Modelling the impact of long-acting monoclonal antibody, maternal vaccine and hybrid programs of RSV immunisation in temperate Western Australia

BackgroundTwo RSV immunisations products: a maternal vaccine, Abrysvo, and a long-acting monoclonal antibody, nirsevimab, both designed to prevent RSV illness in infants, have recently become available. Modelling evidence is required to inform how to optimally use these products in immunisation programs to reduce the burden of RSV in young children. MethodsWe extend a dynamic transmission model calibrated to RSV-hospitalisation data of children aged < 5 years in temperate Western Australia (WA) to simulate a range of potential RSV immunisation programs. Using our model, we estimate the impact of both single-product and hybrid RSV immunisation programs. The analysis considers timing of administration, coverage levels and targeting of high-risk groups. Impact on RSV burden is analysed in the context of the WA setting and the possible significant cost differences between the two products. ResultsAll programs analysed were effective in reducing RSV burden. Programs using nirsevimab for newborn infants at similar coverage levels to the Abrysvo programs, averted more RSV-hospitalisations annually. Seasonal programs that focused on protection during high RSV activity and programs targeting high-risk infants were the most efficient in reducing RSV burden. When dose cost is considered alongside program impact on RSV burden, we find evidence to support further economic analysis of hybrid programs as they could mitigate the cost differential between the two products while remaining highly effective in reducing RSV burden. ConclusionsOur study is the first to comprehensively analyse hybrid RSV immunisation programs that use Abrysvo and nirsevimab. RSV immunisation programs can substantially reduce the burden of RSV in young children. Our modelling analysis provides evidence on immunisation type, timing, coverage, high-risk groups and dosage cost that will support decision makers and can be used in economic evaluations.