Bayesian spatiotemporal modelling of neonatal, infant and under-5 mortality (2000–2022) in 41 Asian countries: a population-level observational study

BACKGROUND: Child mortality continues to pose a major public health challenge across Asia. This study examines trends in under-5, infant and neonatal mortality and identifies key determinants, spatial risk patterns and projections through 2030 using spatiotemporal modelling. METHODS: We used national-level data from 41 Asian countries, representing over 80% of Asia's population, between 2000 and 2022, incorporating 26 health, environmental and sociodemographic indicators. A hierarchical Bayesian model using Integrated Nested Laplace Approximation, incorporating fixed effects, spatially structured and unstructured random effects, and temporal smoothing, was used. Model performance was assessed via the Deviance Information Criterion, Watanabe-Akaike Information Criterion, coefficient of determination (R²), root mean squared error (RMSE) and mean absolute error metrics. RESULTS: Under-5 mortality decreased significantly (p