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

The value for Mortality rate, under-5, male (per 1,000 live births) in Sudan was 61.30 as of 2020. As the graph below shows, over the past 60 years this indicator reached a maximum value of 195.20 in 1983 and a minimum value of 61.30 in 2020.

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:

Year Value
1960 184.10
1961 181.30
1962 178.50
1963 175.90
1964 173.60
1965 171.40
1966 169.30
1967 167.50
1968 166.10
1969 164.70
1970 163.70
1971 162.60
1972 161.80
1973 161.10
1974 160.10
1975 159.20
1976 158.30
1977 157.20
1978 156.10
1979 155.00
1980 153.90
1981 152.90
1982 151.90
1983 195.20
1984 192.90
1985 190.50
1986 147.10
1987 145.30
1988 143.50
1989 141.50
1990 139.30
1991 137.00
1992 134.70
1993 132.20
1994 129.80
1995 127.20
1996 124.50
1997 121.50
1998 118.20
1999 114.80
2000 111.30
2001 107.70
2002 104.10
2003 100.70
2004 97.40
2005 94.30
2006 91.40
2007 88.70
2008 86.10
2009 83.70
2010 81.40
2011 79.40
2012 77.30
2013 75.30
2014 73.30
2015 71.20
2016 69.10
2017 67.10
2018 65.10
2019 63.30
2020 61.30

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