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

The value for Mortality rate, under-5, female (per 1,000 live births) in Tuvalu was 19.60 as of 2020. As the graph below shows, over the past 60 years this indicator reached a maximum value of 163.70 in 1960 and a minimum value of 19.60 in 2020.

Definition: Under-five mortality rate, female is the probability per 1,000 that a newborn female baby will die before reaching age five, if subject to female 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 163.70
1961 156.00
1962 148.70
1963 141.90
1964 135.30
1965 128.90
1966 122.90
1967 117.10
1968 111.50
1969 106.20
1970 100.80
1971 95.50
1972 90.20
1973 85.00
1974 79.80
1975 75.00
1976 70.80
1977 67.10
1978 63.80
1979 60.90
1980 58.40
1981 56.30
1982 54.50
1983 53.00
1984 51.80
1985 50.80
1986 50.20
1987 49.70
1988 49.30
1989 48.80
1990 48.40
1991 47.80
1992 47.10
1993 46.40
1994 45.40
1995 44.30
1996 43.10
1997 41.80
1998 40.50
1999 39.20
2000 38.10
2001 37.20
2002 36.50
2003 35.70
2004 34.90
2005 34.00
2006 33.00
2007 31.70
2008 30.50
2009 29.30
2010 28.10
2011 27.00
2012 26.00
2013 25.00
2014 24.10
2015 23.20
2016 22.40
2017 21.70
2018 20.90
2019 20.30
2020 19.60

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