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

Definition: Under-five mortality rate, male is the probability per 1,000 that a newborn male baby will die before reaching age five, if subject to male 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 120.30 2020
2 Nigeria 120.10 2020
3 Chad 116.50 2020
4 Sierra Leone 114.60 2020
5 Central African Republic 109.00 2020
6 Guinea 101.40 2020
7 Lesotho 96.80 2020
8 Mali 96.30 2020
9 Benin 91.60 2020
10 Burkina Faso 89.60 2020
11 Dem. Rep. Congo 87.40 2020
12 Côte d'Ivoire 85.60 2020
13 Equatorial Guinea 84.30 2020
14 Liberia 84.10 2020
15 Guinea-Bissau 83.00 2020
16 Niger 81.20 2020
17 Cameroon 77.80 2020
18 Angola 77.20 2020
19 Mauritania 76.40 2020
20 Mozambique 75.00 2020
21 Togo 69.30 2020
22 Comoros 66.40 2020
23 Zambia 66.10 2020
24 Sudan 61.30 2020
25 Djibouti 60.80 2020
26 Burundi 58.90 2020
27 Zimbabwe 58.50 2020
28 Madagascar 54.70 2020
29 Ethiopia 54.20 2020
30 The Gambia 54.00 2020
31 Tanzania 52.40 2020
32 Eswatini 51.00 2020
33 Ghana 49.20 2020
34 Botswana 48.80 2020
35 Congo 48.60 2020
36 Uganda 47.80 2020
37 Gabon 45.90 2020
38 Kenya 45.60 2020
39 Eritrea 44.00 2020
40 Namibia 43.90 2020
40 Rwanda 43.90 2020
42 Malawi 42.70 2020
43 Senegal 41.80 2020
44 South Africa 34.80 2020
45 Algeria 24.00 2020
46 Egypt 20.70 2020
47 Morocco 20.50 2020
48 Mauritius 18.20 2020
49 Tunisia 18.00 2020
50 São Tomé and Principe 17.80 2020
51 Cabo Verde 15.50 2020
52 Seychelles 15.00 2020
53 Libya 12.20 2020

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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