Modeling spatial effects on childhood mortality via geo-additive Bayesian discrete-time survival model: a case study from Nigeria

Gebrenegus Ghilagaber, Stockholm University
Diddy Antai, Karolinska Institutet

We introduce a spatial dimension in modelling under-five mortality among Nigerian children using data from Nigeria Demographic and Health Survey of 2003. We achieve this by employing a geo-additive Bayesian model with dynamic and spatial extensions of discrete-time survival models in assessing temporal and spatial variation in the covariates to childhood mortality. The results show that district-level socioeconomic characteristics are important determinants of childhood mortality. More importantly, a separate spatial process produces district clustering of childhood mortality indicating the importance of spatial effects. The visual nature of the maps presented in this paper highlights relationships that would, otherwise, be overlooked in standard methods.

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Presented in Session 68: Understanding health and population dynamics through longitudinal demographic surveillance systems