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

The value for Mortality rate, under-5, female (per 1,000 live births) in Liberia was 72.10 as of 2020. As the graph below shows, over the past 60 years this indicator reached a maximum value of 296.00 in 1961 and a minimum value of 72.10 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 295.90
1961 296.00
1962 295.50
1963 294.50
1964 292.60
1965 290.10
1966 287.00
1967 283.60
1968 279.50
1969 274.80
1970 270.00
1971 265.40
1972 261.10
1973 256.80
1974 252.50
1975 247.90
1976 243.80
1977 239.80
1978 236.20
1979 232.70
1980 229.30
1981 226.70
1982 224.50
1983 223.30
1984 223.40
1985 225.40
1986 229.10
1987 234.00
1988 239.70
1989 245.10
1990 249.50
1991 251.50
1992 250.80
1993 247.50
1994 241.50
1995 233.60
1996 224.30
1997 214.10
1998 203.00
1999 191.00
2000 178.70
2001 166.20
2002 153.60
2003 141.60
2004 130.70
2005 121.20
2006 113.00
2007 106.30
2008 100.80
2009 96.40
2010 92.80
2011 89.80
2012 87.40
2013 85.20
2014 85.50
2015 81.80
2016 79.70
2017 78.00
2018 76.20
2019 74.30
2020 72.10

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