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Cost-effectiveness of intrapartum azithromycin to prevent maternal infection, sepsis, or death in low-income and middle-income countries: a modelling analysis of data from a randomised, multicentre, placebo-controlled trial.

The Lancet. Global health2025-03-29PubMed
Total: 78.5Innovation: 7Impact: 9Rigor: 8Citation: 8

Summary

A probabilistic decision-analytic model using A-PLUS trial inputs suggests intrapartum azithromycin averts 1,592 maternal infection/sepsis/death events per 100,000 pregnancies and is typically cost-saving (mean net savings US$32,661), with 13.2 DALYs averted. Sensitivity analyses identified readmission cost, azithromycin price, and infection probability as key drivers.

Key Findings

  • Model projects 1,592 maternal infection/sepsis/death cases averted per 100,000 pregnancies (95% CI 1,139.7–2,024.1).
  • Estimated mean net savings of US$32,661 per 100,000 pregnancies and 13.2 DALYs averted.
  • Reductions in 248.5 facility readmissions, 866.8 unplanned clinic visits, and 1,816.2 antibiotic regimens per 100,000 pregnancies.

Clinical Implications

Health systems in LMICs can consider intrapartum azithromycin adoption as an economically efficient strategy, prioritizing sites with high maternal infection burden and optimizing procurement to maintain cost-saving.

Why It Matters

Provides robust economic evidence to inform national and global scale-up of maternal infection/sepsis prevention in LMICs, complementing clinical efficacy data.

Limitations

  • Model-based results depend on assumptions and site-specific cost inputs; external validity may vary
  • Antimicrobial resistance externalities and long-term population-level effects were not explicitly modeled

Future Directions

Country-specific budget impact analyses, integration with antimicrobial resistance surveillance, and operational research on delivery at scale.

Study Information

Study Type
Cohort
Research Domain
Prevention
Evidence Level
II - Economic modeling using randomized trial inputs; not a randomized comparison of economic outcomes
Study Design
OTHER