Computational analysis of SARS-CoV-2/COVID-19 surveillance by wastewater-based epidemiology locally and globally: Feasibility, economy, opportunities and challenges

Wastewater-Based Epidemiology for COVID-19: Handling qPCR Nondetects and Comparing Spatially Granular Wastewater and Clinical Data Trends

Wastewater-based epidemiology (WBE) is a useful complement to clinical testing for managing COVID-19. While community-scale wastewater and clinical data frequently correlate, less is known about subcommunity relationships between the two data types. Moreover, nondetects in qPCR wastewater data are typically handled through methods known to bias results, overlooking perhaps better alternatives. We address these knowledge gaps using data collected from September 2020-June 2021 in Davis, California (USA). We hypothesize that coupling the expectation maximization (EM) algorithm with the Markov Chain Monte Carlo (MCMC) method could improve estimation of "missing" values in wastewater qPCR data. We test this hypothesis by applying EM-MCMC to city wastewater treatment plant data and comparing output to more conventional nondetect handling methods. Dissimilarities in results (i) underscore the importance of specifying nondetect handling method in reporting and (ii) suggest that using EM-MCMC may yield better agreement between community-scale clinical and wastewater data. We also present a novel framework for spatially aligning clinical data with wastewater data collected upstream of a treatment plant (i.e., distributed across a sewershed). Applying the framework to data from Davis reveals reasonable agreement between wastewater and clinical data at highly granular spatial scales-further underscoring the public-health value of WBE.

RNA in Municipal Wastewater Reveals Magnitudes of COVID-19 Outbreaks across Four Waves Driven by SARS-CoV-2 Variants of Concern

There are no standardized protocols for quantifying severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in wastewater to date, especially for population normalization. Here, a pipeline was developed, applied, and assessed to quantify SARS-CoV-2 and key variants of concern (VOCs) RNA in wastewater at Saskatoon, Canada. Normalization approaches using recovery ratio and extraction efficiency, wastewater parameters, or population indicators were assessed by comparing to daily numbers of new cases. Viral load was positively correlated with daily new cases reported in the sewershed. Wastewater surveillance (WS) had a lead time of approximately 7 days, which indicated surges in the number of new cases. WS revealed the variant α and δ driving the third and fourth wave, respectively. The adjustment with the recovery ratio and extraction efficiency improved the correlation between viral load and daily new cases. Normalization of viral concentration to concentrations of the artificial sweetener acesulfame K improved the trend of viral load during the Christmas and New Year holidays when populations were dynamic and variable. Acesulfame K performed better than pepper mild mottle virus, creatinine, and ammonia for population normalization. Hence, quality controls to characterize recovery ratios and extraction efficiencies and population normalization with acesulfame are promising for precise WS programs supporting decision-making in public health.

Molecular Monitoring of SARS-CoV-2 in Different Sewage Plants in Venice and the Implications for Genetic Surveillance

Wastewater-based epidemiology is now widely used as an indirect tool to monitor the spread of SARS-CoV-2. In this study, five different sample matrices representing diverse phases of the wastewater treatment process were collected during the second wave of SARS-CoV-2 from two wastewater treatment plants (WWTPs) serving the Civil Hospital and Sacca Fisola island in Venice, Italy. Positive SARS-CoV-2 detections occurred at both WWTPs, and data on viral genome detection rate and quantification suggest that the pellet (i.e., the particulate resulting from the influent) is a sensitive matrix that permits reliable assessment of infection prevalence while reducing time to results. On the contrary, analysis of post-treatment matrices provides evidence of the decontamination efficacy of both WWTPs. Finally, direct sequencing of wastewater samples enabled us to identify B.1.177 and B.1.160 as the prevalent SARS-CoV-2 lineages circulating in Venice at the time of sampling. This study confirmed the suitability of wastewater testing for studying SARS-CoV-2 circulation and established a simplified workflow for the prompt detection and characterization of the virus.

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.

Sentinel Surveillance of SARS-CoV-2 Rates and Equity Impacts using Labor and Delivery Patients in Phoenix, Arizona

Proactive management of SARS-CoV-2 requires timely and complete population data to track the evolution of the virus and identify at risk populations. However, many cases are asymptomatic and are not easily discovered through traditional testing efforts. Sentinel surveillance can be used to estimate the prevalence of infections for geographical areas but requires identification of sentinels who are representative of the larger population. Our goal is to evaluate applicability of a population of labor and delivery patients for sentinel surveillance system for monitoring the prevalence of SARS-CoV-2 infection. We tested 5307 labor and delivery patients from two hospitals in Phoenix, Arizona, finding 195 SARS-CoV-2 positive. Most positive cases were associated with people who were asymptomatic (79.44%), similar to statewide rates. Our results add to the growing body of evidence that SARS-CoV-2 disproportionately impacts people of color, with Black people having the highest positive rates (5.92%). People with private medical insurance had the lowest positive rates (2.53%), while Medicaid patients had a positive rate of 5.54% and people without insurance had the highest positive rates (6.12%). With diverse people reporting for care and being tested regardless of symptoms, labor and delivery patients may serve as ideal sentinels for asymptomatic detection of SARS-CoV-2 and monitoring impacts across a wide range of social and economic classes. A more robust system for infectious disease management requires the expanded participation of additional hospitals so that the sentinels are more representative of the population at large, reflecting geographic and neighborhood level patterns of infection and risk.

Optimal allocation and operation of sewer monitoring sites for wastewater-based disease surveillance: A methodological proposal

Wastewater-based epidemiology (WBE) is drawing increasing attention as a promising tool for an early warning of emerging infectious diseases such as COVID-19. This study demonstrated the utility of a spatial bisection method (SBM) and a global optimization algorithm (i.e., genetic algorithm, GA), to support better designing and operating a WBE program for disease surveillance and source identification. The performances of SBM and GA were compared in determining the optimal locations of sewer monitoring manholes to minimize the difference among the effective spatial monitoring scales of the selected manholes. While GA was more flexible in determining the spatial resolution of the monitoring areas, SBM allows stepwise selection of optimal sampling manholes with equiareal subcatchments and lowers computational cost. Upon detecting disease outbreaks at a regular sewer monitoring site, additional manholes within the catchment can be selected and monitored to identify source areas with a required spatial resolution. SBM offered an efficient method for rapidly searching for the optimal locations of additional sampling manholes to identify the source areas. This study provides strategic and technical elements of WBE including sampling site selection with required spatial resolution and a source identification method.

A Simple and Cheap Method to Extract SARS-COV-2 Nucleic Acid from Nasopharyngeal Swab Without the Need Silica Filter Column

Background: The COVID-19 pandemic affected different aspects of human life seriously, including health issues. Unfortunately, the process of RNA extraction using commercial kits is highly expensive. Replacement of this technique with a cheaper one may help us catch a more affordable approach. Objectives: This study aims to introduce a simple and cost-benefit procedure to extract nucleic acid from swab samples of patients infected with SARS-COV-2. Methods: All 41 positive extracted samples were extracted with three methods separately. The first method was based on the commercial kit using a silica filter column. The second method was made of ammonium acetate, sodium acetate, and alcohol as an extraction solution, and the last method was applied using only the sodium acetate and alcohol solution. Results: All samples extracted with a commercial kit based on a silica column were positive (100%) with Cts 21 ± 4.9, 21.4 ± 4.8, and 28.1 ± 1.8 for RNA-dependent RNA polymerase (RdRp), N, and RNase P genes, respectively. In the precipitation method using ammonium acetate, 40 samples were detected positive (97.5%), and the Cts were 26.3 ± 4.5, 23.6 ± 5.3, and 25.7 ± 3.5 for the above three genes, respectively. Similar to the conventional extraction method, the third method also showed positive results (97.5%) significantly. The mean CTs were 26 ± 4.3, 23 ± 5.4, and 23.7 ± 2.3, respectively. Conclusions: Our results indicated that the precipitation method using ammonium acetate, sodium acetate, and ethanol could be an alternative extraction method instead of the column-based method for SARS-COV-2 by swab samples.

An opinion on Wastewater-Based Epidemiological Monitoring (WBEM) with Clinical Diagnostic Test (CDT) for detecting high-prevalence areas of community COVID-19 Infections

Wastewater-Based Epidemiological Monitoring (WBEM) is an efficient surveillance tool during the COVID-19 pandemic as it meets all requirements of a complete monitoring system including early warning, tracking the current trend, prevalence of the disease, detection of genetic diversity as well asthe up-surging SARS-CoV-2 new variants with mutations from the wastewater samples. Subsequently, Clinical Diagnostic Test is widely acknowledged as the global gold standard method for disease monitoring, despite several drawbacks such as high diagnosis cost, reporting bias, and the difficulty of tracking asymptomatic patients (silent spreaders of the COVID-19 infection who manifest nosymptoms of the disease). In this current reviewand opinion-based study, we first propose a combined approach) for detecting COVID-19 infection in communities using wastewater and clinical sample testing, which may be feasible and effective as an emerging public health tool for the long-term nationwide surveillance system. The viral concentrations in wastewater samples can be used as indicatorsto monitor ongoing SARS-CoV-2 trends, predict asymptomatic carriers, and detect COVID-19 hotspot areas, while clinical sampleshelp in detecting mostlysymptomaticindividuals for isolating positive cases in communities and validate WBEM protocol for mass vaccination including booster doses for COVID-19.

A critical review on the existing wastewater treatment methods in the COVID-19 era: What is the potential of advanced oxidation processes in combatting viral especially SARS-CoV-2?

The COVID-19 epidemic has put the risk of virus contamination in water bodies on the horizon of health authorities. Hence, finding effective ways to remove the virus, especially SARS-CoV-2, from wastewater treatment plants (WWTPs) has emerged as a hot issue in the last few years. Herein, this study first deals with the fate of SARS-CoV-2 genetic material in WWTPs, then critically reviews and compares different wastewater treatment methods for combatting COVID-19 as well as to increase the water quality. This critical review sheds light the efficiency of advanced oxidation processes (AOPs) to inactivate virus, specially SARS-CoV-2 RNA. Although several physicochemical treatment processes (e.g. activated sludge) are commonly used to eliminate pathogens, AOPs are the most versatile and effective virus inactivation methods. For instance, TiO2 is the most known and widely studied photo-catalyst innocuously utilized to degrade pollutants as well as to photo-induce bacterial and virus disinfection due to its high chemical resistance and efficient photo-activity. When ozone is dissolved in water and wastewater, it generates a wide spectrum of the reactive oxygen species (ROS), which are responsible to degrade materials in virus membranes resulting in destroying the cell wall. Furthermore, electrochemical advanced oxidation processes act through direct oxidation when pathogens react at the anode surface or by indirect oxidation through oxidizing species produced in the bulk solution. Consequently, they represent a feasible choice for the inactivation of a wide range of pathogens. Nonetheless, there are some challenges with AOPs which should be addressed for application at industrial-scale.

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

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

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.

Assessment of rotavirus and norovirus emitted from water spray park: QMRA, diseases burden and sensitivity analysis

A quantitative model on exposure to pathogenic viruses in air of recreational area and their corresponding health effects is necessary to provide mitigation actions in content of emergency response plans (ERP). Here, the health risk associated with exposure to two pathogenic viruses of concern: Rotavirus (RoV) and Norovirus (NoV) in air of water spray park were estimated using a quantitative microbial risk assessment (QMRA) model. To this end, real-time Reverse Transcriptase polymerase chain reaction (real-time RT-PCR) was employed to measure the concentration levels of RoV and NoV over a twelve-month period. The probability of infection, illness and diseases burden of gastrointestinal illness (GI) caused by RoV and NoV for both workers and visitors were estimated using QMRA and Monto-Carlo simulation technique. The annual mean concentration for RoV and NoV in sampling air of water spray park were 20and 1754, respectively. The %95 confidence interval (CI) calculated annual DALY indicator for RoV (Workers: 2.62 × 10-4-2.62 × 10-1, Visitors: 1.50 × 10-5-2.42 × 10-1) and NoV (Workers: 5.54 × 10-3-2.53 × 10-1; Visitors: 5.18 × 10-4-2.54 × 10-1) were significantly higher the recommended values by WHO and US EPA (10-6-10-4 DALY pppy). According to sensitivity analysis, exposure dose and disease burden per case (DBPC) were found as the most influencing factors on disease burden as a consequences of exposure to RoV and NoV, respectively. The comprehensive information on DALY and QMRA can aid authorities involved in risk assessment and recreational actions to adopt proper approach and mitigation actions to minimize the health risk.

Anthropogenic Sewage Water Circuit as Vector for SARS-CoV-2 Viral ARN Transport and Public Health Assessment, Monitoring and Forecasting-Sibiu Metropolitan Area (Transylvania/Romania) Study Case

Water is a risk factor for epidemics of waterborne diseases with effects on human health. In 2019, new viral pneumonia cases occurred in China and spread worldwide. The aim of this study was to assess the feasibility and accuracy of a wastewater-based epidemiological (WBE) monitoring tool in a SARS-CoV-2 hot spot (Sibiu City metropolitan area), namely to highlight the correlation between the number of infections on the days of sampling and the amount of viral RNA detected in wastewater. Wastewater samples were collected once a week, and viral RNA was extracted and quantified. In parallel, the daily number of SARS-CoV-2 infections was obtained from the local council. The correlation between the number of infections and viruses detected in sewage was measured by Pearson correlation coefficients. The results show the amount of viral RNA in the wastewater is directly correlated with the number of infections reported in the week up to the sampling day and also the number of infections reported for the sampling day. Moreover, correlation coefficients show the amount of viral RNA in wastewater increases in advance of the increase in reported infection cases. Therefore, WBE can be used as a tool for monitoring virus spread trends in human communities and can help anticipate the trend of this type of viral infection.

Long-term monitoring of SARS-CoV-2 RNA in sewage samples from specific public places and STPs to track COVID-19 spread and identify potential hotspots

Coronavirus pandemic started in March 2020 and since then has caused millions of deaths worldwide. Wastewater-based epidemiology (WBE) can be used as an epidemiological surveillance tool to track SARS-CoV-2 dissemination and provide warning of COVID-19 outbreaks. Considering that there are public places that could be potential hotspots of infected people that may reflect the local epidemiological situation, the presence of SARS-CoV-2 RNA was analyzed by RT-qPCR for approximately 16 months in sewage samples from five public places located in the metropolitan area of Belo Horizonte, MG, Brazil: the sewage treatment plant of Confins International Airport (AIR), the main interstate bus terminal (BUS), an upscale shopping centre (SHC1), a popular shopping centre (SHC2) and a university institute (UNI). The results were compared to those of the influent sewage of the two main sewage treatment plants of Belo Horizonte (STP1 and STP2). Viral monitoring in the STPs proved to be an useful regional surveillance tool, reflecting the trends of COVID-19 cases. However, the viral concentrations in the samples from the selected public places were generally much lower than those of the municipal STPs, which may be due to the behaviour of the non-infected or asymptomatic people, who are likely to visit these places relatively more than the symptomatic infected ones. Among these places, the AIR samples presented the highest viral concentrations and concentration peaks were observed previously to local outbreaks. Therefore, airport sewage monitoring can provide an indication of the regional epidemiological situation. For the other places, particularly the UNI, the results suggested a greater potential to detect the infection and trace cases especially among employees and regular attendees. Taken together, the results indicate that for a regular and permanent sentinel sewage surveillance the sewage from STPs, AIR and UNI could be monitored.

Long-term monitoring of SARS-CoV-2 RNA in sewage samples from specific public places and STPs to track COVID-19 spread and identify potential hotspots

Coronavirus pandemic started in March 2020 and since then has caused millions of deaths worldwide. Wastewater-based epidemiology (WBE) can be used as an epidemiological surveillance tool to track SARS-CoV-2 dissemination and provide warning of COVID-19 outbreaks. Considering that there are public places that could be potential hotspots of infected people that may reflect the local epidemiological situation, the presence of SARS-CoV-2 RNA was analyzed by RT-qPCR for approximately 16 months in sewage samples from five public places located in the metropolitan area of Belo Horizonte, MG, Brazil: the sewage treatment plant of Confins International Airport (AIR), the main interstate bus terminal (BUS), an upscale shopping centre (SHC1), a popular shopping centre (SHC2) and a university institute (UNI). The results were compared to those of the influent sewage of the two main sewage treatment plants of Belo Horizonte (STP1 and STP2). Viral monitoring in the STPs proved to be an useful regional surveillance tool, reflecting the trends of COVID-19 cases. However, the viral concentrations in the samples from the selected public places were generally much lower than those of the municipal STPs, which may be due to the behaviour of the non-infected or asymptomatic people, who are likely to visit these places relatively more than the symptomatic infected ones. Among these places, the AIR samples presented the highest viral concentrations and concentration peaks were observed previously to local outbreaks. Therefore, airport sewage monitoring can provide an indication of the regional epidemiological situation. For the other places, particularly the UNI, the results suggested a greater potential to detect the infection and trace cases especially among employees and regular attendees. Taken together, the results indicate that for a regular and permanent sentinel sewage surveillance the sewage from STPs, AIR and UNI could be monitored.

Wastewater-Based Epidemiology: Detection of SARS-CoV-2 RNA in Different Stages of Domestic Wastewater Treatment in Santa Fe, Argentina

The COVID-19 pandemic affected human life at every level. In this study, we analyzed genetic markers (N and ORF1ab, RNA genes) of SARS-CoV-2 in domestic wastewaters (DWW) in San Justo City (Santa Fe, Argentina), using reverse transcription-quantitative real-time PCR. Out of the 30 analyzed samples, 30% were positive for SARS-CoV-2 RNA. Of the total positive samples, 77% correspond to untreated DWW, 23% to pre-chlorination, and no SARS-CoV-2 RNA was registered at the post-chlorination sampling site. The viral loads of N and OFR1ab genes decreased significantly along the treatment process, and the increase in the number of viral copies of the N gene could anticipate, by 6 days, the number of clinical cases in the population. The concentration of chlorine recommended by the WHO (≥ 0.5 mg L-1 after at least 30 min of contact time at pH 8.0) successfully removed SARS-CoV-2 RNA from DWW. The efficiency of wastewater-based epidemiology (WBE) confirms the need to control and increase DWW treatment systems on a regional and global scale. This work could contribute to building a network for WBE to monitor SARS-CoV-2 in wastewaters during the pandemic waves and the epidemic remission phase.

Graphical abstract

Supplementary Information

The online version contains supplementary material available at 10.1007/s11270-022-05772-w.

SARS-CoV-2 Surveillance in Belgian Wastewaters

Wastewater-based surveillance was conducted by the national public health authority to monitor SARS-CoV-2 circulation in the Belgian population. Over 5 million inhabitants representing 45% of the Belgian population were monitored throughout 42 wastewater treatment plants for 15 months comprising three major virus waves. During the entire period, a high correlation was observed between the daily new COVID-19 cases and the SARS-CoV-2 concentration in wastewater corrected for rain impact and covered population size. Three alerting indicators were included in the weekly epidemiological assessment: High Circulation, Fast Increase, and Increasing Trend. These indicators were computed on normalized concentrations per individual treatment plant to allow for a comparison with a reference period as well as between analyses performed by distinct laboratories. When the indicators were not corrected for rain impact, rainy events caused an underestimation of the indicators. Despite this negative impact, the indicators permitted us to effectively monitor the evolution of the fourth virus wave and were considered complementary and valuable information to conventional epidemiological indicators in the weekly wastewater reports communicated to the National Risk Assessment Group.

Wild type and variants of SARS-COV-2 in Parisian sewage: presence in raw water and through processes in wastewater treatment plants

The presence of SARS-CoV-2 RNA has been extensively reported at the influent of wastewater treatment plants (WWTPs) worldwide, and its monitoring has been proposed as a potential surveillance tool to early alert of epidemic outbreaks. However, the fate of the SARS-CoV-2 RNA in the treatment process of WWTP has not been widely studied yet; therefore, in this study, we aimed to evaluate the efficiency of treatment processes in reducing SARS-CoV-2 RNA levels in wastewater. The treatment process of three WWTPs of the Parisian area in France was monitored on six different weeks over a period of 2 months (from April 14 to June 9, 2021). SARS-CoV-2 RNA copies were detected using digital polymerase chain reaction (dPCR). Investigation on the presence of variants of concern (Del69-70, E484K, and L452R) was also performed. Additionally, SARS-CoV-2 RNA loads in the WWTPs influents were expressed as the viral concentration in per population equivalent (PE) and showed a good correlation with French public health indicators (incidence rate). SARS-CoV-2 RNA loads were notably reduced along the water treatment lines of the three WWTPs studied (2.5-3.4 log reduction). Finally, very low SARS-CoV-2 RNA loads were detected in effluents (non-detected in over half of the samples) which indicated that the potential risk of the release of wastewater effluents to the environment is probably insignificant, in the case of WWTPs enabling an efficient biological removal of nitrogen.

Investigating the Potential Effects of COVID-19 Pandemic on Intestinal Coccidian Infections

New infectious agents pose a global threat to the healthcare system, and studies are conducted to estimate their health and epidemiological outcomes in the long run. The SARS-CoV-2 virus, which has caused the COVID-19 disease, was formerly assumed to be a respiratory virus; however, it can have serious systemic effects, affecting organs such as the gastrointestinal tract (GIT). Viral RNA was reported in the stool in a subset of patients, indicating another mode of transmission and diagnosis. In COVID-19, prolonged GIT symptoms, especially diarrhea, were associated with reduced diversity and richness of gut microbiota, immunological dysregulation, and delayed viral clearance. Intestinal coccidian parasites are intracellular protozoa that are most typically transmitted to humans by oocysts found in fecally contaminated food and water. Their epidemiological relevance is coupled to opportunistic infections, which cause high morbidity and mortality among immunocompromised individuals. Among immunocompetent people, intestinal coccidia is also involved in acute diarrhea, which is usually self-limiting. Evaluating the available evidence provided an opportunity to carefully consider that; the COVID-19 virus and coccidian protozoan parasites: namely, Cryptosporidium spp., Cyclospora cayetanensis, and Isospora belli, could mutually influence each other from the microbiological, clinical, diagnostic, and elimination aspects. We further systemically highlighted the possible shared pathogenesis mechanisms, transmission routes, clinical manifestations, parasite-driven immune regulation, and intestinal microbiota alteration. Finally, we showed how this might impact developing and developed countries prevention and vaccination strategies. To the best of our knowledge, there is no review that has discussed the reciprocal effect between coccidian parasites and COVID-19 coinfection.

Wastewater-based epidemiology (WBE) for SARS-CoV-2 - A review focussing on the significance of the sewer network using a Dublin city catchment case study

Wastewater-based epidemiology (WBE) has been employed by many countries globally since the beginning of the COVID-19 pandemic in order to assess the benefits of this surveillance tool in the context of informing public health measures. WBE has been successfully employed to detect SARS-CoV-2 at wastewater treatment plants for community-wide surveillance, as well as in smaller catchments and institutions for targeted surveillance of COVID-19. In addition, WBE has been successfully used to detect new variants, identify areas of high infection levels, as well as to detect new infection outbreaks. However, due to to the large number of inherent uncertainties in the WBE process, including the inherent intricacies of the sewer network, decay of the virus en route to a monitoring point, levels of recovery from sampling and quantification methods, levels of faecal shedding among the infected population, as well as population normalisation methods, the usefulness of wastewater samples as a means of accurately quantifying SARS-CoV-2 infection levels among a population remains less clear. The current WBE programmes in place globally will help to identify new areas of research aimed at reducing the levels of uncertainty in the WBE process, thus improving WBE as a public health monitoring tool for future pandemics. In the meantime, such programmes can provide valuable comparisons to clinical testing data and other public health metrics, as well being an effective early warning tool for new variants and new infection outbreaks. This review includes a case study of sampled wastewater from the sewer network in Dublin, Ireland, during a peak infection period of COVID-19 in the city, which evaluates the different uncertainties in the WBE process.

Bibliometric analysis for economy in COVID-19 pandemic

Since the outbreak of COVID-19, various fields have been damaged to varying degrees, especially in the economic field. According to a comprehensive study of bibliometrics and content analysis, this paper aims at summarizing studies related to the development of the economic field during the COVID-19 epidemic. We search in Web of Science Core Collection using the subjects such as "economics", "economy", "economic", "financial", and then 2274 related documents are collected, which are published from 2020 to 2022. First, this paper uses the mixed qualitative and quantitative analysis methods to analyze the publication status of the countries, institutions, and authors, respectively, and conducts the document co-citation analysis by CiteSpace software. The results showed that the most popular journal is Sustainability, and the most productive research institutions, countries, and authors are primarily located in North American and European countries. Then, it makes an in-depth study of the cooperative network. With the support of Gephi software, this paper employs the social network analysis method to analyze the situation of the country/region cooperation and institutional cooperation. Finally, the content analysis of the related studies is presented to further explore the current challenges. On this basis, this paper analyzes the economic development in the post-epidemic era and draws some conclusions, which provide some references for scholars interested in this field.

Examining challenges and multi-strategic approaches in waste management during the COVID-19 pandemic: A systematic review

The COVID-19 pandemic has a negative impact on the environment. Waste generation and improper management during the COVID-19 pandemic posed a major threat to human health and the environment. Irregular and improper waste collection, handling, suspension of waste recycling and unsanitary disposal were all important issues in the processing and management of generated waste. This study emphasised a systematic review and content analysis to categorise all types of waste management (WM) during the COVID-19 pandemic to accomplish a well understanding of the relation between the COVID-19 pandemic and its impacts on WM within the literature. In this systematic review, a number of published papers on different aspects of WM during March 2020 to February 2021 were considered in order to identify major challenges in handling WM during the pandemic time and highlight multi-strategic approaches suggested. A content analysis of the 58 relevant papers was carried out by incorporating different types of WM at local as well as global scales. The present review results revealed that the COVID-19 has impacted the quantity and composition of waste, and the crisis caused by the pandemic has also altered the nature of global WM system. A comprehensive analysis on how the systems of WM were affected through the advancement of COVID-19 and what would be the healthier solutions was also highlighted in this systematic review. The results of this systematic review would be beneficial for better policymakers to holistically address potential future pandemics, if any.

Integration of renewable energy in wastewater treatment during COVID-19 pandemic: Challenges, opportunities, and progressive research trends

SARS-CoV-2 has aroused drastic effects on the global economy and public health. In response to this, personal protective equipment, hand hygiene, and social distancing have been considered the most important ways to prevent the direct spread of the virus. SARS-CoV-2 would be possible survive in wastewater for a few days, leading to secondary transmission via contact with water and wastewater. Thus, the most economical and practical approaches for decentralized wastewater treatment are renewable energies such as the solar energy disinfestation process. However, as freshwater requirements increase and fossil fuels become unsustainable, renewable energy becomes more attractive for desalination applications. Solar photovoltaic, membrane-based, and electricity desalination technologies are becoming increasingly popular due to their lower energy requirements. Several aquatic environments could be benefitted from solar energy wastewater disinfection. Besides, utilizing solar energy during the day can inactivate SARS-CoV-2 to nearly 90%. However, conventional membrane-based desalination practices have also been integrated, including reverse osmosis (RO) and electrodialysis (ED). Several exciting membrane processes have been developed recently, including membrane distillation (MD), pressure-reduced osmosis (PRO), and reverse electrodialysis (RED). Such operations can produce clean and sustainable electricity from brine and impaired water, generally considered hazardous to the environment. As a result, neither PRO nor RED can produce electricity without mixing a high salinity solution (such as seawater or brine and wastewater, respectively) with a low salinity solution. Herein, we critically review the progress in applying renewable energy such as solar energy and geothermal energy for generating electricity from wastewater treatment and uniquely discuss the effects of these two types of renewable energy on SARS-CoV-2 in air and wastewater treatment. We also highlight the significant process made on the membrane processes utilizing renewable energy and research gaps from the standpoint of producing clean and sustainable energy. The significant points of this review are: (1) among various types of renewable energy, solar energy and geothermal energy have been predominantly studied for wastewater treatment, (2) effects of these two types of renewable energy on SARS-CoV-2 in air and wastewater treatment are critically analyzed, and (3) the knowledge gaps and anticipated future research outlook have been consequently proposed thereof.

Use of wastewater surveillance for early detection of Alpha and Epsilon SARS-CoV-2 variants of concern and estimation of overall COVID-19 infection burden

A decline in diagnostic testing for SARS-CoV-2 is expected to delay the tracking of COVID-19 variants of concern and interest in the United States. We hypothesize that wastewater surveillance programs provide an effective alternative for detecting emerging variants and assessing COVID-19 incidence, particularly when clinical surveillance is limited. Here, we analyzed SARS-CoV-2 RNA in wastewater from eight locations across Southern Nevada between March 2020 and April 2021. Trends in SARS-CoV-2 RNA concentrations (ranging from 4.3 log10 gc/L to 8.7 log10 gc/L) matched trends in confirmed COVID-19 incidence, but wastewater surveillance also highlighted several limitations with the clinical data. Amplicon-based whole genome sequencing (WGS) of 86 wastewater samples identified the B.1.1.7 (Alpha) and B.1.429 (Epsilon) lineages in December 2020, but clinical sequencing failed to identify the variants until January 2021, thereby demonstrating that 'pooled' wastewater samples can sometimes expedite variant detection. Also, by calibrating fecal shedding (11.4 log10 gc/infection) and wastewater surveillance data to reported seroprevalence, we estimate that ~38% of individuals in Southern Nevada had been infected by SARS-CoV-2 as of April 2021, which is significantly higher than the 10% of individuals confirmed through clinical testing. Sewershed-specific ascertainment ratios (i.e., X-fold infection undercounts) ranged from 1.0 to 7.7, potentially due to demographic differences. Our data underscore the growing application of wastewater surveillance in not only the identification and quantification of infectious agents, but also the detection of variants of concern that may be missed when diagnostic testing is limited or unavailable.

Modeling infection from SARS-CoV-2 wastewater concentrations: promise, limitations, and future directions

Estimating total infection levels, including unreported and asymptomatic infections, is important for understanding community disease transmission. Wastewater can provide a pooled community sample to estimate total infections that is independent of case reporting biases toward individuals with moderate to severe symptoms and by test-seeking behavior and access. We derive three mechanistic models for estimating community infection levels from wastewater measurements based on a description of the processes that generate SARS-CoV-2 RNA signals in wastewater and accounting for the fecal strength of wastewater through endogenous microbial markers, daily flow, and per-capita wastewater generation estimates. The models are illustrated through two case studies of wastewater data collected during 2020-2021 in Virginia Beach, VA, and Santa Clara County, CA. Median simulated infection levels generally were higher than reported cases, but at times, were lower, suggesting a discrepancy between the reported cases and wastewater data, or inaccurate modeling results. Daily simulated infection estimates showed large ranges, in part due to dependence on highly variable clinical viral fecal shedding data. Overall, the wastewater-based mechanistic models are useful for normalization of wastewater measurements and for understanding wastewater-based surveillance data for public health decision-making but are currently limited by lack of robust SARS-CoV-2 fecal shedding data.

Lead time of early warning by wastewater surveillance for COVID-19: Geographical variations and impacting factors

The global data on the temporal tracking of the COVID-19 through wastewater surveillance needs to be comparatively evaluated to generate a proper and precise understanding of the robustness, advantages, and sensitivity of the wastewater-based epidemiological (WBE) approach. We reviewed the current state of knowledge based on several scientific articles pertaining to temporal variations in COVID-19 cases captured via viral RNA predictions in wastewater. This paper primarily focuses on analyzing the WBE-based temporal variation reported globally to check if the reported early warning lead-time generated through environmental surveillance is pragmatic or latent. We have compiled the geographical variations reported as lead time in various WBE reports to strike a precise correlation between COVID-19 cases and genome copies detected through wastewater surveillance, with respect to the sampling dates, separately for WASH and non-WASH countries. We highlighted sampling methods, climatic and weather conditions that significantly affected the concentration of viral SARS-CoV-2 RNA detected in wastewater, and thus the lead time reported from the various climatic zones with diverse WASH situations were different. Our major findings are: i) WBE reports around the world are not comparable, especially in terms of gene copies detected, lag-time gained between monitored RNA peak and outbreak/peak of reported case, as well as per capita RNA concentrations; ii) Varying sanitation facility and climatic conditions that impact virus degradation rate are two major interfering features limiting the comparability of WBE results, and iii) WBE is better applicable to WASH countries having well-connected sewerage system.

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.

A simple SEIR-V model to estimate COVID-19 prevalence and predict SARS-CoV-2 transmission using wastewater-based surveillance data

Wastewater-based surveillance (WBS) has been widely used as a public health tool to monitor SARS-CoV-2 transmission. However, epidemiological inference from WBS data remains understudied and limits its application. In this study, we have established a quantitative framework to estimate COVID-19 prevalence and predict SARS-CoV-2 transmission through integrating WBS data into an SEIR-V model. We conceptually divide the individual-level viral shedding course into exposed, infectious, and recovery phases as an analogy to the compartments in population-level SEIR model. We demonstrated that the temperature effect on viral losses in the sewer can be straightforwardly incorporated in our framework. Using WBS data from the second wave of the pandemic (Oct 02, 2020 â€" Jan 25, 2021) in the Great Boston area, we showed that the SEIR-V model successfully recapitulates the temporal dynamics of viral load in wastewater and predicts the true number of cases peaked earlier and higher than the number of reported cases by 16 days and 8.6 folds ( R = 0.93), respectively. This work showcases a simple, yet effective method to bridge WBS and quantitative epidemiological modeling to estimate the prevalence and transmission of SARS-CoV-2 in the sewershed, which could facilitate the application of wastewater surveillance of infectious diseases for epidemiological inference and inform public health actions.

Correlation between Clinical and Wastewater SARS-CoV-2 Genomic Surveillance, Oregon, USA

SARS-CoV-2 variant proportions in a population can be estimated through genomic sequencing of clinical specimens or wastewater samples. We demonstrate strong pairwise correlation between statewide variant estimates in Oregon, USA, derived from both methods (correlation coefficient 0.97). Our results provide crucial evidence of the effectiveness of community-level genomic surveillance.

Consequence of COVID-19 occurrences in wastewater with promising recognition and healing technologies: A review

Presently, the coronavirus (COVID-19) epidemic presents a major threat to global communal fitness also socio-financial development. Ignoring worldwide isolation as well as shutdown attempts, the occurrence of COVID-19 infected patients continues to be extremely large. Nonetheless, COVID-19's final course, combined with the prevalence of emerging contaminants (antibiotics, pharmaceuticals, nanoplastics, pesticides, and so forth) in wastewater treatment plants (WWTPs), presents a major problem in wastewater situations. The research, therefore, intends near examine an interdisciplinary as well as technical greet to succor COVID-19 with subsequent COVID cycles of an epidemic as a framework for wastewater treatment settings. This research investigated the potential for wastewater-based epidemiology to detect SARS-CoV-2 also the enzymes happening in wastewater conditions. In addition, a chance for the incorporation into the WWTPs of emerging and robust technologies such as mesmeric nanobiotechnology, electrochemical oxidation, microscopy, and membrane processes to enhance the overall likelihood of environmental consequences of COVID-19 also strengthen such quality of water is resolved.

Back-estimation of norovirus infections through wastewater-based epidemiology: A systematic review and parameter sensitivity

The amount of norovirus RNA (Ribonucleic Acid) in raw wastewater, collected from a wastewater treatment plant (WWTP), can provide an indication of disease prevalence within the sampled catchment. However, an accurate back-estimation might be impeded by the uncertainties from in-sewer/in-sample degradation of viral RNA, variable shedding magnitude, and difficulties in measurement within raw wastewater. The current study reviewed the published literature regarding the factors of norovirus shedding, viral RNA decay in wastewater, and the occurrence of norovirus RNA in raw wastewater based on molecular detection. Sensitivity analysis for WBE back-estimation was conducted using the reported data of the factors mentioned above considering different viral loads in wastewater samples. It was found that the back-estimation is more sensitive to analytical detection uncertainty than shedding variability for norovirus. Although seasonal temperature change can lead to variation of decay rates and may influence the sensitivity of this pathogen-specific parameter, decay rates of norovirus RNA contribute negligibly to the variance in estimating disease prevalence, based on the available data from decay experiments in bulk wastewater under different temperatures. However, the effects of in-sewer transportation on viral RNA decay and retardation by sewer biofilms on pipe surfaces are largely unknown. Given the highest uncertainty from analytical measurement by molecular methods and complexity of in-sewer processes that norovirus experienced during the transportation to WWTP, future investigations are encouraged to improve the accuracy of viral RNA detection in wastewater and delineate viral retardation/interactions with wastewater biofilms in real sewers.

A systematic review on the occurrence, fate, and remediation of SARS-CoV-2 in wastewater

The COVID-19 has been declared a pandemic by the World Health Organization. Along with impairing the respiratory system, it also affects the gastrointestinal system. By reviewing experiments on the wastewater analysis for the detection of coronavirus, this study explores the fate, persistence, and various remediation strategies for the virus removal from the wastewater. The results indicated that the virus can be detected in the wastewater samples, feces, and sewage, even before the onset of symptoms. Coronavirus can be a potential panzootic disease, as several mammalian species get infected by the deadly virus. The disinfection strategies used earlier for the treatment of wastewater are not sufficient for the removal of viruses from the wastewater. Therefore, concerted efforts should be made to understand their fate, sources, and occurrence in the environmental matrices. To prevent the spread of the panzootic disease, revised guidelines should be issued for the remediation of the virus. Recent viral remediation methods such as membrane bioreactors and advanced oxidation methods can be used. Therefore, the present review puts a light on the current knowledge on the occurrence of coronaviruses in wastewater, the possible sources, fate, and removal strategies.

SARS-CoV-2 shedding sources in wastewater and implications for wastewater-based epidemiology

Wastewater-based epidemiology (WBE) approach for COVID-19 surveillance is largely based on the assumption of SARS-CoV-2 RNA shedding into sewers by infected individuals. Recent studies found that SARS-CoV-2 RNA concentration in wastewater (CRNA) could not be accounted by the fecal shedding alone. This study aimed to determine potential major shedding sources based on literature data of CRNA, along with the COVID-19 prevalence in the catchment area through a systematic literature review. Theoretical CRNA under a certain prevalence was estimated using Monte Carlo simulations, with eight scenarios accommodating feces alone, and both feces and sputum as shedding sources. With feces alone, none of the WBE data was in the confidence interval of theoretical CRNA estimated with the mean feces shedding magnitude and probability, and 63% of CRNA in WBE reports were higher than the maximum theoretical concentration. With both sputum and feces, 91% of the WBE data were below the simulated maximum CRNA in wastewater. The inclusion of sputum as a major shedding source led to more comparable theoretical CRNA to the literature WBE data. Sputum discharging behavior of patients also resulted in great fluctuations of CRNA under a certain prevalence. Thus, sputum is a potential critical shedding source for COVID-19 WBE surveillance.

Monitoring COVID-19 spread in Prague local neighborhoods based on the presence of SARS-CoV-2 RNA in wastewater collected throughout the sewer network

Many reports have documented that the presence of SARS-CoV-2 RNA in the influents of municipal wastewater treatment plants (WWTP) correlates with the actual epidemic situation in a given city. However, few data have been reported thus far on measurements upstream of WWTPs, i.e. throughout the sewer network. In this study, the monitoring of the presence of SARS-CoV-2 RNA in Prague wastewater was carried out at selected locations of the Prague sewer network from August 2020 through May 2021. Various locations such as residential areas of various sizes, hospitals, city center areas, student dormitories, transportation hubs (airport, bus terminal), and commercial areas were monitored together with four of the main Prague sewers. The presence of SARS-CoV-2 RNA was determined by reverse transcription - multiplex quantitative polymerase chain reaction (RT-mqPCR) after the precipitation of nucleic acids with PEG 8,000 and RNA isolation with TRIzol™ Reagent. The number of copies of the gene encoding SARS-CoV-2 nucleocapsid (N1) per liter of wastewater was compared with the number of officially registered COVID-19 cases in Prague. Although the data obtained by sampling wastewater from the major Prague sewers were more consistent than those obtained from the small sewers, the correlation between wastewater-based and clinical-testing data was also good for the residential areas with more than 7,000 registered inhabitants. It was shown that monitoring SARS-CoV-2 RNA in wastewater sampled from small sewers could identify isolated occurrences of COVID-19-positive cases in local neighborhoods. This can be very valuable while tracking COVID-19 hotspots within large cities.

Basic influent sewage quality reflects sewershed characteristics in Tokyo city

Sewage comprises multifarious information on sewershed characteristics. For instance, influent sewage quality parameters (ISQPs) (e.g., total nitrogen (TN)) are being monitored regularly at all treatment plants. However, the relationship between ISQPs and sewershed characteristics is rarely investigated. Therefore, this study statistically investigated relationships between ISQPs and sewershed characteristics, covering demographic, social, and economic properties in Tokyo city as an example of a megacity. To this end, we collected ISQPs and sewershed characteristic data from 2015 to 2020 in 10 sewersheds in Tokyo city. By principal component analysis, spatial variability of ISQPs was aggregated into two principal components (89.8% contribution in total), indicating organics/nutrients and inorganic salts, respectively. Concentrations of organics/nutrients were significantly correlated with the population in sewersheds (daytime population density, family size, age distribution, etc.). Inorganic salts are significantly correlated with land cover ratios. Finally, a multiple regression model was developed for estimating the concentration of TN based on sewershed characteristics (R²=0.97). Scenario analysis using the regression model revealed that possible population movements in response to the coronavirus pandemic would substantially reduce the concentration of TN. These results indicate close relationships between ISQPs and sewershed characteristics and the potential applicability of big data of ISQPs to estimate sewershed characteristics and vice versa.

Monitoring COVID-19 spread in Prague local neighborhoods based on the presence of SARS-CoV-2 RNA in wastewater collected throughout the sewer network

Many reports have documented that the presence of SARS-CoV-2 RNA in the influents of municipal wastewater treatment plants (WWTP) correlates with the actual epidemic situation in a given city. However, few data have been reported thus far on measurements upstream of WWTPs, i.e. throughout the sewer network. In this study, the monitoring of the presence of SARS-CoV-2 RNA in Prague wastewater was carried out at selected locations of the Prague sewer network from August 2020 through May 2021. Various locations such as residential areas of various sizes, hospitals, city center areas, student dormitories, transportation hubs (airport, bus terminal), and commercial areas were monitored together with four of the main Prague sewers. The presence of SARS-CoV-2 RNA was determined by reverse transcription - multiplex quantitative polymerase chain reaction (RT-mqPCR) after the precipitation of nucleic acids with PEG 8,000 and RNA isolation with TRIzol™ Reagent. The number of copies of the gene encoding SARS-CoV-2 nucleocapsid (N1) per liter of wastewater was compared with the number of officially registered COVID-19 cases in Prague. Although the data obtained by sampling wastewater from the major Prague sewers were more consistent than those obtained from the small sewers, the correlation between wastewater-based and clinical-testing data was also good for the residential areas with more than 7,000 registered inhabitants. It was shown that monitoring SARS-CoV-2 RNA in wastewater sampled from small sewers could identify isolated occurrences of COVID-19-positive cases in local neighborhoods. This can be very valuable while tracking COVID-19 hotspots within large cities.

Detection and quantification of SARS-CoV-2 RNA in wastewater influent in relation to reported COVID-19 incidence in Finland

Wastewater-based surveillance is a cost-effective concept for monitoring COVID-19 pandemics at a population level. Here, SARS-CoV-2 RNA was monitored from a total of 693 wastewater (WW) influent samples from 28 wastewater treatment plants (WWTP, N = 21-42 samples per WWTP) in Finland from August 2020 to May 2021, covering WW of ca. 3.3 million inhabitants (∼ 60% of the Finnish population). Quantity of SARS-CoV-2 RNA fragments in 24 h-composite samples was determined by using the ultrafiltration method followed by nucleic acid extraction and CDC N2 RT-qPCR assay. SARS-CoV-2 RNA signals at each WWTP were compared over time to the numbers of confirmed COVID-19 cases (14-day case incidence rate) in the sewer network area. Over the 10-month surveillance period with an extensive total number of samples, the detection rate of SARS-CoV-2 RNA in WW was 79% (including 6% uncertain results, i.e., amplified only in one out of four, two original and two ten-fold diluted replicates), while only 24% of all samples exhibited gene copy numbers above the quantification limit. The range of the SARS-CoV-2 detection rate in WW varied from 33% (including 10% uncertain results) in Pietarsaari to 100% in Espoo. Only six out of 693 WW samples were positive with SARS-COV-2 RNA when the reported COVID-19 case number from the preceding 14 days was zero. Overall, the 14-day COVID-19 incidence was 7.0, 18, and 36 cases per 100 000 persons within the sewer network area when the probability to detect SARS-CoV-2 RNA in wastewater samples was 50%, 75% and 95%, respectively. The quantification of SARS-CoV-2 RNA required significantly more COVID-19 cases: the quantification rate was 50%, 75%, and 95% when the 14-day incidence was 110, 152, and 223 COVID-19 cases, respectively, per 100 000 persons. Multiple linear regression confirmed the relationship between the COVID-19 incidence and the SARS-CoV-2 RNA quantified in WW at 15 out of 28 WWTPs (overall R2 = 0.36, p < 0.001). At four of the 13 WWTPs where a significant relationship was not found, the SARS-CoV-2 RNA remained below the quantification limit during the whole study period. In the five other WWTPs, the sewer coverage was less than 80% of the total population in the area and thus the COVID-19 cases may have been inhabitants from the areas not covered. Based on the results obtained, WW-based surveillance of SARS-CoV-2 could be used as an indicator for local and national COVID-19 incidence trends. Importantly, the determination of SARS-CoV-2 RNA fragments from WW is a powerful and non-invasive public health surveillance measure, independent of possible changes in the clinical testing strategies or in the willingness of individuals to be tested for COVID-19.

Factors influencing SARS-CoV-2 RNA concentrations in wastewater up to the sampling stage: A systematic review

Wastewater-based surveillance (WBS) for SARS-CoV-2 RNA is a promising complementary approach to monitor community viral circulation. A myriad of factors, however, can influence RNA concentrations in wastewater, impeding its epidemiological value. This article aims to provide an overview and discussion of factors up to the sampling stage that impact SARS-CoV-2 RNA concentration estimates in wastewater. To this end, a systematic review was performed in three databases (MEDLINE, Web of Science and Embase) and two preprint servers (MedRxiv and BioRxiv). Two authors independently screened and selected articles published between January 1, 2019 and May 4, 2021. A total of 22 eligible articles were included in this systematic review. The following factors up to sampling were identified to have an influence on SARS-CoV-2 RNA concentrations in wastewater and its interpretation: (i) shedding-related factors, including faecal shedding parameters (i.e. shedding pattern, recovery, rate, and load distribution), (ii) population size, (iii) in-sewer factors, including solid particles, organic load, travel time, flow rate, wastewater pH and temperature, and (iv) sampling strategy. In conclusion, factors influencing SARS-CoV-2 RNA concentration estimates in wastewater were identified and research gaps were discussed. The identification of these factors supports the need for further research on WBS for COVID-19.

Comparison of high-frequency in-pipe SARS-CoV-2 wastewater-based surveillance to concurrent COVID-19 random clinical testing on a public U.S. university campus

Wastewater-based epidemiology (WBE) is utilized globally as a tool for quantifying the amount of Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) within communities, yet the efficacy of community-level wastewater monitoring has yet to be directly compared to random Coronavirus Disease of 2019 (COVID-19) clinical testing; the best-supported method of virus surveillance within a single population. This study evaluated the relationship between SARS-CoV-2 RNA in raw wastewater and random COVID-19 clinical testing on a large university campus in the Southwestern United States during the Fall 2020 semester. Daily composites of wastewater (24-hour samples) were collected three times per week at two campus locations from 16 August 2020 to 1 January 2021 (n = 95) and analyzed by reverse transcriptase-quantitative polymerase chain reaction (RT-qPCR) targeting the SARS-CoV-2 E gene. Campus populations were estimated using campus resident information and anonymized, unique user Wi-Fi connections. Resultant trends of SARS-CoV-2 RNA levels in wastewater were consistent with local and nationwide pandemic trends showing peaks in infections at the start of the Fall semester in mid-August 2020 and mid-to-late December 2020. A strong positive correlation (r = 0.71 (p < 0.01); n = 15) was identified between random COVID-19 clinical testing and WBE surveillance methods, suggesting that wastewater surveillance has a predictive power similar to that of random clinical testing. Additionally, a comparative cost analysis between wastewater and clinical methods conducted here show that WBE was more cost effective, providing data at 1.7% of the total cost of clinical testing ($6042 versus $338,000, respectively). We conclude that wastewater monitoring of SARS-CoV-2 performed in tandem with random clinical testing can strengthen campus health surveillance, and its economic advantages are maximized when performed routinely as a primary surveillance method, with random clinical testing reserved for an active outbreak situation.

Opportunities and limits of wastewater-based epidemiology for tracking global health and attainment of UN sustainable development goals

Wastewater-based epidemiology (WBE) emerged as a powerful, actionable health management tool during the COVID-19 pandemic. Hypothesizing future uses, we explored its potential for real-time, tracking of progress in attaining United Nations Sustainable Development Goals (SDGs) globally as a non-expensive method using existing infrastructure. We inventoried (i) literature-documented sewerage infrastructure, (ii) demographics of populations served, and (iii) WBE markers informative of 9 SDGs. Among the 17 different sustainable development goals listed by the UN 2030 agenda, more than half of these may be monitored by using WBE monitoring at centralized treatment infrastructure as tabulated in this study. Driven mainly by COVID-19, WBE currently is practiced in at least 55 countries, reaching about 300 million people. Expansion of WBE to 109,000 + treatment plants inventoried in 129 countries would increase global coverage 9-fold to 34.7% or 2.7 billion, leaving out 5 billion people not served by centralized sewerage systems. Associations between population demographics and present-day infrastructure are explored, and geospatial regions particularly vulnerable to infectious disease outbreaks are identified. The results suggest that difference in the differential outcomes in well-being is an outcome of the sanitation infrastructure inequalities and lack of sanitation infrastructure creates doubly disadvantaged populations at risk of poor hygiene and cut off from the early-warning benefits of conventional WBE. This is the first study to explore the feasibility and potential barriers to the use of WBE for tracking the attainment of SDGs globally with at least 9 out of 17 SDGs.

Coronaviruses and SARS-CoV-2 in sewerage and their removal: Step by step in wastewater treatment plants

The fate of Coronaviruses (CoVs) and in particular SARS-CoV-2 in wastewater treatment plants (WWTPs) has not been completely understood yet, but an adequate knowledge on the removal performances in WWTPs could help to prevent waterborne transmission of the virus that is still under debate. CoVs and SARS-CoV-2 are discharged from faeces into the sewer network and reach WWTPs within a few hours. This review presents the fate of SARS-CoV-2 and other CoVs in the primary, secondary and tertiary treatments of WWTPs as well as in sludge treatments. The viral loads decrease progressively along with the treatments from 20 to 3.0E+06 GU/L (Genomic Units/L) in the influent wastewater to concentrations below 2.50E+05 GU/L after secondary biological treatments and finally to negative concentrations (below detection limit) in disinfected effluents. Reduction of CoVs is due to (i) natural decay under unfavourable conditions (solids, microorganisms, temperature) for relatively long hydraulic retention times and (ii) processes of sedimentation, filtration, predation, adsorption, disinfection. In primary and secondary settling, due to the hydrophobic properties, a partial accumulation of CoVs may occur in the separated sludge. In secondary treatment (i.e. activated sludge) CoVs and SARS-CoV-2 loads can be reduced only by about one logarithm (∼90%). To enhance this removal, tertiary treatment with ultrafiltration (Membrane Bioreactors) and chemical disinfection or UV light is needed. CoVs and SARS-CoV-2 in the sludge (1.2E+04-4.6E+08 GU/L) can be inactivated significantly in the thermophilic digestion (55 °C), while mesophilic temperatures (33-37 °C) are not efficient. Additional studies are required to investigate the infectivity of SARS-CoV-2 in WWTPs, especially in view of increasing interest in wastewater reclamation and reuse.

Decay of four enteric pathogens and implications to wastewater-based epidemiology: Effects of temperature and wastewater dilutions

Measurement of pathogens in raw wastewater from a population within certain sewer catchments can provide quantitative information on public health status within the sampled urban area. This so-called wastewater-based epidemiology (WBE) approach has the potential of becoming a powerful tool to monitor pathogen circulation and support timely intervention during outbreaks. However, many WBE studies failed to account for the pathogen decay during wastewater transportation in back calculating the disease prevalence. Various sewer process factors, including water temperature and infiltration/inflow, can lead to the variation of pathogen decay rates. This paper firstly reviewed the effects of temperature and types of water, i.e., wastewater, freshwater, and saline water, on the decay of four selected enteric pathogens, i.e., Campylobacter, Salmonella, Norovirus, and Adenovirus. To elucidate the importance of the pathogen decay rates (measured by culture and molecular methods) to WBE, a sensitivity analysis was conducted on the back-calculation equation for infection prevalence with decay rates collected from published literature. It was found that WBE back-calculation is more sensitive to decay rates under the condition of high wastewater temperature (i.e., over 25 °C) or if wastewater is diluted by saline water (i.e., sewer infiltration or use of seawater as an alternative source of freshwater constituting around 1/3 household water demand in some cities). Stormwater dilution of domestic wastewater (i.e., sewer inflow might achieve 10 times volumetric dilution) was shown to play a role in increasing the sensitivity of WBE back-calculation to bacterial pathogens, but not viral pathogens. Hence, WBE back-calculation in real sewers should account for in-sewer decay of specific pathogen species under different wastewater temperatures and dilutions. Overall, this review contributes to a better understanding of pathogen decay in wastewater which can lead to improved accuracy of WBE back-calculation.

Wastewater-based epidemiology for early warning of SARS-COV-2 circulation: A pilot study conducted in Sicily, Italy

There is increasing evidence of the use of wastewater-based epidemiology to integrate conventional monitoring assessing disease symptoms and signs of viruses in a specific territory. We present the results of SARS-CoV-2 environmental surveillance activity in wastewater samples collected between September 2020 and July 2021 in 9 wastewater treatment plants (WTPs) located in central and western Sicily, serving over 570,000 residents. The presence of SARS-CoV-2, determined in 206 wastewater samples using RT-qPCR assays, was correlated with the notified and geo-referenced cases on the areas served by the WTPs in the same study period. Overall, 51% of wastewater samples were positive. Samples were correlated with 33,807 SARS-CoV-2 cases, reported in 4 epidemic waves, with a cumulative prevalence of 5.9% among Sicilian residents. The results suggest that the daily prevalence of SARS-CoV-2 active cases was statistically significant and higher in areas with SARS-CoV-2 positive wastewater samples. According to these findings, the proposed method achieves a good sensitivity profile (78.3%) in areas with moderate or high viral circulation (≥133 cases/100,000 residents) and may represent a useful tool in the management of epidemics based on an environmental approach, although it is necessary to improve the accuracy of the process.

The challenge of SARS-CoV-2 environmental monitoring in schools using floors and portable HEPA filtration units: Fresh or relic RNA?

Testing surfaces in school classrooms for the presence of SARS-CoV-2, the virus that causes COVID-19, can provide public-health information that complements clinical testing. We monitored the presence of SARS-CoV-2 RNA in five schools (96 classrooms) in Davis, California (USA) by collecting weekly surface-swab samples from classroom floors and/or portable high-efficiency particulate air (HEPA) units (n = 2,341 swabs). Twenty-two surfaces tested positive, with qPCR cycle threshold (Ct) values ranging from 36.07-38.01. Intermittent repeated positives in a single room were observed for both floor and HEPA filter samples for up to 52 days, even following regular cleaning and HEPA filter replacement after a positive result. We compared the two environmental sampling strategies by testing one floor and two HEPA filter samples in 57 classrooms at Schools D and E. HEPA filter sampling yielded 3.02% and 0.41% positivity rates per filter sample collected for Schools D and E, respectively, while floor sampling yielded 0.48% and 0% positivity rates. Our results indicate that HEPA filter swabs are more sensitive than floor swabs at detecting SARS-CoV-2 RNA in interior spaces. During the study, all schools were offered weekly free COVID-19 clinical testing through Healthy Davis Together (HDT). HDT also offered on-site clinical testing in Schools D and E, and upticks in testing participation were observed following a confirmed positive environmental sample. However, no confirmed COVID-19 cases were identified among students associated with classrooms yielding positive environmental samples. The positive samples detected in this study appeared to contain relic viral RNA from individuals infected before the monitoring program started and/or RNA transported into classrooms via fomites. High-Ct positive results from environmental swabs detected in the absence of known active infections supports this conclusion. Additional research is needed to differentiate between fresh and relic SARS-CoV-2 RNA in environmental samples and to determine what types of results should trigger interventions.

Heavy Metal, Waste, COVID-19, and Rapid Industrialization in This Modern Era—Fit for Sustainable Future

Heavy metal contamination, waste, and COVID-19 are hazardous to all living things in the environment. This review examined the effects of heavy metals, waste, and COVID-19 on the ecosystem. Scientists and researchers are currently working on ways to extract valuable metals from waste and wastewater. We prefer Tessier sequential extraction for future use for heavy metal pollution in soil. Results indicated that population growth is another source of pollution in the environment. Heavy metal pollution wreaks havoc on soil and groundwater, especially in China. COVID-19 has pros and cons. The COVID-19 epidemic has reduced air pollution in China and caused a significant reduction in CO2 releases globally due to the lockdown but has a harmful effect on human health and the economy. Moreover, COVID-19 brings a huge amount of biomedical waste. COVID-19’s biomedical waste appears to be causing different health issues. On the other hand, it was discovered that recycling has become a new source of pollution in south China. Furthermore, heavy metal contamination is the most severe ecological effect. Likewise, every problem has a remedy to create new waste management and pollution monitoring policy. The construction of a modern recycling refinery is an important aspect of national waste disposal.

Design of SARS-CoV-2 Variant-Specific PCR Assays Considering Regional and Temporal Characteristics

Monitoring the prevalence of SARS-CoV-2 variants is necessary to make informed public health decisions during the COVID-19 pandemic. PCR assays have received global attention, facilitating a rapid understanding of variant dynamics because they are more accessible and scalable than genome sequencing. However, as PCR assays target only a few mutations, their accuracy could be reduced when these mutations are not exclusive to the target variants. Here we introduce PRIMES, an algorithm that evaluates the sensitivity and specificity of SARS-CoV-2 variant-specific PCR assays across different geographical regions by incorporating sequences deposited in the GISAID database. Using PRIMES, we determined that the accuracy of several PCR assays decreased when applied beyond the geographic scope of the study in which the assays were developed. Subsequently, we used this tool to design Alpha and Delta variant-specific PCR assays for samples from Illinois, USA. In silico analysis using PRIMES determined the sensitivity/specificity to be 0.99/0.99 for the Alpha variant-specific PCR assay and 0.98/1.00 for the Delta variant-specific PCR assay in Illinois, respectively. We applied these two variant-specific PCR assays to six local sewage samples and determined the dominant SARS-CoV-2 variant of either the wild type, the Alpha variant, or the Delta variant. Using next-generation sequencing (NGS) of the spike (S) gene amplicons of the Delta variant-dominant samples, we found six mutations exclusive to the Delta variant (S:T19R, S:Δ156/157, S:L452R, S:T478K, S:P681R, and S:D950N). The consistency between the variant-specific PCR assays and the NGS results supports the applicability of PRIMES. IMPORTANCE Monitoring the introduction and prevalence of variants of concern (VOCs) and variants of interest (VOIs) in a community can help the local authorities make informed public health decisions. PCR assays can be designed to keep track of SARS-CoV-2 variants by measuring unique mutation markers that are exclusive to the target variants. However, the mutation markers may not be exclusive to the target variants because of regional and temporal differences in variant dynamics. We introduce PRIMES, an algorithm that enables the design of reliable PCR assays for variant detection. Because PCR is more accessible, scalable, and robust for sewage samples than sequencing technology, our findings will contribute to improving global SARS-CoV-2 variant surveillance.

Water-sanitation-health nexus in the Indus-Ganga-Brahmaputra River Basin: need for wastewater surveillance of SARS-CoV-2 for preparedness during the future waves of pandemic

The Indus-Ganga-Brahmaputra River Basin (IGBRB) is a trans-boundary river basin flowing through four major countries in South Asia viz., India, Pakistan, Bangladesh, and Nepal. Contamination of surface water by untreated or inadequately treated wastewater has been a huge problem for pathogenic microorganisms in economies in transition. Recent studies have reported that sewage surveillance can provide prior information of the outbreak data, because faeces can contain the novel coronavirus (SARS-CoV-2) shed by infected humans. Hence, in this study we geo-spatially mapped the COVID-19 hotspots during the peak time in the first and second wave of pandemic to demonstrate the need and usefulness of wastewater surveillance strategy in IGBRB during ongoing pandemic. Further we discussed the status of sanitation, health and hand-hygiene in the IGBRB along with characterization of the challenges posed by the pandemic in achieving the United Nations Sustainable Development Goals (UN-SDGs). Monthly Geographical Information System (GIS) mapping of COVID-19 hotspots in the IGBRB showed an increase in the spread along the direct sewage discharge points. The social inequalities expose the vulnerabilities of the urban poor in terms of the burden, risks and access to Water, Sanitation, and Hygiene (WASH) needs. Such an evidence-based image of the actual SARS-CoV-2 viral load in the community along the IGBRB can provide valuable insights and recommendations to deal with the future waves of COVID-19 pandemic in this region that can go a long way in achieving the UN-SDGs.

A comprehensive survey on the biomedical signal processing methods for the detection of COVID-19

The novel coronavirus, renamed SARS-CoV-2 and most commonly referred to as COVID-19, has infected nearly 44.83 million people in 224 countries and has been designated SARS-CoV-2. In this study, we used 'web of Science', 'Scopus' and 'goggle scholar' with the keywords of "SARS-CoV-2 detection" or "coronavirus 2019 detection" or "COVID 2019 detection" or "COVID 19 detection" "corona virus techniques for detection of COVID-19", "audio techniques for detection of COVID-19", "speech techniques for detection of COVID-19", for period of 2019-2021. Some COVID-19 instances have an impact on speech production, which suggests that researchers should look for signs of disease detection in speech utilising audio and speech recognition signals from humans to better understand the condition. It is presented in this review that an overview of human audio signals is presented using an AI (Artificial Intelligence) model to diagnose, spread awareness, and monitor COVID-19, employing bio and non-obtrusive signals that communicated human speech and non-speech audio information is presented. Development of accurate and rapid screening techniques that permit testing at a reasonable cost is critical in the current COVID-19 pandemic crisis, according to the World Health Organization. In this context, certain existing investigations have shown potential in the detection of COVID 19 diagnostic signals from relevant auditory noises, which is a promising development. According to authors, it is not a single "perfect" COVID-19 test that is required, but rather a combination of rapid and affordable tests, non-clinic pre-screening tools, and tools from a variety of supply chains and technologies that will allow us to safely return to our normal lives while we await the completion of the hassle free COVID-19 vaccination process for all ages. This review was able to gather information on biomedical signal processing in the detection of speech, coughing sounds, and breathing signals for the purpose of diagnosing and screening the COVID-19 virus.

A novel approach to concentrate human and animal viruses from wastewater using receptors-conjugated magnetic beads

Viruses are present at low concentrations in wastewater; therefore, an effective method for concentrating virus particles is necessary for accurate wastewater-based epidemiology (WBE). We designed a novel approach to concentrate human and animal viruses from wastewater using porcine gastric mucin-conjugated magnetic beads (PGM-MBs). We systematically evaluated the performances of the PGM-MBs method (sensitivity, specificity, and robustness to environmental inhibitors) with six viral species, including Tulane virus (a surrogate for human norovirus), rotavirus, adenovirus, porcine coronavirus (transmissible gastroenteritis virus or TGEV), and two human coronaviruses (NL63 and SARS-CoV-2) in influent wastewater and raw sewage samples. We determined the multiplication factor (the ratio of genome concentration of the final solution to that of the initial solution) for the PGM-MBs method, which ranged from 1.3 to 64.0 depending on the viral species. Because the recovery efficiency was significantly higher when calculated with virus titers than it was with genome concentration, the PGM-MBs method could be an appropriate tool for assessing the risk to humans who are inadvertently exposed to wastewater contaminated with infectious viruses. Furthermore, PCR inhibitors were not concentrated by PGM-MBs, suggesting that this tool will be successful for use with environmental samples. In addition, the PGM-MBs method is cost-effective (0.5 USD/sample) and has a fast turnaround time (3 h from virus concentration to genome quantification). Thus, this method can be implemented in high throughput facilities. Because of its strong performance, intrinsic characteristics of targeting the infectious virus, robustness to wastewater, and adaptability to high throughput systems, the PGM-MBs method can be successfully applied to WBE and ultimately provides valuable public health information.