Burkina Faso - Mortality rate, infant, female (per 1,000 live births)

The value for Mortality rate, infant, female (per 1,000 live births) in Burkina Faso was 47.90 as of 2020. As the graph below shows, over the past 60 years this indicator reached a maximum value of 145.50 in 1960 and a minimum value of 47.90 in 2020.

Definition: Infant mortality rate, female is the number of female infants dying before reaching one year of age, per 1,000 female 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
1960 145.50
1961 144.10
1962 142.90
1963 141.60
1964 140.30
1965 139.10
1966 138.10
1967 137.20
1968 136.30
1969 135.40
1970 134.40
1971 133.40
1972 131.90
1973 129.70
1974 126.70
1975 123.00
1976 119.10
1977 115.20
1978 111.70
1979 108.70
1980 106.10
1981 104.00
1982 102.20
1983 100.50
1984 98.90
1985 97.10
1986 95.30
1987 93.60
1988 92.30
1989 91.40
1990 91.00
1991 90.80
1992 90.80
1993 90.70
1994 90.50
1995 89.90
1996 89.00
1997 87.90
1998 86.60
1999 85.30
2000 84.00
2001 82.40
2002 80.80
2003 78.80
2004 76.60
2005 74.20
2006 71.70
2007 69.20
2008 66.80
2009 64.50
2010 62.50
2011 60.60
2012 58.90
2013 57.30
2014 55.80
2015 54.40
2016 53.00
2017 51.60
2018 50.30
2019 49.10
2020 47.90

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 Extrapolations based on outdated surveys may not be reliable for monitoring changes in health status or for comparative analytical work.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