Bayesian modeling of virus removal efficiency in wastewater treatment processes

Detecting SARS-CoV-2 RNA prone clusters in a municipal wastewater network using fuzzy-Bayesian optimization model to facilitate wastewater-based epidemiology

The current pandemic disease coronavirus (COVID-19) has not only become a worldwide health emergency, but also devoured the global economy. Despite appreciable research, identification of targeted populations for testing and tracking the spread of COVID-19 at a larger scale is an intimidating challenge. There is a need to quickly identify the infected individual or community to check the spread. The diagnostic testing done at large-scale for individuals has limitations as it cannot provide information at a swift pace in large populations, which is pivotal to contain the spread at the early stage of its breakouts. Recently, scientists are exploring the presence of SARS-CoV-2 RNA in the faeces discharged in municipal wastewater. Wastewater sampling could be a potential tool to expedite the early identification of infected communities by detecting the biomarkers from the virus. However, it needs a targeted approach to choose optimized locations for wastewater sampling. The present study proposes a novel fuzzy based Bayesian model to identify targeted populations and optimized locations with a maximum probability of detecting SARS-CoV-2 RNA in wastewater networks. Consequently, real time monitoring of SARS-CoV-2 RNA in wastewater using autosamplers or biosensors could be deployed efficiently. Fourteen criteria such as population density, patients with comorbidity, quarantine and hospital facilities, etc. are analysed using the data of 14 lac individuals infected by COVID-19 in the USA. The uniqueness of the proposed model is its ability to deal with the uncertainty associated with the data and decision maker's opinions using fuzzy logic, which is fused with Bayesian approach. The evidence-based virus detection in wastewater not only facilitates focused testing, but also provides potential communities for vaccine distribution. Consequently, governments can reduce lockdown periods, thereby relieving human stress and boosting economic growth.

Methods for Handling Left-Censored Data in Quantitative Microbial Risk Assessment

Data below detection limits, left-censored data, are common in environmental microbiology, and decisions in handling censored data may have implications for quantitative microbial risk assessment (QMRA). In this paper, we utilize simulated data sets informed by real-world enterovirus water data to evaluate methods for handling left-censored data. Data sets were simulated with four censoring degrees (low [10%], medium [35%], high [65%], and severe [90%]) and one real-life censoring example (97%) and were informed by enterovirus data assuming a lognormal distribution with a limit of detection (LOD) of 2.3 genome copies/liter. For each data set, five methods for handling left-censored data were applied: (i) substitution with LOD/[Formula: see text], (ii) lognormal maximum likelihood estimation (MLE) to estimate mean and standard deviation, (iii) Kaplan-Meier estimation (KM), (iv) imputation method using MLE to estimate distribution parameters (MI method 1), and (v) imputation from a uniform distribution (MI method 2). Each data set mean was used to estimate enterovirus dose and infection risk. Root mean square error (RMSE) and bias were used to compare estimated and known doses and infection risks. MI method 1 resulted in the lowest dose and infection risk RMSE and bias ranges for most censoring degrees, predicting infection risks at most 1.17 × 10^-2 from known values under 97% censoring. MI method 2 was the next overall best method. For medium to severe censoring, MI method 1 may result in the least error. If unsure of the distribution, MI method 2 may be a preferred method to avoid distribution misspecification.IMPORTANCE This study evaluates methods for handling data with low (10%) to severe (90%) left-censoring within an environmental microbiology context and demonstrates that some of these methods may be appropriate when using data containing concentrations below a limit of detection to estimate infection risks. Additionally, this study uses a skewed data set, which is an issue typically faced by environmental microbiologists.

A review on recent progress in the detection methods and prevalence of human enteric viruses in water

Waterborne human enteric viruses, such as noroviruses and adenoviruses, are excreted in the feces of infected individuals and transmitted via the fecal-oral route including contaminated food and water. Since viruses are normally present at low concentrations in aquatic environments, they should be concentrated into smaller volumes prior to downstream molecular biological applications, such as quantitative polymerase chain reaction (qPCR). This review describes recent progress made in the development of concentration and detection methods of human enteric viruses in water, and discusses their applications for providing a better understanding of the prevalence of the viruses in various types of water worldwide. Maximum concentrations of human enteric viruses in water that have been reported in previous studies are summarized to assess viral abundances in aquatic environments. Some descriptions are also available on recent applications of sequencing analyses used to determine the genetic diversity of viral genomes in water samples, including those of novel viruses. Furthermore, the importance and significance of utilizing appropriate process controls during viral analyses are discussed, and three types of process controls are considered: whole process controls, molecular process controls, and (reverse transcription (RT)-)qPCR controls. Although no standards have been established for acceptable values of virus recovery and/or extraction-(RT-)qPCR efficiency, use of at least one of these appropriate control types is highly recommended for more accurate interpretation of observed data.

Sapovirus in Wastewater Treatment Plants in Tunisia: Prevalence, Removal, and Genetic Characterization

Sapovirus (SaV), from the Caliciviridae family, is a genus of enteric viruses that cause acute gastroenteritis. SaV is shed at high concentrations with feces into wastewater, which is usually discharged into aquatic environments or reused for irrigation without efficient treatments. This study analyzed the incidence of human SaV in four wastewater treatment plants from Tunisia during a period of 13 months (December 2009 to December 2010). Detection and quantification were carried out using reverse transcription-quantitative PCR (RT-qPCR) methods, obtaining a prevalence of 39.9% (87/218). Sixty-one positive samples were detected in untreated water and 26 positive samples in processed water. The Dekhila plant presented the highest contamination levels, with a 63.0% prevalence. A dominance of genotype I.2 was observed on 15 of the 24 positive samples that were genetically characterized. By a Bayesian estimation algorithm, the SaV density in wastewater was estimated using left-censored data sets. The mean value of log SaV concentration in untreated wastewater ranged between 2.7 and 4.5 logs. A virus removal efficiency of 0.2 log was calculated for the Dekhila plant as the log ratio posterior distributions between untreated and treated wastewater. Multiple quantitative values obtained in this study must be available in quantitative microbial risk assessment in Tunisia as parameter values reflecting local conditions.IMPORTANCE Human sapovirus (SaV) is becoming more prevalent worldwide and organisms in this genus are recognized as emerging pathogens associated with human gastroenteritis. The present study describes novel findings on the prevalence, seasonality, and genotype distribution of SaV in Tunisia and Northern Africa. In addition, a statistical approximation using Bayesian estimation of the posterior predictive distribution ("left-censored" data) was employed to solve methodological problems related with the limit of quantification of the quantitative PCR (qPCR). This approach would be helpful for the future development of quantitative microbial risk assessment procedures for wastewater.

Target virus log10 reduction values determined for two reclaimed wastewater irrigation scenarios in Japan based on tolerable annual disease burden

Multiple-barriers are widely employed for managing microbial risks in water reuse, in which different types of wastewater treatment units (biological treatment, disinfection, etc.) and health protection measures (use of personal protective gear, vegetable washing, etc.) are combined to achieve a performance target value of log₁₀ reduction (LR) of viruses. The LR virus target value needs to be calculated based on the data obtained from monitoring the viruses of concern and the water reuse scheme in the context of the countries/regions where water reuse is implemented. In this study, we calculated the virus LR target values under two exposure scenarios for reclaimed wastewater irrigation in Japan, using the concentrations of indigenous viruses in untreated wastewater and a defined tolerable annual disease burden (10^-4 or 10^-6 disability-adjusted life years per person per year (DALY_pppy)). Three genogroups of norovirus (norovirus genogroup I (NoV GI), geogroup II (NoV GII), and genogroup IV (NoV GIV)) in untreated wastewater were quantified as model viruses using reverse transcription-microfluidic quantitative PCR, and only NoV GII was present in quantifiable concentration. The probabilistic distribution of NoV GII concentration in untreated wastewater was then estimated from its concentration dataset, and used to calculate the LR target values of NoV GII for wastewater treatment. When an accidental ingestion of reclaimed wastewater by Japanese farmers was assumed, the NoV GII LR target values corresponding to the tolerable annual disease burden of 10^-6 DALY_pppy were 3.2, 4.4, and 5.7 at 95, 99, and 99.9%tile, respectively. These percentile values, defined as "reliability," represent the cumulative probability of NoV GII concentration distribution in untreated wastewater below the corresponding tolerable annual disease burden after wastewater reclamation. An approximate 1-log₁₀ difference of LR target values was observed between 10^-4 and 10^-6 DALY_pppy. The LR target values were influenced mostly by the change in the logarithmic standard deviation (SD) values of NoV GII concentration in untreated wastewater and the reliability values, which highlights the importance of accurately determining the probabilistic distribution of reference virus concentrations in source water for water reuse.

Virus removal by ultrafiltration: Understanding long-term performance change by application of Bayesian analysis

Ultrafiltration is an effective barrier to waterborne pathogens including viruses. Challenge testing is commonly used to test the inherent reliability of such systems. Performance validation seeks to demonstrate the adequate reliability of the treatment system. Appropriate and rigorous data analysis is an essential aspect of validation testing. In this study we used Bayesian analysis to assess the performance of a full-scale ultrafiltration system which was validated and revalidated after five years of operation. A hierarchical Bayesian model was used to analyse a number of similar ultrafiltration membrane skids working in parallel during the two validation periods. This approach enhanced our ability to obtain accurate estimations of performance variability, especially when the sample size of some system skids was limited. This methodology enabled the quantitative estimation of uncertainty in the performance parameters and generation of predictive distributions incorporating those uncertainties. The results indicated that there was a decrease in the mean skid performance after five years of operation of approximately 1 log reduction value (LRV). Interestingly, variability in the LRV also reduced, with standard deviations from the revalidation data being decreased by a mean 0.37 LRV compared with the original validation data. The model was also useful in comparing the operating performance of the various parallel skids within the same year. Evidence of differences was obtained in 2015 for one of the membrane skids. A hierarchical Bayesian analysis of validation data provides robust estimations of performance and the incorporation of probabilistic analysis which is increasingly important for comprehensive quantitative risk assessment purposes.

Removal of human pathogenic viruses in a down-flow hanging sponge (DHS) reactor treating municipal wastewater and health risks associated with utilization of the effluent for agricultural irrigation

A down-flow hanging sponge (DHS) reactor has been developed as a cost-effective wastewater treatment system that is adaptable to local conditions in low-income countries. A pilot-scale DHS reactor previously demonstrated stable reduction efficiencies for chemical oxygen demand (COD) and ammonium nitrogen over a year at ambient temperature, but the pathogen reduction efficiency of the DHS reactor has yet to be investigated. In the present study, the reduction efficiency of a pilot-scale DHS reactor fed with municipal wastewater was investigated for 10 types of human pathogenic viruses (norovirus GI, GII and GIV, aichivirus, astrovirus, enterovirus, hepatitis A and E viruses, rotavirus, and sapovirus). DHS influent and effluent were collected weekly or biweekly for 337 days, and concentrations of viral genomes were determined by microfluidic quantitative PCR. Aichivirus, norovirus GI and GII, enterovirus, and sapovirus were frequently detected in DHS influent, and the log₁₀ reduction (LR) of these viruses ranged from 1.5 to 3.7. The LR values for aichivirus and norovirus GII were also calculated using a Bayesian estimation model, and the average LR (±standard deviation) values for aichivirus and norovirus GII were estimated to be 1.4 (±1.5) and 1.8 (±2.5), respectively. Quantitative microbial risk assessment was conducted to calculate a threshold reduction level for norovirus GII that would be required for the use of DHS effluent for agricultural irrigation, and it was found that LRs of 2.6 and 3.7 for norovirus GII in the DHS effluent were required in order to not exceed the tolerable burden of disease at 10^-4 and 10^-6 disability-adjusted life years loss per person per year, respectively, for 95% of the exposed population during wastewater reuse for irrigation.

Evaluation of virus reduction efficiency in wastewater treatment unit processes as a credit value in the multiple-barrier system for wastewater reclamation and reuse

The virus reduction efficiency of each unit process is commonly determined based on the ratio of virus concentration in influent to that in effluent of a unit, but the virus concentration in wastewater has often fallen below the analytical quantification limit, which does not allow us to calculate the concentration ratio at each sampling event. In this study, left-censored datasets of norovirus (genogroup I and II), and adenovirus were used to calculate the virus reduction efficiency in unit processes of secondary biological treatment and chlorine disinfection. Virus concentration in influent, effluent from the secondary treatment, and chlorine-disinfected effluent of four municipal wastewater treatment plants were analyzed by a quantitative polymerase chain reaction (PCR) approach, and the probabilistic distributions of log reduction (LR) were estimated by a Bayesian estimation algorithm. The mean values of LR in the secondary treatment units ranged from 0.9 and 2.2, whereas those in the free chlorine disinfection units were from -0.1 and 0.5. The LR value in the secondary treatment was virus type and unit process dependent, which raised the importance for accumulating the data of virus LR values applicable to the multiple-barrier system, which is a global concept of microbial risk management in wastewater reclamation and reuse.

Risk management of viral infectious diseases in wastewater reclamation and reuse: Review

Inappropriate usage of reclaimed wastewater has caused outbreaks of viral infectious diseases worldwide. International and domestic guidelines for wastewater reuse stipulate that virus infection risks are to be regulated by the multiple-barrier system, in which a wastewater treatment process composed of sequential treatment units is designed based on the pre-determined virus removal efficiency of each unit. The objectives of this review were to calculate representative values of virus removal efficiency in wastewater treatment units based on published datasets, and to identify research topics that should be further addressed for improving implementation of the multiple-barrier system. The removal efficiencies of human noroviruses, rotaviruses and enteroviruses in membrane bioreactor (MBR) and conventional activated sludge (CAS) processes were obtained by a systematic review protocol and a meta-analysis approach. The log10 reduction (LR) of norovirus GII and enterovirus in MBR were 3.35 (95% confidence interval: 2.39, 4.30) and 2.71 (1.52, 3.89), respectively. The LR values of rotavirus, norovirus GI and GII in CAS processes were 0.87 (0.20, 1.53), 1.48 (0.96, 2.00) and 1.35 (0.52, 2.18), respectively. The systematic review process eliminated a substantial number of articles about virus removal in wastewater treatment because of the lack of information required for the meta-analysis. It is recommended that future publications should explicitly describe their treatment of left-censored datasets. Indicators, surrogates and methodologies appropriate for validating virus removal performance during daily operation of wastewater reclamation systems also need to be identified.