Speaker
Description
Respiratory syncytial virus (RSV) is one of the leading causes of hospitalisation for bronchiolitis and other lower respiratory tract infections in infants, representing a major cause of pressure on paediatric healthcare systems \cite{manzoni2025prevention}. Recent post-pandemic seasons, for instance in Italy, have highlighted how changes in respiratory virus circulation and heterogeneous prevention policies can complicate planning based on surveillance alone. In this context, there is a clear need for mathematical tools that complement clinical and public health evidence by translating intervention assumptions into quantitative, population-level expectations and by enabling transparent comparisons across alternative implementation scenarios \cite{lang2022use}.
To this end, we develop a stage-structured compartmental model with three age classes to investigate RSV transmission, compare different prevention strategies and support public health decision-making aimed at reducing disease burden. The model explicitly incorporates infant immunoprophylaxis with long-acting monoclonal antibodies, consistent with current preventive practices, and includes vaccination of older adults. Scenario-based comparisons suggest that infant prophylaxis may reduce RSV infection incidence and affect the seasonal pattern of outbreaks. The proposed framework provides an analytical tool to inform coordinated RSV prevention policies in Italy.
Bibliography
Lang, John C. «Use of Mathematical Modelling to Assess Respiratory Syncytial Virus Epidemiology and Interventions: A Literature Review». Journal of Mathematical Biology, vol. 84, fasc. 4, marzo 2022, p. 26. DOI.org (Crossref), https://doi.org/10.1007/s00285-021-01706-y.
Manzoni, Paolo, et al. «Prevention of Respiratory Syncytial Virus Disease across the Lifespan in Italy». Pneumonia, vol. 17, fasc. 1, aprile 2025, p. 8. Springer Link, https://doi.org/10.1186/s41479-025-00160-4.
