Vanuatu - Mortality rate, under-5 (per 1,000 live births)

The value for Mortality rate, under-5 (per 1,000 live births) in Vanuatu was 24.90 as of 2020. As the graph below shows, over the past 60 years this indicator reached a maximum value of 152.10 in 1960 and a minimum value of 24.90 in 2020.

Definition: Under-five mortality rate is the probability per 1,000 that a newborn baby will die before reaching age five, if subject to age-specific mortality rates of the specified 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 152.10
1961 148.20
1962 144.20
1963 140.00
1964 135.50
1965 130.70
1966 126.00
1967 121.30
1968 116.50
1969 111.80
1970 107.30
1971 102.80
1972 98.70
1973 94.60
1974 90.90
1975 87.20
1976 83.50
1977 79.80
1978 75.90
1979 71.80
1980 67.60
1981 63.30
1982 59.10
1983 54.80
1984 50.80
1985 47.30
1986 44.10
1987 41.30
1988 38.90
1989 37.00
1990 35.30
1991 33.90
1992 32.70
1993 31.70
1994 30.80
1995 30.20
1996 29.70
1997 29.40
1998 29.10
1999 28.80
2000 28.50
2001 28.30
2002 28.10
2003 28.10
2004 28.10
2005 28.20
2006 28.40
2007 28.60
2008 28.80
2009 29.00
2010 29.10
2011 29.30
2012 29.30
2013 29.10
2014 28.80
2015 28.20
2016 27.60
2017 26.90
2018 26.30
2019 25.60
2020 24.90

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 Extrapolations based on outdated surveys may not be reliable for monitoring changes in health status or for comparative analytical work.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