Treatment of clinical laboratory sewage using a decentralized treatment unit and risk reduction for its reuse in irrigation using hybrid disinfection.

The disinfection efficacy of standalone chlorine, UV and their combined approach (hybrid) was investigated for the coliform removal in BioKube 1 and 2 treated effluents collected from different environmental settings of clinical and domestic wastes. Chlorine and UV disinfection were applied to BioKube treated wastewater with doses from 0 to 4 mg L-1 and 0-166 mJ cm-2 respectively. Combined disinfection strategies were designed to reduce the dose of chlorine and UV and to exploit the synergistic effect of them. The culturable coliforms were enumerated in treated wastewater sample (control), immediately after (reduction), and 24 h post disinfections (regrowth) using culture media plating and colilert-18 media. Both the BioKube systems (1 and 2) were effective in achieving the strict norms of physicochemical parameters, but not following the coliform counts of treated effluent for reuse in irrigation. A hybrid strategy of chlorine followed by UV was found to be the most effective among various standalone and combination approaches for the removal of coliforms (>4 log ER or <1000 CFU/100 mL) from both the treated effluents. However, coliform present in treated effluent of BioKube 1 were resisting (regrowth) against all kind of applied disinfectants except chlorine followed by UV dose at or more than 0.5 mg L-1 + 41 mJ cm-2. Limited reports are available on hybrid disinfection approaches with decentralized packaged sewage treatment units and this study would help to adopt as an effective tertiary treatment strategy for reuse of treated sewage for irrigation while ensuring public health safety.

Successful application of wastewater-based epidemiology in prediction and monitoring of the second wave of COVID-19 with fragmented sewerage systems-a case study of Jaipur (India).

The present study tracked the city-wide dynamics of severe acute respiratory syndrome-corona virus 2 ribonucleic acids (SARS-CoV-2 RNA) in the wastewater from nine different wastewater treatment plants (WWTPs) in Jaipur during the second wave of COVID-19 out-break in India. A total of 164 samples were collected weekly between February 19th and June 8th, 2021. SARS-CoV-2 was detected in 47.2% (52/110) influent samples and 37% (20/54) effluent samples. The increasing percentage of positive influent samples correlated with the city's increasing active clinical cases during the second wave of COVID-19 in Jaipur. Furthermore, wastewater-based epidemiology (WBE) evidence clearly showed early detection of about 20 days (9/9 samples reported positive on April 20th, 2021) before the maximum cases and maximum deaths reported in the city on May 8th, 2021. The present study further observed the presence of SARS-CoV-2 RNA in treated effluents at the time window of maximum active cases in the city even after tertiary disinfection treatments of ultraviolet (UV) and chlorine (Cl2) disinfection. The average genome concentration in the effluents and removal efficacy of six commonly used treatments, activated sludge process + chlorine disinfection (ASP + Cl2), moving bed biofilm reactor (MBBR) with ultraviolet radiations disinfection (MBBR + UV), MBBR + chlorine (Cl2), sequencing batch reactor (SBR), and SBR + Cl2, were compared with removal efficacy of SBR + Cl2 (81.2%) > MBBR + UV (68.8%) > SBR (57.1%) > ASP (50%) > MBBR + Cl2 (36.4%). The study observed the trends and prevalence of four genes (E, RdRp, N, and ORF1ab gene) based on two different kits and found that prevalence of N > ORF1ab > RdRp > E gene suggested that the effective genome concentration should be calculated based on the presence/absence of multiple genes. Hence, it is imperative to say that using a combination of different detection genes (E, N, RdRp, & ORF1ab genes) increases the sensitivity in WBE.

Sewage surveillance for the presence of SARS-CoV-2 genome as a useful wastewater based epidemiology (WBE) tracking tool in India.

The infection with SARS-CoV-2 is reported to be accompanied by the shedding of the virus in fecal samples of infected patients. Earlier reports have suggested that COVID-19 agents can be present in the sewage samples and thus it can be a good indication of the pandemic extent in a community. However, no such studies have been reported in the Indian context. Hence, it becomes absolutely necessary to detect the presence of the SARS-CoV-2 in the wastewater samples from wastewater treatment plants (WWTPs) serving different localities of Jaipur city. Samples from different WWTPs and hospital wastewater samples were collected and wastewater based epidemiology (WBE) studies were carried out using the RT-PCR to confirm the presence of different COVID-19 target genes namely S gene, E gene, ORF1ab gene, RdRp gene and N gene. The results revealed that the untreated wastewater samples showed the presence of SARS-CoV-2 viral genome, which was correlated with the increased number of COVID-19 positive patients from the concerned areas, as reported in the publically available health data. This is the first study that investigated the presence of SARS-CoV-2 viral genome in wastewater, at higher ambient temperature (45 °C), further validating WBE as potential tool in predicting and mitigating outbreaks.

A comparative study for pathogen removal using different filter media during vermifiltration.

The present study focuses on the effect of filter media (riverbed gravel, mud balls, coal and glass balls) for the removal of pathogens during vermifiltration of domestic wastewater. This novel study was conducted for the first time on different vermifilters (VFs) with different media, and pathogen removal was extensively investigated for a period of 3 months. Results indicated that vermifilter with riverbed material (VFR) showed maximum biochemical oxygen demand and chemical oxygen demand removal of 76 and 67%, respectively and vermifilter with mud balls (VFM) showed maximum log removal of total coliforms (2.8), fecal coliforms (2.7), fecal streptococci (2.2), Salmonella (2.1) and Escherichia coli (2.1). The area-based bacterial removal rate constant (k) was found in the range of 2.96-6.68 m/d, which is very high in comparison to the reported values. The population of total heterotrophic bacteria and total fungi was found to be 2-log (99%) higher in VFR and VFM, as compared to other media. The growth rate of Eisenia fetida was higher (42% increase in biomass) in glass balls vermifilter (VFG), and also the abrasions on the body wall of earthworms in VFG showed fewer injuries. Overall, the results of the study described the importance and role of each filter medium.

Pathogen removal during wastewater treatment by vermifiltration.

The study was designed to determine the effect of earthworms and the mechanism behind removal of pathogens during wastewater treatment by vermifiltration. The experimental phase continued for 10 weeks, starting after the initial stabilization phase of one week. Significant organic matter degradation and coliform removal were observed during vermifiltration of domestic wastewater. It was observed that vermifilter (VF) reduced biochemical oxygen demand and chemical oxygen demand by 84.8% and 73.9%, respectively. Significant log removal was observed for total coliforms (TC), faecal coliforms (FC), faecal streptococci (FS) and Escherichia coli with a mean log removal value (K) of 2.92, 2.20, 1.85 and 1.68, respectively. The decay rate constant (k) for indicator organisms (TC, FC and FS) was observed to be high as 8.04, 6.59 and 5.55 m day(-1), respectively. The population of total heterotrophic bacteria, total fungi and actinomycetes reduced remarkably by 3.14, 1.29 and 2.13 log units, respectively. Antibacterial activity of the isolated microorganisms from VF against gram-positive Staphylococcus aureus (ATCC 29213) and gram-negative E. coli (ATCC 25922) was observed which indicated the existence of a mechanism that may be responsible for pathogen removal during wastewater treatment. This demonstrated the production of antibacterial substance, from the microorganisms associated with earthworms, that causes inhibition of other microbes, specifying the effect of earthworms for pathogen removal. Overall, the present study contributes to the understanding of mechanism for pathogen removal during vermifiltration through antibacterial action of microflora.

Population infection estimation from wastewater surveillance for SARS-CoV-2 in Nagpur, India during the second pandemic wave.

Wastewater-based epidemiology (WBE) has emerged as an effective environmental surveillance tool for predicting severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) disease outbreaks in high-income countries (HICs) with centralized sewage infrastructure. However, few studies have applied WBE alongside epidemic disease modelling to estimate the prevalence of SARS-CoV-2 in low-resource settings. This study aimed to explore the feasibility of collecting untreated wastewater samples from rural and urban catchment areas of Nagpur district, to detect and quantify SARS-CoV-2 using real-time qPCR, to compare geographic differences in viral loads, and to integrate the wastewater data into a modified Susceptible-Exposed-Infectious-Confirmed Positives-Recovered (SEIPR) model. Of the 983 wastewater samples analyzed for SARS-CoV-2 RNA, we detected significantly higher sample positivity rates, 43.7% (95% confidence interval (CI) 40.1, 47.4) and 30.4% (95% CI 24.66, 36.66), and higher viral loads for the urban compared with rural samples, respectively. The Basic reproductive number, R0, positively correlated with population density and negatively correlated with humidity, a proxy for rainfall and dilution of waste in the sewers. The SEIPR model estimated the rate of unreported coronavirus disease 2019 (COVID-19) cases at the start of the wave as 13.97 [95% CI (10.17, 17.0)] times that of confirmed cases, representing a material difference in cases and healthcare resource burden. Wastewater surveillance might prove to be a more reliable way to prepare for surges in COVID-19 cases during future waves for authorities.

Perceiving biobased plastics as an alternative and innovative solution to combat plastic pollution for a circular economy.

Plastic waste from fossil-based sources, including single-use packaging materials, is continuously accumulating in landfills, and leaching into the environment. A 2021 UN Environment Programme (UNEP) report suggests that the plastic pollution is likely to be doubled by 2030, posing a major challenge to the environment and the overall global plastic waste management efforts. The use of biobased plastics such as polyhydroxyalkanoates (PHAs) as a biodegradable substitute for petroleum-based plastics could be a feasible option to combat this issue which may further result in much lower carbon emissions and energy usage in comparison to conventional plastics as additional advantages. Though recent years have seen the use of microbes as biosynthetic machinery for biobased plastics, using various renewable feedstocks, the scaled-up production of such materials is still challenging. The current study outlays applications of biobased plastics, potential microorganisms producing biobased plastics such as Cupriavidus necator, Bacillus sp., Rhodopseudomonas palustris, microalgae, and mixed microbial cultures, and inexpensive and renewable resources as carbon substrates including industrial wastes. This review also provides deep insights into the operational parameters, challenges and mitigation, and future opportunities for maximizing the production of biobased plastic products. Finally, this review emphasizes the concept of biorefinery as a sustainable and innovative solution for biobased plastic production for achieving a circular bioeconomy.

Correlation between SARS-CoV-2 RNA concentration in wastewater and COVID-19 cases in community: A systematic review and meta-analysis.

Wastewater-based epidemiology (WBE) has been considered as a promising approach for population-wide surveillance of coronavirus disease 2019 (COVID-19). Many studies have successfully quantified severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) RNA concentration in wastewater (CRNA). However, the correlation between the CRNA and the COVID-19 clinically confirmed cases in the corresponding wastewater catchments varies and the impacts of environmental and other factors remain unclear. A systematic review and meta-analysis were conducted to identify the correlation between CRNA and various types of clinically confirmed case numbers, including prevalence and incidence rates. The impacts of environmental factors, WBE sampling design, and epidemiological conditions on the correlation were assessed for the same datasets. The systematic review identified 133 correlation coefficients, ranging from -0.38 to 0.99. The correlation between CRNA and new cases (either daily new, weekly new, or future cases) was stronger than that of active cases and cumulative cases. These correlation coefficients were potentially affected by environmental and epidemiological conditions and WBE sampling design. Larger variations of air temperature and clinical testing coverage, and the increase of catchment size showed strong negative impacts on the correlation between CRNA and COVID-19 case numbers. Interestingly, the sampling technique had negligible impact although increasing the sampling frequency improved the correlation. These findings highlight the importance of viral shedding dynamics, in-sewer decay, WBE sampling design and clinical testing on the accurate back-estimation of COVID-19 case numbers through the WBE approach.

Moving forward with COVID-19: Future research prospects of wastewater-based epidemiology methodologies and applications.

Wastewater-based epidemiology (WBE) has been demonstrated for its great potential in tracking of coronavirus disease 2019 (COVID-19) transmission among populations despite some inherent methodological limitations. These include non-optimized sampling approaches and analytical methods; stability of viruses in sewer systems; partitioning/retention in biofilms; and the singular and inaccurate back-calculation step to predict the number of infected individuals in the community. Future research is expected to (1) standardize best practices in wastewater sampling, analysis and data reporting protocols for the sensitive and reproducible detection of viruses in wastewater; (2) understand the in-sewer viral stability and partitioning under the impacts of dynamic wastewater flow, properties, chemicals, biofilms and sediments; and (3) achieve smart wastewater surveillance with artificial intelligence and big data models. Further specific research is essential in the monitoring of other viral pathogens with pandemic potential and subcatchment applications to maximize the benefits of WBE beyond COVID-19.

RNA-Seq of untreated wastewater to assess COVID-19 and emerging and endemic viruses for public health surveillance.

Background: The COVID-19 pandemic showcased the power of genomic sequencing to tackle the emergence and spread of infectious diseases. However, metagenomic sequencing of total microbial RNAs in wastewater has the potential to assess multiple infectious diseases simultaneously and has yet to be explored. Methods: A retrospective RNA-Seq epidemiological survey of 140 untreated composite wastewater samples was performed across urban (n = 112) and rural (n = 28) areas of Nagpur, Central India. Composite wastewater samples were prepared by pooling 422 individual grab samples collected prospectively from sewer lines of urban municipality zones and open drains of rural areas from 3rd February to 3rd April 2021, during the second COVID-19 wave in India. Samples were pre-processed and total RNA was extracted prior to genomic sequencing. Findings: This is the first study that has utilised culture and/or probe-independent unbiased RNA-Seq to examine Indian wastewater samples. Our findings reveal the detection of zoonotic viruses including chikungunya, Jingmen tick and rabies viruses, which have not previously been reported in wastewater. SARS-CoV-2 was detectable in 83 locations (59%), with stark abundance variations observed between sampling sites. Hepatitis C virus was the most frequently detected infectious virus, identified in 113 locations and co-occurring 77 times with SARS-CoV-2; and both were more abundantly detected in rural areas than urban zones. Concurrent identification of segmented virus genomic fragments of influenza A virus, norovirus, and rotavirus was observed. Geographical differences were also observed for astrovirus, saffold virus, husavirus, and aichi virus that were more prevalent in urban samples, while the zoonotic viruses chikungunya and rabies, were more abundant in rural environments. Interpretation: RNA-Seq can effectively detect multiple infectious diseases simultaneously, facilitating geographical and epidemiological surveys of endemic viruses that could help direct healthcare interventions against emergent and pre-existent infectious diseases as well as cost-effectively and qualitatively characterising the health status of the population over time. Funding: UK Research and Innovation (UKRI) Global Challenges Research Fund (GCRF) grant number H54810, as supported by Research England.

Artificial neural network-based estimation of COVID-19 case numbers and effective reproduction rate using wastewater-based epidemiology.

As a cost-effective and objective population-wide surveillance tool, wastewater-based epidemiology (WBE) has been widely implemented worldwide to monitor the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) RNA concentration in wastewater. However, viral concentrations or loads in wastewater often correlate poorly with clinical case numbers. To date, there is no reliable method to back-estimate the coronavirus disease 2019 (COVID-19) case numbers from SARS-CoV-2 concentrations in wastewater. This greatly limits WBE in achieving its full potential in monitoring the unfolding pandemic. The exponentially growing SARS-CoV-2 WBE dataset, on the other hand, offers an opportunity to develop data-driven models for the estimation of COVID-19 case numbers (both incidence and prevalence) and transmission dynamics (effective reproduction rate). This study developed artificial neural network (ANN) models by innovatively expanding a conventional WBE dataset to include catchment, weather, clinical testing coverage and vaccination rate. The ANN models were trained and evaluated with a comprehensive state-wide wastewater monitoring dataset from Utah, USA during May 2020 to December 2021. In diverse sewer catchments, ANN models were found to accurately estimate the COVID-19 prevalence and incidence rates, with excellent precision for prevalence rates. Also, an ANN model was developed to estimate the effective reproduction number from both wastewater data and other pertinent factors affecting viral transmission and pandemic dynamics. The established ANN model was successfully validated for its transferability to other states or countries using the WBE dataset from Wisconsin, USA.

SARS-CoV-2 shedding sources in wastewater and implications for wastewater-based epidemiology.

Wastewater-based epidemiology (WBE) approach for COVID-19 surveillance is largely based on the assumption of SARS-CoV-2 RNA shedding into sewers by infected individuals. Recent studies found that SARS-CoV-2 RNA concentration in wastewater (CRNA) could not be accounted by the fecal shedding alone. This study aimed to determine potential major shedding sources based on literature data of CRNA, along with the COVID-19 prevalence in the catchment area through a systematic literature review. Theoretical CRNA under a certain prevalence was estimated using Monte Carlo simulations, with eight scenarios accommodating feces alone, and both feces and sputum as shedding sources. With feces alone, none of the WBE data was in the confidence interval of theoretical CRNA estimated with the mean feces shedding magnitude and probability, and 63% of CRNA in WBE reports were higher than the maximum theoretical concentration. With both sputum and feces, 91% of the WBE data were below the simulated maximum CRNA in wastewater. The inclusion of sputum as a major shedding source led to more comparable theoretical CRNA to the literature WBE data. Sputum discharging behavior of patients also resulted in great fluctuations of CRNA under a certain prevalence. Thus, sputum is a potential critical shedding source for COVID-19 WBE surveillance.

Effect of earthworms in reduction and fate of antibiotic resistant bacteria (ARB) and antibiotic resistant genes (ARGs) during clinical laboratory wastewater treatment by vermifiltration.

In the recent decades, the role of wastewater treatment plants has been entrenched for the dissemination of antibiotic resistant bacteria into the environment. The present study explores the dynamics of earthworms-microorganisms interactions involved in the high treatment efficacy of vermifiltration technology along with reduction of antibiotic resistant bacteria (ARB). This study is the first of its kind to investigate the performance efficacy of vermifilter (VF) for clinical laboratory wastewater treatment. The results of the study showed that earthworms and VF associated microbial community had a significant effect on Biochemical Oxygen Demand (BOD) and Chemical Oxygen Demand (COD) reduction (78-85%), coliforms and pathogen removal (>99.9%) and caused a significant shift in the prevalence pattern of ARB. Molecular profiling of resistance causing genes such as ESBL (blaSHV, blaTEM and blaCTX-M), MRSA (mec-A) and Colistin (mcr-1) confirmed the probable mechanisms behind the resistance pattern. The microbial community diversity in the influent, earthworm's coelomic fluid and gut and filter media layers associated with the VF assists in the formation of biofilm, which helps in the removal of pathogens from the wastewater. This biofilm formation further results in a paradigm shift in the resistance profile of ARB and ARG, specifically most effective against drugs, targeting cell wall and protein synthesis inhibition such as Ampicillin, Ticarcillin, Gentamicin and Chloramphenicol. These findings further validate vermifiltration technology as a sustainable and natural treatment technology for clinical laboratory wastewater, specifically for the removal of pathogens and antibiotic resistance.

The effect of seasonal temperature on pathogen removal efficacy of vermifilter for wastewater treatment.

The present study explored the effects of seasonal temperature on the treatment efficiency and pathogen removal efficacy from synthetic domestic wastewater, earthworm population characteristics and microbial population in the filter media of a lab-scale vermifilter (VF). The experimental phase lasted for one year and daily mean room temperature showed a difference of 2-16 °C between winter (Dec-Feb), spring (Mar-May), summer (Jun-Aug) and autumn (Sep-Nov) periods. The results showed that variation in ambient temperature had a significant effect on chemical oxygen demand (COD) and biochemical oxygen demand (BOD) reduction, indicator organisms and pathogen removal, earthworm population, bacterial and actinomycetes number, but had no effect on total suspended solids (TSS) removal and fungi number. The study showed that higher BOD and COD removal was accomplished during the spring and autumn period when the mean temperature was 25-27 °C. This temperature range is optimum for the earthworm species Eisenia fetida for its activity, growth and reproduction and any variation in temperature from the optimum range led to decrease in treatment efficiency and earthworm population. However, during summer, when the maximum temperature reached 38-40 °C, the indicator bacteria removal was maximum by 99.9%, Salmonella reduction by 96.9% and Escherichia coli by 99.3%. The pathogen removal efficacy of VF increases with the increase in temperature, as shown by linear regression analysis, which implied that temperature had a significant contribution to the pathogen removal efficiency of VF. Pearson coefficient of correlation (r) derived an important relationship between the seasonal temperature and treatment efficiency, pathogen removal efficacy and microbial numbers during vermifiltration.

Antibacterial and enzymatic activity of microbial community during wastewater treatment by pilot scale vermifiltration system.

The present study investigated microbial community diversity and antibacterial and enzymatic properties of microorganisms in a pilot-scale vermifiltration system during domestic wastewater treatment. The study included isolation and identification of diverse microbial community by culture-dependent method from a vermifilter (VF) with earthworms and a conventional geofilter (GF) without earthworms. The results of the four months study revealed that presence of earthworms in VF could efficiently remove biochemical oxygen demand (BOD), chemical oxygen demand (COD), total and fecal coliforms, fecal streptococci and other pathogens. Furthermore, the burrowing activity of earthworms promoted the aeration conditions in VF which led to the predominance of the aerobic microorganisms, accounting for complex microbial community diversity. Antibacterial activity of the isolated microorganisms revealed the mechanism behind the removal of pathogens, which is reported for the first time. Specifically, cellulase, amylase and protease activity is responsible for biodegradation and stabilization of organic matter.