Wastewater-Based Epidemiology and Biosensor Technology: Emerging Tools for Environmental Risk Management

Public health is attracting increasing attention due to the current global pandemic, and wastewater-based epidemiology (WBE) has emerged as a powerful tool for monitoring of public health by analysis of a variety of biomarkers (e.g., chemicals and pathogens) in wastewater. Rapid development of WBE requires rapid and on-site analytical tools for monitoring of sewage biomarkers to provide immediate decision and intervention. Biosensors have been demonstrated to be highly sensitive and selective tools for the analysis of sewage biomarkers due to their fast response, ease-to-use, low cost and the potential for field-testing. This paper presents biosensors as effective tools for wastewater analysis of potential biomarkers and monitoring of public health via WBE. In particular, we discuss the use of sewage sensors for rapid detection of a range of targets, including rapid monitoring of community-wide illicit drug consumption and pathogens for early warning of infectious diseases outbreaks. Finally, we provide a perspective on the future use of the biosensor technology for WBE to enable rapid on-site monitoring of sewage, which will provide nearly real-time data for public health assessment and effective intervention.

Wastewater-based epidemiology combined with forensic toxicological information: trends in drug use and impact of law enforcement activities

Illicit drug use in Reykjavik by wastewater-based epidemiology

Increased alcohol consumption, especially among young people, is a major concern in Turkey as it is around the world due to negative effects on public health and safety. Regarding this, it is pivotal to monitor and therefore control alcohol use in public. In this case, wastewater-based epidemiology (WBE), which is the in-depth analysis of wastewater and a relatively new method, can deliver complementary information concerning the abuse of different substances. The proven potential of the WBE approach offers new promises in the process of monitoring alcohol use, namely the monitoring of the levels of ethyl sulfate (EtS) as a urinary biomarker of alcohol consumption, and it is a powerful mean to estimate alcohol use at the community level. In this study, raw 24-h composite wastewater samples were collected from Seyhan and Yüregir wastewater treatment plants (WWTPs) in Adana Province for one week per season (October 2016-August 2017). The fast and validated analytical method was performed by liquid chromatography coupled to tandem mass spectrometry (LC-MS/MS) and therefore applied to the analysis of ethyl sulfate (EtS). Obtained concentration values were back-calculated, and regional and temporal social usage rates were determined. Higher values were calculated for both WWTPs on Sunday. Alcohol consumption in the region served by Seyhan WWTP was higher than Yüregir WWTP. The results showed that the levels of alcohol consumption during given periods in Adana ranged from 659.8 to 8998.7 mL/day/1000 per person with an average value of 4983.9 and 3924.2 mL/day/1000 inhabitant in Seyhan WWTP and Yüregir WWTP, respectively. This study shows that weekly and annual trends in alcohol consumption can be detected quickly from wastewater analysis.

Wastewater-based epidemiology (WBE) is a cost-effective and rapid survey approach that involves sampling and detecting chemical and biological markers in wastewater. WBE has been primarily employed to reveal information about illicit drug and pharmaceutical usage, diet, lifestyle, community health, and infectious diseases. In recent years, there has been a surge in research and implementation of WBE to detect COVID-19, which is critical for early-warning and tracking community transmission. Compared to other types of epidemiological surveillance, WBE offers many advantages but also has inherent methodological limitations and associated uncertainties. This talk will address various WBE uncertainties related to biomarker shedding, in-sewer decay and transport, wastewater sampling, biomarker analysis, and the back-calculation method. Comprehensive studies, using approaches such as systematic reviews, bioreactor tests, field studies, and modeling, have been conducted to identify ways to mitigate these uncertainties. However, various protocols have been developed in different WBE programs for wastewater sampling and analysis, making cross-comparisons of data obtained by different protocols challenging. Establishing a standard or best-practice WBE protocol for sampling, analysis, and reporting would be beneficial. Additionally, we will demonstrate how machine learning can enable AI-powered WBE to become a reliable surveillance tool.

Wastewater-based epidemiology is a new approach to monitor drug abuse. It involves collecting wastewater, analysis of residues of drugs or its metabolites in wastewater, and back-calculation of drug consumption by taking into account wastewater flow, stability of drug target residues in wastewater, and excretion rates of drugs/metabolites. Wastewater-based epidemiology has the advantages of being inexpensive and yielding more consistent and near real-time results. It has the great potential to supplement the existing drug monitoring methods. It can be used to build large-scale (regional, national, or even continental) monitoring networks that would yield spatial patterns and temporal trends in drug abuse. This paper described in detail the principle and procedures of this wastewater-based approach. Application of this approach across the globe was also reviewed. The uncertainties involved in the approach and knowledge gaps were identified. Finally, necessity, benefits, and feasibility to set up nation or province-wide monitoring networks based on wastewater analysis in China were discussed.

During the COVID-19 pandemic, wastewater-based epidemiology (WBE) has been engaged to complement medical surveillance and in some cases to also act as an early diagnosis indicator of viral spreading in the community. Most efforts worldwide by the scientific community and commercial companies focus on the formulation of protocols for SARS-CoV-2 analysis in wastewater and approaches addressing the quantitative relationship between WBE and medical surveillance are lacking. In the present study, a mathematical model is developed which uses as input the number of daily positive medical tests together with the highly non-linear shedding rate curve of individuals to estimate the evolution of global virus shedding rate in wastewater along calendar days. A comprehensive parametric study by the model using as input actual medical surveillance and WBE data for the city of Thessaloniki (~700,000 inhabitants, North Greece) during the outbreak of November 2020 reveals the conditions under which WBE can be used as an early warning tool for predicting pandemic outbreaks. It is shown that early warning capacity is different along the days of an outbreak and depends strongly on the number of days apart between the day of maximum shedding rate of infected individuals in their disease cycle and the day of their medical testing. The present data indicate for Thessaloniki an average early warning capacity of around 2 days. Moreover, the data imply that there exists a proportion between unreported cases (asymptomatic persons with mild symptoms that do not seek medical advice) and reported cases. The proportion increases with the number of reported cases. The early detection capacity of WBE improves substantially in the presence of an increasing number of unreported cases. For Thessaloniki at the peak of the pandemic in mid-November 2020, the number of unreported cases reached a maximum around 4 times the number of reported cases.

Classical epidemiology relies on incidence, mortality rates, and clinical data from individual testing, which can be challenging for many countries. Therefore, innovative, flexible, cost-effective, and scalable surveillance techniques are needed. Wastewater-based epidemiology (WBE) has emerged as a highly powerful tool in this regard. WBE analyses substances excreted in human fluids and faeces that enter the sewer system. This approach provides insights into community health status and lifestyle habits. WBE serves as an early warning system for viral surveillance, detecting the emergence of new pathogens, changes in incidence rates, identifying future trends, studying outbreaks, and informing the performance of action plans. While WBE has long been used to study different viruses such as poliovirus and norovirus, its implementation has surged due to the pandemic caused by the Severe Acute Respiratory Syndrome Coronavirus 2. This has led to the establishment of wastewater surveillance programmes at international, national, and community levels, many of which remain operational. Furthermore, WBE is increasingly applied to study other pathogens, including antibiotic resistance bacteria, parasites, fungi, and emerging viruses, with new methodologies being developed. Consequently, the primary focus now is on creating international frameworks to enhance states' preparedness against future health risks. However, there remains considerable work to be done, particularly in integrating the principles of One Health into epidemiological surveillance to acknowledge the interconnectedness of humans, animals, and the environment in pathogen transmission. Thus, a broader approach to analysing the three pillars of One Health must be developed, transitioning from WBE to wastewater and environmental surveillance, and establishing this approach as a routine practice in public health.

Introduction/Objective The rise of antibiotic resistance poses a significant global health threat, needing a robust monitoring system to track its emergence and spread. However, most developing countries lack the infrastructure to monitor such resistance effectively. Wastewater-based epidemiology (WBE) has been proven effective in surveilling various outbreaks and offers a promising method for monitoring antibiotic resistance at the community level. This study aims to assess and compare the antibiotic resistance of Escherichia coli isolated from raw wastewater with those isolated from clinical urinary tract infection (UTI) samples from the same community. Methods/Case Report Conducted from January 2022 to October 2023, this study analyzed antibiogram data from eighty-six Escherichia coli isolates sourced from wastewater and thirty-four isolates derived from clinical urinary tract infections (UTIs). The clinical samples were obtained and processed at the Clinical Microbiology Laboratory of a university campus. The isolates were evaluated against the eleven most prescribed antibiotics for UTIs in the University Clinic including: Amoxicillin/Clavulanic Acid, Ampicillin, Cefazolin, Cefoxitin, Ceftriaxone, Cefuroxime, Ciprofloxacin, Gentamicin, Nalidixic Acid, Nitrofurantoin, and Sulfamethoxazole-trimethoprim. Results (if a Case Study enter NA) Explaining the observed trends in both wastewater and clinical samples from the perspective of AWaRE-WHO classification (Access, Watch, Reserve), we see similar trends of resistance in both data sets. A) The antibiotics used in the Access category (Empiric first or second choice for treatment of most common infections) demonstrates similar resistance patterns for both wastewater and clinical isolates except for Nitrofurantoin. B) The antibiotics used in the Watch category (Antibiotics that have higher toxicity issues and higher potential to negatively impact AMR) resistance pattern shows negligible risk in the university community evaluated. Conclusion It is recommended that the university clinic prescribe Nitrofurantoin as the last antibiotic from the Access list to the university community to treat UTI patients. Furthermore, WBE is a useful tool to determine patterns of resistance under the studied settings.

Illicit drug abuse is a worldwide social and health problem, and monitoring illicit drug use is of paramount importance in the context of public policies. It is already known that relevant epidemiologic information can be obtained from the analysis of urban residual waters. This approach, named wastewater-based epidemiology (WBE), is based on the measurement of specific markers, resulting from human biotransformation of the target drugs, as indicators of the consumption of the compounds by the population served by the wastewater treatment installation under investigation. Drug consumption estimation based on WBE requires sewage sampling strategies that express the concentrations along the whole time period of time. To this end, the most common approach is the use of automatic composite samplers. However, this active sampling procedure is costly, especially for long-term studies and in limited-resources settings. An alternative, cost-effective, sampling strategy is the use of passive samplers, like the polar organic chemical integrative sampler (POCIS). POCIS sampling has already been applied to the estimation of exposure to pharmaceuticals, pesticides, and some drugs of abuse, and some studies evaluated the comparative performances of POCIS and automatic composite samplers. In this context, this manuscript aims to review the most important biomarkers of drugs of abuse consumption in wastewater, the fundamentals of POCIS sampling in WBE, the previous application of POCIS for WBE of drugs of abuse, and to discuss the advantages and disadvantages of POCIS sampling, in comparison with other strategies used in WBE. POCIS sampling is an effective strategy to obtain a representative overview of biomarker concentrations in sewage over time, with a small number of analyzed samples, increased detection limits, with lower costs than active sampling. Just a few studies applied POCIS sampling for WBE of drugs of abuse, but the available data support the use of POCIS as a valuable tool for the long-term monitoring of the consumption of certain drugs within a defined population, particularly in limited-resources settings.

Assessment of human exposure to selected pesticides in Norway by wastewater analysis

Systematic sampling and analysis of wastewater is an increasingly used tool tocomplement more traditional techniques for assessing consumption of licit and illicitchemical substances in the population. The use of wastewater sampling andanalysis contributes to a broader field that is referred to as wastewater-basedepidemiology (WBE). Both spatial and temporal analysis can be conductedquantitatively, quickly and cost effectively using the WBE approach.In brief, per capita exposure to a given chemical within a population is estimated bymeasuring the concentration of that chemical or a metabolite in a representativewastewater sample multiplied by the volume of wastewater represented by thesample, divided by the population size from which the sample originates andcorrecting by factors such as the excretion factor of the metabolite or chemical,molecular weight change and potential stability of the chemical within the sewer. Ithas previously been determined that the population size is the largest uncertainty forWBE estimates.The aim of this thesis it to therefore identify useful markers that allow populationestimation for a given wastewater sample and apply this technique including toassess per capita exposure/release of a group of chemicals that have not beenexamined in previous WBE studies.The approach for this thesis was to systematically collect samples on a day when thepopulation is well defined. For this we collected samples on the 2011 Census Day inAustralia from 10 wastewater catchments ranging in size from approximately 1,500to 500,000 people. By providing catchment maps to the Australian Bureau ofStatistics, the accurate population size for each catchment was determined.The most obvious choice of a potentially useful population markers are endogenouschemicals such as creatinine. Therefore, in Chapter 2, creatinine was assessed as apopulation marker. It was found that there was no correlation between the mass loadof creatinine in wastewater and the population. Using laboratory-scale sewerreactors with conditions representative of both gravity sewers and rising mains, itwas found that creatinine, while stable in collected samples, is unstable under sewerconditions. We therefore conclude that creatinine is not suitable for predictingdifferences in population size particularly when different sewer systems arecompared.In Chapter 3, a method was developed to quantify 96 chemicals in wastewaterinfluent and applied to the census wastewater samples to identify potentialpopulation size markers. Thirteen chemicals including acesulfame, caffeine, andpharmaceuticals and personal care products were detected in all samples and foundto have a good correlation (R2 > 0.8) between mass load and population size. ABayesian inference model was developed which incorporated these potentialpopulation size markers to provide a population size estimate. The model wasvalidated using a leave-one-out approach for all sites and comparing the populationsize estimate from the model with the accurate census population data. It was shownthat for small catchments, the uncertainty of the estimate as measured by the widthof the posterior was 1.1 to 2.4 times narrower than the width of the posterior usingonly the WWTP operator population size estimates. For large WWTP catchments,the width of the posterior using the population size model was between 5 and 40times narrower than the WWTP operator population size estimates. Additionally, itwas found that the posterior width of the model was improved with addition of morechemicals in the model.In Chapter 4, using laboratory-scale sewer reactors, the impact of in-sewerdegradation of the population markers identified in Chapter 3 was evaluated. It wasfound that five of the fourteen markers were stable under all conditions over the 12hour study period. Those which were unstable ranged from little degradation over thestudy period and only under certain conditions to rapid degradation regardless ofsewer conditions. Additionally we assessed whether or not the degradation of thesechemicals impacted the population size estimation model by excluding the unstablecompounds from the model. We found that the uncertainty of the estimate did notdecrease through exclusion of the unstable chemicals.In Chapter 5 we assessed whether WBE can be expanded to chemicals other thanthose previously assessed (i.e. illicit drugs, alcohol and tobacco). For this a methodwas developed to analyse organophosphorous flame retardants (PFRs) inwastewater influent. Using the samples collected during census, it was estimatedthat 2.1 mg person-1 day-1 enter Australian wastewater. In addition we found a goodcorrelation (r2 ≥ 0.87) between the population size and mass load for each of the fourmain contributors (TBOEP, TCIPP, TDCIPP and TCEP).Overall, this thesis demonstrates that the uncertainty of WBE estimates can beimproved through identifying population markers, and developing and calibrating apopulation model. Additionally, we found that WBE is not limited to assessingexposure/consumption of the chemicals previously assessed (i.e. alcohol, illicit drugsand tobacco) and can be expanded to other chemical groups.

Trends in nicotine consumption between 2010 and 2017 in an Australian city using the wastewater-based epidemiology approach

Wastewater concentrations of human influenza, metapneumovirus, parainfluenza, respiratory syncytial virus, rhinovirus, and seasonal coronavirus nucleic-acids during the COVID-19 pandemic: a surveillance study

BACKGROUND AND AIM: Wastewater based epidemiology (WBE) is a promising tool to monitor the prevalence of COVID-19 disease at community level through detection of SARS-CoV-2 RNA in wastewater. Although WBE has been largely adopted in developed countries as complementary to clinical surveillance, the approach is still not widely applied in low-and-lower-middle-income countries (LMICs) owing to number of drawbacks. Despite these limitations, a small number of studies on wastewater based epidemiology for SARS-CoV-2 detection have been conducted in LMICs. The current systematic review provides an overview of the efficacy of WBE in LMICs. METHODS: We conducted keyword searches in PubMed, Web of Science, and Scopus for articles published between January 2020 to February 2022. A total of 2,057 relevant articles were identified, and 21 met our inclusion/exclusion criteria. RESULTS: The most common analytical steps used in included studies are sampling, storage, concentration, extraction, and detection. Studies utilized either composite/grab raw sludge or influents mostly from wastewater treatment plants, which covered a population of one to ten million. Among the studies, Among the studies, the most commonly used concentration technique was Poly Ethylene Glycol (PEG), and the most frequently targeted gene was the N gene. The overall sample positivity was found 81.18%, with viral loads of 40 to 45,000 copies/L. Most of the studies found positive correlation between SARS-CoV-2 viral loads in wastewater and the detected COVID-19 cases. Besides, few studies found higher signals in wastewater with a time lag of one to two weeks before clinical case detection. CONCLUSIONS: These findings of systematic review illustrate the analytical methods used in WBE research, as well as the future of WBE in LMICs, thereby allowing decision-makers to take strategic preventative actions to curb the spread of COVID-19 diseases in LMICs.