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

The value for Mortality rate, infant, female (per 1,000 live births) in Sri Lanka was 5.30 as of 2020. As the graph below shows, over the past 60 years this indicator reached a maximum value of 62.30 in 1960 and a minimum value of 5.30 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 62.30
1961 60.00
1962 58.20
1963 56.60
1964 55.40
1965 54.30
1966 52.60
1967 50.80
1968 49.60
1969 48.60
1970 47.90
1971 47.50
1972 47.00
1973 46.50
1974 45.70
1975 44.50
1976 42.80
1977 40.70
1978 38.20
1979 35.70
1980 33.40
1981 31.40
1982 29.40
1983 27.50
1984 25.10
1985 22.90
1986 20.90
1987 19.30
1988 18.30
1989 19.20
1990 17.30
1991 17.00
1992 16.70
1993 16.30
1994 15.90
1995 15.40
1996 14.90
1997 14.40
1998 13.90
1999 13.40
2000 12.80
2001 12.40
2002 12.00
2003 11.70
2004 16.40
2005 11.00
2006 10.50
2007 9.90
2008 9.50
2009 12.80
2010 8.80
2011 8.40
2012 8.00
2013 7.50
2014 7.10
2015 6.60
2016 6.30
2017 6.00
2018 5.80
2019 5.50
2020 5.30

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 Extrapolations based on outdated surveys may not be reliable for monitoring changes in health status or for comparative analytical work.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