Estimating levels and trends in under-5 mortality: an assessment of biases in data series and an improved estimation method

The under-5 mortality rate (U5MR) is an important measure of the well-being of a country’s children, and its estimation is particularly critical as we approach the deadline of Millennium Development Goal 4 to reduce 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 under-5 mortality is challenging, not only because of limited data availability but also because of issues with data quality. Global estimates of child mortality are often constructed without accounting for potential biases in data series which may lead to inaccurate point estimates and/or uncertainty intervals. We propose a Bayesian spline 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. Preliminary results show that the proposed model is able to flexibly capture changes in U5MR over time and gives point estimates and uncertainty intervals that reflect potential biases in data series.