Progress toward Global Reduction in Under-Five Mortality: A Bootstrap Analysis of Uncertainty in Millennium Development Goal 4 Estimates

Leontine Alkema and colleagues use a bootstrap procedure to assess the uncertainty around the estimates of the under-five mortality rate produced by the United Nations Inter-Agency Group for Child Mortality Estimation. 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. Methods and Findings: 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. Background: In September 2000, world leaders adopted the United Nations Millennium Declaration, committing member states (countries) to a new global partnership to reduce extreme poverty and improve global health by setting out a series of time-bound targets with a deadline of 2015—the Millennium Development Goals (MDGs). There are eight MDGs and the fourth, MDG 4, focuses on reducing the number of deaths in children aged under five years by two-thirds from the 1990 level. Monitoring progress towards meeting all of the MDG targets is of vital importance to measure the effectiveness of interventions and to prioritize slow progress areas. MDG 4 has three specific indicators, and every year, the United Nations Inter-agency Group for Child Mortality Estimation (the UN IGME, which includes the key agencies the United Nations Children's Fund, the World Health Organization, the World Bank, and the United Nations Population Division) produces and publishes estimates of child death rates for all countries. Why Was This Study Done?: Many poorer countries do not have the infrastructure and the functioning vital registration systems in place to record the number of child deaths. Therefore, it is difficult to accurately assess levels and trends in the rate of child deaths because there is limited information (data) or because the data that exists may be inaccurate or of poor quality. In order to deal with this situation, analyzing trends in under-five child death rates (to show progress towards MDG 4) currently focuses on the “best” estimates from countries, a process that relies on “point” estimates. But this practice can lead to inaccurate results and comparisons. It is therefore important to identify a framework for calculating the uncertainty surrounding these estimates. In this study, the researchers use a statistical method to calculate plausible uncertainty intervals for the estimates of death rates in children aged under five years and the yearly reduction in those rates. What Did the Researchers Do and Find?: The researchers used the publicly available information from the UN IGME 2012 database, which collates data from a variety of sources, and a statistical method called bootstrapping to construct uncertainty levels for 174 countries out of 195 countries for which the UN IGME published estimates in 2012. This new method improves current practice for estimating the extent of data errors, as it takes into account the structure and (potentially poor) quality of the data. The researchers used 90% as the uncertainty level and categorized countries according to the likelihood of meeting the MDG 4 target. What Do These Findings Mean?: These findings suggest that new uncertainty assessments constructed by a statistical method called bootstrapping can provide more insights into countries' progress in reducing child mortality and meeting the MDG 4 target. As demonstrated in this study, when data are limited, uncertainty intervals should to be taken into account when estimating progress towards MDG 4 in order to give more accurate assessments on a country' progress, thus allowing for more realistic comparisons and conclusions. Additional Information: Please access these websites via the online version of this summary at http://dx.doi.org/10.1371/journal.pmed.1001355.