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

The value for Mortality rate, infant, female (per 1,000 live births) in Algeria was 18.10 as of 2020. As the graph below shows, over the past 60 years this indicator reached a maximum value of 142.60 in 1967 and a minimum value of 18.10 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 140.20
1961 140.30
1962 140.60
1963 141.10
1964 141.50
1965 142.10
1966 142.50
1967 142.60
1968 142.20
1969 141.20
1970 139.60
1971 137.40
1972 134.70
1973 131.40
1974 127.60
1975 123.50
1976 119.10
1977 114.50
1978 109.60
1979 104.30
1980 98.20
1981 91.10
1982 82.50
1983 72.60
1984 62.90
1985 54.50
1986 48.30
1987 43.90
1988 40.90
1989 38.90
1990 37.60
1991 36.60
1992 35.80
1993 35.00
1994 34.20
1995 33.30
1996 32.50
1997 31.80
1998 31.30
1999 31.20
2000 31.10
2001 30.50
2002 29.40
2003 28.90
2004 28.00
2005 26.90
2006 25.90
2007 24.80
2008 24.00
2009 22.80
2010 22.10
2011 21.50
2012 21.10
2013 20.80
2014 20.50
2015 20.20
2016 19.90
2017 19.40
2018 19.00
2019 18.60
2020 18.10

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 Extrapolations based on outdated surveys may not be reliable for monitoring changes in health status or for comparative analytical work.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