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

The value for Mortality rate, under-5, female (per 1,000 live births) in Mali was 85.40 as of 2020. As the graph below shows, over the past 57 years this indicator reached a maximum value of 415.70 in 1963 and a minimum value of 85.40 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
1963 415.70
1964 408.30
1965 401.30
1966 394.40
1967 388.20
1968 381.80
1969 375.80
1970 369.70
1971 363.70
1972 357.30
1973 350.50
1974 343.30
1975 335.30
1976 327.00
1977 318.50
1978 310.10
1979 301.70
1980 293.40
1981 285.20
1982 276.90
1983 268.70
1984 260.70
1985 253.30
1986 246.30
1987 239.40
1988 232.80
1989 227.00
1990 221.70
1991 217.20
1992 213.20
1993 209.40
1994 206.10
1995 202.70
1996 199.10
1997 195.10
1998 190.60
1999 185.40
2000 179.50
2001 173.40
2002 167.10
2003 161.00
2004 155.10
2005 149.30
2006 143.80
2007 138.40
2008 133.40
2009 128.40
2010 123.70
2011 119.10
2012 114.60
2013 110.30
2014 106.30
2015 102.30
2016 98.60
2017 95.00
2018 91.70
2019 88.50
2020 85.40

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