratory infections.

New prospects of environmental RNA metabarcoding research in biological diversity, ecotoxicological monitoring, and detection of COVID-19: a critical review

Ecosystems are multifaceted and complex systems and understanding their composition is crucial for the implementation of efficient conservation and management. Conventional approaches to biodiversity surveys can have limitations in detecting the complete range of species present. In contrast, the study of environmental RNA (eRNA) offers a non-invasive and comprehensive method for monitoring and evaluating biodiversity across different ecosystems. Similar to eDNA, the examination of genetic material found in environmental samples can identify and measure many species, including ones that pose challenges to traditional methods. However, eRNA is degraded quickly and therefore shows promise in detection of living organisms closer to their actual location than eDNA methods. This method provides a comprehensive perspective on the well-being of ecosystems, facilitating the development of focused conservation approaches to save at-risk species and uphold ecological equilibrium. Furthermore, eRNA has been recognized as a valuable method for the identification of COVID-19 in the environment, besides its established uses in biodiversity protection. The SARS-CoV-2 virus, which is accountable for the worldwide epidemic, releases RNA particles into the surrounding environment via human waste, providing insights into the feasibility of detecting it in wastewater and other samples taken from the environment. In this article, we critically reviewed the recent research activities that use the eRNA method, including its utilization in biodiversity conservation, ecological surveillance, and ecotoxicological monitoring as well as its innovative potential in identifying COVID-19. Through this review, the reader can understand the recent developments, prospects, and challenges of eRNA research in ecosystem management and biodiversity conservation.

Pancreatic and Hepatic Injury in COVID-19: A Worse Prognosis in NAFLD Patients?

The novel disease produced by SARS-CoV-2 mainly harms the respiratory tract, but it has shown the capacity to affect multiple organs. Epidemiologic evidence supports the relationship between Coronavirus Disease 2019 (COVID-19) and pancreatic and hepatic injury development, identified by alterations in these organ function markers. In this regard, it is important to ascertain how the current prevalence of non-alcoholic fatty liver disease (NAFLD) and non-alcoholic steatohepatitis (NASH) might affect COVID-19 evolution and complications. Although it is not clear how SARS-CoV-2 affects both the pancreas and the liver, a multiplicity of potential pathophysiological mechanisms seem to be implicated; among them, a direct viral-induced injury to the organ involving liver and pancreas ACE2 expression. Additionally, immune system dysregulation, coagulopathies, and drugs used to treat the disease could be key for developing complications associated with the patient's clinical decline. This review aims to provide an overview of the available epidemiologic evidence regarding developing liver and pancreatic alterations in patients with COVID-19, as well as the possible role that NAFLD/NASH might play in the pathophysiological mechanisms underlying some of the complications associated with COVID-19. This review employed a comprehensive search on PubMed using relevant keywords and filters. From the initial 126 articles, those aligning with the research target were selected and evaluated for their methodologies, findings, and conclusions. It sheds light on the potential pathophysiological mechanisms underlying this relationship. As a result, it emphasises the importance of monitoring pancreatic and hepatic function in individuals affected by COVID-19.

The Multisystem Impact of Long COVID: A Comprehensive Review

(1) Background: COVID-19 was responsible for the latest pandemic, shaking and reshaping healthcare systems worldwide. Its late clinical manifestations make it linger in medical memory as a debilitating illness over extended periods. (2) Methods: the recent literature was systematically analyzed to categorize and examine the symptomatology and pathophysiology of Long COVID across various bodily systems, including pulmonary, cardiovascular, gastrointestinal, neuropsychiatric, dermatological, renal, hematological, and endocrinological aspects. (3) Results: The review outlines the diverse clinical manifestations of Long COVID across multiple systems, emphasizing its complexity and challenges in diagnosis and treatment. Factors such as pre-existing conditions, initial COVID-19 severity, vaccination status, gender, and age were identified as influential in the manifestation and persistence of Long COVID symptoms. This condition is highlighted as a debilitating disease capable of enduring over an extended period and presenting new symptoms over time. (4) Conclusions: Long COVID emerges as a condition with intricate multi-systemic involvement, complicating its diagnosis and treatment. The findings underscore the necessity for a nuanced understanding of its diverse manifestations to effectively manage and address the evolving nature of this condition over time.

COVID-19 hospitalizations and deaths predicted by SARS-CoV-2 levels in Boise, Idaho wastewater

The viral load of COVID-19 in untreated wastewater from Idaho's capital city Boise, ID (Ada County) has been used to predict changes in hospital admissions (statewide in Idaho) and deaths (Ada County) using distributed fixed lag modeling and artificial neural networks (ANN). The wastewater viral counts were used to determine the lag time between peaks in wastewater viral counts and COVID-19 hospitalizations as well as deaths (14 and 23 days, respectively). Quantitative measurement of SARS-CoV-2 viral RNA counts in the untreated wastewater was determined three times a week using RT-qPCR over a span of 13 months. To mitigate the effects of PCR inhibitors in wastewater, a series of dilution tests were conducted, and the 1/4 dilution was used to generate the most successful model. Wastewater SARS-CoV-2 viral RNA counts and hospitalization from June 7, 2021 to December 29, 2021 were used as training data to predict hospitalizations; and wastewater SARS-CoV-2 viral RNA counts and deaths from June 7, 2021 to December 20, 2021 were used as training data to predict deaths. These training data were used to make predictive ANN models for future hospitalizations and deaths. To the best of our knowledge, this is the first report of prediction of deaths from COVID-19 based on wastewater SARS-CoV-2 viral RNA counts using machine learning-based multilayered ANN. The applied modeling demonstrates that wastewater surveillance data can be combined with hospitalizations and death data to generate machine learning-based ANN models that predict future COVID-19 hospital admissions and deaths, providing an early warning for medical response teams and healthcare policymakers.

Comparison of gene targets and sampling regimes for SARS-CoV-2 quantification for wastewater epidemiology in UK prisons

Prisons are high-risk settings for infectious disease transmission, due to their enclosed and semi-enclosed environments. The proximity between prisoners and staff, and the diversity of prisons reduces the effectiveness of non-pharmaceutical interventions, such as social distancing. Therefore, alternative health monitoring methods, such as wastewater-based epidemiology (WBE), are needed to track pathogens, including SARS-CoV-2. This pilot study assessed WBE to quantify SARS-CoV-2 prevalence in prison wastewater to determine its utility within a health protection system for residents. The study analysed 266 samples from six prisons in England over a 12-week period for nucleoprotein 1 (N1 gene) and envelope protein (E gene) using quantitative reverse transcriptase-polymerase chain reaction. Both gene assays successfully detected SARS-CoV-2 fragments in wastewater samples, with both genes significantly correlating with COVID-19 case numbers across the prisons (p < 0.01). However, in 25% of the SARS-positive samples, only one gene target was detected, suggesting that both genes be used to reduce false-negative results. No significant differences were observed between 14- and 2-h composite samples, although 2-h samples showed greater signal variance. Population normalisation did not improve correlations between the N1 and E genes and COVID-19 case data. Overall, WBE shows considerable promise for health protection in prison settings.

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.

Quantitatively assessing early detection strategies for mitigating COVID-19 and future pandemics

Researchers and policymakers have proposed systems to detect novel pathogens earlier than existing surveillance systems by monitoring samples from hospital patients, wastewater, and air travel, in order to mitigate future pandemics. How much benefit would such systems offer? We developed, empirically validated, and mathematically characterized a quantitative model that simulates disease spread and detection time for any given disease and detection system. We find that hospital monitoring could have detected COVID-19 in Wuhan 0.4 weeks earlier than it was actually discovered, at 2,300 cases (standard error: 76 cases) compared to 3,400 (standard error: 161 cases). Wastewater monitoring would not have accelerated COVID-19 detection in Wuhan, but provides benefit in smaller catchments and for asymptomatic or long-incubation diseases like polio or HIV/AIDS. Air travel monitoring does not accelerate outbreak detection in most scenarios we evaluated. In sum, early detection systems can substantially mitigate some future pandemics, but would not have changed the course of COVID-19.

HLA-DQ2/8 and COVID-19 in Celiac Disease: Boon or Bane

The SARS-CoV-2 pandemic continues to pose a global threat. While its virulence has subsided, it has persisted due to the continual emergence of new mutations. Although many high-risk conditions related to COVID-19 have been identified, the understanding of protective factors remains limited. Intriguingly, epidemiological evidence suggests a low incidence of COVID-19-infected CD patients. The present study explores whether their genetic background, namely, the associated HLA-DQs, offers protection against severe COVID-19 outcomes. We hypothesize that the HLA-DQ2/8 alleles may shield CD patients from SARS-CoV-2 and its subsequent effects, possibly due to memory CD4 T cells primed by previous exposure to human-associated common cold coronaviruses (CCC) and higher affinity to those allele's groove. In this context, we examined potential cross-reactivity between SARS-CoV-2 epitopes and human-associated CCC and assessed the binding affinity (BA) of these epitopes to HLA-DQ2/8. Using computational methods, we analyzed sequence similarity between SARS-CoV-2 and four distinct CCC. Of 924 unique immunodominant 15-mer epitopes with at least 67% identity, 37 exhibited significant BA to HLA-DQ2/8, suggesting a protective effect. We present various mechanisms that might explain the protective role of HLA-DQ2/8 in COVID-19-afflicted CD patients. If substantiated, these insights could enhance our understanding of the gene-environment enigma and viral-host relationship, guiding potential therapeutic innovations against the ongoing SARS-CoV-2 pandemic.

On-site airborne pathogen detection for infection risk mitigation

Human-infecting pathogens that transmit through the air pose a significant threat to public health. As a prominent instance, the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) that caused the COVID-19 pandemic has affected the world in an unprecedented manner over the past few years. Despite the dissipating pandemic gloom, the lessons we have learned in dealing with pathogen-laden aerosols should be thoroughly reviewed because the airborne transmission risk may have been grossly underestimated. From a bioanalytical chemistry perspective, on-site airborne pathogen detection can be an effective non-pharmaceutic intervention (NPI) strategy, with on-site airborne pathogen detection and early-stage infection risk evaluation reducing the spread of disease and enabling life-saving decisions to be made. In light of this, we summarize the recent advances in highly efficient pathogen-laden aerosol sampling approaches, bioanalytical sensing technologies, and the prospects for airborne pathogen exposure measurement and evidence-based transmission interventions. We also discuss open challenges facing general bioaerosols detection, such as handling complex aerosol samples, improving sensitivity for airborne pathogen quantification, and establishing a risk assessment system with high spatiotemporal resolution for mitigating airborne transmission risks. This review provides a multidisciplinary outlook for future opportunities to improve the on-site airborne pathogen detection techniques, thereby enhancing the preparedness for more on-site bioaerosols measurement scenarios, such as monitoring high-risk pathogens on airplanes, weaponized pathogen aerosols, influenza variants at the workplace, and pollutant correlated with sick building syndromes.

Estimating the prevalence of COVID-19 cases through the analysis of SARS-CoV-2 RNA copies derived from wastewater samples from North Dakota

The SARS-CoV-2 virus was first detected in December 2019, which prompted many researchers to investigate how the virus spreads. SARS-CoV-2 is mainly transmitted through respiratory droplets. Symptoms of the SARS-CoV-2 virus appear after an incubation period. Moreover, the asymptomatic infected individuals unknowingly spread the virus. Detecting infected people requires daily tests and contact tracing, which are expensive. The early detection of infectious diseases, including COVID-19, can be achieved with wastewater-based epidemiology, which is timely and cost-effective. In this study, we collected wastewater samples from wastewater treatment plants in several cities in North Dakota and then extracted viral RNA copies. We used log-RNA copies in the model to predict the number of infected cases using Quantile Regression (QR) and K-Nearest Neighbor (KNN) Regression. The model's performance was evaluated by comparing the Mean Absolute Percentage Error (MAPE). The QR model performs well in cities where the population is >10000 . In addition, the model predictions were compared with the basic Susceptible-Infected-Recovered (SIR) model which is the golden standard model for infectious diseases.

Beluga whale and bottlenose dolphin ACE2 proteins allow cell entry mediated by spike protein from three variants of SARS-CoV-2

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) viruses infect numerous non-human species. Spillover of SARS-CoV-2 into novel animal reservoirs may present a danger to host individuals of these species, particularly worrisome in populations already endangered or threatened by extinction. In addition, emergence in new reservoirs could pose spillback threats to humans, especially in the form of virus variants that further mutate when infecting other animal hosts. Previous work suggests beluga whales (Delphinapterus leucas) and bottlenose dolphins (Tursiops truncatus) may be at risk owing to their formation of social groups, contact with humans, exposure to contaminated wastewater, and structure of their angiotensin-converting enzyme 2 (ACE2) proteins, which SARS-CoV-2 uses as a cellular receptor. We examined marine-mammal susceptibility to virus infection by challenging 293T cells expressing beluga or dolphin ACE2 with pseudovirions bearing the SARS-CoV-2 spike protein. Beluga and dolphin ACE2 were sufficient to allow cell entry by an early pandemic isolate (Wuhan-Hu-1) and two evolved variants (Delta B.1.617.2 and Omicron BA.1 strains). We conclude that SARS-CoV-2 poses a potential threat to marine mammal reservoirs that should be considered in surveillance efforts.

The Performance of Diagnostic Tests for Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) in the South African Population: A Scoping Review

To determine the performance and reliability of diagnostic tests for the identification of SARS-CoV-2 infection in South Africa, we conducted a scoping review to identify published studies undertaken in the English language from March 2020 to August 2022 that evaluated the performance of antigen- and antibody-based diagnostic tests for SARS-CoV-2 in South Africa. We identified 17 relevant peer-reviewed articles; six reported on SARS-CoV-2 gene and/or antigen detection whilst 11 reported on antibody detection. Of the SARS-CoV-2 gene and/or antigen-based tests, sensitivity ranged from 40% to 100%, whilst for the antibody-based tests, sensitivity ranged from 13% to 100%. All tests evaluated were highly dependent on the stage of infection and the timing of sample collection. This scoping review demonstrated that no single SARS-CoV-2 gene and/or antigen- or antibody-based assay was sufficiently sensitive and specific simultaneously. The sensitivity of the tests was highly dependent on the timing of sample collection with respect to SARS-CoV-2 infection. In the case of SARS-CoV-2 gene and/or antigen detection, the earlier the collection of samples, the greater the sensitivity, while antibody detection tests showed better sensitivity using samples from later stages of infection.

The occurrence, ecological risk, and control of disinfection by-products from intensified wastewater disinfection during the COVID-19 pandemic

Increased disinfection of wastewater to preserve its microbiological quality during the coronavirus infectious disease-2019 (COVID-19) pandemic have inevitably led to increased production of toxic disinfection by-products (DBPs). However, there is limited information on such DBPs (i.e., trihalomethanes, haloacetic acids, nitrosamines, and haloacetonitriles). This review focused on the upsurge of chlorine-based disinfectants (such as chlorine, chloramine and chlorine dioxide) in wastewater treatment plants (WWTPs) in the global response to COVID-19. The formation and distribution of DBPs in wastewater were then analyzed to understand the impacts of these large-scale usage of disinfectants in WWTPs. In addition, potential ecological risks associated with DBPs derived from wastewater disinfection and its receiving water bodies were summarized. Finally, various approaches for mitigating DBP levels in wastewater and suggestions for further research into the environmental risks of increased wastewater disinfection were provided. Overall, this study presented a comprehensive overview of the formation, distribution, potential ecological risks, and mitigating approaches of DBPs derived from wastewater disinfection that will facilitate appropriate wastewater disinfection techniques selection, potential ecological risk assessment, and removal approaches and regulations consideration.

COVID-19 and the Liver: A Complex and Evolving Picture

Although the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) primarily attacks the respiratory system, other organs, such as the liver, are also affected. In this overview, the effects of SARS-CoV-2 infection on the liver in both healthy people and in those with pre-existing liver disease are documented; the relationship between coronavirus disease 19 (COVID-19) vaccination and liver injury is examined; the mechanism of SARS-CoV-2-associated liver injury is explored; and the long-term consequences of COVID-19 are delineated, both in people with and without pre-existing liver disease.

SARS-CoV-2 genomic surveillance in wastewater as a model for monitoring evolution of endemic viruses

As global SARS-CoV-2 burden and testing frequency have decreased, wastewater surveillance has emerged as a key tool to support clinical surveillance efforts. The aims of this study were to identify and characterize SARS-CoV-2 variants in wastewater samples collected from urban centers across South Africa. Here we show that wastewater sequencing analyses are temporally concordant with clinical genomic surveillance and reveal the presence of multiple lineages not detected by clinical surveillance. We show that wastewater genomics can support SARS-CoV-2 epidemiological investigations by reliably recovering the prevalence of local circulating variants, even when clinical samples are not available. Further, we find that analysis of mutations observed in wastewater can provide a signal of upcoming lineage transitions. Our study demonstrates the utility of wastewater genomics to monitor evolution and spread of endemic viruses.

Quantitatively assessing early detection strategies for mitigating COVID-19 and future pandemics

Researchers and policymakers have proposed systems to detect novel pathogens earlier than existing surveillance systems by monitoring samples from hospital patients, wastewater, and air travel, in order to mitigate future pandemics. How much benefit would such systems offer? We developed, empirically validated, and mathematically characterized a quantitative model that simulates disease spread and detection time for any given disease and detection system. We find that hospital monitoring could have detected COVID-19 in Wuhan 0.4 weeks earlier than it was actually discovered, at 2,300 cases (standard error: 76 cases) compared to 3,400 (standard error: 161 cases). Wastewater monitoring would not have accelerated COVID-19 detection in Wuhan, but provides benefit in smaller catchments and for asymptomatic or long-incubation diseases like polio or HIV/AIDS. Monitoring of air travel provides little benefit in most scenarios we evaluated. In sum, early detection systems can substantially mitigate some future pandemics, but would not have changed the course of COVID-19.

Seroprevalence of SARS-CoV-2 antibodies in pediatric hospital surgical unit: a lower-middle-income country perspective

BACKGROUND

The objective of our study was to measure and give insight into the seropositivity of anti-SARS-CoV-2 antibodies in the patients in our pediatric hospital surgical unit in Pakistan.

METHODS

A prospective cohort study was conducted at a tertiary care pediatric hospital surgical unit in Pakistan between 1 January 2021 and 1 June 2021 on the enrolled neonates and children aged 1 day to 13 years. All patients from three different pediatric strata [neonates (<1 month), infants (1 to 12 months) and children (>1 year)] were enrolled in the study.

RESULTS

Six-hundred patients were enrolled, and 426 patients were included in the study. Among 426 patients, 234 (54.9%) were male, and 192 (45.1%) were female. Overall only 118 (27.7%) patients developed symptoms. The other 308 (72.3%) were asymptomatic of which 28 (9.1%) had fever, 28 (9.1%) had cough, 38 (12.33%) had body aches, 292 (94.8%) had vomiting/diarrhea, and only 28 (9.1%) developed loss of smell and taste. Our results showed seropositivity of 27.7% (n = 118), while 72.3% (n = 308) had negative antibody titers.

CONCLUSION

A much higher pediatric SARS-CoV-2 burden of 27.7% was found in our pediatric surgical unit than has previously been reported in the literature of 6.8% for children in pediatric hospitals or pediatric surgical units. Contrary to reporting early in the COVID-19 pandemic, this study determined that children experience a significant burden of COVID-19 infection. Thus, children appear very important in SARS-CoV-2 pandemic, from harboring the virus and further studies need to be done to find if they are transmitting the disease silently.

[Diseases of the gastrointestinal tract in the context of COVID-19 infection: present and future challenges: A review]

A significant prevalence of gastrointestinal symptoms in SARS-CoV-2 infection is also associated with its fecal-oral transmission, which leads to a progressive increase in the number of patients with diseases of the esophagus, stomach and intestines. In addition, intestinal infections caused by SARS-CoV-2 may be one of the main causes of functional long-term stress-related gastrointestinal disorders, united in the concept of post-COVID syndrome.

COVID-19 and Gastrointestinal Tract: From Pathophysiology to Clinical Manifestations

Background: Since its first report in Wuhan, China, in December 2019, COVID-19 has become a pandemic, affecting millions of people worldwide. Although the virus primarily affects the respiratory tract, gastrointestinal symptoms are also common. The aim of this narrative review is to provide an overview of the pathophysiology and clinical manifestations of gastrointestinal COVID-19. Methods: We conducted a systematic electronic search of English literature up to January 2023 using Medline, Scopus, and the Cochrane Library, focusing on papers that analyzed the role of SARS-CoV-2 in the gastrointestinal tract. Results: Our review highlights that SARS-CoV-2 directly infects the gastrointestinal tract and can cause symptoms such as diarrhea, nausea/vomiting, abdominal pain, anorexia, loss of taste, and increased liver enzymes. These symptoms result from mucosal barrier damage, inflammation, and changes in the microbiota composition. The exact mechanism of how the virus overcomes the acid gastric environment and leads to the intestinal damage is still being studied. Conclusions: Although vaccination has increased the prevalence of less severe symptoms, the long-term interaction with SARS-CoV-2 remains a concern. Understanding the interplay between SARS-CoV-2 and the gastrointestinal tract is essential for future management of the virus.

Comparative analysis of SARS-CoV-2 detection methods using stool, blood, and nasopharyngeal swab samples

Introduction

as a public health policy, the ongoing global coronavirus disease 2019 vaccination drives require continuous tracking, tracing, and testing of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Diagnostic testing is important in virus detection and understanding its spread for timely intervention. This is especially important for low-income settings where the majority of the population remains untested. This is well supported by the fact that of about 9% of the Kenyan population had been tested for the virus.

Methods

this was a cross-sectional study conducted at the Kisumu and Siaya Referral Hospitals in Kenya. Here we report on the sensitivity and specificity of the rapid antigen detection test (Ag-RDT) of SARS-CoV-2 compared with the quantitative reverse transcriptase polymerase chain reaction (RT-qPCR) using stool and nasopharyngeal swab samples. Further, the mean Immunoglobulin M (IgM) and Immunoglobulin G (IgG) antibody levels among symptomatic and asymptomatic individuals in western Kenya were evaluated.

Results

the sensitivity and specificity of Ag-RDT were 76.3% (95% CI, 59.8-88.6%) and 96.3% (95% CI, 87.3-99.5%) with a negative and positive predictive value of 85% (95% CI, 73.8%-93.0%) and 93% (95% CI, 78.6%-99.2%) respectively. There was substantial agreement of 88% (Kappa value of 0.75, 95% CI, 0.74-0.77) between Ag-RDT and nasopharyngeal swab RT-qPCR, and between stool and nasopharyngeal swab RT-qPCR results (83.7% agreement, Kapa value 0.62, 95% CI 0.45-0.80). The mean IgM and IgG antibody response to SARS-CoV-2 were not different in asymptomatic individuals, 1.11 (95% CI, 0.78-1.44) and 0.88 (95% CI, 0.65-1.11) compared to symptomatic individuals 4.30 (95% CI 3.30-5.31) and 4.16 (95% CI 3.32 -5.00).

Conclusion

the choice of an appropriate SARS-CoV-2 diagnostic, screening, and surveillance test should be guided by the specific study needs and a rational approach for optimal results.

A comparison of sampling and testing approaches for the surveillance of SARS-CoV-2 in farmed American mink

Surveillance for SARS-CoV-2 in American mink (Neovison vison) is a global priority because outbreaks on mink farms have potential consequences for animal and public health. Surveillance programs often focus on screening natural mortalities; however, significant knowledge gaps remain regarding sampling and testing approaches. Using 76 mink from 3 naturally infected farms in British Columbia, Canada, we compared the performance of 2 reverse-transcription real-time PCR (RT-rtPCR) targets (the envelope [E] and RNA-dependent RNA polymerase [RdRp] genes) as well as serology. We also compared RT-rtPCR and sequencing results from nasopharyngeal, oropharyngeal, skin, and rectal swabs, as well as nasopharyngeal samples collected using swabs and interdental brushes. We found that infected mink were generally RT-rtPCR-positive on all samples; however, Ct values differed significantly among sample types (nasopharyngeal < oropharyngeal < skin < rectal). There was no difference in the results of nasopharyngeal samples collected using swabs or interdental brushes. For most mink (89.4%), qualitative (i.e., positive vs. negative) serology and RT-rtPCR results were concordant. However, mink were positive on RT-rtPCR and negative on serology and vice versa, and there was no significant correlation between Ct values on RT-rtPCR and percent inhibition on serology. Both the E and RdRp targets were detectable in all sample types, albeit with a small difference in Ct values. Although SARS-CoV-2 RNA can be detected in multiple sample types, passive surveillance programs in mink should focus on multiple target RT-rtPCR testing of nasopharyngeal samples in combination with serology.

Making waves: Integrating wastewater surveillance with dynamic modeling to track and predict viral outbreaks

Wastewater surveillance has proved to be a valuable tool to track the COVID-19 pandemic. However, most studies using wastewater surveillance data revolve around establishing correlations and lead time relative to reported case data. In this perspective, we advocate for the integration of wastewater surveillance data with dynamic within-host and between-host models to better understand, monitor, and predict viral disease outbreaks. Dynamic models overcome emblematic difficulties of using wastewater surveillance data such as establishing the temporal viral shedding profile. Complementarily, wastewater surveillance data bypasses the issues of time lag and underreporting in clinical case report data, thus enhancing the utility and applicability of dynamic models. The integration of wastewater surveillance data with dynamic models can enhance real-time tracking and prevalence estimation, forecast viral transmission and intervention effectiveness, and most importantly, provide a mechanistic understanding of infectious disease dynamics and the driving factors. Dynamic modeling of wastewater surveillance data will advance the development of a predictive and responsive monitoring system to improve pandemic preparedness and population health.

Porcine Epidemic Diarrhea Virus, Surrogate for Coronavirus Decay Measurement in French Coastal Waters and Contribution to Coronavirus Risk Evaluation

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in infected patients mainly displays pulmonary and oronasal tropism; however, the presence of the virus has also been demonstrated in the stools of patients and consequently in wastewater treatment plant effluents, raising the question of the potential risk of environmental contamination (such as seawater contamination) through inadequately treated wastewater spillover into surface or coastal waters even if the environmental detection of viral RNA alone does not substantiate risk of infection. Therefore, here, we decided to experimentally evaluate the persistence of the porcine epidemic diarrhea virus (PEDv), considered as a coronavirus representative model, in the coastal environment of France. Coastal seawater was collected, sterile-filtered, and inoculated with PEDv before incubation for 0 to 4 weeks at four temperatures representative of those measured along the French coasts throughout the year (4, 8, 15, and 24°C). The decay rate of PEDv was determined using mathematical modeling and was used to determine the half-life of the virus along the French coast in accordance with temperatures from 2000 to 2021. We experimentally observed an inverse correlation between seawater temperature and the persistence of infectious viruses in seawater and confirm that the risk of transmission of infectious viruses from contaminated stool in wastewater to seawater during recreational practices is very limited. The present work represents a good model to assess the persistence of coronaviruses in coastal environments and contributes to risk evaluation, not only for SARS-CoV-2 persistence, but also for other coronaviruses, specifically enteric coronaviruses from livestock. IMPORTANCE The present work addresses the question of the persistence of coronavirus in marine environments because SARS-CoV-2 is regularly detected in wastewater treatment plants, and the coastal environment, subjected to increasing anthropogenic pressure and the final receiver of surface waters and sometimes insufficiently depurated wastewater, is particularly at risk. The problem also arises in the possibility of soil contamination by CoV from animals, especially livestock, during manure application, where, by soil impregnation and runoff, these viruses can end up in seawater. Our findings are of interest to researchers and authorities seeking to monitor coronaviruses in the environment, either in tourist areas or in regions of the world where centralized systems for wastewater treatment are not implemented, and more broadly, to the scientific community involved in "One Health" approaches.

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.

Targeting a free viral fraction enhances the early alert potential of wastewater surveillance for SARS-CoV-2: a methods comparison spanning the transition between delta and omicron variants in a large urban center

Introduction

Wastewater surveillance has proven to be a valuable approach to monitoring the spread of SARS-CoV-2, the virus that causes Coronavirus disease 2019 (COVID-19). Recognizing the benefits of wastewater surveillance as a tool to support public health in tracking SARS-CoV-2 and other respiratory pathogens, numerous wastewater virus sampling and concentration methods have been tested for appropriate applications as well as their significance for actionability by public health practices.

Methods

Here, we present a 34-week long wastewater surveillance study that covers nearly 4 million residents of the Detroit (MI, United States) metropolitan area. Three primary concentration methods were compared with respect to recovery of SARS-CoV-2 from wastewater: Virus Adsorption-Elution (VIRADEL), polyethylene glycol precipitation (PEG), and polysulfone (PES) filtration. Wastewater viral concentrations were normalized using various parameters (flow rate, population, total suspended solids) to account for variations in flow. Three analytical approaches were implemented to compare wastewater viral concentrations across the three primary concentration methods to COVID-19 clinical data for both normalized and non-normalized data: Pearson and Spearman correlations, Dynamic Time Warping (DTW), and Time Lagged Cross Correlation (TLCC) and peak synchrony.

Results

It was found that VIRADEL, which captures free and suspended virus from supernatant wastewater, was a leading indicator of COVID-19 cases within the region, whereas PEG and PES filtration, which target particle-associated virus, each lagged behind the early alert potential of VIRADEL. PEG and PES methods may potentially capture previously shed and accumulated SARS-CoV-2 resuspended from sediments in the interceptors.

Discussion

These results indicate that the VIRADEL method can be used to enhance the early-warning potential of wastewater surveillance applications although drawbacks include the need to process large volumes of wastewater to concentrate sufficiently free and suspended virus for detection. While lagging the VIRADEL method for early-alert potential, both PEG and PES filtration can be used for routine COVID-19 wastewater monitoring since they allow a large number of samples to be processed concurrently while being more cost-effective and with rapid turn-around yielding results same day as collection.

Unveiling the unknown: first comprehensive assessment of the knowledge, attitudes and practices of hospital cleaning services staff regarding COVID-19 in Lebanon during the pandemic

BACKGROUND

Hospital cleaners are the unsung heroes in the fight against the COVID-19 pandemic. This study aimed to assess the knowledge, attitudes, and practices (KAP) of hospital cleaners towards COVID-19 and determine factors associated with good practices.

METHODS

A cross-sectional study was conducted in Lebanon between the 1st and 14th November 2020. Using a snowball sampling technique, data were collected through an online survey that was sent to governmental and private hospitals. The questionnaire consisted of socio-demographic characteristics and KAP of hospital cleaners towards COVID-19. Descriptive statistics and logistic regression analysis were performed.

RESULTS

A total of 453 cleaners completed the survey, of whom 54.3% were females. Most participants had a good level of COVID-19 knowledge (98%) and good preventive practices (89.7%). Regarding attitude, 90.7% had a positive attitude toward health facilities, 78.8% toward cleaning and disinfection, and 73.5% toward health authorities. Sociodemographic characteristics, including younger age, higher levels of education, working in private hospitals, and having more than 3 years of experience, were positively associated with good preventive practices. Our results also showed that participants who had good knowledge about COVID-19, COVID-19 prevention and treatment, cleaning and disinfection processes, and COVID-19 risk factors had a higher likelihood of positive preventive practices. Finally, a positive attitude toward health facilities, health authorities, and cleaning and disinfection was positively associated with good practices.

CONCLUSION

The surveyed cleaners have a high level of knowledge and expressed positive attitudes toward health facilities and health authorities, as well as good preventive practices. Understanding the determinants of cleaning performance is critical in tailoring interventions to improve hospital cleaning.

Comparison of Nanotrap® Microbiome A Particles, membrane filtration, and skim milk workflows for SARS-CoV-2 concentration in wastewater

Introduction

Severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) RNA monitoring in wastewater has become an important tool for Coronavirus Disease 2019 (COVID-19) surveillance. Grab (quantitative) and passive samples (qualitative) are two distinct wastewater sampling methods. Although many viral concentration methods such as the usage of membrane filtration and skim milk are reported, these methods generally require large volumes of wastewater, expensive lab equipment, and laborious processes.

Methods

The objectives of this study were to compare two workflows (Nanotrap^® Microbiome A Particles coupled with MagMax kit and membrane filtration workflows coupled with RNeasy kit) for SARS-CoV-2 recovery in grab samples and two workflows (Nanotrap^® Microbiome A Particles and skim milk workflows coupled with MagMax kit) for SARS-CoV-2 recovery in Moore swab samples. The Nanotrap particle workflow was initially evaluated with and without the addition of the enhancement reagent 1 (ER1) in 10 mL wastewater. RT-qPCR targeting the nucleocapsid protein was used for detecting SARS-CoV-2 RNA.

Results

Adding ER1 to wastewater prior to viral concentration significantly improved viral concentration results (P < 0.0001) in 10 mL grab and swab samples processed by automated or manual Nanotrap workflows. SARS-CoV-2 concentrations in 10 mL grab and Moore swab samples with ER1 processed by the automated workflow as a whole showed significantly higher (P < 0.001) results than 150 mL grab samples using the membrane filtration workflow and 250 mL swab samples using the skim milk workflow, respectively. Spiking known genome copies (GC) of inactivated SARS-CoV-2 into 10 mL wastewater indicated that the limit of detection of the automated Nanotrap workflow was ~11.5 GC/mL using the RT-qPCR and 115 GC/mL using the digital PCR methods.

Discussion

These results suggest that Nanotrap workflows could substitute the traditional membrane filtration and skim milk workflows for viral concentration without compromising the assay sensitivity. The manual workflow can be used in resource-limited areas, and the automated workflow is appropriate for large-scale COVID-19 wastewater-based surveillance.

Evaluating the theoretical performance of aircraft wastewater monitoring as a tool for SARS-CoV-2 surveillance

Air travel plays an important role in the cross-border spread of infectious diseases. During the SARS-CoV-2 pandemic many countries introduced strict border testing protocols to monitor the incursion of the virus. However, high implementation costs and significant inconvenience to passengers have led public health authorities to consider alternative methods of disease surveillance at borders. Aircraft wastewater monitoring has been proposed as one such alternative. In this paper we assess the theoretical limits of aircraft wastewater monitoring and compare its performance to post-arrival border screening approaches. Using an infectious disease model, we simulate an unmitigated SARS-CoV-2 epidemic originating in a seed country and spreading to the United Kingdom (UK) through daily flights. We use a probabilistic approach to estimate the time of first detection in the UK in aircraft wastewater and respiratory swab screening. Across a broad range of model parameters, our analysis indicates that the median time between the first incursion and detection in wastewater would be approximately 17 days (IQR: 7-28 days), resulting in a median of 25 cumulative cases (IQR: 6-84 cases) in the UK at the point of detection. Comparisons to respiratory swab screening suggest that aircraft wastewater monitoring is as effective as random screening of 20% of passengers at the border, using a test with 95% sensitivity. For testing regimes with sensitivity of 85% or less, the required coverage to outperform wastewater monitoring increases to 30%. Analysis of other model parameters suggests that wastewater monitoring is most effective when used on long-haul flights where probability of defecation is above 30%, and when the target pathogen has high faecal shedding rates and reasonable detectability in wastewater. These results demonstrate the potential use cases of aircraft wastewater monitoring and its utility in a wider system of public health surveillance.

Stabilization of SARS-CoV-2 RNA in wastewater via rapid RNA extraction

Wastewater-based Epidemiology (WBE) has contributed to surveillance of SARS-CoV-2 in communities across the world. Both symptomatic and asymptomatic patients with COVID-19 can shed the virus through the gastrointestinal tract, enabling the quantification of the virus in stool and ultimately in wastewater (WW). Unfortunately, instability of SARS-CoV-2 RNA in wastewater limits the utility of WBE programs, particularly in remote/rural regions where reliable cold storage and/or rapid shipping may be unavailable. This study examined whether rapid SARS-CoV-2 RNA extraction on the day of sample collection could minimize degradation. Importantly, the extraction technology used in these experiments, termed exclusion-based sample preparation (ESP), is lightweight, portable, and electricity-free, making it suitable for implementation in remote settings. We demonstrated that immediate RNA extraction followed by ambient storage significantly increased the RNA half-life compared to raw wastewater samples stored at both 4 °C or ambient temperature. Given that RNA degradation negatively impacts both the sensitivity and precision of WBE measurements, efforts must be made to mitigate degradation in order to maximize the potential impact of WBE on public health.

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.

Wastewater Genomic Surveillance Captures Early Detection of Omicron in Utah

Wastewater-based epidemiology has emerged as a powerful public health tool to trace new outbreaks, detect trends in infection, and provide an early warning of COVID-19 community spread. Here, we investigated the spread of SARS-CoV-2 infections across Utah by characterizing lineages and mutations detected in wastewater samples. We sequenced over 1,200 samples from 32 sewersheds collected between November 2021 and March 2022. Wastewater sequencing confirmed the presence of Omicron (B.1.1.529) in Utah in samples collected on November 19, 2021, up to 10 days before its corresponding detection via clinical sequencing. Analysis of diversity of SARS-CoV-2 lineages revealed Delta as the most frequently detected lineage during November 2021 (67.71%), but it started declining in December 2021 with the onset of Omicron (B.1.1529) and its sublineage BA.1 (6.79%). The proportion of Omicron increased to ~58% by January 4, 2022, and completely displaced Delta by February 7, 2022. Wastewater genomic surveillance revealed the presence of Omicron sublineage BA.3, a lineage that was not identified from Utah's clinical surveillance. Interestingly, several Omicron-defining mutations began to appear in early November 2021 and increased in prevalence across sewersheds from December to January, aligning with the surge in clinical cases. Our study highlights the importance of tracking epidemiologically relevant mutations in detecting emerging lineages in the early stages of an outbreak. Wastewater genomic epidemiology provides an unbiased representation of community-wide infection dynamics and is an excellent complementary tool to SARS-CoV-2 clinical surveillance, with the potential of guiding public health action and policy decisions. IMPORTANCE SARS-CoV-2, the virus responsible for the COVID-19 pandemic, has had a significant impact on public health. Global emergence of novel SARS-CoV-2 variants, shift to at-home tests, and reduction in clinical tests demonstrate the need for a reliable and effective surveillance strategy to contain COVID-19 spread. Monitoring of SARS-CoV-2 viruses in wastewater is an effective way to trace new outbreaks, establish baseline levels of infection, and complement clinical surveillance efforts. Wastewater genomic surveillance, in particular, can provide valuable insights into the evolution and spread of SARS-CoV-2 variants. We characterized the diversity of SARS-CoV-2 mutations and lineages using whole-genome sequencing to trace the introduction of lineage B.1.1.519 (Omicron) in Utah. Our data showed that Omicron appeared in Utah on November 19, 2021, up to 10 days prior to its detection in patient samples, indicating that wastewater surveillance provides an early warning signal. Our findings are important from a public health perspective as timely identification of communities with high COVID-19 transmission could help guide public health interventions.

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

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

Co-incidence of BA.1 and BA.2 at the start of Singapore's Omicron wave revealed by Community and University Campus wastewater surveillance

Wastewater surveillance (WWS) has been globally recognised to be a useful tool in quantifying SARS-CoV-2 RNA at the community and residential levels without biases associated with case-reporting. The emergence of variants of concern (VOCs) have given rise to an unprecedented number of infections even though populations are increasingly vaccinated. This is because VOCs have been reported to possess higher transmissibility and can evade host immune responses. The B.1.1.529 lineage (Omicron) has severely disrupted global plans to return to normalcy. In this study, we developed an allele-specific (AS) RT-qPCR assay which simultaneously targets the stretch of deletions and mutations in the spike protein from position 24-27 for quantitative detection of Omicron BA.2. Together with previous assays that detect mutations associated with Omicron BA.1 (deletion at position 69 and 70) and all Omicron (mutation at position 493 and 498), we report the validation and time series of these assays from September 2021 to May 2022 using influent samples from two wastewater treatment plants and across four University campus sites in Singapore. Viral RNA concentrations at the treatment plants corroborate with locally reported clinical cases, AS RT-qPCR assays revealed co-incidence of Omicron BA.1 and BA.2 on 12 January 2022, almost two months after initial BA.1 detection in South Africa and Botswana. BA.2 became the dominant variant by the end of January 2022 and completely displaced BA.1 by mid-March 2022. University campus sites were similarly positive for BA.1 and/or BA.2 in the same week as first detection at the treatment plants, where BA.2 became rapidly established as the dominant lineage within three weeks. These results corroborate clinical incidence of the Omicron lineages in Singapore and indicate minimal silent circulation prior to January 2022. The subsequent simultaneous spread of both variant lineages followed strategic relaxation of safe management measures upon meeting nationwide vaccination goals.

20-Month monitoring of SARS-CoV-2 in wastewater of Curitiba, in Southern Brazil

The COVID-19 pandemic resulted in the collapse of healthcare systems and led to the development and application of several approaches of wastewater-based epidemiology to monitor infected populations. The main objective of this study was to carry out a SARS-CoV-2 wastewater based surveillance in Curitiba, Southern Brazil Sewage samples were collected weekly for 20 months at the entrance of five treatment plants representing the entire city and quantified by qPCR using the N1 marker. The viral loads were correlated with epidemiological data. The correlation by sampling points showed that the relationship between the viral loads and the number of reported cases was best described by a cross-correlation function, indicating a lag between 7 and 14 days amidst the variables, whereas the data for the entire city presented a higher correlation (0.84) with the number of positive tests at lag 0 (sampling day). The results also suggest that the Omicron VOC resulted in higher titers than the Delta VOC. Overall, our results showed that the approach used was robust as an early warning system, even with the use of different epidemiological indicators or changes in the virus variants in circulation. Therefore, it can contribute to public decision-makers and health interventions, especially in vulnerable and low-income regions with limited clinical testing capacity. Looking toward the future, this approach will contribute to a new look at environmental sanitation and should even induce an increase in sewage coverage rates in emerging countries.