Model inputs and deterministic parameter values.

Poverty among expectant mothers often results in sub-optimal maternal nutrition and inadequate antenatal care, with negative consequences on child health outcomes. South Africa has a child support grant that is available from birth to those in need. This study aims to determine whether a pregnancy support grant, administered through the extension of the child support grant, would be cost-effective compared to the existing child support grant alone. A cost-utility analysis was performed using a decision-tree model to predict the incremental costs (ZAR) and disability-adjusted life years (DALYs) averted by the pregnancy support grant over a 2-year time horizon. An ingredients-based approach to costing was completed from a governmental perspective. The primary outcome was the incremental cost-effectiveness ratio (ICER). Deterministic and probabilistic sensitivity analyses were performed. The intervention resulted in a cost saving of R13.8 billion ($930 million, 95% CI: ZAR3.91 billion ‐ ZAR23.2 billion/ $1.57 billion ‐ $264 million) and averted 59,000 DALYs (95% CI: -6,400–110,000), indicating that the intervention is highly cost-effective. The primary cost driver was low birthweight requiring neonatal intensive care, with a disaggregated incremental cost of R31,800 ($2,149) per pregnancy. Mortality contributed most significantly to the DALYs accrued in the comparator (0.68 DALYs). The intervention remained the dominant strategy in the sensitivity analyses. The pregnancy support grant is a highly cost-effective solution for supporting expecting mothers and ensuring healthy pregnancies. With its positive impact on child health outcomes, there is a clear imperative for government to implement this grant. By investing in this program, cost savings could be leveraged. The implementation of this grant should be given high priority in public health and social policies.