Mortality rate, neonatal (per 1,000 live births) - Country Ranking - Africa

Definition: Neonatal mortality rate is the number of neonates dying before reaching 28 days of age, per 1,000 live births in a given 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 Lesotho 44.30 2020
2 Central African Republic 38.80 2020
3 Somalia 36.80 2020
4 Nigeria 35.50 2020
5 Guinea-Bissau 35.10 2020
6 Côte d'Ivoire 33.20 2020
7 Chad 32.80 2020
8 Mali 31.60 2020
9 Sierra Leone 31.40 2020
10 Mauritania 31.20 2020
11 Liberia 30.60 2020
12 Djibouti 30.40 2020
13 Guinea 29.90 2020
14 Benin 29.70 2020
15 Comoros 29.00 2020
16 Equatorial Guinea 28.70 2020
17 Mozambique 28.30 2020
18 Angola 27.30 2020
19 Ethiopia 27.00 2020
20 Dem. Rep. Congo 26.80 2020
20 Sudan 26.80 2020
22 Cameroon 26.20 2020
23 Burkina Faso 25.80 2020
24 The Gambia 25.70 2020
24 Zimbabwe 25.70 2020
26 Togo 24.50 2020
27 Niger 24.10 2020
28 Zambia 24.00 2020
29 Ghana 22.90 2020
30 Botswana 21.90 2020
31 Burundi 20.90 2020
32 Senegal 20.60 2020
33 Kenya 20.50 2020
34 Madagascar 20.30 2020
34 Eswatini 20.30 2020
36 Tanzania 20.10 2020
36 Namibia 20.10 2020
38 Gabon 19.70 2020
39 Uganda 19.20 2020
40 Malawi 19.10 2020
41 Congo 18.70 2020
42 Rwanda 17.90 2020
43 Eritrea 17.70 2020
44 Algeria 16.30 2020
45 Tunisia 11.80 2020
46 Morocco 11.50 2020
47 South Africa 10.60 2020
48 Mauritius 10.50 2020
49 Egypt 10.30 2020
50 Cabo Verde 8.50 2020
51 Seychelles 8.40 2020
52 São Tomé and Principe 7.80 2020
53 Libya 6.00 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