South Sudan - Mortality rate, under-5 (per 1,000 live births)

The value for Mortality rate, under-5 (per 1,000 live births) in South Sudan was 97.90 as of 2020. As the graph below shows, over the past 60 years this indicator reached a maximum value of 352.40 in 1960 and a minimum value of 97.90 in 2014.

Definition: Under-five mortality rate is the probability per 1,000 that a newborn baby will die before reaching age five, if subject to 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:

Year Value
1960 352.40
1961 349.40
1962 346.70
1963 343.60
1964 340.40
1965 337.30
1966 334.20
1967 331.30
1968 328.20
1969 324.70
1970 321.70
1971 318.00
1972 314.80
1973 311.20
1974 308.30
1975 305.10
1976 301.60
1977 298.10
1978 295.00
1979 291.60
1980 288.30
1981 285.30
1982 282.30
1983 279.10
1984 275.90
1985 272.20
1986 268.00
1987 263.90
1988 259.60
1989 255.10
1990 250.50
1991 245.80
1992 240.20
1993 234.20
1994 227.80
1995 220.90
1996 213.90
1997 206.40
1998 198.20
1999 189.80
2000 181.20
2001 172.10
2002 163.40
2003 155.10
2004 147.30
2005 139.70
2006 132.70
2007 126.10
2008 119.90
2009 114.00
2010 108.40
2011 103.50
2012 100.00
2013 98.30
2014 97.90
2015 97.90
2016 97.90
2017 97.90
2018 97.90
2019 97.90
2020 97.90

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

Classification

Topic: Health Indicators

Sub-Topic: Mortality