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Wastewater-based epidemiology (WBE) evaluates the health status, environmental exposure, and lifestyle habits of community inhabitants through the investigation of chemical or biological markers present in urban wastewater systems. This approach is frequently employed in discerning drug abuse, disease prevalence, and the presence of environmental contaminants. To comprehend the current state and developmental trajectories in WBE research, the current study utilizes the source literature of the Web of Science Core Collection (WOSCC) database. Implementing the Bibliometrix toolkit in R language and employing CiteSpace and VOSviewer for bibliometric analysis, this investigative pursuit effectuates an all-encompassing evaluation of the WBE literature, traversing a substantial time span of 16 years, encompassing 2008 through 2023. The results of this bibliometric analysis illuminate annual propensities and disciplinary distribution related to WBE research, while discerning the most impactful and prolific contributors, including authors, institutions, countries, and scholarly journals. The onset of the COVID-19 pandemic has engendered the expedited progression of WBE, leading to a substantial escalation in research endeavors in the past three years. By meticulously evaluating highly-cited publications, co-occurrence network of keywords, and keyword burst analysis, it is concluded that the research hotspots in this field focus on the monitoring of illicit drugs, psychoactive substances, and viruses in sewage. Subsequent investigations possess the capacity to propel the advancement of emerging methodologies for biomarker identification and analytical techniques. By concurrently integrating big data technologies (including artificial intelligence and cloud computing) with epidemiological and clinical data sets, a more expansive, precise, and efficacious rendition of WBE research can be realized. [ABSTRACT FROM AUTHOR]

This research evaluated the relationship between daily new Coronavirus Disease 2019 (COVID-19) cases and Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) concentrations in wastewater, followed by effects of differential SARS-CoV-2 shedding loads across various COVID-19 outbreaks. Linear regression analyses were utilized to examine the lead time of the SARS-CoV-2 signal in wastewater relative to new COVID-19 clinical cases. During the Delta wave, no lead time was evident, highlighting limited predictive capability of wastewater monitoring during this phase. However, significant lead times were observed during the Omicron wave, potentially attributed to testing capacity overload and subsequent case reporting delays or changes in shedding patterns. During the Post-Omicron wave (Febuary 23 to May 19, 2022), no lead time was discernible, whereas following the lifting of the COVID-19 state of emergency (May 30, 2022 to May 30, 2023), the correlation coefficient increased and demonstrated the potential of wastewater surveillance as an early warning system. Subsequently, we explored the virus shedding in wastewater through feces, operationalized as the ratio of SARS-CoV-2 concentrations to daily new COVID-19 cases. This ratio varied significantly across the Delta, Omicron, other variants and post-state-emergency phases, with the Kruskal-Wallis H test confirming a significant difference in medians across these stages (P

Wastewater-based epidemiology (WBE) evaluates the health status, environmental exposure, and lifestyle habits of community inhabitants through the investigation of chemical or biological markers present in urban wastewater systems. This approach is frequently employed in discerning drug abuse, disease prevalence, and the presence of environmental contaminants. To comprehend the current state and developmental trajectories in WBE research, the current study utilizes the source literature of the Web of Science Core Collection (WOSCC) database. Implementing the Bibliometrix toolkit in R language and employing CiteSpace and VOSviewer for bibliometric analysis, this investigative pursuit effectuates an all-encompassing evaluation of the WBE literature, traversing a substantial time span of 16 years, encompassing 2008 through 2023. The results of this bibliometric analysis illuminate annual propensities and disciplinary distribution related to WBE research, while discerning the most impactful and prolific contributors, including authors, institutions, countries, and scholarly journals. The onset of the COVID-19 pandemic has engendered the expedited progression of WBE, leading to a substantial escalation in research endeavors in the past three years. By meticulously evaluating highly-cited publications, co-occurrence network of keywords, and keyword burst analysis, it is concluded that the research hotspots in this field focus on the monitoring of illicit drugs, psychoactive substances, and viruses in sewage. Subsequent investigations possess the capacity to propel the advancement of emerging methodologies for biomarker identification and analytical techniques. By concurrently integrating big data technologies (including artificial intelligence and cloud computing) with epidemiological and clinical data sets, a more expansive, precise, and efficacious rendition of WBE research can be realized.

ABSTRACTThe COVID-19 pandemic has exposed a high level of scientific illiteracy and mistrust that pervades the scientific and medical communities. This finding has proven the necessity of updating current methods used to expose undergraduates to research. The research in traditional course-based undergraduate research experiences (CUREs) is limited by undergraduate time constraints, skill level, and course structure, and consequently it does not attain the learning objectives or the high-impact, relevant studies achieved in graduate-level laboratories using a cyclic trainee/trainer model. Although undergraduate independent study (ISY) research more closely matches the structure and learning objectives of graduate-level research, they are uncommon as professors and universities typically view them as a significant time and resource burden with limited return. Cyclic independent study-assisted CUREs (CIS-CUREs) combine many positive aspects of ISY graduate-level research, and CUREs by pre-training ISY research lead to facilitate CURE proposal and project semesters in a cyclic model. The CIS-CURE approach allowed undergraduate students at Stetson University to perform and disseminate more rigorous, involved, long-term, and challenging research projects, such as the surveillance of SARS-CoV-2 in wastewater. In doing so, all students would have the opportunity to participate in a high-impact research project and consequently gain a more comprehensive training, reach higher levels of research dissemination, and increase their competitiveness after graduating. Together, CIS-CUREs generate graduates with higher scientific literacy and thus combat scientific mistrust in communities.

Early prediction of COVID-19 infected communities (potential hotspots) is essential to limit the spread of virus. Diagnostic testing has limitations in big populations because it cannot deliver information at a fast enough rate to stop the spread in its early phases. Wastewater based epidemiology (WBE) experiments showed promising results for brisk detection of 'SARS CoV-2' RNA in urban wastewater. However, a systematic and targeted approach to track COVID-19 virus in the complex wastewater networks at a community level is lacking. This research combines graph network (GN) theory with fuzzy logic to determine the chances of a specific community being a COVID-19 hotspot in a wastewater network. To detect 'SARS-CoV-2' RNA, GN divides wastewater network into communities and fuzzy logic-based inference system is used to identify targeted communities. For the propose of tracking, 4000 sample cases from Minnesota (USA) were tested based on various contributing factors. With a probability score of greater than 0.8, 42% of cases were likely to be designated as COVID-19 hotspots based on multiple demographic characteristics. The research enhances the conventional WBE approach through two novel aspects, viz. (1) by integrating graph theory with fuzzy logic for quick prediction of potential hotspot along with its likelihood percentage in a wastewater network, and (2) incorporating the uncertainty associated with COVID-19 contributing factors using fuzzy membership functions. The targeted approach allows for rapid testing and implementation of vaccination campaigns in potential hotspots. Consequently, governmental bodies can be well prepared to check future pandemics and variant spreading in a more planned manner. [ABSTRACT FROM AUTHOR]

RESUMENAgua y Saneamientos Argentinos S.A. (AySA) brinda servicios esenciales que abarcan la producción de agua potable y el tratamiento de aguas residuales para una población que supera los 14,5 millones de habitantes en el Área Metropolitana de Buenos Aires (AMBA), Argentina. En respuesta a la declaración de pandemia por COVID-19 por parte de la Organización Mundial de la Salud (OMS), AySA desarrolló una metodología para evaluar la carga genética viral del SARS-CoV-2 en aguas residuales sin tratar. Este enfoque tenía como objetivo aprovechar el potencial de la vigilancia epidemiológica basada en aguas residuales, basándose en experiencias internacionales. Para monitorear la carga viral en las secciones representativas del sistema de recolección de aguas residuales, empleamos una técnica de ultracentrifugación adaptada para concentrar muestras. Después de esto, se realizaron la extracción de ARN y RT-qPCR para cuantificar el gen Orf1ab del SARS-CoV-2. Este estudio se realizó de diciembre de 2020 a junio de 2021, para anticipar la segunda ola de la pandemia. Al analizar los datos de cuatro grandes plantas de tratamiento de aguas residuales, identificamos asociaciones estadísticamente significativas entre la carga genómica viral log10 y los casos positivos log10 informados una o dos semanas después. En base a los resultados obtenidos, concluimos que los niveles de virus del alcantarillado podrían ser un buen predictor de futuros casos clínicos a ser diagnosticados en un futuro inmediato.

Heavy metals and trace metals are among the most prevalent contaminants in sewage. Depending on the concentration and frequency of exposure, certain heavy metals are toxic, carcinogenic, and hazardous to humans. In this study, copper (Cu), nickel (Ni), zinc (Zn), iron (Fe), and cadmium (Cd) levels were measured in the collected wastewater samples from 10 selected domestic sewage treatment plants (STPs) in Penang, Malaysia in December 2021. All metals in the wastewater were determined using the atomic absorption spectrometric (AAS) method followed by the wastewater-based epidemiology (WBE) analysis. The mean concentrations of heavy metals in the wastewater samples were found to be in the following order (unit of mg/L): Fe > Ni > Zn > Cu > Cd (influent), and Fe > Ni > Zn > Cd > Cu (effluent). Among the metals, Fe concentrations were found to be the highest in effluent, with average values at 5.93 ± 5.319 mg/L, slightly over than a maximum permissible Fe concentration. Cadmium level in all STPs was significantly higher when compared to the maximum permissible Cd concentration (0.02 mg/L) allowed by Malaysia's regulation, with an average of 0.13 ± 0.011 mg/L. Other metals concentration such as Cu, Ni and Zn in wastewater at the studied STPs showed low level and were considered safe. Using the WBE approach, the collected data were then calculated to estimate the population's exposure consumption to heavy metals. Mass loading demonstrated high Fe exposure in all STPs but low Cd exposure, with the mean exposure of 1,924.86 ± 2451.772 and 46.91 ± 20.936 mg/1000p/d, respectively. Given the World Health Organization's recommendation for tolerable weekly cadmium intake, the estimated human exposure to Cd in this study was particularly concerning, in addition to the lack of efficiency of Cd removal in the studied STPs. [ABSTRACT FROM AUTHOR]

We aimed to estimate the lead time and infection prevalence from SARS-CoV-2 wastewater (WW) monitoring compared with clinical surveillance data in Mexico to generate evidence about the feasibility of a large-scale WW surveillance system. We selected 10 WW treatment plants (WWTP) and 5 COVID-19 hospitals in major urban conglomerates in Mexico and collected biweekly 24-h flow-adjusted composite samples during October–November 2020. We concentrated WW samples by polyethylene glycol precipitation and employed quantitative PCR (RT-qPCR) assays, targeting the nucleoprotein (N1 and N2) genes. We detected and quantified SARS-CoV-2 RNA in 88% and 58% of the raw WW samples from WWTPs and COVID-19 hospitals, respectively. The WW RNA daily loads lead the active cases by more than one month in large and medium WWTP sites. WW estimated that cases were 2 to 20-fold higher than registered active cases. Developing a continuous monitoring surveillance system for SARS-CoV-2 community transmission through WW is feasible, informative, and recognizes three main challenges: (1) WW system data (catchment area, population served), (2) capacity to maintain the cold-chain and process samples, and (3) supplies and personnel to ensure standardized procedures. [ABSTRACT FROM AUTHOR]

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Wastewater-based epidemiology (WBE) may be successfully used to comprehensively monitor and determine the scale and dynamics of some infections in the community. We monitored severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) RNA in raw wastewater samples from Porto Alegre, Southern Brazil. The samples were collected and analyzed every week between May 2020 to May 2021. Meanwhile, different social restrictions were applied according to the number of hospitalized patients in the region. Weekly samples were obtained from two wastewater treatment plants (WWTP), named Navegantes and Serraria. To determine the SARS-CoV-2 RNA titers in wastewater, we performed RT-qPCR analysis targeting the N gene (N1). The highest titer of SARS-CoV-2 RNA was observed between epidemiological weeks (EWs) 33–37 (August), 42–43 (October), 45–46 (November), 49–51 (December) in 2020, and 1–3 (January), 7–13 (February to March) in 2021, with viral loads ranging from 1 × 106–3 × 106 genomic copies/Liter. An increase in positive confirmed cases followed such high viral loads. Depending on the sampling method used, positive cases increased in 6–7 days and 15 days after the rise of viral RNA titers in wastewater, with composite sampling methods showing a lower time lag and a higher resolution on the analyses. The results showed a direct relation between strict social restrictions and the loads of detected RNA reduction in wastewater, corroborating the number of confirmed cases. Differences in viral loads between different sampling points and methods were observed, as composite samples showed more stable results during the analyzed period. Besides, viral loads obtained from samples collected at Serraria WWTP were consistently higher than the ones obtained at Navegantes WWTP, indicating differences in local dynamics of SARS-CoV-2 spread in different regions of Porto Alegre. In conclusion, wastewater sampling to monitor SARS-CoV-2 is a robust tool to evaluate the viral loads contributing to hospitalized patients’ data and confirmed cases. In addition, SARS-CoV-2 detection in sewage may inform and alert the government when there are asymptomatic or non-tested patients.

The discovery of SARS-CoV-2 virus in the water bodies has been reported, and the risk of virus transmission to human via the water route due to poor wastewater management cannot be disregarded. The main source of the virus in water bodies is the sewage network systems which connects to the surface water. Wastewater-based epidemiology has been applied as an early surveillance tool to sense SARS-CoV-2 virus in the sewage network. This review discussed possible transmission routes of the SARS-CoV-2 virus and the challenges of the existing method in detecting the virus in wastewater. One significant challenge for the detection of the virus is that the high virus loading is diluted by the sheer volume of the wastewater. Hence, virus preconcentration from water samples prior to the application of virus assay is essential to accurately detect traceable virus loading. The preparation time, materials and conditions, virus type, recovery percentage, and various virus recovery techniques are comprehensively discussed in this review. The practicability of molecular methods such as Polymer-Chain-Reaction (PCR) for the detection of SARS-CoV-2 in wastewater will be revealed. The conventional virus detection techniques have several shortcomings and the potential of biosensors as an alternative is also considered. Biosensing techniques have also been proposed as an alternative to PCR and have reported detection limits of 10pg/μl. This review serves to guide the reader on the future designs and development of highly sensitive, robust and, cost effective SARS-CoV-2 lab-on-a-chip biosensors for use in complex wastewater.

We aimed to estimate the lead time and infection prevalence from SARS-CoV-2 wastewater (WW) monitoring compared with clinical surveillance data in Mexico to generate evidence about the feasibility of a large-scale WW surveillance system. We selected 10 WW treatment plants (WWTP) and 5 COVID-19 hospitals in major urban conglomerates in Mexico and collected biweekly 24-h flow-adjusted composite samples during October–November 2020. We concentrated WW samples by polyethylene glycol precipitation and employed quantitative PCR (RT-qPCR) assays, targeting the nucleoprotein (N1 and N2) genes. We detected and quantified SARS-CoV-2 RNA in 88% and 58% of the raw WW samples from WWTPs and COVID-19 hospitals, respectively. The WW RNA daily loads lead the active cases by more than one month in large and medium WWTP sites. WW estimated that cases were 2 to 20-fold higher than registered active cases. Developing a continuous monitoring surveillance system for SARS-CoV-2 community transmission through WW is feasible, informative, and recognizes three main challenges: (1) WW system data (catchment area, population served), (2) capacity to maintain the cold-chain and process samples, and (3) supplies and personnel to ensure standardized procedures.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is an RNA virus, a member of the coronavirus family of respiratory viruses that includes severe acute respiratory syndrome coronavirus 1 (SARS-CoV-1) and the Middle East respiratory syndrome (MERS). It has had an acute and dramatic impact on health care systems, economies, and societies of affected countries during the past 8 months. Widespread testing and tracing efforts are being employed in many countries in attempts to contain and mitigate this pandemic. Recent data has indicated that fecal shedding of SARS-CoV-2 is common and that the virus RNA can be detected in wastewater. This indicates that wastewater monitoring may provide a potentially efficient tool for the epidemiological surveillance of SARS-CoV-2 infection in large populations at relevant scales. In particular, this provides important means of (i) estimating the extent of outbreaks and their spatial distributions, based primarily on in-sewer measurements, (ii) managing the early-warning system quantitatively and efficiently, and (iii) verifying disease elimination. Here we report different virus concentration methods using polyethylene glycol (PEG), alum, or filtration techniques as well as different RNA extraction methodologies, providing important insights regarding the detection of SARS-CoV-2 RNA in sewage. Virus RNA particles were detected in wastewater in several geographic locations in Israel. In addition, a correlation of virus RNA concentration to morbidity was detected in Bnei-Barak city during April 2020. This study presents a proof of concept for the use of direct raw sewage-associated virus data, during the pandemic in the country as a potential epidemiological tool.

Wastewater surveillance has emerged as a crucial public health tool for population-level pathogen surveillance. Supported by funding from the American Rescue Plan Act of 2021, the FDA's genomic epidemiology program, GenomeTrakr, was leveraged to sequence SARS-CoV-2 from wastewater sites across the United States. This initiative required the evaluation, optimization, development, and publication of new methods and analytical tools spanning sample collection through variant analyses. Version-controlled protocols for each step of the process were developed and published on protocols.io. A custom data analysis tool and a publicly accessible dashboard were built to facilitate real-time visualization of the collected data, focusing on the relative abundance of SARS-CoV-2 variants and sub-lineages across different samples and sites throughout the project. From September 2021 through June 2023, a total of 3,389 wastewater samples were collected, with 2,517 undergoing sequencing and submission to NCBI under the umbrella BioProject, PRJNA757291. Sequence data were released with explicit quality control (QC) tags on all sequence records, communicating our confidence in the quality of data. Variant analysis revealed wide circulation of Delta in the fall of 2021 and captured the sweep of Omicron and subsequent diversification of this lineage through the end of the sampling period. This project successfully achieved two important goals for the FDA's GenomeTrakr program: first, contributing timely genomic data for the SARS-CoV-2 pandemic response, and second, establishing both capacity and best practices for culture-independent, population-level environmental surveillance for other pathogens of interest to the FDA., Importance: This paper serves two primary objectives. First, it summarizes the genomic and contextual data collected during a Covid-19 pandemic response project, which utilized the FDA's laboratory network, traditionally employed for sequencing foodborne pathogens, for sequencing SARS-CoV-2 from wastewater samples. Second, it outlines best practices for gathering and organizing population-level next generation sequencing (NGS) data collected for culture-free, surveillance of pathogens sourced from environmental samples., Competing Interests: The authors declare no conflict of interest.

This research evaluated the relationship between daily new Coronavirus Disease 2019 (COVID-19) cases and Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) concentrations in wastewater, followed by effects of differential SARS-CoV-2 shedding loads across various COVID-19 outbreaks. Linear regression analyses were utilized to examine the lead time of the SARS-CoV-2 signal in wastewater relative to new COVID-19 clinical cases. During the Delta wave, no lead time was evident, highlighting limited predictive capability of wastewater monitoring during this phase. However, significant lead times were observed during the Omicron wave, potentially attributed to testing capacity overload and subsequent case reporting delays or changes in shedding patterns. During the Post-Omicron wave (Febuary 23 to May 19, 2022), no lead time was discernible, whereas following the lifting of the COVID-19 state of emergency (May 30, 2022 to May 30, 2023), the correlation coefficient increased and demonstrated the potential of wastewater surveillance as an early warning system. Subsequently, we explored the virus shedding in wastewater through feces, operationalized as the ratio of SARS-CoV-2 concentrations to daily new COVID-19 cases. This ratio varied significantly across the Delta, Omicron, other variants and post-state-emergency phases, with the Kruskal-Wallis H test confirming a significant difference in medians across these stages (P < 0.0001). Despite its promise, wastewater surveillance of COVID-19 disease prevalence presents several challenges, including virus shedding variability, data interpretation complexity, the impact of environmental factors on viral degradation, and the lack of standardized testing procedures. Overall, our findings offer insights into the correlation between COVID-19 cases and wastewater viral concentrations, potential variation in SARS-CoV-2 shedding in wastewater across different pandemic phases, and underscore the promise and limitations of wastewater surveillance as an early warning system for disease prevalence trends., Competing Interests: The authors declare no conflicts of interest., (© 2024 The Authors.)

Wastewater based epidemiology studies are a complementary approach used to measure and monitor the presence and prevalence of infectious diseases when clinical testing capacity is limited. It can also help with the detection of coronaviruses in wastewater and how they spread in the society. In the COVID-19 pandemic, SARS-Coronavirus-2 (SARS-CoV-2) is excreted with the feces of infected people and mixed with wastewater. Most people infected with viruses that infect enterically spread their feces and virus into their sewage systems both for the days or weeks before and after symptoms begin to appear. Through the detection of Covid-19 in wastewater, the number of asymptomatic people who do not represent any indication related to diseases but are carriers can be determined, and the total number of people infected in that society can be estimated. Therefore, an early warning system can be created, and it will be possible to take the necessary precautions before the second or third wave occurs.

• Genome sequencing of >19,000 wastewater samples for SARS-CoV2. • Variants tracked at national, regional and city scales. • Tracked subsequent dynamics of Omicron sub-lineages. • Cost-effective relative to individual testing but giving comparable results. The world has moved into a new stage of managing the SARS-CoV-2 pandemic with minimal restrictions and reduced testing in the population, leading to reduced genomic surveillance of virus variants in individuals. Wastewater-based epidemiology (WBE) can provide an alternative means of tracking virus variants in the population but decision-makers require confidence that it can be applied to a national scale and is comparable to individual testing data. We analysed 19,911 samples from 524 wastewater sites across England at least twice a week between November 2021 and February 2022, capturing sewage from >70% of the English population. We used amplicon-based sequencing and the phylogeny based de-mixing tool Freyja to estimate SARS-CoV-2 variant frequencies and compared these to the variant dynamics observed in individual testing data from clinical and community settings. We show that wastewater data can reconstruct the spread of the Omicron variant across England since November 2021 in close detail and aligns closely with epidemiological estimates from individual testing data. We also show the temporal and spatial spread of Omicron within London. Our wastewater data further reliably track the transition between Omicron subvariants BA1 and BA2 in February 2022 at regional and national levels. Our demonstration that WBE can track the fast-paced dynamics of SARS-CoV-2 variant frequencies at a national scale and closely match individual testing data in time shows that WBE can reliably fill the monitoring gap left by reduced individual testing in a more affordable way. [ABSTRACT FROM AUTHOR]

The present study investigated the detection of severe acute respiratory syndrome–coronavirus 2 (SARS-CoV-2) genomes at each treatment stage of 14 aerobic wastewater treatment plants (WWTPs) serving the major municipalities in two states of Rajasthan and Uttarakhand in Northern India. The untreated, primary, secondary and tertiary treated wastewater samples were collected over a time frame ranging from under-lockdown to post-lockdown conditions. The results showed that SARS-CoV-2 RNA was detected in 13 out of 40 wastewater samples in Jaipur district, Rajasthan and in 5 out of 14 wastewater samples in the Haridwar District, Uttarakhand with the E gene predominantly observed as compared to the N and RdRp target genes in later time-points of sampling. The Ct values of genes present in wastewater samples were correlated with the incidence of patient and community cases of COVID-19. This study further indicates that the viral RNA could be detected after the primary treatment but was not present in secondary or tertiary treated samples. This study implies that aerobic biological wastewater treatment systems such as moving bed biofilm reactor (MBBR) technology and sequencing batch reactor (SBR) are effective in virus removal from the wastewater. This work might present a new indication that there is little to no risk in relation to SARS-CoV-2 while reusing the treated wastewater for non-potable applications. In contrast, untreated wastewater might present a potential route of viral transmission through WWTPs to sanitation workers and the public. However, there is a need to investigate the survival and infection rates of SARS-CoV-2 in wastewater.

The COVID-19 pandemic has exposed a high level of scientific illiteracy and mistrust that pervades the scientific and medical communities. This finding has proven the necessity of updating current methods used to expose undergraduates to research. The research in traditional course-based undergraduate research experiences (CUREs) is limited by undergraduate time constraints, skill level, and course structure, and consequently it does not attain the learning objectives or the high-impact, relevant studies achieved in graduate-level laboratories using a cyclic trainee/trainer model. Although undergraduate independent study (ISY) research more closely matches the structure and learning objectives of graduate-level research, they are uncommon as professors and universities typically view them as a significant time and resource burden with limited return. Cyclic independent study-assisted CUREs (CIS-CUREs) combine many positive aspects of ISY graduate-level research, and CUREs by pre-training ISY research lead to facilitate CURE proposal and project semesters in a cyclic model. The CIS-CURE approach allowed undergraduate students at Stetson University to perform and disseminate more rigorous, involved, long-term, and challenging research projects, such as the surveillance of SARS-CoV-2 in wastewater. In doing so, all students would have the opportunity to participate in a high-impact research project and consequently gain a more comprehensive training, reach higher levels of research dissemination, and increase their competitiveness after graduating. Together, CIS-CUREs generate graduates with higher scientific literacy and thus combat scientific mistrust in communities., Competing Interests: The author declares no conflict of interest., (Copyright © 2023 Dye.)

Multi-residue methods for the determination of the myriad of compounds of emerging concern (CECs) entering in the environment are key elements for further assessment on their distribution and fate. Here, we have developed an analytical protocol for the simultaneous analysis of 195 prescription, over-the-counter, and illicit drugs by using a combination of solid phase extraction (SPE) and determination by liquid chromatography coupled to high resolution mass spectrometry (LC-HRMS). The method was applied to the analysis of influent sewage samples from 3 wastewater treatment plants (WWTPs) from Cadiz Bay (SW Spain), enabling the quantification of more than 100 pharmaceuticals, 19 of them at average concentrations higher than 1 μg L−1, including caffeine (92 μg L−1), paracetamol (72 μg L−1), and ibuprofen (56 μg L−1), as well as several illicit drugs (e.g., cocaine). Wastewater based epidemiology (WBE) was applied for 27 of the detected compounds to establish their consumption in the sampling area, which has been never attempted before. Caffeine, naproxen, and salicylic acid stood out because of their high consumption (638, 51, and 20 g d−1·1000pop−1, respectively). Regarding illicit drugs, cocaine showed the highest frequency of detection and we estimated an average consumption of 3683 mg d−1·1000pop−1 in Cadiz Bay. The combination of new HRMS methods, capable of discriminating thousands of chemicals, and WBE will allow for a more comprehensive characterization of chemical substances and their consumption in urban environments in the near future. • More than 100 pharmaceutical compounds were measured in 3 cities of Cadiz Bay. • 19 of them had a concentration higher than 1ug·L-1 and 64 of them had a frequency of detection higher than 50%. • Differences in concentrations were detected between cities that were attenuated when normalized with load. • Consumption was calculated for 27 drugs that did not present significant variations during the week. • Slight differences related to consumption were found between the cities studied. [ABSTRACT FROM AUTHOR]

Wastewater is a complex matrix containing a wide range of chemical and biological markers of human activity. Relating concentrations of these “waste” materials in wastewater influent streams to population-scale use, consumption, or rates of exposure, can provide important qualitative or quantitative information on the activity of inhabitants within a given wastewater catchment. Many publications in this field of study have focussed on the usage of pharmaceuticals, illicit drugs, tobacco and alcohol. However, many other potential applications are emerging which can contribute useful knowledge on human health, exposure to industrial chemicals, infectious diseases or pathogens and antibiotic resistance. This review summarises the established wastewater based epidemiology (WBE) biomarkers, and presents a critical review of the current capabilities of WBE. We further discuss possible future strategies and challenges anticipated in analysing wastewater to measure chemical markers of population health as well as biological markers of microbial exposure and disease. [ABSTRACT FROM AUTHOR]