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

The value for Mortality rate, infant, male (per 1,000 live births) in Syrian Arab Republic was 20.20 as of 2020. As the graph below shows, over the past 60 years this indicator reached a maximum value of 117.80 in 1960 and a minimum value of 17.80 in 2008.

Definition: Infant mortality rate, male is the number of male infants dying before reaching one year of age, per 1,000 male 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 117.80
1961 112.70
1962 108.30
1963 104.20
1964 100.20
1965 96.40
1966 92.70
1967 88.80
1968 84.90
1969 81.10
1970 77.30
1971 73.70
1972 70.40
1973 67.30
1974 64.30
1975 61.50
1976 58.90
1977 56.40
1978 53.90
1979 51.50
1980 49.00
1981 49.20
1982 51.00
1983 42.40
1984 40.60
1985 38.90
1986 37.30
1987 36.00
1988 34.80
1989 33.60
1990 32.50
1991 31.40
1992 30.30
1993 29.10
1994 27.90
1995 26.70
1996 25.50
1997 24.40
1998 23.40
1999 22.40
2000 21.60
2001 20.80
2002 20.10
2003 19.50
2004 19.00
2005 18.60
2006 18.20
2007 18.00
2008 17.80
2009 17.80
2010 17.80
2011 18.30
2012 25.10
2013 28.50
2014 29.30
2015 27.30
2016 26.70
2017 20.60
2018 20.60
2019 20.20
2020 20.20

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 Extrapolations based on outdated surveys may not be reliable for monitoring changes in health status or for comparative analytical work.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