Mapping 123 million neonatal, infant and child deaths between 2000 and 2017

Abstract

Since 2000, many countries have achieved considerable success in improving child survival, but localized progress remains unclear. To inform efforts towards United Nations Sustainable Development Goal 3.2-to end preventable child deaths by 2030-we need consistently estimated data at the subnational level regarding child mortality rates and trends. Here we quantified, for the period 2000-2017, the subnational variation in mortality rates and number of deaths of neonates, infants and children under 5 years of age within 99 low- and middle-income countries using a geostatistical survival model. We estimated that 32% of children under 5 in these countries lived in districts that had attained rates of 25 or fewer child deaths per 1,000 live births by 2017, and that 58% of child deaths between 2000 and 2017 in these countries could have been averted in the absence of geographical inequality. This study enables the identification of high-mortality clusters, patterns of progress and geographical inequalities to inform appropriate investments and implementations that will help to improve the health of all populations.

Fig. 1. U5MR estimates in 99 LMICs.

a, U5MR at the second administrative level in 2000. b, U5MR at the second administrative level in 2017. c, Modelled posterior exceedance probability that a given second administrative unit had achieved the SDG 3.2 target of 25 deaths per 1,000 live births for children under 5 in 2017. d, Proportion of mortality of children under 5 occurring in the neonatal (0–28 days) group at the second administrative level in 2017.

Fig. 2. Geographical inequality in U5MR across 99 countries for 2000 and 2017.

a, Absolute inequalities. Range of U5MR estimates in second administrative-level units across 99 LMICs. b, Relative inequalities. Range of ratios of U5MR estimates in second administrative-level units relative to country means. Each dot represents a second administrative-level unit. The lower bound of each bar represents the second administrative-level unit with the lowest U5MR in each country. The upper end of each bar represents the second administrative-level unit with the highest U5MR in each country. Thus, each bar represents the extent of geographical inequality in U5MRs estimated for each country. Bars indicating the range in 2017 are coloured according to their Global Burden of Disease super-region. Grey bars indicate the range in U5MR in 2000. The diamond in each bar represents the median U5MR estimated across second administrative-level units in each country and year. A coloured bar that is shorter than its grey counterpart indicates that geographical inequality has narrowed.

Fig. 3. Estimated number of children under 5 who died within 99 countries in 2017.

a, Number of deaths of children under 5 in each country. b, Number of deaths in each first administrative-level unit. c, Number of deaths in each second administrative-level unit. d, Number of deaths of children under 5 in each 5 × 5-km grid cell. Note that scales vary for each aggregation unit.

Fig. 4. Number of deaths of children under 5, distributed across level of U5MR, in 2000 and in 2017, across 99 countries.

Bar heights represent the total number of deaths of children under 5 within all second administrative-level units with corresponding U5MR. Bins are a width of 5 deaths per 1,000 live births. The colour of each bar represents the global region as defined by the subset legend map. As such, the sum of heights of all bars represents the total number of deaths across the 99 countries. a, Deaths of children under 5 in 2000. b, Deaths of children under 5 in 2017. The dotted line in the 2000 plot is the shape of the distribution in 2017, and the dotted line in the 2017 plot represents the distribution in 2000.

Extended Data Fig. 1. Neonatal and infant mortality rates in 2017.

a, b, Maps showing the mortality rates of neonates (a; birth to 28 days of age) and infants (b; under 1 year of age) across second administrative-level units in 2017. Note that the ranges in the keys are different for the two maps.

Extended Data Fig. 2. Impact of inequality on U5MR.

a, Potential reduction in the number of deaths that would have occurred if all second administrative-level units in the 20 countries with the greatest number of deaths of children under 5 in 2017 realized a homogenous U5MR that was equal to that of the lowest observed mortality rate in that country. In total, 66% of under-5 deaths could have been averted if all countries maintained mortality rates equal to the second administrative-level unit with lowest mortality. If this reference rate is set to the lowest observed rate across all of the 99 countries that were included in this study, 95% of under-5 deaths could have been averted. The size of each bar represents the total number of under-5 deaths in each country. The red portion of each bar indicates the number of deaths ‘attributed’ to geographical inequality in mortality rates, whereas the blue portion represents the number of deaths that would remain in the scenario in which all second administrative-level units within countries had the same mortality rate as the best-performing unit. b, Locations of under-5 deaths ‘attributable’ to geographical inequality, across all second administrative-level units in each country. Each country has one unit highlighted with a green diamond, which is the reference unit, or the location with the lowest mortality rate in the country in 2017.

Extended Data Fig. 3. Relative uncertainty in U5MR estimates for 2017.

Relative uncertainty in second administrative-level estimates compared with mean estimated U5MRs in each second administrative-level unit for 2017. Mean rates and relative uncertainty are split into population-weighted quartiles. These cut-off points indicate the relative uncertainty minimum, 25th, 50th and 75th percentiles, and maximum, which are 0.29, 0.51, 0.63 and 0.86, and 3.12, respectively. The under-5 mortality minimum, 25th, 50th and 75th percentiles, and maximum are 1.4, 13.0, 22.9 and 44.8, and 190.6 deaths per 1,000 live births. Areas in which our estimates are more uncertain are coloured with a scale of increasing blue hue, whereas areas in which the mean estimates of U5MR are high are coloured with a scale of increasing red hue. Purple areas have high, but uncertain, estimates of U5MRs. White areas have low relative mortality, with fairly certain estimates. Relative uncertainty is defined as the ratio of the width of the 95% uncertainty interval to the mean estimate.

Extended Data Fig. 4. Lower and upper uncertainty interval boundaries for U5MR mortality estimates in 2017.

a, b, Lower (a) and upper (b) 95% uncertainty intervals for U5MR estimates across the second administrative-level units in 99 countries.

Extended Data Fig. 5. The counteracting forces of population change and mortality rate decline on total number of under-5 deaths.

Arrow plots show the mortality rate strata (bins of 10 per 1,000 livebirths) in 2000.

Extended Data Fig. 6. Flowchart summarizing analytical process.

Standard demographic notation were used. n, length of age bin; x, starting age of age bin; d, number of deaths; q, probability of death; a, average time lived in age bin by those who died in the age bin.