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

The value for Mortality rate, under-5 (per 1,000 live births) in Tuvalu was 22.00 as of 2020. As the graph below shows, over the past 60 years this indicator reached a maximum value of 169.60 in 1960 and a minimum value of 22.00 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 169.60
1961 161.70
1962 154.30
1963 147.40
1964 140.70
1965 134.30
1966 128.10
1967 122.40
1968 116.80
1969 111.40
1970 106.00
1971 100.70
1972 95.40
1973 90.20
1974 84.90
1975 80.10
1976 75.80
1977 71.90
1978 68.60
1979 65.70
1980 63.10
1981 61.00
1982 59.10
1983 57.50
1984 56.20
1985 55.30
1986 54.60
1987 54.10
1988 53.70
1989 53.20
1990 52.80
1991 52.20
1992 51.50
1993 50.70
1994 49.70
1995 48.60
1996 47.30
1997 46.00
1998 44.60
1999 43.30
2000 42.10
2001 41.20
2002 40.30
2003 39.50
2004 38.70
2005 37.70
2006 36.60
2007 35.30
2008 34.00
2009 32.60
2010 31.30
2011 30.10
2012 29.00
2013 27.90
2014 26.90
2015 26.00
2016 25.10
2017 24.30
2018 23.50
2019 22.70
2020 22.00

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 Extrapolations based on outdated surveys may not be reliable for monitoring changes in health status or for comparative analytical work.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