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

Acheampong, Edward; Husain, Aliabbas A.; Dudani, Hemanshi; Nayak, Amit R.; Nag, Aditi; Meena, Ekta; Shrivastava, Sandeep K.; McClure, Patrick; Tarr, Alexander W.; Crooks, Colin; Lade, Ranjana; Gomes, Rachel L.; Singer, Andrew ORCID: https://orcid.org/0000-0003-4705-6063; Kumar, Saravana; Bhatnagar, Tarun; Arora, Sudipti; Kashyap, Rajpal Singh; Monaghan, Tanya M.. 2024 Population infection estimation from wastewater surveillance for SARS-CoV-2 in Nagpur, India during the second pandemic wave. PLOS ONE, 19 (5), e0303529. 18, pp. https://doi.org/10.1371/journal.pone.0303529

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Official URL: http://dx.doi.org/10.1371/journal.pone.0303529

Abstract/Summary

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

Item Type:	Publication - Article
Digital Object Identifier (DOI):	https://doi.org/10.1371/journal.pone.0303529
UKCEH and CEH Sections/Science Areas:	Soils and Land Use (Science Area 2017-)
ISSN:	1932-6203
Additional Information. Not used in RCUK Gateway to Research.:	Open Access paper - full text available via Official URL link.
Additional Keywords:	SARS-CoV-2, COVID 19, Monte Carlo method, infectious disease epidemiology, virus testing, humidity, India, viral load
NORA Subject Terms:	Health Hydrology
Related URLs:	Dataset
Date made live:	30 May 2024 15:02 +0 (UTC)
URI:	https://nora.nerc.ac.uk/id/eprint/537503

Item Type:

Publication - Article

Digital Object Identifier (DOI):

https://doi.org/10.1371/journal.pone.0303529

UKCEH and CEH Sections/Science Areas:

Soils and Land Use (Science Area 2017-)

ISSN:

1932-6203

Additional Information. Not used in RCUK Gateway to Research.:

Open Access paper - full text available via Official URL link.

Additional Keywords:

SARS-CoV-2, COVID 19, Monte Carlo method, infectious disease epidemiology, virus testing, humidity, India, viral load