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Estimating under-five mortality in space and time in a developing world context.

Jon Wakefield1,2, Geir-Arne Fuglstad3, Andrea Riebler3

  • 11 Department of Statistics, University of Washington, Seattle, USA.

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|April 20, 2018
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Summary
This summary is machine-generated.

A new Bayesian model accurately estimates under-five mortality rates in developing countries. The model, applied to Kenya, shows a significant decline but highlights persistent regional disparities needing further investigation.

Keywords:
Complex surveysspace–time smoothingstratified cluster samplingunder-five mortality rates

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Area of Science:

  • * Demography
  • * Public Health
  • * Biostatistics

Background:

  • * Under-five mortality rate (U5MR) is a critical indicator of national health status, especially in developing nations.
  • * Existing models may not fully capture spatial and temporal dynamics or account for complex survey designs.

Purpose of the Study:

  • * To develop and apply a novel Bayesian hierarchical model for analyzing under-five mortality survey data.
  • * To estimate U5MR spatially and temporally across subnational regions in Kenya.
  • * To investigate associations between U5MR and spatially varying covariates, adjusting for factors like HIV prevalence.

Main Methods:

  • * Utilized a binomial likelihood with fixed and random effects to accommodate complex survey designs (stratified cluster sampling).
  • * Employed Bayesian hierarchical models with continuous spatial and discrete temporal components for smoothing.
  • * Incorporated an offset term to adjust for potential bias introduced by HIV epidemics.

Main Results:

  • * Demonstrated a substantial reduction in under-five mortality rates in Kenya between 1980 and 2014.
  • * Revealed persistent and significant variability in estimated U5MR across subnational regions.
  • * Exploratory analysis indicated complex interactions between space, time, and covariates (e.g., temperature, malaria prevalence) in explaining U5MR variations.

Conclusions:

  • * The developed Bayesian model provides robust estimates of under-five mortality, accounting for complex survey data and epidemic effects.
  • * Despite overall declines, significant subnational disparities in U5MR persist in Kenya, warranting targeted public health interventions.
  • * Further research is needed to elucidate the complex interplay of spatial, temporal, and environmental factors influencing U5MR variability.