Wastewater-based surveillance of Respiratory Syncytial Virus reveals a temporal disconnect in disease trajectory across an active internatio

Mackenzie Beach, Great Lakes Institute for Environmental Research, University of Windsor, Windsor, ON, N9C 4G3, Canada
Ryland Corchis-Scott, Great Lakes Institute for Environmental Research, University of Windsor, Windsor, ON, N9C 4G3, Canada
Qiudi Geng, Great Lakes Institute for Environmental Research, University of Windsor, Windsor, ON, N9C 4G3, Canada
Ana M. Podadera Gonzalez, Department of Chemistry and Biochemistry, University of Windsor, Windsor, ON N9B 3P4 Canada
Owen Corchis-Scott, Great Lakes Institute for Environmental Research, University of Windsor, Windsor, ON, N9C 4G3, Canada
Ethan Harrop, Great Lakes Institute for Environmental Research, University of Windsor, Windsor, ON, N9C 4G3, Canada
John Norton, Great Lakes Water Authority, Detroit, MI 48226 USA
Andrea Busch, Great Lakes Water Authority, Detroit, MI 48226 USA
Russell A. Faust, Oakland County Health Division, Oakland County, MI 48341 USA
Bridget Irwin, Windsor-Essex County Health Unit, Windsor, ON N9A 4J8 Canada
Mehdi Aloosh, Windsor-Essex County Health Unit, Windsor, ON N9A 4J8 Canada
Kenneth K.S. Ng, Department of Chemistry and Biochemistry, University of Windsor, Windsor, ON N9B 3P4 Canada
Robert M. McKay, Great Lakes Institute for Environmental Research, University of Windsor, Windsor, ON, N9C 4G3, Canada

Description

Conventional metrics for tracking infectious diseases, including case and outbreak data and syndromic surveillance can be resource-intensive, misleading, and comparatively slow with prolonged data collection, analysis and authentication. This study examined the 2022-2023 Respiratory Syncytial Virus (RSV) season in a contiguous metropolitan area connected by an active international land border, affording an opportunity for comparison of the respiratory virus season spanning two independent public health jurisdictions. Time-lagged cross correlation and qualitative examination of the wastewater signals showed that the peak of the Detroit (MI, USA) RSV season predated the peak in Windsor (ON, Canada) by approximately five weeks. A strong positive relationship was observed between RSV N-gene concentrations in wastewater and hospitalization rates in Windsor-Essex (Kendall’s τ = 0.539, p ≤ 0.001, Spearman’s ρ = 0.713, p ≤ 0.001) as well as Detroit (Kendall’s τ = 0.739, p ≤ 0.001, Spearman’s ρ = 0.888, p ≤ 0.001). This study demonstrated that wastewater surveillance can reveal regional differences in infection dynamics between communities and can provide an independent measure of the prevalence of RSV, an underreported disease. These findings support the use of wastewater surveillance as a cost-effective tool in monitoring of RSV to enhance existing surveillance systems and to better inform public health disease mitigation strategies.

 
Mar 22nd, 11:00 AM Mar 22nd, 5:30 PM

Wastewater-based surveillance of Respiratory Syncytial Virus reveals a temporal disconnect in disease trajectory across an active internatio

Conventional metrics for tracking infectious diseases, including case and outbreak data and syndromic surveillance can be resource-intensive, misleading, and comparatively slow with prolonged data collection, analysis and authentication. This study examined the 2022-2023 Respiratory Syncytial Virus (RSV) season in a contiguous metropolitan area connected by an active international land border, affording an opportunity for comparison of the respiratory virus season spanning two independent public health jurisdictions. Time-lagged cross correlation and qualitative examination of the wastewater signals showed that the peak of the Detroit (MI, USA) RSV season predated the peak in Windsor (ON, Canada) by approximately five weeks. A strong positive relationship was observed between RSV N-gene concentrations in wastewater and hospitalization rates in Windsor-Essex (Kendall’s τ = 0.539, p ≤ 0.001, Spearman’s ρ = 0.713, p ≤ 0.001) as well as Detroit (Kendall’s τ = 0.739, p ≤ 0.001, Spearman’s ρ = 0.888, p ≤ 0.001). This study demonstrated that wastewater surveillance can reveal regional differences in infection dynamics between communities and can provide an independent measure of the prevalence of RSV, an underreported disease. These findings support the use of wastewater surveillance as a cost-effective tool in monitoring of RSV to enhance existing surveillance systems and to better inform public health disease mitigation strategies.

https://scholar.uwindsor.ca/we-spark-conference/2025/postersessions/8