Syrian Arab Republic - Mortality rate, infant, female (per 1,000 live births)

The value for Mortality rate, infant, female (per 1,000 live births) in Syrian Arab Republic was 16.50 as of 2020. As the graph below shows, over the past 60 years this indicator reached a maximum value of 113.40 in 1960 and a minimum value of 14.40 in 2009.

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 113.40
1961 108.30
1962 103.70
1963 99.40
1964 95.50
1965 91.50
1966 87.70
1967 83.80
1968 79.90
1969 76.10
1970 72.30
1971 68.70
1972 65.40
1973 62.30
1974 59.50
1975 56.70
1976 54.00
1977 51.30
1978 48.60
1979 46.10
1980 43.70
1981 43.90
1982 45.80
1983 37.30
1984 35.40
1985 33.70
1986 32.20
1987 30.80
1988 29.60
1989 28.50
1990 27.40
1991 26.40
1992 25.30
1993 24.30
1994 23.10
1995 22.00
1996 20.90
1997 19.90
1998 19.00
1999 18.20
2000 17.50
2001 16.80
2002 16.20
2003 15.80
2004 15.40
2005 15.00
2006 14.80
2007 14.60
2008 14.50
2009 14.40
2010 14.40
2011 15.00
2012 21.70
2013 25.00
2014 25.80
2015 23.80
2016 23.10
2017 16.90
2018 16.90
2019 16.50
2020 16.50

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 Extrapolations based on outdated surveys may not be reliable for monitoring changes in health status or for comparative analytical work.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