A Bayesian framework for modeling COVID-19 case numbers through longitudinal monitoring of SARS-CoV-2 RNA in wastewater.

Wastewater-based surveillance has become an important tool for research groups and public health agencies investigating and monitoring the COVID-19 pandemic and other public health emergencies including other pathogens and drug abuse. While there is an emerging body of evidence exploring the possibility of predicting COVID-19 infections from wastewater signals, there remain significant challenges for statistical modeling. Longitudinal observations of viral copies in municipal wastewater can be influenced by noisy datasets and missing values with irregular and sparse samplings. We propose an integrative Bayesian framework to predict daily positive cases from weekly wastewater observations with missing values via functional data analysis techniques. In a unified procedure, the proposed analysis models severe acute respiratory syndrome coronavirus-2 RNA wastewater signals as a realization of a smooth process with error and combines the smooth process with COVID-19 cases to evaluate the prediction of positive cases. We demonstrate that the proposed framework can achieve these objectives with high predictive accuracies through simulated and observed real data.

Longitudinal SARS-CoV-2 RNA wastewater monitoring across a range of scales correlates with total and regional COVID-19 burden in a well-defined urban population.

Wastewater-based epidemiology (WBE) is an emerging surveillance tool that has been used to monitor the ongoing COVID-19 pandemic by tracking SARS-CoV-2 RNA shed into wastewater. WBE was performed to monitor the occurrence and spread of SARS-CoV-2 from three wastewater treatment plants (WWTP) and six neighborhoods in the city of Calgary, Canada (population 1.44 million). A total of 222 WWTP and 192 neighborhood samples were collected from June 2020 to May 2021, encompassing the end of the first-wave (June 2020), the second-wave (November end to December 2020) and the third-wave of the COVID-19 pandemic (mid-April to May 2021). Flow-weighted 24-hour composite samples were processed to extract RNA that was then analyzed for two SARS-CoV-2-specific regions of the nucleocapsid gene, N1 and N2, using reverse transcription-quantitative polymerase chain reaction (RT-qPCR). Using this approach SARS-CoV-2 RNA was detected in 98.06% (406/414) of wastewater samples. SARS-CoV-2 RNA abundance was compared to clinically diagnosed COVID-19 cases organized by the three-digit postal code of affected individuals' primary residences, enabling correlation analysis at neighborhood, WWTP and city-wide scales. Strong correlations were observed between N1 & N2 gene signals in wastewater and new daily cases for WWTPs and neighborhoods. Similarly, when flow rates at Calgary's three WWTPs were used to normalize observed concentrations of SARS-CoV-2 RNA and combine them into a city-wide signal, this was strongly correlated with regionally diagnosed COVID-19 cases and clinical test percent positivity rate. Linked census data demonstrated disproportionate SARS-CoV-2 in wastewater from areas of the city with lower socioeconomic status and more racialized communities. WBE across a range of urban scales was demonstrated to be an effective mechanism of COVID-19 surveillance.

A multicenter study investigating SARS-CoV-2 in tertiary-care hospital wastewater. viral burden correlates with increasing hospitalized cases as well as hospital-associated transmissions and outbreaks.

SARS-CoV-2 has been detected in wastewater and its abundance correlated with community COVID-19 cases, hospitalizations and deaths. We sought to use wastewater-based detection of SARS-CoV-2 to assess the epidemiology of SARS-CoV-2 in hospitals. Between August and December 2020, twice-weekly wastewater samples from three tertiary-care hospitals (totaling > 2100 dedicated inpatient beds) were collected. Hospital-1 and Hospital-2 could be captured with a single sampling point whereas Hospital-3 required three separate monitoring sites. Wastewater samples were concentrated and cleaned using the 4S-silica column method and assessed for SARS-CoV-2 gene-targets (N1, N2 and E) and controls using RT-qPCR. Wastewater SARS-CoV-2 as measured by quantification cycle (Cq), genome copies and genomes normalized to the fecal biomarker PMMoV were compared to the total daily number of patients hospitalized with active COVID-19, confirmed cases of hospital-acquired infection, and the occurrence of unit-specific outbreaks. Of 165 wastewater samples collected, 159 (96%) were assayable. The N1-gene from SARS-CoV-2 was detected in 64.1% of samples, N2 in 49.7% and E in 10%. N1 and N2 in wastewater increased over time both in terms of the amount of detectable virus and the proportion of samples that were positive, consistent with increasing hospitalizations at those sites with single monitoring points (Pearson's r = 0.679, P < 0.0001, Pearson's r = 0.799, P < 0.0001, respectively). Despite increasing hospitalizations through the study period, nosocomial-acquired cases of COVID-19 (Pearson's r = 0.389, P < 0.001) and unit-specific outbreaks were discernable with significant increases in detectable SARS-CoV-2 N1-RNA (median 112 copies/ml) versus outbreak-free periods (0 copies/ml; P < 0.0001). Wastewater-based monitoring of SARS-CoV-2 represents a promising tool for SARS-CoV-2 passive surveillance and case identification, containment, and mitigation in acute- care medical facilities.

Degradation of pharmaceutical mixtures in aqueous solutions using UV/peracetic acid process: Kinetics, degradation pathways and comparison with UV/H2O2.

This paper presents an evaluation of UV/PAA process for degradation of four pharmaceuticals venlafaxine (VEN), sulfamethoxazole (SFX), fluoxetine (FLU) and carbamazepine (CBZ) with comparison to UV/H2O2 process. The effectiveness of combining PAA and H2O2 at various proportions while irradiating with UVC were also evaluated. UVC/PAA (λ = 254 nm) was effective in degrading all four pharmaceuticals and followed pseudo first-order kinetics. Increasing PAA dosage or UVC intensity resulted in a linear increase in pseudo-first order rate coefficient. Both PAA in dark conditions and UVA/PAA (λ = 360 nm) were marginally effective to degrade SFX and ineffective to degrade VEN, CBZ and FLU; indicating the need for UVC irradiation for activation of PAA. For similar oxidant dosages of 50 mg/L UVC/H2O2 was found to be faster than UV/PAA for VEN, CBZ and FLU by 55%, 75% and 33%, respectively. Under similar conditions, SFX was degraded 24% faster by UV/PAA. Increase in the proportion of H2O2 to PAA in UVC/PAA/H2O2 improved kinetics of degradation compared to PAA alone. Tests on TOC were conducted to determine the amount of acetic acid that is released to water when treatment by UVC/PAA is conducted. Results demonstrated that 70% of PAA by mass was ultimately converted to acetic acid and remained in the treated solutions. Hydroxyl radical attack is hypothesized to be the main mechanism of degradation by UV/PAA as degradation intermediates identified for all the target pharmaceuticals coincided with by-products identified during UV/H2O2 process.

Effect of UV dose on degradation of venlafaxine using UV/H2O2: perspective of augmenting UV units in wastewater treatment.

Many water and wastewater treatment plants (WWTPs) are fitted with a UV system that provides post treatment disinfection before the water is released to receiving water. This paper presents a study on expected removal for the pharmaceutical venlafaxine (VEN) in a typical UV unit at a municipal WWTP with analysis of removal rates of an advanced oxidation process using UV irradiation with injection of H2O2. The study is supported by bench scale degradation experiments on VEN. Results demonstrated that UV can completely degrade VEN, but the addition of H2O2 increased pseudo first order rate constant by up to 2.5 times. Extrapolations of the lab data indicated that removal rates of VEN at the UV disinfection unit of a typical municipal WWTP are approximately 0.4% at standard operating conditions. With the addition of 10 mg/L of H2O2, degradation of VEN can be increased by ten times over existing UV treatment. By studying the impact of adjusting parameters such as UV intensity, UV dosage, and H2O2 dosage, a framework is set to allow researchers and engineers to move forward with developing UV/H2O2 systems that meet their future design needs for pharmaceutical removal.