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

The value for Mortality rate, under-5, female (per 1,000 live births) in Burundi was 49.60 as of 2020. As the graph below shows, over the past 56 years this indicator reached a maximum value of 308.80 in 1972 and a minimum value of 49.60 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
1964 232.50
1965 234.60
1966 236.90
1967 238.70
1968 240.30
1969 241.70
1970 242.70
1971 243.20
1972 308.80
1973 243.60
1974 243.60
1975 243.10
1976 241.70
1977 238.40
1978 232.90
1979 225.30
1980 216.30
1981 206.10
1982 195.20
1983 184.70
1984 175.40
1985 168.10
1986 163.30
1987 160.80
1988 160.20
1989 160.80
1990 161.90
1991 163.10
1992 163.90
1993 185.30
1994 164.40
1995 163.60
1996 161.80
1997 159.20
1998 155.50
1999 151.10
2000 146.20
2001 141.10
2002 135.70
2003 130.00
2004 123.80
2005 117.10
2006 110.10
2007 103.30
2008 96.60
2009 90.40
2010 84.60
2011 79.30
2012 74.30
2013 69.80
2014 65.70
2015 62.10
2016 59.10
2017 56.50
2018 53.90
2019 51.60
2020 49.60

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 Extrapolations based on outdated surveys may not be reliable for monitoring changes in health status or for comparative analytical work.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