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

The value for Mortality rate, under-5, male (per 1,000 live births) in Burundi was 58.90 as of 2020. As the graph below shows, over the past 56 years this indicator reached a maximum value of 325.30 in 1972 and a minimum value of 58.90 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
1964 248.60
1965 250.80
1966 252.80
1967 254.80
1968 256.50
1969 258.10
1970 259.20
1971 259.80
1972 325.30
1973 260.20
1974 260.30
1975 259.90
1976 258.70
1977 255.40
1978 249.80
1979 242.50
1980 233.10
1981 222.40
1982 211.30
1983 200.40
1984 190.90
1985 183.80
1986 178.80
1987 176.20
1988 175.60
1989 176.50
1990 177.90
1991 179.30
1992 180.40
1993 201.80
1994 180.80
1995 179.90
1996 178.20
1997 175.50
1998 171.60
1999 167.20
2000 162.30
2001 157.10
2002 151.70
2003 145.90
2004 139.50
2005 132.40
2006 124.90
2007 117.40
2008 110.30
2009 103.40
2010 97.20
2011 91.40
2012 86.00
2013 80.90
2014 76.50
2015 72.80
2016 69.30
2017 66.30
2018 63.80
2019 61.40
2020 58.90

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 Extrapolations based on outdated surveys may not be reliable for monitoring changes in health status or for comparative analytical work.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