title: Progress toward global reduction in under-five mortality: a bootstrap analysis of uncertainty in Millennium Development Goal 4 estimates.
abstract: BACKGROUND
  Millennium Development Goal 4 calls for an annual rate of reduction (ARR) of the under-five mortality rate (U5MR) of 4.4% between 1990 and 2015. Progress is measured through the point estimates of the United Nations Inter-agency Group for Child Mortality Estimation (UN IGME). To facilitate evidence-based conclusions about progress toward the goal, we assessed the uncertainty in the estimates arising from sampling errors and biases in data series and the inferior quality of specific data series.
  
  
  RESULTS
  We implemented a bootstrap procedure to construct 90% uncertainty intervals (UIs) for the U5MR and ARR to complement the UN IGME estimates. We constructed the bounds for all countries without a generalized HIV epidemic, where a standard estimation approach is carried out (174 countries). In the bootstrap procedure, potential biases in levels and trends of data series of different source types were accounted for. There is considerable uncertainty about the U5MR, particularly for high mortality countries and in recent years. Among 86 countries with a U5MR of at least 40 deaths per 1,000 live births in 1990, the median width of the UI, relative to the U5MR level, was 19% for 1990 and 48% for 2011, with the increase in uncertainty due to more limited data availability. The median absolute width of the 90% UI for the ARR from 1990 to 2011 was 2.2%. Although the ARR point estimate for all high mortality countries was greater than zero, for eight of them uncertainty included the possibility of no improvement between 1990 and 2011. For 13 countries, it is deemed likely that the ARR from 1990 to 2011 exceeded 4.4%.
  
  
  CONCLUSIONS
  In light of the upcoming evaluation of Millennium Development Goal 4 in 2015, uncertainty assessments need to be taken into account to avoid unwarranted conclusions about countries' progress based on limited data.
authors.affiliation: Department of Statistics and Applied Probability, National University of Singapore, Singapore. alkema@nus.edu.sg
authors.forename: Leontine
authors.initials: L
authors.lastname: Alkema
authors.forename: Jin Rou
authors.initials: JR
authors.lastname: New
mesh_terms: D046688:Child Mortality / Q000639:trends*; D002675:Child, Preschool; D003627:Data Interpretation, Statistical; D014943:Global Health / Q000639:trends*; D006801:Humans; D007223:Infant; D007226:Infant Mortality / Q000639:trends*; D007231:Infant, Newborn; D009937:Organizational Objectives; D035501:Uncertainty; D014944:World Health Organization