ArticlePLOS global public health2024
A cost-effectiveness analysis of a South African pregnancy support grant.
Article in PLOS global public health, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
5 citing papers in PubMed, 4 citations in OpenAlex.
- A Targeted Review of Available Data Sources to Support Evidence-Informed Decisions: Implications for Health Technology Assessment in South Africa.PharmacoEconomics - open · 2026Review
- Cost-effectiveness and cost-utility of antenatal sexually transmitted infection screening to reduce preterm birth and low birthweight in South Africa.medRxiv : the preprint server for health sciences · 2026Article
- Money, Medicine, and Motherhood: Developing a Cash Transfer for Pregnant Women with HIV in Rural Haiti.AIDS and behavior · 2026Article
- The Effectiveness of an Artificial Intelligence-Based Gamified Intervention for Improving Maternal Health Outcomes Among Refugees and Underserved Women in Lebanon: Community Interventional Trial.JMIR mHealth and uHealth · 2025Article
- Economic Evaluation of Free Prevention of Mother-to-Child Transmissions (PMTCT) Services to Non-South African Women Living in South Africa.Health services insights · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors at 1 institution in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
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.
Identifiers
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.