Real-time estimation of small-area populations with human biomarkers in sewage

Tissue bioaccumulation and distribution of organic contaminants in Brazilian guitarfish Pseudobatos horkelii reveal a concerning impact of contraceptive hormones and fecal sterols

The critically endangered Brazilian guitarfish faces significant threats from environmental contamination. Assessing the impacts of such stressor is paramount from a conservational perspective. This study investigated the concentrations, distribution and accumulation patterns of organic contaminants in pregnant Brazilian guitarfish Pseudobatos horkelii. Blood, gill, gonad, liver, and muscle concentrations of polychlorinated biphenyls (PCBs), organochlorine pesticides (OCPs), polybrominated diphenyl ethers, fecal sterols, and synthetic hormones used as human contraceptives were assessed. Synthetic hormones, especially D-norgestrel, showed the highest concentrations, mainly in the liver. Together with the results of fecal sterols, this finding suggests that guitarfish are exposed to sewage discharge. OCPs, especially hexachlorobenzene, mirex, endosulfans, and drins, showed considerably high concentrations, indicating the relevance of agricultural inputs. PCBs presented significant concentrations in the muscle, indicating long-term exposure, in contrast with other analytes that were primarily concentrated in the liver. These results have conservational implications, since contaminants analyzed herein have endocrine disruptive effects.

Impact of physicochemical parameters on nicotine metabolites and Bisphenol A in municipal wastewater: A pilot study in a German metropolitan area

Wastewater-based epidemiology (WBE) is a promising approach for assessing population-level exposures to toxicants and lifestyle factors. Our pilot investigated the spatial variability of biomarkers indicating exposure to nicotine and endocrine disrupting chemicals in municipal wastewater, taking into account important covariates, i.e. physicochemical wastewater parameters and sewershed characteristics. We also tested normalization by an endogenous population marker. Twenty-four-hour composite samples (n = 24) were collected in a volume-proportional manner using automated samplers from four wastewater treatment plants in Essen, Germany, over three weeks in late 2023. Substances of public health concern, previously already quantified in wastewater and expected to be present in high concentrations, were analyzed using SPE-LC-HRMS. Concentrations were normalized to the reported population (de jure) and the daily mass load of the catecholamine metabolite vanillylmandelic acid (VMA) as a proxy for the de facto population. Spatial variations were analyzed using multiple linear regression. Nicotine metabolites (cotinine, hydroxycotinine) and the industrial chemical Bisphenol A (BPA) were quantifiable in all wastewater samples. The population-normalized daily mass load of nicotine metabolites (median range: 0.6-1.6 g/d/1000 inh) and BPA (2.5-4.0 g/d/1000 inh) varied between the WWTPs, but the observed variation disappeared when adjusting for wastewater temperature (nicotine) and wastewater pH (BPA). Normalization to the VMA daily mass load resulted in different spatial patterns and increased the variance considerably. Our findings highlight the importance of adjusting for physicochemical characteristics when analyzing community-wide differences in exposure to toxicants and lifestyle factors via wastewater, to ensure accurate interpretations of the underlying drivers of these differences.

Improved entropy-CRITIC population model based on temporal and spatial variability: Construction and application in wastewater epidemiology

Numerous factors contribute to the uncertainty inherent in conducting wastewater-based epidemiology (WBE), with shifting populations exerting a significant influence. However, traditional single- and multi-parameter population models suffer from certain limitations. This study employs an evaluation model framework to construct a model (EC model) based on data characteristics. Weight coefficients derived from 16 cities across seven regions of China are aggregated into a national model. In contrast to alternative models, the EC model exhibits a robust correlation (r2 = 0.98) with census population data, suggesting a potentially more precise depiction of population dynamics. The low variability (RSD = 9.73 %) indicates effective constraint of anomalous parameter fluctuations, yielding minimal Bias (-1.12 %) and SRMSE (14.75 %), thus ensuring reliable population estimation. The model is applied to estimate the consumption of lifestyle-related compounds and the prevalence of hypertension in China. Northern regions demonstrate higher consumption levels, alongside a significant disparity in hypertension prevalence (26.96 %) compared to the south (16.01 %). Hypertension exhibits positive correlations with lifestyle-related compounds such as alcohol and nicotine (r = 0.52, r = 0.55). Sensitivity analysis reveals that the EC model introduces an uncertainty of 24.48 % in population estimates. Through the incorporation of representative datasets and novel algorithms, this model has the potential to enhance the reliability of outcomes in WBE strategy implementation.

A 2000-year record of fecal biomarkers reveals past herbivore presence and impacts in a catchment in northern Yellowstone National Park, USA

Molecular biomarkers preserved in lake sediments are increasingly used to develop records of past organism occurrence. When linked with traditional paleoecological methods, analysis of molecular biomarkers can yield new insights into the roles of herbivores and other animals in long-term ecosystem dynamics. We sought to determine whether fecal steroids in lake sediments could be used to reconstruct past ungulate use and dominant taxa in a small catchment in northern Yellowstone National Park. To do so, we characterized the fecal steroid profiles of a selection of North American ungulates historically present in the Yellowstone region (bison, elk, moose, mule deer, and pronghorn) and compared them with those of sediments from a small lake in the Yellowstone Northern Range. Analysis of a set of fecal steroids from herbivore dung (Δ5-sterols, 5α-stanols, 5β-stanols, epi5β-stanols, stanones, and bile acids) differentiated moose, pronghorn, and mule deer, whereas bison and elk were partially differentiated. Our results show that bison and/or elk were the primary ungulates in the watershed over the past c. 2300 years. Fecal steroid influxes reached historically unprecedented levels during the early and middle 20th century, possibly indicating high local use by ungulates. Comparison of fecal steroid influxes with pollen and diatom data suggests that elevated ungulate presence may have contributed to decreased forage taxa (Poaceae, Artemisia, and Salix), relative to long-term averages, and possibly increased lake production. Our results reflect past change within a single watershed, and extending this approach to a network of sites could provide much-needed information on past herbivore communities, use, and environmental influences in Yellowstone National Park and elsewhere.

Normalization of viral loads in Wastewater-Based Epidemiology using routine parameters: One year monitoring of SARS-CoV-2 in urban and tourist sewersheds

In wastewater-based epidemiology, normalization of experimental data is a crucial aspect, as emerged in the recent surveillance of COVID-19. Normalization facilitates the comparison between different areas or periods, and it helps in evaluating the differences due to the fluctuation of the population due to seasonal employment or tourism. Analysis of biomarkers in wastewater (i.e. drugs, beverage and food compounds, microorganisms such as PMMoV or crAssphage, etc.) is complex to perform, and it is not routinely monitored. This study compares the results of alternative normalization approaches applied to SARS-CoV-2 loads in wastewater using population size calculated with conventional hydraulic and/or chemical parameters (i.e. total suspended solids, chemical oxygen demand, nitrogen forms, etc.) commonly used in the routine monitoring of water quality. A total of 12 wastewater treatment plants were monitored, and 1068 samples of influent wastewater were collected in urban areas and in highly touristic areas (summer and/or winter). The results indicated that both census and population estimated with ammonium are effective and reliable parameters with which to normalize SARS-CoV-2 loads in wastewater from urban sewersheds with negligible fluctuating populations. However, this study reveals that, in the case of tourist locations, the population calculated using NH4-N loads can provide a better normalization of the specific viral load per inhabitant.

Relationship between nitrate, heavy metal, and sterols contents in Japanese agricultural soils with risk of groundwater pollution

In Japanese agricultural lands, nitrate-nitrogen contamination of soil and groundwater often occurs due to the application of livestock excrements and compost. Therefore, rural soils in Japan were sampled and analyzed for nitrate-nitrogen leaching, heavy metal content, and sterols associated with livestock excrement and compost to calculate contamination risk indicators. The results were analyzed using self-organizing maps and cluster analysis. Nitrate-nitrogen content using water extraction was detected in most of the sampled soils. In addition, many samples from areas that were already severely contaminated with nitrate-nitrogen showed particularly high concentrations. Coprostanol, an indicator of fecal contamination, was detected in more than half of the samples. The main source of nitrate-nitrogen contamination in these areas is livestock excrement and compost. Self-organization maps showed that areas with high nitrate-nitrogen contamination also corresponded to areas with high copper and zinc soil contents. The self-organization maps and cluster analysis resulted in five clusters: a nitrate-contaminated group mainly originating from livestock excrement and compost, a heavy metal-contaminated group, a general group, a nitrate-contaminated group mainly originating from chemical fertilizers, and a contaminated group with potentially hazardous substances requiring attention. Authorities and decision-makers can use the results to prioritize areas requiring remediation.

Current state and future perspectives on de facto population markers for normalization in wastewater-based epidemiology: A systematic literature review

Wastewater-based epidemiology (WBE) and wastewater surveillance have become a valuable complementary data source to collect information on community-wide exposure through the measurement of human biomarkers in influent wastewater (IWW). In WBE, normalization of data with the de facto population that corresponds to a wastewater sample is crucial for a correct interpretation of spatio-temporal trends in exposure and consumption patterns. However, knowledge gaps remain in identifying and validating suitable de facto population biomarkers (PBs) for refinement of WBE back-estimations. WBE studies that apply de facto PBs (including hydrochemical parameters, utility consumption data sources, endo- and exogenous chemicals, biological biomarkers and signalling records) for relative trend analysis and absolute population size estimation were systematically reviewed from three databases (PubMed, Web of Science, SCOPUS) according to the PRISMA guidelines. We included in this review 81 publications that accounted for daily variations in population sizes by applying de facto population normalization. To date, a wide range of PBs have been proposed for de facto population normalization, complicating the comparability of normalized measurements across WBE studies. Additionally, the validation of potential PBs is complicated by the absence of an ideal external validator, magnifying the overall uncertainty for population normalization in WBE. Therefore, this review proposes a conceptual tier-based cross-validation approach for identifying and validating de facto PBs to guide their integration for i) relative trend analysis, and ii) absolute population size estimation. Furthermore, this review also provides a detailed evaluation of the uncertainty observed when comparing different de jure and de facto population estimation approaches. This study shows that their percentual differences can range up to ±200 %, with some exceptions showing even larger variations. This review underscores the need for collaboration among WBE researchers to further streamline the application of de facto population normalization and to evaluate the robustness of different PBs in different socio-demographic communities.

Towards Evidence-Based Food Safety Governance with Wastewater-Based Epidemiology (WBE) Technology in China

Pesticide residues in food pose significant risks to public health and have long been a major concern in Chinese cities. The management of these risks is influenced by various factors, including the characteristics of responsible officials. This study tests the relationship between the levels of pesticide residues and the responsible officials' interdisciplinary backgrounds and their tenure cycles, which is crucial for improving food safety governance in Chinese cities. Based on wastewater-based epidemiology (WBE) and data from 32 Chinese cities, it was found that the interdisciplinary backgrounds of officials had a significant negative relationship with urban pesticide residues in wastewater, indicating that the interdisciplinary knowledge background or working experience of officials in food safety-related agencies was associated with the supervision and control of urban pesticide residues. This study also generated evidence-based knowledge on how to improve food safety through assigning younger and interdisciplinary officials to the responsible governmental agencies, where WBE is more likely to be adopted.

Estimation of the spatial pattern of gout prevalence across China by wastewater-based epidemiology

Gout is a metabolic arthritis caused by hyperuricemia. In recent years, the prevalence of gout has been increased significantly in China due to the improvement of the living standards, and gout has become another common metabolic disease following diabetes mellitus. Gout severely affects the health status and life quality of human. In order to monitor the near real-time prevalence of gout, a wastewater-based epidemiology (WBE) approach was carried out in 257 Chinese cities using febuxostat as the biomarker. Febuxostat in wastewater was measured by a LC-MS/MS method with satisfactory results of method validation. The average concentration of febuxostat in wastewater was 53.05 ± 31.76 ng/L, with the estimated per capita consumption of 124.40 ± 73.37 mg/day/1000 inhabitant. The calculated prevalence of febuxostat was 0.41 % ± 0.24 %, and the prevalence of gout was finally estimated to be 1.30 % ± 0.77 % (0.60 % to 2.11 %), which was nearly consistent with value of 1.10 % obtained from the Guideline for the diagnosis and management of hyperuricemia and gout in China (2019). The results indicated that the febuxostat-based WBE approach might be reasonable to assess the near real-time gout prevalence in China.

Wastewater-based estimation of diabetes mellitus prevalence in 237 cities: A cross-China study

Diabetes mellitus, a metabolic disease characterized by hyperglycemia, has been witnessed as a rapidly escalating worldwide health crisis. China currently had 140.9 million diabetic population in 2021, which was the largest globally. DM has witnessed a significant surge in the past few decades, leading to an alarming rise in the overall burden caused by this disease. To monitor the near real-time DM prevalence and the consumption of first-line anti-diabetic drugs, a wastewater-based epidemiology (WBE) approach based on the back-calculation of metformin concentration was implemented in 237 cities in China. The quantitative analysis of metformin in wastewater was conducted by LC-MS/MS with satisfactory results of method validation. The average concentration of metformin in wastewater was 14.07 ± 13.16 μg/L, and the per capita consumption was 5.16 ± 2.08 mg/day/inh, ranging from 0.90 to 10.36 ± 4.63 mg/day/inh. The calculated metformin prevalence was found to be 0.52 % ± 0.28 %, and the final estimated DM prevalence was 11.33 % ± 4.99 %, which was nearly consistent with the result of the International Diabetes Federation survey of 9.98 %. The results suggested that metformin might be one of the suitable WBE biomarkers in DM monitoring and WBE strategy could potentially enable the estimation of DM prevalence in most of Chinese cities after reasonable correction of associated parameters.

Application of Magnetic Materials Combined with Echo® Mass Spectrometry System in Analysis of Illegal Drugs in Sewage

The aim of this study is to solve the problems of the complicated pretreatment and high analytical cost in the detection technology of trace drugs and their metabolites in municipal wastewater. A high-performance magnetic sorbent was fsynthesized for the enrichment of trace drugs and their metabolites in wastewater to develop a magnetic solid-phase extraction pretreatment combined with the acoustic ejection mass spectrometry (AEMS) analytical method. The magnetic nanospheres were successfully prepared by magnetic nanoparticles modified with divinylbenzene and vinylpyrrolidone. The results showed that the linear dynamic range of 17 drugs was 1-500 ng/mL, the recovery was 44-100%, the matrix effect was more than 51%, the quantification limit was 1-2 ng/mL, and the MS measurement was fast. It can be seen that the developed magnetic solid-phase extraction (MSPE) method is a good solution to the problems of the complicated pretreatment and analytical cost in the analysis of drugs in wastewater. The developed magnetic material and acoustic excitation pretreatment coupled with mass spectrometry analysis method can realize the low-cost, efficient enrichment, and fast analysis of different kinds of drug molecules in urban sewage.

Wastewater-based surveillance as a tool for public health action: SARS-CoV-2 and beyond

Wastewater-based surveillance (WBS) has undergone dramatic advancement in the context of the coronavirus disease 2019 (COVID-19) pandemic. The power and potential of this platform technology were rapidly realized when it became evident that not only did WBS-measured SARS-CoV-2 RNA correlate strongly with COVID-19 clinical disease within monitored populations but also, in fact, it functioned as a leading indicator. Teams from across the globe rapidly innovated novel approaches by which wastewater could be collected from diverse sewersheds ranging from wastewater treatment plants (enabling community-level surveillance) to more granular locations including individual neighborhoods and high-risk buildings such as long-term care facilities (LTCF). Efficient processes enabled SARS-CoV-2 RNA extraction and concentration from the highly dilute wastewater matrix. Molecular and genomic tools to identify, quantify, and characterize SARS-CoV-2 and its various variants were adapted from clinical programs and applied to these mixed environmental systems. Novel data-sharing tools allowed this information to be mobilized and made immediately available to public health and government decision-makers and even the public, enabling evidence-informed decision-making based on local disease dynamics. WBS has since been recognized as a tool of transformative potential, providing near-real-time cost-effective, objective, comprehensive, and inclusive data on the changing prevalence of measured analytes across space and time in populations. However, as a consequence of rapid innovation from hundreds of teams simultaneously, tremendous heterogeneity currently exists in the SARS-CoV-2 WBS literature. This manuscript provides a state-of-the-art review of WBS as established with SARS-CoV-2 and details the current work underway expanding its scope to other infectious disease targets.

Estimating the prevalence of dyslipidemia by measuring fenofibrate in 33 cities in China

Dyslipidemia, recognized as a predominant risk factor for atherosclerotic cardiovascular disease (CVD), remains a pressing health concern worldwide, particularly in China with nearly 40 % of the population adversely suffering. Fenofibrate, as one of the most commonly used drugs for dyslipidemia therapy, excreted as the format of fenofibrate-acid, which showed considerable stability in sewage samples and could be detected as WBE-biomarkers to monitor the prevalence of dyslipidemia. In this work, we reported the first research on estimating the prevalence of dyslipidemia by WBE approach. 527 sewage samples from 33 cities in China were extracted by solid phase and analyzed by LC-MS/MS. The detected concentration of fenofibrate acid in sewage was on an average of 120.5 ± 59.9 ng/L, and the reverse-calculated consumption of fenofibrate based on fenofibrate acid was 77.8 ± 25.0 mg/day/1000inh. Detailed analysis unveiled an average prevalence of fenofibrate at 0.056 % ± 0.018 %, and the dyslipidemia prevalence among the population aged over 15 was ultimately estimated to be 37.9 % ± 9.3 % and was in accordance with the China Cardiovascular research result of 40.4 %, which proves that WBE is a substitutable approach of traditional epidemiological investigation methods due to its timeliness and cost-effectiveness. This study demonstrated that estimating dyslipidemia prevalence by WBE with metabolite fenofibrate acid as a biomarker is feasible in most Chinese cities.

Analyzing community wastewater in sub-sewersheds for the small-scale detection of SARS-CoV-2 variants in a German metropolitan area

Wastewater surveillance of SARS-CoV-2 proved useful, including for identifying the local appearance of newly identified virus variants. Previous studies focused on wastewater treatment plants (WWTP) with sewersheds of several hundred thousand people or at single building level, representing only a small number of people. Both approaches may prove inadequate for small-scale intra-urban inferences for early detection of emerging or novel virus variants. Our study aims (i) to analyze SARS-CoV-2 single nucleotide variants (SNVs) in wastewater of sub-sewersheds and WWTP using whole genome sequencing in order to (ii) investigate the potential of small-scale detection of novel known SARS-CoV-2 variants of concern (VOC) within a metropolitan wastewater system. We selected three sub-sewershed sampling sites, based on estimated population- and built environment-related indicators, and the inlet of the receiving WWTP in the Ruhr region, Germany. Untreated wastewater was sampled weekly between October and December 2021, with a total of 22 samples collected. SARS-CoV-2 RNA was analyzed by RT-qPCR and whole genome sequencing. For all samples, genome sequences were obtained, while only 13 samples were positive for RT-qPCR. We identified multiple specific SARS-CoV-2 SNVs in the wastewater samples of the sub-sewersheds and the WWTP. Identified SNVs reflected the dominance of VOC Delta at the time of sampling. Interestingly, we could identify an Omicron-specific SNV in one sub-sewershed. A concurrent wastewater study sampling the same WWTP detected the VOC Omicron one week later. Our observations suggest that the small-scale approach may prove particularly useful for the detection and description of spatially confined emerging or existing virus variants circulating in populations. Future studies applying small-scale sampling strategies taking into account the specific features of the wastewater system will be useful to analyze temporal and spatial variance in more detail.

Systematic review and meta-analysis of human health-related protein markers for realizing real-time wastewater-based epidemiology

For effective implementation of the wastewater-based epidemiology (WBE) approach, real-time quantification of markers in wastewater is critical for data acquisition before data interpretation, dissemination, and decision-making. This can be achieved by using biosensor technology, but whether the quantification/detection limits of different types of biosensors comply with the concentration of WBE markers in wastewater is unclear. In the present study, we identified promising protein markers with relatively high concentrations in wastewater samples and analyzed biosensor technologies that are potentially available for real-time WBE. The concentrations of potential protein markers in stool and urine samples were obtained through systematic review and meta-analysis. We examined 231 peer-review papers to collect information regarding potential protein markers that can enable us to achieve real-time monitoring using biosensor technology. Fourteen markers in stool samples were identified at the ng/g level, presumably equivalent to ng/L of wastewater after dilution. Moreover, relatively high average concentrations of fecal inflammatory proteins were observed, e.g., fecal calprotectin, clusterin, and lactoferrin. Fecal calprotectin exhibited the highest average log concentration among the markers identified in stool samples with its mean value being 5.24 [95 % CI: 5.05, 5.42] ng/g. We identified 50 protein markers in urine samples at the ng/mL level. Uromodulin (4.48 [95 % CI: 4.20, 4.76] ng/mL) and plasmin (4.18 [95 % CI: 3.15, 5.21] ng/mL) had the top two highest log concentrations in urine samples. Furthermore, the quantification limit of some electrochemical- and optical-based biosensors was found to be around the femtogram/mL level, which is sufficiently low to detect protein markers in wastewater even after dilution in sewer pipes.

Application of wastewater-based epidemiology to estimate the usage of beta-agonists in 31 cities in China

The illegal use of beta-agonists could cause severe problems to human health. In this study, the usage of beta-agonists in 31 cities across China was estimated using wastewater-based epidemiology (WBE). The proposed method is based on solid-phase extraction (SPE) and LC-MS/MS and was developed and validated to determine the concentration of seven beta-agonists in wastewater. A population model based on cotinine (COT), NH4-N and the flow volume was constructed to estimate the population equivalents for different wastewater treatment plants (WWTPs). Clenbuterol and ractopamine are banned in China for both animal husbandry and medical use, but were nevertheless detected in some wastewater samples at rates of 6.2 % and 4.7 %, respectively (n = 339). The WBE-based consumption of clenbuterol and ractopamine were compared with the acceptable daily intake (ADI) and the health risks were assessed by their hazard quotients (0.26-6.62 for clenbuterol and 9.27 × 10-4-0.05 for ractopamine). Salbutamol, clorprenaline and terbutaline were observed in practically all wastewater samples at concentrations of up to several ng/L, whereas the formoterol and bambuterol concentrations were below the detection limit in all samples. Salbutamol consumption (7.35 ± 4.14 mg/1000 inh/day) was highest among the examined beta-agonists and varied regionally. Beta-agonist consumption based on WBE was higher in some cities than that based on medical survey data, indicating potential illegal use. These results show that WBE can be a straightforward and supplementary method for monitoring beta-agonist usage at the population level and spatially.

Dynamic population normalisation in wastewater-based epidemiology for improved understanding of the SARS-CoV-2 prevalence: a multi-site study

Wastewater-based epidemiology (WBE) is a valuable tool for monitoring the circulation of COVID-19. However, while variations in population size are recognised as major sources of uncertainty, wastewater SARS-CoV-2 measurements are not routinely population-normalised. This paper aims to determine whether dynamic population normalisation significantly alters SARS-CoV-2 dynamics observed through wastewater monitoring, and whether it is beneficial or necessary to provide an understanding of COVID-19 epidemiology. Data from 394 sites in England are used, and normalisation is implemented based on ammoniacal nitrogen and orthophosphate concentrations. Raw and normalised wastewater SARS-CoV-2 metrics are evaluated at the site and spatially aggregated levels are compared against indicators of prevalence based on the Coronavirus Infection Survey and Test and Trace polymerase chain reaction test results. Normalisation is shown, on average, to have a limited impact on overall temporal trends. However, significant variability in the degree to which it affects local-level trends is observed. This is not evident from previous WBE studies focused on single sites and, critically, demonstrates that while the impact of normalisation on SARS-CoV-2 trends is small on average, this may not always be the case. When averaged across many sites, normalisation strengthens the correlation between wastewater SARS-CoV-2 data and prevalence indicators; however, confidence in the improvement is low.

Application of the metal ions as potential population biomarkers for wastewater-based epidemiology: estimating tobacco consumption in Southern China

Wastewater-based epidemiology (WBE) is an objective approach for the estimation of population-level exposure to a wide range of substances, in which the use of a population biomarker (PB) could significantly reduce back-calculation errors. Although some endogenous or exogenous compounds such as cotinine and other hormones have been developed as PBs, more PBs still need to be identified and evaluated. This study aimed to propose a novel method to estimate population parameters from the mass load of metal ion biomarkers in wastewater, and estimate the consumption of tobacco in 24 cities in Southern China using the developed method. Daily wastewater samples were collected from 234 wastewater treatment plants (WWTPs) in 24 cities in Southern China. Atomic absorption spectroscopy (AAS) was applied to determine the concentrations of common health-related metal ions in wastewater, including sodium (Na), potassium (K), magnesium (Mg), calcium (Ca), iron (Fe), and zinc (Zn), and compared them with the daily mass load of cotinine corresponding to catchment populations. The concentrations of cotinine in wastewater samples were measured using liquid chromatography-tandem mass spectrometry. There were clear and strong correlations between the target metal ion equivalent population and census data. The correlation coefficients (R) were R_K = 0.78, R_Na = 0.66, R_Ca = 0.81, R_Mg = 0.77, and R_Fe = 0.69, at p < 0.01 and R² > 0.6. Subsequently, the combination of WBE and metal ion PBs was used to estimate tobacco consumption. Daily consumption of nicotine was estimated to be approximately 1.76 ± 1.19 mg/d/capita, equivalent to an average of 13.0 ± 8.75 cigarettes/d being consumed by smokers. The data on tobacco consumption in this study were consistent with those in traditional surveys in Southern China. The metal ion potassium is an appropriate PB for reflecting the real-time population and could be used to evaluate the tobacco consumption in WBE study.

COVID-19 surveillance in wastewater: An epidemiological tool for the monitoring of SARS-CoV-2

The coronavirus disease 2019 (COVID-19) pandemic has prompted a lot of questions globally regarding the range of information about the virus's possible routes of transmission, diagnostics, and therapeutic tools. Worldwide studies have pointed out the importance of monitoring and early surveillance techniques based on the identification of viral RNA in wastewater. These studies indicated the presence of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) RNA in human feces, which is shed via excreta including mucus, feces, saliva, and sputum. Subsequently, they get dumped into wastewater, and their presence in wastewater provides a possibility of using it as a tool to help prevent and eradicate the virus. Its monitoring is still done in many regions worldwide and serves as an early "warning signal"; however, a lot of limitations of wastewater surveillance have also been identified.

Biomarker selection strategies based on compound stability in wastewater-based epidemiology

The specific compositions of human excreta in sewage can be used as biomarkers to indicate the disease prevalence, health status, and lifestyle of the population living in the investigated catchment. It is important for guiding and evaluating public health policies as well as promoting human health development. Among several parameters of wastewater-based epidemiology (WBE), the decay of biomarkers during transportation in sewer and storage plays a crucial role in the back-calculation of population consumption. In this paper, we summarized the stability data of common biomarkers in storage at different temperatures and in-sewer transportation. Among them, cardiovascular drugs and antidiabetic drugs are very stable which can be used as biomarkers; most of the illicit drugs are stable except for cocaine, heroin, and tetrahydrocannabinol which could be substituted by their metabolites as biomarkers. There are some losses for part of antibiotics and antidepressants even in frozen storage. Rapid detection of contagious viruses is a new challenge for infectious disease control. With the deeper and broader study of biomarkers, it is expected that the reliable application of the WBE will be a useful addition to epidemiological studies.

Evaluation of urban pollution in a tropical lacustrine ecosystem by using n-alkanes and sterols as biomarkers

The Jacarepaguá Lagoon System (JLS) receives industrial and domestic waste in an urban area with high population density and intense economic activity. The hydrography of the lagoons favours the sedimentation of particulate material transferred from the drainage basin. Water engineering, such as channel dredging and subsea outfall, did not satisfactorily mitigate pollution effects. Therefore, the environment is highly eutrophic, presents frequent blooms of algae and generates high emissions of greenhouse gases. There is no record in the literature on the analysis of organic compounds in the water compartment. The present work applies sterols as biomarkers to quantify the degree of pollution caused by biogenic compounds in riverine and lacustrine water of the JLS. n-Alkanes were applied to estimate the fractions of petrogenic contaminants. The sums of n-alkanes and sterols analysed had average concentrations of 21 ± 20 μg L^-1 and 10 ± 8 μg L^-1, respectively, in the river samples and 235 ± 156 μg L^-1 and 30 ± 28 μg L^-1, respectively, in the lagoon samples. The work also showed that the organic compounds inside the lagoons are evenly distributed, and approximately 7% of them are transferred to the marine ecosystem. Biogenic biomarkers and the absolute concentrations of sterols showed that sewage contaminants transferred by the rivers are partially decomposed in the lagoons. The correlations between indices and physicochemical parameters indicated that the degradation of organic compounds in the lagoons occurs mainly in the sediment compartment under anoxic conditions. The indices for sewage indicate that the ecosystem has exceeded its carrying capacity. The indices based on n-alkanes reported strong contamination at all sampling stations and inferred that 75-100% of these compounds were derived from petrogenic sources. These indices did not show any difference between rivers and the lagoon, which demonstrates the resilience of these compounds in the ecosystem.

Illicit drugs and their metabolites in urban wastewater: Analysis, occurrence and consumption in Xinjiang, China

The use of illicit drugs has increased considerably across the world. Wastewater-based epidemiology (WBE) of illicit drugs might help determine the types and quantity of illicit drugs consumed in a region. In this study, WBE was applied to analyze illicit drugs in five representative urban wastewater treatment plants (WWTPs) in Xinjiang, China. The collected samples were pretreated under optimized solid-phase extraction conditions and then analyzed using high-performance liquid chromatography-tandem mass spectrometry (HPLC-MS/MS). The results revealed the presence of 9 of the 11 evaluated drugs; among them, the concentrations of these substances ranged as follows: METH (2.60-10.02 ng/L), MDMA (0.49-6.87 ng/L), MOR (4.53-44.75 ng/L), COD (2.24-8.30 ng/L), MTD (1.36-3.75 ng/L), COC (0.48 ng/L), THC (5.98-18.89 ng/L), BE (1.12-2.45 ng/L) and KET (1.50 ng/L). And an estimate of the per capita consumption revealed morphine (10.2 mg/d/1000inhabitants), cannabis (3.9 mg/d/1000inhabitants), 3,4-methylenedioxymethamphetamine (3.9 mg/d/1000 inhabitants), and methamphetamine (2.2 mg/d/1000 inhabitants) as the main substances of abuse in Xinjiang, China. The results of this study might be taken as a reference for future studies on the continuous monitoring of such drugs.

Surveillance of SARS-CoV-2 in nine neighborhood sewersheds in Detroit Tri-County area, United States: Assessing per capita SARS-CoV-2 estimations and COVID-19 incidence

Wastewater-based epidemiology (WBE) has been suggested as a useful tool to predict the emergence and investigate the extent of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). In this study, we screened appropriate population biomarkers for wastewater SARS-CoV-2 normalization and compared the normalized SARS-CoV-2 values across locations with different demographic characteristics in southeastern Michigan. Wastewater samples were collected between December 2020 and October 2021 from nine neighborhood sewersheds in the Detroit Tri-County area. Using reverse transcriptase droplet digital polymerase chain reaction (RT-ddPCR), concentrations of N1 and N2 genes in the studied sites were quantified, with N1 values ranging from 1.92 × 102 genomic copies/L to 6.87 × 103 gc/L and N2 values ranging from 1.91 × 102 gc/L to 6.45 × 103 gc/L. The strongest correlations were observed with between cumulative COVID-19 cases per capita (referred as COVID-19 incidences thereafter), and SARS-CoV-2 concentrations normalized by total Kjeldahl nitrogen (TKN), creatinine, 5-hydroxyindoleacetic acid (5-HIAA) and xanthine when correlating the per capita SARS-CoV-2 and COVID-19 incidences. When SARS-CoV-2 concentrations in wastewater were normalized and compared with COVID-19 incidences, the differences between neighborhoods of varying demographics were reduced as compared to differences observed when comparing non-normalized SARS-CoV-2 with COVID-19 cases. This indicates when studying the disease burden in communities of different demographics, accurate per capita estimation is of great importance. The study suggests that monitoring selected water quality parameters or biomarkers, along with RNA concentrations in wastewater, will allow adequate data normalization for spatial comparisons, especially in areas where detailed sanitary sewage flows and contributing populations in the catchment areas are not available. This opens the possibility of using WBE to assess community infections in rural areas or the developing world where the contributing population of a sample could be unknown.

MicrobiomeCensus estimates human population sizes from wastewater samples based on inter-individual variability in gut microbiomes

The metagenome embedded in urban sewage is an attractive new data source to understand urban ecology and assess human health status at scales beyond a single host. Analyzing the viral fraction of wastewater in the ongoing COVID-19 pandemic has shown the potential of wastewater as aggregated samples for early detection, prevalence monitoring, and variant identification of human diseases in large populations. However, using census-based population size instead of real-time population estimates can mislead the interpretation of data acquired from sewage, hindering assessment of representativeness, inference of prevalence, or comparisons of taxa across sites. Here, we show that taxon abundance and sub-species diversisty in gut-associated microbiomes are new feature space to utilize for human population estimation. Using a population-scale human gut microbiome sample of over 1,100 people, we found that taxon-abundance distributions of gut-associated multi-person microbiomes exhibited generalizable relationships with respect to human population size. Here and throughout this paper, the human population size is essentially the sample size from the wastewater sample. We present a new algorithm, MicrobiomeCensus, for estimating human population size from sewage samples. MicrobiomeCensus harnesses the inter-individual variability in human gut microbiomes and performs maximum likelihood estimation based on simultaneous deviation of multiple taxa's relative abundances from their population means. MicrobiomeCensus outperformed generic algorithms in data-driven simulation benchmarks and detected population size differences in field data. New theorems are provided to justify our approach. This research provides a mathematical framework for inferring population sizes in real time from sewage samples, paving the way for more accurate ecological and public health studies utilizing the sewage metagenome.

Biomarkers selection for population normalization in SARS-CoV-2 wastewater-based epidemiology

Wastewater-based epidemiology (WBE) has been one of the most cost-effective approaches to track the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) levels in the communities since the coronavirus disease 2019 (COVID-19) outbreak in 2020. Normalizing SARS-CoV-2 concentrations by the population biomarkers in wastewater is critical for interpreting the viral loads, comparing the epidemiological trends among the sewersheds, and identifying the vulnerable communities. In this study, five population biomarkers, pepper mild mottle virus (PMMoV), creatinine (CRE), 5-hydroxyindoleacetic acid (5-HIAA), caffeine (CAF) and its metabolite paraxanthine (PARA) were investigated and validated for their utility in normalizing the SARS-CoV-2 loads through two normalizing approaches using the data from 64 wastewater treatment plants (WWTPs) in Missouri. Their utility in assessing the real-time population contributing to the wastewater was also evaluated. The best performing candidate was further tested for its capacity for improving correlation between normalized SARS-CoV-2 loads and the clinical cases reported in the City of Columbia, Missouri, a university town with a constantly fluctuating population. Our results showed that, except CRE, the direct and indirect normalization approaches using biomarkers allow accounting for the changes in wastewater dilution and differences in relative human waste input over time regardless flow volume and population of the given WWTP. Among selected biomarkers, PARA is the most reliable population biomarker in determining the SARS-CoV-2 load per capita due to its high accuracy, low variability, and high temporal consistency to reflect the change in population dynamics and dilution in wastewater. It also demonstrated its excellent utility for real-time assessment of the population contributing to the wastewater. In addition, the viral loads normalized by the PARA-estimated population significantly improved the correlation (rho=0.5878, p < 0.05) between SARS-CoV-2 load per capita and case numbers per capita. This chemical biomarker complements the current normalization scheme recommended by CDC and helps us understand the size, distribution, and dynamics of local populations for forecasting the prevalence of SARS-CoV2 within each sewershed.

Sterol and PAHs fingerprint analysis of organic matter at Southeast Brazilian Bay

Southeast Brazilian bays have been increasingly degraded by untreated organic loads. Therefore, to assess fecal contamination status, sediment quality regarding polycyclic aromatic hydrocarbons (PAHs), and sources of organic matter (OM), we have determined fine-grained and total organic carbon (TOC) content and concentrations of PAHs and sterols in twenty-six surface sediment samples in Sepetiba Bay. The fine-grained (1-26 %), TOC (0.20-3.45 %), PAHs (<LQ - 78.27 ng g^-1) and sterols (0.10-21.58 μg g^-1) results showed a decreasing trend from the internal to the external sector of the study area. The diagnostic ratios of selected PAHs and sterols indicated a mixture with significant contribution from continental and pyrolytic OM in all stations. The fecal contamination is significant to the internal sector of Sepetiba Bay. Considering a site-specific sediment quality guidelines (SQGs) the PAHs levels with more restricted benchmark values indicate the harbor and the internal sector as contaminated.

Consumption trends of pharmaceuticals and psychoactive drugs in Latvia determined by the analysis of wastewater

Wastewater-based epidemiology (WBE) was applied to evaluate seasonal variations of the consumption of pharmaceuticals (i.e. antibiotics, NSAIDs, antiepileptics, antihypertensives and others), caffeine, alcohol and nicotine in Latvia throughout 2021. In addition, weekly variation of caffeine, nicotine and alcohol consumption was investigated. Pronounced seasonality was observed in the consumption of antibiotics and decongestants, as well as caffeine, nicotine and alcohol. Correlation with COVID-19 statistics was observed in the case of macrolide antibiotics and antiasthmatic salbutamol. Comparison of the estimated consumption values obtained using the WBE approach and the statistics revealed that the majority of compounds data are in good agreement except angiotensin II receptor blocker group antihypertensives where the most overestimated consumption values were observed.

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.

Biomarkers Selection for Population Normalization in SARS-CoV-2 Wastewater-based Epidemiology

Wastewater-based epidemiology (WBE) has been one of the most cost-effective approaches to track the SARS-CoV-2 levels in the communities since the COVID-19 outbreak in 2020. Normalizing SARS-CoV-2 concentrations by the population biomarkers in wastewater can be critical for interpreting the viral loads, comparing the epidemiological trends among the sewersheds, and identifying the vulnerable communities. In this study, five population biomarkers, pepper mild mottle virus (pMMoV), creatinine (CRE), 5-hydroxyindoleacetic acid (5-HIAA), caffeine (CAF) and its metabolite paraxanthine (PARA) were investigated for their utility in normalizing the SARS-CoV-2 loads through developed direct and indirect approaches. Their utility in assessing the real-time population contributing to the wastewater was also evaluated. The best performed candidate was further tested for its capacity for improving correlation between normalized SARS-CoV-2 loads and the clinical cases reported in the City of Columbia, Missouri, a university town with a constantly fluctuated population. Our results showed that, except CRE, the direct and indirect normalization approaches using biomarkers allow accounting for the changes in wastewater dilution and differences in relative human waste input over time regardless flow volume and population at any given WWTP. Among selected biomarkers, PARA is the most reliable population biomarker in determining the SARS-CoV-2 load per capita due to its high accuracy, low variability, and high temporal consistency to reflect the change in population dynamics and dilution in wastewater. It also demonstrated its excellent utility for real-time assessment of the population contributing to the wastewater. In addition, the viral loads normalized by the PARA-estimated population significantly improved the correlation ( rho =0.5878, p <0.05) between SARS-CoV-2 load per capita and case numbers per capita. This chemical biomarker offers an excellent alternative to the currently CDC-recommended pMMoV genetic biomarker to help us understand the size, distribution, and dynamics of local populations for forecasting the prevalence of SARS-CoV2 within each sewershed.

HIGHLIGHT bullet points

The paraxanthine (PARA), the metabolite of the caffeine, is a more reliable population biomarker in SARS-CoV-2 wastewater-based epidemiology studies than the currently recommended pMMoV genetic marker.SARS-CoV-2 load per capita could be directly normalized using the regression functions derived from correlation between paraxanthine and population without flowrate and population data.Normalizing SARS-CoV-2 levels with the chemical marker PARA significantly improved the correlation between viral loads per capita and case numbers per capita.The chemical marker PARA demonstrated its excellent utility for real-time assessment of the population contributing to the wastewater.

Understanding and managing uncertainty and variability for wastewater monitoring beyond the pandemic: Lessons learned from the United Kingdom national COVID-19 surveillance programmes

The COVID-19 pandemic has put unprecedented pressure on public health resources around the world. From adversity, opportunities have arisen to measure the state and dynamics of human disease at a scale not seen before. In the United Kingdom, the evidence that wastewater could be used to monitor the SARS-CoV-2 virus prompted the development of National wastewater surveillance programmes. The scale and pace of this work has proven to be unique in monitoring of virus dynamics at a national level, demonstrating the importance of wastewater-based epidemiology (WBE) for public health protection. Beyond COVID-19, it can provide additional value for monitoring and informing on a range of biological and chemical markers of human health. A discussion of measurement uncertainty associated with surveillance of wastewater, focusing on lessons-learned from the UK programmes monitoring COVID-19 is presented, showing that sources of uncertainty impacting measurement quality and interpretation of data for public health decision-making, are varied and complex. While some factors remain poorly understood, we present approaches taken by the UK programmes to manage and mitigate the more tractable sources of uncertainty. This work provides a platform to integrate uncertainty management into WBE activities as part of global One Health initiatives beyond the pandemic.

Building knowledge of university campus population dynamics to enhance near-to-source sewage surveillance for SARS-CoV-2 detection

Wastewater surveillance has been widely implemented for monitoring of SARS-CoV-2 during the global COVID-19 pandemic, and near-to-source monitoring is of particular interest for outbreak management in discrete populations. However, variation in population size poses a challenge to the triggering of public health interventions using wastewater SARS-CoV-2 concentrations. This is especially important for near-to-source sites that are subject to significant daily variability in upstream populations. Focusing on a university campus in England, this study investigates methods to account for variation in upstream populations at a site with highly transient footfall and provides a better understanding of the impact of variable populations on the SARS-CoV-2 trends provided by wastewater-based epidemiology. The potential for complementary data to help direct response activities within the near-to-source population is also explored, and potential concerns arising due to the presence of heavily diluted samples during wet weather are addressed. Using wastewater biomarkers, it is demonstrated that population normalisation can reveal significant differences between days where SARS-CoV-2 concentrations are very similar. Confidence in the trends identified is strongest when samples are collected during dry weather periods; however, wet weather samples can still provide valuable information. It is also shown that building-level occupancy estimates based on complementary data aid identification of potential sources of SARS-CoV-2 and can enable targeted actions to be taken to identify and manage potential sources of pathogen transmission in localised communities.

Partitioning of phytocannabinoids between faeces and water - Implications for wastewater-based epidemiology

Evaluating consumption estimates for lipophilic drugs in wastewater has proven to be a challenge. A common feature for these compounds is that they are excreted in faeces and in conjugated form in urine. Limited research with no obvious experimental evidence has been conducted to investigate the degree to which faecal-bound chemical markers contribute towards mass loads in wastewater. Cannabis chemical markers, known as phytocannabinoids, have been suggested in literature to fall into this category. In this study, cannabis users (n = 9) and non-cannabis users (n = 5) were recruited and provided faecal and urine samples after using the substance. The common chemical markers of cannabis consumption, 11-nor-9-carboxy-Δ⁹-tetrahydrocannabinol (THC-COOH), 11-hydroxy-Δ⁹-tetrahydrocannabinol (THC-OH), Δ⁹-tetrahydrocannabinol (THC) and cannabidiol (CBD), were investigated. An extraction method was developed for the cannabis chemical markers in faecal matter and urine and analysis was performed by liquid chromatography-mass spectrometry. Participant samples were used to establish adsorption and desorption dissolution kinetics models and to assess the equilibrium between faeces and water for these compounds. Equilibration between phases were found to be fast (<5 min). THC-COOH, which is the primary metabolite used in wastewater studies, partitioned ~40% in water while the less polar metabolite and CBD remained largely associated with the particulate fraction. Faecal loads of both cannabis users and non-users affected the total measured amounts of cannabinoids in the aqueous phase. The implications for wastewater monitoring of lipophilic substances are discussed.

Coprostanol as a Population Biomarker for SARS-CoV-2 Wastewater Surveillance Studies

Wastewater surveillance is a cost-effective tool for monitoring SARS-CoV-2 transmission in a community. However, challenges remain with regard to interpretating such studies, not least in how to compare SARS-CoV-2 levels between different-sized wastewater treatment plants. Viral faecal indicators, including crAssphage and pepper mild mottle virus, have been proposed as population biomarkers to normalise SARS-CoV-2 levels in wastewater. However, as these indicators exhibit variability between individuals and may not be excreted by everyone, their utility as population biomarkers may be limited. Coprostanol, meanwhile, is a bacterial metabolite of cholesterol which is excreted by all individuals. In this study, composite influent samples were collected from a large- and medium-sized wastewater treatment plant in Dublin, Ireland and SARS-CoV-2 N1, crAssphage, pepper mild mottle virus, HF183 and coprostanol levels were determined. SARS-CoV-2 N1 RNA was detected and quantified in all samples from both treatment plants. Regardless of treatment plant size, coprostanol levels exhibited the lowest variation in composite influent samples, while crAssphage exhibited the greatest variation. Moreover, the strongest correlations were observed between SARS-CoV-2 levels and national and Dublin COVID-19 cases when levels were normalised to coprostanol. This work demonstrates the usefulness of coprostanol as a population biomarker for wastewater surveillance studies.

A nationwide indicator to smooth and normalize heterogeneous SARS-CoV-2 RNA data in wastewater

Since many infected people experience no or few symptoms, the SARS-CoV-2 epidemic is frequently monitored through massive virus testing of the population, an approach that may be biased and may be difficult to sustain in low-income countries. Since SARS-CoV-2 RNA can be detected in stool samples, quantifying SARS-CoV-2 genome by RT-qPCR in wastewater treatment plants (WWTPs) has been carried out as a complementary tool to monitor virus circulation among human populations. However, measuring SARS-CoV-2 viral load in WWTPs can be affected by many experimental and environmental factors. To circumvent these limits, we propose here a novel indicator, the wastewater indicator (WWI), that partly reduces and corrects the noise associated with the SARS-CoV-2 genome quantification in wastewater (average noise reduction of 19%). All data processing results in an average correlation gain of 18% with the incidence rate. The WWI can take into account the censorship linked to the limit of quantification (LOQ), allows the automatic detection of outliers to be integrated into the smoothing algorithm, estimates the average measurement error committed on the samples and proposes a solution for inter-laboratory normalization in the absence of inter-laboratory assays (ILA). This method has been successfully applied in the context of Obépine, a French national network that has been quantifying SARS-CoV-2 genome in a representative sample of French WWTPs since March 5th 2020. By August 26th, 2021, 168 WWTPs were monitored in the French metropolitan and overseas territories of France. We detail the process of elaboration of this indicator, show that it is strongly correlated to the incidence rate and that the optimal time lag between these two signals is only a few days, making our indicator an efficient complement to the incidence rate. This alternative approach may be especially important to evaluate SARS-CoV-2 dynamics in human populations when the testing rate is low.

A data fusion approach to the estimation of temporary populations: An application to Australia

This study establishes a new method for estimating the monthly Average Population Present (APP) in Australian regions. Conventional population statistics, which enumerate people where they usually live, ignore the significant spatial mobility driving short term shifts in population numbers. Estimates of the temporary or ambient population of a region have several important applications including the provision of goods and services, emergency preparedness and serve as more appropriate denominators for a range of social statistics. This paper develops a flexible modelling framework to generate APP estimates from an integrated suite of conventional and novel data sources. The resultant APP estimates reveal the considerable seasonality in small area populations across Australia’s regions alongside the contribution of domestic and international visitors as well as absent residents to the observed monthly variations. The modelling framework developed in the paper is conceived in a manner such that it can be adapted and re-deployed both for use with alternative data sources as well as other situational contexts for the estimation of temporary populations.

Estimating dynamic population served by wastewater treatment plants using location-based services data

Wastewater-based epidemiology is a useful approach to estimate population-level exposure to a wide range of substances (e.g., drugs, chemicals, biological agents) by wastewater analysis. An important uncertainty in population normalized loads generated is related to the size and variability of the actual population served by wastewater treatment plants (WWTPs). Here, we built a population model using location-based services (LBS) data to estimate dynamic consumption of illicit drugs. First, the LBS data from Tencent Location Big Data and resident population were used to train a linear population model for estimating population (r² = 0.92). Then, the spatiotemporal accuracy of the population model was validated. In terms of temporal accuracy, we compared the model-based population with the time-aligned ammonia nitrogen (NH₄-N) population within the WWTP of SEG, showing a mean squared error of < 10%. In terms of spatial accuracy, we estimated the model-based population of 42 WWTPs in Dalian and compared it with the NH₄-N and design population, indicating good consistency overall (5% less than NH₄-N and 4% less than design). Furthermore, methamphetamine consumption and prevalence based on the model were calculated with an average of 111 mg/day/1000 inhabitants and 0.24%, respectively, and dynamically displayed on a visualization system for real-time monitoring. Our study provided a dynamic and accurate population for estimating the population-level use of illicit drugs, much improving the temporal and spatial trend analysis of drug use. Furthermore, accurate information on drug use could be used to assess population health risks in a community.

A method and its application to determine the amount of cannabinoids in sewage sludge and biosolids

Xenobiotic cannabinoids (phyto and synthetic) are highly lipophilic compounds and have been shown to accumulate within the particulate fraction of wastewater. Limited research has been conducted to investigate the occurrence of cannabinoids in sewage sludge and/or biosolids. The analysis of excreted cannabinoids from sewage sludge or biosolids can provide information about community health, as well as potentially long-term environmental impacts. In this study, a liquid-liquid extraction method was developed for the extraction and detection method for 50 cannabinoids by liquid chromatography-mass spectrometry, including the cannabis urinary biomarker 11-nor-9-carboxy-Δ⁹-tetrahydrocannabinol (THC-COOH), Δ⁹-tetrahydrocannabinol (THC), cannabidiol (CBD), and a variety of different generation synthetic cannabinoids and their respective metabolites. Method validation assessed criteria including linearity, selectivity, recovery, and matrix effects. The method was applied to samples collected from a conventional activated sludge reactor treatment facility from various stages of the treatment process. Three cannabinoids were abundant in primary sludge including THC, THC-COOH, and CBD, where THC was the most ubiquitous with concentrations up to 3200 μg kg^-1. Only THC and THC-COOH were detectable in aged biosolids. The detection of some cannabinoids in biosolids demonstrated that these compounds are stable throughout the treatment process.

Wastewater-Based Epidemiology for Cost-Effective Mass Surveillance of COVID-19 in Low- and Middle-Income Countries: Challenges and Opportunities

Wastewater-based epidemiology (WBE) is an approach that can be used to estimate COVID-19 prevalence in the population by detecting severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) RNA in wastewater. As the WBE approach uses pooled samples from the study population, it is an inexpensive and non-invasive mass surveillance method compared to individual testing. Thus, it offers a good complement in low- and middle-income countries (LMICs) facing high costs of testing or social stigmatization, and it has a huge potential to monitor SARS-CoV-2 and its variants to curb the global COVID-19 pandemic. The aim of this review is to systematize the current evidence about the application of the WBE approach in mass surveillance of COVID-19 infection in LMICs, as well as its future potential. Among other parameters, population size contributing the fecal input to wastewater is an important parameter for COVID-19 prevalence estimation. It is easier to back-calculate COVID-19 prevalence in the community with centralized wastewater systems, because there can be more accurate estimates about the size of contributing population in the catchment. However, centralized wastewater management systems are often of low quality (or even non-existent) in LMICs, which raises a major concern about the ability to implement the WBE approach. However, it is possible to mobilize the WBE approach, if large areas are divided into sub-areas, corresponding to the existing wastewater management systems. In addition, a strong coordination between stakeholders is required for estimating population size respective to wastewater management systems. Nevertheless, further international efforts should be leveraged to strengthen the sanitation infrastructures in LMICs, using the lessons gathered from the current COVID-19 pandemic to be prepared for future pandemics.

Climate change facilitated the early colonization of the Azores Archipelago during medieval times

Humans have made such dramatic and permanent changes to Earth's landscapes that much of it is now substantially and irreversibly altered from its preanthropogenic state. Remote islands, until recently isolated from humans, offer insights into how these landscapes evolved in response to human-induced perturbations. However, little is known about when and how remote systems were colonized because archaeological data and historical records are scarce and incomplete. Here, we use a multiproxy approach to reconstruct the initial colonization and subsequent environmental impacts on the Azores Archipelago. Our reconstructions provide unambiguous evidence for widespread human disturbance of this archipelago starting between 700_-60 ⁺⁵⁰ and 850_-60 ⁺⁶⁰ Common Era (CE), ca. 700 y earlier than historical records suggest the onset of Portuguese settlement of the islands. Settlement proceeded in three phases, during which human pressure on the terrestrial and aquatic ecosystems grew steadily (i.e., through livestock introductions, logging, and fire), resulting in irreversible changes. Our climate models suggest that the initial colonization at the end of the early Middle Ages (500 to 900 CE) occurred in conjunction with anomalous northeasterly winds and warmer Northern Hemisphere temperatures. These climate conditions likely inhibited exploration from southern Europe and facilitated human settlers from the northeast Atlantic. These results are consistent with recent archaeological and genetic data suggesting that the Norse were most likely the earliest settlers on the islands.

Tracing sewage contamination based on sterols and stanols markers within the mainland aquatic ecosystem: a case study of Linggi catchment, Malaysia

Sewage contamination is a principal concern in water quality management as pathogens in sewage can cause diseases and lead to detrimental health effects in humans. This study examines the distribution of seven sterol compounds, namely coprostanol, epi-coprostanol, cholesterol, cholestanol, stigmasterol, campesterol, and β-sitosterol in filtered and particulate phases of sewage treatment plants (STPs), groundwater, and river water. For filtered samples, solid-phase extraction (SPE) was employed while for particulate samples were sonicated. Quantification was done by using gas chromatography-mass spectrometer (GC-MS). Faecal stanols (coprostanol and epi-coprostanol) and β-sitosterol were dominant in most STP samples. Groundwater samples were influenced by natural/biogenic sterol, while river water samples were characterized by a mixture of sources. Factor loadings from principal component analysis (PCA) defined fresh input of biogenic sterol and vascular plants (positive varimax factor (VF)1), aged/treated sewage sources (negative VF1), fresh- and less-treated sewage and domestic sources (positive VF2), biological sewage effluents (negative VF2), and fresh-treated sewage sources (VF3) in the samples. Association of VF loadings and factor score values illustrated the correlation of STP effluents and the input of biogenic and plant sterol sources in river and groundwater samples of Linggi. This study focuses on sterol distribution and its potential sources; these findings will aid in sewage assessment in the aquatic environment.

Application of catecholamine metabolites as endogenous population biomarkers for wastewater-based epidemiology

Wastewater-based epidemiology studies use catchment populations to normalise chemical marker mass loads in 24-h composite wastewater samples. However, one of the biggest uncertainties within the field is the accuracy of the population used. A population marker in wastewater may significantly reduce the uncertainty. This study evaluated the catecholamine metabolites - homovanillic acid (HVA) and vanillylmandelic acid (VMA) - as potential population biomarkers. Influent wastewater 24-h composite samples were collected from 38 wastewater catchments from around Australia (representing ~33% of Australia's population), extracted and analysed by liquid chromatography tandem mass spectrometry. Measured mass loads were compared to population sizes determined by mapping catchment maps against high-resolution census data. Both biomarkers correlated with coefficient of determinations (r²) of 0.908 and 0.922 for HVA and VMA, respectively. From the regression analysis, a slope (i.e. the daily per-capita excretion) of 1.241 and 1.067 mg.day^-1.person^-1 was obtained for HVA and VMA, respectively. The mass load ratio between VMA:HVA were very similar to that reported in literature for urinary analysis among all catchments. Overall, this study provided further evidence that catecholamine metabolites are suitable candidates as population biomarkers for future studies.

Evaluation of Illicit Drug Consumption by Wastewater Analysis Using Polar Organic Chemical Integrative Sampler as a Monitoring Tool

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.

Application of multi-parameter population model based on endogenous population biomarkers and flow volume in wastewater epidemiology

The consumption or prevalence of acesulfame, caffeine, paracetamol and amantadine was estimated by wastewater-based epidemiology based on a multi-parameter population model in 20 sewage treatment plants (STPs) in Hebei province, China. To minimize the uncertainties contributed by population estimation in WBE, a multi-parameter population model was established based on the population biomarkers equivalent population and flow volume-population with the weight factors calculated by the analytic hierarchy process (AHP). 4-Pyridoxic acid (4-PA), cotinine, trans-3'-hydroxycotinine (trans-3'-OH-Cot) and 1,4-methylimidazole acetic acid (MIAA) were selected as population biomarkers. The estimated model population showed the highest correlations (r² = 0.97, p < 0.01) and lowest variation (one way-ANOVA, p = 0.82, mean variation: -0.1%) comparing to the census data, suggestion better population estimation. The estimated consumption of acesulfame, caffeine, paracetamol and amantadine was 6.7 ± 2.4 mg/day/inh, 50.5 ± 38.5 mg/day/inh, 61.5 ± 52.7 mg/day/inh and 0.52 ± 0.33 mg/day/inh, respectively. Meanwhile, the prevalence of paracetamol and amantadine was calculated to be 5.3% ± 4.5% and 0.28% ± 0.18%, respectively. The estimated results were consistent with that of previous researches in China and were also in accordance with the consumption calculated by sales data (acesulfame and paracetamol). Moreover, uncertainty study showed decrease in population-associated uncertainties by using a multi-parameter population model. The results demonstrated that the multi-parameter population model constructed in this research is feasible to apply in WBE and might lead to lower uncertainties in population estimation.

Wastewater-based prevalence trends of gout in an Australian community over a period of 8 years

Gout is a rheumatic arthritis disease which poses a health burden. Monitoring the prevalence of gout is key to reduce the community burden of gout disease and associated health costs. Allopurinol has been used as a first line gout preventive medication in Australia which is metabolised into oxypurinol and excreted in urine. Wastewater-based epidemiology (WBE) was applied to estimate temporal trends of gout prevalence in an Australian community over eight-years via the quantification of oxypurinol in wastewater. A total of 180 wastewater samples collected between 2012 and 2019 were analysed for oxypurinol to estimate allopurinol consumption in a community in South East Queensland, Australia. Annual gout prevalence was estimated by daily defined doses (DDD) consumed and ranged from 24 to 32 DDD/day/1000, an equivalent gout prevalence of 2.3 to 3.2% over the eight-year period. A statistically significant increase in allopurinol consumption was observed over the period (Slope = 0.094, p = 0.0001), equating to year-on-year increases in gout prevalence of 3.6% per year. To the best of our knowledge, this is the first long-term gout prevalence study using wastewater, adding epidemiological and public health insights in the gout research field.

Basketball and drugs: Wastewater-based epidemiological estimation of discharged drugs during basketball games in Kentucky

High school sports gather a significantly larger number of fans than college and professional sports in the U.S. Adolescent and adult students in high schools and colleges (aged 12-25) are among the most vulnerable population to substance use. Event planners, risk managers, and emergency medical service personnel can extrapolate the mass loads of drugs in wastewater in this study to evaluate the spectator behavior in relatively larger basketball gatherings. Thirty-three illicit and prescribed psychotic drug residues (out of target 36) and five new psychoactive substances (NPS, out of target 40) were quantified in wastewater, using ultra-performance liquid chromatography and tandem mass spectrometry, discharged during a college and a high school basketball games that were played in the same stadium in Kentucky. The wastewater concentrations of amphetamine, methylphenidate, hydromorphone were significantly higher (p ≤ 0.040) during a high school basketball game whereas cocaine, hydrocodone, and gabapentin was significantly higher (p ≤ 0.006) in a college basketball game. Higher cocaine to its metabolite ratio suggested that a significant amount of cocaine may have directly discharged down the drain during the college basketball game. Two synthetic cathinones (methcathinone and 4-methyl pentedrone) and three other NPSs (4-ANPP, mCPP, and 4-methylamphetamine) were also quantified in wastewater indicate the prevalence of NPSs in Kentucky. This is the first report of quantified substances of potential abuses at basketball games.

Effect of lockdown on wastewater characteristics: a comparison of two large urban areas

The effect of the lockdown imposed to limit the spread of SARS-CoV-2 in France between March 14 and May 11, 2020 on the wastewater characteristics of two large urban areas (with between 250,000 and 300,000 inhabitants) was studied. The number of outward and inward daily commuters was extracted from national census databases related to the population and their commuting habits. For urban area A, with the larger number of daily inward commuters (110,000, compared to 53,000 for B), lockdown was observed to have an effect on the monthly load averages of chemical oxygen demand, biochemical oxygen demand, total Kjeldahl nitrogen, total suspended solids and total phosphorus, all of which decreased (confidence level of 95%). This decrease, which varied between 20% and 40% and reached 45% for COD, can be related to the cessation of catering and activities such as hairdressing, which generate large amounts of graywater. The ammonium loads, due to the use of toilets before leaving for work and after returning from work, remained constant. In the case of urban area B, lockdown had no noticeable effect. More data would be necessary in the long term to analyze the effect of changes in the balance between ammonia and carbon sources on the operation of wastewater treatment plants.

Making waves: Wastewater-based epidemiology for COVID-19 - approaches and challenges for surveillance and prediction

The presence of SARS-CoV-2 in the feces of infected patients and wastewater has drawn attention, not only to the possibility of fecal-oral transmission but also to the use of wastewater as an epidemiological tool. The COVID-19 pandemic has highlighted problems in evaluating the epidemiological scope of the disease using classical surveillance approaches, due to a lack of diagnostic capacity, and their application to only a small proportion of the population. As in previous pandemics, statistics, particularly the proportion of the population infected, are believed to be widely underestimated. Furthermore, analysis of only clinical samples cannot predict outbreaks in a timely manner or easily capture asymptomatic carriers. Threfore, community-scale surveillance, including wastewater-based epidemiology, can bridge the broader community and the clinic, becoming a valuable indirect epidemiological prediction tool for SARS-CoV-2 and other pandemic viruses. This article summarizes current knowledge and discusses the critical factors for implementing wastewater-based epidemiology of COVID-19.

Estimating the prevalence of hepatitis B by wastewater-based epidemiology in 19 cities in China

China has the world's largest burden of Hepatitis B virus (HBV) infection, with 86 million HBV carriers, including 32 million chronic Hepatitis B patients. To monitor the HBV prevalence in near real-time, a wastewater-based epidemiology (WBE) method by using lamivudine as a biomarker was conducted in 19 cities in the Southern part of China. LC-MS/MS was utilized to quantify lamivudine in sewage, and satisfactory method validation results were achieved. The average concentration of lamivudine in sewage was 156.4 ± 107.1 ng/L, and the daily consumption was 30.1 ± 19.8 mg/day/1000inh in average ranging from 0.4 to 105.5 mg/day/1000inh. The prevalence of chronic Hepatitis B was estimated to be 2.5% ± 1.7% based on the prevalence of lamivudine usage, which was 0.035% ± 0.023%. Besides, the estimated HBV prevalence in population aged over 15 years in 19 cities was 6.8% ± 4.5% and was consistent with the previous statistical data of 7% in 2018. This research demonstrated that the estimation of HBV prevalence by WBE with lamivudine as a biomarker is feasible in big cities in Southern China.

Implementation of environmental surveillance for SARS-CoV-2 virus to support public health decisions: Opportunities and challenges

Analysing wastewater can be used to track infectious disease agents that are shed via stool and urine. Sewage surveillance of SARS-CoV-2 has been suggested as a tool to determine the extent of COVID-19 in cities and serve as an early warning for (re-)emergence of SARS-CoV-2 circulation in communities. The focus of this review is on the strength of evidence, opportunities and challenges for the application of sewage surveillance to inform public health decision making. Considerations for undertaking sampling programs are reviewed including sampling sites, strategies, sample transport, storage and quantification methods; together with the approach and evidence base for quantifying prevalence of infection from measured wastewater concentration. Published SARS-CoV-2 sewage surveillance studies (11 peer reviewed and 10 preprints) were reviewed to demonstrate the current status of implementation to support public health decisions. Although being very promising, a number of areas were identified requiring additional research to further strengthen this approach and take full advantage of its potential. In particular, design of adequate sampling strategies, spatial and temporal resolution of sampling, sample storage, replicate sampling and analysis, controls for the molecular methods used for the quantification of SARS-CoV-2 RNA in wastewater. The use of appropriate prevalence data and methods to correlate or even translate SARS-CoV-2 concentrations in wastewater to prevalence of virus shedders in the population is discussed.