A new article published in Philosophical Transactions of the Royal Society A presents statistical methods designed to improve the estimation and projection of maternal and child health indicators in low- and middle-income countries. The study includes the participation of ICEH researcher Leonardo Ferreira.

In settings where health data vary in quality and availability, statistical models provide valuable alternatives for estimating and forecasting the coverage of essential health interventions. The study contributes to global health monitoring efforts based on large household surveys such as DHS and MICS. The researchers developed and evaluated Bayesian models capable of combining multiple data sources to produce more reliable estimates and short-term projections for indicators such as antenatal care coverage and childhood vaccination.

The proposed approach allows models to capture long-term historical trends while smoothing atypical observations. The models can also incorporate routine health service data to identify recent patterns, signaling whether coverage is improving, stagnating, or declining, without relying directly on the estimates derived from these records, which are often less precise.

In addition to presenting the modeling framework, the article's key innovation is a structured and accessible validation workflow designed to help analysts without specialized expertise in Bayesian statistics assess model performance across different contexts and indicators. The goal is to enable technical teams to identify systematic projection problems before results are used to guide policy planning and resource allocation.

The research involved collaborators from several leading international institutions and is part of the thematic issue Statistical Workflow, which brings together researchers to reveal the processes behind high-quality data analysis. Linked to the Countdown to 2030 initiative, the study helps strengthen the scientific community's capacity to generate robust estimates despite complex and contemporary challenges, including reductions in international health funding.

The full article is available here.