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Population infection estimation from wastewater surveillance for SARS-CoV-2 in Nagpur, India during the second pandemic wave
by
Crooks, Colin
, Bhatnagar, Tarun
, Gomes, Rachel L.
, McClure, Patrick
, Tarr, Alexander W.
, Nag, Aditi
, Nayak, Amit R.
, Dudani, Hemanshi
, Singer, Andrew
, Lade, Ranjana
, Husain, Aliabbas A.
, Monaghan, Tanya M.
, Shrivastava, Sandeep K.
, Kumar, Saravana
, Kashyap, Rajpal Singh
, Meena, Ekta
, Acheampong, Edward
, Arora, Sudipti
in
Accuracy
/ Biology and life sciences
/ Catchment areas
/ Confidence intervals
/ Coronaviruses
/ COVID-19
/ COVID-19 - diagnosis
/ COVID-19 - epidemiology
/ COVID-19 - virology
/ Dilution
/ Disease transmission
/ Earth Sciences
/ Epidemiology
/ Estimates
/ Health aspects
/ Health surveillance
/ Humans
/ Humidity
/ India - epidemiology
/ Infections
/ Infrastructure (Economics)
/ Mathematical models
/ Medical research
/ Medicine and health sciences
/ Medicine, Experimental
/ Monte Carlo simulation
/ Ordinary differential equations
/ Pandemics
/ People and Places
/ Physical sciences
/ Population
/ Population density
/ Prevalence studies (Epidemiology)
/ Public health
/ Rain and rainfall
/ Rainfall
/ Real time
/ Research and analysis methods
/ Respiratory diseases
/ RNA
/ Rural areas
/ Sanitation
/ SARS-CoV-2 - isolation & purification
/ Severe acute respiratory syndrome coronavirus 2
/ Sewage
/ Sewage - virology
/ Sewer systems
/ Sewers
/ Surveillance
/ Urban catchments
/ Viral diseases
/ Viral Load
/ Wastewater
/ Wastewater - virology
/ Wastewater-Based Epidemiological Monitoring
/ Water sampling
/ Water treatment
2024
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Population infection estimation from wastewater surveillance for SARS-CoV-2 in Nagpur, India during the second pandemic wave
by
Crooks, Colin
, Bhatnagar, Tarun
, Gomes, Rachel L.
, McClure, Patrick
, Tarr, Alexander W.
, Nag, Aditi
, Nayak, Amit R.
, Dudani, Hemanshi
, Singer, Andrew
, Lade, Ranjana
, Husain, Aliabbas A.
, Monaghan, Tanya M.
, Shrivastava, Sandeep K.
, Kumar, Saravana
, Kashyap, Rajpal Singh
, Meena, Ekta
, Acheampong, Edward
, Arora, Sudipti
in
Accuracy
/ Biology and life sciences
/ Catchment areas
/ Confidence intervals
/ Coronaviruses
/ COVID-19
/ COVID-19 - diagnosis
/ COVID-19 - epidemiology
/ COVID-19 - virology
/ Dilution
/ Disease transmission
/ Earth Sciences
/ Epidemiology
/ Estimates
/ Health aspects
/ Health surveillance
/ Humans
/ Humidity
/ India - epidemiology
/ Infections
/ Infrastructure (Economics)
/ Mathematical models
/ Medical research
/ Medicine and health sciences
/ Medicine, Experimental
/ Monte Carlo simulation
/ Ordinary differential equations
/ Pandemics
/ People and Places
/ Physical sciences
/ Population
/ Population density
/ Prevalence studies (Epidemiology)
/ Public health
/ Rain and rainfall
/ Rainfall
/ Real time
/ Research and analysis methods
/ Respiratory diseases
/ RNA
/ Rural areas
/ Sanitation
/ SARS-CoV-2 - isolation & purification
/ Severe acute respiratory syndrome coronavirus 2
/ Sewage
/ Sewage - virology
/ Sewer systems
/ Sewers
/ Surveillance
/ Urban catchments
/ Viral diseases
/ Viral Load
/ Wastewater
/ Wastewater - virology
/ Wastewater-Based Epidemiological Monitoring
/ Water sampling
/ Water treatment
2024
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Population infection estimation from wastewater surveillance for SARS-CoV-2 in Nagpur, India during the second pandemic wave
by
Crooks, Colin
, Bhatnagar, Tarun
, Gomes, Rachel L.
, McClure, Patrick
, Tarr, Alexander W.
, Nag, Aditi
, Nayak, Amit R.
, Dudani, Hemanshi
, Singer, Andrew
, Lade, Ranjana
, Husain, Aliabbas A.
, Monaghan, Tanya M.
, Shrivastava, Sandeep K.
, Kumar, Saravana
, Kashyap, Rajpal Singh
, Meena, Ekta
, Acheampong, Edward
, Arora, Sudipti
in
Accuracy
/ Biology and life sciences
/ Catchment areas
/ Confidence intervals
/ Coronaviruses
/ COVID-19
/ COVID-19 - diagnosis
/ COVID-19 - epidemiology
/ COVID-19 - virology
/ Dilution
/ Disease transmission
/ Earth Sciences
/ Epidemiology
/ Estimates
/ Health aspects
/ Health surveillance
/ Humans
/ Humidity
/ India - epidemiology
/ Infections
/ Infrastructure (Economics)
/ Mathematical models
/ Medical research
/ Medicine and health sciences
/ Medicine, Experimental
/ Monte Carlo simulation
/ Ordinary differential equations
/ Pandemics
/ People and Places
/ Physical sciences
/ Population
/ Population density
/ Prevalence studies (Epidemiology)
/ Public health
/ Rain and rainfall
/ Rainfall
/ Real time
/ Research and analysis methods
/ Respiratory diseases
/ RNA
/ Rural areas
/ Sanitation
/ SARS-CoV-2 - isolation & purification
/ Severe acute respiratory syndrome coronavirus 2
/ Sewage
/ Sewage - virology
/ Sewer systems
/ Sewers
/ Surveillance
/ Urban catchments
/ Viral diseases
/ Viral Load
/ Wastewater
/ Wastewater - virology
/ Wastewater-Based Epidemiological Monitoring
/ Water sampling
/ Water treatment
2024
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Population infection estimation from wastewater surveillance for SARS-CoV-2 in Nagpur, India during the second pandemic wave
Journal Article
Population infection estimation from wastewater surveillance for SARS-CoV-2 in Nagpur, India during the second pandemic wave
2024
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Overview
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, R 0 , 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.
Publisher
Public Library of Science,Public Library of Science (PLoS)
Subject
/ COVID-19
/ Dilution
/ Humans
/ Humidity
/ Medicine and health sciences
/ Ordinary differential equations
/ Prevalence studies (Epidemiology)
/ Rainfall
/ Research and analysis methods
/ RNA
/ SARS-CoV-2 - isolation & purification
/ Severe acute respiratory syndrome coronavirus 2
/ Sewage
/ Sewers
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