Detection of Novel Coronavirus by RT-PCR in Stool Specimen from Asymptomatic Child, China

Evaluation of wastewater percent positive for assessing epidemic trends - A case study of COVID-19 in Shangrao, China

Objective

This study aims to assess the feasibility of evaluating the COVID-19 epidemic trend through monitoring the positive percentage of SARS-CoV-19 RNA in wastewater.

Method

The study collected data from January to August 2023, including the number of reported cases, the positive ratio of nucleic acid samples in sentinel hospitals, the incidence rate of influenza-like symptoms in students, and the positive ratio of wastewater samples in different counties and districts in Shangrao City. Wastewater samples were obtained through grabbing and laboratory testing was completed within 24 h. The data were then normalized using Z-score normalization and analyzed for lag time and correlation using the xcorr function and Spearman correlation coefficient.

Results

A total of 2797 wastewater samples were collected. The wastewater monitoring study, based on sampling point distribution, was divided into two phases. Wuyuan County consistently showed high levels of positive ratio in wastewater samples in both phases, reaching peak values of 91.67% and 100% respectively. The lag time analysis results indicated that the peak positive ratio in all wastewater samples in Shangrao City appeared around 2 weeks later compared to the other three indicators. The correlation analysis revealed a strong linear correlation across all four types of data, with Spearman correlation coefficients ranging from 0.783 to 0.977, all of which were statistically significant.

Conclusion

The positive ratio of all wastewater samples in Shangrao City accurately reflected the COVID-19 epidemic trend from January to August 2023. This study confirmed the lag effect of wastewater percent positive and its strong correlation with the reported incidence rate and the positive ratio of nucleic acid samples in sentinel hospitals, supporting the use of wastewater percent positive monitoring as a supplementary tool for infectious disease surveillance in the regions with limited resources.

Epidemiological monitoring of sewage sludge and wastewater from an upflow anaerobic sludge blanket reactor using SARS-CoV-2 as a model

This study explores the potential of sludge-based monitoring from an upflow anaerobic sludge blanket reactor for epidemiological surveillance, using SARS-CoV-2 as a model. We monitored SARS-CoV-2 copy numbers and mutations, and compared concentrations in sludge to concentrations in wastewater samples taken on the same days. From January to August 2021, 32 sludge samples were analyzed; 30 (93%) were positive for SARS-CoV-2, and copy numbers varied from 0.147 to 2.314 copies ×106/L. In wastewater samples collected on the same days, 31 (96%) were positive for SARS-CoV-2, and copy numbers ranged from 0.058 to 3.014 copies ×106/L. The concentration of SARS-CoV-2 in the sludge rose along with confirmed hospitalization cases in March, while wastewater SARS-CoV-2 concentrations rose 2 weeks earlier along with numbers of new confirmed cases. Mutations of variants of concern, Gamma and Delta, were identified in sludge samples in the same months that they became dominant in the corresponding regions. Our results indicate that, although monitoring of sewage sludge was not effective in anticipating infection numbers, it is a promising way to gain insight into the epidemiological situation in a city or region.

Cryptic transmission of a SARS-CoV-2 variant detected by wastewater surveillance in Panama

The COVID-19 pandemic highlighted the critical role of viral genomic surveillance, prompting numerous countries to enhance their monitoring systems for acute respiratory infections (ARIs), especially influenza-like illnesses (ILIs). Given the significance of asymptomatic cases in severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) transmission, cases often undetected by the ILI surveillance, a more comprehensive approach was essential to track the circulation of SARS-CoV-2 variants in the population. In response, many countries swiftly adopted wastewater surveillance, which allowed the early detection of SARS-CoV-2 variants before they were identified through molecular characterization from confirmed clinical cases. In this report, we detail the implementation of SARS-CoV-2 wastewater genomic surveillance in Panama during the first half of 2024. Wastewater samples were collected monthly in duplicate at two collection points from three districts of Panama city metropolitan area for testing by SARS-CoV-2 RT-qPCR, and positive samples were analyzed by next-generation sequencing to identify sublineages. A total of 36 wastewater samples and 822 samples obtained through the clinical surveillance were analyzed for molecular detection and sequencing. Sublineages detected by wastewater surveillance were compared to those detected by clinical surveillance for the same period of time. Wastewater surveillance allowed the identification of the Omicron sublineage JN.1.16.1 in the capital city and its surroundings, which was not detected by the clinical surveillance in the country, despite its global circulation. This highlights the critical need to sustain both genomic surveillance programs beyond the pandemic in countries like Panama that serve as pivotal exchange hubs.

Schools and Wastewater Surveillance: Practical Implications for an Emerging Technology to Impact Child Health

Since the start of the COVID-19 pandemic, wastewater surveillance has emerged as a public health tool that supplements traditional surveillance methods used to detect the prevalence of the SARS-CoV-2 virus in communities. In May 2020, the Houston Health Department (HHD) partnered with a coalition of municipal and academic partners to develop a wastewater monitoring and reporting system for the city of Houston, Texas. The HHD subsequently launched a program to conduct targeted wastewater sampling at 52 school sites located in a large, urban school district in Houston. Data generated by this program are shared with school district officials and nurses from participating schools. Although initial feedback from these stakeholders indicated that they considered the wastewater data valuable, the emergency nature of the pandemic prevented a systematic evaluation of the program. To address this gap in knowledge, the HHD and Rice University conducted a study to determine how wastewater data are used to make decisions about COVID-19 prevention and mitigation practices in schools. Our findings indicate that maximizing the utility of wastewater data in the school context will require the development of communication strategies and education efforts tailored to the needs of specific audiences and improving collaboration between local health departments, school districts, and school nurses.

Effect of COVID-19 on the Gut Microbiota of Pregnant Women (review)

The Novel coronavirus infection (COVID-19) pandemic has shown that pregnant women are at risk for infection and severe COVID- 19. Pregnant women often experience gastrointestinal symptoms both during the peak of the disease and within 90 days after recovery. This review is devoted to the study of the effect of the SARS-CoV-2 virus on the gut microbiota of pregnant women. Since many studies confirm changes in the composition of the gut microbiota in COVID-19, the dependence of the severity of the course of infection on the composition of the gut microbiota, and the persistence of the virus in the gut after recovery. The question remains whether the composition of the intestinal microbiota changes in pregnant women and newborns during COVID-19, and whether it is possible to correct the state of intestinal dysbiosis during COVID-19 with probiotics for the purpose of prevention and treatment of pregnant women and newborns.

Adjusting for dilution in wastewater using biomarkers: A practical approach

We developed a biomarker-based approach to quantify in-sewer dilution by measuring wastewater quality parameters (ammoniacal-N, orthophosphate, crAssphage). This approach can enhance the environmental management of wastewater treatment works (WWTW) by optimising their operation and providing cost-effective information on the health and behaviour of populations and their interactions with the environment through wastewater-based epidemiology (WBE). Our method relies on site specific baselines calculated for each biomarker. These baselines reflect the sewer conditions without the influence of rainfall-derived inflow and infiltration (RDII). Ammoniacal-N was the best candidate to use as proxy for dilution. We demonstrated that the dilution calculated using biomarkers correlates well with the dilution indicated by measured flow. In some instances, the biomarkers showed much higher dilution than measured flows. These differences were attributed to the loss of flow volume at wastewater treatment works due to the activation of combined sewer overflows (CSOs) and/or storm tanks. Using flow measured directly at the WWTW could therefore result in underestimation of target analyte loads.

SARS-CoV-2 RNA Detection in Wastewater and Its Effective Correlation with Clinical Data during the Outbreak of COVID-19 in Salamanca

Wastewater treatment plants (WWTPs) are the final stage of the anthropogenic water cycle where a wide range of chemical and biological markers of human activity can be found. In COVID-19 disease contexts, wastewater surveillance has been used to infer community trends based on viral abundance and SARS-CoV-2 RNA variant composition, which has served to anticipate and establish appropriate protocols to prevent potential viral outbreaks. Numerous studies worldwide have provided reliable and robust tools to detect and quantify SARS-CoV-2 RNA in wastewater, although due to the high dilution and degradation rate of the viral RNA in such samples, the detection limit of the pathogen has been a bottleneck for the proposed protocols so far. The current work provides a comprehensive and systematic study of the different parameters that may affect the detection of SARS-CoV-2 RNA in wastewater and hinder its quantification. The results obtained using synthetic viral RNA as a template allow us to consider that 10 genome copies per µL is the minimum RNA concentration that provides reliable and consistent values for the quantification of SARS-CoV-2 RNA. RT-qPCR analysis of wastewater samples collected at the WWTP in Salamanca (western Spain) and at six pumping stations in the city showed that below this threshold, positive results must be confirmed by sequencing to identify the specific viral sequence. This allowed us to find correlations between the SARS-CoV-2 RNA levels found in wastewater and the COVID-19 clinical data reported by health authorities. The close match between environmental and clinical data from the Salamanca case study has been confirmed by similar experimental approaches in four other cities in the same region. The present methodological approach reinforces the usefulness of wastewater-based epidemiology (WBE) studies in the face of future pandemic outbreaks.

Tracking SARS-CoV-2 variants of concern in wastewater: an assessment of nine computational tools using simulated genomic data

Wastewater-based surveillance (WBS) is an important epidemiological and public health tool for tracking pathogens across the scale of a building, neighbourhood, city, or region. WBS gained widespread adoption globally during the SARS-CoV-2 pandemic for estimating community infection levels by qPCR. Sequencing pathogen genes or genomes from wastewater adds information about pathogen genetic diversity, which can be used to identify viral lineages (including variants of concern) that are circulating in a local population. Capturing the genetic diversity by WBS sequencing is not trivial, as wastewater samples often contain a diverse mixture of viral lineages with real mutations and sequencing errors, which must be deconvoluted computationally from short sequencing reads. In this study we assess nine different computational tools that have recently been developed to address this challenge. We simulated 100 wastewater sequence samples consisting of SARS-CoV-2 BA.1, BA.2, and Delta lineages, in various mixtures, as well as a Delta-Omicron recombinant and a synthetic 'novel' lineage. Most tools performed well in identifying the true lineages present and estimating their relative abundances and were generally robust to variation in sequencing depth and read length. While many tools identified lineages present down to 1 % frequency, results were more reliable above a 5 % threshold. The presence of an unknown synthetic lineage, which represents an unclassified SARS-CoV-2 lineage, increases the error in relative abundance estimates of other lineages, but the magnitude of this effect was small for most tools. The tools also varied in how they labelled novel synthetic lineages and recombinants. While our simulated dataset represents just one of many possible use cases for these methods, we hope it helps users understand potential sources of error or bias in wastewater sequencing analysis and to appreciate the commonalities and differences across methods.

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.

Simultaneous detection of human norovirus GI, GII and SARS-CoV-2 by a quantitative one-step triplex RT-qPCR

Background

There are many similarities in the clinical manifestations of human norovirus and SARS-CoV-2 infections, and nucleic acid detection is the gold standard for diagnosing both diseases. In order to expedite the identification of norovirus and SARS-CoV-2, a quantitative one-step triplex reverse transcription PCR (RT-qPCR) method was designed in this paper.

Methods

A one-step triplex RT-qPCR assay was developed for simultaneous detection and differentiation of human norovirus GI (NoV-GI), GII (NoV-GII) and SARS-CoV-2 from fecal specimens.

Results

The triplex RT-qPCR assay had high detection reproducibility (CV < 1%) and sensitivity. The lower limits of detection (LLOD95) of the triplex RT-qPCR assay for each target site were 128.5-172.8 copies/mL, and LLOD95 of the singleplex RT-qPCR assay were 110.3-142.0 copies/mL. Meanwhile, among the detection of clinical oropharyngeal swabs and fecal specimens, the results of the singleplex and triplex RT-qPCR assay showed high agreement.

Conclusion

The triplex RT-qPCR assay for simultaneous detection of NoV-GI, NoV-GII and SARS-CoV-2 from fecal specimens has high clinical application value.

One-step and Rapid Identification of SARS-CoV-2 using Real-Time Reverse Transcription Loop-Mediated Isothermal Amplification (RT-LAMP)

Background

SARS-CoV-2 as the cause of novel coronavirus disease (COVID-19) is a member of the family Coronaviridea that has generated an emerging global health concern. Controlling and preventing the spread of the disease requires a simple, portable, and rapid diagnostic method. Today, a standard method for detecting SARS-CoV-2 is quantitative real-time reverse transcription PCR, which is time-consuming and needs an advanced device. The aim of this study was to evaluate a faster and more cost-effective field-based testing method at the point of risk. We utilized a one-step RT-LAMP assay and developed, for the first time, a simple and rapid screening detection assay targeting the Envelope (E) gene, using specific primers.

Methods

For this, the total RNA was extracted from respiratory samples of COVID-19 infected patients and applied to one-step a RT-LAMP reaction. The LAMP products were visualized using green fluorescence (SYBR Green I). Sensitivity testing was conducted using different concentrations of the designed recombinant plasmid (TA-E) as positive control constructs. Additionally, selectivity testing was performed using the influenza H1N1 genome. Finally, the results were compared using with conventional real time RT-PCR.

Results

It was shown that the RT-LAMP assay has a sensitivity of approximately 15 ng for the E gene of SARS-CoV-2 when using extracted total RNA. Additionally, a sensitivity of 112 pg was achieved when using an artificially prepared TA-E plasmid. Accordingly, for the detection of SARS-CoV-2 infection, the RT-LAMP had high sensitivity and specificity and also could be an alternative method for real-time RT-PCR.

Conclusion

Overall, this method can be used as a portable, rapid, and easy method for detecting SARS-CoV-2 in the field and clinical laboratories.

Surveillance of SARS-CoV-2, rotavirus, norovirus genogroup II, and human adenovirus in wastewater as an epidemiological tool to anticipate outbreaks of COVID-19 and acute gastroenteritis in a city without a wastewater treatment plant in the Peruvian Highlands

The coronavirus disease 2019 (COVID-19) pandemic has demonstrated that Wastewater Based Epidemiology is a fast and economical alternative for monitoring severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) at the community level in high-income countries. In the present study, wastewater from a city in the Peruvian Highlands, which lacks a wastewater treatment plant, was monitored for one year to assess the relationship between the concentration of SARS-CoV-2 and the reported cases of COVID-19 in the community. Additionally, we compared the relationship between rotavirus (RV), norovirus genogroup II (NoV GGII), and human adenovirus (HAdV) with the number of reported cases of acute gastroenteritis. Before commencing the analysis of the samples, the viral recovery efficacy of three processing methods was determined in spiked wastewater with SARS-CoV-2. This evaluation demonstrated the highest recovery rate with direct analysis (72.2 %), as compared to ultrafiltration (50.8 %) and skimmed milk flocculation (5.6 %). Wastewater monitoring revealed that 72 % (36/50) of the samples tested positive for SARS-CoV-2, with direct analysis yielding the highest detection frequency and quantification of SARS-CoV-2. Furthermore, a strong correlation was observed between the concentration of SARS-CoV-2 in wastewater and the reported cases of COVID-19, mainly when we shift the concentration of SARS-CoV-2 by two weeks, which allows us to anticipate the onset of the fourth and fifth waves of the pandemic in Peru up to two weeks in advance. All samples processed using the skimmed milk flocculation method tested positive and showed high concentrations of RV, NoV GGII, and HAdV. In fact, the highest RV concentrations were detected up to four weeks before outbreaks of acute gastroenteritis reported in children under four years of age. In conclusion, the results of this study suggest that periodic wastewater monitoring is an excellent epidemiological tool for surveillance and can anticipate outbreaks of infectious diseases, such as COVID-19, in low- and middle-income countries.

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

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

Exploring the binding capacity of lactic acid bacteria derived bacteriocins against RBD of SARS-CoV-2 Omicron variant by molecular simulations

The changes in the SARS-CoV-2 genome have resulted in the emergence of new variants. Some of the variants have been classified as variants of concern (VOC). These strains have higher transmission rate and improved fitness. One of the prevalent were the Omicron variant. Unlike previous VOCs, the Omicron possesses fifteen mutations on the spike protein's receptor binding domain (RBD). The modifications of spike protein's key amino acid residues facilitate the virus' binding capability against ACE2, resulting in an increase in the infectiousness of Omicron variant. Consequently, investigating the prevention and treatment of the Omicron variant is crucial. In the present study, we aim to explore the binding capacity of twenty-two bacteriocins derived from Lactic Acid Bacteria (LAB) against the Omicron variant by using protein-peptidedocking and molecular dynamics (MD) simulations. The Omicron variant RBD was prepared by introducing fifteen mutations using PyMol. The protein-peptide complexes were obtained using HADDOCK v2.4 docking webserver. Top scoring complexes obtained from HADDOCK webserver were retrieved and submitted to the PRODIGY server for the prediction of binding energies. RBD-bacteriocin complexes were subjected to MD simulations. We discovered promising peptide-based therapeutic candidates for the inhibition of Omicron variant for example Salivaricin B, Pediocin PA 1, Plantaricin W, Lactococcin mmfii and Enterocin A. The lead bacteriocins, except Enterocin A, are biosynthesized by food-grade lactic acid bacteria. Our study puts forth a preliminary information regarding potential utilization of food-grade LAB-derived bacteriocins, particularly Salivaricin B and Pediocin PA 1, for Covid-19 treatment and prophylaxis.Communicated by Ramaswamy H. Sarma.

Wastewater-based surveillance can be used to model COVID-19-associated workforce absenteeism

Wastewater-based surveillance (WBS) of infectious diseases is a powerful tool for understanding community COVID-19 disease burden and informing public health policy. The potential of WBS for understanding COVID-19's impact in non-healthcare settings has not been explored to the same degree. Here we examined how SARS-CoV-2 measured from municipal wastewater treatment plants (WWTPs) correlates with workforce absenteeism. SARS-CoV-2 RNA N1 and N2 were quantified three times per week by RT-qPCR in samples collected at three WWTPs servicing Calgary and surrounding areas, Canada (1.4 million residents) between June 2020 and March 2022. Wastewater trends were compared to workforce absenteeism using data from the largest employer in the city (>15,000 staff). Absences were classified as being COVID-19-related, COVID-19-confirmed, and unrelated to COVID-19. Poisson regression was performed to generate a prediction model for COVID-19 absenteeism based on wastewater data. SARS-CoV-2 RNA was detected in 95.5 % (85/89) of weeks assessed. During this period 6592 COVID-19-related absences (1896 confirmed) and 4524 unrelated absences COVID-19 cases were recorded. A generalized linear regression using a Poisson distribution was performed to predict COVID-19-confirmed absences out of the total number of absent employees using wastewater data as a leading indicator (P < 0.0001). The Poisson regression with wastewater as a one-week leading signal has an Akaike information criterion (AIC) of 858, compared to a null model (excluding wastewater predictor) with an AIC of 1895. The likelihood-ratio test comparing the model with wastewater signal with the null model shows statistical significance (P < 0.0001). We also assessed the variation of predictions when the regression model was applied to new data, with the predicted values and corresponding confidence intervals closely tracking actual absenteeism data. Wastewater-based surveillance has the potential to be used by employers to anticipate workforce requirements and optimize human resource allocation in response to trackable respiratory illnesses like COVID-19.

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

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

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.

Application of wastewater-based surveillance and copula time-series model for COVID-19 forecasts

The objective of this study was to develop a novel copula-based time series (CTS) model to forecast COVID-19 cases and trends based on wastewater SARS-CoV-2 viral load and clinical variables. Wastewater samples were collected from wastewater pumping stations in five sewersheds in the City of Chesapeake VA. Wastewater SARS-CoV-2 viral load was measured using reverse transcription droplet digital PCR (RT-ddPCR). The clinical dataset included daily COVID-19 reported cases, hospitalization cases, and death cases. The CTS model development included two steps: an autoregressive moving average (ARMA) model for time series analysis (step I), and an integration of ARMA and a copula function for marginal regression analysis (step II). Poisson and negative binomial marginal probability densities for copula functions were used to determine the forecasting capacity of the CTS model for COVID-19 forecasts in the same geographical area. The dynamic trends predicted by the CTS model were well suited to the trend of the reported cases as the forecasted cases from the CTS model fell within the 99 % confidence interval of the reported cases. Wastewater SARS CoV-2 viral load served as a reliable predictor for forecasting COVID-19 cases. The CTS model provided robust modeling to predict COVID-19 cases.

The Secretory IgA Response in Human Milk Against the SARS-CoV-2 Spike Is Highly Durable and Neutralizing for At Least 1 Year of Lactation Postinfection

Background: Although in the early pandemic period COVID-19 pathology among young children and infants was typically less severe compared with that observed among adults, this has not remained entirely consistent as severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants have emerged. There is an enormous body of evidence demonstrating the benefits of human milk antibodies (Abs) in protecting infants against a wide range of enteric and respiratory infections. It is highly plausible that the same holds true for protection against SARS-CoV-2 as this virus infects cells of the gastrointestinal and respiratory mucosae. Understanding the durability of a human milk Ab response over time after infection is critical. Objective: Previously, we examined the Abs present in milk of those recently infected with SARS-CoV-2 and concluded that the response was secretory immunoglobulin A (sIgA) dominant and that these titers were highly correlated with neutralization potency. The present study aimed to monitor the durability of the SARS-CoV-2 IgA and secretory Ab (sAb) response in milk from COVID-19-recovered lactating individuals over 12 months in the absence of vaccination or reinfection. Results: This analysis revealed a robust and durable spike-specific milk sIgA response, and at 9-12 months after infection, 88% of the samples exhibited titers above the positive cutoff for IgA and 94% were above the cutoff for sAb. Fifty percent of participants exhibited less than twofold reduction of spike-specific IgA through 12 months. A strong, significant positive correlation between IgA and sAb against spike persisted throughout the study period. Nucleocapsid-specific Abs were also assessed, which revealed significant background or cross-reactivity of milk IgA against this immunogen, as well as limited/inconsistent durability compared with Spike titers. Conclusion: These data suggest that lactating individuals are likely to continue producing spike-specific Abs in their milk for 1 year or more, which may provide critical passive immunity to infants against SARS-CoV-2 throughout the lactation period.

A critical assessment of SARS-CoV-2 in aqueous environment: Existence, detection, survival, wastewater-based surveillance, inactivation methods, and effective management of COVID-19

In early January 2020, the causal agent of unspecified pneumonia cases detected in China and elsewhere was identified as a novel severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and was the major cause of the COVID-19 outbreak. Later, the World Health Organization (WHO) proclaimed the COVID-19 pandemic a worldwide public health emergency on January 30, 2020. Since then, many studies have been published on this topic. In the present study, bibliometric analysis has been performed to analyze the research hotspots of the coronavirus. Coronavirus transmission, detection methods, potential risks of infection, and effective management practices have been discussed in the present review. Identification and quantification of SARS-CoV-2 viral loads in various water matrices have been reviewed. It was observed that the viral shedding through urine and feces of COVID-19-infected patients might be a primary mode of SARS-CoV-2 transmission in water and wastewater. In this context, the present review highlights wastewater-based epidemiology (WBE)/sewage surveillance, which can be utilized as an effective tool for tracking the transmission of COVID-19. This review also emphasizes the role of different disinfection techniques, such as chlorination, ultraviolet irradiation, and ozonation, for the inactivation of coronavirus. In addition, the application of computational modeling methods has been discussed for the effective management of COVID-19.

Exploring possible strategies for treating SARS-CoV-2 in sewage wastewater: A review of current research and future directions

The advent of acute respiratory coronavirus disease (COVID-19) is convoyed by the shedding of the virus in stool. Although inhalation from person-to-person and aerosol/droplet transmission are the main modes of SARS-Coronavirus-2 (SARS-CoV-2) transmission, currently available evidence indicates the presence of viral RNA in the sewerage wastewater, which highlights the need for more effective corona virus treatment options. In the existing COVID-19 pandemic, a substantial percentage of cases shed SARS-CoV-2 viral RNA in their faeces. Hence the treating this sewerage wastewater with proper surveillance is essential to contain this deadly pathogen from further transmission. Since, the viral disinfectants will not be very effective on sewerage waste as organic matter, and suspended solids in water can protect viruses that adsorb to these particles. More effective methods and measures are needed to prevent this virus from spreading. This review will explore some potential methods to treat the SARS-CoV-2 infected sewerage wastewater, current research and future directions.

The secretory IgA (sIgA) response in human milk against the SARS-CoV-2 Spike is highly durable and neutralizing for at least 1 year of lactation post-infection

Although in the early pandemic period, COVID-19 pathology among young children and infants was typically less severe compared to that observed among adults, this has not remained entirely consistent as SARS-CoV-2 variants have emerged. There is an enormous body of evidence demonstrating the benefits of human milk antibodies (Abs) in protecting infants against a wide range of enteric and respiratory infections. It is highly plausible that the same holds true for protection against SARS-CoV-2, as this virus infects cells of the gastrointestinal and respiratory mucosae. Understanding the durability of a human milk Ab response over time after infection is critical. Previously, we examined the Abs present in milk of those recently infected with SARS-CoV-2, and concluded that the response was secretory IgA (sIgA)-dominant and that these titers were highly correlated with neutralization potency. The present study aimed to monitor the durability of the SARS-CoV-2 IgA and secretory Ab (sAb) response in milk from COVID-19-recovered lactating individuals over 12 months, in the absence of vaccination or re-infection. This analysis revealed a robust and durable Spike-specific milk sIgA response, that at 9-12 months after infection, 88% of the samples exhibited titers above the positive cutoff for IgA and 94% were above cutoff for sAb. Fifty percent of participants exhibited less than a 2-fold reduction of Spike-specific IgA through 12 months. A strong significant positive correlation between IgA and sAb against Spike persisted throughout the study period. Nucleocapsid-specific Abs were also assessed, which revealed significant background or cross reactivity of milk IgA against this immunogen, as well as limited/inconsistent durability compared to Spike titers. These data suggests that lactating individuals are likely to continue producing Spike-specific Abs in their milk for 1 year or more, which may provide critical passive immunity to infants against SARS-CoV-2 throughout the lactation period.

Effect of an Immune-Boosting, Antioxidant and Anti-Inflammatory Food Supplement in Hospitalized COVID-19 Patients: A Prospective Randomized Pilot Study

Background: COVID-19 disease is a serious global health problem. Few treatments have been shown to reduce mortality and accelerate time to recovery. The aim of this study was to evaluate the potential effect of a food supplement (probiotics, prebiotics, vitamin D, zinc and selenium) in patients admitted with COVID-19. Methods: A prospective randomized non-blinded clinical trial was conducted in a sample of 162 hospitalized patients diagnosed with COVID-19 recruited over eight months. All patients received standard treatment, but the intervention group (n = 67) was given one food supplement stick daily during their admission. After collecting the study variables, a statistical analysis was performed comparing the intervention and control groups and a multivariate analysis controlling for variables that could act as confounding factors. Results: ROC curve analysis with an area under the curve (AUC) value of 0.840 (p < 0.001; 95%CI: 0.741–0.939) of the food supplement administration vs. recovery indicated good predictive ability. Moreover, the intervention group had a shorter duration of digestive symptoms compared with the control group: 2.6 ± 1.3 vs. 4.3 ± 2.2 days (p = 0.001); patients with non-severe disease on chest X-ray had shorter hospital stays: 8.1 ± 3.9 vs. 11.6 ± 7.4 days (p = 0.007). Conclusions: In this trial, the administration of a food supplement (Gasteel Plus®) was shown to be a protective factor in the group of patients with severe COVID-19 and allowed early recovery from digestive symptoms and a shorter hospital stay in patients with a normal–mild–moderate chest X-ray at admission (ClinicalTrials.gov number, NCT04666116).

A descriptive study of abdominal complications in patients with mild COVID-19 presenting to the emergency department: a single-center experience in Japan during the omicron variant phase

BACKGROUND

COVID-19 is widely known to induce a variety of extrapulmonary manifestations. Gastrointestinal symptoms have been identified as the most common extra-pulmonary manifestations of COVID-19, with an incidence reported to range from 3 to 61%. Although previous reports have addressed abdominal complications with COVID-19, these have not been adequately elucidated for the omicron variant. The aim of our study was to clarify the diagnosis of concomitant abdominal diseases in patients with mild COVID-19 who presented to hospital with abdominal symptoms during the sixth and seventh waves of the pandemic of the omicron variant in Japan.

METHODS

This study was a retrospective, single-center, descriptive study. In total, 2291 consecutive patients with COVID-19 who visited the Department of Emergency and Critical Care Medicine, Kansai Medical University Medical Center, Osaka, Japan, between January 2022 and September 2022 were potentially eligible for the study. Patients delivered by ambulance or transferred from other hospitals were not included. We collected and described physical examination results, medical history, laboratory data, computed tomography findings and treatments. Data collected included diagnostic characteristics, abdominal symptoms, extra-abdominal symptoms and complicated diagnosis other than that of COVID-19 for abdominal symptoms.

RESULTS

Abdominal symptoms were present in 183 patients with COVID-19. The number of patients with each abdominal symptom were as follows: nausea and vomiting (86/183, 47%), abdominal pain (63/183, 34%), diarrhea (61/183, 33%), gastrointestinal bleeding (20/183, 11%) and anorexia (6/183, 3.3%). Of these patients, 17 were diagnosed as having acute hemorrhagic colitis, five had drug-induced adverse events, two had retroperitoneal hemorrhage, two had appendicitis, two had choledocholithiasis, two had constipation, and two had anuresis, among others. The localization of acute hemorrhagic colitis was the left-sided colon in all cases.

CONCLUSIONS

Our study showed that acute hemorrhagic colitis was characteristic in mild cases of the omicron variant of COVID-19 with gastrointestinal bleeding. When examining patients with mild COVID-19 with gastrointestinal bleeding, the potential for acute hemorrhagic colitis should be kept in mind.

Occurrence and transport of SARS-CoV-2 in wastewater streams and its detection and remediation by chemical-biological methods

This paper explains the transmission of SARS-CoV and influences of several environmental factors in the transmission process. The article highlighted several methods of collection, sampling and monitoring/estimation as well as surveillance tool for detecting SARS-CoV in wastewater streams. In this context, WBE (Wastewater based epidemiology) is found to be the most effective surveillance tool. Several methods of genomic sequencing are discussed in the paper, which are applied in WBE, like qPCR-based wastewater testing, metagenomics-based analysis, next generation sequencing etc. Additionally, several types of biosensors (colorimetric biosensor, mobile phone-based biosensors, and nanomaterials-based biosensors) showed promising results in sensing SARS-CoV in wastewater. Further, this review paper outlined the gaps in assessing the factors responsible for transmission and challenges in detection and monitoring along with the remediation and disinfection methods of this virus in wastewater. Various methods of disinfection of SARS-CoV-2 in wastewater are discussed (primary, secondary, and tertiary phases) and it is found that a suite of disinfection methods can be used for complete disinfection/removal of the virus. Application of ultraviolet light, ozone and chlorine-based disinfectants are also discussed in the context of treatment methods. This study calls for continuous efforts to gather more information about the virus through continuous monitoring and analyses and to address the existing gaps and identification of the most effective tool/ strategy to prevent SARS-CoV-2 transmission. Wastewater surveillance can be very useful in effective surveillance of future pandemics and epidemics caused by viruses, especially after development of new technologies in detecting and disinfecting viral pathogens more effectively.

Coronavirus: a comparative analysis of detection technologies in the wake of emerging variants

An outbreak of the coronavirus disease caused by a novel pathogen created havoc and continues to affect the entire world. As the pandemic progressed, the scientific community was faced by the limitations of existing diagnostic methods. In this review, we have compared the existing diagnostic techniques such as reverse transcription polymerase chain reaction (RT-PCR), antigen and antibody detection, computed tomography scan, etc. and techniques in the research phase like microarray, artificial intelligence, and detection using novel materials; on the prospect of sample preparation, detection procedure (qualitative/quantitative), detection time, screening efficiency, cost-effectiveness, and ability to detect different variants. A detailed comparison of different techniques showed that RT-PCR is still the most widely used and accepted coronavirus detection method despite certain limitations (single gene targeting- in context to mutations). New methods with similar efficiency that could overcome the limitations of RT-PCR may increase the speed, simplicity, and affordability of diagnosis. In addition to existing devices, we have also discussed diagnostic devices in the research phase showing high potential for clinical use. Our approach would be of enormous benefit in selecting a diagnostic device under a given scenario, which would ultimately help in controlling the current pandemic caused by the coronavirus, which is still far from over with new variants emerging.

Surveillance for SARS-CoV-2 and its variants in wastewater of tertiary care hospitals correlates with increasing case burden and outbreaks

Wastewater-based SARS-CoV-2 surveillance enables unbiased and comprehensive monitoring of defined sewersheds. We performed real-time monitoring of hospital wastewater that differentiated Delta and Omicron variants within total SARS-CoV-2-RNA, enabling correlation to COVID-19 cases from three tertiary-care facilities with >2100 inpatient beds in Calgary, Canada. RNA was extracted from hospital wastewater between August/2021 and January/2022, and SARS-CoV-2 quantified using RT-qPCR. Assays targeting R203M and R203K/G204R established the proportional abundance of Delta and Omicron, respectively. Total and variant-specific SARS-CoV-2 in wastewater was compared to data for variant specific COVID-19 hospitalizations, hospital-acquired infections, and outbreaks. Ninety-six percent (188/196) of wastewater samples were SARS-CoV-2 positive. Total SARS-CoV-2 RNA levels in wastewater increased in tandem with total prevalent cases (Delta plus Omicron). Variant-specific assessments showed this increase to be mainly driven by Omicron. Hospital-acquired cases of COVID-19 were associated with large spikes in wastewater SARS-CoV-2 and levels were significantly increased during outbreaks relative to nonoutbreak periods for total SARS-CoV2, Delta and Omicron. SARS-CoV-2 in hospital wastewater was significantly higher during the Omicron-wave irrespective of outbreaks. Wastewater-based monitoring of SARS-CoV-2 and its variants represents a novel tool for passive COVID-19 infection surveillance, case identification, containment, and potentially to mitigate viral spread in hospitals.

Detection of SARS-CoV-2 RNA in wastewater and comparison to COVID-19 cases in two sewersheds, North Carolina, USA

Wastewater surveillance of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) may be useful for monitoring population-wide coronavirus disease 2019 (COVID-19) infections, especially given asymptomatic infections and limitations in diagnostic testing. We aimed to detect SARS-CoV-2 RNA in wastewater and compare viral concentrations to COVID-19 case numbers in the respective counties and sewersheds. Influent 24-hour composite wastewater samples were collected from July to December 2020 from two municipal wastewater treatment plants serving different population sizes in Orange and Chatham Counties in North Carolina. After a concentration step via HA filtration, SARS-CoV-2 RNA was detected and quantified by reverse transcription droplet digital polymerase chain reaction (RT-ddPCR) and quantitative PCR (RT-qPCR), targeting the N1 and N2 nucleocapsid genes. SARS-CoV-2 RNA was detected by RT-ddPCR in 100 % (24/24) and 79 % (19/24) of influent wastewater samples from the larger and smaller plants, respectively. In comparison, viral RNA was detected by RT-qPCR in 41.7 % (10/24) and 8.3 % (2/24) of samples from the larger and smaller plants, respectively. Positivity rates and method agreement further increased for the RT-qPCR assay when samples with positive signals below the limit of detection were counted as positive. The wastewater data from the larger plant generally correlated (⍴ ~0.5, p < 0.05) with, and even anticipated, the trends in reported COVID-19 cases, with a notable spike in measured viral RNA preceding a spike in cases when students returned to a college campus in the Orange County sewershed. Correlations were generally higher when using estimates of sewershed-level case data rather than county-level data. This work supports use of wastewater surveillance for tracking COVID-19 disease trends, especially in identifying spikes in cases. Wastewater-based epidemiology can be a valuable resource for tracking disease trends, allocating resources, and evaluating policy in the fight against current and future pandemics.

Application and development of fecal microbiota transplantation in the treatment of gastrointestinal and metabolic diseases: A review

Fecal microbiota transplantation (FMT) restores a balanced intestinal flora, which helps to cure recurrent Clostridium difficile infections (RCDI). FMT has also been used to treat other gastrointestinal diseases, including inflammatory bowel disease (IBD), irritable bowel syndrome (IBS), and chronic constipation, as well as a variety of non-GI disorders. The purpose of this review is to discuss gut microbiota and FMT treatment of GI and non-GI diseases. An imbalanced gut microbiota is known to predispose one to Clostridium difficile infections (CDI), IBD, and IBS. However, the complex role of the gut microbiota in maintaining health is a newer concept that is being increasingly studied. The microbiome plays a major role in cellular immunity and metabolism and has been implicated in the pathogenesis of non-GI autoimmune diseases, chronic fatigue syndrome, obesity, and even some neuropsychiatric disorders. Many recent studies have reported that viral gastroenteritis can affect intestinal epithelial cells, and SARS-CoV-2 virus has been identified in the stool of infected patients. FMT is a highly effective cure for RCDI, but a better understanding of the gut microbiota in maintaining health and controlled studies of FMT in a variety of conditions are needed before FMT can be accepted and used clinically.

Alterations in Gut Microbiota Composition in Patients with COVID-19: A Pilot Study of Whole Hypervariable 16S rRNA Gene Sequencing

It is crucial to consider the importance of the microbiome and the gut-lung axis in the context of SARS-CoV-2 infection. This pilot study examined the fecal microbial composition of patients with COVID-19 following a 3-month recovery. Using for the first time metagenomic analysis based on all hypervariable regions (V1-V9) of the 16S rRNA gene, we have identified 561 microbial species; however, 17 were specific only for the COVID-19 group (n = 8). The patients' cohorts revealed significantly greater alpha diversity of the gut microbiota compared to healthy controls (n = 14). This finding has been demonstrated by operational taxonomic units (OTUs) richness (p < 0.001) and Chao1 index (p < 0.01). The abundance of the phylum Verrucomicrobia was 30 times higher in COVID-19 patients compared to healthy subjects. Accordingly, this disproportion was also noted at other taxonomic levels: in the class Verrucomicrobiae, the family Verrucomicrobiaceae, and the genus Akkermansia. Elevated pathobionts such as Escherichia coli, Bilophila wadsworthia, and Parabacteroides distasonis were found in COVID-19 patients. Considering the gut microbiota's ability to disturb the immune response, our findings suggest the importance of the enteric microbiota in the course of SARS-CoV-2 infection. This pilot study shows that the composition of the microbial community may not be fully restored in individuals with SARS-CoV-2 following a 3-month recovery.

Direct wastewater extraction as a simple and effective method for SARS-CoV-2 surveillance and COVID-19 community-level monitoring

Wastewater surveillance has proven to be an effective tool to monitor the transmission and emergence of infectious agents at a community scale. Workflows for wastewater surveillance generally rely on concentration steps to increase the probability of detection of low-abundance targets, but preconcentration can substantially increase the time and cost of analyses while also introducing additional loss of target during processing. To address some of these issues, we conducted a longitudinal study implementing a simplified workflow for SARS-CoV-2 detection from wastewater, using a direct column-based extraction approach. Composite influent wastewater samples were collected weekly for 1 year between June 2020 and June 2021 in Athens-Clarke County, Georgia, USA. Bypassing any concentration step, low volumes (280 µl) of influent wastewater were extracted using a commercial kit, and immediately analyzed by RT-qPCR for the SARS-CoV-2 N1 and N2 gene targets. SARS-CoV-2 viral RNA was detected in 76% (193/254) of influent samples, and the recovery of the surrogate bovine coronavirus was 42% (IQR: 28%, 59%). N1 and N2 assay positivity, viral concentration, and flow-adjusted daily viral load correlated significantly with per-capita case reports of COVID-19 at the county-level (ρ = 0.69-0.82). To compensate for the method's high limit of detection (approximately 106-107 copies l-1 in wastewater), we extracted multiple small-volume replicates of each wastewater sample. With this approach, we detected as few as five cases of COVID-19 per 100 000 individuals. These results indicate that a direct-extraction-based workflow for SARS-CoV-2 wastewater surveillance can provide informative and actionable results.

Environmental challenges of COVID-19 pandemic: resilience and sustainability - A review

The emergence of novel respiratory disease (COVID-19) caused by SARS-CoV-2 has become a public health emergency worldwide and perturbed the global economy and ecosystem services. Many studies have reported the presence of SARS-CoV-2 in different environmental compartments, its transmission via environmental routes, and potential environmental challenges posed by the COVID-19 pandemic. None of these studies have comprehensively reviewed the bidirectional relationship between the COVID-19 pandemic and the environment. For the first time, we explored the relationship between the environment and the SARS-CoV-2 virus/COVID-19 and how they affect each other. Supporting evidence presented here clearly demonstrates the presence of SARS-CoV-2 in soil and water, denoting the role of the environment in the COVID-19 transmission process. However, most studies fail to determine if the viral genomes they have discovered are infectious, which could be affected by the environmental factors in which they are found.The potential environmental impact of the pandemic, including water pollution, chemical contamination, increased generation of non-biodegradable waste, and single-use plastics have received the most attention. For the most part, efficient measures have been used to address the current environmental challenges from COVID-19, including using environmentally friendly disinfection technologies and employing measures to reduce the production of plastic wastes, such as the reuse and recycling of plastics. Developing sustainable solutions to counter the environmental challenges posed by the COVID-19 pandemic should be included in national preparedness strategies. In conclusion, combating the pandemic and accomplishing public health goals should be balanced with environmentally sustainable measures, as the two are closely intertwined.

The Gut Microbiome of Children during the COVID-19 Pandemic

The gut microbiome has been shown to play a critical role in maintaining a healthy state. Dysbiosis of the gut microbiome is involved in modulating disease severity and potentially contributes to long-term outcomes in adults with COVID-19. Due to children having a significantly lower risk of severe illness and limited sample availability, much less is known about the role of the gut microbiome in children with COVID-19. It is well recognized that the developing gut microbiome of children differs from that of adults, but it is unclear if this difference contributes to the different clinical presentations and complications. In this review, we discuss the current knowledge of the gut microbiome in children with COVID-19, with gut microbiome dysbiosis being found in pediatric COVID-19 but specific taxa change often differing from those described in adults. Additionally, we discuss possible mechanisms of how the gut microbiome may mediate the presentation and complications of COVID-19 in children and the potential role for microbial therapeutics.

Detection of the SARS-CoV-2 Delta Variant in the Transboundary Rivers of Yunnan, China

Ruili and Longchuan, two border counties in southwestern China, are facing epidemic control challenges due to the high rate of COVID-19 infections originating from neighboring Myanmar. Here, we aimed to establish the applicability of wastewater and environmental water surveillance of SARS-CoV-2 and conduct whole-genome sequencing (WGS) to trace the possible infection origin. In August 2021, total 72 wastewater and river water samples were collected from 32 sampling sites. SARS-CoV-2 ORF1ab and N genes were measured by RT-qPCR. We found that 19 samples (26.39%) were positive, and the viral loads of ORF1ab and N genes were 6.62 × 102-2.55×105 and 1.86 × 103-2.32 × 105 copies/L, respectively. WGS further indicated the sequences in two transboundary river samples, and one hospital wastewater sample belonged to the delta variant, suggesting that the infection source might be areas with high COVID-19 delta variant incidence in Southeast Asia (e.g., Myanmar). We reported for the first time the detection and quantification of SARS-CoV-2 RNA in the transboundary rivers of Myanmar-China. Our findings demonstrate that wastewater and environmental water may provide independent and nonintrusive surveillance points to monitor the global spread of emerging COVID-19 variants of concern, particularly in high-risk regions or border areas with considerable epidemic challenges and poor wastewater treatment facilities.

Application of machine learning for multi-community COVID-19 outbreak predictions with wastewater surveillance

The potential of wastewater-based epidemiology (WBE) as a surveillance and early warning tool for the COVID-19 outbreak has been demonstrated. For areas with limited testing capacity, wastewater surveillance can provide information on the disease dynamic at a community level. A predictive model is a key to generating quantitative estimates of the infected population. Modeling longitudinal wastewater data can be challenging as biomarkers in wastewater are susceptible to variations caused by multiple factors associated with the wastewater matrix and the sewersheds characteristics. As WBE is an emerging trend, the model should be able to address the uncertainties of wastewater from different sewersheds. We proposed exploiting machine learning and deep learning techniques, which are supported by the growing WBE data. In this article, we reviewed the existing predictive models, among which the emerging machine learning/deep learning models showed great potential. However, most models are built for individual sewersheds with few features extracted from the wastewater. To fulfill the research gap, we compared different time-series and non-time-series models for their short-term predictive performance of COVID-19 cases in 9 diverse sewersheds. The time-series models, long short-term memory (LSTM) and Prophet, outcompeted the non-time-series models. Besides viral (SARS-CoV-2) loads and location identity, domain-specific features like biochemical parameters of wastewater, geographical parameters of the sewersheds, and some socioeconomic parameters of the communities can contribute to the models. With proper feature engineering and hyperparameter tuning, we believe machine learning models like LSTM can be a feasible solution for the COVID-19 trend prediction via WBE. Overall, this is a proof-of-concept study on the application of machine learning in COVID-19 WBE. Future studies are needed to deploy and maintain the model in more real-world applications.

The Efficient and Practical virus Identification System with ENhanced Sensitivity for Solids (EPISENS-S): A rapid and cost-effective SARS-CoV-2 RNA detection method for routine wastewater surveillance

Wastewater-based epidemiology has attracted attention as a COVID-19 surveillance tool. Here, we developed a practical method for detecting SARS-CoV-2 RNA in wastewater (the EPISENS-S method), which employs direct RNA extraction from wastewater pellets formed via low-speed centrifugation. The subsequent multiplex one-step RT-preamplification reaction with forward and reverse primers for SARS-CoV-2 and a reverse primer only for pepper mild mottle virus (PMMoV) allowed for qPCR quantification of the targets with different abundances in wastewater from the RT-preamplification product. The detection sensitivity of the method was evaluated using wastewater samples seeded with heat-inactivated SARS-CoV-2 in concentrations of 2.11 × 103 to 2.11 × 106 copies/L. The results demonstrated that the sensitivity of the EPISENS-S method was two orders of magnitude higher than that of the conventional method (PEG precipitation, followed by regular RT-qPCR; PEG-QVR-qPCR). A total of 37 untreated wastewater samples collected from two wastewater treatment plants in Sapporo, Japan when 1.6 to 18 new daily reported cases per 100,000 people were reported in the city (March 4 to July 8, 2021), were examined using the EPISENS-S method to confirm its applicability to municipal wastewater. SARS-CoV-2 RNA was quantified in 92 % (34/37) of the samples via the EPISENS-S method, whereas none of the samples (0/37) was quantifiable via the PEG-QVR-qPCR method. The PMMoV concentrations measured by the EPISENS-S method ranged from 2.60 × 106 to 1.90 × 108 copies/L, and the SARS-CoV-2 RNA concentrations normalized by PMMoV ranged from 5.71 × 10-6 to 9.51 × 10-4 . The long-term trend of normalized SARS-CoV-2 RNA concentration in wastewater was consistent with that of confirmed COVID-19 cases in the city. These results demonstrate that the EPISENS-S method is highly sensitive and suitable for routine COVID-19 wastewater surveillance.

Label-free laser spectroscopy for respiratory virus detection: A review

Infectious diseases are among the most severe threats to modern society. Current methods of virus infection detection based on genome tests need reagents and specialized laboratories. The desired characteristics of new virus detection methods are noninvasiveness, simplicity of implementation, real-time, low cost and label-free detection. There are two groups of methods for molecular biomarkers' detection and analysis: (i) a sample physical separation into individual molecular components and their identification, and (ii) sample content analysis by laser spectroscopy. Variations in the spectral data are typically minor. It requires the use of sophisticated analytical methods like machine learning. This review examines the current technological level of laser spectroscopy and machine learning methods in applications for virus infection detection.

SARS-COV-2/COVID-19: scenario, epidemiology, adaptive mutations, and environmental factors

The coronavirus pandemic of 2019 has already exerted an enormous impact. For over a year, the worldwide pandemic has ravaged the whole globe, with approximately 250 million verified human infection cases and a mortality rate surpassing 4 million. While the genetic makeup of the related pathogen (SARS-CoV-2) was identified, many unknown facets remain a mystery, comprising the virus's origin and evolutionary trend. There were many rumors that SARS-CoV-2 was human-borne and its evolution was predicted many years ago, but scientific investigation proved them wrong and concluded that bats might be the origin of SARS-CoV-2 and pangolins act as intermediary species to transmit the virus from bats to humans. Airborne droplets were found to be the leading cause of human-to-human transmission of this virus, but later studies showed that contaminated surfaces and other environmental factors are also involved in its transmission. The evolution of different SARS-CoV-2 variants worsens the condition and has become a challenge to overcome this pandemic. The emergence of COVID-19 is still a mystery, and scientists are unable to explain the exact origin of SARS-CoV-2. This review sheds light on the possible origin of SARS-CoV-2, its transmission, and the key factors that worsen the situation.

Global occurrence of SARS-CoV-2 in environmental aquatic matrices and its implications for sanitation and vulnerabilities in Brazil and developing countries

This paper includes a systematic review of the SARS-CoV-2 occurrence in environmental aquatic matrices and a critical sanitation analysis. We discussed the interconnection of sanitation services (wastewater, water supply, solid waste, and stormwater drainage) functioning as an important network for controlling the spread of SARS-CoV-2 in waters. We collected 98 studies containing data of the SARS-CoV-2 occurrence in aquatic matrices around the world, of which 40% were from developing countries. Alongside a significant number of people infected by the virus, developing countries face socioeconomic deficiencies and insufficient public investment in infrastructure. Therefore, our study focused on highlighting solutions to provide sanitation in developing countries, considering the virus control in waters by disinfection techniques and sanitary measures, including alternatives for the vulnerable communities. The need for multilateral efforts to improve the universal coverage of sanitation services demands urgent attention in a pandemic scenario.

Analysis of SARS-CoV-2 viral loads in stool samples and nasopharyngeal swabs from COVID-19 patients in the United Arab Emirates

Coronavirus disease 2019 (COVID-19) was first identified in respiratory samples and was found to commonly cause cough and pneumonia. However, non-respiratory symptoms including gastrointestinal disorders are also present and a big proportion of patients test positive for the virus in stools for a prolonged period. In this cross-sectional study, we investigated viral load trends in stools and nasopharyngeal swabs and their correlation with multiple demographic and clinical factors. The study included 211 laboratory-confirmed cases suffering from a mild form of the disease and completing their isolation period at a non-hospital center in the United Arab Emirates. Demographic and clinical information was collected by standardized questionnaire and from the medical records of the patient. Of the 211 participants, 25% tested negative in both sample types at the time of this study and 53% of the remaining patients had detectable viral RNA in their stools. A positive fecal viral test was associated with male gender, diarrhea as a symptom, and hospitalization during infection. A positive correlation was also observed between a delayed onset of symptoms and a positive stool test. Viral load in stools positively correlated with, being overweight, exercising, taking antibiotics in the last 3 months and blood type O. The viral load in nasopharyngeal swabs, on the other hand, was higher for blood type A, and rhesus positive (Rh factor). Regression analysis showed no correlation between the viral loads measured in stool and nasopharyngeal samples in any given patient. The results of this work highlight the factors associated with a higher viral count in each sample. It also shows the importance of stool sample analysis for the follow-up and diagnosis of recovering COVID-19 patients.

Expanding current guidelines for management of COVID-19 focusing on low- and middle-income countries

Within a short time, Coronavirus disease 2019 (COVID-19) has evolved into a pandemic spreading at a speed and scale that has been able to overwhelm even the most advanced health care systems quickly. Multiple guidelines published by organizations such as the WHO and US' CDC address the response to COVID-19 at the international, national, and local levels. Although these guidelines are meant to be globally accessible, implementing them is a challenge given the variability in the health care systems worldwide between low- and middleincome countries (LMIC) and high-income countries and even amongst different regions within each LMIC. We have chosen to evaluate the current guidelines focusing on LMIC and expand on the guidelines as necessary.

Review of concerned SARS-CoV-2 variants like Alpha (B.1.1.7), Beta (B.1.351), Gamma (P.1), Delta (B.1.617.2), and Omicron (B.1.1.529), as well as novel methods for reducing and inactivating SARS-CoV-2 mutants in wastewater treatment facilities

The coronavirus known as COVID-19, which causes pandemics, is causing a global epidemic at a critical stage today. Furthermore, novel mutations in the SARS-CoV-2 spike protein have been discovered in an entirely new strain, impacting the clinical and epidemiological features of COVID-19. Variants of these viruses can increase the transmission in wastewater, lead to reinfection, and reduce immunity provided by monoclonal antibodies and vaccinations. According to the research, a large quantity of viral RNA was discovered in wastewater, suggesting that wastewater can be a crucial source of epidemiological data and health hazards. The purpose of this paper is to introduce a few basic concepts regarding wastewater surveillance as a starting point for comprehending COVID-19's epidemiological aspects. Next, the observation of Alpha (B.1.1.7), Beta (B.1.351), Gamma (P.1), Delta (B.1.617.2), and Omicron (B.1.1.529) in wastewater is discussed in detail. Secondly, the essential information for the initial, primary, and final treating sewage in SARS-CoV-2 is introduced. Following that, a thorough examination is provided to highlight the newly developed methods for eradicating SARS-CoV-2 using a combination of solar water disinfection (SODIS) and ultraviolet radiation A (UVA (315-400 nm)), ultraviolet radiation B (UVB (280-315 nm)), and ultraviolet radiation C (UVC (100-280 nm)) processes. SARS-CoV-2 eradication requires high temperatures (above 56°C) and UVC. However, SODIS technologies are based on UVA and operate at cooler temperatures (less than 45°C). Hence, it is not appropriate for sewage treatment (or water consumption) to be conducted using SODIS methods in the current pandemic. Finally, SARS-CoV-2 may be discovered in sewage utilizing the wastewater-based epidemiology (WBE) monitoring method.

Comparative Profiles of SARS-CoV-2 Spike-Specific Human Milk Antibodies Elicited by mRNA- and Adenovirus-Based COVID-19 Vaccines

Background: Numerous COVID-19 vaccines are authorized globally. To date, ∼71% of doses comprise the Pfizer/BioNTech vaccine, and ∼17% the Moderna/NIH vaccine, both of which are messenger RNA (mRNA) based. The chimpanzee Ad-based Oxford/AstraZeneca (AZ) vaccine comprises ∼9%, while the Johnson & Johnson/Janssen (J&J) human adenovirus (Ad26) vaccine ranks fourth at ∼2%. No COVID-19 vaccine is yet available for children 0-4. One method to protect this population may be passive immunization through antibodies (Abs) provided in the milk of a lactating vaccinated person. Our early work and other reports have demonstrated that unlike the post-SARS-CoV-2 infection milk Ab profile, which is rich in specific secretory (s)IgA, the vaccine response is highly IgG dominant. Results: In this report, we present a comparative assessment of the milk Ab response elicited by Pfizer, Moderna, J&J, and AZ vaccines. This analysis revealed 86-100% of mRNA vaccine recipient milk exhibited Spike-specific IgG endpoint titers, which were 12- to 28-fold higher than those measured for Ad vaccine recipient milk. Ad-based vaccines elicited Spike-specific milk IgG in only 33-38% of recipients. Specific IgA was measured in 52-71% of mRNA vaccine recipient milk and 17-23% of Ad vaccine recipient milk. J&J recipient milk exhibited significantly lower IgA than Moderna recipients, and AZ recipients exhibited significantly lower IgA titers than Moderna and Pfizer. Less than 50% of milk of any group exhibited specific secretory Ab, with Moderna recipient IgA titers measuring significantly higher than AZ. Moderna appeared to most frequently elicit greater than twofold increases in specific secretory Ab titer relative to prevaccine sample. Conclusion: These data indicate that current Ad-based COVID-19 vaccines poorly elicit Spike-specific Ab in milk compared to mRNA-based vaccines, and that mRNA vaccines are preferred for immunizing the lactating population. This study highlights the need to design vaccines better aimed at eliciting an optimal milk Ab response.

Estimating the incubation period of SARS-CoV-2 Omicron BA.1 variant in comparison with that during the Delta variant dominance in South Korea

Based on exposure history and symptom onset of 22 Omicron BA.1 cases in South Korea from November to December 2021, we estimated mean incubation period of 3.5 days (95% CI: 2.5, 3.8), and then compared to that of 6.5 days (95% CI: 5.3, 7.7) for 64 cases during Delta variants' dominance in June 2021. For Omicron BA.1 variants, we found that 95% of symptomatic cases developed clinical conditions within 6.0 days (95% CI: 4.3, 6.6) after exposure. Thus, a shorter quarantine period may be considered based on symptoms, or similarly laboratory testing, when Omicron BA.1 variants are circulating.

Application of human RNase P normalization for the realistic estimation of SARS-CoV-2 viral load in wastewater: A perspective from Qatar wastewater surveillance

The apparent uncertainty associated with shedding patterns, environmental impacts, and sample processing strategies have greatly influenced the variability of SARS-CoV-2 concentrations in wastewater. This study evaluates the use of a new normalization approach using human RNase P for the logic estimation of SARS-CoV-2 viral load in wastewater. SARS-CoV-2 variants outbreak was monitored during the circulating wave between February and August 2021. Sewage samples were collected from five major wastewater treatment plants and subsequently analyzed to determine the viral loads in the wastewater. SARS-CoV-2 was detected in all the samples where the wastewater Ct values exhibited a similar trend as the reported number of new daily positive cases in the country. The infected population number was estimated using a mathematical model that compensated for RNA decay due to wastewater temperature and sewer residence time, and which indicated that the number of positive cases circulating in the population declined from 765,729 ± 142,080 to 2,303 ± 464 during the sampling period. Genomic analyses of SARS-CoV-2 of thirty wastewater samples collected between March 2021 and April 2021 revealed that alpha (B.1.1.7) and beta (B.1.351) were among the dominant variants of concern (VOC) in Qatar. The findings of this study imply that the normalization of data allows a more realistic assessment of incidence trends within the population.

Longitudinal SARS-CoV-2 RNA wastewater monitoring across a range of scales correlates with total and regional COVID-19 burden in a well-defined urban population

Wastewater-based epidemiology (WBE) is an emerging surveillance tool that has been used to monitor the ongoing COVID-19 pandemic by tracking SARS-CoV-2 RNA shed into wastewater. WBE was performed to monitor the occurrence and spread of SARS-CoV-2 from three wastewater treatment plants (WWTP) and six neighborhoods in the city of Calgary, Canada (population 1.44 million). A total of 222 WWTP and 192 neighborhood samples were collected from June 2020 to May 2021, encompassing the end of the first-wave (June 2020), the second-wave (November end to December 2020) and the third-wave of the COVID-19 pandemic (mid-April to May 2021). Flow-weighted 24-hour composite samples were processed to extract RNA that was then analyzed for two SARS-CoV-2-specific regions of the nucleocapsid gene, N1 and N2, using reverse transcription-quantitative polymerase chain reaction (RT-qPCR). Using this approach SARS-CoV-2 RNA was detected in 98.06% (406/414) of wastewater samples. SARS-CoV-2 RNA abundance was compared to clinically diagnosed COVID-19 cases organized by the three-digit postal code of affected individuals' primary residences, enabling correlation analysis at neighborhood, WWTP and city-wide scales. Strong correlations were observed between N1 & N2 gene signals in wastewater and new daily cases for WWTPs and neighborhoods. Similarly, when flow rates at Calgary's three WWTPs were used to normalize observed concentrations of SARS-CoV-2 RNA and combine them into a city-wide signal, this was strongly correlated with regionally diagnosed COVID-19 cases and clinical test percent positivity rate. Linked census data demonstrated disproportionate SARS-CoV-2 in wastewater from areas of the city with lower socioeconomic status and more racialized communities. WBE across a range of urban scales was demonstrated to be an effective mechanism of COVID-19 surveillance.

Can wastewater surveillance assist China to cost-effectively prevent the nationwide outbreak of COVID-19?

China has controlled the nationwide spread of COVID-19 since April 2020, but it is still facing an enormous threat of disease resurgence originating from infected international travelers. Taking the rapid transmission and the mutation of SARS-CoV-2 into consideration, the current status would be easily jeopardized if sporadic locally-transmitted individuals are not identified at an early stage. Clinical diagnosis is the gold standard for COVID-19 surveillance, but it is hard to screen presymptomatic or asymptomatic cases in those who have not exhibited symptoms. Since presymptomatic or asymptomatic individuals are infectious, it is urgent to establish a surveillance system based on other tools that can profile the entire population. Infected people including those who are symptomatic, presymptomatic, and asymptomatic shed SARS-CoV-2 RNA in feces and thereby endow wastewater-based epidemiology (WBE) with an early-warning ability for mass COVID-19 surveillance. In the context of China's "COVID-zero" strategy, this work intends to discuss the practical feasibility of WBE applications as an early warning and disease surveillance system in hopes that WBE together with clinical testing would cost-effectively restrain sporadic COVID-19 outbreaks in China.

Altered gut microbiota patterns in COVID-19: Markers for inflammation and disease severity

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection leads to a severe respiratory illness and alters the gut microbiota, which dynamically interacts with the human immune system. Microbiota alterations include decreased levels of beneficial bacteria and augmentation of opportunistic pathogens. Here, we describe critical factors affecting the microbiota in coronavirus disease 2019 (COVID-19) patients. These include, such as gut microbiota imbalance and gastrointestinal symptoms, the pattern of altered gut microbiota composition in COVID-19 patients, and crosstalk between the microbiome and the gut-lung axis/gut-brain-lung axis. Moreover, we have illustrated the hypoxia state in COVID-19 associated gut microbiota alteration. The role of ACE2 in the digestive system, and control of its expression using the gut microbiota is discussed, highlighting the interactions between the lungs, the gut, and the brain during COVID-19 infection. Similarly, we address the gut microbiota in elderly or co-morbid patients as well as gut microbiota dysbiosis of in severe COVID-19. Several clinical trials to understand the role of probiotics in COVID-19 patients are listed in this review. Augmented inflammation is one of the major driving forces for COVID-19 symptoms and gut microbiome disruption and is associated with disease severity. However, understanding the role of the gut microbiota in immune modulation during SARS-CoV-2 infection may help improve therapeutic strategies for COVID-19 treatment.

Novel Coronavirus is the Only Virus Causing Childhood Invasive Diarrhea: A Case Series

Introduction: Typical manifestations of Coronavirus disease 2019 (COVID-19) include respiratory involvement. Gastrointestinal (GI) symptoms have also been reported as early clinical manifestations. The GI involvement can represent with diarrhea, vomiting, and abdominal pain. The present research aimed to identify dysentery as one of the signs of GI involvement in the novel coronavirus infection in children. Case Presentation: We report twelve patients with COVID-19 and dysentery. All these children had positive reverse transcription-polymerase chain reaction (RT-PCR) results. None had underlying illnesses or recent travel history. However, all children had contact with a first-degree relative affected by non-digestive COVID-19. In three patients, obvious dysentery was observed, and in the rest, red and white blood cells were evident in the stool exam. Stool exams were negative for bacterial infections, parasites, and the toxin of Clostridium difficile. Abdominal ultrasonography and echocardiographic evaluations to rule out multisystem inflammatory syndrome in children were normal. Supportive treatment, such as zinc supplementation and probiotics, was prescribed. They also received intravenous fluid therapy based on their dehydration percentage. In the end, they were discharged in good general condition without any complications. No GI complications were found in the follow-up series. Conclusions: Dysentery in children can be one of the GI manifestations of COVID-19, which is usually self-limiting. It does not require invasive diagnostic measures and antiviral treatments. This symptom is in contrast to other viral infections of the GI tract.

Improved Analysis of COVID-19 Influenced Pneumonia from the Chest X-Rays Using Fine-Tuned Residual Networks

COVID-19 has remained a threat to world life despite a recent reduction in cases. There is still a possibility that the virus will evolve and become more contagious. If such a situation occurs, the resulting calamity will be worse than in the past if we act irresponsibly. COVID-19 must be widely screened and recognized early to avert a global epidemic. Positive individuals should be quarantined immediately, as this is the only effective way to prevent a global tragedy that has occurred previously. No positive case should go unrecognized. However, current COVID-19 detection procedures require a significant amount of time during human examination based on genetic and imaging techniques. Apart from RT-PCR and antigen-based tests, CXR and CT imaging techniques aid in the rapid and cost-effective identification of COVID. However, discriminating between diseased and normal X-rays is a time-consuming and challenging task requiring an expert's skill. In such a case, the only solution was an automatic diagnosis strategy for identifying COVID-19 instances from chest X-ray images. This article utilized a deep convolutional neural network, ResNet, which has been demonstrated to be the most effective for image classification. The present model is trained using pretrained ResNet on ImageNet weights. The versions of ResNet34, ResNet50, and ResNet101 were implemented and validated against the dataset. With a more extensive network, the accuracy appeared to improve. Nonetheless, our objective was to balance accuracy and training time on a larger dataset. By comparing the prediction outcomes of the three models, we concluded that ResNet34 is a more likely candidate for COVID-19 detection from chest X-rays. The highest accuracy level reached 98.34%, which was higher than the accuracy achieved by other state-of-the-art approaches examined in earlier studies. Subsequent analysis indicated that the incorrect predictions occurred with approximately 100% certainty. This uncovered a severe weakness in CNN, particularly in the medical area, where critical decisions are made. However, this can be addressed further in a future study by developing a modified model to incorporate uncertainty into the predictions, allowing medical personnel to manually review the incorrect predictions.