Mortality rate, under-5, female (per 1,000 live births) - Country Ranking - Africa

Definition: Under-five mortality rate, female is the probability per 1,000 that a newborn female baby will die before reaching age five, if subject to female age-specific mortality rates of the specified year.

Source: Estimates Developed by the UN Inter-agency Group for Child Mortality Estimation (UNICEF, WHO, World Bank, UN DESA Population Division) at www.childmortality.org.

See also: Thematic map, Time series comparison

Find indicator:
Rank Country Value Year
1 Somalia 125.80 2016
2 Chad 120.60 2016
3 Central African Republic 116.90 2016
4 Sierra Leone 106.30 2016
5 Mali 105.40 2016
6 Nigeria 98.10 2016
7 Benin 92.90 2016
8 Dem. Rep. Congo 87.40 2016
9 Niger 87.30 2016
10 Lesotho 86.10 2016
11 Equatorial Guinea 84.30 2016
12 Guinea 83.70 2016
13 Côte d'Ivoire 82.20 2016
14 Guinea-Bissau 80.20 2016
15 Burkina Faso 80.10 2016
16 Angola 76.40 2016
17 Mauritania 74.30 2016
18 Cameroon 74.20 2016
19 Togo 69.50 2016
20 Comoros 67.70 2016
21 Mozambique 66.70 2016
22 Burundi 65.90 2016
23 Swaziland 65.00 2016
24 Liberia 62.20 2016
25 The Gambia 60.70 2016
26 Sudan 59.60 2016
27 Zambia 58.40 2016
28 Djibouti 58.20 2016
29 Ghana 53.40 2016
30 Ethiopia 52.90 2016
30 Tanzania 52.90 2016
32 Zimbabwe 51.20 2016
33 Malawi 50.10 2016
34 Congo 49.40 2016
35 Uganda 47.50 2016
36 Kenya 44.90 2016
37 Senegal 42.80 2016
38 Gabon 42.70 2016
39 Madagascar 42.10 2016
40 Namibia 41.00 2016
41 Eritrea 39.40 2016
42 South Africa 38.70 2016
43 Botswana 37.00 2016
44 Rwanda 34.80 2016
45 São Tomé and Principe 30.10 2016
46 Morocco 24.20 2016
47 Algeria 23.80 2016
48 Egypt 21.50 2016
49 Cabo Verde 19.20 2016
50 Seychelles 12.50 2016
51 Tunisia 12.30 2016
51 Mauritius 12.30 2016
53 Libya 11.50 2016

More rankings: Africa | Asia | Central America & the Caribbean | Europe | Middle East | North America | Oceania | South America | World |

Development Relevance: Mortality rates for different age groups (infants, children, and adults) and overall mortality indicators (life expectancy at birth or survival to a given age) are important indicators of health status in a country. Because data on the incidence and prevalence of diseases are frequently unavailable, mortality rates are often used to identify vulnerable populations. And they are among the indicators most frequently used to compare socioeconomic development across countries.

Limitations and Exceptions: Complete vital registration systems are fairly uncommon in developing countries. Thus estimates must be obtained from sample surveys or derived by applying indirect estimation techniques to registration, census, or survey data. Survey data are subject to recall error, and surveys estimating infant/child deaths require large samples because households in which a birth has occurred during a given year cannot ordinarily be preselected for sampling. Indirect estimates rely on model life tables that may be inappropriate for the population concerned. Extrapolations based on outdated surveys may not be reliable for monitoring changes in health status or for comparative analytical work.

Statistical Concept and Methodology: The main sources of mortality data are vital registration systems and direct or indirect estimates based on sample surveys or censuses. A "complete" vital registration system - covering at least 90 percent of vital events in the population - is the best source of age-specific mortality data. Estimates of neonatal, infant, and child mortality tend to vary by source and method for a given time and place. Years for available estimates also vary by country, making comparisons across countries and over time difficult. To make neonatal, infant, and child mortality estimates comparable and to ensure consistency across estimates by different agencies, the United Nations Inter-agency Group for Child Mortality Estimation (UN IGME), which comprises the United Nations Children's Fund (UNICEF), the World Health Organization (WHO), the World Bank, the United Nations Population Division, and other universities and research institutes, developed and adopted a statistical method that uses all available information to reconcile differences. The method uses statistical models to obtain a best estimate trend line by fitting a country-specific regression model of mortality rates against their reference dates.

Aggregation method: Weighted average

Periodicity: Annual

General Comments: Given that data on the incidence and prevalence of diseases are frequently unavailable, mortality rates are often used to identify vulnerable populations. Moreover, they are among the indicators most frequently used to compare socioeconomic development ac