Cost-effectiveness of pharmaceutical strategies to prevent respiratory syncytial virus disease in young children: a decision-support model for use in low-income and middle-income countries.

Abstract

Respiratory syncytial virus (RSV) is a leading cause of respiratory disease in young children. A number of mathematical models have been used to assess the cost-effectiveness of RSV prevention strategies, but these have not been designed for ease of use by multidisciplinary teams working in low-income and middle-income countries (LMICs). We describe the UNIVAC decision-support model (a proportionate outcomes static cohort model) and its approach to exploring the potential cost-effectiveness of two RSV prevention strategies: a single-dose maternal vaccine and a single-dose long-lasting monoclonal antibody (mAb) for infants. We identified model input parameters for 133 LMICs using evidence from the literature and selected national datasets. We calculated the potential cost-effectiveness of each RSV prevention strategy (compared to nothing and to each other) over the lifetimes of all children born in the year 2025 and compared our results to a separate model published by PATH. We ran sensitivity and scenario analyses to identify the inputs with the largest influence on the cost-effectiveness results. Our illustrative results assuming base case input assumptions for maternal vaccination ($3.50 per dose, 69% efficacy, 6 months protection) and infant mAb ($3.50 per dose, 77% efficacy, 5 months protection) showed that both interventions were cost-saving compared to status quo in around one-third of 133 LMICs, and had a cost per DALY averted below 0.5 times the national GDP per capita in the remaining LMICs. UNIVAC generated similar results to a separate model published by PATH. Cost-effectiveness results were most sensitive to changes in the price, efficacy and duration of protection of each strategy, and the rate (and cost) of RSV hospital admissions. Forthcoming RSV interventions (maternal vaccines and infant mAbs) are worth serious consideration in LMICs, but there is a good deal of uncertainty around several influential inputs, including intervention price, efficacy, and duration of protection. The UNIVAC decision-support model provides a framework for country teams to build consensus on data inputs, explore scenarios, and strengthen the local ownership and policy-relevance of results.