Hodgson, David; Koltai, Mihaly; Krauer, Fabienne; Flasche, Stefan; Jit, Mark; Atkins, Katherine E; (2022) Optimal Respiratory Syncytial Virus intervention programmes using Nirsevimab in England and Wales. Vaccine, 40 (49). pp. 7151-7157. ISSN 0264-410X DOI: https://doi.org/10.1016/j.vaccine.2022.10.041
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Abstract
INTRODUCTION: Respiratory Syncytial Virus (RSV) is a major cause of acute lower respiratory tract infections (ALRI) in infants. There are no licensed vaccines and only one monoclonal antibody available to protect infants from disease. A new and potentially longer-lasting monoclonal antibody, Nirsevimab, showed promising results in phase IIb/III trials. We evaluate the cost-effectiveness of Nirsevimab intervention programmes in England and Wales. METHODS: We used a dynamic model for RSV transmission, calibrated to data from England and Wales. We considered a suite of potential Nirsevimab programmes, including administration to all neonates (year-round); only neonates born during the RSV season (seasonal); or neonates born during the RSV season plus infants less than six months old before the start of the RSV season (seasonal + catch-up). RESULTS: If administered seasonally to all infants at birth, we found that Nirsevimab would have to be priced at £63 or less per dose for at least 50% certainty that it could cost-effectively replace the current Palivizumab programme, using an ICER threshold of £20,000/QALY. An extended seasonal programme which includes a pre-season catch-up becomes the optimal strategy at a purchasing price of £32/dose or less for at least 50% certainty. At a purchasing price per dose of £5-32, the annual implementation costs of a seasonal programme could be as high as £2 million before a switch to a year-round strategy would be optimal. DISCUSSION: Nirsevimab has the potential to be cost-effective in England and Wales not only for use in high-risk infants.
Item Type | Article |
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Faculty and Department |
Faculty of Epidemiology and Population Health > Dept of Infectious Disease Epidemiology & Dynamics (2023-) Faculty of Epidemiology and Population Health > Dept of Infectious Disease Epidemiology (-2023) |
Research Centre |
?? 181801 ?? Centre for the Mathematical Modelling of Infectious Diseases |
PubMed ID | 36328884 |
Elements ID | 196165 |
Official URL | http://dx.doi.org/10.1016/j.vaccine.2022.10.041 |
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