Using COVID-19 pandemic perturbation to model RSV-hMPV interactions and potential implications under RSV interventions

Emily Howerton (), Thomas C. Williams, Jean-Sébastien Casalegno, Samuel Dominguez, Rory Gunson, Kevin Messacar, C. Jessica E. Metcalf, Sang Woo Park, Cécile Viboud and Bryan T. Grenfell
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Emily Howerton: Princeton University
Thomas C. Williams: University of Edinburgh
Jean-Sébastien Casalegno: Laboratoire de Virologie
Samuel Dominguez: University of Colorado School of Medicine and Children’s Hospital Colorado
Rory Gunson: NHS Greater Glasgow and Clyde
Kevin Messacar: University of Colorado School of Medicine and Children’s Hospital Colorado
C. Jessica E. Metcalf: Princeton University
Sang Woo Park: Princeton University
Cécile Viboud: National Institutes of Health
Bryan T. Grenfell: Princeton University

Nature Communications, 2025, vol. 16, issue 1, 1-12

Abstract: Abstract Respiratory syncytial virus (RSV) and human metapneumovirus (hMPV) are closely related pathogens responsible for a significant burden of acute respiratory infections. Interactions between RSV and hMPV have been hypothesized, but the mechanisms of interaction are largely unknown. Here, we use a mathematical model to quantify the likelihood of interactions from population-level surveillance data and investigate whether interactions could lead to increases in hMPV burden under RSV medical interventions, including active and passive immunization. In Scotland, Korea, and three regions of Canada, annual hMPV outbreaks lag RSV outbreaks by up to 18 weeks; two Canadian regions show patterns consistent with out-of-phase biennial outbreaks. Using a two-pathogen transmission model, we show that a negative effect of RSV infection on hMPV transmissibility can explain these dynamics. We use post-pandemic RSV-hMPV rebound dynamics as an out of sample test for our model, and the model with interactions better predicts this period than a model where the pathogens are assumed to be independent. Finally, our model suggests that hMPV peak timing and magnitude may change under RSV interventions. Our analysis provides a foundation for detecting possible RSV-hMPV interactions at the population level, although such a model oversimplifies important complexities about interaction mechanisms.

Date: 2025
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DOI: 10.1038/s41467-025-62358-w

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