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

The value for Mortality rate, under-5, female (per 1,000 live births) in Sudan was 51.50 as of 2020. As the graph below shows, over the past 60 years this indicator reached a maximum value of 180.00 in 1983 and a minimum value of 51.50 in 2020.

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:

Year Value
1960 168.80
1961 166.10
1962 163.50
1963 161.10
1964 158.80
1965 156.60
1966 154.80
1967 153.10
1968 151.90
1969 150.70
1970 149.70
1971 148.80
1972 147.90
1973 147.00
1974 146.20
1975 145.10
1976 144.00
1977 142.80
1978 141.60
1979 140.40
1980 139.20
1981 138.10
1982 136.80
1983 180.00
1984 177.50
1985 175.00
1986 131.40
1987 129.70
1988 127.70
1989 125.60
1990 123.60
1991 121.50
1992 119.20
1993 116.80
1994 114.30
1995 111.80
1996 109.00
1997 106.10
1998 103.20
1999 100.20
2000 96.90
2001 93.60
2002 90.40
2003 87.20
2004 84.30
2005 81.50
2006 78.90
2007 76.40
2008 74.00
2009 71.80
2010 69.70
2011 67.70
2012 65.80
2013 64.10
2014 62.20
2015 60.30
2016 58.50
2017 56.60
2018 54.90
2019 53.10
2020 51.50

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