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Wastewater‐based surveillance can be used as an early warning system to identify COVID‐19 outbreaks because the viral load can be observed in sewage before it is clinically verified. Wastewater surveillance of SARS‐CoV‐2 can trace the transmission dynamics of infection in communities when using the scale of a wastewater diversion and treatment system. Using this early detection method can help protect human health and mitigate socio‐economic losses. It can help quantify the epidemiological data of a given population in real‐time and circumvent the need for other epidemiological indicators. There are challenges in using this technique in areas with underdeveloped sewerage infrastructure. It is especially the case in developing nations where uniform protocols for viral detection are lacking, and wastewater is heterogeneous because of environmental and operational conditions. This article explains the need for and importance of wastewater‐based surveillance for SARS‐CoV‐2. It lays out the most recent methodological approaches for detecting SARS‐CoV‐2 in municipal wastewater and outlines the main challenges associated with wastewater‐based epidemiology (WBE). The article includes a case study of surveillance work across India to demonstrate how a developing nation manages research and locational challenges. The socio‐economic, ethical, and policy dimensions of WBE for SARS‐CoV‐2 are also discussed. This article is categorized under:Engineering Water > Water, Health, and SanitationEngineering Water > Sustainable Engineering of WaterEngineering Water > Methods [ABSTRACT FROM AUTHOR]

One Health concept recognizes the inextricable interactions of diverse ecosystems and their subsequent effect on human, animal and plant health. Antimicrobial resistance (AMR) is a major One Health concern and is predicted to cause catastrophes if appropriate measures are not implemented. To understand the AMR landscape in a south Indian metropolitan city, metagenomic analysis of open drains was performed. The data suggests that in January 2022, macrolide class of antibiotics contributed the highest resistance of 40.1% in the city, followed by aminoglycoside- 24.4%, tetracycline- 11.3% and lincosamide- 6.7%. The 'mutations in the 23S rRNA gene conferring resistance to macrolide antibiotics' were the major contributor of resistance with a prevalence of 39.7%, followed by '16s rRNA with mutation conferring resistance to aminoglycoside antibiotics'- 22.2%, '16S rRNA with mutation conferring resistance to tetracycline derivatives'- 9.2%, and '23S rRNA with mutation conferring resistance to lincosamide antibiotics'- 6.7%. The most prevalent antimicrobial resistance gene (ARG) 'mutations in the 23S rRNA gene conferring resistance to macrolide antibiotics' was present in multiple pathogens including Escherichia coli, Campylobacter jejuni, Acinetobacter baumannii, Streptococcus pneumoniae, Pseudomonas aeruginosa, Neisseria gonorrhoeae, Klebsiella pneumoniae and Helicobacter pylori. Most of the geographical locations in the city showed a similar landscape for AMR. Considering human mobility and anthropogenic activities, such an AMR landscape could be common across other regions too. The data indicates that pathogens are evolving and acquiring antibiotic resistance genes to evade antibiotics of multiple major drug classes in diverse hosts. The outcomes of the study are relevant not only in understanding the resistance landscape at a broader level but are also important for identifying the resistant drug classes, the mechanisms of gaining resistance and for developing new drugs that target specific pathways. This kind of surveillance protocol can be extended to regions in other developing countries to assess and combat the problem of antimicrobial resistance., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024. Published by Elsevier Inc.)

Background: Environmental surveillance (ES) for Salmonella Typhi potentially offers a low-cost tool to identify communities with a high burden of typhoid fever., Methods: We developed standardized protocols for typhoid ES, including sampling site selection, validation, characterization; grab or trap sample collection, concentration; and quantitative PCR targeting Salmonella genes (ttr, staG, and tviB) and a marker of human fecal contamination (HF183). ES was implemented over 12 months in a historically high typhoid fever incidence setting (Vellore, India) and a lower incidence setting (Blantyre, Malawi) during 2021-2022., Results: S. Typhi prevalence in ES samples was higher in Vellore compared with Blantyre; 39/520 (7.5%; 95% confidence interval [CI], 4.4%-12.4%) vs 11/533 (2.1%; 95% CI, 1.1%-4.0%) in grab and 79/517 (15.3%; 95% CI, 9.8%-23.0%) vs 23/594 (3.9%; 95% CI, 1.9%-7.9%) in trap samples. Detection was clustered by ES site and correlated with site catchment population in Vellore but not Blantyre. Incidence of culture-confirmed typhoid in local hospitals was low during the study and zero some months in Vellore despite S. Typhi detection in ES., Conclusions: ES describes the prevalence and distribution of S. Typhi even in the absence of typhoid cases and could inform vaccine introduction. Expanded implementation and comparison with clinical and serological surveillance will further establish its public health utility., Competing Interests: Potential conflicts of interest. All authors: No reported conflicts. All authors have submitted the ICMJE Form for Disclosure of Potential Conflicts of Interest. Conflicts that the editors consider relevant to the content of the manuscript have been disclosed., (© The Author(s) 2023. Published by Oxford University Press on behalf of Infectious Diseases Society of America.)

Wastewater-based epidemiology (WBE) has been implemented globally. However, there remains confusion about the number and frequency of samples to be collected, as well as which types of treatment systems can provide reliable specific details about the virus prevalence in specific areas or communities, enabling prompt management and intervention measures. More research is necessary to fully comprehend the possibility of deploying sentinel locations in sewer networks in larger geographic areas. The present study introduces the first report on wastewater-based surveillance in Gandhinagar City using digital PCR (d-PCR) as a SARS-Cov-2 quantification tool, which describes the viral load from five pumping stations in Gandhinagar from October 2021 to March 2022. Raw wastewater samples (n = 119) were received and analyzed weekly to detect SARS-CoV-2 RNA, 109 of which were positive for N1 or N2 genes. The monthly variation analysis in viral genome copies depicted the highest concentrations in January 2022 and February 2022 (p < 0.05; Wilcoxon signed rank test) coincided with the Omicron wave, which contributed mainly from Vavol and Jaspur pumping stations. Cross-correlation analysis indicated that WBE from five stations in Gandhinagar, i.e., capital city sewer networks, provided two-week lead times to the citywide and statewide active cases (time-series cross-correlation function [CCF]; 0.666 and 0.648, respectively), mainly from individual contributions of the urbanized Kudasan and Vavol stations (CCF; 0.729 and 0.647, respectively). These findings suggest that sewer pumping stations in urbanized neighborhoods can be used as sentinel sites for statewide clinical surveillance and that WBE surveillance using digital PCR can be an efficient monitoring and management tool., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Crown Copyright © 2023. Published by Elsevier B.V. All rights reserved.)

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 10 2 (October 2020) to 1.4 x 10 4 (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., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023. Published by Elsevier Ltd.)

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]

Wastewater-based Epidemiological (WBE) surveillance offers a promising approach to assess the pandemic situation covering pre-symptomatic and asymptomatic cases in highly populated area under limited clinical tests. In the present study, we analyzed SARS-CoV-2 RNA in the influent wastewater samples (n = 43) from four wastewater treatment plants (WWTPs) in Gandhinagar, India, during August 7th to September 30th, 2020. A total of 40 samples out of 43 were found positive i.e. having at least two genes of SARS-CoV-2. The average Ct values for S, N, and ORF 1 ab genes were 32.66, 33.03, and 33.95, respectively. Monthly variation depicted a substantial rise in the average copies of N (~120%) and ORF 1 ab (~38%) genes in the month of September as compared to August, while S-gene copies declined by 58% in September 2020. The SARS-CoV-2 genome concentration was higher in the month of September (~924.5 copies/L) than August (~897.5 copies/L), corresponding to a ~2.2-fold rise in the number of confirmed cases during the study period. Further, the percentage change in genome concentration level on a particular date was found in the lead of 1-2 weeks of time with respect to the official confirmed cases registered based on clinical tests on a temporal scale. The results profoundly unravel the potential of WBE surveillance to predict the fluctuation of COVID-19 cases to provide an early warning. Our study explicitly suggests that it is the need of hour that the wastewater surveillance must be included as an integral part of COVID-19 pandemic monitoring which can not only help the water authorities to identify the hotspots within a city but can provide up to 2 weeks of time lead for better tuning the management interventions., (Copyright © 2021 Elsevier Inc. All rights reserved.)