Genomic Analysis and Surveillance of Respiratory Syncytial Virus Using Wastewater-Based Epidemiology
Danielle M Allen, Marina Reyne, Pearce Allingham, Ashley Levickas, Stephen H. Bell, Jonathan Lock, Jonathon D. Coey, Stephen Carson, Andrew Lee, Cormac McSparron, Behnam Firoozi Nejad, James McKenna, Mark Shannon, Kathy Li, Tanya Curran, Lindsay Broadbent, D.G. Downey, Ultan F. Power, Helen Groves, Jennifer McKinley, John W. McGrath, Connor Bamford, D.F. Gilpin
Abstract
Respiratory syncytial virus (RSV) causes severe infections in infants, immunocompromised or elderly individuals resulting in annual epidemics of respiratory disease. Currently, limited clinical surveillance and the lack of predictable seasonal dynamics limit the public health response. Wastewater-based epidemiology (WBE) has recently been used globally as a key metric in determining prevalence of severe acute respiratory syndrome coronavirus 2 in the community, but its application to other respiratory viruses is limited. In this study, we present an integrated genomic WBE approach, applying reverse-transcription quantitative polymerase chain reaction and partial G-gene sequencing to track RSV levels and variants in the community. We report increasing detection of RSV in wastewater concomitant with increasing numbers of positive clinical cases. Analysis of wastewater-derived RSV sequences permitted identification of distinct circulating lineages within and between seasons. Altogether, our genomic WBE platform has the potential to complement ongoing global surveillance and aid the management of RSV by informing the timely deployment of pharmaceutical and nonpharmaceutical interventions.