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

The value for Mortality rate, infant, female (per 1,000 live births) in Afghanistan was 41.50 as of 2020. As the graph below shows, over the past 59 years this indicator reached a maximum value of 225.80 in 1961 and a minimum value of 41.50 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
1961 225.80
1962 221.80
1963 217.90
1964 214.20
1965 210.60
1966 207.00
1967 203.20
1968 199.60
1969 196.10
1970 192.40
1971 188.80
1972 185.10
1973 181.30
1974 177.70
1975 174.00
1976 170.30
1977 166.50
1978 162.60
1979 158.60
1980 154.60
1981 150.60
1982 146.50
1983 142.50
1984 138.50
1985 134.50
1986 130.60
1987 126.50
1988 122.60
1989 118.70
1990 114.90
1991 111.10
1992 107.70
1993 104.30
1994 101.10
1995 98.10
1996 95.10
1997 92.40
1998 89.90
1999 87.40
2000 85.00
2001 82.70
2002 80.40
2003 77.80
2004 75.30
2005 72.70
2006 70.10
2007 67.50
2008 65.00
2009 62.60
2010 60.30
2011 57.90
2012 55.70
2013 53.60
2014 51.60
2015 49.60
2016 47.70
2017 46.10
2018 44.50
2019 42.90
2020 41.50

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 Extrapolations based on outdated surveys may not be reliable for monitoring changes in health status or for comparative analytical work.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