Abstract

How to effectively leverage wastewater data to estimate the risk of various infectious diseases remains a great challenge. To address this issue, we conducted continuous wastewater surveillance in Dalian city during the summer-autumn seasons of 2022, targeting coronavirus and bacterial diseases. The surveillance included daily sampling at a wastewater treatment plant (WWTP) and weekly sampling in three sewersheds. Targeting the bacteria's 16S rRNA gene and the coronavirus's RNA-dependent RNA polymerase (RdRp) gene, we first employed RT–PCR and amplicon sequencing techniques to analyze the presence and phylogenetic relationship of detected coronavirus and bacterial pathogens. Next, qPCR was used to quantify the abundances of detected coronavirus and bacterial species. Based on the daily shedding dynamics of SARS-CoV-2, a novel model was developed to predict daily new cases. Based on the medium shedding density of 12 pathogens, two thresholds of sewage pathogen load (indicating 0.1 % and 1 % infection rates) were proposed. Our PanCoV RT–PCR detected coronavirus on 12th August and from 26th August to 12th September 2022. Targeted amplicon sequencing further identified human coronavirus OC43 (hCoV-OC43) on 12th August and the SARS-CoV-2 Omicron variant since 26th August in samples from WWTPs and sewersheds. Phylogenetic analysis revealed that hCoV-OC43 from this study belonged to genotype K and suggested a close relationship between the amplified coronavirus sequences from wastewater and clinical samples in a local COVID-19 outbreak on 26th August. Amplicon sequencing targeting the bacterial 16S rRNA gene also revealed the presence of several bacterial pathogens. Finally, we assessed the microbial risk of specific pathogens in sewersheds and identified a number of pathogens that reached high (>1 % prevalence) and medium risk levels (>0.1 % prevalence) at sewershed B. Our findings underline wastewater surveillance as a valuable early warning system for coronavirus and other waterborne bacterial diseases, complementing public health response measures.

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