RESUMO
Wastewater-based epidemiology (WBE) has emerged as a promising tool for monitoring the spread of COVID-19, as SARS-CoV-2 can be shed in the faeces of infected individuals, even in the absence of symptoms. This study aimed to optimize a prediction model for estimating COVID-19 infection rates based on SARS-CoV-2 RNA concentrations in wastewater, and reveal the infection trends and variant diversification in Shenzhen, China following the lifting of a strict COVID-19 strategy. Faecal samples (n = 4337) from 1204 SARS-CoV-2 infected individuals hospitalized in a designated hospital were analysed to obtain Omicron variant-specific faecal shedding dynamics. Wastewater samples from 6 wastewater treatment plants (WWTPs) and 9 pump stations, covering 3.55 million people, were monitored for SARS-CoV-2 RNA concentrations and variant abundance. We found that the viral load in wastewater increased rapidly in December 2022 in the two districts, demonstrating a sharp peak in COVID-19 infections in late-December 2022, mainly caused by Omicron subvariants BA.5.2.48 and BF.7.14. The prediction model, based on the mass balance between total viral load in wastewater and individual faecal viral shedding, revealed a surge in the cumulative infection rate from <0.1 % to over 70 % within three weeks after the strict COVID-19 strategy was lifted. Additionally, 39 cryptic SARS-CoV-2 variants were identified in wastewater, in addition to those detected through clinical surveillance. These findings demonstrate the effectiveness of WBE in providing comprehensive and efficient assessments of COVID-19 infection rates and identifying cryptic variants, highlighting its potential for monitoring emerging pathogens with faecal shedding.