Wastewater Surveillance for Poliovirus in Selected Jurisdictions, United States, 2022-2023.

Wastewater testing can inform public health action as a component of polio outbreak response. During 2022-2023, a total of 7 US jurisdictions (5 states and 2 cities) participated in prospective or retrospective testing of wastewater for poliovirus after a paralytic polio case was identified in New York state. Two distinct vaccine-derived poliovirus type 2 viruses were detected in wastewater from New York state and New York City during 2022, representing 2 separate importation events. Of those viruses, 1 resulted in persistent community transmission in multiple New York counties and 1 paralytic case. No poliovirus was detected in the other participating jurisdictions (Connecticut, New Jersey, Michigan, and Illinois and Chicago, IL). The value of routine wastewater surveillance for poliovirus apart from an outbreak is unclear. However, these results highlight the ongoing risk for poliovirus importations into the United States and the need to identify undervaccinated communities and increase vaccination coverage to prevent paralytic polio.

Wastewater Surveillance for Norovirus, California, USA.

Norovirus is a leading cause of acute gastroenteritis and imposes a substantial disease burden. In California, USA, norovirus surveillance is limited. We evaluated correlations between wastewater norovirus concentrations and available public health surveillance data. Wastewater surveillance for norovirus genotype GII in California provided timely, localized, and actionable data for public health authorities.

The effects of RT-qPCR standards on reproducibility and comparability in monitoring SARS-CoV-2 levels in wastewater.

Reverse transcription-quantitative PCR (RT-qPCR) is widely used for monitoring viruses, including severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), in wastewater. Various materials, including plasmid DNA, synthetic nucleic acids, PCR amplicons, genomic DNA, and cDNA, are currently used for SARS-CoV-2 quantification by generating standard curves. We assessed three common standards on quantifying SARS-CoV-2 RNA across nine wastewater treatment plants in Finland, as part of the national wastewater surveillance effort. We pairwise compared RT-qPCR results from 148 wastewater samples, using both IDT (#10006625, IDT, USA) and CODEX standards (#SC2-RNAC-1100, CODEX DNA), and 179 samples using both IDT and EURM019 standards (#EURM-019, European Commission, Joint Research Centre) in our assessment. Amongst the tested standards, the CODEX standard consistently yielded more stable results than either the IDT or EURM019 standards. We found that SARS-CoV-2 levels were higher with the IDT standard (4.36 Log10 GC/100 mL) compared to the CODEX standard (4.05 Log10 GC/100 mL). Similarly, quantification using the IDT standard was higher (5.27 Log10 GC/100 mL) than values obtained with the EURM019 (4.81 Log10 GC/100 mL). SARS-CoV-2 RNA quantified with IDT and CODEX standards exhibited stronger concordance (Spearman's correlation rho median of 0.79) compared to those quantified with IDT and EURM019 standards (rho median of 0.59). This study highlights the significant impact of standard material selection on SARS-CoV-2 RNA quantification, emphasizing the need for harmonization in standard material.

Real-Time Monitoring of SARS-CoV-2 Variants in Oklahoma Wastewater through Allele-Specific RT-qPCR.

During the COVID-19 pandemic, wastewater surveillance was used to monitor community transmission of SARS-CoV-2. As new genetic variants emerged, the need for timely identification of these variants in wastewater became an important focus. In response to increased reports of Omicron transmission across the United States, the Oklahoma Wastewater Surveillance team utilized allele-specific RT-qPCR assays to detect and differentiate variants, such as Omicron, from other variants found in wastewater in Oklahoma. The PCR assays showed presence of the Omicron variant in Oklahoma on average two weeks before official reports, which was confirmed through genomic sequencing of selected wastewater samples. Through continued surveillance from November 2021 to January 2022, we also demonstrated the transition from prevalence of the Delta variant to prevalence of the Omicron variant in local communities. We further assessed how this transition correlated with certain demographic factors characterizing each community. Our results highlight RT-qPCR assays as a rapid, simple, and cost-effective method for monitoring the community spread of SARS-CoV-2 genetic variants in wastewater. Additionally, they demonstrate that specific demographic factors such as ethnic composition and household income can correlate with the timing of SARS-CoV-2 variant introduction and spread.

Evaluating survey techniques in wastewater-based epidemiology for accurate COVID-19 incidence estimation.

Wastewater-based epidemiology (WBE) requires high-quality survey methods to determine the incidence of infections in wastewater catchment areas. In this study, the wastewater survey methods necessary for comprehending the incidence of infection by WBE are clarified. This clarification is based on the correlation with the number of confirmed coronavirus disease 2019 (COVID-19) cases, considering factors such as handling non-detect data, calculation method for representative values, analytical sensitivity, analytical reproducibility, sampling frequency, and survey duration. Data collected from 15 samples per week for two and a half years using a highly accurate analysis method were regarded as gold standard data, and the correlation between severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) RNA concentrations in wastewater and confirmed COVID-19 cases was analyzed by Monte Carlo simulation under the hypothetical situation where the quality of the wastewater survey method was reduced. Regarding data handling, it was appropriate to replace non-detect data with estimates based on distribution, and to use geometric means to calculate representative values. For the analysis of SARS-CoV-2 RNA in samples, using a highly sensitive and reproducible method (non-detect rates of <40 %; ≤0.4 standard deviation) and surveying at least three samples, preferably five samples, per week were considered desirable. Furthermore, conducting the survey over a period of time that included at least 50 weeks was necessary. A WBE that meets these survey criteria is sufficient for the determination of the COVID-19 infection incidence in the catchment. Furthermore, WBE can offer additional insights into infection rates in the catchment, such as the estimated 48 % decrease in confirmed COVID-19 cases visiting a clinic following a COVID-19 legal reclassification in Japan.

Wastewater and environmental sampling holds potential for antimicrobial resistance surveillance in food-producing animals - a pilot study in South African abattoirs.

Antimicrobial resistance (AMR) poses a significant global One Health challenge that causes increased mortality and a high financial burden. Animal production contributes to AMR, as more than half of antimicrobials are used in food-producing animals globally. There is a growing body of literature on AMR in food-producing animals in African countries, but the surveillance practices across countries vary considerably. This pilot study aims to explore the potential of wastewater and environmental surveillance (WES) of AMR and its extension to the veterinary field. Floor drainage swab (n = 18, 3/abattoir) and wastewater (n = 16, 2-3/abattoir) samples were collected from six South African abattoirs that handle various animal species, including cattle, sheep, pig, and poultry. The samples were tested for Extended-Spectrum Beta-Lactamase (ESBL) and Carbapenemase-producing Enterobacterales, Methicillin-Resistant Staphylococcus aureus (MRSA), Vancomycin-resistant Enterococci (VRE), and Candida auris by using selective culturing and MALDI-TOF MS identification. The phenotype of all presumptive ESBL-producing Escherichia coli (n = 60) and Klebsiella pneumoniae (n = 24) isolates was confirmed with a disk diffusion test, and a subset (15 and 6 isolates, respectively), were further characterized by whole-genome sequencing. In total, 314 isolates (0-12 isolates/sample) withstood MALDI-TOF MS, from which 37 species were identified, E. coli and K. pneumoniae among the most abundant. Most E. coli (n = 48/60; 80%) and all K. pneumoniae isolates were recovered from the floor drainage samples, while 21 presumptive carbapenem-resistant Acinetobacter spp. isolates were isolated equally from floor drainage and wastewater samples. MRSA, VRE, or C. auris were not found. All characterized E. coli and K. pneumoniae isolates represented ESBL-phenotype. Genomic analyses revealed multiple sequence types (ST) of E. coli (n = 10) and K. pneumoniae (n = 5), including STs associated with food-producing animals globally, such as E. coli ST48 and ST10 and K. pneumoniae ST101. Common beta-lactamases linked to food-producing animals, such as bla CTX-M-55 and bla CTX-M-15, were detected. The presence of food-production-animal-associated ESBL-gene-carrying E. coli and K. pneumoniae in an abattoir environment and wastewater indicates the potential of WES in the surveillance of AMR in food-producing animals. Furthermore, the results of this pilot study encourage studying the topic further with refined methodologies.

Genomic mapping of wastewater bacteriophage may predict potential bacterial pathogens infecting the community.

Most existing wastewater surveillance studies that focus on viruses have identified a large fraction of bacteriophages. Identifying bacteria by considering bacteriophage-host interactions is a novel method for detecting bacterial pathogens circulating in a community, using wastewater surveillance. This study aims to identify human-related bacterial pathogens in municipal wastewater collected in metro Detroit, using high-throughput sequencing and bioinformatics. Untreated municipal wastewater samples were collected on August 11, 2020, and bacteriophages were concentrated using the VIRus ADsorption-ELution (VIRADEL) method. Bacteriophage-related contigs in samples ranged from 15.53 % to 18.91 %, with 2477 classified and 8853 unclassified contigs. Most identified bacteriophages were from Caudoviricetes and Malgrandaviricetes classes belonging to 19 families. Hosts of bacteriophages were predicted with the PhaBOX (CHERRY) tool. The results indicated that out of the 2477 classified phages, 2373 were associated with known bacterial hosts. Also, out of 8853 unclassified bacteriophages, 8421 were associated with known bacterial hosts, and the remaining 432 were with unknown bacterial hosts. Among all bacteriophage-associated hosts, 399 were identified as pathogenic bacteria at the species level. Approximately, 85 % of the identified pathogenic bacteria are reported to be associated with human diseases. Genome quality assessments showed that 15 bacteriophages had nearly complete genomes, which were further analyzed to understand bacteriophage-bacteria interactions in wastewater. Identified hosts of these complete-genome phages included human pathogens such as Salmonella enterica, Bacillus cereus, Achromobacter xylosoxidans, and Escherichia coli. The S. enterica bacteriophage (k141_1005294) genomic map was annotated, and responsible open reading frames (ORFs) were characterized to illustrate bacteriophage behavior during infection of pathogenic bacteria in untreated wastewater. To the best of our knowledge, this is the first attempt to characterize human bacterial pathogens in wastewater through bacteriophage-pathogen interactions. Novel bioinformatic approaches enhance pathogen detection and improve the understanding of community wastewater microbiomes.

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.

Assessment of Public Health Agency and Utility Training Needs for CDC National Wastewater Surveillance System Jurisdictions in the United States.

Since the start of the COVID-19 pandemic, wastewater surveillance hasemerged as a critical tool for tracking the spread of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) virus and other pathogens in communities throughout the United States. In 2020, the Centers for Disease Control and Prevention (CDC) launched the National Wastewater Surveillance System (NWSS), which partners with state, local, tribal, and territorial health departments to develop and implement wastewater collection and analysis systems and to share data. In 2022, the CDC established the first two NWSS Centers of Excellence to lead its implementation and coordination efforts-one in Colorado (Colorado CoE) and one in Houston (Houston CoE). As the NWSS expands, it is becoming more important to support the training needs of jurisdictions at different stages of developing their wastewater surveillance infrastructure. To evaluate these needs, the Colorado CoE and Houston CoE conducted a needs assessment study of NWSS-funded public health agencies and public utilities departments located in the United States using surveys developed by the Colorado CoE. The results of the surveys showed that although some training needs were universal, it will be most beneficial to develop training modules tailored to the needs of entities that operate wastewater surveillance programs of various sizes, workforce experience levels, and at different stages in the infrastructure development process.

Development of new RT-PCR assays for the specific detection of BA.2.86 SARS-CoV-2 and its descendent sublineages.

The SARS-CoV-2 BA.2.86 variant, also known as Pirola, has acquired over 30 amino acid changes in the Spike protein, evolving into >150 sublineages within ten months of its emergence. Among these, the JN.1, has been rapidly increasing globally becoming the most prevalent variant. To facilitate the identification of BA.2.86 sublineages, we designed the PiroMet-1 and PiroMet-2 assays in silico and validated them using BA.2.86 viral RNA and clinical samples to ascertain analytical specificity and sensitivity. Both assays resulted very specific with limit of detection of about 1-2 RNA copies/µL. The assays were then applied in a digital RT-PCR format to wastewater samples, combined with the OmMet assay (which identifies Omicron sublineages except BA.2.86 and its descendants) and the JRC-UCE.2 assay (which can universally recognize all SARS-CoV-2 variants). When used together with the OmMet and JRC-CoV-UCE.2 assays, the PiroMet assays accurately quantified BA.2.86 sublineages in wastewater samples. Our findings support the integration of these assays into routine SARS-CoV-2 wastewater surveillance as a timely and cost-effective complement to sequencing for monitoring the prevalence and spread of BA.2.86 sublineages within communities.

Reporting population size in wastewater-based epidemiology: A scoping review.

Knowledge of the number of people present in a catchment is fundamental for the assessment of spatio-temporal trends in wastewater-based epidemiology (WBE). Accurately estimating the number of people connected to wastewater catchments is challenging however, because populations are dynamic. Methods used to estimate population size can significantly influence the calculation and interpretation of population-normalised wastewater data (PNWD). This paper systematically reviews the reporting of population data in 339 WBE studies. Studies were evaluated based on their reporting of population size, the source of population data, the population calculation methods, and the uncertainties in population estimates. Most papers reported population size (96 %) and the source of population data (60 %). Fewer studies reported the uncertainties in their population data (50 %) and the methods used to calculate these estimates (28 %). This is relevant because different methods have unique strengths and limitations which can affect the accuracy of PNWD. Only 64 studies (19 %) reported all four components of population data. The reporting of population data has remained consistent in the past decade. Based on the findings, we recommend generalised reporting criteria for population data in WBE. As WBE is further mainstreamed and applied, the clear and comprehensive reporting of population data will only become increasingly important.

Enabling quantitative comparison of wastewater surveillance data across methods through data standardization without method standardization.

Wastewater surveillance for COVID-19 and other pathogens has expanded globally. Rapid development and availability of various assays has facilitated swift adoption of wastewater surveillance in localities with diverse requirements. However, it presents challenges in comparing data due to methodological variations. Using surrogates for recovery control to address quantification biases has limitations as the recovery of surrogates and target pathogens often diverges significantly. Using non-spiked field-obtained wastewater samples as reference samples in an inter-lab study, this article proposes a straightforward, inexpensive, and most representative way of measuring relative quantification biases that occurs in analyzing field wastewater samples. Five labs participated in the study, testing five types of assays, resulting in a total of seven methods of lab-assay combinations. Each method quantified the concentration of SARS-CoV-2 and pepper mild mottle virus (PMMoV) RNAs in two types of reference samples. The results showed significant variations in quantification among methods, but the relative quantification biases were consistent across reference samples. This suggests that relative quantification biases measured with the reference samples are contingent on methods rather than wastewater samples, and that the once-determined method-specific factors can be used to correct for quantification biases in routine wastewater surveillance results. Subsequent data standardization was performed on year-long observational data from seven cities, serving as a preliminary validation of the proposed approach. This process demonstrated the potential for quantitative data comparison through the bias correction factors obtained in this inter-lab study.

Wastewater Surveillance Pilot at US Military Installations: Cost Model Analysis.

Background: The COVID-19 pandemic highlighted the need for pathogen surveillance systems to augment both early warning and outbreak monitoring/control efforts. Community wastewater samples provide a rapid and accurate source of environmental surveillance data to complement direct patient sampling. Due to its global presence and critical missions, the US military is a leader in global pandemic preparedness efforts. Clinical testing for COVID-19 on US Air Force (USAF) bases (AFBs) was effective but costly with respect to direct monetary costs and indirect costs due to lost time. To remain operating at peak capacity, such bases sought a more passive surveillance option and piloted wastewater surveillance (WWS) at 17 AFBs to demonstrate feasibility, safety, utility, and cost-effectiveness from May 2021 to January 2022. Objective: We model the costs of a wastewater program for pathogens of public health concern within the specific context of US military installations using assumptions based on the results of the USAF and Joint Program Executive Office for Chemical, Biological, Radiological and Nuclear Defense pilot program. The objective was to determine the cost of deploying WWS to all AFBs relative to clinical swab testing surveillance regimes. Methods: A WWS cost projection model was built based on subject matter expert input and actual costs incurred during the WWS pilot program at USAF AFBs. Several SARS-CoV-2 circulation scenarios were considered, and the costs of both WWS and clinical swab testing were projected. Analysis was conducted to determine the break-even point and how a reduction in swab testing could unlock funds to enable WWS to occur in parallel. Results: Our model confirmed that WWS is complementary and highly cost-effective when compared to existing alternative forms of biosurveillance. We found that the cost of WWS was between US $10.5-$18.5 million less expensive annually in direct costs as compared to clinical swab testing surveillance. When the indirect cost of lost work was incorporated, including lost work associated with required clinical swab testing, we estimated that over two-thirds of clinical swab testing could be maintained with no additional costs upon implementation of WWS. Conclusions: Our results support the adoption of WWS across US military installations as part of a more comprehensive and early warning system that will enable adaptive monitoring during disease outbreaks in a more cost-effective manner than swab testing alone.

Infectious Disease Physicians' Knowledge and Practices Regarding Wastewater Surveillance, United States, 2024.

A survey of US infectious disease physicians indicated that few regularly reviewed wastewater surveillance (WWS) data but many reported examples of how WWS has affected or could affect their clinical practice. WWS data can be useful for physicians, but increased communication between public health professionals and physicians regarding WWS could improve its utility.

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).

Mapping the heterogeneous removal landscape of wastewater virome in effluents of different advanced wastewater treatment systems of swine farm.

In advanced wastewater treatment plants on pig farms, meticulous design aims to eliminate intrinsic pollutants such as organic matter, heavy metals, and biological contaminants. In our field survey across Southern China, a notable disparity in wastewater treatment procedures among various farming facilities lies in the utilization of terminal chemical oxidation post-sedimentation tank. However, recent focus in wastewater surveillance has predominantly centered on antibiotic resistance genes, leaving the efficacy of virus removal in different effluent systems largely unexplored. To profile virus composition at the effluent, assess the virus elimination efficiency of chemical oxidation at the effluent end, and the potential environmental driver of virus abundance, we deployed a meta-transcriptomics approach to first determine the total virome in effluent specimens of terminal clean water tank system (CWT) and terminal chemical oxidation system (TCO) in Southern China pig farms, respectively. From these data, 172 viruses were identified, with a median reads per million (RPM) of 27,789 in CWT and 19,982 in TCO. Through the integration of analyses encompassing the co-occurrence patterns within viral communities, the ecology of viral diversity, and a comparative assessment of average variation degrees, we have empirically demonstrated that the procedure of TCO may perturb viral communities and diminish their abundance, particularly impacting RNA viral communities. However, despite the diminished abundance, pathogenic viruses such as PEDV and PRRSV persisted in the effluent following chemical deoxidation at a moderate RPM value, indicating a substantial in situ presence at effluent. Our environmental driver modeling, employing GLM and mantel tests, substantiated the intricate nature of virus community variation within the effluent, influenced heterogeneously by diverse factors. Notably, pond temperature emerged as the foremost determinant, while fishing farming exhibited a positive correlation with virus diversity (p < 0.05). This revelation of the cryptic persistence of virus communities in wastewater effluent expands our understanding of the varied responses of different virus categories to oxidation. Such insights transcend mere virus characterization, offering valuable implications for enhancing biosafety measures in farming practices and informing wastewater-based epidemiological surveillance.

Wastewater Surveillance of SARS-CoV-2: A Comparison of Two Concentration Methods.

Wastewater surveillance is crucial for the epidemiological monitoring of SARS-CoV-2. Various concentration techniques, such as skimmed milk flocculation (SMF) and polyethylene glycol (PEG) precipitation, are employed to isolate the virus effectively. This study aims to compare these two methods and determine the one with the superior recovery rates. From February to December 2021, 24-h wastewater samples were collected from the Ioannina Wastewater Treatment Plant's inlet and processed using both techniques. Subsequent viral genome isolation and a real-time RT-qPCR detection of SARS-CoV-2 were performed. The quantitative analysis demonstrated a higher detection sensitivity with a PEG-based concentration than SMF. Moreover, when the samples were positive by both methods, PEG consistently yielded higher viral loads. These findings underscore the need for further research into concentration methodologies and the development of precise protocols to enhance epidemiological surveillance through wastewater analysis.

Combining Short- and Long-Read Sequencing Technologies to Identify SARS-CoV-2 Variants in Wastewater.

During the COVID-19 pandemic, the monitoring of SARS-CoV-2 RNA in wastewater was used to track the evolution and emergence of variant lineages and gauge infection levels in the community, informing appropriate public health responses without relying solely on clinical testing. As more sublineages were discovered, it increased the difficulty in identifying distinct variants in a mixed population sample, particularly those without a known lineage. Here, we compare the sequencing technology from Illumina and from Oxford Nanopore Technologies, in order to determine their efficacy at detecting variants of differing abundance, using 248 wastewater samples from various Quebec and Ontario cities. Our study used two analytical approaches to identify the main variants in the samples: the presence of signature and marker mutations and the co-occurrence of signature mutations within the same amplicon. We observed that each sequencing method detected certain variants at different frequencies as each method preferentially detects mutations of distinct variants. Illumina sequencing detected more mutations with a predominant lineage that is in low abundance across the population or unknown for that time period, while Nanopore sequencing had a higher detection rate of mutations that are predominantly found in the high abundance B.1.1.7 (Alpha) lineage as well as a higher sequencing rate of co-occurring mutations in the same amplicon. We present a workflow that integrates short-read and long-read sequencing to improve the detection of SARS-CoV-2 variant lineages in mixed population samples, such as wastewater.

Implementing an Alert System for Communicating Actionable Wastewater Surveillance Results to School Communities, Houston, Texas, 2023-2024.

In 2020, the Houston Health Department (HHD) in Texas launched a citywide wastewater surveillance program, including a pilot program that monitored manholes at schools in Houston's largest school district (prekindergarten-12th grade). By 2022, the pilot program monitored wastewater for SARS-CoV-2, influenza A and B, and respiratory syncytial virus. To ensure effective communication of wastewater surveillance results to school communities, HHD designed and implemented a text- and email-based alert system using existing City of Houston resources. This alert program informs recipients about the presence of a virus at their schools and actions to protect themselves and others against that virus. To promote alert program sign-ups, a dedicated bilingual community involvement coordinator conducted in-person outreach geared toward school nurses and student caregivers. From September 2023 through February 2024, a combined 5178 alerts for 43 schools were sent following virus detections. As a supplemental initiative, HHD offered vaccination events to pilot program schools with consistent virus detection. As wastewater surveillance becomes more common across the United States, this alert program presents a framework for other public health agencies to scale and adapt according to their resources.

Tracking Chlamydia and Syphilis in the Detroit Metro Area by Molecular Analysis of Environmental Samples.

This paper describes one of the first studies applying wastewater surveillance to monitor Chlamydia and Syphilis and back-estimate infections in the community, based on bacterial shedding and wastewater surveillance data. Molecular biology laboratory methods were optimized, and a workflow was designed to implement wastewater surveillance tracking Chlamydia and Syphilis in the Detroit metro area (DMA), one of the most populous metropolitan areas in the U.S. Untreated composite wastewater samples were collected weekly from the three main interceptors that service DMA, which collect wastewater and discharge it to the Great Lakes Water Authority Water Resource Recovery Facility. Additionally, untreated wastewater was also collected from street manholes in three neighborhood sewersheds in Wayne, Macomb, and Oakland counties. Centrifugation, DNA extraction, and ddPCR methods were optimized and performed, targeting Chlamydia trachomatis and Treponema pallidum, the causative agents of Chlamydia and Syphilis, respectively. The limit of blank and limit of detection methods were determined experimentally for both targets. Both targets were detected and monitored in wastewater between December 25th, 2023, and April 22nd, 2024. The magnitudes of C. trachomatis and T. pallidum concentrations observed in neighborhood sewersheds were higher as compared to the concentrations observed in the interceptors. Infections of Chlamydia and Syphilis were back-estimated through an optimized formula based on shedding dynamics and wastewater surveillance data, which indicated potentially underreported conditions relative to publicly available clinical data.