Bayesian Estimation of Child Mortality

• Activity Number: 298
• Type: Topic Contributed
• Date/Time: Tuesday, August 6, 2013 : 8:30 AM to 10:20 AM
• Sponsor: Social Statistics Section
• Author(s): Leontine Alkema*+ and Jin Rou New
• Companies: National University of Singapore and National University of Singapore
• Keywords: Bayesian inference ; B-splines regression ; Model validation ; Multi-level modeling ; Under-5 mortality rate (U5MR) ; United Nations Interagency Group on Child Mortality Estimation (UN-IGME)

Abstract

National estimates of the under-5 mortality rate (U5MR) are used to track progress in reducing child mortality and to evaluate countries' performance related to Millennium Development Goal 4, which calls for a reduction in the U5MR by two-thirds between 1990 and 2015. However, 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. Global U5MR estimates are often constructed without accounting for potential biases in data series which may lead to inaccurate point estimates and/or uncertainty intervals. We describe a Bayesian B-splines regression model for assessing levels and trends in the U5MR, whereby biases in data series are estimated for each source type through the inclusion of a multilevel model to improve upon the drawbacks of current methods. The proposed model is able to flexibly capture changes in U5MR over time, gives point estimates and uncertainty intervals that reflect potential biases in data series and performs well in out-of-sample validation exercises.