Interactions between influenza and respiratory syncytial viruses: two-pathogen modelling to analyse multiplex data
- 1Institut Pasteur
Abstract
BackgroundInfluenza and respiratory syncytial virus (RSV) both cause annual peaks in hospitalisation and with considerable overlap. Epidemiological studies suggest an inhibitory relationship, which is supported by laboratory studies. Several biological mechanisms including resource competition and immune activation have been identified, but limited evidence exists to distinguish their effects at the population level.
MethodsWe developed an influenza-RSV compartmental model to estimate and compare potential interactions using data on virus-associated hospitalisations in Valencia, Spain from 2010 through 2020. We considered five interaction mechanisms: altered susceptibility, transmissibility and severity, a refractory period post-infection, and a residual positivity period. Using Bayesian inference, we fit the model to weekly hospitalisations with influenza, RSV or both, and to national surveillance data for influenza-like illness.
ResultsWe found evidence for inhibition between influenza and RSV, with several interaction mechanisms being supported. In the best-fitting model, active RSV infection reduced the probability of hospitalisation with influenza to 20% of the baseline (with the data supporting values from 0%-60%). Compared to a model without interaction, this mechanism reduced the number of hospital cases with influenza-RSV co-detection by 63%.
ConclusionsOur results support the existence of inhibitory mechanisms, with small but substantial effects on disease epidemiology. These results highlight the importance of understanding these interactions under the changing epidemiology of respiratory viruses and vaccinations.
SummaryWe identified potential mechanisms of within-host interaction between influenza and respiratory syncytial virus (RSV) using two-pathogen models and a 10-year active surveillance cohort. In the best supported model, active RSV infection reduced the hospitalisation probability of influenza infection.
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BibTeX
@misc{shirreff2026interactions,
title = {{Interactions between influenza and respiratory syncytial viruses: two-pathogen modelling to analyse multiplex data}},
author = {G. Shirreff and S. S. Chaves and L. Coudeville and B. Mengual-Chulia and A. Mira-Iglesias and J. Puig-Barbera and A. Orrico-Sanchez and J. Diez-Domingo and Valencia Hospital Surveillance Network for the Study of Influenza and Other Respiratory Viruses and L. Opatowski and F. X. Lopez-Labrador},
howpublished = {medRxiv},
year = {2026},
month = sep,
doi = {10.64898/2026.09.03.26362151},
url = {https://www.medrxiv.org/content/10.64898/2026.09.03.26362151v1},
note = {CC BY-ND},
}
RIS
TY - UNPB
TI - Interactions between influenza and respiratory syncytial viruses: two-pathogen modelling to analyse multiplex data
AU - G. Shirreff
AU - S. S. Chaves
AU - L. Coudeville
AU - B. Mengual-Chulia
AU - A. Mira-Iglesias
AU - J. Puig-Barbera
AU - A. Orrico-Sanchez
AU - J. Diez-Domingo
AU - Valencia Hospital Surveillance Network for the Study of Influenza and Other Respiratory Viruses
AU - L. Opatowski
AU - F. X. Lopez-Labrador
PY - 2026
DA - 2026/09/03
PB - medRxiv
DO - 10.64898/2026.09.03.26362151
UR - https://www.medrxiv.org/content/10.64898/2026.09.03.26362151v1
AB - BackgroundInfluenza and respiratory syncytial virus (RSV) both cause annual peaks in hospitalisation and with considerable overlap. Epidemiological studies suggest an inhibitory relationship, which is supported by laboratory studies. Several biological mechanisms including resource competition and immune activation have been identified, but limited evidence exists to distinguish their effects at the population level. MethodsWe developed an influenza-RSV compartmental model to estimate and compare potential interactions using data on virus-associated hospitalisations in Valencia, Spain from 2010 through 2020. We considered five interaction mechanisms: altered susceptibility, transmissibility and severity, a refractory period post-infection, and a residual positivity period. Using Bayesian inference, we fit the model to weekly hospitalisations with influenza, RSV or both, and to national surveillance data for influenza-like illness. ResultsWe found evidence for inhibition between influenza and RSV, with several interaction mechanisms being supported. In the best-fitting model, active RSV infection reduced the probability of hospitalisation with influenza to 20% of the baseline (with the data supporting values from 0%-60%). Compared to a model without interaction, this mechanism reduced the number of hospital cases with influenza-RSV co-detection by 63%. ConclusionsOur results support the existence of inhibitory mechanisms, with small but substantial effects on disease epidemiology. These results highlight the importance of understanding these interactions under the changing epidemiology of respiratory viruses and vaccinations. SummaryWe identified potential mechanisms of within-host interaction between influenza and respiratory syncytial virus (RSV) using two-pathogen models and a 10-year active surveillance cohort. In the best supported model, active RSV infection reduced the hospitalisation probability of influenza infection.
ER -