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

The value for Mortality rate, infant, female (per 1,000 live births) in Liberia was 52.50 as of 2020. As the graph below shows, over the past 60 years this indicator reached a maximum value of 192.50 in 1961 and a minimum value of 52.50 in 2020.

Definition: Infant mortality rate, female is the number of female infants dying before reaching one year of age, per 1,000 female 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 192.40
1961 192.50
1962 192.10
1963 191.30
1964 190.00
1965 188.40
1966 186.20
1967 183.80
1968 181.10
1969 178.00
1970 174.80
1971 171.70
1972 169.00
1973 166.20
1974 163.30
1975 160.50
1976 157.90
1977 155.20
1978 152.80
1979 150.50
1980 148.40
1981 146.70
1982 145.40
1983 144.60
1984 144.70
1985 146.10
1986 148.60
1987 152.00
1988 155.90
1989 159.30
1990 162.20
1991 163.50
1992 163.10
1993 161.00
1994 157.10
1995 151.90
1996 145.90
1997 139.40
1998 132.60
1999 125.20
2000 117.60
2001 109.80
2002 102.40
2003 95.20
2004 88.50
2005 82.60
2006 77.60
2007 73.50
2008 70.10
2009 67.40
2010 65.20
2011 63.30
2012 61.90
2013 60.60
2014 59.80
2015 58.30
2016 57.10
2017 56.10
2018 54.90
2019 53.80
2020 52.50

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 Extrapolations based on outdated surveys may not be reliable for monitoring changes in health status or for comparative analytical work.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