Poster Session - Abstract # 13

SARS-CoV-2 Wastewater Monitoring in Kansas: Correlation with Clinical Data and Variant Tracking

Justin M. Hutchison, Yasawantha Hiripitiyage, Belinda Sturm

Civil, Environmental, and Architectural Engineering, The University of Kansas, Lawrence, KS, USA

Introduction

The COVID-19 pandemic has highlighted the potential role that wastewater-based epidemiology (WBE) can play in assessing aggregate community health.  However, efforts to translate SARS-CoV-2 gene copy numbers obtained from wastewater samples into meaningful community health indicators are ongoing.  This work will highlight two efforts to promote the use of WBE: 1) comparison of SARS-CoV-2 wastewater measurements during a low-frequency and a high-frequency clinical testing period and 2) the appearance of variants of interest in Kansas communities over time.

Methods

These efforts measured the SARS-CoV-2 nucleocapsid (N) genes (N1 and N2) weekly using reverse transcriptase droplet digital PCR.  To compare measurements with clinical results, two municipal wastewater treatment plants were monitored for six months.  Four biomarkers (human mitochondrial gene NADH dehydrogenase subunit 5 (mit5), creatinine, ammonia, and biological oxygen demand (BOD)) were quantified and used to normalize Sars-CoV-2 gene copy numbers to account for variations in sewershed conditions.  The normalized values were correlated to daily new case data and one-, two-, and three-week cumulative case data.  Variants were determined by amplifying and sequencing the spike (S) gene using artic primers 75, 76 alt, and 77 followed by with clade assignment performed by Nextclade.

Results

Mitochondrial and creatinine normalization methods showed the strongest correlations throughout the studying indicating that human-specific biomarkers were better at normalizing wastewater data than ammonia or BOD.  During low-frequency clinical testing periods, results were strongly correlated with a six-day case data lag (ρ = 0.83), while the high-frequency clinical testing period yielded correlations of 0.81 with a one-day case data lag.  Emergence of variants of concern was observed in wastewater at the same time as clinical samples.

Conclusion

WBE has emerged as an effective public health tool to detect the emergence of disease in a community. As research continues, variant identification has become an additional tool for WBE.