Real-Time Environmental Surveillance for SARS-CoV-2 in Dhaka, Bangladesh, Provides an Early Warning of Increases in COVID-19 Incidence
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Abstract
Background: Clinical surveillance for COVID-19 has typically been challenging in low-middle income settings. From March 2020-December 2021, we implemented environmental surveillance (ES) in a converging informal sewage network in Dhaka, Bangladesh, to investigate SARS-CoV-2 transmission across different income levels of the city in comparison to clinical surveillance. Methods: We analysed 2,073 sewage samples from 37 sites and 648 days of case data from 8 wards with varying socio-economic 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 despite large differences in reported clinical cases and periods of no cases. Most COVID-19 cases (60.3%) were reported from high-income areas with high levels of clinical testing (261-1603 monthly tests per 100,000 vs. 0-189 in lower-income areas). Conversely, a similar quantity of SARS-CoV-2 was detected in sewage across different income levels (mean difference in high vs. lower-income areas: 0.35 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 July 2021-December 2021 and R=0.59 July 2020-December 2020). Before major waves of infection, viral load quantity in sewage samples increased one to two weeks before the clinical cases.Interpretation: This study demonstrates the utility and importance of environmental surveillance for SARS-CoV-2 in a low-middle income country. We show ES provides an early warning of increases in transmission and shows evidence of persistence of circulation in poorer areas where access to clinical testing is limited.Funding Information: This study was funded by the Bill & Melinda Gates Foundation (INV-022699 and OPP1193124 to M Taniuchi).Declaration of Interests: All authors declare no competing interests.
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