To effectively curb the spread of SARS-CoV-2 within communities, prompt detection of the virus is imperative because the traditional methods pose a challenge in detecting the emerging variants and accurately quantifying their prevalence (Amman et. al., 2022). In light of this, our study utilized Wastewater-Based Epidemiology (WBE) to examine the virus's proliferation, dissemination, and evolution across urban, suburban and densely populated areas of Maharashtra state, areas that are particularly vulnerable to outbreaks. Drawing on the findings of Haque R. et al., which demonstrate the successful detection of SARS-CoV-2 in wastewater, unhindered by inhibitors, xenobiotics, diluted viral loads, and fragmented RNA (Haque et. al., 2023); we isolated SARS-CoV-2 RNA from wastewater samples. Subsequently, we employed RT-qPCR for viral load quantification and whole genome amplicon sequencing to understand the progression of SARS-CoV-2 lineages in the community.
Over a period of 12-month study conducted between June 2022 and May 2023, SARS-CoV-2 RNA was consistently detected in open drain wastewater samples collected from multiple cities across three major regions of Maharashtra: Mumbai (10 sites), Western Maharashtra (6 sites), and Central Maharashtra (7 sites). An RT-qPCR assay targeting three SARS-CoV-2 genes (N, RdRp, and E) was employed to screen all samples for SARS-CoV-2 detection and quantification. A sample was deemed positive for SARS-CoV-2 if it exhibited Ct values below 35 for at least two of these gene targets. A total of 1548 samples were collected from WW open drain sites over the 12 months. Of these, 44.89% (n = 695) were found to be positive for SARS-CoV-2 via RT-qPCR, whereas the remaining 55.11% were negative. Our analysis of the RT-qPCR data revealed inconsistencies in the recovery rate of SARS-CoV-2 RNA, possibly attributable to the varying dilution rates of domestic wastewater, shifts in variant trends, and the influence of different inhibitors, such as detergents and chemicals, and other physicochemical properties of wastewater across different locations (Maida et. al., 2023; Jimenez et. al., 2023). Moreover, our findings underscore wastewater's potential to provide early insights into the passive and active transmission of SARS-CoV-2, even preceding clinical detection. This is significant, as clinical surveillance often struggles to anticipate pathogen outbreaks promptly due to restricted clinical testing capacities and the prevalence of asymptomatic or passively infectious individuals within populations (Wannigama et. al., 2023).
3.1 Quantification of SARS-CoV-2 RNA in Wastewater
To further assess the extent of viral spread in the community across all regions, a viral load calculation tool (https://coviquant.genepathdx.com/) was employed to quantify SARS-CoV-2 RNA copies in each sample. Analysis of weekly average viral loads from Mumbai, Western Maharashtra, and Central Maharashtra regions, including their respective cities, revealed an almost identical viral trend across these regions (Fig. 2). This finding indicates the widespread circulation of SARS-CoV-2 in the region. Specifically, a significant surge in viral load was first detected in July 2022, continuing until September 2022 with an average viral load of 37,237 gc/l. This was followed by a decline from September 2022 and a second, less intense peak from November 2022 to December 2022, with an average viral load of 13,517 gc/l. A third peak occurred from February 2023 to April 2023, with an average viral load of 56,363 gc/l, declining from May 2023 onward. Overall, the high detection rate of SARS-CoV-2 fragments across all regions highlights the sensitivity of wastewater-based surveillance (WBS) for monitoring ongoing viral activity within a population. This approach provides valuable insights into community-level transmission dynamics, potentially detecting trends that may not be fully reflected in clinical testing data.
Mumbai region
In the Mumbai region, a drop in average viral load was observed in the first week of the study, from 92,334 gc/l (June 2022, week 3) to 1,936.92 gc/l (June 2022, week 4), with Bhiwandi-Nizampur MC city recording the highest viral load (365,000 gc/l). The first peak occurred from July to August 2022, with an average viral load of 28,933 gc/l. High viral titers were observed in Mira Bhayandar, Navi Mumbai, and Bhiwandi-Nizampur MC city. A second peak was observed from November to December 2022, with Kalyan recording the highest load (60,500 gc/l). In February 2023, a viral load increase led to a peak in April 2023, with Badlapur reporting the highest titer in the region (747,000gc/l). (Fig. 3A)
Central Maharashtra region
The Central Maharashtra region comprised a total of 7 cities (mentioned in methodology). All the locations showed an increase in viral load from 1st week of July 2022. Among these Solapur was noticed to grab a peak in 2nd week of July 2022 with a total of 314500 gc/l, followed by Ahmednagar and Aurangabad in 3rd and 4th week of July 2022 respectively. The 2nd peak in the region was observed in the 3rd week of Dec 2022, and the highest peak was exhibited by Barshi with 206000 gc/l while other locations had viral loads between 21200 gc/l to 53100 gc/l. For the 3rd peak of the epidemic wave, viral load started increasing from 1st week of Feb 2023, and the subsequent increase was noticed from 1st week of Mar 2023. The peak was exhibited by Ahmednagar and Solapur in the 4th week of March 2023 with more than 400000 gc/l (Fig. 3B).
Western Maharashtra region
In Western Maharashtra region, viral load of Sangli and Ichalkaranji reached a height during the first epidemic wave with an average viral load of 181750 gc/l. While, in the Sept 2022 and Dec 2022, all the 6 locations represented a peak with the average viral titre of 112875 gc/l and 68927 gc/l respectively. In the 2nd week of Feb 2023, a third epidemic wave was initiated with an increase in genomic copies and grabbed a peak in the 3rd week of Feb 2023. For a couple of weeks, there was a drop in viral load and again in the 2nd week of Mar 2023, the peak was noticed in all the locations, after which it subsequently reduced. Despite that, Sangli represented a steep increase to 296500 gc/l in the 2nd week of Apr 2023 (Fig. 3C).
Conclusively, the higher viral titer grabbed by Bhiwandi Nizampur MC, Mira Bhayandar, Kalyan, Ambarnath and Navi Mumbai, the cities among the Mumbai region, might be due to the high population density of the respective areas. Islam et. al. believes that COVID-19 incidence rates are directly proportional to population density because viruses can be transmitted easily when the population is in closer contact for a wider time span (Islam et. al., 2020). Hence, it can be inferred that the aforementioned locations were remarked with heightened viral loads in RT-qPCR analysis, likely attributed to their densely populated nature, which is prone to transmit the infections hastily. A similar research by Panda et. al. has suggested that slums are conducive to the rapid spread of viruses due to their high density. To further investigate this aspect, their study examines COVID-19 incidence within the slums of Mumbai (Dharavi- Asia's largest slum) where higher COVID-19 incidences were found (Panda S. & Ray S. S., 2021). This report corroborates the findings of our study. Specifically, certain cities within the Mumbai region, such as Mira Bhayandar and Bhiwandi Nizampur Municipal Corporation (MC) city, which are characterized by substantial slum populations, exhibited higher viral titers compared to other cities in the region. Conversely, in the central and western regions of Maharashtra, population density appears to be a less significant factor in influencing viral load. Most of the cities in the Central and Western Maharashtra region border the metropolitan area of Pune, which is one of the locations in Western Maharashtra region. And as metropolitan cities facilitate with the easy availability of essential services like healthcare, food services, public transportation and retail; there is a conceivability for observing the quick spread of pathogens causing higher viral loads in the locales (Lee et.al., 2021). Therefore it can be predicted that in central Maharashtra region- Solapur, Ahmednagar, Barshi and Aurangabad; and in Western Maharashtra region- Sangli and Ichalkaranji remarked with the higher viral titers.
The SARS-CoV-2 RNA viral load trend was compared with the positivity trend of the clinical cases in Maharashtra state. It was noticed from the clinical data obtained from IDSP (Integrated Disease Surveillance Program) that the number of clinical testing in the state drastically fell down from the end of the year 2022 (Fig. 4). As of 2022, global COVID-19 reporting trends indicate that the true extent of infections and reinfections may be underestimated due to which numbers of clinical case reportings are declined (Puenpa et. al., 2024). Related observations were found in Clinical case Data from Maharashtra state from the year 2022; a significant decline in confirmed cases: from nearly 26000 cases in June 2022 and then down to about 5000–6000 cases in April 2023. Additionally, linking wastewater measurements to clinical cases is complex due to individuals' mobility across different neighbourhoods, which complicates tracing infections to specific areas based on residential addresses. (Parkins et. al., 2023). Even though, in the present study, during each peak of escalating viral load in wastewater, the number of clinical cases showed a slight height. The Omicron wave of COVID-19 was distinct, primarily due to the variant's high transmissibility but low virulence, and significant vaccination coverage among adults (Haque et. al., 2023). This combination resulted in less severe symptoms and reduced strain on critical care compared to earlier waves (Bhagavthula et. al., 2022). Consequently, it resulted in the less number of clinical testing in further years. Therefore Wastewater-based epidemiology (WBE) is poised to become a key tool in tracking and managing the spread of COVID-19, offering a cost-effective and efficient alternative to individual testing. This approach can help pinpoint the spread and hotspots of the virus in communities, provided that the virus can be detected in faeces (Hamouda et. al., 2021).
3.2 SARS-CoV-2 Lineage Speculation in Wastewater
To acknowledge the variant trends over the state, we implemented extensive whole genome amplicon sequencing on the samples ascertained positive in RT-qPCR on both Nanopore (MK1C) and Illumina (Illumina NextSeq 550 sequencer) platforms. Among all the samples sequenced, 497 out of 989 samples passed on the Nanopore platform and 59 out of 361 samples passed on Illumina platform, resulting in an overall sequencing success rate of 41.25% with ≥ 40% genome coverage. However, the remaining 58.81% of samples failed in sequencing due to insufficient data and low-quality reads. We successfully sequenced and analysed a total of 556 samples which were passed in sequencing using the “Lineage decomposition” (LCS) tool to previse the lineage diversity and their relative probability. This comprehensive analysis identified 22 distinct lineages.
Beginning from June 2022 to Dec 2022, BA.2.75 lineage showed dominance followed by BA.2.38 and BA.2.10. Further, XBB.1.16.X emerged as most dominant from Dec 2022 to May 2023. Over this one year of study, XBB.1.16.X accounted for 24.7%, followed by BA.2.75 with 16% of total abundance. Besides this, other lineages such as Omicron (BA) (5.3%), BA.1 (0.8%), BA.1.X (4%), BA.2 (1.1%), BA.2.X (2.4%), BA.2.12 (0.8%), BA.2.38 (5.3%), BA.3 (1.6%), BA.5 (0.6%), BF.7.X (0.7%), BQ.X (0.2%), CH.1.1 (1.7%), XBB (2.8%) XBB.1.5.X (8.5%), XBB.1.9.1.X (4.3%), XBB.2.3.X (7.9%) and BA.2.86.X (1.2%) also highlighted their signals. Additionally, our study also noted the transient prominence of variants like CH.1.1.X, BQ.X, BF.7 and BA.2.86 which, although less frequent, contributed to the overall diversity of SARS-CoV-2 variants observed in Maharashtra state.
3.3 Early detection of emerging variants
Our approach was to detect lineages outspreading in the regions of Maharashtra state that are more vulnerable to epidemic infections. In this study, when we investigated the reports of genome sequencing, three epidemic waves were observed– 1st wave (3rd week of June 2022–2nd week of Sept 2022) and 2nd wave (1st week of Nov 2022–2nd week of Dec 2022) were noticed to be overlapping with the spread of BA.2.38 & BA.2.75. The 3rd wave (1st week of Feb 2023–1st week of May 2023) showed dominance of XBB 1.16.X. In this one year of surveillance, dominance was mainly shown by BA and XBB variants and their respective sublineages. Samal et.al. also describes the similar findings with the clinical reportings from Delhi, India (Samal et.al., 2023; Puenpa et.al., 2024). In June 2022, the most dominating lineage was BA.2.38 with 39.6% till August 2022 followed by BA.2.75 with 23.4%. By July 2022, BA.2.75 had overtaken the dominance till Dec 2022. Thereafter, its eminence diminished and XBB.1.16.X demonstrated an upward trend showing its supremacy by Jan 2023. In contrast, BA, BA.2.10, XBB.1.5.X and XBB.2.3.X were noticed to be signalled throughout a year of study. (Fig. 5).
Furthermore, as we revealed the ascendancy of omicron sub-lineages such as BA, BA.2.38 and BA.2.75 during the initial months of study (June 2022- Dec 2022); In conformity with the GISAID database and some other published reports, BA.2.38 was clinically detected for the first time in India on 07 Jan 2022 (Rajput et. al., 2023). While in Maharashtra state, it was clinically reported for the first time in Aug 2022. However, in the present study, BA.2.38 was noticed in wastewater in June 2022 which is two months prior to the clinical reporting. Similarly, BA.2.75 was globally reported for the first time in two states of India namely in Karnataka and Jammu and Kashmir in June 2022, and when we started the present surveillance in June 2022, its prevalence was already there with 27.4% of abundance and further increased to 43.8% in Sept 2022.
According to Karyakarte et. al., clinical case of XBB.1.16.X firstly appeared in India, in the sample collected from Tamilnadu state on 25 Dec 2023 (karyakarte et. al., 2023). On the other hand, as per the GISAID database and some Indian news collections, it was reported for the first time in India on 9 Jan 2023 (Puenpa et. al. 2024). While, in our report some traces of XBB.1.16.X were observed in late July 22 that is 157 days earlier than clinical reporting with 9.9% of total abundance in Ahmednagar city of Central Maharashtra region, and subsequently increasing by Jan 2023 which finally reached to 52.4% in May 23 (Fig. 3C-lineage trend in central MH). Therefore, based on these findings our study predicts that XBB may have been circulating in the community with low frequency prior to its high prevalence which commenced in January 2023.
In the Mumbai region, a drastic increase in the abundance of XBB.1.16.X was observed by March 2023 (Fig. 6A). On the contrary, in the Central (Fig. 6B) and Western Maharashtra region (Fig. 6C), the same incidence was noticed from January 2023. Conclusively, 4/23 cities presented traces of XBB.1.16.X signals in Aug 2022 (Approx. 5 months before). 6/23 cities revealed in Sept and Oct 2022 (4 months before). Rest of the cities showed its signals from Dec 2022 (1 month before). In addition to this, XBB.1.5.X was discovered in Africa on 2nd June 2022, in Gujrat, India, on 10th Oct 2022; and in Maharashtra, India it was reported clinically on 23rd Nov 2022. While in this study its signals were noticed in the wastewater samples of the Mumbai region in June 2022 that is around 180 days before clinical prevalence (Fig. 6A). The BA.2.86 variant was first reported globally in the USA on 22 Oct 2022. Subsequently, it was identified in India on 18 Oct 2023, and a wastewater study in Thailand detected it earlier on July 28, 2023. Notably, our study detected signals of BA.2.86 as early as January 2023, where it constituted 4% of the total variants identified with no documented clinical cases at that time. Similar findings were noticed for XBB.1.9.2, XBB.1.9.1.X, CH.1.1. Consequently, our study detects the transition of BA to XBB variant from June 2022 to May 2023. Additionally, the dominating period of the variants detected in this report mirrors the GISAID database, expressing the early signals of the newly emerging variants in wastewater samples.
Similar studies have been published earlier by Rajput et.al. and Dharmadhikari et.al. reporting Delta to Omicron transition and Analysis of SARS-CoV-2 mutations using wastewater respectively (Rajput et. al., 2023; Dharmadhikari et. al., 2022). However, their findings are restricted to only Pune city, whereas our study has surveyed the Western (including Pune city) and the Central part of Maharashtra state including the Mumbai region which outlined the changeover of BA.2.75 to XBB.1.16.X. The three regions surveyed in this study encompass both urban and suburban areas. Notably, the urban cities within these regions such as Navi Mumbai and Pune exhibit a higher susceptibility to the transmission of new viral variants, attributable to their denser networks of transportation and the presence of multiple amenities for foreign visitors. This factor may contribute to a higher incidence of clinically reported cases in urban cities compared to suburban areas of the region. Furthermore, the presence of new variants can be detected through wastewater surveillance in communities where clinical testing is less prevalent. Rajput et al. suggest that the early detection and monitoring of infectious pathogens are crucial; thus, they advocate for the global implementation of wastewater-based epidemiology (WBE). They acknowledge that WBE is pivotal for tracking the dynamics of viral infections, as it allows for the early identification of viruses shed in wastewater, thereby serving as an essential tool for monitoring the spread of infections within communities (Hamouda et.al., 2021; Rajput et. al., 2023). WBE is a non-invasive method for monitoring SARS-CoV-2 in communities by analysing sewage in near-real-time. But In many urban areas of LMICs and most areas particularly from suburban regions lack centralized sewer connections, limiting the reach of wastewater-based surveillance (WBS). Despite this, strategically placed WBS sites can lead to WBS and effectively monitor disease prevalence cost-effectively (Parkins et. al., 2023) Moreover, the lack of formal sewerage systems in LMICs complicates wastewater surveillance, but adapting environmental surveillance methods for these areas could improve monitoring and response to COVID-19 and future pandemics (Murni et. al. 2022). This data can then be used for retrospective analysis to trace back the source communities (Lamba et. al., 2022), aiding in the early detection of COVID-19 infections up to several weeks before cases are clinically reported at a city-wide scale.