Abstract
Understanding the distribution of respiratory syncytial virus (RSV) disease burden by more granular age bands in infants is necessary for optimising infant RSV immunisation strategies. Using a Bayesian model, we synthesised published data from a systematic literature review and unpublished data shared by international collaborators for estimating the distribution of infant RSV hospitalisations by month of age. Based on local RSV seasonality data, we further developed and validated a web-based prediction tool for estimating infant RSV hospitalisation distribution by birth month. Although RSV hospitalisation burden mostly peaked at the second month of life and was concentrated in infants under six months globally, substantial variations were noted in the age distribution of RSV hospitalisation among infants born in different months. Passive immunisation strategies should ideally be tailored to the local RSV disease burden distribution by age and birth month to maximise their per-dose effectiveness before a universal immunisation can be achieved.