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

The value for Mortality rate, infant, male (per 1,000 live births) in Burundi was 42.80 as of 2020. As the graph below shows, over the past 56 years this indicator reached a maximum value of 174.80 in 1972 and a minimum value of 42.80 in 2020.

Definition: Infant mortality rate, male is the number of male infants dying before reaching one year of age, per 1,000 male live births in a given 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 152.20
1965 153.60
1966 154.90
1967 156.10
1968 157.20
1969 158.30
1970 159.00
1971 159.40
1972 174.80
1973 160.00
1974 160.10
1975 159.80
1976 159.10
1977 157.20
1978 153.80
1979 149.20
1980 143.30
1981 137.00
1982 130.70
1983 124.50
1984 119.10
1985 115.10
1986 112.40
1987 111.00
1988 110.60
1989 111.00
1990 111.70
1991 112.50
1992 113.00
1993 118.00
1994 113.10
1995 112.50
1996 111.60
1997 110.00
1998 107.80
1999 105.50
2000 102.70
2001 99.80
2002 96.80
2003 93.50
2004 89.90
2005 85.90
2006 81.50
2007 77.20
2008 73.10
2009 69.10
2010 65.50
2011 62.00
2012 58.80
2013 55.80
2014 53.20
2015 50.90
2016 49.00
2017 47.20
2018 45.70
2019 44.20
2020 42.80

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 Extrapolations based on outdated surveys may not be reliable for monitoring changes in health status or for comparative analytical work.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