Global Estimation of Child Mortality Using a Bayesian B-Spline Bias-Reduction Method

Leontine Alkema, National University of Singapore
Jin Rou New, National University of Singapore

For the great majority of developing countries without well-functioning vital registration systems, estimating levels and trends in child mortality is challenging, not only because of limited data availability but also because of issues with data quality. We developed a Bayesian penalized B-spline regression model for assessing levels and trends in the under-five mortality rate (U5MR) for all countries in the world, whereby biases in data series are estimated through the inclusion of a multilevel model. This model was recently accepted by the United Nations Inter-agency Group for Child Mortality Estimation to measure countries' progress in reducing U5MR. In this paper, we present the model and the resulting estimates of the U5MR for selected countries.

  See extended abstract

Presented in Poster Session 3: Health of Women, Children, and Families