Eswatini - Mortality rate, infant, male (per 1,000 live births)

The value for Mortality rate, infant, male (per 1,000 live births) in Eswatini was 41.40 as of 2020. As the graph below shows, over the past 60 years this indicator reached a maximum value of 150.30 in 1960 and a minimum value of 41.40 in 2020.

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 150.30
1961 148.00
1962 145.70
1963 143.40
1964 140.80
1965 138.30
1966 135.60
1967 133.00
1968 130.30
1969 127.60
1970 124.70
1971 121.70
1972 118.30
1973 114.70
1974 110.90
1975 106.90
1976 103.10
1977 99.30
1978 95.60
1979 91.90
1980 88.30
1981 84.60
1982 80.80
1983 83.00
1984 73.20
1985 69.60
1986 66.20
1987 63.10
1988 60.40
1989 58.30
1990 56.90
1991 56.40
1992 57.10
1993 58.90
1994 61.20
1995 63.70
1996 66.00
1997 68.20
1998 70.40
1999 72.40
2000 74.40
2001 75.70
2002 76.10
2003 76.40
2004 75.50
2005 74.70
2006 64.40
2007 64.90
2008 66.80
2009 63.40
2010 60.00
2011 56.60
2012 55.60
2013 54.40
2014 54.90
2015 49.60
2016 46.90
2017 47.80
2018 43.50
2019 41.60
2020 41.40

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 Extrapolations based on outdated surveys may not be reliable for monitoring changes in health status or for comparative analytical work.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