Modeling Spatial Effects on Childhood Mortality Via Geo-additive Bayesian Discrete-Time Survival Model: A Case Study from Nigeria

Gebrenegus Ghilagaber (), Diddy Antai and Ngianga-Bakwin Kandala ()
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Gebrenegus Ghilagaber: Stockholm University, Department of Statistics
Diddy Antai: Karolinska Institute, Department of Public Health Sciences
Ngianga-Bakwin Kandala: University of Warwick, Warwick Medical School, Division of Health Sciences

Chapter Chapter 3 in Advanced Techniques for Modelling Maternal and Child Health in Africa, 2014, pp 29-48 from Springer

Abstract: Abstract Childhood mortality is an important indicator of overall health and development in a country. It is the result of a complex interplay of determinants at many levels, and as such several studies have recognized that, for instance, maternal (Caldwell 1979; Cleland and van Ginneken 1988), socio-economic (Castro-Leal et al. 1999; Wagstaff 2001), and environmental (Wolfe and Behrman 1982; Lee et al. 1997) factors are important determinants of childhood mortality. However, only a few studies have incorporated environmental factors that are spatial in nature and derived from geographic databases, such as distances from households or communities (Watson et al. 1997).

Keywords: Childhood Mortality; Spatial Effect; Birth Interval; Deviance Information Criterion; Markov Chain Monte Carlo Simulation (search for similar items in EconPapers)
Date: 2014
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DOI: 10.1007/978-94-007-6778-2_3

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