ArticlePloS one2024
Population infection estimation from wastewater surveillance for SARS-CoV-2 in Nagpur, India during the second pandemic wave.
Article in PloS one, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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Who cites it
4 citing papers in PubMed.
- Evaluation and estimation of epidemic trajectories for SARS-CoV-2 from clinical and wastewater data in Gauteng Province, South Africa.PLOS global public health · 2026Article
- The potential of wastewater monitoring as a novel surveillance tool for early warning ofEmerging microbes & infections · 2025Article
- Article
- A Review of Wastewater-Based Epidemiology for the SARS-CoV-2 Virus in Rural, Remote, and Resource-Constrained Settings Internationally: Insights for Implementation, Research, and Policy for First Nations in Canada.International journal of environmental research and public health · 2024Review
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Authors and funding
18 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
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.
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