The use of antibiotics is a significant problem that impacts the environment and public health. Various antibiotics, such as azithromycin, were applied at greater frequency to treat severely infected patients during the COVID-19 pandemic. Wastewater is an important source of antibiotics to natural water systems. A temporal study of antibiotics in wastewater influents and effluents is needed to assess if the pandemic changed removal rates during treatment and environmental loadings. This work investigates occurrence, concentration, and removal efficiency of antibiotics by WWTPs in Minnesota. From August 2020 to July 2022, monthly influent and effluent samples were collected form four WWTPs with treatment capacities of 22‒172 million gallon/day, serving a total population of ~2,500,000 people. Samples were extracted and concentrated by solid-phase extraction, and 26 selected antibiotics (sulfonamides, macrolides, tetracyclines, fluoroquinolones, beta-lactams, and uncategorized compounds) were analyzed by LC-MS/MS. Profiles of antibiotics in each class were dominated by the compounds used by humans instead of those solely for animals, i.e., sulfamethoxazole for sulfonamides, azithromycin for macrolides, doxycycline for tetracyclines, ciprofloxacin for fluoroquinolones, and trimethoprim for the other compounds. Wastewater treatment effectively removed certain antibiotics (on average 50.3%‒73.3% for sulfamethoxazole, and 49.6%-95.7% for doxycycline), while negative removals were observed in other cases (possibly due to adsorption of antibiotics to particles/flocs in the influent samples leading to lower recoveries). Concentrations of the prevalent compounds were 0 to ~4000 ng/L in the effluent samples. Based on the antibiotic concentrations, their loadings to the environment and relationships with prescription data will be presented.

Many wastewater-based epidemiology (WBE) applications assume that longitudinal measurements are representative of all infected individuals in the sewershed equally. However, wastewater samples contain material from numerous individuals at different stages of infection, with likely dramatically different fecal shedding patterns and dynamics. The degree to which individual dynamics of fecal shedding influences the relationship between wastewater concentrations and the number of infected individuals is poorly understood. In this study, we use fecal shedding data recently collected by our team to create a stochastic, longitudinal model of individual fecal shedding of SARS-CoV-2, PMMoV, and crAssphage genomic sequences over the course of 30 days after infection. We then pair dynamic fecal shedding with epidemiological and materials balance mathematical models to mechanistically link individual fecal shedding with community level wastewater concentrations over the course of a simulated outbreak. Using this integrated model, we find that individuals shedding at high concentrations can have a significant influence on resulting wastewater concentrations. Intuitively, this phenomenon is more pronounced when anomalous shedders represent a larger proportion of the population. Additionally, we observe that both crAssphage and PMMoV serve as reasonably reliable correlates to fecal strength only at large population scales. Together, these results highlight biases associated with quantitative WBE data collected at small scales, which are due to dynamics of individual fecal shedding.

In response to the COVID-19 pandemic, wastewater surveillance programs around the world expanded rapidly, resulting in the application of diverse methodologies for sample collection, sample processing, and data analysis. While many programs have assessed quantified SARS-CoV-2 RNA in wastewater through comparison to reported COVID-19 cases, no consensus has been reached regarding a standard approach for this comparison. We reviewed data analysis strategies used for such comparisons in 103 articles (published within the first 30 months of the COVID-19 pandemic) focused on wastewater surveillance in sewersheds served by centralized wastewater treatment facilities. Notable differences were found across studies in (1) normalizing wastewater data (e.g., accounting for population or wastewater flow rates) and (2) summarizing clinical testing data (e.g., averaging or totaling new cases over specific time ranges). In comparing wastewater data and clinical testing data, reported strategies ranged in complexity from correlation analysis (44% of articles) or simple linear regression (23%) to modeling that accounts for fecal shedding of SARS-CoV-2 (25%) or applications of machine learning (6%). We compared a subset of the most commonly-used strategies using a SARS-CoV-2 wastewater monitoring data set from New York City to inform data analysis decisions in future surveillance efforts. Finally, we identified common ambiguities and variations in terminology, likely stemming from contributions made across various disciplines including virology, environmental engineering, and public health. We suggest standardized terminology and minimum reporting requirements to improve the utility of methodological summaries in wastewater surveillance studies and facilitate comparison of findings from different sewersheds.

Two photobioreactors with different airflow rates (PSBR-L and PSBR-H) were designed to evaluate the airflow rate effect on their performance and pathogen elimination, and reduction. Real wastewater collected from Penn State Water Resource Recovery Facility was used in this study. Liquid-solid partition, and biomass particle associations of E. coli, Enterococcus Sp., F-specific coliphage (MS2), and Somatic coliphage (phi-X174) were evaluated using a cascade filtration approach. Fecal indicators bacteria (FIB) were quantified by membrane filtration technique, and the double agar plaque assay was used for coliphages. Four filters (180, 20, 0.45, and 0.03μm) were employed for appraisal of particles association. PSBRs eliminate over 75% of COD and 95% of inorganic nitrogen. The average log removal of E. coli and Enterococcus Sp., considering the liquid portion, were 3.2 and 2.9 for PSBR-L and 2.8 and 2.7 for PSBR-H, respectively. While the average log removal for MS2 and phi-X174 were 2.9 and 3.4 for PSBR-L and 2.5 and 3.2 for PSBR-H. Pathogens indicators overall reduction ranged from 2.0 to 2.4 without exhibiting any significant difference between PSBR-L and PSBR-H. All pathogen indicators were recognized on all particle fractions; however, FIB had their maximum association on the 0.45μm filter (46.1% - 63.3%) while the coliphage had the highest association on the 3μm filter (44.7% - 51.2%). Outcomes reveal the appropriateness of PSBR systems to reduce indicators from real wastewater and the systems might be valuable for wastewater reuse in the agriculture sector.

Opioid-related deaths as a result of illicitly manufactured fentanyl and fentanyl-like compounds, termed novel synthetic opioids (NSOs), have been on the rise in the United States (US). The current understanding of overdoses and general use patterns throughout communities may be a vast underestimation as these compounds are not included in routine coroner toxicology screenings or general criminal justice-related assessments. Wastewater-based epidemiology (WBE) may be a suitable approach to assess population-level use and to fill these gaps. A systematic literature review identified 46 NSOs of concern associated with overdoses reported by medical examiners and/or seizures by the US Drug Enforcement Agency. Seven NSOs had higher fentanyl milligram equivalents (FMEs) >1 while many were similar to or lower than morphine (0.01-0.02 FME). Estimated doses based on FMEs were combined with historic wastewater flow and population data (n = 1249) from ASU’s Human Health Observatory to assess drug user visibility in communities ranging in population size from 1,000 to 5 million. Sufentanil, 3-methylfentanyl, and α-methylfentanyl required the highest percentages of users for detectability (10 to 16%), while the remainder required ≤1% of the population. Detection of carfentanil was determined infeasible in any sized community due to extremely high potency (10,000X more potent than morphine) resulting in a low dose. Limited information related to human excreted metabolites, percent excretion in urine, and in-sewer degradation in this systematic evaluation posed challenges to the work and warrant future study to support the application of WBE in public health efforts to address the opioid epidemic.