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Preprint in English | medRxiv | ID: ppmedrxiv-22275432

ABSTRACT

Wastewater-based epidemiology (WBE) monitoring can play a key role in managing future pandemics because it covers both pre-symptomatic and asymptomatic cases, especially in densely populated areas with limited community health care. In the present work, wastewater monitoring was employed in Ahmedabad, India, after the successful containment of the first wave of COVID-19 to predict resurgence of the disease in the expected second wave of the pandemic. Here we show wastewater levels of COVID-19 virus particles (i.e., SARS-CoV-2) positively correlated with the number of confirmed clinical cases during the first wave, and provided early detection of COVID-19 presence before the second wave in Ahmedabad and an WBE-based city zonation plan was developed for health protection. A eight-month data of Surveillance of Wastewater for Early Epidemic Prediction (SWEEP) was gathered, including weekly SARS-CoV-2 RNA wastewater analysis (n=287) from nine locations between September 2020 and April 2021. Across this period, 258 out of 287 samples were positive for least two out of three SARS-CoV-2 genes (N, ORF 1ab, and S). Monitoring showed a substantial decline in all three gene markers between October and September 2020, followed by an abrupt increase in November 2020. Similar changes were seen in March 2021, which preceded the second COVID-19 wave. Measured wastewater ORF-1ab gene copies ranged from 6.1 x 102 (October, 2020) to 1.4 x 104 (November, 2020) copies/mL, and wastewater gene levels typically lead confirmed cases by one to two weeks. The study highlights the value of WBE as a monitoring tool to predict waves within a pandemic, identifying local disease hotspots within a city and guiding rapid management interventions. HighlightsO_LIEight-months of SARS-CoV-2 gene variations explicitly predicts 2nd COVID-19 wave. C_LIO_LI258 out of 287 wastewater samples were positive for SARS-CoV-2 genes. C_LIO_LIWBE offers a lead time of 1-2 weeks relative to clinical cases. C_LIO_LIModel suggests that ORF 1ab gene is the most effective as a marker gene in WBE study. C_LIO_LIWBE RT-PCR screening for pathogens should be mandatory for global health monitoring. C_LI

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