ArticlesThe Lancet Regional
Health - Southeast
Asia 2023;14: 100205
Published Online xxx
https://doi.org/10.
1016/j.lansea.2023.
100205RNA-Seq of untreated wastewater to assess COVID-19 and
emerging and endemic viruses for public health surveillance
Stephen R. Stockdale,a Adam M. Blanchard,b Amit Nayak,c Aliabbas Husain,c Rupam Nashine,c Hemanshi Dudani,c C. Patrick McClure,d,e
Alexander W. Tarr,d,e,f Aditi Nag,g Ekta Meena,g Vikky Sinha,g Sandeep K. Shrivastava,h Colin Hill,a Andrew C. Singer,i Rachel L. Gomes,j
Edward Acheampong,j,k Saravana B. Chidambaram,l Tarun Bhatnagar,m Umashankar Vetrivel,n,o Sudipti Arora,g,∗∗ Rajpal Singh Kashyap,c,∗∗∗ and
Tanya M. Monaghand,p,∗
aAPC Microbiome Ireland, University College Cork, Co. Cork, Ireland
bSchool of Veterinary Medicine and Science, University of Nottingham, Nottingham, United Kingdom
cResearch Centre, Dr G.M. Taori Central India Institute of Medical Sciences (CIIMS), Nagpur, Maharashtra, India
dNational Institute for Health Research Nottingham Biomedical Research Centre, Nottingham University Hospitals National Health
Service Trust, Nottingham, United Kingdom
eWolfson Centre for Global Virus Research, University of Nottingham, Nottingham, United Kingdom
fQueen’s Medical Centre, School of Life Sciences, University of Nottingham, Nottingham, United Kingdom
gDr. B. Lal Institute of Biotechnology, 6-E, Malviya Industrial Area, Malviya Nagar, Jaipur, India
hCentre for Innovation, Research & Development, Dr. B. Lal Clinical Laboratory Pvt. Ltd., Malviya Industrial Area, Malviya Nagar, Jaipur,
India
iUK Centre for Ecology and Hydrology, Wallingford, United Kingdom
jFood Water Waste Research Group, Faculty of Engineering, University of Nottingham, United Kingdom
kDepartment of Statistics and Actuarial Science, University of Ghana, P.O. Box, LG 115, Legon, Ghana
lDepartment of Pharmacology, JSS College of Pharmacy, JSS Academy of Higher Education & Research, Mysuru, 570015, KA, India
mICMR-National Institute of Epidemiology, Chennai, Tamil Nadu, India
nNational Institute of Traditional Medicine, Indian Council of Medical Research, Belagavi, 590010, India
oVirology and Biotechnology Division, ICMR-National Institute for Research in Tuberculosis, Chennai, 600031, India
pNottingham Digestive Diseases Centre, School of Medicine, University of Nottingham, Nottingham, United Kingdom
Summary
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*Corresponding author. National Institute for Health Research Nottingham Biomedical Research Centre, Nottingham University Hospitals National
Health Service Trust, Nottingham, United Kingdom.
**Corresponding author.
***Corresponding author.
E-mail addresses: tanya.monaghan@nottingham.ac.uk (T.M. Monaghan), sudiptiarora@gmail.com (S. Arora), rajpalsingh.kashyap@gmail.com
(R.S. Kashyap).
www.thelancet.com Vol 14 July, 2023 1
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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.
Copyright © 2023 The Author(s). Published by Elsevier Ltd. This is an open access article under the CC BY-NC-ND
license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
Keywords: COVID-19; Endemic viruses; RNA-Seq; SARS-CoV-2; Sewage surveillance; Wastewater-based
epidemiologyResearch in context
Evidence before this study wastewater from India. This observational wastewater-based
High-throughput RNA-sequencing (RNA-Seq) is an emerging proof-of-principle epidemiological study conducted during
tool to monitor, identify, and explore the diversity of viral the second wave of the COVID-19 pandemic, revealed the
pathogens circulating among human and livestock detection of gastrointestinal, parenterally transmitted, and
populations. However, to date, few studies have implemented zoonotic viruses. Of note, our findings reveal for the first time
this technique to study wastewater matrices for the purpose the detection of endemic zoonotic viruses in wastewater
of understanding human population health. Wastewater- samples including Jingmen tick virus, rabies virus and
based epidemiology is a promising strategy to detect chikungunya virus. SARS-CoV-2 was detected in 59% of
pathogens such as severe acute respiratory syndrome sampling locations in Nagpur district, Central India, showing a
coronavirus 2 (SARS-CoV-2) and may serve as an early rural area predominance. Hepatitis C virus was the most
warning system for disease outbreaks, and also as a routine frequently detected virus of which the most prominent
monitoring system for public health departments to genotype was genotype 2, identified in 113 locations and co-
understand the state of health of their nation. A search of occurring 77 times with SARS-CoV-2. Sequencing analysis also
primary research articles published in PubMed up until June revealed the presence of influenza A virus, norovirus, and
18, 2022, using the search terms “RNA-Seq” and rotavirus in addition to several other diarrhoeal-causing
“wastewater” or “RNA-Seq” and “sewage” or “wastewater viruses including astroviruses, saffold virus, husavirus and
virome” returned 54, 19, and 38 studies, respectively aichi viruses.
describing transcriptome sequencing findings, of which the
Implications of all the available evidence
majority were biased towards specific microorganisms and
This study supports the use of wastewater RNA-Seq as a
were mainly conducted in high-income countries. Two studies
valuable qualitative tool for public health surveillance and
detected potential human pathogenic viruses in wastewaters
can be implemented for the identification of endemic and
from Latin America and China. Additionally, three studies
problematic viruses. RNA-Seq as applied to wastewater-
employed RNA-Seq approach for the detection and
based epidemiology may also assist in the design and
mutational/variant analysis of SARS-CoV-2 in wastewater.
implementation of national vaccination programs against
Added value of this study emergent and pre-existent infectious diseases.
To our knowledge, this study is the first to use unbiased RNA-
Seq to obtain a snapshot of the RNA virosphere in untreatedIntroduction
Successful detection of SARS-CoV-2 and other patho-
genic microbes underscores the potential utility of
wastewater-based epidemiology (WBE) for community
surveillance of infectious diseases. Wastewater surveil-
lance can complement clinical diagnostic surveillance by
providing early signs of potential transmission to enable
more active public health responses.1 However, many
WBE studies at the outset of the pandemic focused their
efforts on wastewater treatment plants for WBE, as this
offered a cost-effective insight into large populations.
However, over time, interest grew in understanding
sub-catchment scale epidemiological trends, leading toincreasing numbers of studies focused on within sewer
network and near-source WBE.2 Most studies describing
wastewater surveillance have been conducted in high-
income countries with well-developed sewage infra-
structure.3 Nevertheless, many households in low-to
middle income countries (LMIC) are not connected to
sewage networks due to poor sanitation infrastructure,
with consequent mismanagement of sewage. As such,
surveillance approaches that commence with sampling
WWTP influent in LMICs might not be representative
of actual disease prevalence in the wider community
within the city under surveillance. Few studies have
reported SARS-CoV-2 wastewater surveillance data inwww.thelancet.com Vol 14 July, 2023
Articleslow sanitation settings such as India,4–9 emphasising
that more investigation of wastewater surveillance ap-
proaches is urgently warranted in LMIC settings who at
present might be deprived of the early-warning benefits
of WBE.10 Another important limitation is the lack
of sequencing studies on wastewater samples, particu-
larly high-throughput RNA sequencing (RNA-Seq)
analysis.10–18 This is in contrast to DNA sequencing
studies such as Singh et al. who recently reported on the
bacterial composition of the Indian sewage microbiome
using 16 S rRNA gene amplicon sequencing.19
In view of these limiting factors, our primary aims
were to firstly explore the feasibility of undertaking a
wastewater-based RNA-Seq study of untreated waste-
water samples in a resource limited and environmen-
tally challenging LMIC setting, here Nagpur district,
Maharashtra, Central India. Our secondary aims were to
showcase the power of genomic sequencing to assess
the abundance of multiple viral pathogens simulta-
neously, to examine the co-occurrence of SARS-CoV-2
with other viruses, and to compare the geographic dis-
tribution of viruses in wastewater samples from urban
and rural areas in wastewater samples of this selected
region. We thus concentrated our sampling efforts
during the second wave of the COVID-19 pandemic in
Nagpur, India. Nagpur was the epicentre of the second
deadly wave of COVID-19 in India, which was driven by
the SARS-CoV-2 Delta variant B.1.617 and saw daily
peaks ranging from 5000 to 7000 cases during the
month of April 2021 (figures from Nagpur Municipal
Corporation).Methods
Approvals for wastewater sample collection
As this was an environmental wastewater sampling
study, no formal ethics was required from the respective
institutions. However, official permissions for sample
collection were taken from Nagpur Municipal corpora-
tion (NMC).
Study design and sample collection
We performed a retrospective cross-sectional metatran-
scriptional analysis of untreated wastewater samples in
Nagpur district, Maharashtra, India from 3rd February
to 3rd April 2021 during the second wave of the COVID-
19 pandemic. For wastewater sampling, 422 grab sam-
ples of volume 1 L each were collected in sterile plastic
leak proof containers from the main sewer drainage
lines of 10 different urban municipality zones and from
open drains/surface water resources in rural areas from
Nagpur district. Typically, wastewater samples were
collected by directly filling sample containers up to the 1
L mark. After sample collection, the sample containers
were sanitized with 70% ethanol, labelled with zonal
information and sealed in zip-lock bags. One member of
the field team created a separate performa sheet for eachwww.thelancet.com Vol 14 July, 2023grab sample and filed it while the other team members
collected the samples simultaneously. All samples were
transported to the CIIMS Research department under
cold chain while being kept at the ideal temperature
(2–4 ◦C) in a thermocol box with ice gel packs. All
discrete individual samples were then pooled together in
equal volume, spanning geography and time (3–4
random samples) under aseptic conditions. Based on
the above sampling strategy, a total of 140 composite
samples were prepared which included 112 composites
prepared from urban areas and 28 from rural areas of
Nagpur district. All sampling was conducted in the
morning hours between 07:30 and 12:00 when flow rate
was presumed to be highest due to an anticipated higher
defecation frequency in the morning as previously re-
ported by Heaton et al.20 maximizing the likelihood of
detecting viruses. Area demographics, in addition to
GPS co-ordinates, temperature, relative humidity and
rainfall were also recorded during the sampling period.
All procedures of sample collection were done under
biosafety conditions as per the standard operating pro-
cedures recommended by the Government of India.21
All samples were labelled according to zonal informa-
tion, sealed in zip lock pouches, and transported under
cold chain (4± 2 ◦C) to the Research Department, Cen-
tral India Institute of Medical Sciences (CIIMS). Sam-
ples were then transferred to the Environmental
Biotechnology Laboratory at Dr. B. Lal Institute of
Biotechnology, Jaipur under cold chain transportation
for pre-processing of wastewater and RNA extraction for
sequencing as previously described (Fig. 1).8,22
Storage and pre-processing
Upon receipt of all wastewater samples at the Dr. B. Lal
Institute of Biotechnology, each sample was checked to
ensure that cold chain transport was maintained during
transportation. Wastewater samples were kept at 4 ◦C
until they were pre-processed within 24 h for nucleic
acid extraction. The sample containers were first exter-
nally sterilised for 30 min using UV treatment followed
by heat inactivation done at 70 ◦C for 90 min in a son-
icating water bath.8 Samples were brought to room
temperature and the grit particles were removed by
crude filtration using Whatmann paper and then filtered
using a vacuum filter assembly via a 0.45 μm mem-
brane. Each sample’s filtrate was placed in a new 50 mL
falcon containing 0.9 g sodium chloride (NaCl) and 4 g
polyethylene glycol (PEG). The contents were dissolved
by gentle manual mixing. Samples were then centri-
fuged at 4 ◦C for 30 min at 5750×g. The pellet was re-
suspended in the RNA/DNA shield solution provided
in the ZYMOBIOMICS™ kit.
Nucleic acid extraction
Sample pellets were re-suspended in RNA/DNA shield
buffer and were then further processed for manual
extraction of nucleic acid by the ZymoBIOMICS™ kit3
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Fig. 1: Schematic outline of study methodology.
4
(catalogue no. R2136) according to the manufacturer’s
instructions. Samples were then vortexed mixed for
15 min and centrifuged at 10,000×g for 1 min at and
20 μL of proteinase K was added to the sample and
incubated at room temperature for 30 min. A volume
of 500 μL of DNA/RNA lysis buffer was next added to
the 200 μL sample and mixed well. This was followed
by a DNA separation step by adding 30 μL of Mag-
Binding beads in the above mixture and mixing wellfor 20 min. The microfuge tubes were then transferred
to the magnetic stand until all the beads pelleted. Clear
supernatant containing RNA was transferred to a fresh
tube.
RNA purification
For RNA purification, 700 μL of 95–100% ethanol was
added to the supernatant and mixed well. Next, 30 μL of
MagBinding bead was added to the sample and mixedwww.thelancet.com Vol 14 July, 2023
Articleswell for 10 min. The microfuge tubes were then trans-
ferred to the magnetic stand until the beads pelleted. Next,
500 μL of MagBead DNA/RNA wash was added, and the
sample was mixed, the beads were pelleted and super-
natant discarded. This wash step was repeated. Next,
500 μL of 95–100% ethanol was added, the beads pelleted,
and supernatant discarded. This wash step was repeated
once. The pellet was then air dried until matt. Finally,
50 μL of ZymoBIOMICS™ DNase/RNase-free water was
added and the sample mixed well for 5 min. The super-
natant was transferred into a fresh tube and this latter step
repeated once more. The supernatant was stored
at −70 ◦C. The quality and quantity of the RNA sample
was determined by using Eppendorf biospectrometer®.
Library preparation
Extracted RNA was prepared for sequencing using the
Illumina TruSeq Total RNA Library Preparation Kit
(Illumina, USA). RNA was reverse transcribed using a
random hexamer and superscript II transcriptase (Invi-
trogen, USA) and a second strand synthesised. The ds
cDNA was purified using AmpureXP beads (Beckman &
Coulter, USA) before fragmentation to approximately
300bp using a Covaris M220 (Covaris Inc, USA). The
fragmented ds cDNA was then end repaired, A-tailed
and had Illumina adaptors ligated before size selection
and further purification using AMPureXP beads
(Beckman & Coulter USA). The ds cDNA was then PCR
amplified to incorporate index adaptors (98 ◦C for 30 s,
followed by 15 cycles of 98 ◦C for 10 s, 60 ◦C for 30 s,
72 ◦C for 30 s and a final extension of 72 ◦C for 5 min).
The PCR product was purified again using AMPureXP
beads (Beckman & Coulter USA) before being assessed
on an Agilent Tapestation using the high sensitivity
D1000 tape (Agilent USA). Finally, the libraries were
quantified using a Qubit BR DNA assay (Invitrogen
USA) and then normalised and pooled according to
manufacturer recommendations.
Sequencing
Sequencing was performed on an Illumina HiSeq 2500,
employing paired end 2 × 150bp chemistry to generate
approximately 5 GB of data per sample. Reads were
provided by Eurofins Genomics Bengaluru, India as
quality-checked and adaptor-free. Compressed reads
were downloaded individually from Eurofins India’s
cloud-based ShareFile infrastructure. The quality of
RNA-Seq reads were further assessed using Fastqc
(v0.11.5), with an additionally more stringent quality-
based processing performed using Trimmomatic
(v0.36; SLIDINGWINDOW:4:30 LEADING:3 TRAIL-
ING:3 MINLEN:50). Potential human reads were re-
moved from the RNA-Seq data using Kraken 2 (v2.0.8),
after the kraken2-build command was utilised to ftp
download and compile a Homo sapien (Hsa) database.
Finally, paired end read files were repaired using
BBMap’s “repair.sh” script.www.thelancet.com Vol 14 July, 2023Virome analysis
A custom viral database of human-infecting RNA vi-
ruses was built (March 7th, 2022) using the following
Boolean search in NCBI’s web portal: “Viruses [Organ-
ism] AND txid2559587 [Organism:exp] AND srcdb_ref-
seq [PROP] NOT wgs [PROP] NOT cellular organisms
[ORGN] NOT AC_000001:AC_999,999 [PACC] AND
(“vhost human“ [Filter])”. Processed RNA-Seq reads
were aligned to the RNA viral database using Bowtie 2
(v2.3.5.1) in end-to-end mode. The number of reads
aligned, and their breadth of coverage, per viral
sequence was calculated using SAMTools (v1.10) and
BEDTools (v2.18). However, a BED (Browser Extensible
Data) formatted version of the human-infecting RNA
viral database was necessary and created using the
following commands: (i) samtools faidx [input fasta file];
and (ii) awk ‘BEGIN {FS = “\t”}; {print $1 FS “0” FS $2}’
[fai indexed input fasta file] > [output bed format file]. A
“grep ‘@’ –c” command was used to calculate the overall
number of paired-end and unpaired sequencing reads
per sample after concatenation (median: 30,677,058;
SD: 13,271,310).
Read mapping summaries were imported into R
Studio v3.6.1 for analysis. Dataframes and matrices
were manipulated as necessary using the reshape 2
package. Filtering criteria of (i) ten or more RNA-Seq
reads mapped per viral genome and (ii) a breadth of
coverage of 5% or more was applied. A negative control
buffer-only sequenced sample was used to normalise
the read alignment counts per sample. Subsequently,
viral abundances were normalised by transforming the
alignment counts to reads per kilobase per million reads
(RPKM). The multiple raw metadata records of mixed
composite samples were used to generate a single
representative metadata entry per sample. Where met-
adata variables were numeric, the median value was
chosen, although for character variables, either the most
frequent or middle value after sorting was chosen (for
further details, see Supplementary Tables S1–S3). For
natural composite samples lacking locality metadata, the
following three criteria were applied sequentially to
populate missing values: (1) samples with a longitude
≥79.5 were deemed as a village locality, (2) samples with
a latitude ≥21.1 were assigned to an urban locality, and
(3) the remaining unknown values with a latitude ≤21.1
were considered peri-urban.
Manuscript images were produced using the ggplot2
package with the ggpubr extension. Colours were ob-
tained from the R package pals. The representative map
of the Nagpur district was obtained from Google maps,
with the image cropped using Cartesian points over-
lapping with the longitudinal and latitude collection
locations of untreated sewage samples. Clustering of co-
occurring viruses was performed using base R packages
as follows. The RPKM normalised abundances of
genomic segments and genotypes of related viruses
were aggregated after simplifying each virus’ name.5
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6
Viruses within samples with an RPKM value greater
than zero were deemed present. The measure of simi-
larity and dissimilarity between samples was calculated
using Euclidean distances, with subsequent hierarchical
clustering using the Ward.D2 method. All images were
arranged into their final multi-plot figures using Ink-
scape (v1.1).
Statistical methods
Median comparisons between two groups, or for three
or more groups, were performed using the Wilcoxon or
Kruskal–Wallis tests, respectively, with Bonferroni false
discovery rate correction. Normality of data was assess
using the Shapiro–Wilks test. As a result, Spearman
rank-order correlations were performed. Statistical dif-
ferences between two categorical variables were deter-
mined using the Chi-squared test, except for small
group comparisons that were performed using Fisher’s
exact test. Statistical significance between three or more
categorical variables was established using ANOVA
tests. All statistical tests were carried out at significance
level of P < 0.05.
Role of funding source
The funder of the study had no role in study design, data
collection, data analysis, data interpretation, or writing
of the report.Results
140 untreated wastewater samples were collected during
a COVID-19 wave in the Nagpur district of Central India
(February–April 2021). Of the 140 samples, 83 samples
were collected from urban locations where sewage from
multiple sewerage systems lines were pooled, termed
“pooled piped sewage” samples. There were an addi-
tional 29 urban and 28 rural “mixed composite” samples
that were generated by pooling geographically similar
samples from the same period. This was performed to
ensure all wastewater samples were heterogeneous for
the catchment areas they represent. Given the study’s
sampling size restrictions, and the nature by which
samples were collected, the metadata associated with
each sample was derived from the median of numeric
variables or most frequently coded character variable.
Therefore, nuanced and potentially interesting data may
be overlooked. For instance, where a market or hospital
is in the vicinity of one of the untreated wastewater
samples, these were pooled with other samples from a
similar locality. Therefore, additional investigations us-
ing this study’s data as a resource should note
Supplementary Tables S1–S3.
RNA-Seq reads from all 140 samples were assessed
against a RefSeq-derived custom database of all known
human-infecting RNA viruses (updated March 2022;
see Methods). Of the 822 sequences composing this
viral database, which encompasses viruses with bothmonopartite and segmented genomes and viral geno-
types, 63 unique sequences were detected at least
once.
Non-gastrointestinal human viruses are identifiable
in untreated wastewaters
SARS-CoV-2 was detectable in 83 of the 140 untreated
wastewater samples (Fig. 2a). Furthermore, SARS-CoV-
2 accounted for >1% of the total metagenomic reads for
eight samples and even recruited 35.3% of the RNA-Seq
reads for the rural mixed composite sample, CR4.
Although there was an uneven sampling of urban and
rural sites (Chi-Squared test, P < 0.001), there was a
statistically significant difference in the normalised
abundance of samples positive for SARS-CoV-2 by ge-
ography. Rural samples contained more SARS-CoV-2
than urban samples (Bonferroni adjusted Wilcoxon
test, P = 0.014). This statistical significance was lost
when SARS-CoV-2 was assessed by more stratified lo-
calities (i.e., urban, urban/peri-urban, peri-urban, slum,
and village). The reads per kilobase per million reads
(RPKM) abundances of SARS-CoV-2 were also assessed
against temperature and humidity. Rank-order
Spearman correlations showed no significant relation-
ship between viral normalised abundance and temper-
ature (rho = 0.15, P = 0.085), whereas a significant
correlation between SARS-CoV-2 and humidity was
observed (rho = −0.29, P < 0.0001).
Beyond SARS-CoV-2, untreated wastewater revealed
an abundance of co-occurring human-infecting viruses
(Fig. 2b). This included gastrointestinal viruses, paren-
terally transmitted viruses (i.e., outside of the inte-
stines), and zoonotic viruses. However, when viral
co-occurrence was arranged by hierarchical clustering,
no clear distinction was observed between sampling
locality and the viruses detected. Hepatitis C virus
(HCV) was the most frequently detected virus in the
untreated wastewater samples, present in 113 of the 140
samples (Fig. 3a). HCV and SARS-CoV-2 co-occurred in
77 wastewater samples, with only six samples positive
for SARS-CoV-2 without HCV. The most prominent
HCV genotype detected in this study was genotype 2
(n = 113), followed by genotype 1 (n = 65) and genotype
6 (n = 32). All HCV genotype 6 positive samples also
contained genotype 1, and again, all genotype 1 positive
samples were contained within the genotype 2 positive
samples. Therefore, while HCV genotype sequences can
differ by as much as 33% over their genome23 conserved
HCV regions may contribute to metagenomic-derived
misclassifications of HCV genotypes.
Influenza A virus is continuously monitored for its
potential to cause a pandemic-scale outbreak, with
frequent mutations and genomic segment rearrange-
ments, between human and animal-infecting strains,
altering its infectious and immunogenic properties. In
comparison to SARS-CoV-2, influenza A was infre-
quently detected in the wastewater samples analysed inwww.thelancet.com Vol 14 July, 2023
Articles
a
b
Fig. 2: RNA-Seq to assess emerging and pre-existing pathogenic viruses in untreated sewage samples. (a) The normalised abundance and
best-approximation of geographical position of SARS-CoV-2 detected in untreated sewage samples from the Nagpur district of Central India. (b)
The presence/absence co-occurrence of endemic viruses from the Nagpur district of Central India. RPKM, reads per kilobase per million reads.this study (Fig. 3b). However, the rural mixed composite
sample, CR26, harboured influenza A (H1N1) genomic
segments 1, 2, 3, and 7. Whereas the urban mixed
composite sample, C54, contained influenza A (H1N1)
genomic segments 1, 2, and 5. C54 was recorded as an
urban wastewater sample i.e., sampling location with a
developed sewage infrastructure and CR26 was a rural
wastewater sample collected from open drains, having
an underdeveloped or poor sanitation system. It was
also observed that in rural locations, there was a popu-
lation of livestock nearby, which could possibly
contribute to the finding.www.thelancet.com Vol 14 July, 2023RNA-Seq can detect faecal-oral viruses that
disproportionally affect children
Rotaviruses A (RVA) and C (RVC) were detected in our
untreated wastewater samples (Fig. 4a), with the
magnitude of detection potentially inflated by a seasonal
increase associated with this disease.24 Urban samples
C77, C94, C73, and C22, simultaneously contained nine,
seven, five, and four rotavirus (RV) genomic segments,
respectively. Whereas an additional three, nine and
twenty samples contained three, two, or only one RV
genomic segment, respectively. The most frequently
detected rotaviral genomic segments were RVA segment7
Articles
a Hepatitis C virus
3.0e-07 Hepatitis C virus (isolate H77) genotype 1
Hepatitis C virus genotype 1
2.5e-07
Hepatitis C virus genotype 2
2.0e-07
Hepatitis C virus genotype 6
1.5e-07
1.0e-07
5.0e-08
131 1 26 5 48
0.0e+00
BA
N AN AN UM GE
UR UR
B RBU S
L A
I I VIL
L
R R
, P
E PE
N
RB
A
U
b Influenza A virus
4e−10
3e−10
2e−10
1e−10
7 5
0e+00
AN GE
UR
B LA
VIL
A/Puerto Rico/8/1934(H1N1)  segment 1 A/Puerto Rico/8/1934(H1N1)  segment 7
A/Puerto Rico/8/1934(H1N1)  segment 2 A/Korea/426/1968(H2N2)  segment 2
A/Puerto Rico/8/1934(H1N1)  segment 3 A/California/07/2009(H1N1)  segment 6 neuraminidase (NA) gene
A/Puerto Rico/8/1934(H1N1)  segment 5 A/goose/Guangdong/1/1996(H5N1)  polymerase (PA) and PA−X protein (PA−X) genes
Fig. 3: Abundance and distribution of Hepatitis C virus and Influenza A virus in untreated sewage samples. The normalised abundances of
putative (a) Hepatitis C viral genotypes and (b) Influenza A viral genomic segments identified in untreated sewage samples. The number of
samples with positive RPKM values that were accumulated per location are indicated at the base of each bar. RPKM, reads per kilobase per
million reads.
8
RPKM RPKM11 and segment 6, present in 31 and 10 samples,
respectively. RVA segment 6 co-occurred with segment
11 seven times. RVC genomic segments were detected
more sporadically in untreated sewage, with no specific
RVC segment present in more than 3 of the 140 samples,
indicative of the biased urban sampling in this study and
less frequent association of RVC with humans. Recalling
that data manipulation was necessary to generate
representative metadata for mixed composite samples,
there were three sampling locations observed as having
underdeveloped sewage infrastructure and four areas
predominantly composed of open drains.
In our analysis of untreated wastewater, norovirus
was only detected in urban localities (Fig. 4b). The
Norovirus genogroup GII was the most frequently
detected and abundant genogroup observed. The puta-
tive detection of norovirus genogroups GI and GIV both
only occurred in single samples, whereas samples C94,
C22, and C88, contained five, four, and three noroviralgenomic segments, respectively. Where metadata was
available for norovirus positive mixed composite sam-
ples, one and six locations were recorded as open drains
with a properly developed sanitation infrastructure, and
closed drains and with underdeveloped sanitation,
respectively. Finally, as sample C22 was positive for both
rotavirus and norovirus, we further investigated the
metadata associated with this sample. Searching the
longitude and latitude coordinates of C22 revealed it is
centrally located and within approximately 2 km of five
hospitals and primary health centres, which may reflect
the emergence of nosocomial infection.
A multitude of human pathogenic viruses can be
identified in untreated wastewater through RNA-
Seq
Several additional diarrheal-causing viruses were iden-
tified in the untreated wastewater samples from the
Nagpur district. In our analysis, astroviruses and saffoldwww.thelancet.com Vol 14 July, 2023
Articles
a Rotavirus
1.0e-08
Rotavirus A segment 6 Rotavirus C segment 1 Rotavirus C segment 6
7.5e−09 Rotavirus A segment 7 Rotavirus C segment 2 Rotavirus C segment 7
Rotavirus A segment 8 Rotavirus C segment 3 Rotavirus C segment 8
Rotavirus A segment 10 Rotavirus C segment 4 Rotavirus C segment 9
5.0e−09
Rotavirus A segment 11 Rotavirus C segment 5 Rotavirus C segment 10
2.5e−09
66 1 1 4
0.0e+00
N
BA BA
N M E
R R SL
U AG
U IU VIL
L
R
PE
b Norovirus
8e−10 Norovirus GI/Hu/JP/2007/GI.P3_GI.3/Shimizu/KK2866
Norovirus GII
6e−10 Norovirus GII.P7_GII.6
Norovirus GII.17
4e−10 Norovirus GII.2 strain Env/CHN/2016/GII.P16−GII.2/BJSMQ
Norovirus GIV
2e−10
22 1 2
0e+00
AN AN UM
UR
B B L
IU
R S
PE
R
Fig. 4: Abundance and distribution of the acute gastroenteritis-causing viruses Rotavirus and Norovirus. The normalised abundances of
putative (a) Rotavirus species and its genomic segments and (b) Norovirus genogroups in untreated sewage samples. The number of samples with
positive RPKM values that were accumulated per location are indicated at the base of each bar. RPKM, reads per kilobase per million reads.
RPKM RPKMvirus were both more frequently detected in urban lo-
calities (Fig. 5a and b; Chi-squared tests, P < 0.0001 and
P = 0.002, respectively). However, statistical significance
was not achieved when analysing the cumulative nor-
malised abundance of astroviruses and saffold virus by
locales (Bonferroni adjusted ANOVA tests, P = 0.9 and
0.42, respectively). Husavirus and aichi virus were only
identified in urban areas and were infrequently detected
compared to other human-infecting viruses (Fig. 5c and
e). Interestingly, a single rural sample, CR8, contained
the measles virus with a cumulative abundance greater
than all aichi viral detections combined (Fig. 5d). The
possibility that this observation was an artifact due to
our RNA-Seq and bioinformatic pipeline was rejected,
as it was determined that 30.5% of the 15.9 kb measles
virus genome was covered by sequencing reads.
Untreated wastewater provides a glimpse of
endemic zoonotic viruses
Chikungunya virus (CHIKV) was identified in 11 urban,
4 peri-urban, and 5 village-associated untreated waste-
water endemic samples (Chi-squared test, P < 0.0001),
with the normalised abundance of CHIKV significantly
greater in Nagpur rural areas (Fig. 6a; Bonferroni
adjusted ANOVA test, P = 0.048). The levels of CHIKV
were substantial in several untreated wastewaterwww.thelancet.com Vol 14 July, 2023samples, with four samples having >0.1% of the total
RNA-Seq reads mapping across >90% of CHIKV’s
11.8 kb genome.
Considering the emergence and cross-species trans-
mission of animal viruses into human hosts, the
detection of Jingmen tick virus (JMTV) in untreated
wastewater samples was further investigated (Fig. 6b).
The frequency of detection of JMTV was greater in ur-
ban locales (Chi-squared test, P < 0.0001), although the
cumulative normalised abundance was non-significant
between the collection locations of the untreated
wastewater samples (Bonferroni adjusted ANOVA test,
P = 0.5). Only genomic segment 2 (of four genomic
segments) of JMTV was detected in the RNA-Seq data of
samples.
Stray dogs and rabies are a significant problem in
India, accounting for 35% of the global disease in-
cidents.25 Like JMTV, rabies virus was more frequently
detected in urban localities (Fig. 6c; Chi-squared test, P-
value = 0.003) although its cumulative normalised
abundance was not significantly different between ur-
ban and rural environments (Bonferroni adjusted
ANOVA test, P = 0.11). Given the increased public
awareness of zoonotic diseases and the potential for
emergent viruses through human-animal interactions,
we included porcine endogenous retrovirus (PERV) E in9
Articles
a Astrovirus b Saffold virus
8e−09 3e−09
6e−09
4e−09 2e−09
2e−09
60 1 3 4 2
0e+00
1e−09
AN AN AN UM GE
UR
B B B L
UR UR S ILL
A
RI RI V
 PE PE,
AN 15 4 3
UR
B
0e+00
Astrovirus MLB1 Astrovirus MLB3 isolate MLB3/human/Vellore/26564/2004 Human astrovirus
AN AN GE
Astrovirus MLB2 Astrovirus VA3 isolate VA3/human/Vellore/28054/2005 Mamastrovirus 1 genomic RNA RB RB AU L
RI
U VIL
PE
c Husavirus d Measles virus e Aichi virus
3e−10 2.0e−10
8.0e-10
6.0e-10 2e−10
1.5e−10
4.0e-10 1.0e−10
1e−10
2.0e-10 7 1 5.0e−11 4
0.0e+00 0e+00 0.0e+00
AN AG
E N
B L BA
UR VIL UR
Fig. 5: Abundance and distribution of additional noteworthy human pathogenic viruses. The normalised abundances of putative (a)
Astrovirus genotypes, (b) Saffold virus, (c) Husavirus, (d) Measles virus, and (e) Aichi virus. The number of samples with positive RPKM values
that were accumulated per location are indicated at the base of each bar. RPKM, reads per kilobase per million reads.
10
RPKM RPKM
RPKM
RPKM
RPKM
our analysis (Fig. 6d). No significant difference was
observed in the frequency of detection (Fisher’s exact
test, P = 1.0) or cumulative normalised abundance
(Bonferroni adjusted ANOVA test, P = 0.37) of PERV in
the untreated wastewater samples between geographic
areas.
Finally, encephalomyocarditis virus (EMCV) was the
fourth most frequently detected virus in the RNA-Seq
data analysed, abundant in 60 samples (48 urban vs 12
rural; Chi-Squared test, P < 0.0001). However, an
assessment of its RPKM cumulative abundance shows
EMCV as only the 29th most abundant virus detected.
Discussion
This is one of the few studies to utilise culture-and/or
probe-independent unbiased RNA sequencing to iden-
tify human-infecting RNA viruses in wastewater sam-
ples, and to our knowledge, the first which has analysed
Indian wastewater samples by this technique. Our
findings largely concur with those reported by Corpuz
et al. and Gholipour et al. who summarised the main
pathogenic viruses detected in wastewater, which has
been shown to reflect the pattern of infection in the
human population.26,27 For SARS-CoV-2, we observed a
significantly higher normalised abundance in the rural
samples compared to the urban samples, coupled with a
weak but significant negative association between SARSCoV-2 and humidity. Rural regions in India often have
limited healthcare infrastructure, lack of health educa-
tion, and lower rates of vaccination, which may partially
account for this observation, together with pandemic
denial and social stigma. Meteorological factors, such as
temperature and humidity have previously been sug-
gested to be associated with the transmissibility of
certain infectious diseases and pandemic spreading.
Here, RNA-Seq data demonstrated a negative correla-
tion between SARS-CoV-2 and humidity, which is
concordant with recent cross-sectional surveys in China
and the US which showed robust negative correlations
between temperature/relative humidity and COVID-19
transmissibility.28 Although we did not find any signifi-
cant correlation between SARS-CoV-2 and temperature
in the present study, high temperatures and high rela-
tive humidity have previously been reported to reduce
viability of SARS coronavirus.29 We are aware of only
one earlier clinical study which has examined the inci-
dence of COVID-19 in Nagpur urban region only.
During the study period from May to November 2020,
the overall COVID-19 RT-PCR positivity rate in the
tested samples was 34% in Nagpur region.30
Our genomic results demonstrate that HCV was the
most frequently detected RNA virus in the untreated
wastewater samples and co-occurred with SARS-CoV-2
in 77 samples. Whilst there is no HCV nationalwww.thelancet.com Vol 14 July, 2023
Articles
a Chikungunya virus b Jingmen tick virus isolate SY84 segment 2
2.0e−08
7e−09
1.5e−08
5e−09
1.0e−08
3e−09
5.0e−09
11 4 5 15 3 4
1e−09
0.0e+00 0e+00
AN AN GE N N E
RB RB LL
A A
RB RB
A AG
U U I LL
ER
I V U RI
U VI
P PE
c Rabies virus d Porcine endogenous retrovirus E
5e−09 1.5e−09
4e−09
1.0e−09
3e−09
2e−09
5.0e−10
1e−09
7 1 3 8 2
0e+00
0.0e+00
AN N E
RB B
A AG
U IU
R
VIL
L
BA
N GE
ER UR L
A
P LVI
Fig. 6: Abundance and distribution of human disease-causing zoonotic viruses. The normalised abundances of putative (a) Chikungunya
virus, (b) Jingmen tick virus, (c) Rabies virus, and (d) Porcine endogenous retrovirus E. The number of samples with positive RPKM values that
were accumulated per location are indicated at the base of each bar. RPKM, reads per kilobase per million reads.
RPKM RPKM
RPKM RPKMregistry in India and thus epidemiology is scarce, HCV
seroprevalence has been reported to range between
0.09% and 5.2% across various Indian states.31–33 The
most prominent HCV genotype was genotype 2 which
contrasts with findings from a previous epidemiological
analysis of HCV which showed that genotype 3 was the
most prevalent in India.34 One possible biological
explanation for the concurrent identification of HCV
and SARS-CoV-2 is suggested by emerging evidence
which shows that HCV increases the expression of the
SARS-CoV-2 entry receptor ACE2 in hepatocytes, lead-
ing to enhanced entry of both HCV and SARS-CoV-2
into hepatocytes.35 Furthermore, transmembrane prote-
ase serine 2 (TMPRSS2) expression is over-expressed in
patients with HCV and TMPRSS2 can potentiate SARS-
CoV-2 viral entry.36 However, the degree and nature of
HCV-SARS-CoV-2 interactions and the underlying
mechanisms remain largely unknown and require
further attention. It remains unexplained why we did
not detect Hepatitis A, E, or B in the sequencing data,
particularly when such viruses have been reported to be
endemic in India.32,37,38 RNA-Seq analysis also detected
EMCV in the wastewater samples. As EMCV is infre-
quently associated with human illnesses, its detection in
untreated wastewater is potentially the result of rodentwww.thelancet.com Vol 14 July, 2023and/or animal excrement. Nonetheless, EMCV in non-
human primates principally results in death through
laboured respiration and acute heart failure.39
The transcriptomic data also revealed the presence
of acute gastroenteritis-causing viruses including
several species of type A and B rotaviruses, which were
more prevalent in the urban areas, and various nor-
ovirus genotypes. These findings are consistent with
other next-generation sequencing studies recently
summarised in a systematic review which reports the
occurrence of several pathogenic viruses in sewage
sludge.27 In India, several enteric viruses have been
reported to cause outbreaks, including the co-existence
of multiple viruses. Single viral infections showed
predominance of enterovirus and rotavirus A (RVA).
Genotyping of the viruses revealed predominance of
RVA G2P [4], rotavirus group B (RVB) G2 (Indian
Bangladeshi lineage), norovirus (NoV) GII.4, adeno-
virus (AdV)-40, human astrovirus (HAstV)-8 and
aichivirus (Aiv) B types.40 RVA has also been sewage-
impacted lakes in highly urbanized regions of west-
ern India, where there was a correlation between RVA
and coliphages.41 The burden of viral infectious dis-
eases, such as rotavirus, disproportionally affects
lower-income countries. While the development of a11
Articles
12vaccine severely curbed the mortality rate associated
with rotavirus, there are still an estimated 128,500 to
215,000 global vaccine-preventable deaths annually
due to this virus.42 Children under 5 years of age are at
a greater risk of diarrheal-associated RV mortality,
particularly where there is poor sanitation, inadequate
water quality or water sources not fit for purpose
(drinking, bathing), and unattainable medical care.43
While rotaviruses infect a wide range of mammals,
rotavirus group A (RVA) is more frequently associated
with diarrhoeal infections in children and Rotavirus
group C (RVC) is more commonly associated with
animal contamination.43–45 Unlike rotavirus, norovirus
is problematic in both lower and higher-income
countries due to the lack of a licenced vaccine, with
most people expected to contract the virus five times in
their lifetime.46 There are an estimated 200,000 global
deaths annually attributable to norovirus, the most
cases and deaths associated with any bacterial or viral
diarrhoeal-causing pathogen,47 with cases and deaths
disproportionally affecting children less than 5 years
of age.48
Alongside the common enteric viruses, several
additional diarrhoeal-causing viruses were identified,
including astroviruses and saffold virus which were
more frequently detected in urban localities of Nagpur
district compared with rural areas. However, husavirus
and aichi virus were only detected in urban areas.
While astroviruses are well documented as causing
sporadic and potentially severe cases of gastroenteritis
in children and at-risk groups,49 saffold virus, husa-
virus, and aichi virus are emergent human-infecting
viruses detected with the advent of next-generation
sequencing applications.50–52
Notably, Chikungunya, an arthropod-borne disease
caused by the Chikungunya virus was detected in 19
wastewater samples and was significantly more preva-
lent in the rural areas of Nagpur. This is the first report
describing the detection of CHIKV in wastewater sam-
ples from any country. The CHIKV is currently endemic
across India, with regional outbreaks linked to mosquito
seasonality and human-mosquito habitat interactions.53
While the majority of CHIKV infections are acute,
with a high fever and arthralgia lasting one to two
weeks, the painful arthritic symptoms can last months
and even years.54 Additionally, there is growing evidence
for CHIKV-associated neurological manifestations such
as encephalopathy in adults and children.55 A recent
study in Pune, India reported a fivefold increase in
chikungunya seroprevalence from 2009 to 2019, rising
from 8.5% to 53.2%.56 Therefore, considering the hu-
man and economic impacts caused by CHIKV, greater
surveillance and accurate assessments of its burden are
required to motivate vaccine developments or antiviral
discoveries.
Genomic segment 2 of JMTV was detected at a
higher frequency in urban locales. To the best of ourknowledge, JMTV has not previously been reported in
humans or in wastewater samples, underscoring the
power of wastewater epidemiology, although JMTV and
related viruses have been identified in cattle, rodents,
and primates in multiple regions globally.57 Therefore,
further investigations are warranted to identify and
perform full genomic sequencing of JMTV or related
viruses that are endemic to the district of Nagpur.
Although we detected PERV E-type retrovirus in our
analysis, we observed no significant difference in fre-
quency or cumulative normalised abundance between
different geographic localities. Currently, specific sub-
types of PERV are capable of infecting porcine and hu-
man cells,58 although the principal fear around human
PERV infections is currently focused on the risks
following xenotransplantation.59
EMCV virus has previously been reported in India
where it can cause a human febrile illness, although
there are no recent epidemiological surveys.60,61
Finally, the notable absence of poliovirus may be
attributed to the elimination of poliovirus in India in
2011 with the global immunisation campaigns and
continuation of vaccination efforts thereafter. Indeed, in
India, environmental surveillance complementary to
active surveillance of acute flaccid paralysis (AFP) cases
played a crucial role in poliovirus elimination and has
stimulated COVID-19 surveillance in sewage.62 None-
theless, given the long-drawn effort to eliminate polio,
wastewater surveillance is likely to play an integral part
of public health programs to identify any unreported
cases due to lack of notification.
Our study has some limitations and is partially a
reflection of the logistics with sampling, processing, and
analysing during a pandemic, and the lack of a fully
developed infrastructure for WBE. Samples were
collected over a relatively short time frame of 8 weeks in
one Central Indian district only, and sampling was
cross-sectional rather than longitudinal, meaning there
was no opportunity to evaluate wastewater variability in
terms of composition or to undertake spatiotemporal
distribution analyses. Due to resource limitations,
personnel shortages during the pandemic, long dis-
tances to travel between remote sites, and high tem-
peratures, it was not practical or feasible to deploy
autosamplers to undertake 24-h continuous wastewater
sampling or to assess other wastewater metrics that are
informative of the fate of viruses and other microbes
such as flow rate, pH, and turbidity. Also, our sampling
of wastewater samples was predominantly from urban
areas which might have introduced some bias in the
viruses reported. For example, more rural sites might
have picked up more agricultural/animal signals.
However, the lack of infrastructure in rural settings
further complicates the urban/rural comparison. We
could not correlate the RNA-Seq results with local clin-
ical incident data since this was not available for enteric
and zoonotic viruses. Future studies which aim to buildwww.thelancet.com Vol 14 July, 2023
Articlesupon these observations by performing multicentre
longitudinal sampling over many months to capture
spatiotemporal dynamics. Such studies/monitoring
programs would implicitly then capture the impact of
seasonality and changes in human behaviour on viral
detection. Finally, due to the high levels of variability of
metagenomic reads mapping to reference viral se-
quences, metagenomic assembled genomes from indi-
vidual samples and genotyping analyses of a conserved
phylogenetic marker were not possible.
In conclusion, our analysis provides, for the first
time, the detection of several zoonotic RNA viruses in
urban and rural wastewater samples in Nagpur India,
such as chikungunya and rabies viruses. The COVID-19
pandemic has exposed the weaknesses in rural health-
care in India and other resource-limited settings. This
emphasises the need to shift the urban-centric focus of
policy makers and researchers to ensure equitable
healthcare access and vaccination uptake across all
communities, including those most marginalised.
Considering the COVID-19 pandemic is an emerging
infectious disease of probable animal origin, there is a
clear impetus to improve the surveillance of infectious
diseases and the sanitary conditions of people world-
wide, as well as undertake more intensive surveillance
of wildlife species, which pose a danger for emerging
zoonotic viruses. Our findings add to the growing body
of evidence which suggests that epidemiological sur-
veillance through wastewater-based sequencing can
assist in the identification of endemic and problematic
viruses at a population scale. Comprehensive applica-
tion of this effective and adaptable epidemiological alert
tool can be leveraged for the rapid assessment of
emerging threats, aid pandemic preparedness, and to
monitor progress in attaining global health and the
Sustainable Development Goals (SDGs) formulated by
the United Nations. To realise the full potential reach of
this complementary population health tool in India and
other LMICs, it will be important to build capacity and
scale up current wastewater surveillance and infra-
structure beyond SARS-CoV-2 and polio to other path-
ogens which will also help understand major pathways
and drivers of antimicrobial resistance in the environ-
ment and zoonotic diseases. However, it will be
imperative to standardise and validate existing surveil-
lance methods, including lab procedures, sample size
estimations and statistical tests, where normative bodies
such as the World Health Organisation and Centers for
Disease Control and Prevention alongside national
bodies can play a major role in ensuring quality control.
Contributors
TM was the chief investigator. TM, RK and SA conceived and designed
the study, had full access to all the data in the study and took re-
sponsibility for the integrity of the data and the accuracy of the data
analysis. SS led the RNA-Seq analysis and compiled the results and data
interpretation with assistance from AB and UV. AN (Nagpur team
member), AH, RN and HD were responsible for collection andwww.thelancet.com Vol 14 July, 2023transportation of wastewater samples in Nagpur district as well as data
compilation. AN (Jaipur team member) contributed to protocol stan-
dardization and supervised sample procurement, pre-processing,
nucleic acid extraction and shipments to Eurofins. EM, VS and SS
assisted with sample cataloguing, storage and pre-processing of waste-
water samples. CH advised SS in RNA-Seq data analysis and interpre-
tation. TM, SS and RSK drafted the paper. AS, RG, EA, SC, TB, AT and
PM provided advice on wastewater sampling strategy, statistical analysis
and general data interpretation. All authors read and edited the manu-
script. All authors approved the final version, had full access to all the
data, and had final responsibility to submit for publication.
Data sharing statement
Date reported in the manuscript will be made available to investigators
who provide a methodologically sound proposal to the corresponding
author. The protocol is available upon request. The metadata, processed
sequencing data, and scripts required to generate the images and
interpret the results of this study are provided as Supplementary Data.
The raw RNA-Seq sequencing data analysed in this study is available
through NCBI BioProject accession code: PRJNA842541.
Declaration of interests
This study was principally funded by the Global Challenges Research
Fund (GCRF) awarded to chief investigator TM and GCRF grant co-
investigators RSK, SA, PM, AT, AS, RG, EA, TB, UV, AA, AH as sup-
ported by Research England under UKRI. SS and CH received financial
support from the Science Foundation Ireland (SFI) under Grant Num-
ber SFI/12/RC/2273, a Science Foundation Ireland’s Spokes Pro-
gramme which is co-funded under the European Regional Development
Fund under Grant Number SFI/14/SP APC/B3032, and a research
grant from Janssen Biotech, Inc.
The authors declare no conflict of interest, financial or otherwise.
Acknowledgments
We thank Lorraine Draper for providing intellectual support to SS. We
also thank the Nagpur Municipal Cooperation for their assistance with
wastewater collection. Finally, we thank Saumitra Mardikar, Bishwa-
deep, Samiksha, Ankita Bharshankh and Prachi Gandhi for their
assistance with wastewater sample collection, transportation of samples
and the literature survey.
Appendix A. Supplementary data
Supplementary data related to this article can be found at https://doi.
org/10.1016/j.lansea.2023.100205.References
1 Mao K, Zhang K, Du W, Ali W, Feng X, Zhang H. The potential of
wastewater-based epidemiology as surveillance and early warning
of infectious disease outbreaks. Curr Opin Environ Sci Health.
2020;17:1–7.
2 Castro-Gutierrez V, Hassard F, Vu M, et al. Monitoring occurrence
of SARS-CoV-2 in school populations: a wastewater-based
approach. PLoS One. 2022;17(6):e0270168.
3 Tlhagale M, Liphadzi S, Bhagwan J, et al. Establishment of local
wastewater-based surveillance programmes in response to the
spread of infection of COVID-19-case studies from South Africa,
the Netherlands, Turkey, and England. J Water Health. 2022;
20(2):287–299.
4 Hemalatha M, Kiran U, Kuncha SK, et al. Surveillance of SARS-
CoV-2 spread using wastewater-based epidemiology: comprehen-
sive study. Sci Total Environ. 2021;768:144704.
5 Kopperi H, Tharak A, Hemalatha M, et al. Defining the methodo-
logical approach for wastewater-based studies—surveillance of
SARS-CoV-2. Environ Technol Innov. 2021;23:101696.
6 Tharak A, Kopperi H, Hemalatha M, et al. Longitudinal and long-
term wastewater surveillance for COVID-19: infection dynamics
and zoning of Urban community. Int J Environ Res Public Health.
2022;19(5):2697.
7 Chakraborty P, Pasupuleti M, Jai Shankar MR, et al. First surveil-
lance of SARS-CoV-2 and organic tracers in community wastewater13
Articles
14during post lockdown in Chennai, South India: methods, occur-
rences, and concurrence. Sci Total Environ. 2021;778:146252.
8 Arora S, Nag A, Sethi J, et al. Sewage surveillance for the presence
of SARS-CoV-2 genome as a useful wastewater-based epidemiology
(WBE) tracking tool in India. Water Sci Technol. 2020;82(12):2823–
2836.
9 Lamba S, Ganesan S, Daroch N, et al. SARS-CoV-2 infection dy-
namics and genomic surveillance to detect variants in wastewater–a
longitudinal study in Bengaluru, India. Lancet Reg Health Southeast
Asia. 2023;11:100151.
10 Shah S, Gwee SXW, Ng JQX, Lau N, Koh J, Pang J. Wastewater
surveillance to infer COVID-19 transmission: a systematic review.
Sci Total Environ. 2022;804:150060.
11 Wang Y, Jiang X, Liu L, et al. High-resolution and spatial patterns
of virome in wastewater treatment systems. Environ Sci Technol.
2018;52:18.
12 Gulino K, Rahman J, Badri M, et al. Initial mapping of the New
York City wastewater virome. mSystems. 2020;5(3):e00876–e00919.
13 Garcia-Fontana C, Rodriguez-Sanchez A, Munoz-Palazon B, et al.
Profile of the spatial distribution of the human and bacteriophage
virome in a wastewater treatment plant located in the South of
Spain. Water. 2020;12(8):2316.
14 Guajardo-Leiva S, Chnaiderman J, Gaggero A, et al. Metagenomic
insights into the sewage RNA virosphere of a large city. Viruses.
2020;12:1050.
15 Nieuwenhuijse DF, Oude Munnink BB, Phan MVT, et al. Setting a
baseline for global urban virome surveillance in sewage. Sci Rep.
2020;10:13748.
16 Adriaenssens EM, Farkas K, McDonald JE, Jones DL, Allison HE,
McCarthy AJ. Tracing the fate of wastewater viruses reveals
catchment-scale virome diversity and connectivity. Water Res.
2021;203:117568.
17 Baaijens JA, Zulli A, Ott IM, et al. Variant abundance estimation
for SARS-CoV-2 in wastewater using RNA-Seq quantification.
medRxiv. 2021. https://doi.org/10.1101/2021.08.31.21262938.
18 Balleste E, Blanch AR, Muniesta M, et al. Bacteriophages in sewage:
abundance, roles, and applications. FEMS Microbes. 2022;3:1–12.
19 Singh KS, Paul D, Gupta A, et al. Indian sewage microbiome has
unique community characteristics and potential for population-
level disease predictions. Sci Total Environ. 2023;858:160178.
20 Heaton KW, Radvan J, Cripps H, et al. Defecation frequency and
timing, and stool from in the general population: a prospective
study. Gut. 1992;33(6):818–824.
21 Specimen Collection. Packaging and transport guidelines for 2019
nCOV-acute respiratory disease control. Government of India; 2020.
http://ncdc.gov.in/WriteReadData/1892s/50471431021580628750.
pdf. Cited November 2022.
22 Arora S, Nag A, Kalra A, et al. 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). Environ Monit Assess. 2022;194(5):342.
23 Okamoto H, Kurai K, Okada S-I, et al. Full-length sequence of a
hepatitis C virus genome having poor homology to reported iso-
lates: comparative study of four distinct genotypes. Virology.
1992;188:331–341.
24 Kahn G, Fitzwater S, Tate J, et al. Epidemiology and prospects for
prevention of rotavirus disease in India. Indian Pediatr. 2012;
49:467–474.
25 John D, Royal A, Bharti O. Burden of illness of dog-mediated rabies
in India: a systematic review. Clin Epidemiology Glob Health. 2021;
12:100804.
26 Corpuz MVAC, Buonerba A, Vigliotta G, et al. Viruses in waste-
water: occurrence, abundance, and detection methods. Sci Total
Environ. 2020;745:140910.
27 Gholipour S, Ghalhari MR, Nikaeen M, Rabbani D, Pakzad P,
Miranzadeh MB. Occurrence of viruses in sewage sludge: a sys-
tematic review. Sci Total Environ. 2022;824:153886.
28 Wang J, Tang K, Feng K, et al. Impact of temperature and relative
humidity on the transmission of COVID-19: a modelling study in
China and the United States. BMJ Open. 2021;11:e043863.
29 Chan KH, Peiris JSM, Lam SY, Poon LLM, Yuen KY, Seto WH. The
effects of temperature and relative humidity on the viability of the
SARS coronavirus. Adv Virol. 2011;2011:1–7.
30 Tanna J, Singha B, Nayak AR, et al. Incidence and epidemiological
study of COVID-19 in Nagpur Urban region (India) using molec-
ular testing. medRxiv. 2021. 2021.5.11.21256719 https://dpi.org/10.
1101/2021/05.11.21256719.31 Puri P, Anand AC, Saraswat VA, et al. Consensus statement of
HCV task force of the Indian national association for study of the
liver (INASL). Part I: status report of HCV infection in India. J Clin
Exp Hepatol. 2014;4(2):106–116.
32 Anand A, Shalimar. Hepatitis C virus in India: challenges and
successes. Clin Liver Dis. 2021;18(3):150–154.
33 Bhaumik P. Epidemiology of viral hepatitis and liver diseases in
India. Euroasian J Hepatogastroenterol. 2015;5(1):34–36.
34 Shah SR, Rao PN, Sarin SK, et al. Chronic hepatitis C virus
infection in India: regional demographics and distribution of viral
genotypes. Indian J Gastroenterol. 2016;35:469–477.
35 Domovitz T, Ayoub S, Werbner M, et al. HCV infection increases
the expression of ACE2 receptor, leading to enhanced entry of both
HCV and SARS-CoV-2 into hepatocytes and a coinfection state.
Microbiol Spectr. 2022;10(6):e0115022.
36 Ronderos D, Omar AMS, Abbas H, et al. Chronic hepatitis-C
infection in COVID-19 patients is associated with in-hospital
mortality. World J Clin Cases. 2021;9(29):8749–8762.
37 Bansal Y, Singla N, Garg K, et al. Seroprevalence of hepatitis A
and hepatitis E in patients at a teaching hospital of Northern India
over a period of 8 years. J Family Med Prim Care. 2022;11(2):567–
572.
38 Reddy DCA. Elimination of viral hepatitis: evolution and India’s
response. Indian J Public Health. 2019;63(4):275–276.
39 Carocci M, Bakkali-Kassimi L. The encephalomyocarditis virus.
Virulence. 2012;3:351–367.
40 Chitambar S, Gopalkrishna V, Chhabra P, et al. Diversity in the
enteric viruses detected in outbreaks of gastroenteritis from
Mumbai, Western India. Int J Environ Res Public Health. 2012;9(3):
895–915.
41 Pisharaody L, Suresh S, Mukherji S. Surveillance and seasonal
correlation of rotavirus A with coliphages and coliforms in two
sewage impacted lakes in highly urbanized regions of Western
India. Environ Sci: Water Res Technol. 2022;8:139–150.
42 Cates JE, Tate JE, Parashar U. Rotavirus vaccines: progress and new
developments. Expert Opin Biol Ther. 2022;22:423–432.
43 Varghese T, Kang G, Steele AD. Understanding rotavirus vaccine
efficacy and effectiveness in countries with high child mortality.
Vaccines. 2022;10:346.
44 Rahman M, Banik S, Faruque ASG, et al. Detection and charac-
terization of human group C rotaviruses in Bangladesh. J Clin
Microbiol. 2005;43:4460–4465.
45 Chepngeno J, Diaz A, Paim FC, Saif LJ, Vlasova AN. Rotavirus C:
prevalence in suckling piglets and development of virus-like parti-
cles to assess the influence of maternal immunity on the disease
development. Vet Res. 2019;50:84.
46 Mans J. Norovirus infections and disease in lower-middle and low-
income countries, 1997–2018. Viruses. 2019;11:341.
47 Pires SM, Fischer-Walker CL, Lanata CF, et al. Aetiology-specific
estimates of the global and regional incidence and mortality of
diarrhoeal diseases commonly transmitted through food. PLoS One.
2015;10:e0142927.
48 Bartsch SM, Lopman BA, Ozawa S, Hall AJ, Lee BY. Global eco-
nomic burden of norovirus gastroenteritis. PLoS One. 2016;11:
e0151219.
49 Oude Munnink B, Van der Hoek L. Viruses causing gastroenteritis:
the known, the new and those beyond. Viruses. 2016;8:42.
50 Yamashita T, Sugiyama M, Tsuzuki H, Sakae K, Suzuki Y,
Miyazaki Y. Application of a reverse transcription-PCR for identi-
fication and differentiation of aichi virus, a new member of the
picornavirus family associated with gastroenteritis in humans.
J Clin Microbiol. 2000;38:2955–2961.
51 Jones MS, Lukashov VV, Ganac RD, Schnurr DP. Discovery of a
novel human picornavirus in a stool sample from a pediatric pa-
tient presenting with fever of unknown origin. J Clin Microbiol.
2007;45:2144–2150.
52 Oude Munnink BB, Cotten M, Deijs M, et al. A novel genus in the
order Picornavirales detected in human stool. J Gen Virol.
2015;96:3440–3443.
53 The Translational Research Consortia (TRC) for Chikungunya Vi-
rus in India. Current status of chikungunya in India. Front Micro-
biol. 2021;12:695173.
54 Silva LA, Dermody TS. Chikungunya virus: epidemiology, replica-
tion, disease mechanisms, and prospective intervention strategies.
J Clin Invest. 2017;127:737–749.
55 Brizzi K. Neurologic manifestation of chikungunya virus. Curr
Infect Dis Rep. 2017;19:6.www.thelancet.com Vol 14 July, 2023
Articles56 Tomar SJ, Alagarasu K, More A, et al. Decadel change in seropre-
valence of chikungunya virus infection in Pune city, India. Viruses.
2022;14(5):998.
57 Guo J-J, Lin X-D, Chen Y-M, et al. Diversity and circulation of Jing-
men tick virus in ticks and mammals. Virus Evol. 2020;6:veaa051.
58 Denner J. Recombinant porcine endogenous retroviruses
(PERV-A/C): a new risk for xenotransplantation? Arch Virol.
2008;153:1421–1426.
59 Łopata K, Wojdas E, Nowak R, Łopata P, Mazurek U. Porcine en-
dogenous retrovirus (PERV)—molecular structure and replicationwww.thelancet.com Vol 14 July, 2023strategy in the context of retroviral infection risk of human cells.
Front Microbiol. 2018;9:730.
60 Paul SD, Pavri KM, D’Lima LV, Rajagopalan PK, Goverdhan MK,
Singh KR. Isolation of encephalomyocarditis (EMC) virus strains in
India. Indian J Med Res. 1968;56(3):264–274.
61 Oberste MS, Gotuzzo E, Blair P, et al. Human febrile illness caused
by encephalomyocarditis virus infection, Peru. Emerg Infect Dis.
2009;15(4):640–646.
62 Ishtiaq F. India must scale up wastewater analysis for health. Na-
ture India. 2022. https://doi.org/10.1038/d44151-022-00130-5.15