A coupled model to value indirect impacts of maternal, newborn and child health interventions
- 1Burnet Institute, Melbourne, Australia
- 2School of Public Health and Preventive Medicine, Monash University, Melbourne, Australia
Abstract
Outcomes associated with maternal, newborn and child health (MNCH) conditions have improved significantly over the past 20 years, however, they are not on track to meet the global SDG targets by 2030. Emerging interventions have the potential to greatly increase access to care, but estimating their impacts is difficult due to complicated interactions between interventions. Models exist to quantify outcomes and costs associated with scaling up interventions related to MNCH (e.g., The Lives saved tool (LiST)), but none have been designed to flexibly integrate novel interventions. This study aimed to develop a model that can estimate the impact of standard-of-care (SOC) and novel interventions on MNCH conditions, and present an example use case. We developed a compartment-based model with 15 interconnected population- and condition-specific modules for pregnant women (in different trimesters), newborns and children <5 years to quantify impacts of bespoke novel interventions. The model included modules for anemia, pre-eclampsia, obstructed labour, hemorrhage, maternal sepsis, preterm, small-for-gestation-age (SGA), respiratory distress syndrome (RDS), neonatal sepsis, birth asphyxia, wasting (neonates and children), stunting and modules that captures neonatal and childhood conditions not captured elsewhere in the model. The model captures dynamic interactions between MNCH conditions, including across trimesters, and accounts for the full impact of early detection and prevention of conditions during pregnancy. In an example use case, the model identified that scaling-up standard-of-care and novel diagnostic interventions for anemia and pre-eclampsia plus AI-ultrasound (for early detection of obstructed labour, hemorrhage and birth outcome risks, leading to facility referrals) to 60% could avert 207 million DALYs globally over 2024–2040. We have developed a modelling tool which can be flexibly adapted to assess the impacts of novel interventions for MNCH conditions, and can be applied at a global, regional, national or sub-national level.
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BibTeX
@article{walsh2026coupled,
title = {{A coupled model to value indirect impacts of maternal, newborn and child health interventions}},
author = {Tom Walsh and Joshua P. Vogel and Maureen Makama and Romesh Abeysuriya and Nick Scott},
journal = {PLOS Global Public Health},
year = {2026},
month = nov,
doi = {10.1371/journal.pgph.0005507},
url = {https://journals.plos.org/globalpublichealth/article?id=10.1371/journal.pgph.0005507},
note = {CC BY 4.0},
}
RIS
TY - JOUR
TI - A coupled model to value indirect impacts of maternal, newborn and child health interventions
AU - Tom Walsh
AU - Joshua P. Vogel
AU - Maureen Makama
AU - Romesh Abeysuriya
AU - Nick Scott
PY - 2026
DA - 2026/11/06
JO - PLOS Global Public Health
DO - 10.1371/journal.pgph.0005507
UR - https://journals.plos.org/globalpublichealth/article?id=10.1371/journal.pgph.0005507
AB - Outcomes associated with maternal, newborn and child health (MNCH) conditions have improved significantly over the past 20 years, however, they are not on track to meet the global SDG targets by 2030. Emerging interventions have the potential to greatly increase access to care, but estimating their impacts is difficult due to complicated interactions between interventions. Models exist to quantify outcomes and costs associated with scaling up interventions related to MNCH (e.g., The Lives saved tool (LiST)), but none have been designed to flexibly integrate novel interventions. This study aimed to develop a model that can estimate the impact of standard-of-care (SOC) and novel interventions on MNCH conditions, and present an example use case. We developed a compartment-based model with 15 interconnected population- and condition-specific modules for pregnant women (in different trimesters), newborns and children <5 years to quantify impacts of bespoke novel interventions. The model included modules for anemia, pre-eclampsia, obstructed labour, hemorrhage, maternal sepsis, preterm, small-for-gestation-age (SGA), respiratory distress syndrome (RDS), neonatal sepsis, birth asphyxia, wasting (neonates and children), stunting and modules that captures neonatal and childhood conditions not captured elsewhere in the model. The model captures dynamic interactions between MNCH conditions, including across trimesters, and accounts for the full impact of early detection and prevention of conditions during pregnancy. In an example use case, the model identified that scaling-up standard-of-care and novel diagnostic interventions for anemia and pre-eclampsia plus AI-ultrasound (for early detection of obstructed labour, hemorrhage and birth outcome risks, leading to facility referrals) to 60% could avert 207 million DALYs globally over 2024–2040. We have developed a modelling tool which can be flexibly adapted to assess the impacts of novel interventions for MNCH conditions, and can be applied at a global, regional, national or sub-national level.
SN - 2767-3375
ER -