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

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

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.

Wastewater-based epidemiology applied at the building-level reveals distinct virome profiles based on the age of the contributing individuals.

BACKGROUND: Human viruses released into the environment can be detected and characterized in wastewater. The study of wastewater virome offers a consolidated perspective on the circulation of viruses within a population. Because the occurrence and severity of viral infections can vary across a person's lifetime, studying the virome in wastewater samples contributed by various demographic segments can provide valuable insights into the prevalence of viral infections within these segments. In our study, targeted enrichment sequencing was employed to characterize the human virome in wastewater at a building-level scale. This was accomplished through passive sampling of wastewater in schools, university settings, and nursing homes in two cities in Catalonia. Additionally, sewage from a large urban wastewater treatment plant was analysed to serve as a reference for examining the collective excreted human virome. RESULTS: The virome obtained from influent wastewater treatment plant samples showcased the combined viral presence from individuals of varying ages, with astroviruses and human bocaviruses being the most prevalent, followed by human adenoviruses, polyomaviruses, and papillomaviruses. Significant variations in the viral profiles were observed among the different types of buildings studied. Mamastrovirus 1 was predominant in school samples, salivirus and human polyomaviruses JC and BK in the university settings while nursing homes showed a more balanced distribution of viral families presenting papillomavirus and picornaviruses and, interestingly, some viruses linked to immunosuppression. CONCLUSIONS: This study shows the utility of building-level wastewater-based epidemiology as an effective tool for monitoring the presence of viruses circulating within specific age groups. It provides valuable insights for public health monitoring and epidemiological studies.

Correlation between Viral Wastewater Concentration and Respiratory Tests, Oregon, USA.

We evaluated the association between wastewater concentration and weekly percent positivity of patient testing for SARS-CoV-2, influenza, and respiratory syncytial virus in Oregon, USA. We found strong, positive correlations for SARS-CoV-2 (ρ = 0.84, p<0.001), influenza (ρ = 0.73, p<0.001) and respiratory syncytial virus (ρ = 0.69, p<0.001).

Respiratory Viruses in Wastewater Compared with Clinical Samples, Leuven, Belgium.

In a 2-year study in Leuven, Belgium, we investigated the use of wastewater sampling to assess community spread of respiratory viruses. Comparison with the number of positive clinical samples demonstrated that wastewater data reflected circulation levels of typical seasonal respiratory viruses, such as influenza, respiratory syncytial virus, and enterovirus D68.

Wastewater surveillance for bacterial targets: current challenges and future goals.

Wastewater-based epidemiology (WBE) expanded rapidly in response to the COVID-19 pandemic. As the public health emergency has ended, researchers and practitioners are looking to shift the focus of existing wastewater surveillance programs to other targets, including bacteria. Bacterial targets may pose some unique challenges for WBE applications. To explore the current state of the field, the National Science Foundation-funded Research Coordination Network (RCN) on Wastewater Based Epidemiology for SARS-CoV-2 and Emerging Public Health Threats held a workshop in April 2023 to discuss the challenges and needs for wastewater bacterial surveillance. The targets and methods used in existing programs were diverse, with twelve different targets and nine different methods listed. Discussions during the workshop highlighted the challenges in adapting existing programs and identified research gaps in four key areas: choosing new targets, relating bacterial wastewater data to human disease incidence and prevalence, developing methods, and normalizing results. To help with these challenges and research gaps, the authors identified steps the larger community can take to improve bacteria wastewater surveillance. This includes developing data reporting standards and method optimization and validation for bacterial programs. Additionally, more work is needed to understand shedding patterns for potential bacterial targets to better relate wastewater data to human infections. Wastewater surveillance for bacteria can help provide insight into the underlying prevalence in communities, but much work is needed to establish these methods.IMPORTANCEWastewater surveillance was a useful tool to elucidate the burden and spread of SARS-CoV-2 during the pandemic. Public health officials and researchers are interested in expanding these surveillance programs to include bacterial targets, but many questions remain. The NSF-funded Research Coordination Network for Wastewater Surveillance of SARS-CoV-2 and Emerging Public Health Threats held a workshop to identify barriers and research gaps to implementing bacterial wastewater surveillance programs.

Persistence of human respiratory viral RNA in wastewater-settled solids.

Wastewater-based epidemiology has emerged as a valuable tool for monitoring respiratory viral diseases within communities by analyzing concentrations of viral nucleic-acids in wastewater. However, little is known about the fate of respiratory virus nucleic-acids in wastewater. Two important fate processes that may modulate their concentrations in wastewater as they move from household drains to the point of collection include sorption or partitioning to wastewater solids and degradation. This study investigated the decay kinetics of genomic nucleic-acids of seven human respiratory viruses, including severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), respiratory syncytial virus (RSV), human coronavirus (HCoV)-OC43, HCoV-229E, HCoV-NL63, human rhinovirus (HRV), and influenza A virus (IAV), as well as pepper mild mottle virus (PMMoV) in wastewater solids. Viruses (except for PMMoV) were spiked into wastewater solids and their concentrations were followed for 50 days at three different temperatures (4°C, 22°C, and 37°C). Viral genomic RNA decayed following first-order kinetics with decay rate constants k from 0 to 0.219 per day. Decay rate constants k were not different from 0 for all targets in solids incubated at 4°C; k values were largest at 37°C and at this temperature, k values were similar across nucleic-acid targets. Regardless of temperature, there was limited viral RNA decay, with an estimated 0% to 20% reduction, over the typical residence times of sewage in the piped systems between input and collection point (<1 day). The k values reported herein can be used directly in fate and transport models to inform the interpretation of measurements made during wastewater surveillance.IMPORTANCEUnderstanding whether or not the RNA targets quantified for wastewater-based epidemiology (WBE) efforts decay during transport between drains and the point of sample collection is critical for data interpretation. Here we show limited decay of viral RNA targets typically measured for respiratory disease WBE.

Highly sensitive wastewater surveillance of SARS-CoV-2 variants by targeted next-generation amplicon sequencing provides early warning of incursion in Victoria, Australia.

The future of the COVID pandemic and its public health and societal impact will be determined by the profile and spread of emerging variants and the timely identification and response to them. Wastewater surveillance of SARS-CoV-2 has been widely adopted in many countries across the globe and has played an important role in tracking infection levels and providing useful epidemiological information that cannot be adequately captured by clinical testing alone. However, novel variants can emerge rapidly, spread globally, and markedly alter the trajectory of the pandemic, as exemplified by the Delta and Omicron variants. Most mutations linked to the emergence of new SARS-CoV-2 variants are found within variable regions of the SARS-CoV-2 Spike protein. We have developed a duplex hemi-nested PCR method that, coupled with short amplicon sequencing, allows simultaneous typing of two of the most highly variable and informative regions of the Spike gene: the N-terminal domain and the receptor binding motif. Using this method in an operationalized public health program, we identified the first known incursion of Omicron BA.1 into Victoria, Australia and demonstrated how sensitive amplicon sequencing methods can be combined with wastewater surveillance as a relatively low-cost solution for early warning of variant incursion and spread.IMPORTANCEThis study offers a rapid, cost-effective, and sensitive approach for monitoring SARS-CoV-2 variants in wastewater. The method's flexibility permits timely modifications, enabling the integration of emerging variants and adaptations to evolving SARS-CoV-2 genetics. Of particular significance for low- and middle-income regions with limited surveillance capabilities, this technique can potentially be utilized to study a range of pathogens or viruses that possess diverse genetic sequences, similar to influenza.

Monitoring of hepatitis E virus in wastewater can identify clinically relevant variants.

Hepatitis E virus (HEV) is prevalent worldwide and can cause persistent infection with severe morbidity. Antiviral treatment approaches can lead to the emergence of viral variants encoding escape mutations that may impede viral clearance. The frequency of these variants remains unknown in the human population as well as environment due to limited comprehensive data on HEV diversity. In this study, we investigated the HEV prevalence and diversity of circulating variants in environmental samples, that is, wastewater and rivers from North-Rhine Westphalia, Germany. HEV prevalence could be determined with 73% of samples tested positive for viral RNA via qRT-PCR. Using high-throughput sequencing, we were able to assess the overall genetic diversity in these samples and identified the presence of clinically relevant variants associated with drug resistance. In summary, monitoring variants from environmental samples could provide valuable insights into estimating HEV prevalence and identifying circulating variants that can impact treatment outcome.

Evaluation of the Impact of Concentration and Extraction Methods on the Targeted Sequencing of Human Viruses from Wastewater.

Sequencing human viruses in wastewater is challenging due to their low abundance compared to the total microbial background. This study compared the impact of four virus concentration/extraction methods (Innovaprep, Nanotrap, Promega, and Solids extraction) on probe-capture enrichment for human viruses followed by sequencing. Different concentration/extraction methods yielded distinct virus profiles. Innovaprep ultrafiltration (following solids removal) had the highest sequencing sensitivity and richness, resulting in the successful assembly of several near-complete human virus genomes. However, it was less sensitive in detecting SARS-CoV-2 by digital polymerase chain reaction (dPCR) compared to Promega and Nanotrap. Across all preparation methods, astroviruses and polyomaviruses were the most highly abundant human viruses, and SARS-CoV-2 was rare. These findings suggest that sequencing success can be increased using methods that reduce nontarget nucleic acids in the extract, though the absolute concentration of total extracted nucleic acid, as indicated by Qubit, and targeted viruses, as indicated by dPCR, may not be directly related to targeted sequencing performance. Further, using broadly targeted sequencing panels may capture viral diversity but risks losing signals for specific low-abundance viruses. Overall, this study highlights the importance of aligning wet lab and bioinformatic methods with specific goals when employing probe-capture enrichment for human virus sequencing from wastewater.

Considerations and Opportunities for Probe Capture Enrichment Sequencing of Emerging Viruses from Wastewater.

Until recently, wastewater-based monitoring for pathogens of public health concern primarily used PCR-based quantification methods and targeted sequencing for specific pathogens (e.g., SARS-CoV-2). In the past three years, researchers have expanded sequencing to monitor a broad range of pathogens, applying probe capture enrichment to wastewater. The goals of those studies included (1) monitoring and expanding fundamental knowledge of disease dynamics for known pathogens and (2) evaluating the potential for early detection of emerging diseases resulting from zoonotic spillover or novel viral variants. Several studies using off-the-shelf probe panels designed for clinical and environmental surveillance reported that enrichment increased virus relative abundance but did not recover complete genomes for most nonenteric viruses. Based on our experience and recent results reported by others using these panels for wastewater, clinical, and synthetic samples, we discuss challenges and technical factors that affect the rates of false positive and false negative results. We identify trade-offs and opportunities throughout the workflow, including in wastewater sample processing, probe panel design, and bioinformatic analysis. We suggest tailored methods of virus concentration and background removal, carefully designed probe panels, and multithresholded bioinformatics analysis.

Emergence and spread of SARS-CoV-2 variants of concern in Canada: a retrospective analysis from clinical and wastewater data.

BACKGROUND: The spread of SARS-CoV-2 has been studied at unprecedented levels worldwide. In jurisdictions where molecular analysis was performed on large scales, the emergence and competition of numerous SARS-CoV-2lineages have been observed in near real-time. Lineage identification, traditionally performed from clinical samples, can also be determined by sampling wastewater from sewersheds serving populations of interest. Variants of concern (VOCs) and SARS-CoV-2 lineages associated with increased transmissibility and/or severity are of particular interest. METHOD: Here, we consider clinical and wastewater data sources to assess the emergence and spread of VOCs in Canada retrospectively. RESULTS: We show that, overall, wastewater-based VOC identification provides similar insights to the surveillance based on clinical samples. Based on clinical data, we observed synchrony in VOC introduction as well as similar emergence speeds across most Canadian provinces despite the large geographical size of the country and differences in provincial public health measures. CONCLUSION: In particular, it took approximately four months for VOC Alpha and Delta to contribute to half of the incidence. In contrast, VOC Omicron achieved the same contribution in less than one month. This study provides significant benchmarks to enhance planning for future VOCs, and to some extent for future pandemics caused by other pathogens, by quantifying the rate of SARS-CoV-2 VOCs invasion in Canada.

High-throughput microfluidic quantitative PCR system for the simultaneous detection of antibiotic resistance genes and bacterial and viral pathogens in wastewater.

Comprehensive data on bacterial and viral pathogens of diarrhea and studies applying culture-independent methods for examining antibiotic resistance in wastewater are lacking. This study aimed to simultaneously quantify antibiotic resistance genes (ARGs), class 1 integron-integrase (int1), bacterial and viral pathogens of diarrhea, 16S rRNA, and other indicators using a high-throughput quantitative PCR (HT-qPCR) system. Thirty-six grab wastewater samples from a wastewater treatment plant in Japan, collected three times a month between August 2022 and July 2023, were centrifuged, followed by nucleic acid extraction, reverse transcription, and HT-qPCR. Fourteen targets were included, and HT-qPCR was performed on the Biomark X9™ System (Standard BioTools). For all qPCR assays, R2 was ≥0.978 and the efficiencies ranged from 90.5% to 117.7%, exhibiting high performance. Of the 36 samples, 20 (56%) were positive for Norovirus genogroup II (NoV-GII), whereas Salmonella spp. and Campylobacter jejuni were detected in 24 (67%) and Campylobacter coli in 13 (36%) samples, with mean concentrations ranging from 3.2 ± 0.8 to 4.7 ± 0.3 log10 copies/L. NoV-GII detection ratios and concentrations were higher in winter and spring. None of the pathogens of diarrhea correlated with acute gastroenteritis cases, except for NoV-GII, suggesting the need for data on specific bacterial infections to validate bacterial wastewater-based epidemiology (WBE). All samples tested positive for sul1, int1, and blaCTX-M, irrespective of season. The less explored blaNDM-1 showed a wide prevalence (>83%) and consistent abundance ranging from 4.3 ± 1.0 to 4.9 ± 0.2 log10 copies/L in all seasons. sul1 was the predominant ARG, whereas absolute abundances of 16S rRNA, int1, and blaCTX-M varied seasonally. int1 was significantly correlated with blaCTX-M in autumn and spring, whereas it showed no correlation with blaNDM-1, questioning the applicability of int1 as a sole indicator of overall resistance determinants. This study exhibited that the HT-qPCR system is pivotal for WBE.

Surveillance of Wastewater to Monitor the Prevalence of Gastroenteritis Viruses in Chiba Prefecture (2014-2019).

BACKGROUND: In Japan, sentinel surveillance is used to monitor the trend of infectious gastroenteritis. Another method of pathogen surveillance, wastewater-based epidemiology, has been used recently because it can help to monitor infectious disease without relying on patient data. Here, we aimed to determine the viral trends reflected in the number of reported patients and number of gastroenteritis virus-positive samples. We focused on gastroenteritis viruses present in wastewater and investigated the usefulness of wastewater surveillance for the surveillance of infectious gastroenteritis. METHODS: Real-time polymerase chain reaction was used for viral gene detection in wastewater. The number of reported patients per pediatric sentinel site and number of viral genome copies were compared for correlation potential. The number of gastroenteritis virus-positive samples reported by National Epidemiological Surveillance of Infectious Disease (NESID) and the status of gastroenteritis viruses detected in wastewater were also evaluated. RESULTS: Genes of norovirus genotype I, norovirus genotype II, sapovirus, astrovirus, rotavirus group A, and rotavirus group C were detected in wastewater samples. Viruses were detected in wastewater during periods when no gastroenteritis virus-positive samples were reported to NESID. CONCLUSION: Norovirus genotype II and other gastroenteritis viruses were detected in wastewater even during periods when no gastroenteritis virus-positive samples were found. Therefore, surveillance using wastewater can complement sentinel surveillance and is an effective tool for the surveillance of infectious gastroenteritis.

Heavy metal contamination in Sungai Petani, Malaysia: a wastewater-based epidemiology study.

The aim of this study was to investigate the use of wastewater-based epidemiology (WBE) to estimate heavy metal exposure in Sungai Petani, Malaysia. Atomic absorption spectroscopy was used to detect copper (Cu), nickel (Ni), zinc (Zn), iron (Fe), and cadmium (Cd) in wastewater from eight sewage treatment facilities in Sungai Petani in January 2022. The heavy metal concentrations were measured in both influent and effluent, and the mean concentrations in the wastewater were found to be in the following order: Fe > Ni > Zn > Cd > Cu, with a 100% detection frequency. The results of WBE estimation showed that Fe, Ni, and Zn had the highest estimated per population exposure levels, while Cd had the lowest. Compared to a similar study conducted in Penang, Malaysia, all metals except Cu were found to have higher concentrations in Sungai Petani, even though it is a non-industrial district. These findings highlight the importance of addressing heavy metal contamination in Sungai Petani and implementing effective risk management and prevention strategies.

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

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

Wastewater surveillance for antibiotic resistance genes during the late 2020 SARS-CoV-2 peak in two different populations.

The United States Centers for Disease Control and Prevention reported a rise in resistant infections after the coronavirus disease 2019 (COVID-19) pandemic started. How and if the pandemic contributed to antibiotic resistance in the larger population is not well understood. Wastewater treatment plants are good locations for environmental surveillance because they can sample entire populations. This study aimed to validate methods used for COVID-19 wastewater surveillance for bacterial targets and to understand how rising COVID-19 cases from October 2020 to February 2021 in Portugal (PT) and King County, Washington contributed to antibiotic resistance genes in wastewater. Primary influent wastewater was collected from two treatment plants in King County and five treatment plants in PT, and hospital effluent was collected from three hospitals in PT. Genomic extracts were tested with the quantitative polymerase chain reaction for antibiotic resistance genes conferring resistance against antibiotics under threat. Random-effect models were fit for log-transformed gene abundances to assess temporal trends. All samples collected tested positive for multiple resistance genes. During the sampling period, mecA statistically significantly increased in King County and PT. No statistical evidence exists of correlation between samples collected in the same Portuguese metro area.

An evaluation of a new rapid qPCR test for the detection of 2019-novel coronavirus nucleocapsid (N1) gene in wastewater in Roanoke and Salem VA sewersheds.

The COVID-19 pandemic initiated public interest in wastewater-based epidemiology (WBE). Public and private entities responded to the need to produce timely and accurate data. LuminUltra and Hach partnered to provide a rapid, field-based quantitative polymerase chain reaction (qPCR) test for detecting severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in wastewater. This study evaluates the Hach GeneCount SARS-CoV-2 Wastewater RT-qPCR Assay Kit and LuminUltra GeneCount® Q-16 RT-PCR instrument. The Hach LuminUltra methods were compared to the Promega Wizard® Enviro Total Nucleic Acid kit and Bio-Rad CFX Opus 96 Real-time PCR Detection System. Over a 12-week period, wastewater samples were collected weekly from seven locations in the Roanoke/Salem, VA sewersheds. Concentration and extraction of the viral RNA were followed by qPCR analysis. The target gene for detection was the nucleocapsid gene (N1) of the SARS-CoV-2 virus. Costs, ease of use, time to produce results, sample preparation, and data comparisons were considered. The comparison determined that the Hach LuminUltra method and instrument were more affordable, consumed less time, and required less technical expertise. While the new method was specific, it had low sensitivity. This evaluation suggests the Hach LuminUltra method should be reserved for limited situations requiring onsite field analysis where data accuracy is not essential.

Towards the outbreak tail, what is the public opinion about wastewater surveillance in the United States?

National opinions on a wide variety of public health topics can change over time and have highly contextual nuances. This study is a follow-up to prior inquiries into the knowledge of wastewater-based epidemiology, privacy concerns surrounding sample collection, and the use of data acquired, along with privacy awareness from an online survey conducted in the metropolitan United States during the winter of 2023. Mentions of wastewater-surveillance-related terms in the media remained common. Towards the outbreak tail in 2023, public support for surveillance of toxins (91%), diseases (91%), terrorist threats (87%), illicit drugs (70%), prescription medications (69%), and gun residue (60%) remained high. There was less support for surveillance of alcohol consumption (49%), mental illness (46%), healthy eating (37%), and lifestyle behaviors (35%). In terms of geographic scale, most respondents supported citywide surveillance (85%) with markedly lower levels of support for smaller (less anonymous) geographic scales covered by specific locations. Wastewater surveillance does not receive the public pushback that other COVID-19-related health system actors have witnessed. Instead, the public supports the expansion of wastewater surveillance as a standard to complement public health tools in other areas of health protection.

Longitudinal mass loads of phthalate esters in sewage sludge and their association with public health and social measures for COVID-19 control in Beijing.

This study examines the concentrations and population-normalized mass loads (PNML) of five phthalate esters (PAEs) and four metabolites (mPAEs) in 390 sewage sludge samples collected from two municipal wastewater treatment plants in Beijing between July 2020 and June 2023, amidst the COVID-19 pandemic. Through GC/MS analysis, the compounds were simultaneously quantified, with peak concentrations in 2020. Bis(2-ethylhexyl) phthalate (DEHP) and mono(2-ethyl-5-oxohexyl) phthalate emerged as predominant PAE and mPAE congeners with concentrations of 78.7 µg/g dw and 259 µg/g dw, respectively. DEHP and monobenzyl phthalate had the highest median PNML among PAEs and mPAEs, respectively, at 128 µg/inhabitant/day and 798 µg/inhabitant/day. Linear regression models revealed a positive association between PNML of PAEs and five public health and social measures aimed at mitigating the COVID-19 pandemic. This research contributes to the expanding body of literature by emphasizing the role of wastewater-based epidemiology as a vital tool for monitoring community-level exposure to environmental contaminants.