Genomic Analysis and Surveillance of Respiratory Syncytial Virus Using Wastewater-Based Epidemiology

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.

Keywords: RSV; genome; respiratory syncytial virus; surveillance; wastewater.

Figure 1.

A, Averaged respiratory syncytial virus (RSV) RNA concentrations—in gene copies (gc) per 100 000 population equivalents (pe) per day—across 20 wastewater treatment works (WWTWs) in Northern Ireland (NI; black circles) and smoothed data based on fitting a B spline model (black line) from August 2021 to February 2023 (n = 83 weeks). Histogram showing the number of RSV-positive cases for NI during the same period. B, Heat map showing the distribution of RSV RNA concentrations in wastewater samples (n = 587) across the 20 WWTWs in NI between August 2021 and February 2023. White boxes indicate no detection of RSV RNA gene copies at the WWTW.

Figure 2.

Maximum likelihood phylogenetic trees of generated Northern Ireland (NI) respiratory syncytial virus (RSV) A (A) and B (B) based on G-gene sequences alongside contemporary sequences (available through GISAID), with 1000 bootstrap replicates using IQ-TREE software. The whole phylogeny is shown on the left, with sequences generated in this study highlighted alongside focused clades containing NI sequences (inset). In the inset, taxa are labeled with date and geographic origin metadata for all derived NI sequences and for certain global sequences. For clarity, only bootstraps >70 are shown.

Figure 3.

Encoded amino acid sequences for respiratory syncytial virus (RSV) A (A) and RSV B (B) samples from this study and other relevant non–Northern Ireland sequences within our clusters were visualized using Jalview software. Amino acid sequences were separated into groups based on the clades from the phylogenetic analysis. Mutations shown in reference to the consensus of all sequences [33]. Amino acids the same as consensus were highlighted with a dot. Stop codons were shown (asterisks). Mutations of interest were shaded in red, and N-linked glycosylation site in green.

Figure 4.

The geospatial detection of the respiratory syncytial virus (RSV) A and B lineages across 2021 and 2022 seasons in Northern Ireland (NI), divided into 6 counties (Antrim, Armagh, Fermanagh, Tyrone, Londonderry, and Down). RSV A and B lineages are shown as circles or squares, and the different RSV A and B lineages (A1.1, A1.2, A2, A3, B1, B2, B3.1, and B3.2) are shown in different colors and shades.