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In this work, we present an eight-month longitudinal study of wastewater-based epidemiology (WBE) in Ahmedabad, India, where wastewater surveillance was introduced in September 2020 after the successful containment of the first wave of COVID-19 to predict the resurge of the infection during the second wave of the pandemic. The study aims to elucidate the weekly resolution of the SARS-CoV-2 RNA data for eight months in wastewater samples to predict the COVID-19 situation and identify hotspots in Ahmedabad. A total of 287 samples were analyzed for SARS-CoV-2 RNA using RT-PCR, and Spearman's rank correlation was applied to depict the early warning potential of WBE. During September 2020 to April 2021, the increasing number of positive wastewater influent samples correlated with the growing number of confirmed clinical cases. It also showed clear evidence of early detection of the second wave of COVID-19 in Ahmedabad (March 2021). 258 out of a total 287 samples were detected positive with at least two out of three SARS-CoV-2 genes (N, ORF- 1 ab, and S). Monthly variation represented a significant decline in all three gene copies in October compared to September 2020, followed by an abrupt increase in November 2020. A similar increment in the gene copies was observed in March and April 2021, which would be an indicator of the second wave of COVID-19. A lead time of 1–2 weeks was observed in the change of gene concentrations compared with clinically confirmed cases. Measured wastewater ORF- 1 ab gene copies ranged from 6.1 x 102 (October 2020) to 1.4 x 104 (November 2020) copies/mL, and wastewater gene levels typically lead to confirmed cases by one to two weeks. The study highlights the value of WBE as a monitoring tool to predict waves within a pandemic, identify local disease hotspots within a city, and guide rapid management interventions. [Display omitted] • Eight-months of SARS-CoV-2 gene variations explicitly predicts 2nd COVID-19 wave. • 258 out of 287 wastewater samples were detected positive for SARS-CoV-2 genes. • WBE offers a lead time of 1–2 weeks for the preparedness of pandemic situation. • Model suggests that ORF 1 ab gene is the most effective marker gene in WBE study. • Gathered WBE data worldwide may now be subjected to several AI/ML based simulations. [ABSTRACT FROM AUTHOR]

Wastewater-based genomic surveillance can identify a huge majority of variants shed by the infected individuals within a population, which goes beyond genomic surveillance based on clinical samples (i.e., symptomatic patients only). We analyzed four samples to detect key mutations in the SARS-CoV-2 genome and track circulating variants in Ahmedabad during the first wave (Sep/Nov 2020) and before the second wave (in Feb 2021) of COVID-19 in India. The analysis identified a total of 34 mutations in the spike protein across samples categorized into 23 types. The spike protein mutations were linked to the VOC-21APR-02; B.1.617.2 lineage (Delta variant) with 57% frequency in wastewater samples of Feb 2021. The key spike protein mutations were T19R, L452R, T478K, D614G, & P681R and deletions at 22029 (6 bp), 28248 (6 bp), & 28271 (1 bp). Interestingly, these mutations were not seen in the samples from Sep/Nov 2020 but did appear before the massive second wave of COVID-19 cases, which in India started in early April 2021. In fact, genetic traces of the Delta variant were found in samples of early Feb 2021, more than a month before the first clinically confirmed case of this in March 2021 in Ahmedabad, Gujarat. The present work describes the circulating of SARS-CoV-2 variants in Ahmedabad and confirms the consequential value of wastewater surveillance for the early detection of variants of concerns (VOCs). Such monitoring must be included as a major component of future health protection systems. [Display omitted] • First detection of delta variant (VOC-21APR-02; B.1.617.2) in the wastewater of India. • Treated water showed more prevalence of Delta variant than the non-treated wastewater. • WBE is capable to detect and deal with SARS-CoV-2 variants and their cryptic transmission. • WW genomic surveillance can aid the decision-making system for public health policies. • Delta variant found a month earlier in the wastewater than the first confirmed clinical case. Delta variant found a month earlier in the wastewater of Ahmedabad than the first confirmed clinical patient report. [ABSTRACT FROM AUTHOR]

[Display omitted] • Early-warning capability of wastewater-based epidemiology (WBE) is reviewed globally. • Clarity is required whether the WBE generated lead-time is pragmatic or latent. • WBE data showed a noticeable difference in temperate & tropical regions. • Sanitation and climatic variabilities limit the global comparability of WBE lead-time. • WBE is more applicable to WASH countries, as evident in normalized WBE data. The global data on the temporal tracking of the COVID-19 through wastewater surveillance needs to be comparatively evaluated to generate a proper and precise understanding of the robustness, advantages, and sensitivity of the wastewater-based epidemiological (WBE) approach. We reviewed the current state of knowledge based on several scientific articles pertaining to temporal variations in COVID-19 cases captured via viral RNA predictions in wastewater. This paper primarily focuses on analyzing the WBE-based temporal variation reported globally to check if the reported early warning lead-time generated through environmental surveillance is pragmatic or latent. We have compiled the geographical variations reported as lead time in various WBE reports to strike a precise correlation between COVID-19 cases and genome copies detected through wastewater surveillance, with respect to the sampling dates, separately for WASH and non-WASH countries. We highlighted sampling methods, climatic and weather conditions that significantly affected the concentration of viral SARS-CoV-2 RNA detected in wastewater, and thus the lead time reported from the various climatic zones with diverse WASH situations were different. Our major findings are: i) WBE reports around the world are not comparable, especially in terms of gene copies detected, lag-time gained between monitored RNA peak and outbreak/peak of reported case, as well as per capita RNA concentrations; ii) Varying sanitation facility and climatic conditions that impact virus degradation rate are two major interfering features limiting the comparability of WBE results, and iii) WBE is better applicable to WASH countries having well-connected sewerage system. [ABSTRACT FROM AUTHOR]

[Display omitted] • Wastewater treatments may not completely remove the SARS-CoV-2 RNA. • Activated sludge process exhibited better RNA removal efficacy than root-zone treatment. • ORF 1ab and S genes appeared more sensitive to treatment than N genes. • Temporal variability is observed in the removal efficacy of wastewater treatment plants. In the initial pandemic phase, effluents from wastewater treatment facilities were reported mostly free from Severe Acute Respiratory Coronavirus 2 (SARS-CoV-2) RNA, and thus conventional wastewater treatments were generally considered effective. However, there is a lack of first-hand data on i) comparative efficacy of various treatment processes for SARS-CoV-2 RNA removal; and ii) temporal variations in the removal efficacy of a given treatment process in the backdrop of active COVID-19 cases. This work provides a comparative account of the removal efficacy of conventional activated sludge (CAS) and root zone treatments (RZT) based on weekly wastewater surveillance data, consisting of forty-four samples, during a two-month period. The average genome concentration was higher in the inlets of CAS-based wastewater treatment plant (WWTP) in the Sargasan ward (1.25 × 103 copies/ L), than that of RZT-based WWTP (7.07 × 102 copies/ L) in an academic institution campus of Gandhinagar, Gujarat, India. ORF 1ab and S genes appeared to be more sensitive to treatment i.e., significantly reduced (p < 0.05) than N genes (p > 0.05). CAS treatment exhibited better RNA removal efficacy (p = 0.014) than RZT (p = 0.032). Multivariate analyses suggested that the effective genome concentration should be calculated based on the presence/absence of multiple genes. The present study stresses that treated effluents are not always free from SARS-CoV-2 RNA, and the removal efficacy of a given WWTP is prone to exhibit temporal variability owing to variations in active COVID-19 cases in the vicinity and genetic material accumulation over the time. Disinfection seems less effective than the adsorption and coagulation processes for SARS-CoV-2 removal. Results stress the need for further research on mechanistic insight on SARS-CoV-2 removal through various treatment processes taking solid–liquid partitioning into account. [ABSTRACT FROM AUTHOR]

The ongoing COVID-19 pandemic increases the consumption of antimicrobial substances (ABS) due to the unavailability of approved vaccine(s). To assess the effect of imprudent consumption of ABS during the COVID-19 pandemic, we compare the 2020 prevalence of antidrug resistance (ADR) of Escherichia coli (E. coli) with a similar survey carried out in 2018 in Ahmedabad, India using SARS-CoV-2 gene detection as a marker of ABS usage. We found a significant ADR increase in 2020 compared to 2018 in ambient water bodies, harbouring a higher incidence of ADR E. c oli towards non-fluoroquinolone drugs. Effective SARS-CoV-2 genome copies were found to be associated with the ADR prevalence. The prevalence of ADR depends on the efficiency of WWTPs (Wastewater Treatment Plants) and the catchment area in its vicinity. In the year 2018 study, prevalence of ADR was discretely distributed, and the maximum ADR prevalence recorded was ~ 60%; against the current homogenous ADR increase, and up to 85% of maximum ADR among the incubated E.coli isolated from the river (Sabarmati) and lake (Chandola and Kankaria) samples. Furthermore, wastewater treatment plants showed less increase in comparison to the ambient waters, which eventually imply that although SARS-CoV-2 genes and faecal pollution may be diluted in the ambient waters, as indicated by low C t -value and E.coli count, the danger of related aftermath like ADR increase cannot be nullified. Also, Non-fluoroquinolone drugs exhibited overall more resistance than quinolone drugs. Overall, this is probably the first-ever study that traces the COVID-19 pandemic imprints on the prevalence of antidrug resistance (ADR) through wastewater surveillance and hints at monitoring escalation of other environmental health parameters. This study will make the public and policyholders concerned about the optimum use of antibiotics during any kind of treatment. [Display omitted] • COVID-19 pandemic imprints on antibiotic resistance bacteria (ARB) was evaluated. • Ambient waters ex. lakes and rivers exhibited an increase in ARB concentrations. • E. coli gained more resistance for non-fluoroquinolone drugs than fluoroquinolone. • Effective SARS-CoV-2 genome count coincided with the ARB prevalence in the vicinity. • The antibiotic resistance depends on the catchment area and efficiency of WWTPs. [ABSTRACT FROM AUTHOR]

In this review, we present the environmental perspectives of the viruses and antiviral drugs related to SARS-CoV-2. The present review paper discusses occurrence, fate, transport, susceptibility, and inactivation mechanisms of viruses in the environment as well as environmental occurrence and fate of antiviral drugs, and prospects (prevalence and occurrence) of antiviral drug resistance (both antiviral drug resistant viruses and antiviral resistance in the human). During winter, the number of viral disease cases and environmental occurrence of antiviral drug surge due to various biotic and abiotic factors such as transmission pathways, human behaviour, susceptibility, and immunity as well as cold climatic conditions. Adsorption and persistence critically determine the fate and transport of viruses in the environment. Inactivation and disinfection of virus include UV, alcohol, and other chemical-base methods but the susceptibility of virus against these methods varies. Wastewater treatment plants (WWTPs) are major reserviors of antiviral drugs and their metabolites and transformation products. Ecotoxicity of antiviral drug residues against aquatic organisms have been reported, however more threatening is the development of antiviral resistance, both in humans and in wild animal reservoirs. In particular, emergence of antiviral drug-resistant viruses via exposure of wild animals to high loads of antiviral residues during the current pandemic needs further evaluation. ga1 • We analysed environmental perspectives of antiviral drugs and SARS-CoV-2. • Susceptibility and inactivation causes seasonality in the prevalence of SARS-CoV-2. • Surface-charge interactions govern environmental fate and transport of SARS-CoV-2. • Unprecedented use of antiviral drugs is hazardous to the environment. • Emergence of antiviral drug-resistant viruses needs further investigations. [ABSTRACT FROM AUTHOR]

For the first time, we present, i) an account of decay in the genetic material loading of SARS-CoV-2 during Upflow Anaerobic Sludge Blanket (UASB) treatment of wastewater, and ii) comparative evaluation of polyethylene glycol (PEG), and ultrafiltration as virus concentration methods from wastewater for the quantification of SARS-CoV-2 genes. The objectives were achieved through tracking of SARS-CoV-2 genetic loadings i.e. ORF1ab, N and S protein genes on 8th and 27th May 2020 along the wastewater treatment plant (106000 m3 million liters per day) equipped with UASB system in Ahmedabad, India. PEG method performed better in removing materials inhibiting RT-qPCR for SARS-CoV-2 gene detection from the samples, as evident from constant and lower C T values of control (MS2). Using the PEG method, we found a reduction >1.3 log 10 reduction in SARS-CoV-2 RNA abundance during UASB treatment, and the RNA was not detected at all in the final effluent. The study implies that i) conventional wastewater treatment systems is effective in SARS-CoV-2 RNA removal, and ii) UASB system significantly reduces SARS-CoV-2 genetic loadings. Finally, PEG method is recommended for better sensitivity and inhibition removal during SARS-CoV-2 RNA quantification in wastewater. Unlabelled Image • First report of the decay of SARS-CoV-2 gene during UASB treatment • Polyethylene glycol method had superior inhibition removal than filtration method. • The viral genetic loading reduction during UASB treatment was more than 1.3 log 10. • Higher RNA loading in the influent on 27th May 2020 translated into higher reduction. [ABSTRACT FROM AUTHOR]

In order to benefit the public, community workers and scientific community, we hereby present a chronicle of SARS-CoV-2 that leads to the unseen precedent of social distancing and lockdown owing to coronavirus disease (COVID-19). Information on this life-threatening pandemic of COVID-19 is sparse and discrete; and the urgency is such that the dissemination of information is increasing with numerous daily publications on the topic. Therefore, we developed a comprehensive review on various aspects of SARS-CoV-2 and COVID-19. We scientifically compiled published research, news, and reports from various sources to comprehend and summarize the information and findings on Coronaviruses. The review explicitly covers the aspects like genome and pedigree of SARS-CoV-2; epidemiology, prognosis, pathogenesis, symptoms and diagnosis of COVID-19 in order to catalog the right information on transmission route, and influence of environmental factors on virus transmissions, for the robust understanding of right strategical steps for proper COVID-19 management. We have explicitly highlighted several useful information and facts like: i) No established relationship between progression of SARS-CoV-2 with temperature, humidity and/or both, ii) The underlying mechanism of SARS-CoV-2 is not fully understood, iii) Respiratory droplet size determines drop and airborne-based transmission, iv) Prognosis of COVID-19 can be done by its effects on various body organs, v) Infection can be stopped by restricting the binding of S protein and AE2, vi) Hydroxychloroquine is believed to be better than chloroquine for COVID-19, vii) Ivermectin with Vero-hSLAM cells is able to reduce infection by ~5000 time within 2 days, and viii) Nafamostat mesylate can inhibit SARS-CoV-2 S protein-initiated membrane fusion. We have also suggested future research perspectives, challenges and scope. Unlabelled Image • Phylogeny of the SARS-CoV-2 is remarkably similar to SARS of pangolin and/or bat origin. • Transmission depends on respiratory droplet size, environmental condition and immunity. • COVID-19 progression is highly debated for temperature, humidity, and lifestyle dependence. • Infection can be restricted through restricting binding of S protein and AE2. • Increasing neutrophil and lymphocyte ratio (NLR) may give early sign of COVID-19. [ABSTRACT FROM AUTHOR]

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 (C RNA). However, the correlation between the C RNA 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 C RNA 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 C RNA 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 C RNA 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. [Display omitted] • A systematic review of WBE performance in estimating COVID prevalence or incidence. • Differentiating the outbreak stage can improve the correlation between COVID-19 cases and C RNA. • Large temperature fluctuation and catchment size correlated with reduced WBE performance. • Sampling frequency and epidemiological factors are essential to improve WBE estimation. • WBE studies should report a minimum set of data for cross-study comparability. [ABSTRACT FROM AUTHOR]

• ANN models to estimation COVID case numbers developed using >10,000 WBE data. • The model inputs include data of WBE, weather, clinical testing and vaccine coverage. • The ANN model accurately estimates COVID incidence and prevalence rate. • ANN model can also estimate the COVID effective reproduction rate effectively. • The lead-time of early warning of incidence was determined to be 2-4 days. 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. [Display omitted] [ABSTRACT FROM AUTHOR]

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 (C RNA) could not be accounted by the fecal shedding alone. This study aimed to determine potential major shedding sources based on literature data of C RNA , along with the COVID-19 prevalence in the catchment area through a systematic literature review. Theoretical C RNA 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 C RNA estimated with the mean feces shedding magnitude and probability, and 63% of C RNA 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 C RNA in wastewater. The inclusion of sputum as a major shedding source led to more comparable theoretical C RNA to the literature WBE data. Sputum discharging behavior of patients also resulted in great fluctuations of C RNA under a certain prevalence. Thus, sputum is a potential critical shedding source for COVID-19 WBE surveillance. [Display omitted] • A review of SARS-CoV-2 shedding sources and their parameters in wastewater. • Major SARS-CoV-2 shedding sources (feces and sputum) were assessed by Monte Carlo simulations. • Feces, as a major shedding source, contribute partly to SARS-CoV-2 in wastewater. • Sputum is confirmed by simulations as a major source of SARS-CoV-2 in wastewater. [ABSTRACT FROM AUTHOR]