Age distribution, trends, and forecasts of under-5 mortality in 31 sub-Saharan African countries: A modeling study

Background Despite the sharp decline in global under-5 deaths since 1990, uneven progress has been achieved across and within countries. In sub-Saharan Africa (SSA), the Millennium Development Goals (MDGs) for child mortality were met only by a few countries. Valid concerns exist as to whether the region would meet new Sustainable Development Goals (SDGs) for under-5 mortality. We therefore examine further sources of variation by assessing age patterns, trends, and forecasts of mortality rates. Methods and findings Data came from 106 nationally representative Demographic and Health Surveys (DHSs) with full birth histories from 31 SSA countries from 1990 to 2017 (a total of 524 country-years of data). We assessed the distribution of age at death through the following new demographic analyses. First, we used a direct method and full birth histories to estimate under-5 mortality rates (U5MRs) on a monthly basis. Second, we smoothed raw estimates of death rates by age and time by using a two-dimensional P-Spline approach. Third, a variant of the Lee–Carter (LC) model, designed for populations with limited data, was used to fit and forecast age profiles of mortality. We used mortality estimates from the United Nations Inter-agency Group for Child Mortality Estimation (UN IGME) to adjust, validate, and minimize the risk of bias in survival, truncation, and recall in mortality estimation. Our mortality model revealed substantive declines of death rates at every age in most countries but with notable differences in the age patterns over time. U5MRs declined from 3.3% (annual rate of reduction [ARR] 0.1%) in Lesotho to 76.4% (ARR 5.2%) in Malawi, and the pace of decline was faster on average (ARR 3.2%) than that observed for infant (IMRs) (ARR 2.7%) and neonatal (NMRs) (ARR 2.0%) mortality rates. We predict that 5 countries (Kenya, Rwanda, Senegal, Tanzania, and Uganda) are on track to achieve the under-5 sustainable development target by 2030 (25 deaths per 1,000 live births), but only Rwanda and Tanzania would meet both the neonatal (12 deaths per 1,000 live births) and under-5 targets simultaneously. Our predicted NMRs and U5MRs were in line with those estimated by the UN IGME by 2030 and 2050 (they overlapped in 27/31 countries for NMRs and 22 for U5MRs) and by the Institute for Health Metrics and Evaluation (IHME) by 2030 (26/31 and 23/31, respectively). This study has a number of limitations, including poor data quality issues that reflected bias in the report of births and deaths, preventing reliable estimates and predictions from a few countries. Conclusions To our knowledge, this study is the first to combine full birth histories and mortality estimates from external reliable sources to model age patterns of under-5 mortality across time in SSA. We demonstrate that countries with a rapid pace of mortality reduction (ARR ≥ 3.2%) across ages would be more likely to achieve the SDG mortality targets. However, the lower pace of neonatal mortality reduction would prevent most countries from achieving those targets: 2 countries would reach them by 2030, 13 between 2030 and 2050, and 13 after 2050.
Iván Mejía-Guevara and colleagues predict neonatal and under-5 mortality in sub-Sahara Africa by 2030, with most countries missing Millennium Development Goals for child mortality
Author summary Why was this study done? Under-5 mortality remains high in sub-Saharan Africa (SSA), and it is declining unevenly across countries and age groups. Only a few countries in SSA met the Millennium Development Goals (MDGs) for child mortality reduction. A new analysis that explores sources of variation is needed to address concerns on whether the region would be able to reach the Sustainable Development Goals (SDGs). What did the researchers do and find? Using data from full birth histories, we developed a new demographic model to assess age patterns of mortality, fit mortality profiles across age and time, and forecast under-5 mortality. We found marked differences in mortality profiles by age and levels across countries over time. The average annual rate of reduction (ARR) for under-5 mortality rates (U5MRs) between 1990 and 2017 was 3.2%, but it varied from 0.1% in Lesotho to 5.2% in Malawi. Based on our prediction model, we assessed the achievability of SDGs mortality targets by 2030 (2050 when possible) for 31 SSA countries. Countries with a rapid pace of mortality decline would be more likely to meet the sustainable mortality goals (e.g., Rwanda and Tanzania), as opposed to those with a slower pace (e.g., Chad and Nigeria). However, the slow pace in neonatal mortality would prevent most countries from reaching the SDGs by 2030, even countries like Ethiopia that have met the MDGs before the 2015 deadline. What do these findings mean? Our analytical approach aims to provide insights for the assessment of sustainable targets of child mortality and to identify the range of epidemiological situations and trajectories. The acceleration of neonatal mortality decline is key to advancing the agenda for sustainable development and should be considered in future programmatic assessments.