First detection of SARS-CoV-2 in untreated wastewaters in Italy

Preconcentration and detection of SARS-CoV-2 in wastewater: A comprehensive review

Severe acute respiratory syndrome coronaviruses 2 (SARS-CoV-2) causing coronavirus disease 2019 (COVID-19) affected the health of human beings and the global economy. The patients with SARS-CoV-2 infection had viral RNA or live infectious viruses in feces. Thus, the possible transmission of SARS-CoV-2 through wastewater received great attentions. Moreover, SARS-CoV-2 in wastewater can serve as an early indicator of the infection within communities. We summarized the preconcentration and detection technology of SARS-CoV-2 in wastewater aiming at the complex matrices of wastewater and low virus concentration and compared their performance characteristics. We described the emerging tests that would be possible to realize the rapid detection of SARS-CoV-2 in fields and encourage academics to advance their technologies beyond conception. We concluded with a brief discussion on the outlook for integrating preconcentration and the detection of SARS-CoV-2 with emerging technologies.

Facility wastewater monitoring as an effective tool for pandemic infection control: An experience in COVID-19 pandemic with long-term monitoring

INTRODUCTION

Since the first report of a novel coronavirus infection caused by SARS-CoV-2 in late 2019, the infection has spread rapidly and had a significant impact on our lives. In the early stages of the COVID-19 pandemic, there was no adequate testing system in place, despite an urgent need for infection control measures in student dormitories.

METHODS

We have been monitoring SARS-CoV-2 in wastewater as part of our infection control efforts in the university facilities since fall 2020. In the four dormitories, absorbent cotton was placed in the drains that the facility wastewater passed through, and samples were collected twice a week and processed by RT-PCR for SARS-CoV-2. The dormitory residents were informed of the monitoring results the next morning.

RESULTS

The positivity of residents in the dormitories was highly consistent with the positivity of wastewater. Wastewater was positive in 89 % of cases before any residents were tested and found positive. Facility wastewater monitoring showed sensitivities of 80.4 % and specificities of 87.6 %. No traceable resident-to-resident transmission of infection within the facility was confirmed during the study period.

CONCLUSION

Sampling a single wastewater outlet in a building for SARS-CoV-2 PCR can effectively indicate the presence or absence of COVID-19 cases and be very useful for infection control of a facility. This simple and effective monitoring is applicable to future outbreaks of both emerging and re-emerging infectious diseases.

Wastewater Surveillance of SARS-CoV-2 in Zambia: An Early Warning Tool

Wastewater-based surveillance has emerged as an important method for monitoring the Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2). This study investigated the presence of SARS-CoV-2 in wastewater in Zambia. We conducted a longitudinal study in the Copperbelt and Eastern provinces of Zambia from October 2023 to December 2023 during which 155 wastewater samples were collected. The samples were subjected to three different concentration methods, namely bag-mediated filtration, skimmed milk flocculation, and polythene glycol-based concentration assays. Molecular detection of SARS-CoV-2 nucleic acid was conducted using real-time Polymerase Chain Reaction (PCR). Whole genome sequencing was conducted using Illumina COVIDSEQ assay. Of the 155 wastewater samples, 62 (40%) tested positive for SARS-CoV-2. Of these, 13 sequences of sufficient length to determine SARS-CoV-2 lineages were obtained and 2 sequences were phylogenetically analyzed. Various Omicron subvariants were detected in wastewater including BA.5, XBB.1.45, BA.2.86, and JN.1. Some of these subvariants have been detected in clinical cases in Zambia. Interestingly, phylogenetic analysis positioned a sequence from the Copperbelt Province in the B.1.1.529 clade, suggesting that earlier Omicron variants detected in late 2021 could still be circulating and may not have been wholly replaced by newer subvariants. This study stresses the need for integrating wastewater surveillance of SARS-CoV-2 into mainstream strategies for monitoring SARS-CoV-2 circulation in Zambia.

Evaluating approach uncertainties of quantitative detection of SARS-CoV-2 in wastewater: Concentration, extraction and amplification

Substantial uncertainties pose challenges to the accuracy of Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) quantification in wastewater. We conducted a comprehensive evaluation of two concentration methods, three nucleic acid extraction methods, and the amplification performance of eight primer-probe sets. Our results showed that the two concentration methods exhibited similar recovery rates. Specifically, using a 30 kDa cut-off ultrafilter and a centrifugal force of 2500 g achieved the highest virus recovery rates (27.32 ± 8.06 % and 26.37 ± 7.77 %, respectively), with lower corresponding quantification uncertainties of 29.51 % and 29.47 % in ultrafiltration methods. Similarly, a 15 % PEG concentration with 1.5 M NaCl markedly improved virus recovery (26.76 ± 5.92 % and 28.47 ± 6.74 %, respectively), and reducing variation to 22.16 % and 23.66 % in the PEG precipitation method. Additionally, employing a vigorous bead-beating approach at 6 m/s during viral RNA extraction significantly increased RNA yield, with an efficiency reaching up to 82.18 %. Among the evaluated eight primer-probe sets, the E_Sarbeco primer-probe set provided the most stable and consistent quantitative results across various sample matrices. These findings are crucial for establishing robust viral quantification protocols and enhancing methodological precision for effective wastewater surveillance, enabling sensitive and precise detection of SARS-CoV-2.

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 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.

Evaluation of different molecular systems for detection and quantification of SARS-CoV-2 RNA from wastewater samples

Wastewater-based epidemiology has proved to be a suitable approach for tracking the spread of epidemic agents including SARS-CoV-2 RNA. Different protocols have been developed for quantitative detection of SARS-CoV-2 RNA from wastewater samples, but little is known on their performance. In this study we compared three protocols based on Reverse Transcription Real Time-PCR (RT-PCR) and one based on Droplet Digital PCR (ddPCR) for SARS-CoV-2 RNA detection from 35 wastewater samples. Overall, SARS-CoV-2 RNA was detected by at least one method in 85.7 % of samples, while 51.4 %, 22.8 % and 8.6 % resulted positive with two, three or all four methods, respectively. Protocols based on commercial RT-PCR assays and on Droplet Digital PCR showed an overall higher sensitivity vs. an in-house assay. The use of more than one system, targeting different genes, could be helpful to increase detection sensitivity.

Analysis of chlorhexidine, antibiotics and bacterial community composition in water environments from Brazil, Cameroon and Madagascar during the COVID-19 pandemic

The widespread of chlorhexidine and antibiotics in the water bodies, which grew during the global COVID-19 pandemic, can increase the dispersion of antibiotic resistance. We assessed the occurrence of these pharmaceutical compounds as well as SARS-CoV-2 and analysed the bacterial community structure of hospital and urban wastewaters from Brazil, Cameroon, and Madagascar. Water and wastewater samples (n = 59) were collected between January-June 2022. Chlorhexidine, azithromycin, levofloxacin, ceftriaxone, gentamicin and meropenem were screened by Ultra-High-Performance Liquid Chromatography coupled with mass spectrometer. SARS-CoV-2 was detected based on the nucleocapsid gene (in Cameroon and Madagascar), and envelope and spike protein-encoding genes (in Brazil). The total community-DNA was extracted and used for bacterial community analysis based on the 16S rRNA gene. To unravel likely interaction between pharmaceutical compounds and/or SARS-CoV-2 with the water bacterial community, multivariate statistics were performed. Chlorhexidine was found in hospital wastewater effluent from Brazil with a maximum concentration value of 89.28 μg/L. Additionally, antibiotic residues such as azithromycin and levofloxacin were also present at concentrations between 0.32-7.37 μg/L and 0.11-118.91 μg/L, respectively. In Cameroon, azithromycin was the most found antibiotic present at concentrations from 1.14 to 1.21 μg/L. In Madagascar instead, ceftriaxone (0.68-11.53 μg/L) and levofloxacin (0.15-0.30 μg/L) were commonly found. The bacterial phyla statistically significant different (P < 0,05) among participating countries were Proteobacteria, Patescibacteria and Dependentiae which were mainly abundant in waters sampled in Africa and, other phyla such as Firmicutes, Campylobacterota and Fusobacteriota were more abundant in Brazil. The phylum Caldisericota was only found in raw hospital wastewater samples from Madagascar. The canonical correspondence analysis results suggest significant correlation of azithromycin, meropenem and levofloxacin with bacteria families such as Enterococcaceae, Flavobacteriaceae, Deinococcaceae, Thermacetogeniaceae and Desulfomonilaceae, Spirochaetaceae, Methanosaetaceae, Synergistaceae, respectively. Water samples were also positive for SARS-CoV-2 with the lowest number of hospitalized COVID-19 patients in Madagascar (n = 7) and Brazil (n = 30). Our work provides new data about the bacterial community profile and the presence of pharmaceutical compounds in the hospital effluents from Brazil, Cameroon, and Madagascar, whose limited information is available. These compounds can exacerbate the spreading of antibiotic resistance and therefore pose a risk to public health.

Presence and Persistence of ESKAPEE Bacteria before and after Hospital Wastewater Treatment

The metagenomic surveillance of antimicrobial resistance in wastewater has been suggested as a methodological tool to characterize the distribution, status, and trends of antibiotic-resistant bacteria. In this study, a cross-sectional collection of samples of hospital-associated raw and treated wastewater were obtained from February to March 2020. Shotgun metagenomic sequencing and bioinformatic analysis were performed to characterize bacterial abundance and antimicrobial resistance gene analysis. The main bacterial phyla found in all the samples were as follows: Proteobacteria, Bacteroides, Firmicutes, and Actinobacteria. At the species level, ESKAPEE bacteria such as E. coli relative abundance decreased between raw and treated wastewater, but S. aureus, A. baumannii, and P. aeruginosa increased, as did the persistence of K. pneumoniae in both raw and treated wastewater. A total of 172 different ARGs were detected; blaOXA, blaVEB, blaKPC, blaGES, mphE, mef, erm, msrE, AAC(6'), ant(3″), aadS, lnu, PBP-2, dfrA, vanA-G, tet, and sul were found at the highest abundance and persistence. This study demonstrates the ability of ESKAPEE bacteria to survive tertiary treatment processes of hospital wastewater, as well as the persistence of clinically important antimicrobial resistance genes that are spreading in the environment.

Monitoring SARS-CoV-2 RNA in wastewater from a shared septic system and sub-sewershed sites to expand COVID-19 disease surveillance

Wastewater-based epidemiology has expanded as a tool for collecting COVID-19 surveillance data, but there is limited information on the feasibility of this form of surveillance within decentralized wastewater systems (e.g., septic systems). This study assessed SARS-CoV-2 RNA concentrations in wastewater samples from a septic system servicing a mobile home park (66 households) and from two pumping stations serving a similarly sized (71 households) and a larger (1,000 households) neighborhood within a nearby sewershed over 35 weeks in 2020. Also, raw wastewater from a hospital in the same sewershed was sampled. The mobile home park samples had the highest detection frequency (39/39 days) and mean concentration of SARS-CoV-2 RNA (2.7 × 107 gene copies/person/day for the N1) among the four sampling sites. N1 gene and N2 gene copies were highly correlated across mobile home park samples (Pearson's r = 0.93, p < 0.0001). In the larger neighborhood, new COVID-19 cases were reported every week during the sampling period; however, we detected SARS-CoV-2 RNA in 12% of the corresponding wastewater samples. The results of this study suggest that sampling from decentralized wastewater infrastructure can be used for continuous monitoring of SARS-CoV-2 infections.

The occurrence of SARS-CoV-2 in Tehran's municipal wastewater: performance of treatment systems and feasibility of wastewater-based epidemiology

Analyzing municipal wastewater for the presence of Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) helps to evaluate the efficacy of treatment systems in mitigating virus-related health risks. This research investigates wastewater treatment plants' (WWTPs) performance in the reduction of SARS-CoV-2 from municipal wastewater in Tehran, Iran. SARS-CoV-2 RNA was measured within sewers, at the inlets, and after the primary and secondary treatment stages of three main WWTPs. Within sewers, the average virus titer stood at 58,600 gc/L, while at WWTP inlets, it measured 38,136 gc/L. A substantial 67% reduction in virus titer was observed at the inlets, accompanied by a 2-log reduction post-primary treatment. Remarkably, the biological treatment process resulted in complete virus elimination across all plants. Additionally, a notable positive correlation (r > 0.8) was observed between temperature and virus titer in wastewater. Using wastewater-based epidemiology (WBE) technique and the estimated SARS-CoV-2 RNA shedding rates, the infection prevalence among populations served by WWTPs found to be between 0.128% to 0.577%. In conclusion, this research not only advances our understanding of SARS-CoV-2 dynamics within wastewater treatment systems but also provides practical insights for enhancing treatment efficiency and implementing the feasibility of WBE strategies in Tehran. These implications contribute to the broader efforts to protect public health and mitigate the impact of future viral outbreaks.

Graphical abstract

Discovery of novel RNA viruses through analysis of fungi-associated next-generation sequencing data

BACKGROUND

Like all other species, fungi are susceptible to infection by viruses. The diversity of fungal viruses has been rapidly expanding in recent years due to the availability of advanced sequencing technologies. However, compared to other virome studies, the research on fungi-associated viruses remains limited.

RESULTS

In this study, we downloaded and analyzed over 200 public datasets from approximately 40 different Bioprojects to explore potential fungal-associated viral dark matter. A total of 12 novel viral sequences were identified, all of which are RNA viruses, with lengths ranging from 1,769 to 9,516 nucleotides. The amino acid sequence identity of all these viruses with any known virus is below 70%. Through phylogenetic analysis, these RNA viruses were classified into different orders or families, such as Mitoviridae, Benyviridae, Botourmiaviridae, Deltaflexiviridae, Mymonaviridae, Bunyavirales, and Partitiviridae. It is possible that these sequences represent new taxa at the level of family, genus, or species. Furthermore, a co-evolution analysis indicated that the evolutionary history of these viruses within their groups is largely driven by cross-species transmission events.

CONCLUSIONS

These findings are of significant importance for understanding the diversity, evolution, and relationships between genome structure and function of fungal viruses. However, further investigation is needed to study their interactions.

Advances in Nucleic Acid Assays for Infectious Disease: The Role of Microfluidic Technology

Within the fields of infectious disease diagnostics, microfluidic-based integrated technology systems have become a vital technology in enhancing the rapidity, accuracy, and portability of pathogen detection. These systems synergize microfluidic techniques with advanced molecular biology methods, including reverse transcription polymerase chain reaction (RT-PCR), loop-mediated isothermal amplification (LAMP), and clustered regularly interspaced short palindromic repeats (CRISPR), have been successfully used to identify a diverse array of pathogens, including COVID-19, Ebola, Zika, and dengue fever. This review outlines the advances in pathogen detection, attributing them to the integration of microfluidic technology with traditional molecular biology methods and smartphone- and paper-based diagnostic assays. The cutting-edge diagnostic technologies are of critical importance for disease prevention and epidemic surveillance. Looking ahead, research is expected to focus on increasing detection sensitivity, streamlining testing processes, reducing costs, and enhancing the capability for remote data sharing. These improvements aim to achieve broader coverage and quicker response mechanisms, thereby constructing a more robust defense for global public health security.

Modelling and optimization of membrane process for removal of biologics (pathogens) from water and wastewater: Current perspectives and challenges

As one of the 17 sustainable development goals, the United Nations (UN) has prioritized "clean water and sanitation" (Goal 6) to reduce the discharge of emerging pollutants and disease-causing agents into the environment. Contamination of water by pathogenic microorganisms and their existence in treated water is a global public health concern. Under natural conditions, water is frequently prone to contamination by invasive microorganisms, such as bacteria, viruses, and protozoa. This circumstance has therefore highlighted the critical need for research techniques to prevent, treat, and get rid of pathogens in wastewater. Membrane systems have emerged as one of the effective ways of removing contaminants from water and wastewater However, few research studies have examined the synergistic or conflicting effects of operating conditions on newly developing contaminants found in wastewater. Therefore, the efficient, dependable, and expeditious examination of the pathogens in the intricate wastewater matrix remains a significant obstacle. As far as it can be ascertained, much attention has not recently been given to optimizing membrane processes to develop optimal operation design as related to pathogen removal from water and wastewater. Therefore, this state-of-the-art review aims to discuss the current trends in removing pathogens from wastewater by membrane techniques. In addition, conventional techniques of treating pathogenic-containing water and wastewater and their shortcomings were briefly discussed. Furthermore, derived mathematical models suitable for modelling, simulation, and control of membrane technologies for pathogens removal are highlighted. In conclusion, the challenges facing membrane technologies for removing pathogens were extensively discussed, and future outlooks/perspectives on optimizing and modelling membrane processes are recommended.

A scoping review of global SARS-CoV-2 wastewater-based epidemiology in light of COVID-19 pandemic

Recently, wastewater-based epidemiology (WBE) research has experienced a strong impetus during the Coronavirus disease 2019 (COVID-19) pandemic. However, a few technical issues related to surveillance strategies, such as standardized procedures ranging from sampling to testing protocols, need to be resolved in preparation for future infectious disease outbreaks. This review highlights the study characteristics, potential use of WBE and overview of methods, as well as methods utilized to detect severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) including its variant in wastewater. A literature search was performed electronically in PubMed and Scopus according to PRISMA guidelines for relevant peer-reviewed articles published between January 2020 and March 2022. The search identified 588 articles, out of which 221 fulfilled the necessary criteria and are discussed in this review. Most global WBE studies were conducted in North America (n = 75, 34 %), followed by Europe (n = 68, 30.8 %), and Asia (n = 43, 19.5 %). The review also showed that most of the application of WBE observed were to correlate SARS-CoV-2 ribonucleic acid (RNA) trends in sewage with epidemiological data (n = 90, 40.7 %). The techniques that were often used globally for sample collection, concentration, preferred matrix recovery control and various sample types were also discussed. Overall, this review provided a framework for researchers specializing in WBE to apply strategic approaches to their research questions in achieving better functional insights. In addition, areas that needed more in-depth analysis, data collection, and ideas for new initiatives were identified.

Urban wastewater-based epidemiology for multi-viral pathogen surveillance in the Valencian region, Spain

Wastewater-based epidemiology (WBE) has lately arised as a promising tool for monitoring and tracking viral pathogens in communities. In this study, we analysed WBE's role as a multi-pathogen surveillance strategy to detect the presence of several viral illness causative agents. Thus, an epidemiological study was conducted from October 2021 to February 2023 to estimate the weekly levels of Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2), Respiratory Syncytial virus (RSV), and Influenza A virus (IAV) in influent wastewater samples (n = 69). In parallel, a one-year study (October 2021 to October 2022) was performed to assess the presence of pathogenic human enteric viruses. Besides, monitoring of proposed viral fecal contamination indicators crAssphage and Pepper mild mottle virus (PMMoV) was also assessed, along with plaque counting of somatic coliphages. Genetic material of rotavirus (RV), human astrovirus (HAStV), and norovirus genogroup I (GI) and GII was found in almost all samples, while hepatitis A and E viruses (HAV and HEV) only tested positive in 3.77 % and 22.64 % of the samples, respectively. No seasonal patterns were overall found for enteric viruses, although RVs had a peak prevalence in the winter months. All samples tested positive for SARS-CoV-2 RNA, with a mean concentration of 5.43 log genome copies per liter (log GC/L). The tracking of the circulating SARS-CoV-2 variants of concern (VOCs) was performed by both duplex RT-qPCR and next generation sequencing (NGS). Both techniques reliably showed how the dominant VOC transitioned from Delta to Omicron during two weeks in Spain in December 2021. RSV and IAV viruses peaked in winter months with mean concentrations 6.40 and 4.10 log GC/L, respectively. Moreover, the three selected respiratory viruses strongly correlated with reported clinical data when normalised by wastewater physico-chemical parameters and presented weaker correlations when normalising sewage concentration levels with crAssphage or somatic coliphages titers. Finally, predictive models were generated for each respiratory virus, confirming high reliability on WBE data as an early-warning system and communities illness monitoring system. Overall, this study presents WBE as an optimal tool for multi-pathogen tracking reflecting viral circulation and diseases trends within a selected area, its value as a multi-pathogen early-warning tool stands out due to its public health interest.

Leveraging wastewater surveillance for managing the spread of SARS-CoV-2 and concerned pathogens during FIFA World Cup Qatar 2022

Wastewater-based epidemiology (WBE) has been proven effective for the monitoring of infectious disease outbreaks during mass gathering events and for timely public health interventions. As part of Qatar's efforts to monitor and combat the spread of infectious diseases during the FIFA World Cup Qatar 2022™ (FWC'22), wastewater surveillance was used to monitor the spread of SARS-CoV-2, human enterovirus, and poliovirus. The screening covered five major wastewater treatment plants servicing the event locations between October 2022 and January 2023. Viruses were concentrated from the wastewater samples by PEG precipitation, followed by qRT-PCR to measure the viral load in the wastewater. As expected, SARS-CoV-2 and enterovirus RNA were detected in all samples, while poliovirus was not detected. The concentration of SARS-CoV-2 was correlated with population density, such as areas surrounding the World Cup venues, and with the number of reported clinical cases. Additionally, we observed temporal fluctuations in viral RNA concentrations, with peak levels coinciding with the group stage matches of the FWC'22. This study has been useful in providing public health authorities with an efficient and cost-effective surveillance system for potential infectious disease outbreaks during mega-events.

Molecular basis of hippopotamus ACE2 binding to SARS-CoV-2

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has a wide range of hosts, including hippopotami, which are semi-aquatic mammals and phylogenetically closely related to Cetacea. In this study, we characterized the binding properties of hippopotamus angiotensin-converting enzyme 2 (hiACE2) to the spike (S) protein receptor binding domains (RBDs) of the SARS-CoV-2 prototype (PT) and variants of concern (VOCs). Furthermore, the cryo-electron microscopy (cryo-EM) structure of the SARS-CoV-2 PT S protein complexed with hiACE2 was resolved. Structural and mutational analyses revealed that L30 and F83, which are specific to hiACE2, played a crucial role in the hiACE2/SARS-CoV-2 RBD interaction. In addition, comparative and structural analysis of ACE2 orthologs suggested that the cetaceans may have the potential to be infected by SARS-CoV-2. These results provide crucial molecular insights into the susceptibility of hippopotami to SARS-CoV-2 and suggest the potential risk of SARS-CoV-2 VOCs spillover and the necessity for surveillance.

IMPORTANCE

The hippopotami are the first semi-aquatic artiodactyl mammals wherein SARS-CoV-2 infection has been reported. Exploration of the invasion mechanism of SARS-CoV-2 will provide important information for the surveillance of SARS-CoV-2 in hippopotami, as well as other semi-aquatic mammals and cetaceans. Here, we found that hippopotamus ACE2 (hiACE2) could efficiently bind to the RBDs of the SARS-CoV-2 prototype (PT) and variants of concern (VOCs) and facilitate the transduction of SARS-CoV-2 PT and VOCs pseudoviruses into hiACE2-expressing cells. The cryo-EM structure of the SARS-CoV-2 PT S protein complexed with hiACE2 elucidated a few critical residues in the RBD/hiACE2 interface, especially L30 and F83 of hiACE2 which are unique to hiACE2 and contributed to the decreased binding affinity to PT RBD compared to human ACE2. Our work provides insight into cross-species transmission and highlights the necessity for monitoring host jumps and spillover events on SARS-CoV-2 in semi-aquatic/aquatic mammals.

Wastewater tiling amplicon sequencing in sentinel sites reveals longitudinal dynamics of SARS-CoV-2 variants prevalence

The ongoing evolution of SARS-CoV-2 is a significant concern, especially with the decrease in clinical sequencing efforts, which impedes the ability of public health sectors to prepare for the emergence of new variants and potential COVID-19 outbreaks. Wastewater-based epidemiology (WBE) has been proposed as a surveillance program to detect and monitor the SARS-CoV-2 variants being transmitted in communities. However, research is limited in evaluating the effectiveness of wastewater collection at sentinel sites for monitoring disease prevalence and variant dynamics, especially in terms of inferring the epidemic patterns on a broader scale, such as at the state/province level. This study utilized a multiplexed tiling amplicon-based sequencing (ATOPlex) to track the longitudinal dynamics of variant of concern (VOC) in wastewater collected from municipalities in Queensland, Australia, spanning from 2020 to 2022. We demonstrated that wastewater epidemiology measured by ATOPlex exhibited a strong and consistent correlation with the number of daily confirmed cases. The VOC dynamics observed in wastewater closely aligned with the dynamic profile reported by clinical sequencing. Wastewater sequencing has the potential to provide early warning information for emerging variants. These findings suggest that WBE at sentinel sites, coupled with sensitive sequencing methods, provides a reliable and long-term disease surveillance strategy.

Quantification of multiple respiratory viruses in wastewater in the Kathmandu Valley, Nepal: Potential implications of wastewater-based epidemiology for community disease surveillance in developing countries

Despite being the major cause of death, clinical surveillance of respiratory viruses at the community level is very passive, especially in developing countries. This study focused on the surveillance of three respiratory viruses [severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), influenza A virus (IFV-A), and respiratory syncytial virus (RSV)] in the Kathmandu Valley, Nepal, by implication of wastewater-based epidemiology (WBE). Fifty-one untreated wastewater samples were from two wastewater treatment plants (WWTPs) between April and October 2022. Among eight combinations of the pre-evaluated methods, the combination of concentration by simple centrifugation, pretreatment by DNA/RNA Shield (Zymo Research), and extraction by the QIAamp Viral RNA Mini Kit (QIAGEN) showed the best performance for detecting respiratory viruses. Using this method with a one-step reverse transcription-quantitative polymerase chain reaction (RT-qPCR), SARS-CoV-2 RNA was successfully detected from both WWTPs (positive ratio, 100 % and 81 %) at concentrations of 5.6 ± 0.6 log10 copies/L from each WWTP. Forty-six SARS-CoV-2 RNA-positive samples were further tested for three mutation site-specific one-step RT-qPCR (L452R, T478K, and E484A/G339D), where G339D/E484A mutations were frequently detected in both WWTPs (96 %). IFV-A RNA was more frequently detected in WWTP A (84 %) compared to WWTP B (38 %). RSV RNA was also detected in both WWTPs (28 % and 8 %, respectively). This is the first study on detecting IFV-A and RSV in wastewater in Nepal, showing the applicability and importance of WBE for respiratory viruses in developing countries where clinical data are lacking.

Identifying outbreaks in sewer networks: An adaptive sampling scheme under network's uncertainty

Motivated by the implementation of a SARS-Cov-2 sewer surveillance system in Chile during the COVID-19 pandemic, we propose a set of mathematical and algorithmic tools that aim to identify the location of an outbreak under uncertainty in the network structure. Given an upper bound on the number of samples we can take on any given day, our framework allows us to detect an unknown infected node by adaptively sampling different network nodes on different days. Crucially, despite the uncertainty of the network, the method allows univocal detection of the infected node, albeit at an extra cost in time. This framework relies on a specific and well-chosen strategy that defines new nodes to test sequentially, with a heuristic that balances the granularity of the information obtained from the samples. We extensively tested our model in real and synthetic networks, showing that the uncertainty of the underlying graph only incurs a limited increase in the number of iterations, indicating that the methodology is applicable in practice.

A multilayer network model of interaction between rumor propagation and media influence

Rumors spread among the crowd have an impact on media influence, while media influence also has an impact on rumor dissemination. This article constructs a two-layer rumor media interaction network model, in which the rumors spread in the crowd are described using the susceptibility-apathy-propagation-recovery model, and the media influence is described using the corresponding flow model. The rationality of the model is studied, and then a detailed analysis of the model is conducted. In the simulation section, we undertake a sensitivity analysis of the crucial parameters within our model, focusing particularly on their impact on the basic reproduction number. According to data simulation analysis, the following conclusion can be drawn: First, when the media unilaterally influences the crowd and does not accept feedback from the crowd, the influence of the media will decrease to zero over time, which has a negative effect on the spread of rumors among the crowd (the degree of rumor dissemination decreases). Second, when the media does not affect the audience and accepts feedback from the audience, this state is similar to the media collecting information stage, which is to accept rumors from the audience but temporarily not disclose their thoughts. At this time, both the media influence and the spread of rumors in the audience will decrease. Finally, the model is validated using an actual dataset of rumors. The simulation results show an R-squared value of 0.9606, indicating that the proposed model can accurately simulate rumor propagation in real social networks.

Detection of SARS-CoV-2 and Omicron variant RNA in wastewater samples from Manila, Philippines

Manila, a highly urbanized city, is listed as one of the top cities with the highest recorded number of coronavirus disease 2019 (COVID-19) cases in the Philippines. This study aimed to detect and quantify the RNA of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and the Omicron variant in 51 wastewater samples collected from three locations in Manila, namely Estero de Santa Clara, Estero de Pandacan, which are open drainages, and a sewage treatment plant (STP) at De La Salle University-Manila, between July 2022 and February 2023. Using one-step reverse transcription-quantitative polymerase chain reaction, SARS-CoV-2 and Omicron variant RNA were detected in 78 % (40/51; 4.9 ± 0.5 log10 copies/L) and 60 % (24/40; 4.4 ± 0.3 log10 copies/L) of wastewater samples collected from all sampling sites, respectively. SARS-CoV-2 RNA was detected frequently at Estero de Santa Clara (88 %, 15/17); its highest concentration was at the STP (6.3 log10 copies/L). The Omicron variant RNA was present in the samples collected (4.4 ± 0.3 log10 copies/L) from all sampling sites, with the highest concentration at the STP (4.9 log10 copies/L). Regardless of normalization, using concentrations of pepper mild mottle virus RNA, SARS-CoV-2 RNA concentrations exhibited the highest positive correlation with COVID-19 reported cases in Manila 5 days after the clinical report. These findings revealed that wastewater-based epidemiology may aid in identifying and monitoring of the presence of pathogens in open drainages and STPs in the Philippines. This paper provides the first documentation on SARS-CoV-2 and the Omicron variant in wastewater from Manila.

Detection of Echovirus 11 lineage 1 in wastewater samples in Sicily

We report the presence of Echovirus 11 (E11) in wastewater in Sicily (Southern Italy), since August 2022. Overall, the 5.4 % of sewage samples (7/130) collected in 2022 were positives for E11 and then the percentage of E11-positive sewage samples reached the value of 27.27(18/66) in the first semester of 2023. Phylogenetic analysis of VP1 sequences showed for most E11-positive samples (16/25: 64 %) close genetic correlation (98.4-99.4 % nucleotide identity) to E11 lineage 1 strains involved in recently reported severe neonatal infections.

First Molecular Detection of SARS-CoV-2 in Sewage and Wastewater in Ghana

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is shed in the stool of infected individuals and can be detected in sewage and wastewater contaminated with infected stool. This study is aimed at detecting the virus and its potential survival in sewage and wastewater in Ghana. The cross-sectional study included samples from 16 validated environmental surveillance sites in 7 regions of Ghana. A total of 354 samples composed of wastewater (280) and sewage (74) were collected from November 2020 to November 2022. Overall, 17% of the samples were positive for SARS-CoV-2 by real-time PCR, with 6% in sewage and 11% in wastewater. The highest number of positive samples was collected from the Greater Accra Region (7.3%) with the least recorded in the Bono East Region (0.6%). Further characterization of the positive samples using the next-generation sequencing (NGS) approach yielded two variants: Alpha (B.1.1.7) and Delta (AY.36). Attempts to isolate SARS-CoV-2 in the Vero cell line were not successful probably due to the low viral load concentrations (Ct values > 35) or prolonged exposure to high temperatures rendering the virus noninfectious. Our findings suggest that SARS-CoV-2 RNA in sewage and wastewater may not be infectious, but the prevalence shows that the virus persists in the communities within Ghana.

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.

Global and genetic diversity of SARS-CoV-2 in wastewater

The analysis of SARS-CoV-2 in wastewater has enabled us to better understand the spread and evolution of the virus worldwide. To deepen our understanding of its epidemiological and genomic characteristics, we analyzed 10,147 SARS-CoV-2 sequences from 5 continents and 21 countries that were deposited in the GISAID database up until January 31, 2023. Our results revealed over 100 independent lineages of the virus circulating in water samples from March 2020 to January 2023, including variants of interest and concern. We observed four clearly defined periods of global distribution of these variants over time, with one variant being replaced by another. Interestingly, we found that SARS-CoV-2 water-borne sequences from different countries had a close phylogenetic relationship. Additionally, 40 SARS-CoV-2 water-borne sequences from Europe and the USA did not show any phylogenetic relationship with SARS-CoV-2 human sequences. We also identified a significant number of non-synonymous mutations, some of which were detected in previously reported cryptic lineages. Among the countries analyzed, France and the USA showed the highest degree of sequence diversity, while Austria reported the highest number of genomes (6,296). Our study provides valuable information about the epidemiological and genomic diversity of SARS-CoV-2 in wastewater, which can be employed to support public health initiatives and preparedness.

Meta-analysis of the SARS-CoV-2 positivity rate in municipal wastewater

The aim of this study is to conduct a systematic analysis of the SARS-CoV-2 levels in urban sewage and evaluate the associated positivity rates, thereby developing comprehensive insights into the epidemic situation and providing valuable inputs for the development of effective disease prevention and control strategies. The PubMed, Scopus, Embase, China National Knowledge Infrastructure, Wanfang Database, and VIP databases were systematically searched based on the predefined retrieval strategy. The literature published up to February 2023 was meticulously screened according to the predetermined inclusion and exclusion criteria, and the relevant data were extracted for subsequent integration. The quality assessment of the included studies adhered to the rigorous Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) Statement guidelines. The meta-analysis was conducted using Stata 17.0 software. The meta-analysis included a total of 34 studies, encompassing 8429 municipal wastewater samples. A random effects model was employed for the analysis, revealing an overall SARS-CoV-2 positivity rate of 53.7% in the municipal wastewater samples. The subgroup analyses demonstrated significant regional variations in the SARS-CoV-2 positivity rate in municipal wastewater, with Africa exhibiting the highest rate at 62.5% (95% confidence interval [CI] 47.4 ~ 76.0%) and Oceania displaying the lowest at 33.3% (95% CI 22.0 ~ 46.3%). However, the subgroup analyses based on the sampling site, strain prevalence period, and laboratory testing method did not yield any statistically significant differences. The SARS-CoV-2 positivity rate in wastewater is relatively high globally, although it exhibits regional disparities. Regions with larger populations and lower economic levels demonstrate higher viral detection rates in sewage. Different types of wastewater sampling sites can be employed to monitor distinct aspects of the COVID-19 pandemic. Continuous surveillance of SARS-CoV-2 in wastewater plays a pivotal role in complementing clinical data, helping to track outbreak progression across diverse regions.

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

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

SARS-CoV-2 presence in recreational seawater and evaluation of intestine permeability: experimental evidence of low impact on public health

Introduction

Coastal seawater pollution poses a public health risk due to the potential ingestion of contaminated water during recreational activities. Wastewater-based epidemiology has revealed the abundant presence of SARS-CoV-2 in seawater emitted from wastewater outlets. The objective of this research was to investigate the impact of seawater on SARS-CoV-2 infectivity to assess the safety of recreational activities in seawater.

Methods

Wild SARS-CoV-2 was collected from oral swabs of COVID-19 affected patients and incubated for up to 90 min using the following solutions: (a) standard physiological solution (control), (b) reconstructed seawater (3.5% NaCl), and (c) authentic seawater (3.8%). Samples were then exposed to two different host systems: (a) Vero E6 cells expressing the ACE2 SARS-CoV-2 receptor and (b) 3D multi-tissue organoids reconstructing the human intestine. The presence of intracellular virus inside the host systems was determined using plaque assay, quantitative real-time PCR (qPCR), and transmission electron microscopy.

Results

Ultrastructural examination of Vero E6 cells revealed the presence of virus particles at the cell surface and in replicative compartments inside cells treated with seawater and/or reconstituted water only for samples incubated up to 2 min. After a 90-min incubation, the presence of the virus and its infectivity in Vero E6 cells was reduced by 90%. Ultrastructural analysis performed in 3D epi-intestinal tissue did not reveal intact viral particles or infection signs, despite the presence of viral nucleic acid detected by qPCR. Indeed, viral genes (Orf1ab and N) were found in the intestinal luminal epithelium but not in the enteric capillaries. These findings suggest that the intestinal tissue is not a preferential entry site for SARS-CoV-2 in the human body. Additionally, the presence of hypertonic saline solution did not increase the susceptibility of the intestinal epithelium to virus penetration; rather, it neutralized its infectivity.

Conclusion

Our results indicate that engaging in recreational activities in a seawater environment does not pose a significant risk for COVID-19 infection, despite the possible presence of viral nucleic acid deriving from degraded and fragmented viruses.

A retrospective cohort study on early antibiotic use in vaccinated and unvaccinated COVID-19 patients

The bacteriophage behavior of SARS-CoV-2 during the acute and post-COVID-19 phases appears to be an important factor in the development of the disease. The early use of antibiotics seems to be crucial to inhibit disease progression-to prevent viral replication in the gut microbiome, and control toxicological production from the human microbiome. To study the impact of specific antibiotics on recovery from COVID-19 and long COVID (LC) taking into account: vaccination status, comorbidities, SARS-CoV-2 wave, time of initiation of antibiotic therapy and concomitant use of corticosteroids and nonsteroidal anti-inflammatory drugs (NSAIDs). A total of 211 COVID-19 patients were included in the study: of which 59 were vaccinated with mRNA vaccines against SARS-CoV-2 while 152 were unvaccinated. Patients were enrolled in three waves: from September 2020 to October 2022, corresponding to the emergence of the pre-Delta, Delta, and Omicron variants of the SARS-CoV-2 virus. The three criteria for enrolling patients were: oropharyngeal swab positivity or fecal findings; moderate symptoms with antibiotic intake; and measurement of blood oxygen saturation during the period of illness. The use of antibiotic combinations, such as amoxicillin with clavulanic acid (875 + 125 mg tablets, every 12 h) plus rifaximin (400 mg tablets every 12 h), as first choice, as suggested from the previous data, or azithromycin (500 mg tablets every 24 h), plus rifaximin as above, allows healthcare professionals to focus on the gut microbiome and its implications in COVID-19 disease during patient care. The primary outcome measured in this study was the estimated average treatment effect, which quantified the difference in mean recovery between patients receiving antibiotics and those not receiving antibiotics at 3 and 9 days after the start of treatment. In the analysis, both vaccinated and unvaccinated groups had a median illness duration of 7 days (interquartile range [IQR] 6-9 days for each; recovery crude hazard ratio [HR] = 0.94, p = 0.700). The median illness duration for the pre-Delta and Delta waves was 8 days (IQR 7-10 days), while it was shorter, 6.5 days, for Omicron (IQR 6-8 days; recovery crude HR = 1.71, p < 0.001). These results were confirmed by multivariate analysis. Patients with comorbidities had a significantly longer disease duration: median 8 days (IQR 7-10 days) compared to 7 days (IQR 6-8 days) for those without comorbidities (crude HR = 0.75, p = 0.038), but this result was not confirmed in multivariate analysis as statistical significance was lost. Early initiation of antibiotic therapy resulted in a significantly shorter recovery time (crude HR = 4.74, p < 0.001). Concomitant use of NSAIDs did not reduce disease duration and in multivariate analysis prolonged the disease (p = 0.041). A subgroup of 42 patients receiving corticosteroids for a median of 3 days (IQR 3-6 days) had a longer recovery time (median 9 days, IQR 8-10 days) compared to others (median 7 days, IQR 6-8 days; crude HR = 0.542, p < 0.001), as confirmed also by the adjusted HR. In this study, a statistically significant reduction in recovery time was observed among patients who received early antibiotic treatment. Early initiation of antibiotics played a crucial role in maintaining higher levels of blood oxygen saturation. In addition, it is worth noting that a significant number of patients who received antibiotics in the first 3 days and for a duration of 7 days, during the acute phase did not develop LC.

Identifying spatiotemporal trends of SARS-CoV-2 RNA in wastewater: from the perspective of upstream and downstream wastewater-based epidemiology (WBE)

Recently, many efforts have been made to address the rapid spread of newly identified COVID-19 virus variants. Wastewater-based epidemiology (WBE) is considered a potential early warning tool for identifying the rapid spread of this virus. This study investigated the occurrence of SARS-CoV-2 in eight wastewater treatment plants (WWTPs) and their sewerage systems which serve most of the population in Taoyuan City, Taiwan. Across the entire study period, the wastewater viral concentrations were correlated with the number of COVID-19 cases in each WWTP (Spearman's r = 0.23-0.76). In addition, it is confirmed that several treatment technologies could effectively eliminate the virus RNA from WWTP influent (> 90%). On the other hand, further results revealed that an inverse distance weighted (IDW) interpolation and hotspot model combined with the geographic information system (GIS) method could be applied to analyze the spatiotemporal variations of SARS-CoV-2 in wastewater from the sewer system. In addition, socio-economic factors, namely, population density, land use, and income tax were successfully identified as the potential drivers which substantially affected the onset of the COVID-19 outbreak in Taiwan. Finally, the data obtained from this study can provide a powerful tool in public health decision-making not only in response to the current epidemic situation but also to other epidemic issues in the future.

A Comparative Analysis of Molecular Biological Methods for the Detection of SARS-CoV-2 and Testing the In Vitro Infectivity of the Virus

The virus discovered in 2019 in the city of Wuhan, China, which was later identified as SARS-CoV-2 and which spread to the level of a pandemic, put diagnostic methods to the test. Early in the pandemic, we developed a nested PCR assay for the detection of SARS-CoV-2, which we validated and applied to detect the virus in feline samples. The present study describes the application of the nested PCR test in parallel with LAMP for the detection of the virus in 427 nasopharyngeal and oropharyngeal human samples taken between October 2020 and January 2022. Of the swabs tested, there were 43 positives, accounting for 10.1% of all samples tested, with the negatives numbering 382, i.e., 89.5%, and there were 2 (0.4%) invalid ones. The nPCR results confirmed those obtained by using LAMP, with results concordant in both methods. Nasal swabs tested using nPCR confirmed the results of oropharyngeal and nasopharyngeal swab samples tested using LAMP and nPCR. The focus of the discussion is on the two techniques: the actual practical application of the laboratory-developed assays and the diagnostic value of nasal samples. The nPCR used is a reliable and sensitive technique for the detection of SARS-CoV-2 in nasopharyngeal, oropharyngeal, and nasal swab samples. However, it has some disadvantages related to the duration of the entire process, as well as a risk of contamination. Experiments were performed to demonstrate the infectivity of the virus from the positive isolates in vitro. A discrepancy was reported between direct and indirect methods of testing the virus and accounting for its ability to cause infection in vitro.

Comparison of adsorption-extraction (AE) workflows for improved measurements of viral and bacterial nucleic acid in untreated wastewater

The lack of standardized methods and large differences in virus concentration and extraction workflows have hampered Severe Acute Respiratory Syndrome (SARS-CoV-2) wastewater surveillance and data reporting practices. Numerous studies have shown that adsorption-extraction (AE) method holds promise, yet several uncertainties remain regarding the optimal AE workflow. Several procedural components may influence the recovered concentrations of target nucleic acid, including membrane types, homogenization instruments, speed and duration, and lysis buffer. In this study, 42 different AE workflows that varied these components were compared to determine the optimal workflow by quantifying endogenous SARS-CoV-2, human adenovirus 40/41 (HAdV 40/41), and a bacterial marker gene of fecal contamination (Bacteroides HF183). Our findings suggest that the workflow chosen had a significant impact on SARS-CoV-2 concentrations, whereas it had minimal impact on HF183 and no effect on HAdV 40/41 concentrations. When comparing individual components in a workflow, such as membrane type (MF-Millipore™ 0.45 μm MCE vs. Isopore™ 0.40 μm), we found that they had no impact on SARS-CoV-2, HAdV 40/41, and HF183 concentrations. This suggests that at least some consumables and equipment are interchangeable. Buffer PM1 + TRIzol-based workflows yielded higher concentrations of SARS-CoV-2 than other workflows. HF183 concentrations were higher in workflows without chloroform. Similarly, higher homogenization speeds (5000-10,000 rpm) led to increased concentrations of SARS-CoV-2 and HF183 but had no effect on HAdV 40/41. Our findings indicate that minor enhancements to the AE workflow can improve the recovery of viruses and bacteria from the wastewater, leading to improved outcomes from wastewater surveillance efforts.

Development of highly sensitive one-step reverse transcription-quantitative PCR for SARS-CoV-2 detection in wastewater

The emergence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants is a major public health concern that has highlighted the need to monitor circulating strains to better understand the coronavirus disease 2019 (COVID-19) pandemic. This study was carried out to monitor SARS-CoV-2 RNA and its variant-specific mutations in wastewater using reverse transcription-quantitative polymerase chain reaction (RT-qPCR). One-step RT-qPCR using the SARS-CoV-2 Detection RT-qPCR Kit for Wastewater (Takara Bio), which amplified two N-gene regions simultaneously using CDC N1 and N2 assays with a single fluorescence dye, demonstrated better performance in detecting SARS-CoV-2 RNA (positive ratio, 66 %) compared to two-step RT-qPCR using CDC N1 or N2 assay (40 % each, and 52 % when combined), with significantly lower Ct values. The one-step RT-qPCR assay detected SARS-CoV-2 RNA in 59 % (38/64) of influent samples collected from a wastewater treatment plant in Japan between January 2021 and March 2022. The correlation between the concentration of SARS-CoV-2 RNA in the wastewater and the number of COVID-19 cases reported each day for 7 days pre- and post-sampling was significant (p < 0.05, r = 0.76 ± 0.03). Thirty-one influent samples which showed two-well positive for SARS-CoV-2 RNA were further tested by six mutations site-specific one-step RT-qPCR (E484K, L452R, N501Y, T478K, G339D, and E484A mutations). The N501Y mutation was detected between March and June 2021 but was replaced by the L452R and T478K mutations between July and October 2021, reflecting the shift from Alpha to Delta variants in the study region. The G339D and E484A mutations were identified in January 2022 and later when the incidence of the Omicron variant peaked. These findings indicate that wastewater-based epidemiology has the epidemiological potential to complement clinical tests to track the spread of COVID-19 and monitor variants circulating in communities.

Molecular epidemiology of SARS-CoV-2 in Northern South Africa: wastewater surveillance from January 2021 to May 2022

Introduction

Wastewater-based genomic surveillance of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) provides a comprehensive approach to characterize evolutionary patterns and distribution of viral types in a population. This study documents the molecular epidemiology of SARS-CoV-2, in Northern South Africa, from January 2021 to May 2022.

Methodology

A total of 487 wastewater samples were collected from the influent of eight wastewater treatment facilities and tested for SARS-CoV-2 RNA using quantitative reverse transcriptase polymerase chain reaction (qRT-PCR). SARS-CoV-2 positive samples with genome copies/mL ≥1,500 were subjected to allele-specific genotyping (ASG) targeting the Spike protein; 75 SARS-CoV-2 positive samples were subjected to whole genome sequencing (WGS) on the ATOPlex platform. Variants of concern (VoC) and lineages were assigned using the Nextclade and PangoLIN Software. Concordance for VoC between ASG and WGS analyses was determined. Sequence relationship was determined by phylogenetic analysis.

Results

Seventy-five percent (365/487) of the influent samples were positive for SARS-CoV-2 RNA. Delta and Omicron VoC were more predominant at a prevalence of 45 and 32%, respectively, and they were detected as early as January and February 2021, while Beta VoC was least detected at a prevalence of 5%. A total of 11/60 (18%) sequences were assigned lineages and clades only, but not a specific VoC name. Phylogenetic analysis was used to investigate the relationship of these sequences to other study sequences, and further characterize them. Concordance in variant assignment between ASG and WGS was seen in 51.2% of the study sequences. There was more intra-variant diversity among Beta VoC sequences; mutation E484K was absent. Three previously undescribed mutations (A361S, V327I, D427Y) were seen in Delta VoC.

Discussion and Conclusion

The detection of Delta and Omicron VoCs in study sites earlier in the outbreak than has been reported in other regions of South Africa highlights the importance of population-based approaches over individual sample-based approaches in genomic surveillance. Inclusion of non-Spike protein targets could improve the specificity of ASG, since all VoCs share similar Spike protein mutations. Finally, continuous molecular epidemiology with the application of sensitive technologies such as next generation sequencing (NGS) is necessary for the documentation of mutations whose implications when further investigated could enhance diagnostics, and vaccine development efforts.

Removal of intI1, ARGs, and SARS-CoV-2 and changes in bacterial communities in four sewage treatment facilities

Currently, discharge regulations for wastewater treatment plants (WWTPs) are based on conventional parameters, but more is needed to ensure safe water reuse. In particular, emerging pollutants, as antimicrobials and antibiotic resistance genes (ARGs), are not considered. This research focuses on the fate of emerging biological contaminants during wastewater treatment in Mexico City. intI1 and the ARGs cphA-02, OXA-10 and sul1 were analyzed by qPCR; pathogenic bacteria species were characterized by high throughput sequencing of complete 16S rRNA gene, and fragments of SARS-CoV-2 were quantified by RT-qPCR. Conventional parameters (chemical oxygen demand and coliform bacteria) were also determined. Two sampling campaigns (rainy and dry seasons) were carried out in four municipal WWTPs in Mexico City, representing five biological treatment processes: conventional activated sludge, extended aeration activated sludge, membrane bioreactor, direct anaerobic digestion, and constructed wetland, followed by ultraviolet light or chlorine disinfection. In most cases, gene fragments of SARS-CoV-2 were eliminated below the detection limit of RT-qPCR. The abundance of intI1 positively correlated with the sul1, OXA-10, and cphA-02 abundances; intI1 and the ARGs here studied were partially removed in the WWTPs, and in most cases, the number of copies per second discarded in the sludge were higher those in the effluent. The treatment processes decreased the abundance of dominant bacterial groups in the raw wastewater, while enriching bacterial groups in the effluent and the biological sludge, with possible pollutant removal capabilities. Bacterial communities in the raw wastewater showed the predominance of the genus Arcobacter (from 62.4 to 86.0 %) containing potentially pathogenic species. Additionally, DNA of some species persisted after the treatment processes: A. johnsonii, A. junii, A. caviae, A. hydrophila, A. veronii, A. butzleri, A. cryaerophilus, Chryseobacterium indologenes, Hafnia paralvei, M. osloensis, Pseudomonas putida and Vibrio cholerae, which deserves special attention in future regulation for safe water reuse.

Interlaboratory comparison using inactivated SARS-CoV-2 variants as a feasible tool for quality control in COVID-19 wastewater monitoring

Wastewater-based SARS-CoV-2 epidemiology (WBE) has proven as an excellent tool to monitor pandemic dynamics supporting individual testing strategies. WBE can also be used as an early warning system for monitoring the emergence of novel pathogens or viral variants. However, for a timely transmission of results, sophisticated sample logistics and analytics performed in decentralized laboratories close to the sampling sites are required. Since multiple decentralized laboratories commonly use custom in-house workflows for sample purification and PCR-analysis, comparative quality control of the analytical procedures is essential to report reliable and comparable results. In this study, we performed an interlaboratory comparison at laboratories specialized for PCR and high-throughput-sequencing (HTS)-based WBE analysis. Frozen reserve samples from low COVID-19 incidence periods were spiked with different inactivated authentic SARS-CoV-2 variants in graduated concentrations and ratios. Samples were sent to the participating laboratories for analysis using laboratory specific methods and the reported viral genome copy numbers and the detection of viral variants were compared with the expected values. All PCR-laboratories reported SARS-CoV-2 genome copy equivalents (GCE) for all spiked samples with a mean intra- and inter-laboratory variability of 19 % and 104 %, respectively, largely reproducing the spike-in scheme. PCR-based genotyping was, in dependence of the underlying PCR-assay performance, able to predict the relative amount of variant specific substitutions even in samples with low spike-in amount. The identification of variants by HTS, however, required >100 copies/ml wastewater and had limited predictive value when analyzing at a genome coverage below 60 %. This interlaboratory test demonstrates that despite highly heterogeneous isolation and analysis procedures, overall SARS-CoV-2 GCE and mutations were determined accurately. Hence, decentralized SARS-CoV-2 wastewater monitoring is feasible to generate comparable analysis results. However, since not all assays detected the correct variant, prior evaluation of PCR and sequencing workflows as well as sustained quality control such as interlaboratory comparisons are mandatory for correct variant detection.

Surveillance of COVID-19 and influenza A(H1N1) prevalence in China via medicine-based wastewater biomarkers

The simultaneous monitoring of individual or multiple diseases can be achieved by selecting therapeutic medicines used to treat the primary symptoms of the condition as biomarkers in wastewater. This study proposes a novel approach to monitor the prevalence of COVID-19 and influenza A (H1N1) by selecting nine medicines to serve as biomarkers, including three antipyretics, three antivirals, and three cough suppressants. To verify our approach, wastewater samples were collected from seventeen urban and five rural wastewater treatment plants (WWTPs) in a Chinese city over a period of one year. The use of antipyretics increased notably during the COVID-19 pandemic, while the consumption of antivirals for influenza A (H1N1) rose in the post-COVID-19 pandemic period, indicating a minor spike in the occurrence of influenza A (H1N1) after the COVID-19 pandemic. Fever is a significant symptom of COVID-19 and can serve as a reliable indicator of disease prevalence. Our research found that the prevalence of COVID-19 in urban areas was significantly higher (at 78.5 %, 95 % CI: 73.4 % - 83.9 %) than in rural areas (with a prevalence of 48.1 %, 95 % CI: 42.4 % - 53.8 %). The prevalence of COVID-19 in urban areas in this study was consistent with the data reported by the Chinese center for Disease Control and Prevention (82.4 %). Continuous monitoring of WWTPs in urban areas with fluctuating populations and complex demographics can provide early disease warning. Our results demonstrate the feasibility of evaluating community disease prevalence by selecting major therapeutic medicines as biomarkers in wastewater.

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.

Electrochemical degradation of favipiravir (anti-viral) drug from aqueous solution: optimization of operating parameters using the response surface method

The aim of the current study is to investigate the efficacy of the electro-Fenton process in the degradation of favipiravir drugs from aqueous solutions, which has increased in use as a result of the COVID-19 pandemic. The Response Surface Methodology (RSM) was developed using a Central Composite Design (CCD) in which five independent variables, including Fe2+ concentration, current density, initial FVP concentration, pH, and reaction time, were coded with high and low levels, and the maximum removal percentage of FVP (97.8%) and COD (91.65%) were determined as responses. In the EF process, 530 mg/L H2O2 was produced in-situ by cathodic reduction of O2 in aqueous solution and thus FVP has been successfully oxidized through hydroxyl radicals. The H2O2/Fe2+ ratio was determined to be 0.51 under optimum conditions. At the end of the experiment, the maximum energy consumption was found to be 2.12 kWh per g COD. The FVP was completely mineralized in a very short time by the EF process, according to the LC-MS/MS examination. The EF process followed the pseudo first-order kinetic model with the rate constants of 0.023, 0.016 and 0.006 1/min for pH 2, 3 and 4, respectively. According to the findings of this study, the electro-Fenton process is an effective method for removing FVP from aqueous solutions. To the authors' knowledge, this is the first study to show the degradation and optimum conditions of FVP in aqueous solution using the electro-Fenton (EF) process.

A narrative review of alternative transmission routes of COVID 19: what we know so far

The Coronavirus disease 19 (COVID-19) pandemics, caused by severe acute respiratory syndrome coronaviruses, SARS-CoV-2, represent an unprecedented public health challenge. Beside person-to-person contagion via airborne droplets and aerosol, which is the main SARS-CoV-2's route of transmission, alternative modes, including transmission via fomites, food and food packaging, have been investigated for their potential impact on SARS-CoV-2 diffusion. In this context, several studies have demonstrated the persistence of SARS-CoV-2 RNA and, in some cases, of infectious particles on exposed fomites, food and water samples, confirming their possible role as sources of contamination and transmission. Indeed, fomite-to-human transmission has been demonstrated in a few cases where person-to-person transmission had been excluded. In addition, recent studies supported the possibility of acquiring COVID-19 through the fecal-oro route; the occurrence of COVID-19 gastrointestinal infections, in the absence of respiratory symptoms, also opens the intriguing possibility that these cases could be directly related to the ingestion of contaminated food and water. Overall, most of the studies considered these alternative routes of transmission of low epidemiological relevance; however, it should be considered that they could play an important role, or even be prevalent, in settings characterized by different environmental and socio-economic conditions. In this review, we discuss the most recent findings regarding SARS-CoV-2 alternative transmission routes, with the aim to disclose what is known about their impact on COVID-19 spread and to stimulate research in this field, which could potentially have a great impact, especially in low-resource contexts.

Development of an early alert model for pandemic situations in Germany

The COVID-19 pandemic has pointed out the need for new technical approaches to increase the preparedness of healthcare systems. One important measure is to develop innovative early warning systems. Along those lines, we first compiled a corpus of relevant COVID-19 related symptoms with the help of a disease ontology, text mining and statistical analysis. Subsequently, we applied statistical and machine learning (ML) techniques to time series data of symptom related Google searches and tweets spanning the time period from March 2020 to June 2022. In conclusion, we found that a long-short-term memory (LSTM) jointly trained on COVID-19 symptoms related Google Trends and Twitter data was able to accurately forecast up-trends in classical surveillance data (confirmed cases and hospitalization rates) 14 days ahead. In both cases, F1 scores were above 98% and 97%, respectively, hence demonstrating the potential of using digital traces for building an early alert system for pandemics in Germany.

Response of wastewater-based epidemiology predictor for the second wave of COVID-19 in Ahmedabad, India: A long-term data Perspective

In this work, we present an eight-month longitudinal study of wastewater-based epidemiology (WBE) in Ahmedabad, India, where wastewater surveillance was introduced in September 2020 after the successful containment of the first wave of COVID-19 to predict the resurge of the infection during the second wave of the pandemic. The study aims to elucidate the weekly resolution of the SARS-CoV-2 RNA data for eight months in wastewater samples to predict the COVID-19 situation and identify hotspots in Ahmedabad. A total of 287 samples were analyzed for SARS-CoV-2 RNA using RT-PCR, and Spearman's rank correlation was applied to depict the early warning potential of WBE. During September 2020 to April 2021, the increasing number of positive wastewater influent samples correlated with the growing number of confirmed clinical cases. It also showed clear evidence of early detection of the second wave of COVID-19 in Ahmedabad (March 2021). 258 out of a total 287 samples were detected positive with at least two out of three SARS-CoV-2 genes (N, ORF- 1 ab, and S). Monthly variation represented a significant decline in all three gene copies in October compared to September 2020, followed by an abrupt increase in November 2020. A similar increment in the gene copies was observed in March and April 2021, which would be an indicator of the second wave of COVID-19. A lead time of 1-2 weeks was observed in the change of gene concentrations compared with clinically confirmed cases. Measured wastewater ORF- 1 ab gene copies ranged from 6.1 x 102 (October 2020) to 1.4 x 104 (November 2020) copies/mL, and wastewater gene levels typically lead to confirmed cases by one to two weeks. The study highlights the value of WBE as a monitoring tool to predict waves within a pandemic, identify local disease hotspots within a city, and guide rapid management interventions.

Comparing solid-based concentration methods for rapid and efficient recovery of SARS-CoV-2 for wastewater surveillance

As wastewater-based surveillance of SARS-CoV-2 attracts interest globally, there is a need to evaluate and identify rapid and efficient methods for concentrating enveloped viruses in wastewater. When comparing five precipitation/flocculation-based concentration methods (including aluminum hydroxide adsorption-precipitation, AHAP; zinc acetate precipitation, ZAP; skimmed milk flocculation, SMF; FeCl3 precipitation, FCP; and direct centrifugation, DC), AHAP was found to be the most efficient method in terms of seeded BCoV recovery (50.2 %). Based on the BCoV recovery efficiency and turnaround time, the AHAP and DC methods were selected and tested on five additional wastewater samples containing both seeded BCoV and indigenous wastewater SARS-CoV-2 RNA. The BCoV recovery (DC: average=30.1 %, sx =14.7 %; AHAP: average=33.0 %, sx =14.2 %) and SARS-CoV-2 based on the N2 gene assay (DC: average=3.6 ×103 gene copies or GC/mL, sx =1.9 × 103 GC/mL; AHAP: average=3.0 ×103 GC/mL, sx =2.0 ×103 GC/mL) of both methods were not significantly different in solid fraction (p = 0.89). This study showed significant higher BCoV recovery and SARS-CoV-2 viral RNA in wastewater solid fraction (p = 0.006) than liquid fraction. Our result suggests that the solid fraction of wastewater samples is more suitable for recovering enveloped viruses from wastewater, and the DC and AHAP methods equally provide suitably rapid, cost-effective, and significantly higher recovery of SARS-CoV-2 viral RNA in wastewater samples.

Evaluation of concentration procedures, sample pre-treatment, and storage condition for the detection of SARS-CoV-2 in wastewater

Crucial information on the pandemic's spread has been gathered by monitoring the trend of SARS-CoV-2 in wastewater. This surveillance has highlighted that the initial concentration is a critical step of the analytical procedure due to the low viral titer that may be present in this matrix. This paper presents the results of the evaluation of two different wastewater concentration protocols to determine the most efficient and cost-effective. The two methods tested were the following: (a) a biphasic separation system with PEG-dextran and (b) a PEG/NaCl precipitation protocol. Other aspects of the detection method were also investigated including the influence of storage temperature on virus recovery and the heat treatment of pasteurization, which aims to make samples safer for operators and the environment. The PEG/NaCl precipitation method was found to perform better than the biphasic separation system, allowing for more sensitive identification of the presence of the virus and the detection of a higher viral titer than that identified with the biphasic separation in all results. Storage of the samples at 4.3±0.2°C for up to 3 weeks did not adversely affect the virus titer and the pasteurization pre-treatment increases operator safety and maintains the identification of the viral concentration.

Potential transmission of SARS-CoV-2 through microplastics in sewage: A wastewater-based epidemiological review

In light of the current COVID-19 pandemic caused by the virus SARS-CoV-2, there is an urgent need to identify and investigate the various pathways of transmission. In addition to contact and aerosol transmission of the virus, this review investigated the possibility of its transmission via microplastics found in sewage. Wastewater-based epidemiological studies on the virus have confirmed its presence and persistence in both influent sewage as well as treated ones. The hypothesis behind the study is that the huge amount of microplastics, especially Polyvinyl Chloride and Polyethylene particles released into the open waters from sewage can become a good substrate and vector for microbes, especially Polyvinyl Chloride and Polyethylene particles, imparting stability to microbes and aiding the "plastisphere" formation. A bibliometric analysis highlights the negligence of research toward plastispheres and their presence in sewage. The ubiquity of microplastics and their release along with the virus into the open waters increases the risk of viral plastispheres. These plastispheres may be ingested by aquatic organisms facilitating reverse zoonosis and the commercial organisms already reported with accumulating microplastics through the food chain poses a risk to human populations as well. Reliance of high population density areas on open waters served by untreated sewage in economically less developed countries might bring back viral transmission.

Comparison of ordinary reverse transcription real-time polymerase chain reaction (qRT-PCR) with a newly developed one-step single-tube nested real-time RT-PCR (OSN-qRT-PCR) for sensitive detection of SARS-CoV-2 in wastewater

Wastewater monitoring has proven to be an important approach to detecting and controlling the development of the SARS-CoV-2 pandemic. Various tests based on reverse transcription real-time PCR (qRT-PCR) have been developed and used for the detection of SARS-CoV-2 in wastewater samples. In this study, we attempted to increase the sensitivity of qRT-PCR by developing a one-step single-tube nested qRT-PCR assay (OSN-qRT-PCR). Two variants were developed, oriented to nucleocapsid phosphoprotein gene (N) and to spike protein gene (S), respectively. The performance of conventional qRT-PCR assays oriented to these genes with two novel OSN-qRT-PCR assays were firstly optimized using wastewater artificially contaminated with two encapsidated RNA mimic systems harboring a portion either N or S gene (ENRM and ESRM, respectively). The assays were coupled to a polyethylene glycol-based RNA precipitation/extraction method and applied to detect SARS-CoV-2 in wastewater samples from four cities in Slovakia. Both novel OSN-qRT-PCR assays demonstrated higher detection rates than the ordinary qRT-PCR counterparts. The virus levels in the analyzed wastewater samples had a high or very high relation with the numbers of clinical cases in the monitored regions. In fact, correlation with a 3-, 4-, or 5-day temporal offset was revealed. The OSN-qRT-PCR assays demonstrated robustness, mainly in samples with low viral loads.

SARS-CoV-2 RNA in Wastewater and Bivalve Mollusk Samples of Campania, Southern Italy

SARS-CoV-2 can be detected in the feces of infected people, consequently in wastewater, and in bivalve mollusks, that are able to accumulate viruses due to their ability to filter large amounts of water. This study aimed to monitor SARS-CoV-2 RNA presence in 168 raw wastewater samples collected from six wastewater treatment plants (WWTPs) and 57 mollusk samples obtained from eight harvesting sites in Campania, Italy. The monitoring period spanned from October 2021 to April 2022, and the results were compared and correlated with the epidemiological situation. In sewage, the ORF1b region of SARS-CoV-2 was detected using RT-qPCR, while in mollusks, three targets-RdRp, ORF1b, and E-were identified via RT-dPCR. Results showed a 92.3% rate of positive wastewater samples with increased genomic copies (g.c.)/(day*inhabitant) in December-January and March-April 2022. In the entire observation period, 54.4% of mollusks tested positive for at least one SARS-CoV-2 target, and the rate of positive samples showed a trend similar to that of the wastewater samples. The lower SARS-CoV-2 positivity rate in bivalve mollusks compared to sewages is a direct consequence of the seawater dilution effect. Our data confirm that both sample types can be used as sentinels to detect SARS-CoV-2 in the environment and suggest their potential use in obtaining complementary information on SARS-CoV-2.

Long-term study on wastewater SARS-CoV-2 surveillance across United Arab Emirates

Wastewater-based epidemiology (WBE) demonstrates an efficient tool to monitor and predict SARS-CoV-2 community distribution. Many countries across the world have adopted the technique, however, most of these studies were conducted for a short duration with a limited sampling size. In this study, long-term reliability and quantification of wastewater SARS-CoV-2 surveillance is reported via analyzing 16,858 samples collected from 453 different locations across the United Arab Emirates (UAE) from May 2020 to June 2022. The collected composite samples were first incubated at 60 °C followed by filtration, concentration, and then RNA extraction using commercially available kits. The extracted RNA was then analyzed by one-step RT-qPCR and RT-ddPCR, and the data was compared to the reported clinical cases. The average positivity rate in the wastewater samples was found to be 60.61 % (8.41-96.77 %), however, the positivity rate obtained from the RT-ddPCR was significantly higher than the RT-qPCR suggesting higher sensitivity of RT-ddPCR. Time-lagged correlation analysis indicated an increase in positive cases in the wastewater samples when the clinical positive cases declined suggesting that wastewater data are highly affected by the unreported asymptomatic, pre-symptomatic and recovering individuals. The weekly SARS-CoV-2 viral count in the wastewater samples are positively correlated with the diagnosed new clinical cases throughout the studied period and the studied locations. Viral count in wastewater peaked approximately one to two weeks prior to the peaks appearing in active clinical cases indicating that wastewater viral concentrations are effective in predicting clinical cases. Overall, this study further confirms the long-term sensitivity and robust approach of WBE to detect trends in SARS-CoV-2 spread and helps contribute to pandemic management.