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Real-time sewage surveillance for SARS-CoV-2 in Dhaka, Bangladesh versus clinical COVID-19 surveillance: a longitudinal environmental surveillance study (December, 2019–December, 2021)
BACKGROUND: Clinical surveillance for COVID-19 has typically been challenging in low-income and middle-income settings. From December, 2019, to December, 2021, we implemented environmental surveillance in a converging informal sewage network in Dhaka, Bangladesh, to investigate SARS-CoV-2 transmissi...
Autores principales: | , , , , , , , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier Ltd
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10069819/ https://www.ncbi.nlm.nih.gov/pubmed/37023782 http://dx.doi.org/10.1016/S2666-5247(23)00010-1 |
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author | Rogawski McQuade, Elizabeth T Blake, Isobel M Brennhofer, Stephanie A Islam, Md Ohedul Sony, Syed Shahnewaj Siraj Rahman, Tonima Bhuiyan, Md Hamim Resha, Sabrina Karim Wettstone, Erin G Hughlett, Lauren Reagan, Claire Elwood, Sarah E Mira, Yoann Mahmud, Ayesha S Hosan, Kawsar Hoque, Md Raihanul Alam, Md Masud Rahman, Mahbubur Shirin, Tahmina Haque, Rashidul Taniuchi, Mami |
author_facet | Rogawski McQuade, Elizabeth T Blake, Isobel M Brennhofer, Stephanie A Islam, Md Ohedul Sony, Syed Shahnewaj Siraj Rahman, Tonima Bhuiyan, Md Hamim Resha, Sabrina Karim Wettstone, Erin G Hughlett, Lauren Reagan, Claire Elwood, Sarah E Mira, Yoann Mahmud, Ayesha S Hosan, Kawsar Hoque, Md Raihanul Alam, Md Masud Rahman, Mahbubur Shirin, Tahmina Haque, Rashidul Taniuchi, Mami |
author_sort | Rogawski McQuade, Elizabeth T |
collection | PubMed |
description | BACKGROUND: Clinical surveillance for COVID-19 has typically been challenging in low-income and middle-income settings. From December, 2019, to December, 2021, we implemented environmental surveillance in a converging informal sewage network in Dhaka, Bangladesh, to investigate SARS-CoV-2 transmission across different income levels of the city compared with clinical surveillance. METHODS: All sewage lines were mapped, and sites were selected with estimated catchment populations of more than 1000 individuals. We analysed 2073 sewage samples, collected weekly from 37 sites, and 648 days of case data from eight wards with varying socioeconomic statuses. We assessed the correlations between the viral load in sewage samples and clinical cases. FINDINGS: SARS-CoV-2 was consistently detected across all wards (low, middle, and high income) despite large differences in reported clinical cases and periods of no cases. The majority of COVID-19 cases (26 256 [55·1%] of 47 683) were reported from Ward 19, a high-income area with high levels of clinical testing (123 times the number of tests per 100 000 individuals compared with Ward 9 [middle-income] in November, 2020, and 70 times the number of tests per 100 000 individuals compared with Ward 5 [low-income] in November, 2021), despite containing only 19·4% of the study population (142 413 of 734 755 individuals). Conversely, a similar quantity of SARS-CoV-2 was detected in sewage across different income levels (median difference in high-income vs low-income areas: 0·23 log(10) viral copies + 1). The correlation between the mean sewage viral load (log(10) viral copies + 1) and the log(10) clinical cases increased with time (r = 0·90 in July–December, 2021 and r=0·59 in July–December, 2020). Before major waves of infection, viral load quantity in sewage samples increased 1–2 weeks before the clinical cases. INTERPRETATION: This study demonstrates the utility and importance of environmental surveillance for SARS-CoV-2 in a lower-middle-income country. We show that environmental surveillance provides an early warning of increases in transmission and reveals evidence of persistent circulation in poorer areas where access to clinical testing is limited. FUNDING: Bill & Melinda Gates Foundation. |
format | Online Article Text |
id | pubmed-10069819 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Elsevier Ltd |
record_format | MEDLINE/PubMed |
spelling | pubmed-100698192023-04-04 Real-time sewage surveillance for SARS-CoV-2 in Dhaka, Bangladesh versus clinical COVID-19 surveillance: a longitudinal environmental surveillance study (December, 2019–December, 2021) Rogawski McQuade, Elizabeth T Blake, Isobel M Brennhofer, Stephanie A Islam, Md Ohedul Sony, Syed Shahnewaj Siraj Rahman, Tonima Bhuiyan, Md Hamim Resha, Sabrina Karim Wettstone, Erin G Hughlett, Lauren Reagan, Claire Elwood, Sarah E Mira, Yoann Mahmud, Ayesha S Hosan, Kawsar Hoque, Md Raihanul Alam, Md Masud Rahman, Mahbubur Shirin, Tahmina Haque, Rashidul Taniuchi, Mami Lancet Microbe Articles BACKGROUND: Clinical surveillance for COVID-19 has typically been challenging in low-income and middle-income settings. From December, 2019, to December, 2021, we implemented environmental surveillance in a converging informal sewage network in Dhaka, Bangladesh, to investigate SARS-CoV-2 transmission across different income levels of the city compared with clinical surveillance. METHODS: All sewage lines were mapped, and sites were selected with estimated catchment populations of more than 1000 individuals. We analysed 2073 sewage samples, collected weekly from 37 sites, and 648 days of case data from eight wards with varying socioeconomic statuses. We assessed the correlations between the viral load in sewage samples and clinical cases. FINDINGS: SARS-CoV-2 was consistently detected across all wards (low, middle, and high income) despite large differences in reported clinical cases and periods of no cases. The majority of COVID-19 cases (26 256 [55·1%] of 47 683) were reported from Ward 19, a high-income area with high levels of clinical testing (123 times the number of tests per 100 000 individuals compared with Ward 9 [middle-income] in November, 2020, and 70 times the number of tests per 100 000 individuals compared with Ward 5 [low-income] in November, 2021), despite containing only 19·4% of the study population (142 413 of 734 755 individuals). Conversely, a similar quantity of SARS-CoV-2 was detected in sewage across different income levels (median difference in high-income vs low-income areas: 0·23 log(10) viral copies + 1). The correlation between the mean sewage viral load (log(10) viral copies + 1) and the log(10) clinical cases increased with time (r = 0·90 in July–December, 2021 and r=0·59 in July–December, 2020). Before major waves of infection, viral load quantity in sewage samples increased 1–2 weeks before the clinical cases. INTERPRETATION: This study demonstrates the utility and importance of environmental surveillance for SARS-CoV-2 in a lower-middle-income country. We show that environmental surveillance provides an early warning of increases in transmission and reveals evidence of persistent circulation in poorer areas where access to clinical testing is limited. FUNDING: Bill & Melinda Gates Foundation. Elsevier Ltd 2023-06 /pmc/articles/PMC10069819/ /pubmed/37023782 http://dx.doi.org/10.1016/S2666-5247(23)00010-1 Text en © 2023 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY 4.0 license https://creativecommons.org/licenses/by/4.0/This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Articles Rogawski McQuade, Elizabeth T Blake, Isobel M Brennhofer, Stephanie A Islam, Md Ohedul Sony, Syed Shahnewaj Siraj Rahman, Tonima Bhuiyan, Md Hamim Resha, Sabrina Karim Wettstone, Erin G Hughlett, Lauren Reagan, Claire Elwood, Sarah E Mira, Yoann Mahmud, Ayesha S Hosan, Kawsar Hoque, Md Raihanul Alam, Md Masud Rahman, Mahbubur Shirin, Tahmina Haque, Rashidul Taniuchi, Mami Real-time sewage surveillance for SARS-CoV-2 in Dhaka, Bangladesh versus clinical COVID-19 surveillance: a longitudinal environmental surveillance study (December, 2019–December, 2021) |
title | Real-time sewage surveillance for SARS-CoV-2 in Dhaka, Bangladesh versus clinical COVID-19 surveillance: a longitudinal environmental surveillance study (December, 2019–December, 2021) |
title_full | Real-time sewage surveillance for SARS-CoV-2 in Dhaka, Bangladesh versus clinical COVID-19 surveillance: a longitudinal environmental surveillance study (December, 2019–December, 2021) |
title_fullStr | Real-time sewage surveillance for SARS-CoV-2 in Dhaka, Bangladesh versus clinical COVID-19 surveillance: a longitudinal environmental surveillance study (December, 2019–December, 2021) |
title_full_unstemmed | Real-time sewage surveillance for SARS-CoV-2 in Dhaka, Bangladesh versus clinical COVID-19 surveillance: a longitudinal environmental surveillance study (December, 2019–December, 2021) |
title_short | Real-time sewage surveillance for SARS-CoV-2 in Dhaka, Bangladesh versus clinical COVID-19 surveillance: a longitudinal environmental surveillance study (December, 2019–December, 2021) |
title_sort | real-time sewage surveillance for sars-cov-2 in dhaka, bangladesh versus clinical covid-19 surveillance: a longitudinal environmental surveillance study (december, 2019–december, 2021) |
topic | Articles |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10069819/ https://www.ncbi.nlm.nih.gov/pubmed/37023782 http://dx.doi.org/10.1016/S2666-5247(23)00010-1 |
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